BMJ Open · acute upper respiratory infections in rural primary care settings in China, through...
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A pragmatic cluster randomised controlled trial for reducing irrational antibiotic prescribing among children with upper
respiratory infections in rural China: a trial protocol
Journal: BMJ Open
Manuscript ID bmjopen-2015-010544
Article Type: Protocol
Date Submitted by the Author: 13-Nov-2015
Complete List of Authors: Zou, Guanyang; China Global Health Research and Development; Queen Margaret University, Institute for Global Health and Development Wei, X-L.; Dalla Lana School of Public Health; China Global Health
Research and Development Hicks, Joseph; University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute of Health Sciences Hu, Yanhong; The Chinese University of Hong Kong Walley, John; University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute of Health Sciences Zeng, Jun; Guangxi Autonomous Region Centre for Disease Control and Prevention Elsey, Helen; University of Leeds, Nuffield Centre for International Health and Development King, Rebecca; University of Leeds, Nuffield Institute For International Health and Development, Leeds Institute of Health Sciences
Yin, Jia; The Chinese University of Hong Kong Huang, Yuanyuan; China Global Health Research and Development Deng, Simin; China Global Health Research and Development, Zhang, Zhitong; China Global Health Research and Development Blacklock, Claire; University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute of Health Sciences Sun, Qiang; Shandong University Lin, Mei; Guangxi Autonomous Region Centre for Disease Control and Prevention
<b>Primary Subject Heading</b>:
Public health
Secondary Subject Heading: Health policy, Public health, Health services research, Paediatrics, Respiratory medicine
Keywords: Antibiotics, Rational use, Clustered randomized control trial, PRIMARY CARE, China
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A pragmatic cluster randomised controlled trial for reducing irrational
antibiotic prescribing among children with upper respiratory infections in rural
China: a trial protocol
Guanyang Zou1,2+
, Xiaolin Wei3,1,4+
, Joseph P Hicks5, Yanhong Hu
4, John Walley
5,
Jun Zeng6, Helen Elsey
5, Rebecca King
5, Jia Yin
4, Yuanyuan Huang
1, Simin Deng
1,
Zhitong Zhang1, Claire Blacklock
5, Qiang Sun
7, Mei Lin
6*
* Corresponding author: Mei Lin Email: [email protected]
+ Equal contributors
1China Global Health Research and Development, Shenzhen, China
2 Institute for Global Health and Development, Queen Margaret University,
Edinburgh, UK
3 Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
4School of Public Health and Primary Care, Chinese University of Hong Kong, Hong
Kong, China
5Nuffield Centre for International Health and Development, University of Leeds,
Leeds, UK
6 Guangxi Autonomous Region Centre for Disease Control and Prevention, Nanning,
China
7 Centre for Health Management and Policy, Shandong University, Jinan, China
Guanyang Zou and Xiaolin Wei contributed equally to this work.
Key words: antibiotics, rational use, upper respiratory infection, cluster randomized
controlled trial, primary care, China
Word count: 3994
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Abstract
Introduction
Irrational use of antibiotics is a serious issue within China and internationally. In 2012
the Chinese Ministry of Health issued a regulation for antibiotic prescriptions limiting
them to less than 20% of all prescriptions for outpatients, but no operational details
have been issued regarding policy implementation, especially at the primary care
level. This study aims to test the effectiveness of a multi-dimensional intervention
designed to reduce the use of antibiotics among children (aged 2-14 years old) with
acute upper respiratory infections in rural primary care settings in China, through
changing doctors’ prescribing behaviors and educating parents/caregivers.
Methods and analysis
This is a pragmatic, prospective, parallel-group, controlled, cluster-randomized
superiority trial, stratified by county, with blinded evaluation of outcomes and data
analysis, but un-blinded treatment. From two counties in Guangxi Province 12
township hospitals will be randomized to the intervention arm and 13 to the control
arm. In the control arm, the management of antibiotics prescriptions will continue
through usual care via clinical consultations. In the intervention arm, a provider and
client focused intervention will be embedded within routine primary care practice.
The provider intervention includes operational guidelines, systematic training, peer
review of antibiotic prescribing, and health education to patient caregivers. We will
also provide printed educational materials and educational videos to patient caregivers.
We aim to collect a minimum of 200 prescriptions per township hospital. The primary
outcome, collected over three months, is the proportion of all prescriptions for upper
respiratory infections in children aged 2-14 years old that include antibiotics.
Ethics and dissemination
The trial has received ethical approval from the Ethics Committee of Guangxi
Provincial Centre for Disease Control and Prevention, China. The results will be
disseminated through workshops, policy briefs, peer-reviewed publications, local and
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international conferences.
Trial registration: Current Controlled Trials: ISRCTN14340536
Strength and limitations
• We aim to test a comprehensive intervention targeting doctors and patients, an
approach shown to have the largest effect on reducing the irrational
prescribing on antibiotics in rural primary care settings.
• The study is adapted to the local context and fits into the current national
priority on antibiotics control.
• All the interventions are embedded within the routine primary care
management and practice, thus enhancing the replicability of the intervention.
• The effectiveness of the pragmatic trial will be limited by various contextual
factors, which will be explored by a qualitative process evaluation.
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INTRODUCTION
Irrational use of antibiotics is a serious issue within China and internationally.
Worldwide, around 50% of medicines are not appropriately prescribed, dispensed or
sold. 1-3 Irrational use of antibiotics not only brings high economic burdens to health
systems, but also increases the risk of antibiotic resistance.4 Acute upper respiratory
infections (URIs) are very common among children, but are usually viral and
self-limiting, with antibiotic treatment for URIs being unnecessary. For example, a
systematic review has shown that antibiotic use does not shorten the duration of
URIs.5 However, there is a high prevalence of antibiotics prescriptions for URIs in
primary care facilities.6 Antibiotic resistant bacteria are also frequently found in
children, especially infants, contributing to high childhood mortality in countries with
inadequate health infrastructure.7
China is one of the most notorious countries for antibiotic abuse. In 2012 the national
Ministry of Health reported that the average person consumed 138 grams of
antibiotics per year, ten times the rate in the Unites States.8 The situation is worse in
rural areas where health workers receive less education and continuous medical
training in practice.9 A recent study found frequent and inappropriate use of
antibiotics in primary health care settings in China with 78 % antibiotics prescribing
rate for colds and 93.5% for acute bronchitis.10 An earlier study in the primary care
settings of ten provinces in rural Western China showed that antibiotics accounted for
nearly half of all prescriptions, predominantly provided for URIs; while one fourth of
those receiving antibiotics were children under ten years old.11
Several national policies have been issued by the Ministry of Health, including the
most recent one limiting antibiotic prescriptions to less than 60% of all prescriptions
for inpatients and 20% for outpatients.12 However, no operational details were
provided on how to implement the policy, and no guidelines were provided on the
diagnosis and treatment of childhood URIs, or related clinician training especially for
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primary care doctors. In the 2009 health sector reform China launched the Essential
Medicines List policy, supported by the centralized procurement of essential
medicines and the Zero-Markup policy. However, after two years of implementation
there was no significant improvement in the rational use of medicines and cost
control.13
The majority of studies on reducing irrational antibiotic use have been conducted in
developed countries, which demonstrated that improving knowledge, attitudes and
behaviours of healthcare providers and consumers can effectively reduce irrational
antibiotic use.14 Commonly reported interventions for improving antibiotic use in URI
treatment included clinical decision support,15-18
point-of-care testing for C-reactive
protein,19-22
clinician communication skills training19-21
, education and feedbacks,23
discussion and monitoring workshops,24 governance structure change,
25 and
behavioral economics and social psychology.26 A Cochrane review demonstrated that
multi-faceted interventions targeting both physicians and patients significantly
reduced inappropriate antibiotic use in community settings;27 while single
interventions with parents have failed to impact on antibiotic prescribing.28-30
Studies of irrational antibiotic prescribing in the primary care are currently limited
settings in China and are mainly cross-sectional surveys.1110
The intervention studies
aimed at reducing the irrational prescribing of antibiotics at primary care were rarely
reported, although one study using public reporting method showed limited impact on
reducing antibiotics prescribing in primary care facilities.31 We aim to test the
effectiveness of multidimensional interventions aimed at changing doctor’s
prescribing behaviours and educating parents/caregivers to reduce the irrational use of
antibiotics among children with acute URIs in China’s rural primary care context.
METHODS AND ANALYSIS
Design of the study
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This is a prospective, parallel-group, cluster randomized controlled trial, designed as
a pragmatic evaluation of the superiority of a health behaviour change intervention
compared with routine practice (Figure 1). The study will be conducted in 25
township hospitals, with randomization of which stratified by county. Study
participants and doctors will not be blinded to the treatment, but measures will be
taken to ensure a blinded outcome evaluation by using the ‘PROBE’ design 32 and a
blinded analysis of the outcome data.
The study design broadly follows the Medical Research Council framework
Developing and evaluating complex interventions: new guidance.33 Prior to the
conduct of the trial we conducted a systematic review of interventions aimed at
reducing antibiotic use in children with URIs.34 We then developed our intervention
based on the results, which supported findings 27 that interventions targeting both
clinicians and patients had a greater effect on reducing irrational antibiotic use than
those targeting a single group. An internal pilot approach will be used to examine the
feasibility and acceptability of intervention and research procedures in a small number
of township hospitals. An independent trial steering committee has also been setup to
supervise the trial.
Setting
The trial will take place in two counties of Guangxi province, which is one of the
poorest provinces, and is located in the southwest mountainous terrain joining
Vietnam and Laos. Guangxi has a population of 48 million and contains 110 counties.
In the rural areas, primary care is provided by public township hospitals. Each
township hospital covers 20,000 to 100,000 people. Doctors in the township hospitals
are responsible for acute and preventive care. Although township hospitals have
inpatient treatment facilities, we only consider outpatients in this study because
inpatients are likely to have a range of co-morbidities, adding to the difficulty of
assessing the rationality of antibiotic prescriptions for URIs. Each township hospital
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has 5 to 20 doctors. Most patients visit township hospitals without prior booking or
referrals. We have not included village clinics, often equipped with an upgraded
community health worker, called a ‘village doctor’, who may be consulted. Rather,
our intervention focuses on professionally qualified clinicians who work as general
practitioners (‘doctors’) in township hospitals.
Eligibility
Eligibility criteria for clusters
All township hospitals from the two selected counties in Guangxi who agree to
participate in the study will be included. However, we will exclude the two township
hospitals located in the two county centres, as they have much better staff capacity
and equipment than their peers, and are close to the county general hospital. Both
counties have implemented the Essential Medicine List, its treatment guidelines and
the Zero-Markup Policy since 2012.
Eligibility criteria for participants
All outpatient prescriptions for children, aged between 2 and 14 years old, diagnosed
with URIs during the study period will be included for analysis. Children under 2
years old will be excluded because they are more vulnerable to secondary bacterial
infection, and exploratory work indicated that it was very difficult for doctor’s to
refuse antibiotics for younger children in this context. Prescriptions for children
diagnosed with pneumonia (where antibiotic prescription is appropriate) or severe
diseases such as cancer, tuberculosis, HIV/AIDS/immunodeficiency, chronic heart
diseases or others who need long term antibiotic treatment or as prophylaxis will be
excluded.
Intervention
No antibiotic should be used for common URIs as per national and international
guidelines. The multi-dimensional intervention aimed at changing doctor’s
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prescribing behaviours and educating parents/caregivers to reduce the irrational use of
antibiotics among children with acute URIs. It is designed to fit within the policy
requirements of antibiotics prescribing and routine supervision by the local health
authorities.
On the doctors’ side, the intervention include: 1) Operational guideline, which is
distributed to township hospital doctors. The guideline is based on Chinese antibiotics
use guidelines, Integrated Management of Childhood Illness (IMCI), and the National
Institute for Health and Care Excellence (NICE) guideline, focus on but not limit to
URIs. The guideline covers the work flow of URI management, methods of diagnosis
URI and other common diseases among children, communication skills between
doctors and patients. 2) Training workshops. All the doctors in the township doctors
are trained on rational use of antibiotics especially for childhood URI, using
participatory and interactive lectures, case discussion and questions and answers
sections. 3) Monthly peer review of rational use of antibiotics. Antibiotics
prescriptions are collected and reviewed by research team at the beginning of each
month. The research team calculates the APR and feed back to the township hospitals.
Peer review of antibiotics use are conducted based on the APR feedback in the
monthly hospital staff meeting. The project coordinator in the township hospitals
write a memo on the results of the peer review and send back to the research team. 4)
Health education to caregivers. Specific short messages are given to the caregivers
whose children have URIs during the clinical consultations. Examples of the short
messages are definition of antibiotic, rational antibiotic use for childhood URIs
On the caregivers’ side, the intervention includes: 1) Printed educational
material/leaflets (with simple words and pictures), which are distributed to the
caregivers whose children have URIs during the clinical consultation. They mainly
cover definition of antibiotic, impact of antibiotic resistance, rational use of
antibiotics for childhood URIs. 2) Educational videos, which are played on a loop in
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the waiting areas of township hospitals (5-8 minutes). The content mainly includes
definition of antibiotic, situation of irrational use antibiotics in China, impact of
antibiotics resistance (using local TV show).
Usual care
In the control arm doctors will be allowed to continue prescribing antibiotics
according to current national guidelines and existing practices. In these conventional
clinical consultations treatment is provided according to existing knowledge,
antibiotics are given at the individual clinician’s discretion, and no systematic health
education is provided to patients.
Outcomes
The primary outcome is the antibiotic prescription rate for childhood URIs, defined as
the proportion of prescriptions among all outpatient prescriptions for URIs that
include antibiotics (aged between 2 and 14 years old). This primary outcome is
selected because it should reflect the behavior change of both doctors and caregivers.
A reduction in the URIs will be a clinically beneficial outcome demonstrating
increased rational prescribing of antibiotics as most URIs are caused by viral infection
that do not require antibiotics. This measurement is reliable and feasible in the
primary care setting where prescriptions are well preserved either electronically or in
paper files.
The secondary outcomes are other commonly observed practices in routine primary
care. These include childhood URI prescription rate for multiple antibiotics,
broad-spectrum antibiotics and quinolones, defined as the proportion of prescriptions
among all outpatient prescriptions for URIs that include two or more antibiotics, a
broad-spectrum and quinolones respectively (aged between 2 and 14 years old).
Irrational prescribing causes great concern for the potential drug-resistance; while
misuse of quinolones may result in the increasing identification of extensively
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drug-resistant tuberculosis.35 Additionally, we will measure the mean cost of
childhood URI prescriptions, based on all prescriptions for URIs among outpatients
aged between 2 and 14 years old.
Sample size
We expect our intervention to lead to at least a 25% reduction in the antibiotic
prescription rate within township hospitals, based on a conservative estimate from our
systematic review.34 Based on our exploratory study the current average antibiotic
prescription rate is approximately 50%, which is therefore assumed for the usual care
arm. Consequently, our sample size calculation 36 is based on being able to detect a
25% or greater reduction in the antibiotic prescription rate in the intervention arm
compared to the usual care arm (i.e. an absolute reduction to 37.5% or less). Based on
exploratory work and an outcome data collection period of three-months, we assume a
cluster size of 200, using the harmonic mean to account for variation in cluster size,
and we assume a moderate between cluster coefficients of 0.15. Consequently, to
achieve 90% power using two-sided testing at the 5% significance level it is estimated
that 9 township hospitals per arm will be required. Allowing for stratified
randomization and a 10% loss of data due to lost and illegible prescriptions requires a
total of 24 township hospitals. As there are 25 eligible township hospitals within the
two counties it was decided to include all 25.
Randomization
In total, 25 township hospitals were eligible for the trial, with 14 in Rong county and
11 in Liujiang county. Randomization was stratified by county, and blocking was
used to ensure control over the allocation ratio within each county, with the block size
equal to the size of the stratum. Randomization was conducted by the study
statistician (JPH) using a computer program written in R (version 3.2.0), 36 37
and
township hospitals were randomized for the main trial and the internal pilot in the
same process. Initially, township hospitals within Rong county were randomized in a
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1:1 allocation ratio, whilst within Liujiang county township hospitals were
randomized in a 5:6 allocation ratio (treatment:control). Subsequently, within Rong
county six hospitals, three from each treatment arm, were randomly selected to
become the internal pilot clusters. The remaining 19 township hospitals (8 in Rong
county and 11 in Liujiang county) will therefore participate in the main trial along
with the six hospitals involved in the internal pilot. Overall the 25 hospitals were
allocated in a12:13 (treatment:control) allocation ratio.
