why have the members gone? explanations for dropout from a community-based insurance scheme

WHY HAVE THE MEMBERS GONE?EXPLANATIONS FOR DROPOUT FROM A

COMMUNITY-BASED INSURANCE SCHEME

TARA SINHA1*, M. KENT RANSON2, FALGUNI PATEL1 AND ANNE MILLS3

1SEWA Insurance, Self-Employed Women’s Association, Ahmedabad, India2Health Policy Unit, London School of Hygiene and Tropical Medicine, London, UK

3Department of Public Health and Policy, London School of Hygiene and Tropical Medicine,

London, UK

Abstract: A common challenge faced by voluntary community based insurance (CBI)

schemes is ensuring re-enrolment of their members. This study examines factors that may

explain dropout from a CBI scheme targeting poorer self-employed women in Gujarat.

Members who exited from the scheme were poorer and less educated; had weaker links with

the promoting institution; and used the scheme less in the preceding year. The primary reason

for dropping out was that members were not contacted by programme staff to re-enrol. Scheme

administrators can reduce dropout rates by maintaining better contact with scheme members

and systematically seeking them out at the time of enrolment. Such relatively simple

improvements in scheme administration can enhance the efficiency and equity of the scheme.

Copyright # 2006 John Wiley & Sons, Ltd.

Keywords: community based insurance; member dropout; member renewal; India; South

Asia; SEWA Insurance; sustainability; non government organisation

1. INTRODUCTION

In recent years, community based insurance (CBI) schemes have gained recognition as an

important means of providing financial protection to the poor against the risks of sickness,

accident, asset loss and death (World Bank, 2001; International Labour Office (STEP Unit,

2005)). By pooling small contributions from individual members, such schemes mobilise

community resources and protect individuals from unexpected losses.

Journal of International Development

J. Int. Dev. 19, 653–665 (2007)

Published online 19 December 2006 in Wiley InterScience

(www.interscience.wiley.com) DOI: 10.1002/jid.1346

*Correspondence to: Ms T. Sinha, Chanda Niwas, Opposite Karnavati Hospital, Ellisbridge, Ahmedabad 380001,India. E-mail: [email protected]

Copyright # 2006 John Wiley & Sons, Ltd.

A common challenge faced by many CBIs is continued membership of their members

(Ekman, 2004; Ahmed et al., 2005; McCord and Churchill, 2005). Membership in most

CBIs is voluntary, and members are required to renew their membership periodically.

Dropping out, that is, the failure of clients to renew their insurance, can be ‘astonishingly

high’, reaching 70–80% in some cases (McCord, 2001).

Maintaining continued membership is important for several reasons, for both the

member and the scheme. It is important for the member because it provides continued

financial protection, year after year. Lapsed members in some insurance schemes are

treated like newmembers, and there is a waiting period during which they are ineligible for

scheme benefits.

Retaining members also contributes to the financial sustainability of the CBI

programme. Having the same members year after year reduces the scheme’s exposure

to adverse selection. This is especially so in the case of health insurance, where it has been

found that people are more likely to join if they are sicker or have recently experienced a

hospitalisation in the family (Supakankunti, 2004). Also, having longer term members

means less expenditure on educating the members about the scheme. Member attrition can

adversely affect the reputation of a CBI, making it more difficult to manage partnerships

with providers of services such as health care, raising marketing costs, and ultimately,

threatening the financial sustainability of the scheme (Tabor, 2005). A high rate of renewal

is a measure of customer satisfaction, and member dropout may signify poor service or lack

of trust in the programme. Keeping renewal rates high is also important from an equity

perspective; experience has shown that the poor are more likely to drop out, threatening the

objective of providing protection to poorer populations (Supakankunti, 2004).

Some studies have looked at reasons for low renewal in CBI schemes, and have found a

variety of factors (McCord, 2001; Yap and Aldaba, 2002; Herrera and Miranda, 2004;

Rodriguez and Miranda, 2004; Supakankunti, 2004; Ahmed et al., 2005; Derriennic et al.,

2005). These include: lack of funds to pay the premium; poor understanding of the scheme

benefits or the concept of insurance; and dissatisfaction with some scheme features.

