Barriers to managing chronic illness among urban households in coastal Kenya

Journal of International Development

J. Int. Dev. 21, 271–290 (2009)

Published online 4 February 2009 in Wiley InterScience

(www.interscience.wiley.com) DOI: 10.1002/jid.1552

BARRIERS TO MANAGING CHRONICILLNESS AMONG URBAN HOUSEHOLDS

IN COASTAL KENYAy

THOMAS PORTER1*, JANE CHUMA2 and CATHERINE MOLYNEUX2,3

1Oxford Deanery Public Health, Oxford, UK2Kenya Medical Research Institute (KEMRI) Wellcome Trust Research Programme, Kilifi, Kenya

3University of Oxford, Oxford, UK

Abstract: The burden of chronic illnesses is rising throughout the world but information on

barriers to managing such diseases in developing countries is scarce. Qualitative data from

focus group discussions and interview transcripts from a longitudinal study involving

22 households in urban, coastal Kenya were analysed. Themes around barriers to chronic

illness care were identified and a conceptual framework developed which described relation-

ships between these themes. The main barrier to chronic illness management was the cost of

care. Other barriers identified were patient knowledge and beliefs, stigma, quality and trust in

providers and long care pathways. Household resilience was adversely affected by chronic

illness, further reducing households’ ability to cope with illness. Policy options to address the

barriers identified are discussed. Copyright # 2009 John Wiley & Sons, Ltd.

Keywords: chronic illness; barriers; coping strategies; household; Kenya; policy; healthcare

1 INTRODUCTION

The burden of chronic illnesses is rising in developing countries (Strong et al., 2005).

Although there is a paucity of epidemiological data for sub-Saharan Africa (Mufunda et al.,

2006), estimates for non-communicable diseases (NCDs) may be used as a proxy for

*Correspondence to: Dr Thomas Porter, Specialist Registrar in Public Health, Oxford Deanery Public Health,Richards Building, Old Road Campus, Oxford, OX3 7LG, United Kingdom. E-mail: [email protected] paper is published with the permission of the Director of KEMRI. Thomas Porter carried out the qualitativeand quantitative analyses presented in this paper, and wrote the paper draft. Catherine Molyneux and Jane Chumaconducted the original ATP study. Catherine Molyneux gave comments and corrections on the draft. ThomasPorter received a salary from the Oxford Deanery Public Health programme, with travel and accomodation costsfor the study paid for by a stipend from the University of Oxford Global Health Science MSc programme. Theoriginal study was funded through a Fellowship awarded to Catherine Molyneux by the Wellcome Trust, UK andsupported by the Kenya Medical Research Institute. The authors have no declared competing interests.

Copyright # 2009 John Wiley & Sons, Ltd.

272 T. Porter et al.

chronic illness, although this is not without problems (the NCD definition includes acute

illnesses such as appendicitis and excludes chronic illness due to infection, such as

tuberculosis and HIV). In 2002 NCDs were estimated to account for 18 per cent of total

disability-adjusted life years (DALYs) in the region and by 2020 this is projected to have

nearly doubled to 32 per cent (Murray and Lopez, 1997; WHO, 2002a). In Kenya NCDs

accounted for 20 per cent of total DALYs in 2002 (WHO, 2002b). In addition to the

suffering associated with chronic illness, the financial burden is high (Su et al., 2006;

WHO, 2005).

The rising incidence and prevalence of chronic illnesses is partly due to population

expansion and ageing but is also the consequence of increasing prevalence of risk factors

and behaviours for long-term illnesses, such as urbanisation (Harpham and Stephens, 1991;

Wang et al., 2005). Other factors are likely to become increasingly prominent, such as the

use of therapies with the potential to delay mortality in some illnesses (e.g. antiretroviral

therapy in HIV).

The majority of health systems in developing countries were designed to manage acute,

especially infectious, illnesses (Wagner et al., 1996; WHO, 2002c), with little literature on

managing chronic illness in resource-poor settings (Unwin et al., 2001; El Ansari, 2006).

The Chronic Care Model (CCM) suggested that optimal chronic disease management

would result from success in six areas: community resources and policies; healthcare

organisations; self-management support (assisting patients and families to manage their

illnesses day-to-day); delivery system design; decision support; and clinical information

systems (Wagner, 1998; Bodenheimer et al., 2002). Whilst the CCM has generally been

successful where implemented (Tsai et al., 2005; Adams et al., 2007), its reliance on

information systems and motivated patients able to access care, makes it primarily suited

to developed countries. In 2002 the World Health Organisation published the innovative

care for chronic conditions (ICCC) framework, partly based on the CCM, which

recognised broader determinants including local community involvement and national

leadership and policies, making it more suitable for use in developing countries (WHO,

2002c).