Internal pilot process
The internal pilot study aims to assess recruitment rates and the extent to which the
intervention is delivered within township hospitals, as well as contributing outcome
data to the main trial. The six township hospitals in the pilot study will be recruited
and followed-up for three months, and the decision as to whether to continue with the
full trial will then be taken based on two key criteria: 1) sufficient levels of
recruitment (number of prescriptions sufficient to achieve minimum sample size
required); 2) feasibility of implementing the intervention (at least 50% of clinicians
trained and 50% using the guidelines at the end of the three months after the
intervention). If these criteria are met, the internal pilot hospitals and their outcome
data will then become part of the main trial, and will be followed-up for a further
three months. The remaining 19 hospitals will have been recruited, and if the trial is
proven to be feasible via the pilot they will be enrolled into the study and followed-up
for six months (meaning that data collection in the pilot and main trial hospitals will
finish at different times).
Data collection and management
To evaluate the primary and secondary outcomes, a minimum of two hundred
prescriptions for childhood URIs will be randomly selected in each township hospital
during the three months before (to provide baseline data) and the last three months
after the implementation of the intervention. Prescription data will be obtained from
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electronic records where available, or alternatively photographic copies will be taken
of patients’ paper prescriptions. Data collected from electronic or photographic
records will then be entered into a password-protected SPSS version 20.0 (IBM Corp.
Armonk, NY.) database. Information includes the township hospital, the date of the
prescription, the patient’s age, symptoms, diagnosis, related treatment, related
laboratory tests, treatment payment and insurance status. Personally identifying
information (e.g, names) will not be entered into the database, and each prescription
will be assigned a unique study identification number. Physical study data materials
will be stored securely in a locked cabinet, separate from the data of other studies. The
photographed prescriptions will be managed as audio files that will be deleted as soon
as possible following information extraction.
Data analysis
Analysis of outcomes
There are no interim analyses planned. Therefore, the outcomes will be analysed once
all data has been collected from all eligible prescriptions. The intention-to-treat (ITT)
population is defined as all patient-prescriptions issued for URIs in children (aged
2-14 years old) collected from each township hospital, regardless of the compliance of
township hospitals to the intervention. Statistical analyses of primary and secondary
outcomes will initially be by ITT, but per-protocol analyses will also be considered if
there are any protocol violators (i.e. if any township hospitals randomized to the
intervention arm do not implement the intervention). Inference will be based on
hypothesis testing with statistical significance assessed at the 5% level.
The crude-effect of the intervention on outcomes will be analysed using methods
appropriate for cRCTs where there are less than 20 clusters per arm.36 For the primary
outcome and those secondary outcomes involving proportions an overall risk ratio
will be estimated from a weighted average of the within-stratum risk ratios, with
weights inversely proportional to the stratum-specific variances. Stratum-specific risk
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ratios will be calculated from the unweighted stratum-specific means of
township-hospital-level outcomes. If the within-arm distribution of risk ratios is found
to be strongly skewed for an outcome, a logarithmic transformation will first be
applied. Formal hypothesis testing will be conducted using stratified t-tests, and 95%
confidence intervals will be adjusted for between-cluster variance and stratification.
The average cost of childhood URI prescriptions will be analysed using the same
methods, but with stratum-specific differences between the mean outcomes in each
arm used in place of stratum-specific risk ratios.
To adjust for important covariates, including individual and contextual factors, a
two-stage process will be carried out.36 For proportion outcomes a logistic regression
model will be fitted to the individual-level data including stratum and the covariates
of interest as fixed effects, but ignoring the treatment effect. Covariate-adjusted ratio
residuals will then be calculated from the ratios of cluster-specific observed and
expected values. The covariate-adjusted ratios will then be used in place of
cluster-specific proportions to conduct stratified t-tests and calculate 95% confidence
intervals using the above methods. To analyse the average cost of childhood URI
prescriptions using this two-stage method a normal regression model will be used; and
cluster-specific difference residuals, calculated from the differences between
cluster-specific observed and expected values, used in place of stratum-specific
differences in means.
Due to the likely causes of missing data described previously all missing data will be
assumed to be missing completely at random, and complete case analyses will be
conducted. All data will be analysed using STATA version 12.1 (SE) (STATA
Corporation, College Station, Texas).
Sub-group analyses
Planned sub-group analyses will be conducted on all outcomes to determine whether
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there is any significant heterogeneity in treatment effects occurring in township
hospitals of different size, and in patients of different ages and genders. For each
outcome the cluster-level residuals described above will be regressed on stratum,
treatment group, the subgroup variable and all their possible two-way interactions.
F-tests will be used to determine whether there are any significant interactions
between treatment group and subgroups.
Process evaluation
A qualitative process evaluation will be conducted at six months into the intervention
in selected clusters from the intervention and control arms (in the control arm to
understand the implementation process of existing guidelines by clinicians, i.e. usual
practice). The process evaluation aims to describe the health system and service
delivery context in which the intervention was delivered; explore whether or not the
intervention is delivered as intended, both at the cluster level (training) and the
individual level (provider delivery); and understand mechanisms of impact both at the
provider level and caregiver level. Methods will include document review (e.g.
meeting minutes), observation of training sessions and consultations, and qualitative
interviews.
In each county we will select one control cluster. After three months of
implementation we will review prescription rates in intervention clusters. If all
intervention clusters are performing in a similar way (i.e. very good, medium, poor),
then we will select one intervention cluster from each county. However, if
intervention clusters are performing very differently, then we will need to select two
intervention clusters from each county (high and low performers) to understand
cluster level factors. In each township hospital selected, we will interview doctors, the
hospital director and the pharmacist. We will conduct a focus group discussion with
caregivers. A sampling frame will be developed and participants will be purposively
selected for inclusion from the selected sites.
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Qualitative data will be recorded if the participants agree to use audio-recording. The
audio files will be transcribed as soon as possible, and any audio files recorded by
mobile recording devices will be immediately deleted once they have been
transcribed. Only the researchers conducting the study will know the names of
participants, and have access to the responses from individual participants.
Analysis of process evaluation
Qualitative data will be analysed as soon as possible after it has been collected. The
analysis should feed into subsequent interviews, and if interesting issues emerge they
can be followed up in subsequent interviews. Data will be audio recorded and
transcribed. Nvivo version 10 (QSR International Pty Ltd) will be used to manage the
data. The data will be analysed using a simple thematic approach.38
Discussion
Our study is one of the first addressing irrational antibiotic prescribing in the primary
care context of a developing country. The study is of great significance given
antibiotic-resistant infections have contributed to high mortality among children,
particularly in developing contexts.7 Our study will contribute to the currently limited
number of studies addressing irrational antibiotic prescribing in the primary care
context of rural of China. In China most studies have focused on either clinicians or
patients. We therefore aim to test a comprehensive intervention targeting both
clinicians and patients, an approach shown to have the largest effect 27 in rural
primary care settings.
The evidence-based and user-friendly guideline on rational antibiotic prescribing is
developed to address the current lack of operational guidelines for primary care
practices. However, simple dissemination of guidelines alone has had limited effects
on health worker performance39 40
, including in ambulatory care settings27.
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Considering the insufficient medical training received by rural primary care doctors
compared to their urban peers in China 9, we aim to improve their knowledge through
continued professional training in rational antibiotic prescribing. Peer review of
antibiotics prescribing is also planned at monthly hospital staff meetings to monitor
fidelity to the intervention, and enhance the knowledge of doctors. Antibiotics are
culturally accepted in rural China as the first response to URIs. Thus, educating the
caregivers through primary care doctors is challenging but essential.41 We have
designed an iterative and participatory training process, with an emphasis on
improving the communication and educational skills of primary care doctors
interacting with elders. Our study will be conducted in poor rural areas where many
young parents have migrated to cities, leaving grandparents to act as caregivers for
children. We have thus tailored the educational materials to be more easily understood
by people with less education. By improving caregivers’ knowledge, the intervention
is expected to reduce patient demand for antibiotic prescribing in URIs.
The study fits into the current national priority on antibiotics control in China.
However, major control efforts have currently focused on referral hospitals rather than
the primary care level, especially in rural areas. The study will thus help to shape the
policies and regulations regarding antibiotic use, especially in primary care.12 Multiple
interventions have proved effective on improving the rational use of antibiotics.
However, some interventions, such as point-of-care tests, are not feasible in primary
care settings in the poorer rural areas of China. In this trial, all the interventions are
embedded within the routine primary care management and practice. Thus, additional
work and costs that would otherwise have been added to primary care will be reduced,
enhancing the replicability of the intervention.
Through this trial we aim to understand the barriers and facilitators which are
embedded within the context, the implementation and mechanisms of impact, and
which affect the behaviour change outcome;42 and we aim to understand how to
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overcome implementation challenges and scale-up the intervention. For instance, the
uncertain effect of the zero-price mark-up policy on reducing medicine use may
suggest influences beyond providers and patients, such as those of pharmaceutical
companies. It is hoped that our intervention may be able to influence this and other
negative factors, and achieve desirable behavior change outcomes. Outputs will
include an operational guideline on the rational use of antibiotics for URIs among
children, and training modules and other materials that may be scaled-up in Guangxi
and other western provinces. These materials also have the potential to be adapted to
other low and middle income countries. We therefore believe this trial will greatly
contribute to improving the prescribing behavior of doctors in the rural primary care
context of Guangxi, China.
Ethics and dissemination
The trial has received ethical approval from the Ethics Committee of Guangxi
Provincial Centre for Disease Control and Prevention, China. The results will be
disseminated through policy briefs, workshops, peer-reviewed publications and local
and international conferences.
Contributors
All authors made substantive contributions to the trial development and provided final
approval for this manuscript. XW, GZ, JW, HE ,RK and YH designed the trial and
related studies. GZ and XW drafted the manuscript. ML, JZ, YH, YH, ZZ, SD, RK,
HE contributed to designing the trial and participated in the pilot study. JPH
contributed to the statistical issues in the study design and wrote the statistical
analysis plan. RK contributed to the design of the process evaluation and qualitative
methods. HE contributed to trial and process evaluation design and critically reviewed
the manuscript. CB, JW, JPH and QS contributed to ethics development and critically
reviewed the manuscript. JW, JPH and QS critically reviewed the manuscript.
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Funding
The trial is supported by the Department for International Development of the UK
Government (DFID) via the Communicable Disease - Health Service Delivery
(COMDIS-HSD) Research Programme Consortium.
Competing interests
The authors declare that they have no competing interests.
.
References:
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2. World Health Organisation, Geneva. Medicines use in primary care in developing and
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3. Sabaté E. Adherence to long-term therapies. Evidence for action. World Health
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4. WHO, Promoting rational use of medicines: core components. . Secondary WHO,
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suppurative complications from undifferentiated acute respiratory infections in
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6. Andrews T, Thompson M, Buckley DI, et al. Interventions to influence consulting and
antibiotic use for acute respiratory tract infections in children: a systematic review
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7. Ilic K, Jakovljevic E, Skodric-Trifunovic V. Social-economic factors and irrational antibiotic
use as reasons for antibiotic resistance of bacteria causing common childhood
infections in primary healthcare. Eur J Pediatr 2012;171(5):767-77.
8. Li Y. China’s misuse of antibiotics should be curbed, 2014.
9. Anand S, Fan VY, Zhang J, et al. China's human resources for health: quantity, quality, and
distribution. Lancet 2008;372(9651):1774-81.
10. Wang J, Wang P, Wang X, et al. Use and prescription of antibiotics in primary health care
settings in China. JAMA internal medicine 2014;174(12):1914-20.
11. Dong L, Yan H, Wang D. Antibiotic prescribing patterns in village health clinics across 10
provinces of Western China. J Antimicrob Chemother 2008;62(2):410-5.
12. Xiao Y, Li L. Legislation of clinical antibiotic use in China. The Lancet infectious diseases
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2013;13(3):189-91.
13. Mao W, Vu H, Xie Z, et al. Systematic Review on Irrational Use of Medicines in China and
Vietnam. PloS one 2015;10(3):e0117710.
14. Harbarth S, Albrich W, Brun-Buisson C. Outpatient antibiotic use and prevalence of
antibiotic-resistant pneumococci in France and Germany: a sociocultural
perspective. Emerg Infect Dis 2002;8(12):1460-7.
15. Mainous AG, 3rd, Lambourne CA, Nietert PJ. Impact of a clinical decision support system
on antibiotic prescribing for acute respiratory infections in primary care:
quasi-experimental trial. J Am Med Inform Assoc 2013;20(2):317-24.
16. Litvin CB, Ornstein SM, Wessell AM, et al. Use of an electronic health record clinical
decision support tool to improve antibiotic prescribing for acute respiratory
infections: the ABX-TRIP study. J Gen Intern Med 2013;28(6):810-6.
17. Gonzales R, Anderer T, McCulloch CE, et al. A cluster randomized trial of decision support
strategies for reducing antibiotic use in acute bronchitis. JAMA Intern Med
2013;173(4):267-73.
18. Litvin CB, Ornstein SM, Wessell AM, et al. Adoption of a clinical decision support system
to promote judicious use of antibiotics for acute respiratory infections in primary
care. Int J Med Inform 2012;81(8):521-6.
19. Little P, Stuart B, Francis N, et al. Effects of internet-based training on antibiotic
prescribing rates for acute respiratory-tract infections: a multinational, cluster,
randomised, factorial, controlled trial. Lancet 2013;382(9899):1175-82.
20. Cals JW, de Bock L, Beckers PJ, et al. Enhanced communication skills and C-reactive
protein point-of-care testing for respiratory tract infection: 3.5-year follow-up of a
cluster randomized trial. Ann Fam Med 2013;11(2):157-64.
21. Altiner A, Berner R, Diener A, et al. Converting habits of antibiotic prescribing for
respiratory tract infections in German primary care--the cluster-randomized
controlled CHANGE-2 trial. BMC Fam Pract 2012;13:124.
22. Price EL, Mackenzie TD, Metlay JP, et al. A computerized education module improves
patient knowledge and attitudes about appropriate antibiotic use for acute
respiratory tract infections. Patient Educ Couns 2011;85(3):493-8.
23. Pettersson E, Vernby A, Molstad S, et al. Can a multifaceted educational intervention
targeting both nurses and physicians change the prescribing of antibiotics to nursing
home residents? A cluster randomized controlled trial. J Antimicrob Chemother
2011;66(11):2659-66.
24. Ruvinsky S, Monaco A, Perez G, et al. Effectiveness of a program to improve antibiotic
use in children hospitalized in a children's tertiary care facility in Argentina. Arch
Argent Pediatr 2014;112(2):124-31.
25. Liang X, Xia T, Zhang X, et al. Governance structure reform and antibiotics prescription in
community health centres in Shenzhen, China. Fam Pract 2014;31(3):311-8.
26. Persell SD, Friedberg MW, Meeker D, et al. Use of behavioral economics and social
psychology to improve treatment of acute respiratory infections (BEARI): rationale
and design of a cluster randomized controlled trial [1RC4AG039115-01]--study
protocol and baseline practice and provider characteristics. BMC Infect Dis
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2013;13:290.
27. Arnold Sandra R, Straus Sharon E. Interventions to improve antibiotic prescribing
practices in ambulatory care. Cochrane Database of Systematic Reviews 2005; (4).
http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD003539.pub2/abstract
http://onlinelibrary.wiley.com/store/10.1002/14651858.CD003539.pub2/asset/CD003539.p
df?v=1&t=ifphjtif&s=aaa533bb3d45fdf3ed3d83bfa608884a95301f66.
28. Huang SS, Rifas-Shiman SL, Kleinman K, et al. Parental knowledge about antibiotic use:
results of a cluster-randomized, multicommunity intervention. Pediatrics
2007;119(4):698-706.
29. Taylor JA, Kwan-Gett TS, McMahon EM, Jr. Effectiveness of a parental educational
intervention in reducing antibiotic use in children: a randomized controlled trial.
Pediatr Infect Dis J 2005;24(6):489-93.
30. Wheeler JG, Fair M, Simpson PM, et al. Impact of a waiting room videotape message on
parent attitudes toward pediatric antibiotic use. Pediatrics 2001;108(3):591-6.
31. Yang L, Liu C, Wang L, et al. Public reporting improves antibiotic prescribing for upper
respiratory tract infections in primary care: a matched-pair cluster-randomized trial
in China. Health Res Policy Syst 2014;12:61.
32. Hansson L, Hedner T, Dahlf B. Prospective Randomized Open Blinded End-point (PROBE)
Study: A novel design for intervention trials. Blood Pressure 1992;1(2):113-9.
33. Medical Research Council. Medical Research Council (MRC) framework Developing and
evaluating complex interventions: new guidance.
http://wwwmrcacuk/documents/pdf/complex-interventions-guidance/.
34. Hu Y, Walley J, Zou G, et al. Report on a meta-analysis on educational intervention to
reduce inappropriate antibiotic prescription among children with upper respiratory
infections COMDIS Health Service Delivery Research Consortium, China Programme
2015.
35. Chan ED, Strand MJ, Iseman MD. Multidrug-resistant tuberculosis (TB) resistant to
fluoroquinolones and streptomycin but susceptible to second-line injection therapy
has a better prognosis than extensively drug-resistant TB. Clinical Infectious Diseases
2009;48(5):e50-e52.