Non-use of the insurance generates expectations of getting the premium money back, and

in the absence of that, a member who has not used the scheme in 1 year may not enroll the

following year. Comparing a group of dropouts with renewed members, Supakankunti

(2004) found that the latter group had a significantly higher incidence of illness compared

to the dropout group. In the case of community based health insurance programmes,

distance of the health care provider and consequent difficulty of access may influence a

member to drop out of the scheme (Bennett et al., 1998).

This study aims to contribute to the limited but growing understanding of factors that

underlie dropout from a CBI scheme. Unlike previous studies, it focuses solely on

understanding whymembers drop out of a CBI scheme. The next section describes SEWA’s

CBI scheme. In Section 3 we discuss the methodology used in the study; this is followed by

a section on the findings of the study. In the last section we discuss the findings and

implications of these for CBI schemes.

2. SEWA’S INSURANCE PROGRAMME

The Self-Employed Women’s Association (SEWA) is a trade union of informal women

workers, started by Ela Bhatt in Ahmedabad in 1972. Headquartered in Ahmedabad

(Gujarat, India), and inclusive of members from 11 of the state’s 25 districts, ‘It is an

Copyright # 2006 John Wiley & Sons, Ltd. J. Int. Dev. 19, 653–665 (2007)

DOI: 10.1002/jid

654 T. Sinha et al.

organization of poor, self-employed women workers. . . who earn a living through their

own labour or small businesses. . . (and who) do not obtain regular salaried employment

with welfare benefits like workers in the organized sector’ (Self-Employed Women’s

Association, 1999). The organisation has two main goals: to organise women workers to

achieve full employment, that is, work security, income security, food security and social

security; and to make women individually and collectively self-reliant, economically

independent and capable of making their own decisions.

In 1992 SEWA started an integrated insurance programme, Vimo SEWA, or SEWA

Insurance, for its members. SEWA Insurance provides life, accident, hospitalisation and

asset insurance as an integrated package. Membership is voluntary. Women are the

principal members, and can buy insurance for husbands and children. Most members pay

an annual premium, and this amount is passed on to a formal-sector insurance company,

which shoulders most of the financial risk. The annual premium is Rs. 100, which is equal

to about 2 days of wages for a rural agricultural worker.

SEWA Insurance is run by a team of full-time staff and local women leaders called

aagewans. The aagewan is a grassroots level worker who is the critical link between

members and scheme administrators. The aagewans are responsible for enrolling members

and servicing their claims.

SEWA Insurance has two enrollment options for members. Members may either join

by paying a fixed deposit (FD) or by paying an annual premium. The FD amount has

been calculated to ensure that the annual interest income equals the annual insurance

premium. Members who use the FD option have their annual interest income on the FD

transferred towards the annual insurance premium each year. The membership of FD

members is therefore automatically renewed each year. Of the total membership in 2005,

over 90 000 members (74%) paid annually.

Members who pay the annual premium (‘annual members’) have to renew their

insurance membership each year. Annual premiums are collected by aagewans from

SEWA Insurance and other SEWA departments during a 3-month enrolment campaign,

September 1st through November 30th, for coverage starting on January 1st. As premiums

are collected, the SEWA aagewan fills out a receipt which records, among other things, the

member’s name, address, age and the premium paid. Members who miss the campaign

have to wait until the following year if they wish to purchase the annual policy. If a person’s

membership lapses in 1 year and she joins after a year’s break, she is treated as a new

member. New members have a waiting period of 6 months before they can be reimbursed

for hospitalisation due to a chronic disease.