There are few data available on the barriers to chronic illness management at the

household level in resource-poor settings, with most papers focusing on supply-side (i.e.

healthcare organisation) issues (e.g. Birbeck, 2000; Furber et al., 2004). The household

unit is important because it is at this level that most costs are ultimately borne and decisions

about treatment-seeking made (Berman et al., 1994). Poor management of long-term

illnesses, in comparison with that of acute illnesses, has a greater potential for prolonged

and ongoing impact on families’ livelihoods; a clearer understanding of the barriers to

management would enable the development of targeted interventions to improve chronic

illness management in these settings.

This paper presents data from a larger study which investigated household illness-related

treatment-seeking behaviour, costs, coping mechanisms and impoverishment (Chuma

et al., 2006, 2007; Molyneux et al., 2007, and papers in this issue by Chuma et al., and

Molyneux et al.). The aims of the current analysis were to describe household management

of chronic illnesses in urban Kenya and barriers to successful management. At the

household level, these were generally barriers to accessing care, and to self-management

by the patient. A comparison of the results with the existing literature in this field is

presented, along with their applicability to other settings. Relevant proposals in a recent

strategy document by the Government of Kenya, the National Health Sector Strategic Plan

(NHSSP), are reviewed in light of the present findings.

Copyright # 2009 John Wiley & Sons, Ltd. J. Int. Dev. 21, 271–290 (2009)

DOI: 10.1002/jid

Barriers to Managing Chronic Illness in Kenya 273

2 METHODS

2.1 Study Setting and Design

The original study was carried out in 2003/2004 in Kilifi District, the second poorest

district in Kenya, to investigate households’ ability to pay (ATP) for healthcare in both

urban and rural environments, initially focusing on costs for malaria treatment. It included

two large cross-sectional surveys of 870 adults; focus group discussions (FGDs); health

provider interviews; and an in-depth longitudinal study involving over 60 households. The

study was approved by local, national and international research ethics committees

(Chuma et al., 2007).

As part of the ATP study, a longitudinal study of 31 households, and 12 FGDs, took place

in the urban setting of Mtwapa. Mtwapa is a rapidly expanding town on the Kenyan coast,

10 km north of Mombasa, with a population of �70 000. The town is served by three

government hospitals, two government health centres, and one government dispensary.

There are also numerous private pharmacies, clinics and hospitals, as well as small general

shops selling basic medication. Although the area is considered urban, in practice some

neighbourhoods are more characteristic of rural settlements.

Households were selected for the case study through the cross-sectional survey, based

on their socioeconomic status (SES, derived from monthly per capita expenditure and

asset ownership), and average monthly health expenditure. Households were

categorised into low, medium and high SES; and low, medium and high health

expenditure. Four groups were eligible for the case study (low SES/low costs; low SES/

high costs; high SES/low costs and high SES/high costs), on the basis that these

households would contribute most to emerging theories in the original study. This list

was further refined based on fieldworkers’ estimation of which households would be

most likely to co-operate with the long-term study and complete follow up. The presence

or absence of chronic illness in the household was not used in selection. Case study

households were visited on at least five occasions by the same trained local fieldworker,

with specific topics explored at each visit (historical timeline; family tree and assets;

social resources; expenditure diaries; changes over follow-up period). Where

households had reported a chronic illness this was also discussed in detail. Consent

was sought for each household visit, with participants free to leave the study at any

point. 29 of the 31 households completed follow-up; no reason was given by the two

which withdrew consent during the study. Illness diagnoses were checked by the

fieldworker with patient-held health records when available. Detailed monthly

household expenditure data were noted by hand for February, March, May, June,

July and August 2004. Direct illness costs (expenditure on seeking and obtaining

treatment, including special food and transport) were recorded. Interviews were semi-

structured and conducted in the local language, with fieldworkers making detailed

handwritten notes in English following each visit. Interview notes and expenditure

summaries were later typed and stored electronically. The FGDs were also carried

out by trained fieldworkers, with six male-only and six female-only groups. The

initial FGDs were based around clinical vignettes, with participants asked how they

would react if members of their household developed specific symptoms. These

FGDs were followed by open-ended discussions addressing themes from the initial

FGDs in more detail, especially treatment-seeking behaviour and household coping

mechanisms.


DOI: 10.1002/jid


2.2 Data Analysis for This Paper

This analysis was conducted at the KEMRI-Wellcome Trust Collaborative Programme,

Kilifi, between April and July 2007. Data generated through the urban household case

studies and FGDs were analysed.

Case study and FGD transcripts were read through in their entirety a number of times, to

identify initial coding categories, specifically concerning chronic illnesses and related

treatment-seeking behaviour. Manual coding of content suggested a number of emergent

themes, with analysis focusing in particular on perceived barriers to accessing treatment

and/or self-management of these conditions. As links between themes were explored a

conceptual framework was developed iteratively, based on these links. The same coding

schemawas used for both the case studies and FGD transcripts, with themes identified from

both sources. ‘Chronic illness’ was defined here as any which had been symptomatic for at

least 3months, or which had been diagnosed at least 3months prior. ‘Management’ of

chronic illness was taken to include any actions, opinions or feelings expressed by a

household member, acquaintance or health professional, concerning chronic illness.

