Quality Improvement Strategies for Antibiotic Prescribing
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Transcript of Quality Improvement Strategies for Antibiotic Prescribing
Quality Improvement Strategies for Antibiotic Prescribing
Sumant Ranji, M.D.February 16, 2005
“Closing the Quality Gap”• Based on subject areas identified in 2003 Based on subject areas identified in 2003
IOM report, “Transforming Health Care IOM report, “Transforming Health Care Quality”Quality”
• Identifying activities that increase the rate increase the rate of use of practices that are known to be of use of practices that are known to be effectiveeffective
• Synthesis of QI strategies across diseases Synthesis of QI strategies across diseases and topic areasand topic areas
Definitions• Quality Gap: difference between observed Quality Gap: difference between observed
processes/outcomes and those achievable based on processes/outcomes and those achievable based on current knowledgecurrent knowledge– Due to deficiency that could be addressed by health care systemDue to deficiency that could be addressed by health care system
• Quality improvement strategy: any intervention aimed at Quality improvement strategy: any intervention aimed at reducing the quality gap for representative patientsreducing the quality gap for representative patients– Should attempt to improve care for broad group of patientsShould attempt to improve care for broad group of patients– May involve patient-, provider-, or system-level changesMay involve patient-, provider-, or system-level changes
• Quality improvement target: outcome/process/structure Quality improvement target: outcome/process/structure the strategy is intended to influencethe strategy is intended to influence
Antibiotic prescribing: background• Majority of prescriptions in US are for acute
respiratory infections (ARI’s)– 41 million prescriptions in 1998
• 55% of prescriptions for ARI’s are unnecessary
• Successes and failures during 1990’s– Significant decline in prescribing overall
• Especially among children• Inappropriate script rate still >40% for common conditions
– Marked increase in use of broad-spectrum agents• Quinolones, macrolides, 2nd/3rd gen cephalosporins, others
Quality of prescribing• Quality Gap:Quality Gap:
– Unnecessary prescribing of antibiotics for Unnecessary prescribing of antibiotics for non-bacterial illnessesnon-bacterial illnesses
– Unnecessary use of broad-spectrum Unnecessary use of broad-spectrum antibiotics where narrow-spectrum agents are antibiotics where narrow-spectrum agents are effectiveeffective
• Quality improvement target:Quality improvement target:– Rate of antibiotic prescribing for non-bacterial Rate of antibiotic prescribing for non-bacterial
diseasesdiseases– Frequency of use of broad-spectrum agentsFrequency of use of broad-spectrum agents
Quality Improvement Strategies
• Provider Education• Audit and Feedback• Provider Reminders• Facilitated relay of clinical data to providers• Patient Education• Patient self-management• Patient reminders• Organizational change• Financial and regulatory incentives
Kleinman et al, 1999
Theoretical Framework for ABX prescribing
Patient Factors-sociodemographics-past experiences-expressed expectations-reported symptoms-illness severity
Clinician Factors-sociodemographics-training/specialty-knowledge-judgment and heuristics-perceived patient expectations
System Factors-practice setting-health plan features-visit and pharmacy copay-patient enabling systems-formularies/restrictions-pharmaceutical detailing
Clinician's Decision to Prescribe
Antibiotics
Quality Improvement Strategies:Prescribing specific
• Patient-directed:– Education– Self-management (delayed prescriptions)– Financial and regulatory incentives
• Copayments
• Providers – Education by different modalities– Audit and feedback of prescribing practices– Financial and regulatory incentives
• Capitation, restricted formularies
• Combinations of above strategies
Research questions• Which QI strategies reduce antibiotic prescribing for Which QI strategies reduce antibiotic prescribing for
acute non-bacterial illnesses?acute non-bacterial illnesses?– Are particular QI strategies more effective for certain target Are particular QI strategies more effective for certain target
conditionsconditions?– Are these strategies safe for patients?
• Effects on health services utilization, clinical outcomes, satisfaction– What are the consequences of these strategies for public health
and the health care system?• Effects on antimicrobial resistance, costs of prescribingEffects on antimicrobial resistance, costs of prescribing
• Which QI strategies are most effective in improving the selection of recommended antibiotics?– Subtopics as above
Inclusion/Exclusion Criteria• Topic
– Acute outpatient illnesses• Major contributor to problem• Different theoretical model for inpatient prescribing
• Study design:– Evaluate a QI strategy– RCT, quasi-RCT, CBA, or ITS
• Outcomes – Measurement of antibiotic prescribing (overall or selection)– Antimicrobial resistance, disease outcomes, costs of prescribing,
health services utilization, satisfaction with care: only abstracted if study also measured prescribing
A priori hypotheses• Publication bias
– Smaller, non-randomized trials will have greater effects• Effect of baseline prescribing rate
– Studies done in populations where over-prescribing/poor selection is common will have greater effects
• Targeting of specific diseases– Studies targeting prescribing for specific diseases will be more
effective than those targeting a variety of conditions or general ABX prescribing
• Multifaceted strategies– As with prior research, studies using multiple QI strategies will
be more effective than those using a single strategy• Intensity of intervention
– Studies using interventions repeated over time will be more effective