SEWA Insurance would like to achieve 100% renewal of its annual members so that they

get continuous protection under the insurance scheme. SEWA Insurance also recognises

that if it is able to increase its retention rate, it will be able to increase the outreach and

efficiency of its insurance programme. While the renewal rate among annual members at

SEWA Insurance has improved over the last 3 years, from 22% in 2003 to 30% in 2004 and

41% in 2005 (Garand, 2005), it remains low.

SEWA Insurance has both urban and rural members—the membership break down in

the last few years has been one-third urban and two-thirds rural. While programme

managers are concerned about member dropout in both urban and rural areas, the

underlying reasons for member dropout may vary for the two areas. This study is limited to

the urban membership since SEWA Insurance has begun scaling up its operations amongst

its urban membership, and strategically, it is important to understand and address

systematically the issue of member dropout in this area.


DOI: 10.1002/jid

Dropout from community-based insurance 655

3. METHODOLOGY

3.1. Conceptual Framework

The study aims to explore why CBI members do not re-enroll into the scheme. Avariety of

factors may lead to a member’s dropping out (Figure 1). The factors can be classified as

demand-side factors (characteristics of individuals, households or groups in the target

population) and supply-side factors (characteristics of the CBI scheme). On the

demand-side are the factors that might underlie willingness to renew and perceived

likelihood of benefiting from the scheme. These include age, education, health status, trust

in the scheme, previous claim experience, participation in the scheme by friends and

neighbours, etc. Ability to pay for renewal is also determined by socio-economic status

(SES). On the supply-side are factors that determine whether members actually have the

opportunity to enroll, and factors that engender trust in, and knowledge of the scheme.

3.2. Survey Instrument

The survey instrument was designed to quantify both supply side and demand side factors

and to compare dropouts with renewed members across the four domains illustrated in

Figure 1. Questions were identical for dropouts and renewed members, except for two

additional questions asked to dropouts regarding their reasons for not renewing and their

Figure 1. Factors that may influence membership renewal in a CBI scheme.


DOI: 10.1002/jid

656 T. Sinha et al.

willingness to join again in the future. The survey instrument was pilot tested and revised

prior to the survey.

The survey was conducted in April and May 2005, 4 months after the campaign to enroll

members for calendar year 2005. Three research assistants were trained over a period of

10 days to administer the questionnaire.

3.3. Sampling

The sampling frame comprised the 17 168 adult women in Ahmedabad city who were

annual members in 2004. Of these, 6450 (37.5%) renewed their membership in 2005 while

10 718 (62.5%) dropped out of the scheme. We took a stratified random sample, with equal

numbers (n¼ 110) of dropouts and renewed members—a total of 220 individuals—using

simple random sampling from lists of dropouts and renewed members. If a selected

individual could not be located at the first visit—for example, due to poor or incomplete

address data, or because she had moved away without leaving a forwarding address—then

this was recorded as such. Respondents were recorded as ‘not available for interview’ only

if they were away from the house at the time of three separate visits. Respondents who

could not be located or who were not available for interview were not replaced in the

sample.

3.4. Data Analysis

Survey data were double-entered into a custom-designed Microsoft Access database.

Statistical analyses were performed using Stata 7.0 (Stata Corporation, College Station,

TX). SES of individuals was measured using a composite index (Ranson et al., 2006). The

summary index, for the general population of Ahmedabad City, has a mean of zero and

standard deviation of one. Thus an index value of þ2 indicates very high SES, whereas a

value of �2 indicates very low status, and a value of zero indicates intermediate levels. In

comparing dropouts and renewed members, we used the chi-squared test for proportions

and the two-sample t-test for means.

4. RESULTS

4.1. Relative Response Rates

Response rates were not significantly different between dropouts (74%; n¼ 81) and

renewed members (82%; n¼ 90). The reasons for non-response, however, differed

significantly (Chi2¼ 9.26, p-value¼ 0.026, see Table 1). The dropouts were far more likely

to have moved and been lost to follow-up (8 vs. 1 respondent) or to have been unavailable

for interview (9 vs. 3 respondents).

4.2. Willingness to Renew

In terms of factors likely to impact on willingness to renew (or perceived likelihood of

benefiting from the scheme) there were relatively few significant differences (Table 2).