Management was considered ‘successful’ if a condition was described as stable with

symptoms routinely controlled (through active monitoring if necessary) during the follow

up period.

Of the 29 households completing follow-up, 22 reported at least one chronic illness

during the follow-up period. If no expenditure was apparent on a reported chronic illness

during the six months analysed, the reasons for this were explored.

For each household total expenditure, total direct health expenditure, and chronic illness

expenditure were calculated for each of 6months during the follow-up period, along with

coefficients of variation to assess between-month fluctuation. In addition, expenditure data

were analysed to determine if any household’s total direct health expenditure or chronic

illness expenditure exceeded 10 per cent of its total expenditure in any month, one measure

of ‘catastrophic’ expenditure (Russell, 2004). At catastrophic levels, households are more

likely to sell assets, acquire debts and reduce consumption of necessities such as food.

3 FINDINGS

3.1 Household Characteristics and Illness Symptoms

A summary of the case study households is given in Table 1. Nearly two-thirds of

households (63.6 per cent, 14/22) had a household member educated to secondary school

level or above, a similar proportion to those in the original survey (65.0 per cent, 372/572).

The illness names given by householders usually directly matched a biomedical term,

although sometimes culturally-specific terms were used. The commonest chronic illnesses

were bone/joint pains, asthma and hypertension (Tables 1, 2).

3.2 Conceptual framework for management of chronic illnesses (Figure 1)

A conceptual framework linking the themes identified in content analysis is presented in

Figure 1, which includes household responses to chronic illnesses, barriers to these

responses, outcomes and feedback mechanisms. The remaining findings are presented

according to this structure, with excerpts from fieldworker and FGD notes where relevant.


DOI: 10.1002/jid

Table 1. Case study household characteristics

Household (HH) HH members with chronic illness

HH code Number of

HH members

Highest

educational

level

Members with

chronic illness

Gender Age or age

range (years)

Chronic illnesses

A 6 College 2 F 6 Asthma

F 36 Stress/anxiety

B 8 Secondary 2 M 21 Asthma

F 2 Eye problem

C 6 College 2 F 35–50 Stomach ulcer, knee pain

F 50–80 Hypertension

D 10 Primary 1 F >60 ‘Chunu kuluma’ (waist ache)

E 7 Primary 1 F 50–80 Hypertension, ‘chunu kuluma’

F 7 Secondary 1 F 54 Diabetes mellitus, hypertension

G 8 Primary 2 M 75 Blind, diabetes mellitus,

hypertension, ‘chunu kuluma’

F 40 ‘Chunu kuluma’, ‘chala cha

mdudu’ (finger infection)

H 5 College 1 M 30 Epilepsy

I 7 Primary� 2 F 12 Meningitis complications

F 32 Stomach ulcers; breast lesion

J 3 College 1 M 35–50 Epilepsy

K 5 Secondary 1 M 57 Leg trauma

L 11 Secondary 2 M 46 Heart disease, stomach ulcers

M 26 Stress/anxiety

M 9 Secondary 2 M 23 Asthma

F 15 Gynaecological growth

N 13 Primary 1 M 18–35 Developmental delay

O 11 Primary� 1 F 30 Goitre

P 4 Secondary� 1 F 36 Tuberculosis

Q 6 Secondary 1 M 1 Asthma

R 6 Secondary 1 F 10–18 Down’s syndrome

S 5 Koran School 1 F 50–80 Mental illness

T 13 College 1 M 12 Asthma

U 12 Secondary 2 F >80 Hypertension, ’Maguu kuuma’

(leg pain)

M 20 Tuberculosis

V 13 Primary� 1 F 14 Epilepsy

Mean 8 1.4 36

�left before finishing.


3.3 Household Responses (Box A, Figure 1)

Responses to chronic illness ranged from non-treatment to visiting multiple health

providers. Visiting a single, appropriately qualified, provider was unusual. Among those

not seeking treatment, some were delaying treatment as long as possible while others did

not intend to seek help.

Case study Household I: ‘The breast swelled and ached, and when she tried to

squeeze it some pus and blood come out. . . Since the problem started she has not seen

a doctor for medication because she has no money to go to hospital. Instead, when

she experiences the pain she boils water and sponges it. . .’


DOI: 10.1002/jid

Table 2. Frequency of chronic illnesses in case study households

Chronic illness Frequency

Bone/joint pains (including knee pain, ‘chunu kuluma’,

leg trauma, ‘maguu kuuma’)

7

Asthma 5

Hypertension 5

Epilepsy 3

Stomach ulcers 3

Diabetes mellitus 2

Eye problems (including non-specific eye problem and blindness) 2

Stress/anxiety 2

Tuberculosis 2

Other (breast lesion, ‘chala cha mdudu’, developmental delay,

Down’s syndrome, goitre, gynaecological growth, heart disease,

mental illness, neurological complications)

9

Total 40


Individuals often visited a number of different providers for the same problem, e.g.

starting at a pharmacy then attending a private clinic, or seeking a second opinion after an

initial diagnosis. In other cases, private providers would be visited in the first instance, even

if they were more expensive than government facilities. Traditional healers were also

commonly attended, more so in the semi-rural areas of Mtwapa. The majority of visits to

health providers occurred once a patient had developed symptoms; it was rare for

preventive management to be sought.

