Working Paper No. 608
Renewing membership in three community-based health insurance schemes in rural India
Pradeep Panda, Arpita Chakraborty, Wameq Raza and Arjun Bedi
April 2015
ISSN 0921-0210 The Institute of Social Studies is Europe’s longest-established centre of higher education and research in development studies. On 1 July 2009, it became a University Institute of the Erasmus University Rotterdam (EUR). Post-graduate teaching programmes range from six-week diploma courses to the PhD programme. Research at ISS is fundamental in the sense of laying a scientific basis for the formulation of appropriate development policies. The academic work of ISS is disseminated in the form of books, journal articles, teaching texts, monographs and working papers. The Working Paper series provides a forum for work in progress which seeks to elicit comments and generate discussion. The series includes academic research by staff, PhD participants and visiting fellows, and award-winning research papers by graduate students. Working Papers are available in electronic format at www.iss.nl
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Table of Contents ABSTRACT 1
2
3
INTRODUCTION
1
Scheme description and uptake
3
METHODOLOGY
6
Analytical Framework
6
Data
10
RESULTS
14
Renewal after experiencing CBHI for one year (renewed in 2012, joined in 2011) 14 Renewal after experiencing CBHI for one year (renewed in 2013, joined in 2012) 15
4
Determinants of renewal after experiencing CBHI for two years
18
CONCLUSIONS
21
REFERENCES
23
APPENDICES
25
ABSTRACT Low renewal rate is a key challenge facing the sustainability of Communitybased Health Insurance (CBHI) schemes. While there is a large literature on initial enrolment into such schemes, there is limited evidence on the factors that impede renewal. This paper uses longitudinal data to analyse what determines renewal, both one and two years after the introduction of three CBHI schemes, which have been operating in rural Bihar and Uttar Pradesh since 2011. We find that initial scheme uptake is about 23-24 % and that two years after scheme operation, only about 20 % of the initial enrolees maintain their membership. A household’s socio-economic status does not seem to play a large role in impeding renewal. In some instances, a greater understanding of the scheme boosts renewal. The link between health status and use of health care in maintaining renewal is mixed. The clearest effect is that individuals living in households that have received benefits from the scheme are substantially more likely to renew their contracts. We find that having access to a national health insurance scheme is not a substitute for the CBHI. We conclude that the low retention rates may be attributed to limited benefit packages, slow claims processing times and the gaps between the amounts claimed and amounts paid out by insurance.
Keywords Community-based health insurance, renewing membership, rural India.
Research reported in this paper has been funded by the European Union’s FP7 programme, project – Community-based Health Insurance in India, HEALTH-F22009-223518. The authors gratefully acknowledge comments from David Dror on an initial draft of this paper. Pradeep Panda: Micro Insurance Academy, India em:
[email protected]; Arpita Chakraborty: Micro Insurance Academy, India and Public Health Foundation of India, em:
[email protected]; Wameq Raza: Institute for Health Policy and Management, Erasmus University Rotterdam, em:
[email protected]; Arjun Bedi: International Institute of Social Studies (ISS), Erasmus University Rotterdam, The Netherlands, em:
[email protected]. Corresponding author: Pradeep Panda,
[email protected], postal mail: Micro Insurance Academy, 52-B, Okhla Industrial Estate, Phase III, New Delhi – 110025, India. Ph: +91-11-43799100.