36. Hayes RJ ML. Cluster Randomised Trials: CRC Press, 2009.
37. Team. RDC. R: A Language and Environment for Statistical Computing. . Available online
at http://www.R-project.org/: Vienna, Austria : the R Foundation for Statistical
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38. Patton M. Qualitative research and evaluation methods: integrating theory and practice.
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39. Giguere A, Legare F, Grimshaw J, et al. Printed educational materials: effects on
professional practice and healthcare outcomes. Cochrane Database Syst Rev
2012;10:Cd004398.
40. Rowe AK, de Savigny D, Lanata CF, et al. How can we achieve and maintain high-quality
performance of health workers in low-resource settings? The
Lancet;366(9490):1026-35.
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41. Yu M, Zhao G, Stalsby Lundborg C, et al. Knowledge, attitudes, and practices of parents in
rural China on the use of antibiotics in children: a cross-sectional study. BMC
infectious diseases 2014;14(1):112.
42. Moore GF, Audrey S, Barker M, et al. Process evaluation of complex interventions:
Medical Research Council guidance. BMJ 2015;350.
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a. Eligible subjects include all outpatient prescriptions for children, aged between 2 and 14 years old, diagnosed with URIs
b. Intervention package includes: operational guidelines, training, peer review, consultation(providers); education leaflets, video(patients);
c. Usual care refers to health care following routine works at the discretion of individual doctors.
Figure 1 Trial flow chart
Process
evaluation
Outcome
evaluation
Total clusters in two counties (n=27)
Eligible clusters for randomization (n=25)
Exclude 2
ineligible
clusters
Intervention arm (n=12) Control arm (n=13)
Internal pilot
� Intervention(n=3), 3 months
� Baseline data collection in
pilot clusters
Internal pilot
� Usual care(n=3), 3 months
� Baseline data collection in
pilot clusters
Main trial
� Intervention:
3 pilot clusters, 3 months;
9 remaining clusters, 6
months
� Baseline data collection in
remaining clusters
Main trial
� Usual care:
3 pilot clusters, 3 months;
10 remaining clusters, 6
months
� Baseline data collection in
remaining clusters
Outcome data collection Outcome data collection
Analyse prescriptions
(Intention-to-treat)
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Reducing irrational antibiotic prescribing among children with upper respiratory
infections: statistical analysis plan of a clustered randomized controlled trial in rural
China
Version 1.0
1. Introduction
1.1. Background
Irrational use of antibiotics is a serious international issue that is particularly acute in low-
and middle-income countries, and it is estimated that globally over half of all medicines are
inappropriately prescribed or sold, whilst over half all patients fail to take their medicine
appropriately.[1-3] Irrational use of antibiotics not only brings high economic burdens to
health systems, but also increases the risk of antibiotic resistance.[2] Acute upper respiratory
infections (URIs) are very common among children, but are usually viral and self-limiting,
with antibiotic treatment being unnecessary.[4] However, irrational use of antibiotics for
URIs in children is very prevalent in primary care settings internationally.[5]
A cross-sectional study in ten provinces in rural Western China showed that antibiotics
accounted for over half of all prescriptions, predominantly provided for URIs, and with
approximately one quarter of those receiving antibiotics being children under ten years
old.[6] Irrational antibiotic use amongst children is known to contribute to higher childhood
mortality in countries with inadequate health infrastructure.[7] Several national policies have
been issued by the Ministry of Health, including the most recent one limiting antibiotic
prescriptions to less than 60% of all prescriptions for inpatients and 20% for outpatients.[8]
However, no operational details were provided on how to implement the policy, and no
guidelines were provided for the diagnosis and treatment of URIs in children, or related
clinician training. Potentially because of this situation, despite attempts at health sector
reform there has been no significant improvement in the rational use of antibiotics or cost
control in China.[9]
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Commonly reported interventions for improving antibiotic use in URI treatment included
clinical decision support,[10-13] point-of-care testing for C-reactive protein,[14-17] clinician
communication skills training,[14-16] education and feedback,[18] public reporting of
antibiotic prescribing rates,[19] discussion and monitoring workshops,[20] governance
structure change,[21] and interventions based on behavioural economics and social
psychology.[22] However, a Cochrane review demonstrated that while multi-faceted
interventions targeting both physicians and patients significantly reduced inappropriate
antibiotic use in community settings,[23] single interventions with parents failed to impact on
antibiotic prescribing.[24-26]
Therefore, we developed a multidimensional intervention targeting doctors and patient
caregivers which aimed to reduce the irrational use of antibiotics for URIs in children within
China’s rural primary care context (specifically within township hospitals). The intervention
was developed through exploratory work, and its feasibility, acceptance and the adequate
adherence of doctors to the intervention has been confirmed via an internal pilot.
1.2. Aims and objectives
This study aims to evaluate the clinical effectiveness of the intervention in realistic primary
care settings in rural China, to guide decisions on the implementation of programmes to
reducing irrational antibiotic use across China. Therefore, the study’s objective is to
determine whether the intervention reduces the amount of antibiotics prescribed for URIs in
child outpatients within township hospitals, compared to existing practice.
1.3. Study design and randomisation process
The trial has been designed as a pragmatic, parallel-group, multi-centre, cluster randomised,
controlled trial. The trial will evaluate the superiority of the intervention within township
hospitals, which are the unit of randomisation. The trial will be undertaken within two
counties, across which a total of 25 township hospitals (14 in Rong county and 11 in Liujiang
county) will be recruited and allocated between treatment arms (including 6 hospitals used in
the internal pilot). Randomization was conducted by the study statistician (JPH) using a
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computer program written in R (version 3.2.0). To control the allocation ratio block
randomisation was conducted, stratified by county, with the block size equal to the size of the
stratum. For the main trial hospitals within Rong county were randomised in a 1:1 allocation
ratio, and hospitals within Liujiang county were randomised in a 5:6 (treatment:control)
allocation ratio to reduce financial and logistical costs. Within Rong county 6 hospitals were
then randomly selected from the allocation list, three from each arm, to become the internal
pilot clusters. Therefore, 19 hospitals remained for the main trial (8 in Rong county and 11 in
Liujiang county), with an overall 12:13 (treatment:control) allocation ratio for all 25
hospitals.
Outcome data will be collected from at least 5000 prescriptions (approximately 200 per
hospital) issued for URIs in outpatients aged between 2 and 14 years old during the last three
months following the implementation of the intervention in treatment-arm hospitals, and
during the equivalent period in control-arm hospitals. Baseline outcome data will also be
gathered from at least 5000 child-outpatient URI prescriptions issued during the three months
prior to the implementation of the intervention in each arm.
Within intervention hospitals all family doctors will receive training to increase their
knowledge on the rational use of antibiotics, and to improve the effectiveness of their
communication skills when interacting with caregivers of children with URIs, facilitating the
education of caregivers on the rational use of antibiotics. Monthly peer review meetings will
also assess doctors’ antibiotic prescribing practices, and reinforce desired behaviours. Printed
and video-based educational materials will also be provided for caregivers in intervention
hospital waiting rooms to improve understanding about the rational use of antibiotics. In
control hospitals none of the intervention components will be implemented, and the only
apparent impact will be via the collection of prescription data.
Blinding is clearly not possible for doctors or caregivers, but there will be blinded evaluation
of all outcomes. Similarly, a cluster design was chosen due to the difficulty of preventing
contamination of both doctors and caregivers, and the need for hospital-wide participation of
doctors in the peer review meetings, which are felt to be a key component of the intervention.
1.4. Sample size (if applicable) and expected accrual
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The intervention is expected to lead to at least a 25% reduction in the antibiotic prescription
rate (the primary outcome) within township hospitals, based on a conservative estimate from
similar interventions.[27] This change would be clinically highly significant. Based on
exploratory work the current average antibiotic prescription rate is estimated to be
approximately 50%, which is assumed for the usual care arm. The resulting sample size
calculation [28] is based on being able to detect a 25% or greater reduction in the antibiotic
prescription rate in the intervention arm compared to the usual care arm (i.e. an absolute
reduction from 50% to 37.5% or less). Based on exploratory work we assume a mean of 200
eligible prescriptions will be collected per township hospital over the three-month outcome
collection period, and a moderate between-cluster coefficient of variation of 0.15.
Consequently, to achieve 90% power using two-sided testing at the 5% significance level it is
estimated that 9 township hospitals per arm will be required. Allowing for stratified
randomization and a 10% loss of data due to expected hospital-losses and illegible
prescriptions 24 township hospitals are required. As there are 25 eligible township hospitals
in total it was decided to include all 25 on ethical grounds.
1.5. Planned analyses
No interim analyses are planned. All outcomes will be analysed after the data collection
period ends.
2. Outcomes
All outcome data will be collected from prescriptions (both paper and, where available,
electronic records) over a three month period prior to the implementation of the intervention
(baseline outcome data), and over the last three month period following the implementation
of the intervention (with data collection in control hospitals occurring over the same period).
2.1. Primary outcome
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The antibiotic prescription rate for childhood URIs. Defined at the township-hospital level as
the proportion of prescriptions for URIs among outpatients aged between 2 and 14 years old
that include at least one antibiotic. The antibiotic prescription rate is the primary outcome
because it should reflect the behaviour change of both doctors and caregivers. Most URIs are
caused by viral infection that are self-limiting and do not require antibiotics, and a reduction
in this rate will be a clinically beneficial outcome demonstrating increased rational
prescribing of antibiotics for childhood URIs. This measurement is also reliable and feasible
in the primary care setting because prescriptions are well preserved either electronically or in
paper files.
2.2. Secondary outcome
• The childhood URI multiple antibiotic prescription rate: the proportion of
prescriptions for URIs among outpatients aged between 2 and 14 years old that
include two or more antibiotics;
• The childhood URI broad-spectrum antibiotic prescription rate: the proportion of
prescriptions for URIs among outpatients aged between 2 and 14 years old that
include a broad-spectrum antibiotic;
• The childhood URI quinolones prescription rate: the proportion of prescriptions for
URIs among outpatients aged between 2 and 14 years old that include a quinolone
antibiotic;
• Additionally, to understand the medical costs associated with antibiotics prescribing
we will measure the mean cost (Yuan) of childhood URI prescriptions, based on all
prescriptions for URIs among outpatients aged between 2 and 14 years old.
Secondary outcomes were chosen to assess the extent to which the intervention will reduce
other commonly observed practices in routine primary care relating to antibiotic prescribing
practices for URIs that are particularly likely to increase drug-resistance, and the
intervention’s cost effectiveness.
2.3. Missing data
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Due to the assumed plausible reasons for missing data (lost paper and electronic prescriptions
records, and unreadable paper prescription records) all missing data will be assumed to be
missing completely at random, and only complete case analyses will be conducted.
3. Populations
3.1. Township hospital eligibility criteria
All township hospitals from the two selected counties in Guangxi who agree to participate in
the study will be included. However, we will exclude the two township hospitals located in
the two county centres. Compared to all other township hospitals they have much higher staff
capacity and equipment levels, and their proximity to the county general hospital is likely to
result in patient populations with substantially different characteristics.
3.2. Patient prescription eligibility criteria
All outpatient prescriptions for children aged between 2 and 14 years old who are diagnosed
with URIs during the study period will be included for analysis. Children under 2 years old
will be excluded because they are more vulnerable to secondary bacterial infection, and
exploratory work indicated that it was very difficult for doctor’s to refuse antibiotics for
younger children in China’s context. Prescriptions for children diagnosed with pneumonia
(where antibiotic prescription is appropriate) or other severe diseases requiring long-term
antibiotic treatment (or as prophylaxis) will also be excluded. Prescriptions for inpatients will
not be collected.
3.3. Populations
The intention-to-treat (ITT) population is defined as all outpatient-prescriptions issued for
URIs in children aged 2-14 years old collected from township hospitals, regardless of the
compliance of township hospitals to the intervention. Statistical analyses of primary and
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secondary outcomes will initially be by ITT, but per-protocol analyses will also be considered
if there are any protocol violators (i.e. if any township hospitals randomized to the
intervention arm do not implement the intervention).
4. Data handling
4.1. Data monitoring
All personally identifying details will be removed from the study database. Data will be
checked weekly for quality and completeness by the study data manager (ZZ), and any
missing data will be followed-up with township hospitals until received (if electronically
available), confirmed as set aside for later collection by researchers (if paper-based) or
confirmed as not available. Recruitment rates will be monitored on a monthly basis. There is
no Data Monitoring and Ethics Committee or equivalent associated with the study.
4.2. Data validation
Prior to analysis the final database will be validated using a STATA program to identify any
anomalous, inconsistent and missing data. This program will check/identify:
• Eligibility criteria of prescriptions
• Consistency of prescription issue dates relative to the baseline and outcome data
collection periods
• Outlying and anomalous (e.g. incorrect format, impossible value) data
• Missing data
All anomalous, inconsistent or unexpectedly missing data will be checked against original
paper or photographic prescription records where feasible. Any anomalous or inconsistent
data that can be unambiguously corrected will be, but where any ambiguity cannot be
resolved values will be recorded as missing data.
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5. Data analysis
5.1. General calculations
Percentage calculations will exclude any missing prescriptions from the denominators.
Summary statistics such as percentages and means will be rounded to 1 decimal place, or 1
significant figure for numbers less than 1, but standard deviations will be rounded to 2
decimal places, or 2 significant figures for numbers less than 1. Parameter estimates,
including standard errors SEs and 95% confidence intervals (CIs), will be rounded to 2
decimal places, or 2 significant figures for numbers less than 1. All hypothesis testing will be
2-sided and at the 5% significance level. All analyses will be carried out using STATA
Version 12.1 (SE) software, but other packages will be employed if necessary. The primary
and the secondary outcome analyses will be based on the intention-to-treat (ITT) population.
All analyses will be conducted by the study statistician (JPH).
5.2. Analysis
5.2.1. Baseline characteristics
The baseline characteristics of the ITT population will be summarised using frequencies and
means (with SDs) as appropriate for each treatment group.
5.2.2. Primary and secondary outcome analyses
The crude and covariate adjusted effect of the intervention on outcomes will be analysed
using methods appropriate for cRCTs where there are less than 20 clusters per arm.[28] For
the primary outcome and those secondary outcomes involving proportions an overall risk
ratio will be estimated from a weighted average of the within-stratum risk ratios, with
weights inversely proportional to the stratum-specific variances. Stratum-specific risk ratios
will be calculated from the unweighted stratum-specific means of township-hospital-level
outcomes. If the within-arm distribution of risk ratios is found to be strongly skewed for an
outcome, a logarithmic transformation will first be applied to the outcome proportions.
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Formal hypothesis testing will be conducted using stratified t-tests, and 95% confidence
intervals will be adjusted for between-cluster variance and stratification. The average cost of
childhood URI prescriptions will be analysed using the same methods, but with stratum-
specific differences between the mean outcomes in each arm used in place of stratum-specific
risk ratios.
To adjust for important covariates, including individual and township-hospital level factors, a
two-stage process will also be followed. For proportion outcomes a logistic regression model
will be fitted to the individual-level data including stratum and the covariates of interest as
fixed effects, but ignoring the treatment effect. Covariate-adjusted ratio residuals will then be
calculated from the ratios of cluster-specific observed and expected values. The covariate-
adjusted ratios will then be used in place of cluster-specific proportions to conduct stratified
t-tests and calculate 95% confidence intervals using the above methods. To analyse the
average cost of childhood URI prescriptions using this two-stage method a normal regression
model will be used, and cluster-specific difference residuals, calculated from the differences
between cluster-specific observed and expected values, used in place of stratum-specific
differences in means. As per CONSORT both unadjusted and adjusted results will be
presented.
For all outcomes, within each treatment arm and strata estimates of the between-cluster
coefficient of variation and the intraclass correlation coefficient will also be calculated and
made available to facilitate future trial planning and systematic reviews.
5.2.3. Subgroup analyses
Planned sub-group analyses will be conducted for all outcomes to determine whether there is
any significant heterogeneity in treatment effects due to variation in the size of township
hospitals, patient age or patient gender. In a normal regression model for each outcome the
unadjusted and adjusted cluster-level residuals described above will be regressed on county,
treatment group, a subgroup dummy variable and all their possible two-way interactions. Any
significant interactions (based on t-tests) between treatment group and subgroups will be
taken as evidence for differences in treatment effects between subgroups.