Figure 1. Conceptual framework for management of chronic illnesses: household responses tochronic illness, barriers to household responses, outcomes and feedback mechanisms


DOI: 10.1002/jid


3.4 Modifiers/Barriers to Household Responses (Box B, Figure 1)

A summary of how specific barriers contributed to household response is shown in Table 3,

with more detail below.

3.4.1 Anticipated cost

Cost was a very important factor underlying households’ responses, evidenced by 16/22

households which employed at least one cost-prevention or cost-reduction strategy. These

strategies were: not seeking medical advice (cost-prevention); seeking symptomatic

instead of preventive treatment, for example in asthma; not following or delaying advised

treatment; or attending a non-specialist facility (cost-reduction strategies). Cost-

management strategies (such as selling assets or going without food) were also widely

used. Since households usually made an estimate of treatment costs before seeking care,

the anticipated cost was often as important as the provider fee, and would take into account

transport and time off work. For tuberculosis (TB) and HIV/AIDS user fees were waived,

meaning patients were more likely to seek and receive treatment:

Case study Household P: ‘I thank God TB treatment is free, so I don’t spend much

on it’

Ironically, visiting multiple providers was often the result of cost-reduction strategies

(e.g. visiting a cheap provider but receiving inadequate treatment, necessitating further care;

or seeking a second opinion to obtain a diagnosis associated with less costly management).

3.4.2 Patient knowledge and beliefs

Varying levels of patient knowledge about diseases were found between FGD participants

and for different conditions.

FGDParticipant: ‘All the dust you inhaled went inside your lungs and this can bring

cough problems. That’s when people can say you have TB. And also smoking. . .Even a lady can get TB. Sometime back my cousin got TB and she used to cut Tano

(cutting or clearing the forests). . . And after about 4 years she suffered from TB and

all this was caused by the work and smoke (burning the cleared fields)’.

FGD Participant: ‘That man used to cough and is now serious. . . he needs to go tohospital for tests for TB (sputum). The doctor will know and treat’.

Some households seemed to be unaware that chronic illnesses can sometimes be

managed preventatively as well as acutely, indicating that avoiding preventive care could

result from a lack of knowledge as well as a deliberate cost-prevention strategy. A number

of households had strong traditional beliefs which caused them to seek healers or herbs for

certain illnesses, often regardless of cost.

Case study Household L: ‘Traditional healers are given first priority in the

household because he says experience has taught him that traditional medicine is

more effective than clinical medicine’.

Traditional beliefs were more pronounced among residents in the semi-rural areas of

Mtwapa, and there were suggestions from the FGDs that the use of healers was declining in

more urban areas.


DOI: 10.1002/jid

Table

3.

Specificeffectsofmodifiers/barriers(BoxB,Figure

1)onhousehold

responses(BoxA,Figure

1)

Household

response

Modifiers/barrierswhichmay

contribute

toresponse

Anticipated

cost

Patientknowledge

andbeliefs

Stigma

Provider

quality

Trust/perceived

quality

Longcare

pathway

Non-treatment

Notseekingmedical

adviceat

all

**

Delay

treatm

ent-seeking

*

Treatment-seeking

Visitmultiple

providers

**

**

*

Visitexpensiveprovider

only

**

*

Visittraditional

healer

**

**

Symptomatic

treatm

entonly

**

Attendingnon-specialistfacility

*

Visitsingle,appropriateprovider

*

Copyright # 2009 John Wiley & Sons, Ltd. J. Int. Dev. 21, 271–290 (2009

DOI: 10.1002/jid


)


3.4.3 Stigma

Individuals who thought they may have TB were sometimes deterred from visiting a health

facility for diagnosis because they feared being diagnosed with HIV/AIDS at the same

time. This fear seemed to result from a recognition that some of the symptoms of TB and

HIV can be similar and was demonstrated in an FGD and one of the case study households.

FGDFacilitator: ‘Now, why is it that the young people are afraid to visit the hospital

when they have TB’? Participant 2: ‘They are afraid depending on what one is

suffering from’. Participant 1: ‘For example if a man goes to the hospital with his

wife and has tests done, good if TB is found but if it’s the disease of nowadays

(AIDS) they become ashamed and that’s the reason they don’t visit the hospital’.

In household H there was also evidence of community stigma associated with epilepsy.

There was no evidence of stigma for other chronic illnesses in the study.