Introduction Since the late 1990s, there has been a proliferation of community-based health insurance (CBHI) schemes in low and middle-income countries (Ekman, 2004; Mebratie et al., 2013). Such schemes bring together individuals from a common background (for example, geographical, economic, occupational, ethnic, gender) to set up, own and operate a health insurance scheme on a not-for-
profit or profit sharing basis (Dror, 2014). It is based on the principle of risk sharing amongst the community of insured people to provide financial protection against the impoverishing effects of health expenditure (Carrin et al., 2005). Enrolment in most CBHI schemes is voluntary, typically premiums are low and independent of individual health status (Radermacher and Dror, 2006). There is substantial evidence that being affiliated to CBHI schemes is associated with an increase in health care utilisation and some evidence that such schemes provide financial protection in terms of
reduced out-of-pocket spending (Panda et al., 2014c). Despite such effects, initial uptake and renewal rates in CBHI schemes tend to be low. Based on a systematic review of 46 micro level studies conducted between 1995 and 2012, Mebratie et al. (2013) report an unweighted average uptake rate of 37%. Although initial uptake is important (Panda, Chakraborty, Dror & Bedi, 2013), scheme sustainability clearly requires renewal of membership. While the literature that has examined
renewal is limited (Friedman, 2013), the few studies that have dealt with this issue report a high dropout rate. For instance, in a scheme in Guinea-Conakry, initial enrolment rate was 8% in 1998 which dropped to 6% a year later (Criel and Waelkens, 2003). In the Nouna district scheme in Burkina Faso, enrolment lay between 5.2% and 6.3% in the years 2004 to 2006 with a drop-out rate of 30.9% in 2005 and 45.7% in 2006 (Dong et al., 2009). In Senegal, for three schemes set up between 1997 and 2001, Mladovsky (2014) reports that in 2009, scheme drop-out rates ranged
between 58 and 83%. While low renewal rates appear to be the norm, an exception is the case of a CBHI scheme in Ethiopia which reports a drop-out rate of only 18% (Mebratie et al., 2015). Turning to the Indian context, a scheme operating in Gujarat witnessed a drop-out rate of 49% (Bhat and
1
Jain, 2007), while another scheme operating in Maharashtra observed a drop-out rate of 67% (Platteau and Ontiveros, 2013). An assessment of the literature suggests that there are four broad sets of factors that inhibit renewal. These are scheme affordability, the poor quality of care that may be accessed through the scheme, the health status of individuals and information failures, which include poor understanding of insurance in general and insufficient information on how to use the insurance scheme on offer (Panda et al., 2014c). For example, in Guinea-Conakry, scheme affordability and poor quality of care on offer were identified as the main reasons for declining enrolment rates (Criel and Waelkens, 2003). Another study reports a similar finding in Burkina Faso (Dong et al., 2009). A recent study in Senegal concluded that episodes of ill-health and active scheme participation increase retention, while a negative perception of quality of care increases scheme drop-out (Mladovsky, 2014). In the case of Ethiopia’s CBHI scheme, it was found that households that have greater knowledge about the CBHI scheme and those who have actually used services through the scheme are more likely to renew their contracts (Mebratie et al., 2015). In the Indian context, low level of awareness about the CBHI schemes, affordability, no-claim in the previous term and exclusion of out-patient services from the benefit package were the primary reasons for dropping out (Sinha et al., 2007). While there are some variations, similar
conclusions may be drawn from the experience of micro health insurance schemes in Gujarat (Bhat and Jain, 2007) and Karnataka (Aggarwal, 2011). Most recently, based on a CBHI scheme in Maharashtra, the authors concluded that a better understanding of insurance reduced attrition (Platteau and Ontiveros, 2013). The same study also demonstrated that a better understanding of insurance reduced the negative effect of not having received any pay outs through insurance, on contract renewal. The current study contributes to the existing literature by analysing the factors that affect renewal decisions in the case of three CBHI schemes operating in rural India, one each in Pratapgarh and Kanpur Dehat districts of Uttar Pradesh and one in Vaishali district, Bihar. The data on hand allows an analysis of renewal both, one year and two years after scheme launch. The paper focuses 2
on the role played by socio-economic status, health status, scheme-related features and knowledge and understanding of insurance - both general and scheme-specific, in influencing renewal. The paper proceeds by providing, in the next section, a description of the three CBHI schemes, followed by a description of our analytical framework and a discussion of the data. The subsequent section contains results and a discussion, while the final section concludes the study.