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6. References
1. WHO Policy Perspectives on Medicines, No. 5 Geneva, World Health Organisation.
Promoting rational use of medicines: Core components. 2002
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1990 and 2006. 2009
3. Sabaté E. Adherence to long-term therapies. Evidence for action. World Health
Organisation 2003
4. Alves Galvão Márcia G, Rocha Crispino Santos Marilene A, Alves da Cunha Antonio JL.
Antibiotics for preventing suppurative complications from undifferentiated acute
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5. Andrews T, Thompson M, Buckley DI, et al. Interventions to influence consulting and
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7. Ilic K, Jakovljevic E, Skodric-Trifunovic V. Social-economic factors and irrational
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9. Mao W, Vu H, Xie Z, et al. Systematic Review on Irrational Use of Medicines in China
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and Vietnam. PloS one 2015;10(3):e0117710
10. Gonzales R, Anderer T, McCulloch CE, et al. A cluster randomized trial of decision
support strategies for reducing antibiotic use in acute bronchitis. JAMA Intern Med
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11. Litvin CB, Ornstein SM, Wessell AM, et al. Adoption of a clinical decision support
system to promote judicious use of antibiotics for acute respiratory infections in
primary care. Int J Med Inform 2012;81(8):521-6 doi:
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12. Litvin CB, Ornstein SM, Wessell AM, et al. Use of an electronic health record clinical
decision support tool to improve antibiotic prescribing for acute respiratory infections:
the ABX-TRIP study. J Gen Intern Med 2013;28(6):810-6 doi: 10.1007/s11606-012-
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13. Mainous AG, 3rd, Lambourne CA, Nietert PJ. Impact of a clinical decision support
system on antibiotic prescribing for acute respiratory infections in primary care:
quasi-experimental trial. J Am Med Inform Assoc 2013;20(2):317-24 doi:
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14. Altiner A, Berner R, Diener A, et al. Converting habits of antibiotic prescribing for
respiratory tract infections in German primary care--the cluster-randomized controlled
CHANGE-2 trial. BMC Fam Pract 2012;13:124 doi: 10.1186/1471-2296-13-
124[published Online First: Epub Date]|.
15. Cals JW, de Bock L, Beckers PJ, et al. Enhanced communication skills and C-reactive
protein point-of-care testing for respiratory tract infection: 3.5-year follow-up of a
cluster randomized trial. Ann Fam Med 2013;11(2):157-64 doi:
10.1370/afm.1477[published Online First: Epub Date]|.
16. Little P, Stuart B, Francis N, et al. Effects of internet-based training on antibiotic
prescribing rates for acute respiratory-tract infections: a multinational, cluster,
randomised, factorial, controlled trial. Lancet 2013;382(9899):1175-82 doi:
10.1016/s0140-6736(13)60994-0[published Online First: Epub Date]|.
17. Price EL, Mackenzie TD, Metlay JP, et al. A computerized education module improves
patient knowledge and attitudes about appropriate antibiotic use for acute respiratory
tract infections. Patient Educ Couns 2011;85(3):493-8 doi:
10.1016/j.pec.2011.02.005[published Online First: Epub Date]|.
18. Pettersson E, Vernby A, Molstad S, et al. Can a multifaceted educational intervention
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targeting both nurses and physicians change the prescribing of antibiotics to nursing
home residents? A cluster randomized controlled trial. J Antimicrob Chemother
2011;66(11):2659-66 doi: 10.1093/jac/dkr312[published Online First: Epub Date]|.
19. Yang L, Liu C, Wang L, et al. Public reporting improves antibiotic prescribing for upper
respiratory tract infections in primary care: a matched-pair cluster-randomized trial in
China. Health Res Policy Syst 2014;12:61 doi: 10.1186/1478-4505-12-61[published
Online First: Epub Date]|.
20. Ruvinsky S, Monaco A, Perez G, et al. Effectiveness of a program to improve antibiotic
use in children hospitalized in a children's tertiary care facility in Argentina. Arch
Argent Pediatr 2014;112(2):124-31 doi: 10.1590/s0325-
00752014000200004[published Online First: Epub Date]|.
21. Liang X, Xia T, Zhang X, et al. Governance structure reform and antibiotics prescription
in community health centres in Shenzhen, China. Fam Pract 2014;31(3):311-8 doi:
10.1093/fampra/cmu001[published Online First: Epub Date]|.
22. Persell SD, Friedberg MW, Meeker D, et al. Use of behavioral economics and social
psychology to improve treatment of acute respiratory infections (BEARI): rationale
and design of a cluster randomized controlled trial [1RC4AG039115-01]--study
protocol and baseline practice and provider characteristics. BMC Infect Dis
2013;13:290 doi: 10.1186/1471-2334-13-290[published Online First: Epub Date]|.
23. Arnold Sandra R, Straus Sharon E. Interventions to improve antibiotic prescribing
practices in ambulatory care. Cochrane Database of Systematic Reviews 2005; (4).
http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD003539.pub2/abstract
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?v=1&t=ifphjtif&s=aaa533bb3d45fdf3ed3d83bfa608884a95301f66.
24. Huang SS, Rifas-Shiman SL, Kleinman K, et al. Parental knowledge about antibiotic use:
results of a cluster-randomized, multicommunity intervention. Pediatrics
2007;119(4):698-706 doi: 10.1542/peds.2006-2600[published Online First: Epub
Date]|.
25. Taylor JA, Kwan-Gett TS, McMahon EM, Jr. Effectiveness of a parental educational
intervention in reducing antibiotic use in children: a randomized controlled trial.
Pediatr Infect Dis J 2005;24(6):489-93
26. Wheeler JG, Fair M, Simpson PM, et al. Impact of a waiting room videotape message on
parent attitudes toward pediatric antibiotic use. Pediatrics 2001;108(3):591-6
27. Hu Y, Walley J, Zou G, et al. Report on a meta-analysis on educational intervention to
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reduce inappropriate antibiotic prescription among children with upper respiratory
infections COMDIS Health Service Delivery Research Consortium, China
Programme 2015.
28. Hayes RJ ML. Cluster Randomised Trials: CRC Press, 2009.
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A protocol for a pragmatic cluster randomized controlled trial for reducing irrational antibiotic prescribing among
children with upper respiratory infections in rural China
Journal: BMJ Open
Manuscript ID bmjopen-2015-010544.R1
Article Type: Protocol
Date Submitted by the Author: 08-Apr-2016
Complete List of Authors: Zou, Guanyang; China Global Health Research and Development Wei, xiaolin; University of Toronto, DL School of Public Health; China Global Health Research and Development
Hicks, Joseph; University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute of Health Sciences Hu, Yanhong; The Chinese University of Hong Kong Walley, John; University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute of Health Sciences Zeng, Jun; Guangxi Autonomous Region Centre for Disease Control and Prevention Elsey, Helen; University of Leeds, Nuffield Centre for International Health and Development King, Rebecca; University of Leeds, Nuffield Institute For International Health and Development, Leeds Institute of Health Sciences Zhang, Zhitong; China Global Health Research and Development
Deng, Simin; China Global Health Research and Development, Huang, Yuanyuan; China Global Health Research and Development Blacklock, Claire; University of Leeds, Nuffield Centre for International Health and Development, Leeds Institute of Health Sciences Yin, Jia; The Chinese University of Hong Kong Sun, Qiang; Shandong University Lin, Mei; Guangxi Autonomous Region Centre for Disease Control and Prevention
<b>Primary Subject Heading</b>:
Public health
Secondary Subject Heading: Health policy, Public health, Health services research, Paediatrics,
Respiratory medicine
Keywords: Antibiotics, Rational use, Clustered randomized control trial, PRIMARY CARE, China
Note: The following files were submitted by the author for peer review, but cannot be converted to PDF. You must view these files (e.g. movies) online.
Figure_1_Trial_flow_chart.tif
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1
A protocol for a pragmatic cluster randomized controlled trial for reducing
irrational antibiotic prescribing among children with upper respiratory
infections in rural China
Guanyang Zou1+, Xiaolin Wei
2,1+*, Joseph P Hicks
3, Yanhong Hu
4, John Walley
3, Jun
Zeng5, Helen Elsey
3, Rebecca King
3, Zhitong Zhang
1, Simin Deng
1, Yuanyuan
Huang1, Claire Blacklock
3, Jia Yin
4, Qiang Sun
6, Mei Lin
5*
* Corresponding authors: Mei Lin Email: [email protected]
Xiaolin Wei: [email protected]
+ Equal contributors
1 China Global Health Research and Development, Shenzhen, China
2 Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
3 Nuffield Centre for International Health and Development, University of Leeds,
Leeds, UK
4 School of Public Health and Primary Care, Chinese University of Hong Kong, Hong
Kong, China
5 Guangxi Autonomous Region Centre for Disease Control and Prevention, Nanning,
China
6 Centre for Health Management and Policy, Shandong University, Jinan, China
Guanyang Zou and Xiaolin Wei contributed equally to this work.
Key words: antibiotics, rational use, upper respiratory infection, cluster randomized
controlled trial, primary care, China
Word count: 4878
Document version number and date: 02 (30th March 2016).
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2
Abstract
Introduction
Irrational use of antibiotics is a serious issue within China and internationally. In 2012
the Chinese Ministry of Health issued a regulation for antibiotic prescriptions limiting
them to less than 20% of all prescriptions for outpatients, but no operational details
have been issued regarding policy implementation. This study aims to test the
effectiveness of a multi-dimensional intervention designed to reduce the use of
antibiotics among children (aged 2-14 years old) with acute upper respiratory
infections in rural primary care settings in China, through changing doctors’
prescribing behaviors and educating parents/caregivers.
Methods and analysis
This is a pragmatic, parallel-group, controlled, cluster-randomized superiority trial,
with blinded evaluation of outcomes and data analysis, but un-blinded treatment.
From two counties in Guangxi Province 12 township hospitals will be randomized to
the intervention arm and 13 to the control arm. In the control arm, the management of
antibiotics prescriptions will continue through usual care via clinical consultations. In
the intervention arm, a provider and patient/caregiver focused intervention will be
embedded within routine primary care practice. The provider intervention includes
operational guidelines, systematic training, peer review of antibiotic prescribing, and
provision of health education to patient caregivers. We will also provide printed
educational materials and educational videos to patients’ caregivers. The primary
outcome is the proportion of all prescriptions issued by providers for upper respiratory
infections in children, aged 2-14 years old, which include at least one antibiotic.
Ethics and dissemination
The trial has received ethical approval from the Ethics Committee of Guangxi
Provincial Centre for Disease Control and Prevention, China. The results will be
disseminated through workshops, policy briefs, peer-reviewed publications, local and
international conferences.
Trial registration: Current Controlled Trials: ISRCTN14340536
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Strength and limitations
• We aim to test a comprehensive intervention targeting doctors and patients/
caregivers, an approach shown to have the largest effect on reducing the
irrational prescribing of antibiotics in rural primary care settings.
• The study is adapted to the local context and fits into the current Chinese
national priority on antibiotics control.
• All the interventions are embedded within routine primary care management
and practice, thus enhancing the potential scale-up of the intervention.
• The effectiveness of the pragmatic trial may be limited by various contextual
factors, which will be explored by a qualitative process evaluation.
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INTRODUCTION
Irrational use of antibiotics is a serious issue within China and internationally.
Worldwide, around 50% of medicines are not appropriately prescribed, dispensed or
sold. 1-3 Irrational use of antibiotics not only brings high economic burdens to health
systems, but also increases the risk of antibiotic resistance.4 Acute upper respiratory
infections (URIs) are very common among children, however most are usually viral
and self-limiting, with antibiotic treatment for URIs being unnecessary. For example,
a systematic review has shown that antibiotic use does not shorten the duration of
URIs.5 Despite this, there is a high prevalence of antibiotics prescriptions for URIs in
primary care facilities.6 Antibiotic resistant bacteria are also frequently found in
children, especially infants, particularly in countries with less stringent prescribing
regulations in healthcare and agriculture.7
China is notorious for antibiotic misuse in healthcare. In 2012 the national Ministry of
Health reported that the average person consumed 138 grams of antibiotics per year,
ten times the rate in the Unites States.8 The situation is worst in rural areas where
health workers receive less education and continuous medical training in practice.9
Knowledge and awareness about antibiotic misuse and resistance is also poorer in
rural communities compared to amongst urban residents.10 Another recent study
found frequent and inappropriate use of antibiotics in primary health care settings in
China, that a 78% antibiotics were prescribed for colds and 93.5% for acute
bronchitis.11 An earlier study in the primary care settings of ten provinces in rural
Western China showed that antibiotics accounted for nearly half of all prescriptions,
predominantly provided for URIs, while one fourth of those receiving antibiotics were
children under ten years old.12
Several national policies have been issued by the Ministry of Health, including the
most recent limiting antibiotic prescriptions to less than 60% of all prescriptions for
inpatients and 20% for outpatients.13 However, no operational details were provided
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on how to implement the policy, and no guidelines were provided on the diagnosis
and treatment of childhood URIs, or related clinician training especially for primary
care doctors. In the 2009 health sector reform China launched the Essential Medicines
List policy, supported by the centralized procurement of essential medicines and the
Zero-Markup policy. However, after two years of implementation there was no
significant improvement in the rational use of medicines and cost control.14
The majority of studies on reducing irrational antibiotic use have been conducted in
developed countries, which have demonstrated that improving knowledge, attitudes
and behaviors of healthcare providers and consumers can effectively reduce irrational
antibiotic use.15 Commonly reported interventions for improving antibiotic use in URI
treatment included clinical decision support,16-20
point-of-care testing for C-reactive
protein,21-24
clinician communication skills training21-23
, education and feedbacks,25
discussion and monitoring workshops,26 governance structure change,
27 and
behavioral economics and social psychology.28 A Cochrane review demonstrated that
multi-faceted interventions targeting both physicians and patients significantly
reduced inappropriate antibiotic use in community settings;29 whereas single
interventions with parents failed to impact on antibiotic prescribing.30-32
Studies of irrational antibiotic prescribing in primary care settings in China are
currently limited, and mainly cross-sectional surveys.11 12
Studies involving
interventions aimed at reducing the irrational prescribing of antibiotics in primary are
rare, except one study showing limited impact of a public reporting intervention on
reducing antibiotics prescribing in primary care facilities.33 Therefore, we aim to test
the effectiveness of a multidimensional intervention targeting doctors’ prescribing
behaviors and the education of parents/caregivers, which we hypothesize will reduce
the irrational use of antibiotics among children with acute URIs in China’s rural
primary care context.
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METHODS AND ANALYSIS
Design of the study
This is a parallel-group, cluster randomized controlled trial, designed as a pragmatic
evaluation of the superiority of a health behaviour change intervention compared with
routine practice (Figure 1 Trial Flow Chart). The study will be conducted in 25
township hospitals, with randomization stratified by county. Randomization is at the
level of township hospitals because it would not be practically or logistically feasible
to randomize individual doctors or patients/caregivers in this multidimensional
intervention that involves both provider and patient/caregivers components. Study
participants and doctors will not be blinded to the treatment, but measures will be
taken to ensure a blinded outcome evaluation by using the ‘PROBE’ design.34
The study design broadly follows the Medical Research Council framework
Developing and evaluating complex interventions: new guidance.35 Prior to the
conduct of the trial we conducted a systematic review of interventions aimed at
reducing antibiotic use in children with URIs.36 We then developed our intervention
based on the results, which supported findings29 that interventions targeting both
clinicians and patients had a greater effect on reducing irrational antibiotic use than
those targeting a single group. An internal pilot approach will be used to examine the
feasibility and acceptability of intervention and research procedures in six township
hospitals. An independent trial steering committee, where lead investigators will be
steering committee members, has also been setup to supervise the trial, review
progress, and if necessary decide on any changes to the protocol. A data monitoring
committee will not be set up given the lack of any interim analyses and very low risk
to participants, but the statistician will provide any data advice to the trial steering
committee as necessary.
Setting
The trial will take place in two counties of Guangxi province, which is one of the
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poorest provinces in China, and is located in the southwest mountainous terrain
joining Vietnam and Laos. Guangxi has a population of 48 million and contains 110
counties. In the rural areas, primary care is provided by public township hospitals, and
this trial will be conducted in 25 such hospitals. Each township hospital covers 20,000
to 100,000 people, and doctors in the township hospitals are responsible for acute and
preventive care. Although township hospitals have inpatient treatment facilities, we
only consider outpatients in this study because inpatients are likely to have a range of
co-morbidities, leading to difficulty in assessing rational prescribing for URIs. Each
township hospital has 5 to 20 doctors. No booking system is operated in rural
township hospitals. We have not included village clinics, often equipped with an
upgraded community health worker, called a ‘village doctor’, because both public and
private clinics co-exist which may confound the interventions. Rather, our
intervention focuses on professionally qualified public clinicians who work as general
practitioners (‘doctors’) in township hospitals.
Eligibility
Eligibility criteria for clusters
All doctors working in township hospitals from the two selected counties in Guangxi
who agreed to participate in the study are included. We excluded the two township
hospitals located in the two county centers, as they have much better staff capacity
and equipment than their peers, and are close to the county general hospital. Both
counties have implemented the Essential Medicine List, its treatment guidelines and
the Zero-Markup Policy since 2012.