Women who had dropped out were not significantly different from members in terms of


DOI: 10.1002/jid


age, education or hospitalisation within the last 1 year. Dropouts were more likely to report

that they had belonged to SEWA Insurance only during the previous year (i.e. that they

were new members in 2004 and therefore had had a shorter association with the scheme.)

(Chi2¼ 87.8, p-value¼ 0.000, see Table 1).

At the level of the entire household, the mean percentage of adults who had completed

secondary school (i.e. 10th standard) was significantly higher in renewed member

households (14% of adults) than in dropout households (0% of adults) (t-test¼�5.22,

p-value¼ 0.000). Dropout households were more likely to have insured only the woman

(69.2% vs. 44.2%) and not other household members (Chi2¼ 12.0, p-value¼ 0.003). And

dropout households were significantly less likely to have submitted any insurance claim to

SEWA Insurance during 2004 (t-test¼�3.07, p-value¼ 0.003). Dropout and member

households did not differ significantly in terms of: percentage of households in which any

member had been hospitalised within the last year (although there was a non-significant

trend suggesting higher rates of hospitalisation in the member households); percentage of

households enrolled in any other type of insurance scheme, or average number of adults

(15 years of age and above) per household.

4.3. Ability to Renew: Socio-Economic Status

Table 3 compares dropout and member households by indicators of SES. Almost all the

indicators suggest that members were less poor than the dropouts, but the differences were

generally not statistically significant. For example, 58% of member households used gas

for cooking (rather than kerosene, or wood, for example) compared with 51% of dropouts

(t-test¼�0.936, p-value¼ 0.351). Member households owned 0.90 television sets, on

average, compared to 0.80 among dropouts (t-test¼�1.81, p-value¼ 0.072). The average

SES index score was higher for members (�0.39) than for dropouts (�0.54), but this

difference was not statistically significant (t-test¼�1.44, p-value¼ 0.152). Of the

variables that made up the SES index, the only one which showed a statistically significant

difference was ‘mean percentage of adults who had completed secondary school’—this

variable was also included in the previous sub-section, as it may influence demand for

insurance (e.g. better educated individuals/households more likely to appreciate the value

of insurance) and ability to pay (e.g. better educated households are more likely to have the

resources necessary to pay the premium).

Table 1. Response rates

Dropouts Renewed members Test statistic p-valueNumber (%) Number (%)

Successfully interviewed 81 (73.6) 90 (81.8) 2.1267 0.145

Not found based on available

address information

12 (10.9) 14 (12.7)

Moved and lost to follow-up 8 (7.3) 1 (0.9)

Not available (visited thrice) 9 (8.2) 3 (2.7)

Deceased or unable to respond 0 (0.0) 2 (1.8) 9.2575 0.026

Total sampled 110 (100.0) 110 (100.0)


DOI: 10.1002/jid

658 T. Sinha et al.

Table

2.

Variablesthat

may

underliewillingnessto

renew

,dropoutsversusmem

bers

Dropouts

Renew

edmem

bers

Teststatistic

p-value

Number

1Meanor%

Number

1Meanor%

Primary(w

oman)mem

ber

Meanage

81

36.8

90

37.3

�0.346

0.730

%did

notcomplete

secondaryschool

71/81

87.7

79/89

88.8

%completedsecondaryschool(10th

standard)