Scheme description and uptake The three CBHI schemes are located in Uttar Pradesh and Bihar, two of India’s most populated and poorest states. The study sites are rural areas, about 50-100 kilometres from the nearest urban centres. The project’s target group was defined as households with at least one woman registered as a member of a woman’s self-help group (SHG) in March 2010 (when the baseline study was conducted). The target group for the project consisted of 3685 SHG households (1283 in Pratapgarh, 1039 in Kanpur Dehat and 1363 in Vaishali) representing a total of 24,094 individuals (8852, 6931 and 8311 in Pratapgarh, Kanpur Dehat and Vaishali respectively). Each of the CBHI schemes has been designed as a cluster randomised control trial (CRCT) with a three wave implementation process (Doyle et al., 2011). Each cluster was designed to contain approximately the same number of SHG-affiliated households and subsequently, each cluster was randomly assigned to one of the three waves of treatment. In each wave, one-third of clusters received treatment, that is, they were offered a chance to join the CBHI. At all locations, the project was implemented by the Delhi-based Micro Insurance Academy (MIA) in co-operation with a local non-governmental organization which had well-established relations with the SHGs. The three field partners were BAIF (Bharatiya Agro Industries Foundation) in Pratapgarh, Shramik Bharti in Kanpur Dehat and Nidan in Vaishali. The implementation process followed MIA’s 17-step model that includes awareness building, insurance education, initial package design and premium-pricing based on information obtained from a baseline survey, modification of package design and premium-setting on the basis of interactions with the SHGs during benefit options consultation workshops, and finally training of SHG members to manage the scheme (Dror 3
et al., 2014). Following insurance education, the SHG members participated in designing the benefit package through a simulation game called CHAT (Choosing Health-Plans All Together). Details on the benefit package selected at each site are provided in Table 1. The packages in Pratapgarh and Kanpur Dehat are similar except that in the first year, SHGs in Pratapgarh did not opt for coverage of outpatient services. SHGs in Vaishali district opted not to include coverage of inpatient care but opted for out-patient care and coverage of various diagnostic tests. There are caps on the maximum amounts that may be claimed for inpatient care and for the use of laboratory and imaging services. There is no limit in terms of using outpatient care. However, at all three sites such care is provided only by designated practitioners. During the second year of the project, the scheme in Pratapgarh also offered out-patient services. Following the CRCT design, during the first phase of implementation in 2011, 7722 individuals were offered the possibility of joining the CBHI schemes (see Table 2). A year later, the schemes were offered to 6,493 individuals (see Annexure I for detailed timeline). Of the 7722 individuals offered the scheme in the first year, 1806 enrolled (23%). A year later 46% (768 individuals among 1667 resurveyed in 2012 out of 1806) renewed their membership and two years later 301 individuals of those who had enrolled in 2011 retained their membership (see Table 2). There is some variation across the three schemes, with renewal rates in 2013 ranging from 13% in
Kanpur Dehat to 21% in Pratapgarh. Amongst those who were offered the scheme in the second year, the overall enrolment rate was 24% and a year later, only 37% renewed their membership. While there are variations across the schemes both in terms of initial enrolment and renewal, there is no clear indication that one scheme is performing systematically better than others in terms of uptake and renewal. The low initial uptake and high dropout rates in these three CBHI schemes is reminiscent of the patterns that have been observed in other CBHI schemes in India. The low and
declining renewal rates despite the efforts that have been put in to involve the community before and after scheme implementation, calls for an analysis of factors that influence the decision to renew membership in the CBHI schemes.
4
Table 1 Description of benefit packages under the CBHI schemes (in INR) Year 1 Indicators Annual CBHI premium per person/per year
Year 1I
Year 111
Pratapgarh
Kanpur Dehat
Vaishali
Pratapgarh
Kanpur Dehat
Vaishali
Pratapgarh
Kanpur Dehat
Vaishali
176
192
197
250
192
197
250
199
197
Coverage for hospitalization (more than 24 hours) Fees (cap per person per event)
Wage loss (per day) Transport (maximum coverage per episode)
per event per family per year per event per day
per event
6000
3000
-
4000
3000
-
4000
4000
-
-
30000
25000
-
30000
30000
-
100
75
100
100
50
100
100
50
100
3-8th day
4-13th day
4-9th day
4-7th day
3-6th day
4-9th day
4-7th day
3-7th day
4-9th day
100
100
-
100
250
-
100
300
-
-
Unlimited
Unlimited
Unlimited
Unlimited
Unlimited
Unlimited
Unlimited
Unlimited
-
-
200
-
-
200
-
-
400
-
-
-
-
-
-
2000
-
-
-
-
-
-
500
-
-
-
-
-
-
2000
-
-
-
-
400
-
-
100
-
-
-
-
-
1000
-
-
500
-
-
-
-
-
-
Coverage for outpatient care
Fees Lab tests (per year)*