Eligibility criteria for participants
All outpatient prescriptions for children aged between 2 and 14 years old and
diagnosed with URIs during the baseline and intervention data collection period
(Figure 1) will be included for analysis. Children under 2 years old will be excluded
because they are more vulnerable to secondary bacterial infection, and exploratory
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work indicated that it was very difficult for doctor’s to refuse antibiotics for younger
children in this context. Prescriptions for children diagnosed with pneumonia (where
antibiotic prescription is appropriate) or severe diseases such as cancer, tuberculosis,
HIV/AIDS/immunodeficiency, chronic heart diseases or others who need long-term
antibiotic treatment or as prophylaxis will be excluded.
Intervention
No antibiotic should be used for self-limiting viral URIs, as per national and
international guidelines. The multi-dimensional intervention is aimed at changing
doctors’ prescribing behaviors and educating parents/caregivers to reduce the
irrational use of antibiotics among children with acute URIs. It is designed to fit
within the policy requirements of antibiotics prescribing and routine supervision by
the local health authorities.
The intervention design is informed by the Theoretical Domains Framework (TDF),
an emerging method developed from a wide range of theories relevant to behavior
change. The TDF, which consists of 14 theoretical domains (groups of constructs
from theories of behavior change) has been widely used for exploring influencing
factors and designing interventions37-39
in implementation research. Based on our
exploratory study and systematic review, several theoretical domains from the TDF
were identified as important in antibiotic prescribing, to which relevant behaviour
change techniques, and content of interventions were targeted (Table 1). 40
On the doctors’ side the intervention includes: 1) Operational guidelines. These will
be distributed to township hospital doctors. The guidelines are based on Chinese
antibiotics use guidelines, Integrated Management of Childhood Illness (IMCI)
guidelines, and the National Institute for Health and Care Excellence UK (NICE)
guidelines, which focus on but are not limited to URIs. The operational guidelines
cover the workflow of URI management, methods of diagnosis of URIs and other
common diseases among children, and communication skills between doctors and
patients; 2) Training workshops. All the doctors in the township hospitals are trained
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on the rational use of antibiotics, especially for childhood URIs, using participatory
and interactive lectures, case discussion and question and answer sessions. These two
components address the theoretical domains of knowledge, skills, and beliefs about
capabilities of rational prescribing, using the technique of information provision; 3)
Monthly peer review of rational use of antibiotics. Antibiotics prescriptions are
collected and reviewed by research team at the beginning of each month. The research
team calculates the antibiotic prescription rate (APR) for childhood URIs and feeds it
back to the township hospitals. Peer review of antibiotics use are then conducted
based on the APR feedback in the monthly hospital staff meeting. The project
coordinator in the township hospitals will communicate the results of the peer review
back to the research team. This component addresses the theoretical domain of
behavior regulation among doctors, using the techniques of monitoring and feedback;
and 4) Health education to caregivers. Concise messages are given by doctors to the
caregivers whose children have URIs during the clinical consultations, along with
simple printed educational materials. Examples of the messages are explanations
about antibiotics and rational use of antibiotics for childhood URIs. This component
addresses the theoretical domains of beliefs about consequences (specifically of not
being given antibiotics), knowledge and social influence of antibiotics use among
caregivers/parents, and uses techniques of information giving and persuasive
communication.
On the caregivers’ side, the intervention includes: 1) Health education messages from
doctor and printed educational materials/leaflets (with simple words and pictures),
which are distributed to the caregivers whose children have URIs during the clinical
consultation. They mainly cover explanations about antibiotics, the impacts of
antibiotic resistance, and rational use of antibiotics for childhood URIs; and 2)
Educational videos, which are played on a loop in the waiting areas of township
hospitals (5-8 minutes). The content mainly includes explanations about antibiotics,
the situation of irrational use of antibiotics in China, and the impacts of antibiotic
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resistance (using a local TV show). This component also addresses the theoretical
domains of beliefs about consequences (specifically of not giving antibiotics),
knowledge and social influence of antibiotics use among caregivers/parents, and uses
the technique of information giving.
Usual care
In the control arm doctors will be allowed to continue prescribing antibiotics
according to current national guidelines and existing practices. In these conventional
clinical consultations treatment is provided according to existing knowledge,
antibiotics are given at the individual clinician’s discretion, and no systematic health
education is provided to patients. This is therefore a pragmatic comparator reflecting
typical routine practice, which allows the intervention to be usefully compared to the
existing situation.
Outcomes
The primary outcome is the APR for childhood URIs, and will be measured for each
township hospital based on all prescriptions for URIs in outpatients aged between 2
and 14 years old issued between the start of the intervention’s implementation and
six-month follow-up. Based on these prescriptions the APR is defined as the
proportion of outpatients aged between 2 and 14 years old who have been diagnosed
with a URI and, from that consultation, prescribed at least one antibiotic as a result of
their diagnosis. This primary outcome is selected because it should reflect the
integrated effect of the behavior change of both doctors and patients/caregivers. A
reduction in the APR will be a clinically beneficial outcome demonstrating increased
rational prescribing of antibiotics, as most self-limiting URIs are caused by viral
infection that do not require antibiotics. This measurement is reliable and feasible in
the primary care setting where prescriptions are well preserved either electronically or
in paper files.
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The secondary outcomes are all based on data extracted from the same prescriptions
as described for the primary outcome:
1. The multiple antibiotic prescription rate: the proportion of prescriptions for
childhood URIs that include two or more antibiotics.
2. The broad-spectrum antibiotic prescription rate: the proportion of
prescriptions for childhood URIs that include at least one broad-spectrum
antibiotic.
3. The quinolones prescription rate: the proportion of prescriptions for
childhood URIs that include at least one quinolone.
4. The mean cost of childhood URI prescriptions.
These secondary outcomes relate to other commonly observed practices in routine
primary care that cause great concern for their potential to promote drug-resistance,
while misuse of quinolones may also contribute to the increasing identification of
extensively drug-resistant tuberculosis.41
Sample size
Based on our exploratory study the current APR is approximately 50%, which is
therefore assumed for the usual care arm. We expect our intervention to lead to at
least a 25% relative reduction in the antibiotic prescription rate within township
hospitals, based on a conservative estimate from our systematic review.36
Consequently, to detect a 25% or greater reduction in the APR (i.e. an absolute
reduction to 37.5% APR or less) with 90% power, using two-sided testing at the 5%
significant level, assuming a harmonic mean cluster size of 200 and a between cluster
coefficient of variation of 0.15 (based on exploratory and pilot work), we estimate
that we require 9 township hospitals per arm.42 Allowing for stratified randomization
and a 10% loss of data, due to lost and illegible prescriptions, requires a total of 24
township hospitals. As there are 25 eligible township hospitals within the two
counties it was decided to include all 25.
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Randomization
A total of 25 township hospitals were eligible for the trial, with 14 in Rong County
and 11 in Liujiang County. Randomization was stratified by county to avoid any
imbalances in allocation between counties, given potentially important variation in
outcomes between counties. Within each county randomization was further restricted
to two subsets of all possible allocation ratios. In Rong County randomization was
restricted to those allocations resulting in equal numbers of township hospitals in
each arm, whilst in Liujiang County randomization was restricted to those allocations
resulting in township hospital treatment: control arm allocation ratio of 5:6. This was
chosen to ensure as equal an allocation ratio as possible, whilst minimizing the
logistical cost from treatment arm hospitals. After all 25 hospitals were randomized,
within Rong County 6 hospitals, 3 from each arm, were further randomly selected to
become the internal pilot clusters. The remaining 19 township hospitals (8 in Rong
County and 11 in Liujiang County) will therefore participate in the main trial, along
with the 6 hospitals involved in the internal pilot. Therefore, overall the 25 hospitals
were allocated in a 12:13 treatment: control allocation ratio. Randomization was
conducted by the study statistician (JPH) using a computer program written in R
(version 3.2.0).42 43
Internal pilot process
The internal pilot study aims to assess recruitment rates and the extent to which the
intervention is delivered within township hospitals, as well as contributing outcome
data to the main trial. The six township hospitals in the pilot study will be recruited
and followed-up for three months, and the decision as to whether to continue with the
full trial will then be taken based on two key criteria: 1) sufficient levels of
recruitment (number of prescriptions sufficient to achieve minimum sample size
required); 2) feasibility of implementing the intervention (at least 50% of clinicians
trained and 50% using the guidelines at the end of the three months after the
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intervention). If these criteria are met, the internal pilot hospitals and their outcome
data will then become part of the main trial, and will be followed-up for a further
three months. The remaining 19 hospitals will have been recruited, and if the trial is
proven to be feasible via the pilot they will be enrolled into the study and followed-up
for six months (meaning that data collection in the pilot and main trial hospitals will
finish at different times).
Data collection and management
To evaluate the primary and secondary outcomes two hundred prescriptions for
childhood URIs will be randomly selected in each township hospital during the three
months before the implementation of the intervention to provide baseline data, and
during the 4th to the 6
th months after randomization. Prescription data will be obtained
from electronic records where available, or alternatively photographic copies will be
taken of patients’ paper prescriptions. Data collected from electronic or photographic
records will then be entered into a password-protected SPSS database (version 20.0,
IBM Corp. Armonk, NY.). Information collected will include the township hospital,
the date of the prescription, the patient’s age, symptoms, diagnosis, prescribed
medicines, related treatment, related laboratory tests, treatment payment and
insurance status.
Data analysis
Analysis of outcomes
The statistical analyses are described in full detail in the accompanying statistical
analysis plan (SUPP INFO 1), and are therefore only outlined in brief here. No
interim analyses are planned, and all outcomes will be analysed following data
collection. All analyses will be on the intention-to-treat (ITT) population, defined as
all outpatient-prescriptions issued in township hospitals for URIs in children aged
2-14 years old, regardless of the compliance of township hospitals, doctors and
parents/caregivers to the intervention. Descriptive statistics will be calculated and
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presented, and formal inference will be based on hypothesis testing with statistical
significance assessed at the 5% level.
The crude-effect of the intervention on outcomes will be analysed using methods
appropriate for cRCTs where there are small numbers of clusters per arm.42 For the
primary and secondary outcomes involving proportions, data at the township hospital
level will be used to calculate weighted risk ratios and their 95% confidence intervals
(accounting for between-hospital variance and stratification), and formal hypothesis
testing with stratified t-tests will be conducted. If the data are strongly skewed a
logarithmic transformation will first be applied. The same methods will be used to
analyse the data on the average cost of childhood URI prescriptions, but based on the
weighted mean difference in the outcome between treatment arms.
To adjust for important covariates, including individual and contextual factors, a
two-stage process will be carried out.42 This will involve fitting either logistic or
normal regression models (for the proportion or average cost of prescription outcomes
respectively) to individual-level outcome data with all covariates of interest (including
stratum) included apart from the treatment effect. Township-hospital specific
covariate-adjusted ratio or difference residuals will then be calculated for proportion
or average cost of prescription outcomes respectively. Using the methods described
above the hospital-specific residuals will then be used in place of raw hospital-level
outcome data to calculate covariate-adjusted weighted risk ratios/the weighted mean
difference (as appropriate) and their 95% confidence intervals, and to conduct
stratified t-tests. All data will be analysed using STATA version 12.1 (SE) (STATA
Corporation, College Station, Texas).
Sub-group analyses
Planned sub-group analyses will be conducted on outcomes to determine whether
there is any significant heterogeneity in treatment effects occurring between important
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groups, such as across patients of different genders and ages, and between hospitals of
different sizes. For each outcome the cluster-level residuals described above will be
regressed on stratum, treatment group, the subgroup variable and all their possible
two-way interactions. F-tests will be used to determine whether there are any
significant interactions between treatment group and subgroups.
Process evaluation
A qualitative process evaluation44 will be conducted at six months into the
intervention, in selected clusters from the intervention and control arms (in the control
arm to understand the implementation process of existing guidelines by clinicians, i.e.
usual practice). The process evaluation aims to describe the health system and service
delivery context in which the intervention was delivered; explore whether or not the
intervention is delivered as intended, both at the cluster level (training) and the
individual level (provider delivery); and understand mechanisms of impact both at the
provider level and caregiver level. The methods, which will also be informed by the
TDF,37-39
will include document review (e.g. meeting minutes), observation of
training sessions and consultations, and qualitative interviews.
In each county we will select one control cluster. After three months of
implementation we will review prescription rates in intervention clusters. If all
intervention clusters are performing in a similar way (i.e. very good, medium, poor),
then we will select one intervention cluster from each county. However, if
intervention clusters are performing very differently, then we will need to select two
intervention clusters from each county (high and low performers) to understand
cluster level factors. In each township hospital selected we will interview doctors, the
hospital director and the pharmacist. We will also conduct a focus group discussion
with caregivers. A sampling frame will be developed and participants will be
purposively selected for inclusion from the selected sites.
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Qualitative data will be recorded if the participants agree to use audio-recording. The
audio files will be transcribed as soon as possible, and any audio files recorded by
mobile recording devices will be immediately deleted once they have been
transcribed.
Analysis of process evaluation
Qualitative data will be analysed as soon as possible after it has been collected. The
analysis will feed into subsequent interviews, and if new issues emerge they can be
followed up in subsequent interviews. Data will be audio recorded and transcribed.
Nvivo version 10 (QSR International Pty Ltd) will be used to manage the data. The
data will be analysed using a simple thematic approach.45 Quality of reporting the
qualitative study will be ensured by adhering to the Consolidated criteria for reporting
qualitative studies (COREQ) .46
Discussion
Our study is one of the first trials to address irrational antibiotic prescribing in the
primary care context in China. The study is of great significance given
antibiotic-resistant infections have contributed to high levels of resistance among
children, particularly in countries with less stringent antibiotic prescribing
regulations.7 Our study will contribute to the currently limited number of studies
addressing irrational antibiotic prescribing in the primary care context of rural of
China, and should be more widely applicable to similar contexts. In China most
studies have focused on either clinicians or patients. We therefore aim to test a
comprehensive intervention targeting both clinicians and patients, an approach shown
to have the largest effect29 in rural primary care settings.
The evidence-based and user-friendly guideline on rational antibiotic prescribing is
developed to address the current lack of operational guidelines for primary care
practices. However, simple dissemination of guidelines alone has had limited effects
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on health worker performance,47 48
including in ambulatory care settings.29
Considering the insufficient medical training received by rural primary care doctors
compared to their urban peers in China, 9 we aim to improve their knowledge through
continued professional training in rational antibiotic prescribing. Peer review of
antibiotics prescribing is also planned at monthly hospital staff meetings to monitor
fidelity to the intervention, and enhance the knowledge of doctors. Antibiotics are
culturally accepted in rural China as the first response to self-limiting viral URIs.
Thus, educating the caregivers through primary care doctors is challenging but
essential.49 We have designed an iterative and participatory training process, with an
emphasis on improving the communication and educational skills of primary care
doctors interacting with elders. Our study will be conducted in poor rural areas where
many caregivers are grandparents because many of the young generation have
temporally migrated to cities for employment. We have thus tailored the educational
materials to be more easily understood by people with less education. By improving
caregivers’ knowledge, the intervention is expected to reduce patient demand for
antibiotic prescribing in URIs.
The study fits into the current national priority on antibiotics control in China.
However, major control efforts have currently focused on referral hospitals rather than
the primary care level, especially in rural areas. The study will thus help to shape the
policies and regulations regarding antibiotic use, especially under primary care
settings.13 Multiple interventions have proved effective on improving the rational use
of antibiotics. However, some interventions, such as point-of-care tests, are not
feasible in primary care settings in poor rural areas of China. In this trial, all the
interventions are embedded within the routine primary care management and practice.
Thus, additional work and costs that would otherwise have been added to primary
care will be reduced, enhancing the replicability of the intervention.
Normaliszation Process Theory (NPT)50 51
provides a useful lens for understanding
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the processes that affect the implementation, embedding, and integration of rational
antibiotic prescribing into healthcare systems. However, our main aim for the process
evaluation 44 is to understand the barriers and facilitators which are embedded within
the context, the implementation and mechanisms of impact, and which mechanisms
affect behaviour change outcomes. We also aim to understand how to overcome
implementation challenges and scale-up the intervention. For instance, the uncertain
effect of the zero-price mark-up policy on reducing medicine use may suggest
influences beyond providers and patients, such as those of pharmaceutical companies.
In this study we use the APR as the outcome, rather than other clinical and laboratory
measures such as the positive rate of the extended-spectrum beta-lactamases, because
we want to focus on provider behavior, whereas more complex patient outcomes will
be difficult to interpret in the face of many confounding factors. Trials of reducing
antibiotic prescriptions for acute respiratory infections are not uncommon in
high-income countries.18 21 25 28
Given few relevant interventions exist in
low-to-middle income countries, and different studies have focused on different
populations, comparisons with other studies needs to be cautious. Misdiagnosis (either
over- or under-diagnosis) of URIs may happen, which would bias the APR and could
even have a negative impact on treatment. However, this bias will be minimized as
diagnosis and treatment in both arms is based on Chinese antibiotics use guidelines
and IMCI guidelines.