3.4.4 Provider quality

Households and FGD participants cited difficulties encountered with providers, including

long queues, unhelpful staff and slow service at government hospitals, and a lack of

common drugs at government dispensaries. Traditional healers could apparently

sometimes expose patients to additional risk:

FGD Participant: ‘Others also get [HIV] by bad luck - for example if one goes to a

mganga (local healer) and she uses a razor which she cuts on you and has been used

on another person, one can get infected’.

3.4.5 Trust/perceived quality

Trust seemed to influence householders’ choice of provider, reinforcing some relationships

and curtailing others. A lack of trust was suggested in some cases where individuals

visited multiple providers for a set of symptoms, only to be given the same diagnosis at

each:

Case study Household F: ‘Three years ago the spouse found herself at [a private

hospital]. She was suffering from high blood pressure and diabetes and she knew this

after undergoing some tests. . . She did not believe she had high blood pressure. Thismade her seek another doctor where she was also diagnosed with the same disease’.

Trust was also linked to patients’ previous clinical outcomes, reinforced after a positive

experience.

3.4.6 Long care pathways

For tuberculosis it was found that the official treatment pathway for patients wishing to use

government facilities was complex and required visiting three health facilities, often with

associated transport costs:

FGD Participant 1:‘One goes to the Coast General Hospital first for a picture (X-

ray) and then referred to Port Reitz’. Participant 2: ‘At Port Reitz you’ll get treated

then you’ll be referred to the nearest hospital near your home to get drugs. Like here

in Mtwapa one is referred to get them at Shimo la Tewa’


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3.5 Outcomes (Box C, Figure 1)

3.5.1 Clinical

Following a single episode of treatment seeking, most patients’ symptoms were addressed

either temporarily, or not at all—few gained long-term control of their chronic illness. For

individuals who could not afford or delayed definitive treatment, disease progression was a

possibility.

Case study Household K: ‘November this year, it was very hard on me. I wouldn’t

walk, hold my stick or do anything. I was extremely sick. . .[then, following admission

to hospital for 3 days, shorter than advised]. . . I feared the bill would be too enormous

for the household to pay! And I come back home still very sick. . . [later in the year,

described by the fieldworker] Walking is now a serious problem. . . in fact this

problem is the main reason why the household head can’t/isn’t earning nowadays’

3.5.2 Costs of chronic illness

A summary of household expenditure (from expenditure diaries kept by the households),

including chronic illness expenditure, is given in Table 4. Chronic illnesses contributed, on

average, to just under one fifth (18.3 per cent, 104/569KSh) of total health expenditure in

households with chronic illness. Interestingly, whilst in 14 households total direct health

expenditure was catastrophic during at least one month in the study period, only in

4 households was this due to chronic illness alone. Pharmacies and private clinics were

responsible for the majority of chronic illness spending (34.7 and 34.2 per cent,

respectively), with little spent at government dispensaries (0.6 per cent) (data not shown).

There was also qualitative evidence of significant indirect illness costs associated with

chronic illness, such as time off work.

There was considerable month-by-month fluctuation in total expenditure, health

expenditure and chronic illness expenditure. Households broadly fell into four categories

with respect to the latter (Figure 2); interestingly only one household, U, showed a pattern

of regular chronic illness expenditure (category c). In households where no expenditure

was made during the formal diary period, the reasons for this were explored in the

interviews (Table 5); for example, in some cases, families related that chronic illness costs

had occurred, but outside the formal diary period.

3.5.3 Household vulnerability and resilience implications

Both direct and indirect costs associated with illness and treatment-seeking behaviour reduced

the resilience of households to face future illness episodes and other crises. For example, some

households were forced to sell assets or go without food in order to pay for treatment:

Case study Household F: ‘At the hospital she paid 800KSh from personal savings

because the husband works and from tenants. This affected the family financially

because. . .sometimes they were going without food’.

Others found difficulty working due to incapacitation. Social assets were often

diminished if debts taken to pay for treatment could not be paid back and illnesses were

sometimes responsible for breakdowns in family relationships:

Case study Household H: ‘The husband suffers from kifafa (epilepsy). During this

time he had no money to treat his illness and therefore after seeing the wife’s savings


DOI: 10.1002/jid

Table

4.

Financial

summaryofcase

studyhouseholdsFebruary–August

2004(excl

April)

Household

Totalexpenditure

Healthexpenditure

Chronic

illnessexpenditure

Catastrophic

costs�

Monthly

average

(KSh)

Coefficient

ofvariation

(%)

Monthly

average

(KSh)

Coefficient

ofvariation

(%)

%oftotal

expenditure

(mean)

Monthly

average

(KSh)

Coefficient

ofvariation

(%)

%oftotal

expenditure

(mean)