7/81

8.6

6/89

6.7

%attended

collegeoruniversity

3/81

3.7

4/89

4.5

0.271

0.873

%hospitalised

within

1year

5/81

6.2

5/90

5.6

0.0295

0.864

%mem

ber

inonly

1previousyear

62/80

77.5

5/85

5.9

%mem

ber

inonly

2previousyears

14/80

17.5

58/85

68.2

%mem

ber

in3ormore

previousyears

4/80

5.0

22/85

25.9

87.772

0.000

Entire

household

Mean%

Hhadultswhocompletedsecondaryeducation

81

0.0

90

13.7

�5.222

0.000

Mean%

Hhadultsattended

collegeoruniversity

81

5.8

90

7.4

�0.553

0.581

%Hhwithanyhospitalisation

14/81

17.3

23/90

25.6

1.7203

0.190

%Hhwithwomen

only

insured

54/78

69.2

38/86

44.2

%Hhwithwomen

plusspouse

insured

20/78

25.6

33/86

38.4

%Hhwithwomen

plusspouse

andchildreninsured

4/78

5.1

15/86

17.4

11.978

0.003

%Hhthat

madeclaim

within

last1year

1/80

1.3

12/88

13.6

9.0052

0.003

%Hhwithanyother

kindofinsurance

16/81

19.8

18/89

20.2

0.0059

0.939

Meannumber

ofadultsin

Hh(15years

orolder)

81

3.9

90

4.0

�0.253

0.801

1Forcontinuousvariables(i.e.wheremeansarepresented)thetotalnumber

ofobservationsisprovided.Fordichotomousandcategoricalvariables,both

thenumeratorandthe

denominator(i.e.totalnumber

ofobservations)

areprovided.


DOI: 10.1002/jid


Table

3.

Socio-economic

variablesthat

may

underlieabilityto

renew

,dropoutsversusmem

bers

Dropouts

Renew

edmem

bers

Teststatistic

p-value

Number

1Meanor%

Number

1Meanor%

%Hhusinggas

forcooking

41/81

50.62

52/90

57.78

�0.936

0.351

Meanno.ofroomsper

Hh

81

1.75

90

1.77

�0.112

0.911

Meanno.structuralconditionofdwelling2

81

3.59

90

3.63

�0.431

0.667

Meanmonthsofoilstore

81

0.43

90

0.68

�1.122

0.264

Mean%

ofHhadultsattended

collegeoruniv.

81

5.83

90

7.37

�0.553

0.581

Mean%

ofHhadultscompletedsecondaryeducation

81

0.00

90

13.75

�5.222

0.000

Mean%

ofHhadultsunskilledwork/daily

wages

81

36.75

90

40.68

�0.789

0.431

Meanno.ofwristwatches

per

Hh

81

1.15

90

1.41

�1.154

0.250

Meanno.ofrefrigerators

per

Hh

81

0.19

90

0.21

�0.422

0.674

Meanno.oftelevisionsper

Hh

81

0.80

90

0.90

�1.809

0.072

Meanno.ofVCRs/VCDsper

Hh

81

0.11

90

0.08

0.744

0.458

Meanno.ofmotorcycles/scooters

per

Hh

81

0.33

90

0.29

0.511

0.610

Meansesindex

score

81

�0.54

90

�0.39

�1.438

0.152

PercentageofHhfallingbelow

30th

decileofses

39/81

48.1

33/90

36.7

2.305

0.130

1Forcontinuousvariables(i.e.wheremeansarepresented)thetotalnumber

ofobservationsisprovided.Fordichotomousandcategoricalvariables,both

thenumeratorandthe

denominator(i.e.totalnumber

ofobservations)

areprovided.

2Thestructuralconditionofthehouse

was

measuredonafour-pointscale,withascore

of1indicatingaseriouslydilapidated

structure

andascore

of4indicatingasoundstructure.


DOI: 10.1002/jid

660 T. Sinha et al.

4.4. Engendering Trust and Knowledge

Relative to the dropouts, members were significantly more likely to have ‘heard about

SEWA’, to have paid the membership fee (of Rs. 5) to SEWAUnion in 2004, and to have an

account at SEWA Bank (Table 4). Members were also more likely to know a grassroots

level representative of SEWA (an aagewan), to have an aagewan who was a relative or

neighbour, and to know the aagewan who sold them insurance, but these differences were

not statistically significant. Members were significantly more knowledgeable about

the benefits available under the scheme—79% of members answered two or more of the

scheme-related questions correctly, compared with only 51% of the dropouts.