Outputs will include an operational guideline on the rational use of antibiotics for
URIs among children, and training modules and other materials that may be scaled-up
in Guangxi and other western provinces. These materials also have the potential to be
adapted to other low- and middle-income country contexts. We therefore believe this
trial will greatly contribute to improving the prescribing behavior of doctors in the
rural primary care context in China, and other developing countries.
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Ethics and dissemination
The trial has received ethical approval from the Ethics Committees of the University
of Leeds and Guangxi Provincial Centre for Disease Control and Prevention, China.
The results will be disseminated through policy briefs, workshops, peer-reviewed
publications and local and international conferences.
There have been no modifications to the protocol which may impact on the conduct of
the study, potential benefit and safety of the patients, including changes of the
objectives, design, population, sample sizes, procedures, or significant administrative
aspects of the study. Any amendment in the future will seek prior approval from the
Ethics Committees.
No consent form will be provided for prescription review. Guangxi CDC will seek
agreement from each hospital under study. They will explain to them that we will use
the patients’ information only for research purposes and ensure the confidentiality of
the patients. Personal identifying information such as names and national ID would be
deleted before data is input into our research files. For the provider interviews, to
allow for the rural China context, we will allow verbal consent to be given by
providers if requested for interviews, to protect people working in bureaucratic health
systems, and to obtain as much objective information as much. Regarding the
patient/caregiver focus groups, written informed consent will be obtained from each
participant (verbal consent from the illiterate parents/caregivers). Information sheets
will be provided and/or explained for both providers (SUPP INFO 2) and caregivers
(SUPP INFO 3).
For the prescription data, personally identifying information will be deleted before
data is entered into the database, and each prescription will be assigned a unique study
identification number. Physical hard copies of study data materials will be stored
securely in a locked cabinet, separate from the data of other studies. The
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photographed prescriptions will be deleted as soon as possible following information
extraction. For the qualitative data, only the researchers conducting the study will
know the names of participants, and have access to the responses from individual
participants.
Only the principal investigators (XW and ML) will be given access to the cleaned
data sets. Project data sets will be stored electronically by the China Global Health
Research and Development, and all data sets will be password protected.
We will disseminate the main findings to provincial and national CDC and authorities,
our Communicable Disease – Health Service Delivery (COMDIS-HSD) Research
Programme Consortium country partners in South Asia and Africa, and relevant
international stakeholders. We will publish in national and international journals, and
present at national and international conferences.
The protocol adheres to the recommendations provided by the SPIRIT 2013.52 All
items from the World Health Organization Trial Registration Data Set are available in
SUPP INFO 4.
Contributors
All authors made substantive contributions to the trial development and provided final
approval for this manuscript. XW, GZ, JW, HE, RK and YH designed the trial and
related studies. GZ and XW drafted the manuscript. JW, ML, JZ, YH, YH, ZZ, SD,
RK, HE, QS contributed to designing the trial and participated in the pilot study. JPH
contributed to the statistical issues in the study design and wrote the statistical
analysis plan. RK contributed to the design of the process evaluation and qualitative
methods. HE contributed to trial and process evaluation design and critically reviewed
the manuscript. CB, SD and GZ contributed to ethics development. CB, JW and JPH
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critically reviewed the manuscript. XW and ML are co-principal investigators of the
trial.
The trial sponsor is China Global Health Research and Development (Contact name:
Dr. Xiaolin Wei, Address: Room 403 No.1032 Dongmen Bei Road, Shenzhen, China
Tel: (86)755 22250390, Email: [email protected])
Funding
The trial is supported by the Department for International Development of the UK
Government (DFID) via the COMDIS-HSD Research Programme Consortium. This
funding source had no role in the design of this study and will not have any role
during its execution, analyses, interpretation of the data, or decision to submit results.
Competing interests
The authors declare that they have no competing interests.
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18. Gonzales R, Anderer T, McCulloch CE, et al. A cluster randomized trial of decision support
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to promote judicious use of antibiotics for acute respiratory infections in primary
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20. Hingorani R, Mahmood M, Alweis R. Improving antibiotic adherence in treatment of
acute upper respiratory infections: a quality improvement process. 2015 2015;5(3).
21. Little P, Stuart B, Francis N, et al. Effects of internet-based training on antibiotic
prescribing rates for acute respiratory-tract infections: a multinational, cluster,
randomised, factorial, controlled trial. Lancet 2013;382(9899):1175-82.
22. Cals JW, de Bock L, Beckers PJ, et al. Enhanced communication skills and C-reactive
protein point-of-care testing for respiratory tract infection: 3.5-year follow-up of a
cluster randomized trial. Ann Fam Med 2013;11(2):157-64.
23. Altiner A, Berner R, Diener A, et al. Converting habits of antibiotic prescribing for
respiratory tract infections in German primary care--the cluster-randomized
controlled CHANGE-2 trial. BMC Fam Pract 2012;13:124.
24. Price EL, Mackenzie TD, Metlay JP, et al. A computerized education module improves
patient knowledge and attitudes about appropriate antibiotic use for acute
respiratory tract infections. Patient Educ Couns 2011;85(3):493-8.
25. Pettersson E, Vernby A, Molstad S, et al. Can a multifaceted educational intervention
targeting both nurses and physicians change the prescribing of antibiotics to nursing
home residents? A cluster randomized controlled trial. J Antimicrob Chemother
2011;66(11):2659-66.
26. Ruvinsky S, Monaco A, Perez G, et al. Effectiveness of a program to improve antibiotic
use in children hospitalized in a children's tertiary care facility in Argentina. Arch
Argent Pediatr 2014;112(2):124-31.
27. Liang X, Xia T, Zhang X, et al. Governance structure reform and antibiotics prescription in
community health centres in Shenzhen, China. Fam Pract 2014;31(3):311-8.
28. Persell SD, Friedberg MW, Meeker D, et al. Use of behavioral economics and social
psychology to improve treatment of acute respiratory infections (BEARI): rationale
and design of a cluster randomized controlled trial [1RC4AG039115-01]--study
protocol and baseline practice and provider characteristics. BMC Infect Dis
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29. Arnold Sandra R, Straus Sharon E. Interventions to improve antibiotic prescribing
practices in ambulatory care. Cochrane Database of Systematic Reviews 2005, Issue
4. Art. No.: CD003539. DOI: 10.1002/14651858.CD003539.pub2.
30. Huang SS, Rifas-Shiman SL, Kleinman K, et al. Parental knowledge about antibiotic use:
results of a cluster-randomized, multicommunity intervention. Pediatrics
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31. Taylor JA, Kwan-Gett TS, McMahon EM, Jr. Effectiveness of a parental educational
intervention in reducing antibiotic use in children: a randomized controlled trial.
Pediatr Infect Dis J 2005;24(6):489-93.
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32. Wheeler JG, Fair M, Simpson PM, et al. Impact of a waiting room videotape message on
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36. Hu Y, Walley J, Zou G, et al. Report on a meta-analysis on educational intervention to
reduce inappropriate antibiotic prescription among children with upper respiratory
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37. Cane J, O’Connor D, Michie S. Validation of the theoretical domains framework for use in
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38. French SD, Green SE, O’Connor DA, et al. Developing theory-informed behaviour change
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39. Tavender EJ, Bosch M, Gruen RL, et al. Understanding practice: the factors that influence
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40. Michie S, Johnston M, Francis J, et al. From theory to intervention: mapping theoretically
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41. Chan ED, Strand MJ, Iseman MD. Multidrug-resistant tuberculosis (TB) resistant to
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42. Hayes RJ ML. Cluster Randomised Trials: CRC Press, 2009.
43. Team. RDC. R: A Language and Environment for Statistical Computing. . Available online
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45. Patton M. Qualitative research and evaluation methods: integrating theory and practice.
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46. Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research
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for Quality in Health Care 2007;19(6):349.
47. Giguere A, Legare F, Grimshaw J, et al. Printed educational materials: effects on
professional practice and healthcare outcomes. Cochrane Database Syst Rev
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2012;10:Cd004398.
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49. Yu M, Zhao G, Stalsby Lundborg C, et al. Knowledge, attitudes, and practices of parents in
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infectious diseases 2014;14(1):112.
50. Finch TL, Rapley T, Girling M, et al. Improving the normalization of complex
interventions: measure development based on normalization process theory
(NoMAD): study protocol. Implement Sci 2013;8:43.
51. McEvoy R, Ballini L, Maltoni S, et al. A qualitative systematic review of studies using the
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52. Chan A-W, Tetzlaff JM, Gøtzsche PC, et al. SPIRIT 2013 explanation and elaboration:
guidance for protocols of clinical trials. BMJ 2013;346.
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Table 1: Multi-dimensional interventions designed to reduce the use of antibiotics among children
Targeted group Theoretical domains Behavior change techniques, modes and content of delivery
Provider side
(doctors)
1. Knowledge
2. Skills
3. Beliefs about capabilities
Techniques: information provision.
Mode 1: operational guidelines.
Content: URI management work flow, methods of diagnosis URI and other
common diseases among children, communication skills between clinicians and
patients.
Mode 2: facilitated training/workshop.
Content: rational antibiotics use especially for childhood URI (using lectures,
case discussion and Q&A (participatory and interactive).
Behavior regulation Techniques: monitoring and feedback
Mode: antibiotics prescribing appraisal
Contents/procedures:
1) Monthly antibiotic prescriptions collected by research team at the
beginning of every month; 2) Feedback sent back to township hospital
after calculating the APR by research team; 3) Antibiotics use appraisal
according to APR feedback in monthly hospital staff meeting; 4) Meeting
memo written down by the township coordinator; 5) Township
coordinator sends the memo to trial manager.
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1. Beliefs about consequences
(care givers)
2. Knowledge (caregivers)
3. Social influence (caregivers)
Techniques: information provision and persuasive communication.
Mode: health education to patient caregivers during clinical consultations.
Content: specific short messages, e.g., definition of antibiotic, rational antibiotic
use for childhood URIs, accompanied by simple printed educational materials.
Consumer side
(parents/caregivers)
1. Beliefs about consequences
(care givers)
2. Knowledge (caregivers)
3. Social influence (caregivers)
Techniques: information provision.
Mode 1: Educational messages from doctors, and educational material/leaflets.
Content: explanation about antibiotics, the impacts of antibiotic resistance and
rational antibiotics use for childhood URIs (using leaflets with simple words and
pictures).
Mode 2: educational videos played at township hospitals (5-8 minutes).
Content: explanation about antibiotics, the situation of irrational use of antibiotics
in China and the impact of antibiotic resistance (using a local TV show)
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a. Eligible subjects include all outpatient prescriptions for children, aged between 2 and 14 years
old, diagnosed with URIs.
b. Intervention package for doctors includes: operational guidelines, training, peer review
meetings, consultation (with educational leaflets); and for parents/caregivers includes:
messages from doctors, educational leaflets and videos.
c. Usual care refers to health care following routine practice at discretion of individual doctors.
d. Baseline data: three months before intervention; outcome data: the last three months of the
intervention.
Figure 1 Trial Flow Chart
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An analysis plan for a pragmatic cluster randomized controlled trial for reducing
irrational antibiotic prescribing among children with upper respiratory infections in
rural China
Introduction
Irrational use of antibiotics, defined by the World Health Organization as antibiotic
prescriptions exceeding 30% of all prescriptions,1 is a serious issue both within China and
internationally. Worldwide, around 50% of medicines are not appropriately prescribed,
dispensed or sold.1 Irrational use of antibiotics not only brings high economic burdens to
health systems, but also increases the risk of antibiotic resistance.1 Acute upper respiratory
infections (URIs) are very common among children, but are usually viral and self-limiting,
with antibiotic treatment being unnecessary.2 However, irrational use of antibiotics for URIs
in children is very prevalent in primary care settings internationally.3
A cross-sectional study in ten provinces in rural Western China showed that antibiotics
accounted for over half of all prescriptions, predominantly provided for URIs, and with
approximately one quarter of those receiving antibiotics being children under ten years old.4
Irrational antibiotic use amongst children is known to contribute to higher childhood
mortality in countries with inadequate health infrastructure.5 Several national policies have
been issued by the Ministry of Health, including the most recent one limiting antibiotic
prescriptions to less than 60% of all prescriptions for inpatients and 20% for outpatients.6
However, no operational details were provided on how to implement the policy, and no
guidelines were provided for the diagnosis and treatment of URIs in children, or related
clinician training. Potentially because of this situation, despite attempts at health sector
reform there has been no significant improvement in the rational use of antibiotics or cost
control in China.7
Commonly reported interventions for improving antibiotic use in URI treatment include
clinical decision support,8-11
clinician communication skills training,12-14
education and
feedback,15
public reporting of antibiotic prescribing rates,16
discussion and monitoring
workshops,17
governance structure change,18
and interventions based on behavioural
economics and social psychology.19
However, a Cochrane review demonstrated that while
multi-faceted interventions targeting both physicians and patients significantly reduced
inappropriate antibiotic use in community settings,20
single interventions with parents failed
to impact on antibiotic prescribing.21-23
Therefore, we developed a multidimensional intervention targeting doctors and patient
caregivers that aimed to reduce the irrational use of antibiotics for treating URIs in children
within China’s rural primary care context (specifically within township hospitals). The
intervention was developed through exploratory work, and its feasibility, acceptance and the
adequate adherence of doctors to the intervention has been confirmed via an internal pilot.
Aims and objectives
This study aims to evaluate the clinical effectiveness of the intervention in realistic primary
care settings in rural China, by determining whether the intervention reduces the amount of
antibiotics prescribed for URIs in child outpatients within township hospitals, compared to
existing prescribing practice.
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Study design
The trial has been designed as a pragmatic, parallel-group, cluster randomised, controlled
trial. The trial will evaluate the superiority of the intervention within township hospitals,
which are therefore the unit of randomization.
Randomization process
In total 25 township hospitals were eligible for the trial, with 14 in Rong County and 11 in
Liujiang County. Randomization was stratified by county to avoid imbalances in allocation
between counties, because of the potential for important variation in outcomes between the
counties. Randomization was further restricted within each county to a subset of all possible
allocation ratios. Within Rong County randomization was restricted to only that subset of
allocations that resulted in equal numbers of township hospitals in each arm, and in Liujiang
County randomization was restricted to only that subset of allocations that resulted in the
allocation of township hospitals to the treatment and control arms in a 5:6 allocation ratio.
This allocation ratio was chosen to ensure that the allocation ratio was as equal as possible
with an odd number of township hospitals, whilst minimizing the logistical costs of the
treatment arm by having the additional hospital allocated to the control arm. After all 25
hospitals were randomized, within Rong County 6 hospitals, 3 from each arm, were further
randomly selected to become the internal pilot clusters. The remaining 19 township hospitals
(8 in Rong County and 11 in Liujiang County) will therefore participate in the main trial,
along with the 6 hospitals involved in the internal pilot. Therefore, overall the 25 hospitals
were allocated to treatment and control arms in a 12:13 allocation ratio. Randomization was
conducted by the study statistician (JPH) using a computer program written in R (version
3.2.0).24 25
Outcome data will be collected from at least 5000 prescriptions (approximately 200 per
hospital) issued for URIs in outpatients aged between 2 and 14 years old during the three
months before the implementation of the intervention to provide baseline data, and during the
4th
to the 6th
month following randomization of hospitals.
Within intervention hospitals all family doctors will receive training to increase their
knowledge on the rational use of antibiotics, and to improve the effectiveness of their
communication skills when interacting with caregivers of children with URIs, facilitating the
education of caregivers on the rational use of antibiotics. Monthly peer review meetings will
also assess doctors’ antibiotic prescribing practices, and reinforce desired behaviours. Printed
and video-based educational materials will also be provided for caregivers in intervention
hospital waiting rooms to improve understanding about the rational use of antibiotics. In
control hospitals none of the intervention components will be implemented, and the only
apparent impact will be via the collection of prescription data.
Blinding is clearly not possible for doctors or caregivers, but there will be blinded evaluation
of all outcomes. A cluster design was chosen due to the difficulty of preventing
contamination of both doctors and caregivers, and the need for hospital-wide participation of
doctors in the peer review meetings, which are a key component of the intervention.
Sample size
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Based on our exploratory study the current APR is approximately 50%, which is therefore
assumed for the usual care arm. We expect our intervention to lead to at least a 25% relative
reduction in the antibiotic prescription rate within township hospitals, based on a
conservative estimate from our systematic review.26
Consequently, to detect a 25% or greater
reduction in the APR (i.e. an absolute reduction to 37.5% APR or less) with 90% power,
using two-sided testing at the 5% significant level, assuming a harmonic mean cluster size of
200 and a between cluster coefficient of variation of 0.15 (based on exploratory and pilot
work), we estimate that we require 9 township hospitals per arm.24
Allowing for stratified
randomization and a 10% loss of data, due to lost and illegible prescriptions, requires a total
of 24 township hospitals. As there are 25 eligible township hospitals within the two counties
it was decided to include all 25.