Search Strategy EPOC537 citations
549 citations
167 articles
ABX prescription34 articles
(41 comparisons)
54 articles(74 comparisons)
ABX selection25 articles
(33 comparisons)
Hand Search12 citations
382 title exclusions
93 full text exclusions
Analysis
• Measured outcomes– ABX prescribing:
• % visits at which patient received ABX prescription• Prescriptions per person-year• Prescriptions per provider
– ABX selection:• % of total prescriptions written for recommended agent• % compliance to clinical guideline for prescribing• Prescriptions for recommended/nonrecommended ABX per
person• Prescriptions for recommended/nonrecommended ABX per
provider
Analysis• Quantitative
– N=31 for ABX prescribing, N=19 for ABX selection– Meta-regression: planned but failed…– Random effects meta-analysis
• However, extreme heterogeneity (I2 >90%)– Median effects semi-quantitative analysis
• Limitations: no weighting by sample size/variance• Necessitates stratified analyses• Does allow preservation of natural study units
• Qualitative– N=10 for ABX prescribing, N=14 for ABX selection– Systematic review format, complementary to above
Key Findings(a work in progress)
• Overall effectiveness of QI strategies– Possible benefit of self-management
• Variable methodologic quality of studies
• No benefit from more intense interventions
• Possible benefit of multifaceted strategies
Results: studies suitable for quantitative analysis
• ABX prescription (N=31)– 8 US, 23 non-US– 26 target prescribing for ARI’s– 18 RCT, 13 CBA
• ABX selection (N=19)– 3 US, 16 non-US– 12 target choice for ARI, 7 for UTI– 7 RCT, 12 CBA
Study quality• Failure to properly document intervention
– Rationale for study methodology not explained– Key study components described inadequately
• Duration and intensity of intervention– Short follow-up– Minimal reporting of outcomes beyond prescribing
• Failure to report key data– e.g. number of patients in study
• Inappropriate statistical analyses– Unit of analysis errors– Lack of accounting for temporal trends in prescribing
Overall results
• QI strategies overall beneficial
– Prescribing: Median reduction of 9.0% (IQR -16.6% to -3.4%) in prescribing of ABX when not indicated
– Selection: Median increase in prescribing of recommended ABX of 13.8% (IQR 4.6% - 19.7%)
Comparative effects on ABX prescribingQI Strategy Median effect WITH
strategy[IQ range]
Median effect WITHOUT strategy
[IQ range]
Provider Education alone
-7.9%[-16%,-8%]
N=9
-10.0%[-17%,-4%]
N=22
Patient Education alone
-12.0%[-17.8%, -8.8%]
N=4
-8.6%[-14.8%,-4.8%]
N=27
Audit and Feedback alone
-12.0%[-20.0%,-6.9%]
N=7
-8.3%[-16.4%,-6.7%]
N=24
Provider education and audit/feedback
-14.0%[-26.0%, -12.0%]
N=5
-8.3%[-16.4%,-6.7%]
N=26
Self-management -26.0%[-46.7%,-15.0%]
N=5
-8.3%[-16.4%,-6.7%]
N=26
Comparative effects on ABX selectionQI Strategy Median effect WITH
strategy[IQ range]
Median effect WITHOUT strategy
[IQ range]
Provider Education alone
16.3%[7.8% - 24.3%]
N=10
6.5%[3.8% - 15.6%]
N=9
Provider and patient education
20.3%[13.4% - 27.1%]
N=2
12.0% [4.0% - 15.8%]
N=17
Provider education and
audit/feedback
4.0%[3.8% - 12.0%]
N=5
16.0%[6.9% - 25.4%]
N=13
Median effect on Prescribing Stratified by study size and design
Design characteristic
Median effect[IQR]
(sample size)
Lower 2 quartiles -13.8%[-17.8% to -5.4%)
(N=14)
Upper 2 quartiles -7.8%[-12.5% to -6.3%]]
(N = 17)
RCT -8.6%[-12.0% to -5.3%
(N = 13)
Non-RCT -9.5%[-15.9% to -7.2%]
(N = 18)
Publication Bias
• Larger effects among smaller trials
• Less effect of study design type
Baseline prescribing rate
• Prescribing studies:– Would expect that studies with high baseline
prescribing rate may show larger effects– Not found in our sample, but skew issues
• Selection studies:– Expect baseline low compliance to correlate
with higher effects– Also not demonstrated
Targeting of specific diseases
• Hypothesize that studies targeting prescribing for specific conditions may be more likely to show effects
• Not found in our analysis for either prescribing or selection studies
• Confounding by sample size?
Multifaceted strategies
• Previous work (DM) did not reveal benefit for multifaceted strategies
• Possible benefit in prescribing studies– Median effect -12.0% (IQR -16.0% to -1.7%) for multifaceted
studies (N=15)– Median effect -8.8% (IQR -16.9% to -5.9%) for single-faceted
studies (N=16)
• Selection studies: single-faceted studies all provider education only; no difference seen
Repeated Interventions
• Complicated by poor description of study details
• No difference found for either prescribing or selection studies
Other outcomes• Antimicrobial resistance
– Only assessed in 2 studies; both showed no effect, but short duration of followup
• Health services utilization– Assessed in 6 studies in prescribing group– No increase in return visits, hospitalizations seen– ? Effect on duration of illness
• Patient satisfaction– Assessed only in delayed prescribing studies (N=6)– No significant effect seen
• Costs of prescribing– Assessed in 7 studies; 15-30% reductions seen, but in short-term (<6
months) only– Mostly non-US
Conclusions and Hypotheses• No clear benefit for any single QI strategy
• Possible exception of patient self-management (delayed prescribing)
• Poor quality of studies limits interpretation of results
• However, overall trials are effective at reducing prescribing and improving selection
• Future analyses:– Stratified analyses: effects of QI strategies in relation to sample
size, baseline prescribing, study design, disease targeting, country
• Preliminarily no major effects– Nonparametric (rank-sum) tests for differences between groups– Further attempts at meta-regression
• Common outcome measure for dichotomous and continuous studies
Thanks• Stanford
– Vandana Sundaram– Robyn Lewis– Kathy McDonald– Doug Owens
• UCSF– Ralph Gonzales– Mike Steinman
• Ottawa– Kaveh Shojania