4.5. Self-Reported Reasons for Dropping Out

Among the 81 respondents who had dropped out of SEWA Insurance, 57% said that their

only or primary (for those who gave two reasons) reason was that no one had come to sell

them the insurance. An additional 16% said that they did not have money when they were

approached by an aagewan (Table 5).

5. DISCUSSION

5.1. Summary

Few demand-side variables were significantly associated with dropping out, but some

important trends were observed, and deserve further attention. Renewed members

were more likely to come from better educated households and were more likely to have

submitted an insurance claim during the year preceding the survey. Among renewed

members (vs. dropouts) there was a trend towards higher SES and higher probability of

hospitalisation per household. There were important supply-side factors which prevented

people from re-enrolling. Among those dropouts who could be contacted, 57% said that

their primary reason for dropping out was that nobody had come to sell them the insurance.

Women were significantly more likely to renew if they had stronger linkages with SEWA,

including membership in SEWA Union or an account at SEWA Bank.

5.2. Strengths and Weaknesses

The main strength of the study is that it uses a well organised and comprehensive

conceptual framework for exploring demand- and supply-side factors that might impact on

the retention of members by a CBHI scheme. The authors are aware of only one other study

that has examined this issue in a detailed and systematic manner (Supakankunti, 2004).

Weaknesses are threefold. First, the sample size was too small to examine the statistical

significance of certain associations between supply- and demand-side variables and

outcome (i.e. drop-out vs. renewal). The study was designed as a quick and efficient means

of identifying the most important barriers to renewal, and a much larger study would be

required to determine whether some of the trends observed (e.g. higher SES of renewed

members relative to dropouts) are indeed statistically significant. A larger sample size


DOI: 10.1002/jid


Table

4.

Variablesunderlyingtrustandknowledge,

dropoutsversusmem

bers

Dropouts

Renew

edmem

bers

Teststatistic

p-value

Number

1Meanor%

Number

1Meanor%

Know

SEWA

union

37/81

45.7

59/90

65.6

6.840

0.009

Mem

ber

ofSEWAUnion

42/81

51.9

64/90

71.1

6.711

0.010

Havean

accountat

SEWA

Bank

29/81

35.8

59/88

67.0

16.497

0.000

HaveachildcaredforbySEWA

childcare

centre

5/81

6.2

5/90

5.6

0.030

0.864

Mem

ber

ofaSEWAwork

cooperative

3/81

3.7

0/90

0.0

3.393

0.065

Know

anySEWA

aagew

an

67/81

82.7

82/90

91.1

2.680

0.103

Aagew

anisarelativeorneighbour

20/67

29.9

31/82

37.8

1.036

0.309

Know

SEWA

Insurance

aagew

anwhosold

them

Insurance

51/81

63.0

67/90

74.4

2.628

0.105

Know

losses

covered

bySEWA

Insurance

Nocorrectresponse

12/81

14.8

5/90

5.6

1correctresponse

28/81

34.6

14/90

15.6

2correctresponses

25/81

30.9

45/90

50.0

3correctresponses

12/81

14.8

20/90

22.2

All4responsescorrect

4/81

4.9

6/90

6.7

15.232

0.004

1Fordichotomousandcategoricalvariables,both

thenumeratorandthedenominator(i.e.totalnumber

ofobservations)

areprovided.


DOI: 10.1002/jid

662 T. Sinha et al.

would also allow for multiple regression analysis—which would in turn permit control for

confounding and assessment of the relative importance of variables as determinants of

dropping-out/renewal.

Second, because this was a cross-sectional study, it is impossible to establish causality.

For example, the study found a significant, positive association between knowledge of

SEWA Insurance and renewal of membership in the scheme. But it cannot be known

whether it was the more knowledgeable members whowere then more likely to renew their

membership, or whether women who had renewed their membership were more

knowledgeable about the scheme because they had more recently heard again about the

scheme from a scheme representative.