Allhealth

expenditure

Chronic

illness

only

A23638

70

452

159

4.8

3245

0.0

*

B33852

47

1426

140

4.1

314

122

0.7

*

C20853

12

403

144

2.0

382

156

1.9

D6754

42

170

119

2.3

0—

0.0

E7176

17

262

161

3.4

171

245

2.1

**

F10174

15

323

196

4.0

306

210

3.8

**

G5319

18

228

194

4.3

185

242

3.4

**

H15515

47

1136

83

9.2

205

124

1.4

*

I5192

53

19

40

0.4

0—

0.0

J11388

53

446

124

7.2

170

224

1.6

*

K6906

92

295

200

2.1

0—

0.0

L15801

36

266

168

1.2

40

224

0.3

M11435

64

2295

233

11.0

0—

0.0

*

N8803

39

71

160

0.8

0—

0.0

O12956

48

689

148

3.6

333

245

1.9

**

P19427

38

1553

111

7.4

0—

0.0

*

Q10461

26

374

167

3.0

44

239

0.3

*

R24618

65

475

179

4.4

0—

0.0

*

S4987

42

133

81

4.2

0—

0.0

*

T31319

65

1138

117

5.2

75

245

0.1

*

U12187

43

118

121

0.9

60

00.6

V16784

32

248

81

1.5

0—

0.0

Mean(allHH)

14343

44

569

142

4.0

104

194

0.8

Note:Exchangerate

£1¼144KShKenyan

Shillingson1March

2004(O

andA.com,2007).

� catastrophiccostsdefined

hereas

atleast1month

when

directhealthorchronicillnesscostsexceeded

10%

oftotalhousehold

expenditure

(notethiswillnotbeapparentfrom

the

Copyright # 2009 John Wiley & Sons, Ltd. J. Int. Dev. 21, 271–290 (20

DOI: 10.1002


meanfigure

given

inthecolumnto

theleft).

09)

/jid

Figure 2. Household chronic illness expenditure by month, categorised by expenditure pattern


in the house, he decided to use it and tell the wife when she came back. . .He thoughthewas doing the right thing to use the money to get treatment but it changed when the

wife returned. . . and found her money was missing. . . in the end she decided to

[leave]. . . ’

Furthermore, it was not always just the household of the ill individual which became

more vulnerable: it was common for relatives to be asked by the patient to help pay large

treatment bills at short notice.


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Table 5. Reasons for households (HH) reporting chronic illnesses but no associated expenditure

Household Treatment not sought or delayed

Treatment sought Treatment desiredby HH

Treatment not desiredby HH

Costs incurredoutside study

period

Freetreatment

Inabilityto pay

Fear ofrequestingcredit

Previoustreatmentfailure

No symptomsrequiringtreatment

D * *

I * * *

K *

M * *

N *

P *

R *

S * *

V * *


3.6 Feedback Mechanisms (Box D, Figure 1)

There appeared to be a feedback loop between households’ illness responses and outcomes

and the barriers they faced to chronic illness management: in many cases barriers to

successfully managing future illness episodes increased. The cost of care sometimes

impacted on households’ resilience, reducing their ability to afford to pay for future

treatment; and where care was expensive (particularly if multiple providers were attended),

the anticipated cost of future episodes in some cases deterred a timely response. Finally,

clinical outcomes seemed to influence trust in providers in some households, with

increased or reduced trust following a positive or negative experience respectively.

4 DISCUSSION

4.1 Critique of Methods

The majority of studies examining household expenditure and treatment-seeking

behaviour are cross-sectional and more longitudinal studies such as this have been called

for to understand the relationship between treatment-seeking behaviour and long-term

household outcomes (Russell, 2004). Although the sample size was good for the

longitudinal qualitative data, the reliability of the quantitative expenditure data would

increase with a larger study. The generalisability of this latter dataset is also limited by the

selection procedure used for case study households.

The definition for ‘catastrophic’ expenditure used here (direct costs over 10 per cent of

total household expenditure) is widely accepted, although some poorer households would

experience catastrophic spending at levels below 10 per cent and less-poor households may

be able to cushion expenditure above this; an alternative measure may have been more

sensitive (indirect and direct costs over 40 per cent of non-food expenditure) (Xu et al.,

2003). Although only direct cost data were available to be analysed quantitatively here,

there was qualitative evidence of significant indirect costs captured in household


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interviews, consistent with the literature that indirect costs in chronic illness can be large

(McIntyre et al., 2006), often higher than direct (Babu et al., 2002); quantitative analysis of

indirect costs would have been useful to confirm this. The observation that households’

expenditure patterns fell into distinct groups (Figure 2) could have been spurious. For

example, it is possible that most households face catastrophic chronic illness costs from

time to time, even if this was not picked up during the study.

Barriers were identified from the perspective of households and FGD members and as

such (except for cost) were ‘expressed’ or ‘felt’ barriers; this study did not explore whether

these were problems of perception rather than reality. It is also known that the frequency of

self-reported chronic illness often exceeds formally diagnosed illness, since many chronic

symptoms are never reported to health professionals (Bazargan et al., 2005). There are also

likely to be barriers in further areas, especially on the supply-side (e.g. healthcare

organisations), outside the scope of this primarily demand-side study. Compliance with

expenditure diaries was generally good (126/132¼ 95.4 per cent complete), with high

between-month variation unlikely to be the result of measurement error.