Outcomes and data
All outcome data will be obtained from the prescriptions collected at baseline and during
follow-up, either in the form of electronic or photographic records of paper copies of
prescriptions. Information collected will include the township hospital, the date of the
prescription, the patient’s age, symptoms, diagnosis, prescribed medicines, related treatment,
related laboratory tests, treatment payment and insurance status.
Primary outcome
The antibiotic prescription rate for childhood URIs. Measured at the township hospital level,
and defined as the proportion of prescriptions for URIs among outpatients aged between 2
and 14 years old that include at least one antibiotic. The antibiotic prescription rate is the
primary outcome because it should reflect the behaviour change of both doctors and
caregivers. Most URIs are caused by viral infection that are self-limiting and do not require
antibiotics, and a reduction in this rate will be a clinically beneficial outcome demonstrating
increased rational prescribing of antibiotics for childhood URIs. This measurement is also
reliable and feasible in the primary care setting because prescriptions are well preserved
either electronically or in paper files.
Secondary outcomes
The childhood URI multiple antibiotic prescription rate: measured at the township
hospital level and defined as the proportion of prescriptions for URIs among
outpatients aged between 2 and 14 years old that include two or more antibiotics;
The childhood URI broad-spectrum antibiotic prescription rate: measured at the
township hospital level and defined as the proportion of prescriptions for URIs among
outpatients aged between 2 and 14 years old that include a broad-spectrum antibiotic;
The childhood URI quinolones prescription rate: measured at the township hospital
level and defined as the proportion of prescriptions for URIs among outpatients aged
between 2 and 14 years old that include a quinolone antibiotic;
Additionally, to understand the medical costs associated with antibiotics prescribing
we will measure the mean cost (in Yuan) at the township hospital level of childhood
URI prescriptions, based on all prescriptions for URIs among outpatients aged
between 2 and 14 years old.
Secondary outcomes were chosen to assess the extent to which the intervention will reduce
other commonly observed practices in routine primary care relating to antibiotic prescribing
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practices for URIs that are particularly likely to increase drug-resistance, and the
intervention’s cost effectiveness.
Missing data
An exploration of the patterns of missingness will be conducted, but it is expected that due to
the most likely and plausible reasons for missing data (lost paper and electronic prescriptions
records, and unreadable paper prescription records), missing data will be missing completely
at random. Therefore, only complete case analyses will be conducted unless there is an
indication that data may be missing at random, in which appropriate methods to deal with
missingness will be employed as sensitivity analyses in addition to the complete case
analyses.
Populations
Township hospital eligibility criteria
All township hospitals from the two selected counties in Guangxi who agree to participate in
the study will be included. However, we will exclude the two township hospitals located in
the two county centres. Compared to all other township hospitals they have much higher staff
capacity and equipment levels, and their proximity to the county general hospital is likely to
result in patient populations with substantially different characteristics.
Patient prescription eligibility criteria
All outpatient prescriptions for children aged between 2 and 14 years old who are diagnosed
with URIs during the study period will be included for analysis. Children under 2 years old
will be excluded because they are more vulnerable to secondary bacterial infection, and
exploratory work indicated that it was very difficult for doctor’s to refuse antibiotics for
younger children in China’s context. Prescriptions for children diagnosed with pneumonia
(where antibiotic prescription is appropriate) or other severe diseases requiring long-term
antibiotic treatment (or as prophylaxis) will also be excluded. Prescriptions for inpatients will
not be collected.
Populations
The intention-to-treat (ITT) population is defined as all outpatient-prescriptions issued for
URIs in children aged 2-14 years old collected from township hospitals, regardless of the
compliance of township hospital doctors and/or caregivers to the intervention. All statistical
analyses of primary and secondary outcomes will be by ITT.
Data handling
Data monitoring
All personally identifying details will be removed from the study database. Data will be
checked weekly for quality and completeness by the study data manager, and any missing
data will be followed-up with township hospitals until received (if electronically available),
confirmed as set aside for later collection by researchers (if paper-based) or confirmed as not
available. Recruitment rates will be monitored on a monthly basis. There is no Data
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Monitoring and Ethics Committee or equivalent associated with the study. Data collected
from electronic or photographic records of prescriptions will be entered into a password-
protected SPSS database (version 20.0, IBM Corp. Armonk, NY.).
Data validation
Prior to analysis the final database will be validated using a STATA program to identify any
anomalous, inconsistent and missing data. This program will check/identify:
Eligibility criteria of prescriptions
Consistency of prescription issue dates relative to the baseline and outcome data
collection periods
Outlying and anomalous (e.g. incorrect format, impossible value) data
Missing data
All anomalous, inconsistent or unexpectedly missing data will be checked against original
paper or photographic prescription records where feasible. Any anomalous or inconsistent
data that can be unambiguously corrected will be, but where any ambiguity cannot be
resolved values will be recorded as missing data.
Data analysis
General calculations
Percentage calculations will exclude any missing prescriptions from the denominators.
Summary statistics such as percentages and means will be rounded to 1 decimal place, or 1
significant figure for numbers less than 1, but standard deviations will be rounded to 2
decimal places, or 2 significant figures for numbers less than 1. Parameter estimates,
including standard errors SEs and 95% confidence intervals (CIs), will be rounded to 2
decimal places, or 2 significant figures for numbers less than 1. All hypothesis testing will be
2-sided and at the 5% significance level. All analyses will be carried out using STATA
Version 12.1 (SE) software, but other packages will be employed if necessary. The primary
and the secondary outcome analyses will be based on the intention-to-treat (ITT) population.
All analyses will be conducted by the study statistician (JPH).
Planned analyses
No interim analyses are planned. Therefore, all outcomes will be analysed after data
collection is completed.
Baseline characteristics
The baseline characteristics of the ITT population (including gender, age, insurance type,
total prescription fee, total number of medicines prescribed; whether or not they were
prescribed an antibiotic, a broad spectrum antibiotic, multiple antibiotics, and which category
of antibiotic(s) they were prescribed; whether the antibiotic was delivered via injection or
orally; and type of diagnosis) and township hospitals (within township hospitals catchment
areas the number of residents, average annual income, number of village clinics and the
number of doctors who can prescribe medicines) will be summarised using frequencies (plus
sample sizes) and means (plus SDs) as appropriate for each treatment group.
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Primary and secondary outcome analyses
The crude and covariate adjusted average effect of the intervention on outcomes will be
analysed using methods appropriate for cRCTs with small numbers of clusters per arm.24
For
the primary outcome an estimate of the overall risk ratio between the intervention and control
arms will be estimated from the weighted average of the stratum-specific risk ratios, with
weights that are inversely proportional to the stratum-specific variances. Stratum-specific risk
ratios will be calculated from the unweighted stratum-specific risks (mean township-hospital-
level outcomes) in each arm. If the within-arm distribution of risk ratios is found to be
strongly skewed for an outcome, a logarithmic transformation will first be applied to the
outcome proportions. Formal testing of the null hypothesis that the overall risk ratios are
equal to 1 will be conducted using stratified t-tests, and 95% confidence intervals will be
adjusted for between-cluster variance and stratification.
Secondary outcomes involving proportions will be analysed using the same methods as the
primary outcome, whilst the average cost of childhood URI prescriptions outcome will be
analysed using similar methods, but with stratum-specific differences between the mean
township-hospital-level outcomes in each arm used in place of stratum-specific risk ratios.
To adjust for potentially important covariates, including baseline values of outcomes, sex,
age and additional important individual and township-hospital level factors two-stage
adjusted analyses will also be conducted. For the primary outcome a logistic regression
model will be fitted to the individual-level data including stratum and the covariates of
interest as fixed effects, but without adjusting for the treatment effect. Covariate-adjusted
ratio residuals will then be calculated from the ratios of cluster-specific observed and
expected values. The covariate-adjusted ratio residuals will then be used in place of cluster-
specific proportions to conduct stratified t-tests and calculate 95% confidence intervals using
the above methods. To analyse the secondary outcomes involving proportions the same
methods will be used as for the primary outcome. To analyse the average cost of childhood
URI prescriptions outcome the same two-stage method will be employed, but using a normal
regression model instead, and with cluster-specific difference residuals, calculated from the
differences between cluster-specific observed and expected values, used in place of stratum-
specific differences in means. Following CONSORT guidelines both unadjusted and adjusted
results will be presented.
For all outcomes within each treatment arm and strata estimates of the between-cluster
coefficient of variation and the intraclass correlation coefficient will also be calculated and
made available to facilitate future trial planning and systematic reviews.
Subgroup analyses
Planned sub-group analyses will be conducted on outcomes to determine whether there is any
significant heterogeneity (or effect modification) in treatment effects occurring between
important groups, such as across patients of different genders and ages, and between hospitals
of different sizes. Cluster-level subgroup analyses will be based on cluster-level covariates
with two groups only, given the limited number of clusters. The methods for unadjusted
cluster-level analyses described above will be used for the cluster-level subgroup analyses,
but applied separately to the two groups of clusters, as determined by the relevant cluster-
level covariate, to obtain estimates of the treatment effect, its 95% confidence interval and
statistical significance within each subgroup. However, if the number of clusters per stratum
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are too few for either of the subgroups then a non-stratified version of these methods will be
used. To estimate the statistical significance of any differences in treatment effect between
subgroups analysis of variance will be used on the cluster-level summary outcome data, with
terms for treatment arm, the relevant subgroup and the interaction between them.24
Individual-level subgroup analyses will be based on computing the difference in outcome
(logged when the outcome effect wanted is a ratio) between subgroups within each cluster,
and then comparing the mean difference in the treatment and control arms. To estimate the
size (and associated 95% confidence intervals) and significance of any interaction between
the treatment effect and subgroups (i.e. effect modification) an unpaired t-test will be
conducted on the cluster-level differences between subgroups.24
References
1. El Mahalli A. WHO/INRUD drug prescribing indicators at primary health care centres in
Eastern province, Saudi Arabia. EMHJ;18(11).
2. Alves Galvão Márcia G, Rocha Crispino Santos Marilene A, Alves da Cunha Antonio JL.
Antibiotics for preventing suppurative complications from undifferentiated acute
respiratory infections in children under five years of age. Cochrane Database of
Systematic Reviews 2014; (2).
http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD007880.pub2/abstract
http://onlinelibrary.wiley.com/store/10.1002/14651858.CD007880.pub2/asset/CD007880.pdf
?v=1&t=ifqozjug&s=ffa4fb20e6eb6cab84110af79bf87112e990651c.
3. Andrews T, Thompson M, Buckley DI, et al. Interventions to influence consulting and
antibiotic use for acute respiratory tract infections in children: a systematic review and
meta-analysis. PLoS One 2012;7(1):e30334.
4. Dong L, Yan H, Wang D. Antibiotic prescribing patterns in village health clinics across 10
provinces of Western China. J Antimicrob Chemother 2008;62(2):410-5.
5. Ilic K, Jakovljevic E, Skodric-Trifunovic V. Social-economic factors and irrational
antibiotic use as reasons for antibiotic resistance of bacteria causing common
childhood infections in primary healthcare. Eur J Pediatr 2012;171(5):767-77.
6. Xiao Y, Li L. Legislation of clinical antibiotic use in China. Lancet Infectious Diseases
2013;13(3):189-91.
7. Mao W, Vu H, Xie Z, et al. Systematic Review on Irrational Use of Medicines in China
and Vietnam. PloS one 2015;10(3):e0117710.
8. Gonzales R, Anderer T, McCulloch CE, et al. A cluster randomized trial of decision
support strategies for reducing antibiotic use in acute bronchitis. JAMA Intern Med
2013;173(4):267-73.
9. Litvin CB, Ornstein SM, Wessell AM, et al. Adoption of a clinical decision support system
to promote judicious use of antibiotics for acute respiratory infections in primary care.
Int J Med Inform 2012;81(8):521-6.
10. Litvin CB, Ornstein SM, Wessell AM, et al. Use of an electronic health record clinical
decision support tool to improve antibiotic prescribing for acute respiratory infections:
the ABX-TRIP study. J Gen Intern Med 2013;28(6):810-6.
11. Mainous AG, 3rd, Lambourne CA, Nietert PJ. Impact of a clinical decision support
system on antibiotic prescribing for acute respiratory infections in primary care:
quasi-experimental trial. J Am Med Inform Assoc 2013;20(2):317-24.
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12. Altiner A, Berner R, Diener A, et al. Converting habits of antibiotic prescribing for
respiratory tract infections in German primary care--the cluster-randomized controlled
CHANGE-2 trial. BMC Fam Pract 2012;13:124.
13. Cals JW, de Bock L, Beckers PJ, et al. Enhanced communication skills and C-reactive
protein point-of-care testing for respiratory tract infection: 3.5-year follow-up of a
cluster randomized trial. Ann Fam Med 2013;11(2):157-64.
14. Little P, Stuart B, Francis N, et al. Effects of internet-based training on antibiotic
prescribing rates for acute respiratory-tract infections: a multinational, cluster,
randomised, factorial, controlled trial. Lancet 2013;382(9899):1175-82.
15. Pettersson E, Vernby A, Molstad S, et al. Can a multifaceted educational intervention
targeting both nurses and physicians change the prescribing of antibiotics to nursing
home residents? A cluster randomized controlled trial. J Antimicrob Chemother
2011;66(11):2659-66.
16. Yang L, Liu C, Wang L, et al. Public reporting improves antibiotic prescribing for upper
respiratory tract infections in primary care: a matched-pair cluster-randomized trial in
China. Health Res Policy Syst 2014;12:61.
17. Ruvinsky S, Monaco A, Perez G, et al. Effectiveness of a program to improve antibiotic
use in children hospitalized in a children's tertiary care facility in Argentina. Arch
Argent Pediatr 2014;112(2):124-31.
18. Liang X, Xia T, Zhang X, et al. Governance structure reform and antibiotics prescription
in community health centres in Shenzhen, China. Fam Pract 2014;31(3):311-8.
19. Persell SD, Friedberg MW, Meeker D, et al. Use of behavioral economics and social
psychology to improve treatment of acute respiratory infections (BEARI): rationale
and design of a cluster randomized controlled trial [1RC4AG039115-01]--study
protocol and baseline practice and provider characteristics. BMC Infect Dis
2013;13:290.
20. Arnold Sandra R, Straus Sharon E. Interventions to improve antibiotic prescribing
practices in ambulatory care. Cochrane Database of Systematic Reviews 2005; (4).
http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD003539.pub2/abstract
http://onlinelibrary.wiley.com/store/10.1002/14651858.CD003539.pub2/asset/CD003539.pdf
?v=1&t=ifphjtif&s=aaa533bb3d45fdf3ed3d83bfa608884a95301f66.
21. Huang SS, Rifas-Shiman SL, Kleinman K, et al. Parental knowledge about antibiotic use:
results of a cluster-randomized, multicommunity intervention. Pediatrics
2007;119(4):698-706.
22. Taylor JA, Kwan-Gett TS, McMahon EM, Jr. Effectiveness of a parental educational
intervention in reducing antibiotic use in children: a randomized controlled trial.
Pediatr Infect Dis J 2005;24(6):489-93.
23. Wheeler JG, Fair M, Simpson PM, et al. Impact of a waiting room videotape message on
parent attitudes toward pediatric antibiotic use. Pediatrics 2001;108(3):591-6.
24. Hayes RJ ML. Cluster Randomised Trials: CRC Press, 2009.
25. Team. RDC. R: A Language and Environment for Statistical Computing. . Available
online at http://www.R-project.org/: Vienna, Austria : the R Foundation for Statistical
Computing., 2011.
26. Hu Y, Walley J, Zou G, et al. Report on a meta-analysis on educational intervention to
reduce inappropriate antibiotic prescription among children with upper respiratory
infections COMDIS Health Service Delivery Research Consortium, China
Programme 2015.
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Reducing irrational antibiotic use among children with upper respiratory
infections (URIs) in Guangxi
Participant Information Sheet (PIS) for township hospital directors/clinical
doctors - In-depth interview
Background to the research study
Overuse of antibiotics is an issue in rural China. Inappropriate use of antibiotics increases the
risk of bacterial resistance, and can lead to difficulty treating patient with serious bacterial
infections.
An intervention was designed to reduce inappropriate antibiotic use in rural Guangxi (for
example, for minor childhood upper respiratory viral infections). The intervention aims to
reduce inappropriate prescribing of antibiotics by doctors, and increase the health knowledge
of parents and caregivers in regards to minor self-limiting childhood viral illnesses. It does
this through the provision of up-to-date guidelines on antibiotics prescribing for doctors,
training, and clinical support activities. In addition, parents and caregivers of children are
given information leaflets, and videos about antibiotics and minor illnesses in childhood are
available to watch in waiting areas.