Third, the quantitative (and largely ‘closed-ended’) nature of the survey tool meant that

it was difficult to explore complex issues and associations. For example, in the course of

their work with SEWA Insurance, the authors have observed that some who have dropped

out of the scheme will readily cite lack of money as the reason. Deeper probing may reveal

that money was, in fact, available; but that other purchases were perceived as more

important than insurance or that the member was dissatisfied in some way with SEWA

Insurance. Such issues can be better explored using a qualitative methodology, such as

in-depth interviews.

5.3. Discussion and Recommendations

The study suggests that many who drop out of the SEWA Insurance scheme do so because

they are not contacted by SEWA Insurance, during the annual enrolment campaign, for

collection of the premium. This may be because of problems with the scheme’s database

(e.g. address data that are incorrect, inadequate or out-of-date); women and their families

are away from home when the aagewan visits to collect the premium; and/or systems are

not in place to make sure that all current members are visited at the time of the annual

campaign.

Table 5. Reasons given by dropouts for not renewing SEWA Insurance membership

Reason for dropping out Only reason Persons who gavetwo reasons

Only and primaryreason as a %of total (N¼ 81)

Primaryreason

Secondaryreason

No one came to collect premium 39 7 3 56.79

No money at the time 6 7 6 16.05

Dissatisfied with SEWA Insurance rules 1 4 3 6.17

Have not suffered loss in previous years 2 2 2 4.94

Do not understand scheme 2 0 4 2.47

Dissatisfied as previous claim rejected 1 1 1 2.47

Dissatisfied with SEWA Insurance generally 1 1 1 2.47

Unable to submit claim, despite loss 2 0 0 2.47

Other family member bought SEWA Insurance

last time

1 0 0 1.23

Other 3 1 3 4.94

Total 58 23 23 100


DOI: 10.1002/jid


SEWA Insurance is already trying to address some of these issues. During the most

recent enrolment campaign, various steps were taken to maximise re-enrolment rates.

Aagewans were assigned a target population of 2005 members, 800 members on average.

They were provided with a list (in Gujarati language) of the members for whom they were

responsible. Prior to the campaign, they visited each of the households in their list and

provided education about the SEWA Insurance scheme, an information pamphlet, and

three adhesive barcodes displaying that member’s unique identification code. Then, during

the campaign (September to November), they visited each member household again

to re-enroll them. This measure met with considerable success, and in the space of only

1 year, re-enrolment rates rose from 42 to 59% in Ahmedabad city.

SEWA Insurance can also consider rewarding members who continue for a longer term in

the programme. BRAC inBangladesh has been able to increase the renewal rate in its insurance

programme by giving premium discounts to renewing members (Ahmed et al., 2005).

The stronger linkages between renewed members and the institution (SEWA and SEWA

Insurance) and its representatives suggest that it would be easier to retain members if

aagewans maintained regular contact with the members and strengthened their servicing.

This would result not only in better service but also in building of trust in the insurance

programme, a feature which is key in arrangements which function without written

agreements (Schneider, 2004; Walker and Gilson, 2004). A programme strategy that would

facilitate member-aagewan contact would be to increase member density in geographic

areas. This would reduce the cost of maintaining member contact and increase member

retention due to the community’s influence and the positive demonstration effects of

successful claimants.

The data suggest that poorer members are more likely to drop out. This is problematic

from an equity perspective. Given that SEWA Insurance aims to provide financial

protection to poorer women and their families, it needs to ensure that the insurance

package, and systems for delivering it, is well-suited to the poor.

Those who have not submitted a claim to SEWA Insurance are more likely to withdraw

from the scheme. This is indirect evidence of adverse selection, wherein those at higher risk of

the event being insured against are more likely to enroll than those at lower risk. One way to

counter this problem would be to implement a ‘no claims bonus’ (or discount), such that

households that have not submitted any claim pay a lower premium at the time of renewal.