The use in some cases of culturally-specific illness labels (e.g. ‘chunu kuluma’) could

make comparisons with other studies and applicability to other settings difficult, but it was

felt that attempting to convert these labels to biomedical diagnoses may be misleading.

Although many of the same barriers to chronic illness care are likely to exist in resource-

poor settings elsewhere, the detail and relative significance of each probably vary between

countries and cultures, so local studies would be needed to assess these and identify

appropriate interventions in each context.

4.2 Cost is By Far the Most Important Barrier

The illness costs observed in this study fit broadly with the general literature on household

health expenditure, with mean total health expenditure of 4 per cent (Table 4) within the

2.5–7 per cent range seen in similar settings (Russell, 2004) and chronic illness costs

contributing to catastrophic expenditure (Su et al., 2006). Costs may escalate as a result of

particular household responses, with the behaviour contributing to this cycle documented

for acute care elsewhere in Kenya (Nyamongo, 2002).

The ICCC framework calls for protection from catastrophic health costs. In many

countries—including Kenya—costs have been found to be ‘regressive’, with the poor

paying a larger proportion of their income on health (Chuma et al., 2007). How easily

households can meet costs is determined in part by their ‘resilience’, a concept related to

‘vulnerability’, encompassing their financial, social and human assets (Russell, 1996). The

present study found that expenditure on chronic illness could affect the determinants of

household resilience, through an erosion of these assets. This implies that, in contrast to

most acute illnesses, the poor management of a chronic illness could potentially affect

resilience over a period of months or years.

4.3 Other Barriers Also Play A Significant Role


The ICCC ideal of patients as ‘active participants in care’ was not observed in this setting.

A lack of awareness of preventive care for many chronic conditions has been found

elsewhere in sub-Saharan Africa (Berhanu et al., 2002), and in Ghana the use of traditional

healers was found to be one form of coping strategy if it was cheaper than biomedicine


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(de-Graft Aikins, 2005), mirroring the responses of some Kenyan households. In Tanzania,

traditional healers were often preferred because they accepted payment ‘in kind’ and

costs for traditional treatment were more likely to be shared by the family (Muela et al.,

2000).

4.3.2 Stigma

HIV-related stigma in patients with suspected tuberculosis has also been seen in other low-

income settings (Ngamvithayapong et al., 2000; Godfrey-Faussett and Ayles, 2003), along

with stigma due to TB alone (Liefooghe et al., 1995), and may be responsible for delayed

presentation of individuals for tuberculosis investigation.

4.3.3 Provider quality and trust

There is circumstantial evidence from this study of under-performing health providers,

causing patients to seek second opinions or visit expensive providers at the outset. The

numbers of government hospitals, dispensaries and health centres in Coast Province are

below the Kenyan average for the population size (Gondi et al., 2006), suggesting this may

partly be due to a lack of capacity.

4.3.4 Long care pathways

Providing management is not delayed by patients visiting a number of different providers

(Pronyk, 2001), siting specialist facilities at a regional referral hospital may actually help

maintain quality of care, although transport costs can still be limiting for the very poor.

4.4 Addressing the Barriers

A recent strategy document, the NHSSP, has proposed widespread changes in the way the

Kenyan health system is organised and funded (Government of Kenya, 2005). Where

applicable, proposals in the NHSSP are discussed in relation to the findings presented here.

4.4.1 Cost

To make it easier for households with chronic illness to cope with the resulting costs, two

main approaches exist: reduce (or even out) the absolute cost of healthcare for chronic

illnesses; or reduce the relative cost of healthcare by increasing household resilience.

(Additionally, increasing access to acute care could have an effect on chronic illness

management—some of the illnesses reported here were likely to have been inadequately

treated acute diseases.)

In recent years user fees have been criticised as disadvantaging the poor, leading to calls

for their abolition (Palmer et al., 2004; McIntyre et al., 2006). In Kenya, user fees were

introduced through a ‘cost sharing’ initiative in 1989, but due to increasingly

heterogeneous costs at health facilities, consultation tariffs were fixed in 2004 at

10KSh and 20KSh at government dispensaries and health centres respectively (Oyaya and

Rifkin, 2003; Pearson, 2005). The results of the present analysis would support the

abolition of user fees for the poorest in society, although without extra funding this risks a

knock-on reduction in the quality or availability of other government health services. The

recent waiver of user fees for HIV/AIDS and TB in Kenya, and the plans set out in the

NHSSP for user fees to be replaced by compulsory National Social Health Insurance Fund

(NSHIF) payments which would be waived for the poorest members of society, are


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encouraging developments. It is implied that chronic illness management would be funded

by the NSHIF for vulnerable members of society, although this is not categorically stated in

the NHSSP. Research into alternative funding mechanisms for healthcare has also been

called for (McIntyre et al., 2006), with health insurance and microeconomic loans

proposed to reduce the economic impact of illness (Sherer, 2004).