Who is conducting the research?
The research is led by Global Health Research and Development (GHRD), China. Technical
support is provided by Leeds University, UK.
Why have I been invited to take part in an interview?
The township hospital in which you work has been involved in this intervention study. We
would like to find out your views and experiences.
What am I being asked to do?
You are invited to participate in a short interview with a researcher. Your views are important
to us, and will help our future efforts to improve the current intervention. The interview will
last about 30-40 minutes, and will be audio-recorded. The decision to participate is yours.
Before starting the interview, a researcher will ask for your signed consent/ agreement. If you
change your mind during the interview, we will respect your wish and end the interview.
Your participation is entirely voluntary; you will not receive payment for the interview.
What will happen to the information I give?
All information collected during the interview will be used for research purposes. We will not
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Reducing irrational antibiotic use among children with upper respiratory
infections (URIs) in Guangxi
share any information that could identify you outside the research team. All identifying
information will be kept securely locked away by the research team, and a number will be
used instead of your name where required. Any quotes from interviews which are used in
research reports will not contain information that could identify you.
Who has approved the research?
The study has been approved by the Guangxi Centre for Disease Control Ethical Review
Board and the University of Leeds School of Medicine Research Ethics Committee.
Who has funded the research?
This project has been funded by Department for International Development (DFID), as part
of the COMDIS-HSD consortium of the University of Leeds, UK.
What should I do if I have more questions?
Please talk to the researcher who gave you this form if you have any questions. If you have
any further questions about this study, please contact Prof. Wei Xiaolin, the principal
investigator of the project, by phone 0755-22250390 or by Email at [email protected].
Or contact Guangxi CDC Dr. Mei Lin by phone 0771-5300561.
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Reducing irrational antibiotic use among children with upper respiratory
infections (URIs) in Guangxi
Consent Form for township hospital directors/clinical doctors – In-depth
interview
The purpose of the interview has been explained to me.
I consent to take part in an interview about my views and experiences as outlined in the
information sheet.
I also consent for the interview to be audio-recorded.
My participation is completely voluntary. I understand that I am free to stop the interview
at any time.
None of my experiences or thoughts will be shared anyone outside of this study unless all
identifying information is removed first.
Participant’s name: ________________ Date ________________
Participant's signature(no need to sign if oral consent is used): ____________
Researcher's name: ________________ Date ________________
Researcher's signature: ____________
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Reducing irrational antibiotic use among children with upper
respiratory infections (URIs) in Guangxi
1
Participant Information Sheet (PIS) for parents/caregivers – Focus
group
Background to the research study
Antibiotics are sometimes used when they are not needed, in rural areas of China. This
causes bacteria to become more resistant to antibiotics, and serious infections are more
difficult for doctors to treat effectively. One way to reduce resistance is to stop using
unnecessary antibiotics for minor illnesses (such as self-limiting viral infections in
children).
An intervention has been designed to reduce unnecessary antibiotic use in rural Guangxi
(for example, for minor childhood upper respiratory viral infections). The intervention
aims to reduce unnecessary antibiotics given by doctors, and educate parents and
caregivers on minor self-limiting childhood viral illnesses. The intervention gives doctors
up-to-date guidelines on antibiotics, training, and support. Parents and caregivers of
children are given information leaflets, and videos about antibiotics and minor illnesses in
childhood are available to watch in waiting areas.
Who is conducting the research?
The research is led by Global Health Research and Development (GHRD), China.
Technical support is provided by Leeds University, UK.
Why have I been invited to take part in an interview?
A researcher has invited you to be part of a focus group discussion because your child was
treated for an upper respiratory infection in the township hospital recently.
What am I being asked to do?
We would like you to join a discussion about patient and caregiver experiences of their
child’s recent hospital visit. The discussion will be in a small group with other parents and
caregivers, and a researcher. Your views are important to us, and will help our efforts to
reduce unnecessary prescribing of antibiotics. The focus group discussion will last about
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respiratory infections (URIs) in Guangxi
2
30-40 minutes, and will be audio-recorded. The decision to participate is yours, and will
not affect the care your child receives in any way. Before starting the focus group, a
researcher will ask for your signed consent/ agreement to participate. If you change your
mind during the focus group, your decision will be respected. Your contribution up to that
point will remain (since it is a part of the audio-recording), but the researcher will
facilitate your exit from the group and from any further discussions. Your participation is
entirely voluntary; you will not receive payment for the being in the focus group.
What will happen to the information I give?
All information collected during the focus group will be used for research purposes, to
improve efforts to stop antibiotic resistance. We will not share any information that could
identify you outside the research team: all identifying information will be kept securely
locked away by the research team, and any quotes from the focus group which are used in
research reports will not contain information that could identify you.
Who has approved the research?
The study has been approved by the Guangxi Centre for Disease Control Ethical Review
Board and the University of Leeds School of Medicine Research Ethics Committee.
Who has paid for the research?
This project has been funded by Department for International Development (DFID), as
part of the COMDIS-HSD consortium of the University of Leeds, UK.
What should I do if I have more questions?
Please talk to the researcher who gave you this form if you have any questions. If you
have any further questions about this study, please contact Prof. Wei Xiaolin, the principal
investigator of the project, by phone 0755-22250390 or by Email at
[email protected]. Or contact Guangxi CDC Dr. Mei Lin by phone 0771-5300561.
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Reducing irrational antibiotic use among children with upper
respiratory infections (URIs) in Guangxi
3
Consent Form for parent/ caregiver – Focus group
The purpose of the focus group has been explained to me.
I consent to take part in a focus group about my child’s recent hospital visit.
I consent for the focus group to be audio-recorded.
My participation is completely voluntary. I understand that I am free to leave the
focus group at any time, however my contribution up to that point would remain as
part of the group’s audio-recording.
None of my experiences or thoughts will be shared anyone outside of this study unless
all identifying information is removed first.
Participant’s name: ________________ Date ________________
Participant's signature: ____________
Researcher's name: ________________ Date ________________
Researcher's signature: ____________
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Category Information
Primary registry and
trial identifying number
ISRCTN14340536
Date of registration in
primary registry
23 June, 2015
Secondary identifying
numbers
N/A
Source(s) of monetary
or material support
Department for International Development of the UK Government
Primary sponsor China Global Health Research and Development
Secondary sponsor(s) N/A
Contact for public
queries
Dr. Xiaolin Wei, MD, MPH,PHD [[email protected]]
Contact for scientific
queries
Dr. Xiaolin Wei, MD, MPH,PHD [[email protected]]
China Global Health Research and Development, Shenzhen, China
Public title Reducing irrational antibiotic prescribing among children with upper respiratory infections in rural China
Scientific title A pragmatic cluster randomized controlled trial for reducing irrational antibiotic prescribing among children
with upper respiratory infections in rural China
Countries of recruitment China
Health condition(s) or
problem(s) studied
Antibiotic treatment, Upper respiratory infections
Intervention(s) Operational guidelines
Systematic training
Peer review of antibiotic prescribing
Health education to patient caregivers with printed educational materials and educational videos provided
Key inclusion and
exclusion criteria
Ages eligible for study: 2-14 years
Sexes eligible for study: both
Accepts healthy volunteers: no
Inclusion criteria: All outpatient prescriptions for children aged between 2 and 14 years old, diagnosed with
URIs during the baseline and intervention data collection period will be included for analysis.
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Category Information
Exclusion criteria: Prescriptions for children diagnosed with pneumonia or severe diseases such as cancer,
tuberculosis, HIV/AIDS/immunodeficiency, chronic heart diseases or others who need long term antibiotic
treatment or as prophylaxis
Study type Interventional
Allocation: randomized intervention model. Parallel assignment masking: blinded outcome evaluation, but
un-blinded treatment.
Primary purpose: prevention
Date of first enrolment June 2015
Target sample size 5000
Recruitment status Completed
Primary outcome(s) Antibiotic prescription rate for childhood URIs
Key secondary
outcomes
Childhood URI prescription rate for multiple antibiotics, broad-spectrum antibiotics and quinolones; mean
cost of childhood URI prescriptions
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1
SPIRIT 2013 Checklist: Recommended items to address in a clinical trial protocol and related documents*
Section/item Item No
Description Addressed on page number
Administrative information
Title 1 Descriptive title identifying the study design, population, interventions, and, if applicable, trial
acronym
Page 1
Trial registration 2a Trial identifier and registry name. If not yet registered, name of intended registry Page 2
2b All items from the World Health Organization Trial Registration Data Set SUPP INFO 4____________
Protocol version 3 Date and version identifier Page 1____________
Funding 4 Sources and types of financial, material, and other support Page 21_____________
Roles and
responsibilities
5a Names, affiliations, and roles of protocol contributors Page 1 & 20____________
5b Name and contact information for the trial sponsor Page 21____________
5c Role of study sponsor and funders, if any, in study design; collection, management, analysis,
and interpretation of data; writing of the report; and the decision to submit the report for
publication, including whether they will have ultimate authority over any of these activities
Page 21_____________
5d Composition, roles, and responsibilities of the coordinating centre, steering committee,
endpoint adjudication committee, data management team, and other individuals or groups
overseeing the trial, if applicable (see Item 21a for data monitoring committee)
Page 6_____________
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Introduction
Background and
rationale
6a Description of research question and justification for undertaking the trial, including summary
of relevant studies (published and unpublished) examining benefits and harms for each
intervention
Page 4-6_____________
6b Explanation for choice of comparators Page 10
Objectives 7 Specific objectives or hypotheses Page 5_____________
Trial design 8 Description of trial design including type of trial (eg, parallel group, crossover, factorial, single
group), allocation ratio, and framework (eg, superiority, equivalence, noninferiority,
exploratory)
Page 6_____________
Methods: Participants, interventions, and outcomes
Study setting 9 Description of study settings (eg, community clinic, academic hospital) and list of countries
where data will be collected. Reference to where list of study sites can be obtained
Page 6-7____________
Eligibility criteria 10 Inclusion and exclusion criteria for participants. If applicable, eligibility criteria for study centres
and individuals who will perform the interventions (eg, surgeons, psychotherapists). How are
patients recruited, or self-selected?
Page 7____________
Interventions 11a Interventions for each group with sufficient detail to allow replication, including how and when
they will be administered
Page 8-10____________
11b Criteria for discontinuing or modifying allocated interventions for a given trial participant (eg,
drug dose change in response to harms, participant request, or improving/worsening disease)
N/A
11c Strategies to improve adherence to intervention protocols, and any procedures for monitoring
adherence (eg, drug tablet return, laboratory tests)
Page 8-10____________
11d Relevant concomitant care and interventions that are permitted or prohibited during the trial N/A
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Outcomes 12 Primary, secondary, and other outcomes, including the specific measurement variable (eg,
systolic blood pressure), analysis metric (eg, change from baseline, final value, time to event),
method of aggregation (eg, median, proportion), and time point for each outcome. Explanation
of the clinical relevance of chosen efficacy and harm outcomes is strongly recommended
Page 10-11____________
Participant timeline 13 Time schedule of enrolment, interventions (including any run-ins and washouts), assessments,
and visits for participants. A schematic diagram is highly recommended (see Figure)
Fig 1____________
Sample size 14 Estimated number of participants needed to achieve study objectives and how it was
determined, including clinical and statistical assumptions supporting any sample size
calculations
Page 11_____________
Recruitment 15 Strategies for achieving adequate participant enrolment to reach target sample size N/A as data come from prescriptions, so no
enrolment._____________
Methods: Assignment of interventions (for controlled trials)
Allocation:
Sequence
generation
16a Method of generating the allocation sequence (eg, computer-generated random numbers), and
list of any factors for stratification. To reduce predictability of a random sequence, details of
any planned restriction (eg, blocking) should be provided in a separate document that is
unavailable to those who enrol participants or assign interventions
Page 11-12_____________
Allocation
concealment
mechanism
16b Mechanism of implementing the allocation sequence (eg, central telephone; sequentially
numbered, opaque, sealed envelopes), describing any steps to conceal the sequence until
interventions are assigned
N/A
Implementation 16c Who will generate the allocation sequence, who will enrol participants, and who will assign
participants to interventions
Page 12 (but note as a cRCT there is no
enrolment/participant assignment).
Blinding (masking) 17a Who will be blinded after assignment to interventions (eg, trial participants, care providers,
outcome assessors, data analysts), and how
Page 6_____________
17b If blinded, circumstances under which unblinding is permissible, and procedure for revealing a
participant’s allocated intervention during the trial
N/A
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Methods: Data collection, management, and analysis
Data collection
methods
18a Plans for assessment and collection of outcome, baseline, and other trial data, including any
related processes to promote data quality (eg, duplicate measurements, training of assessors)
and a description of study instruments (eg, questionnaires, laboratory tests) along with their
reliability and validity, if known. Reference to where data collection forms can be found, if not
in the protocol
Page 12-16_____________
18b Plans to promote participant retention and complete follow-up, including list of any outcome
data to be collected for participants who discontinue or deviate from intervention protocols
NA_____________
Data management 19 Plans for data entry, coding, security, and storage, including any related processes to promote
data quality (eg, double data entry; range checks for data values). Reference to where details
of data management procedures can be found, if not in the protocol
Page 12-13_____________
Statistical methods 20a Statistical methods for analysing primary and secondary outcomes. Reference to where other
details of the statistical analysis plan can be found, if not in the protocol
Page 13-14 & accompanying statistical
analysis plan( SUPP INFO 1)________
20b Methods for any additional analyses (eg, subgroup and adjusted analyses) Page 13-14 & accompanying statistical
analysis plan( SUPP INFO 1)________
20c Definition of analysis population relating to protocol non-adherence (eg, as randomised
analysis), and any statistical methods to handle missing data (eg, multiple imputation)
Page 13-14 & accompanying statistical
analysis plan( SUPP INFO
1)____________
Methods: Monitoring
Data monitoring 21a Composition of data monitoring committee (DMC); summary of its role and reporting structure;
statement of whether it is independent from the sponsor and competing interests; and
reference to where further details about its charter can be found, if not in the protocol.
Alternatively, an explanation of why a DMC is not needed
Page 6
21b Description of any interim analyses and stopping guidelines, including who will have access to
these interim results and make the final decision to terminate the trial
No interim analyses._____________
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Harms 22 Plans for collecting, assessing, reporting, and managing solicited and spontaneously reported
adverse events and other unintended effects of trial interventions or trial conduct
N/A
Auditing 23 Frequency and procedures for auditing trial conduct, if any, and whether the process will be
independent from investigators and the sponsor
N/A, but see p12 for details of internal pilot
process involving thresholds for start of
main trial_____________
Ethics and dissemination
Research ethics
approval
24 Plans for seeking research ethics committee/institutional review board (REC/IRB) approval Page 20
Protocol
amendments
25 Plans for communicating important protocol modifications (eg, changes to eligibility criteria,
outcomes, analyses) to relevant parties (eg, investigators, REC/IRBs, trial participants, trial
registries, journals, regulators)
Page 19-20
Consent or assent 26a Who will obtain informed consent or assent from potential trial participants or authorised
surrogates, and how (see Item 32)
Page 19-20
26b Additional consent provisions for collection and use of participant data and biological
specimens in ancillary studies, if applicable
N/A
Confidentiality 27 How personal information about potential and enrolled participants will be collected, shared,
and maintained in order to protect confidentiality before, during, and after the trial
Page 19-20____________
Declaration of
interests
28 Financial and other competing interests for principal investigators for the overall trial and each
study site
Page 21_____________
Access to data 29 Statement of who will have access to the final trial dataset, and disclosure of contractual
agreements that limit such access for investigators
Page 20___________
Ancillary and post-
trial care
30 Provisions, if any, for ancillary and post-trial care, and for compensation to those who suffer
harm from trial participation
N/A
Dissemination policy 31a Plans for investigators and sponsor to communicate trial results to participants, healthcare
professionals, the public, and other relevant groups (eg, via publication, reporting in results
databases, or other data sharing arrangements), including any publication restrictions
Page 20_____________
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31b Authorship eligibility guidelines and any intended use of professional writers N/A____________
31c Plans, if any, for granting public access to the full protocol, participant-level dataset, and
statistical code
N/A
Appendices
Informed consent
materials
32 Model consent form and other related documentation given to participants and authorised
surrogates
SUPP INFO 2 AND 3
Biological
specimens
33 Plans for collection, laboratory evaluation, and storage of biological specimens for genetic or
molecular analysis in the current trial and for future use in ancillary studies, if applicable
N/A
*It is strongly recommended that this checklist be read in conjunction with the SPIRIT 2013 Explanation & Elaboration for important clarification on the items.
Amendments to the protocol should be tracked and dated. The SPIRIT checklist is copyrighted by the SPIRIT Group under the Creative Commons
“Attribution-NonCommercial-NoDerivs 3.0 Unported” license.
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