6. CONCLUSIONS

Most CBI schemes are very small, both in terms of absolute membership numbers and in

terms of the proportion of target population reached (International Labour Office

(Universitas Programme, 2002); Ekman, 2004). Against this background, SEWA Insurance

stands out with respect to its size and achievements. Nonetheless, this study has

demonstrated that relatively simple measures, to do primarily with scheme administration,

are likely to pay big dividends in terms of increasing the efficiency of the insurance

operation, and improving the extent to which SEWA Insurance can serve its poorer

members.

ACKNOWLEDGEMENTS

Financial support was provided by the ILO-STEP.


DOI: 10.1002/jid

664 T. Sinha et al.

REFERENCES

Ahmed MU, Islam SK, Quashem MdA, Ahmed N. 2005. Health Microinsurance-a comparative

study of three examples in Bangladesh. Washington DC, CGap Working Group on Microinsur-

ance, World Bank: 1–73.

Bennett S, Creese A, Monasch R. 1998.Health Insurance Schemes for People Outside Formal Sector

Employment. Geneva, Division of Analysis, Research and Assessment, World Health Organiz-

ation.

Derriennic Y, Wolf K, Kiwanuka-Mukiibi P. 2005. An Assessment of Community-Based Health

Financing Activities in Uganda. Abt Associates: Bethesda, Maryland 1–51.

Ekman B. 2004. Community-based health insurance in low-income countries: a systematic review of

the evidence. Health Policy and Planning 19(5): 249–270.

Garand D. 2005. Vimo SEWA, India. Washington DC, CGap Working Group on Microinsurance,

World Bank: 1–57.

Herrera C, Miranda B. 2004. Columna: Guatemala. Geneva, CGap Working Group on Microinsur-

ance, World Bank: 1–50.

International Labour Office (STEPUnit). 2005. Community Based Schemes—India: An inventory of

micro insurance-schemes. Geneva, ILO-STEP.

International Labour Office (Universitas Programme). 2002. Extending social protection in health

through community based health organizations: Evidence and Challenges. Geneva, ILO: 1–79.

McCord MJ. 2001. Health care microinsurance—case studies from Uganda, Tanzania, India and

Cambodia. Small Enterprise Development 12(1): 25–38.

McCord MJ, Churchill C. 2005. Delta life: Bangladesh. Washington DC, CGap Working Group on

Microinsurance, World Bank: 1–75.

RansonMK, Sinha T, ChatterjeeM, Acharya A, Bhavsar A, Morris SS,Mills A. 2006. Making health

insurance work for the poor: learning from SEWA’s community-based health insurance scheme.

Social Science and Medicine 62(3): 707–720.

Rodriguez MU, Miranda B. 2004. Serviperu: Peru Washington DC, CGap Working Group on

Microinsurance, World Bank: 1–45.

Schneider P. 2004. Why should the poor insure? Theories of decision-making in the context of health

insurance. Health Policy and Planning 19(6): 329–355.

Self-Employed Women’s Association. 1999. Self-Employed Women’s Association: Annual Report

1999. Ahmedabad, SEWA: 83.

Supakankunti S. 2004. Impact of the Thailand Health Card. In Health Financing for Poor People.

Preker A, Carrin G (eds). World Bank: Washington DC, 315–357.

Tabor SR. 2005. Community-based health insurance and social protection policy. In Social Protec-

tion Discussion Paper Series, Social Protection Unit. World Bank: Washington DC, 1–65.

Walker L, Gilson L. 2004.We are bitter but we are satisfied: nurses as street level bureaucrats in South

Africa. Social Science and Medicine 59(6): 1251–1261.

World Bank. 2001. World Development Report 2000/2001: Attacking Poverty. Oxford University

Press: Oxford.

Yap ME, Aldaba E. 2002. ORT Health Plus Scheme in the Province of La Union, Philippines. A Case

Study of a Community Based Health Micro-Insurance Scheme. International Labour Office:

Geneva. 1–65.


DOI: 10.1002/jid


why have the members gone? explanations for dropout from a community-based insurance scheme

Documents