The cost of providing care might be reduced through the use of peer-support groups or

trained laypeople. New ‘community owned resource persons’ (CORPs) suggested in the

NHSSP may prove useful, so long as difficulties encountered with community health

worker and Primary Health Care initiatives elsewhere (mainly around adequacy of training

and support), are avoided (Berman et al., 1987; Stekelenburg et al., 2003). Encouraging

responsible self-management could also reduce this bill (WHO, 2002c; Newman et al.,

2004), and given the rapid uptake of mobile phones in Kenya and many other parts of sub-

Saharan Africa (Ovum, 2007), telephone consultations could also have a role in disease

monitoring (Piette et al., 2006), although this may decrease equity by favouring those who

own a mobile phone.

Addressing household resilience is the second approach. Measures to help households

increase or stabilise their income, promote savings, support social networks and increase

equity would have a positive effect on their ability to cope with chronic illness costs, over

the longer term. These measures would require concerted government-wide action; the

NHSSP proposes identifying and providing financial support for vulnerable groups at the

local level, although the details are vague. In Kenya most borrowing is through informal

contacts, such as neighbours or self-help groups, with only 6.5 per cent of borrowers using

banks (Daily Nation, 2007); recent work suggests that community-based organisations

could play a significant role in supporting households coping with illness costs (Molyneux

et al., 2007).


Information asymmetry between patients and providers makes it difficult for patients to

accurately assess the quality of providers and self-manage their condition. Empowered,

knowledgeable patients are particularly important in chronic compared with acute

illnesses; the use of independent consumer education could help in this respect (Mills et al.,

2002). The NHSSP suggestion of regular health promotion is a start, but appears to be

restricted to the elderly and may not be ambitious enough to empower patients to manage

their own diseases. However, proposals to develop a network of CORPs managed at the

village level and the adoption of a ‘human rights’ approach to health are more encouraging,

although again much of the detail of these measures is to be decided. Registering and

regulating traditional healers and medicines may also help patients make a more informed

choice as well as increasing provider quality (see below) (WHO, 2002d).

4.4.3 Stigma

It has been suggested HIV-related stigma is best addressed through community

mobilisation and advocacy, encouraging the HIV-positive community to actively oppose

stigmatisation (WHO, 2002c; Parker and Aggleton, 2003), rather than by attempting to

directly increase tolerance among the general population (Brown et al., 2003).

4.4.4 Provider quality

Accreditation and regulation of providers could help improve quality, so long as excessive

or poorly targeted regulation was avoided (Soderlund and Tangcharoensathien, 2000);


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NHSSP proposals for increased power to be handed to professional regulatory bodies, as

well as the development of quality assurance programmes for traditional medicine, are

useful if limited.

4.4.5 Trust

Trust between patient and provider may be increased by providing high quality services,

and ensuring staff adhere to professional and ethical codes. Visibly increasing the equity of

government services and ensuring probity and good management practice, may also

improve trust (Tibandebage and Mackintosh, 2005). Increasing trust may have other

benefits too, increasing system efficiency and providing therapeutic advantages for the

individual (Gilson, 2003; Tibandebage and Mackintosh, 2005).

4.5 Applying Chronic Illness Management Frameworks

The ICCC framework identifies ‘building blocks’ to promote chronic illness management

at three levels—micro (the patient and family and primary care/community professionals),

meso (healthcare organisations and the community), and macro (the policy environment)

(WHO, 2002c). None of the barriers identified in this analysis relate to just one ICCC level;

instead they transect all three. In general, the building blocks are useful reference points

with which to compare local healthcare provision, although some of the present findings

suggest that implementation of the framework in coastal Kenya could still be challenging,

such as integrating care pathways and empowering patients.

5 CONCLUSION

This analysis has provided evidence for some of the barriers faced when managing chronic

illnesses in resource-poor settings. In particular, treatment costs are punitive and

unpredictable and in concert with other barriers can adversely affect households’

resilience, further limiting their ability to cope.

The NHSSP is encouraging but ambitious and requires implementation through wide-

reaching legislation in the health, social and financial sectors. In particular, policies to

reduce chronic illness costs must be honoured if their management is to improve.

Further studies are needed to examine whether the barriers identified here expressed at

the household level are also present at the micro, meso and macro levels and in other

resource-poor settings. Operational research is needed to examine how best to implement

policy changes in local environments.

ACKNOWLEDGEMENTS

We would like to thank Isaac Charoh, Gladys Sanga and all the individuals who took part

in the case study and focus group discussions for their help and advice. Also thanks to

Dr Steve Russell for his helpful comments on drafts of this paper. Finally, Thomas Porter is

sincerely grateful to his wife for remaining patient while he was ‘in the field’!


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Barriers to managing chronic illness among urban households in coastal Kenya

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