Imaging tests (per year)* Injuries (if plaster is required)
per event per family per year per event per family per year per event per family per year
300
300
Coverage for maternity care Caesarean (per episode)
per event
5000
-
-
-
"-" indicates "Not Included in package" *
Maximum amount, per person per year
5
Table 2 Renewal rates for individuals over the years Pratapgarh
Kanpur Dehat
Vaishali
All
2594
2264
2864
7722
Enrolled in 2011
604
334
868
1806
Percentage of enrolment in 2011
23%
15%
30%
23%
Resurveyed in 2012 among the enrolled in 2011
547
314
806
1667
Renewed in 2012
222
110
436
768
Percentage of renewal in 2012
41%
35%
54%
46%
Resurveyed in 2013 among the renewed in 2012
194
99
381
674
Renewed in 2013
125
45
131
301
Percentage of renewal with respect to 2012
64%
45%
34%
45%
Percentage of renewal with respect to 2011
21%
13%
15%
17%
1907
1993
6493
Indicators
Individuals offered CBHI in 2011 1st Year of Implementation (2011) Offered to enrol in 2011
2nd Year of Implementation (2012)
3rd Year of Implementation (2013)
Individuals offered CBHI in 2012 2nd Year of Implementation (2012) Offered to enrol in 2012
2593
Enrolled in 2012
491
451
600
1542
Percentage of enrolment in 2012
19%
24%
30%
24%
419
386
534
1339
3rd Year of Implementation (2013) Resurveyed in 2013 among the enrolled in 2012 Renewed in 2013
110
177
206
493
Percentage of renewal in 2013
26%
46%
39%
37%
Note: *With respect to enrolment in 2011
Methodology Analytical Framework Our aim is to identify the factors that determine scheme renewal. Drawing on the existing literature as well as our knowledge of the context we focus mainly on the role of four sets of factors in influencing renewal. These are scheme affordability, scheme use, knowledge of insurance and understanding of the scheme, and recent episodes of illness. We do not have information on the quality of care on offer but control for access to care. We also control for a range of individual demographic attributes (membership in SHG, age, gender, marital status, relation to the head of
6
household) and whether an individual is a member of the Rashtriya Swasthya Bima Yojna (RSBY).1 Having access to the RSBY may be likely to reduce the expected benefits of enrolling in the CBHI schemes. We specify the probability that an individual i belonging to household h renews (RENEW = 1) their subscription in time period t as a function of a set of variables in time period t-1. Regressing current renewal status on past values of the various sets of covariates allows us to provide estimates that are less likely to be influenced by the endogenous nature of some of the explanatory variables. A household’s ability to afford the scheme is treated as a function of a set of socio-economic characteristics (SES) which includes caste, household size, education and employment status of the household head, the monthly per capita expenditure tertile in which a household falls, and monthly per capita financial liability. Since scheme use (SU) is likely to beget scheme renewal we include a variable which indicates whether the household to which an individual belongs, has been reimbursed through the scheme in the preceding period. Two indices are constructed to capture knowledge of insurance and understanding of the CBHI scheme (KU) (respondent is the SHG member). The indices are constructed using responses to six questions related to insurance and seven questions on the concepts and operational aspects of the CBHI schemes (for details, see Panda, Chakraborty, & Dror, 2014). Each correct answer is assigned a score of 1 and 0 otherwise. These scores are added
to obtain a total score and subsequently dummy variables are used to indicate whether a household has a score above or below average.2 The role of an individual’s health status (HE) in influencing enrolment is captured by the number of episodes of short-term (acute), long-term (chronic) and hospitalisation. Access to care (AC) is proxied by the time taken to reach the nearest available source of in-patient and out-patient care. Precise definitions of the variables included in the specification are contained in Table A1 and descriptive statistics are provided in Table 3.
1
RSBY is a dummy variable indicating whether households are members of a public provided health insurance scheme which covers in-patient care. The scheme provides coverage of up to Rs. 30,000 for families who are below the poverty line. 2 We also experimented with a three-part classification of these variables. However, given the small number of observations, especially in the site-specific regressions, we switched to a two-part classification.
7
Table 3 Descriptive statistics (mean and standard deviation) Variable
Schedule caste/Schedule tribe
Individuals who joined CBHI in 2011 and Individuals who joined CBHI in 2012 and renewed/dropped out in 2012 renewed/dropped out in 2013 PratapKanpur PratapKanpur Vaishali All Vaishali All garh Dehat garh Dehat Household Socio-Economic Indicators
Individuals who joined CBHI in 2011, renewed in 2012 and renewed/dropped out in 2013 PratapKanpur Vaishali All garh Dehat
0.39±0.49
0.23±0.42
0.47±0.50
0.40±0.49
0.43±0.50
0.15±0.36
0.37±0.48
0.32±0.47
0.41±0.49
0.27±0.45
0.50±0.50
0.44±0.50
Poor by MPCE (tertile 1)
0.53±0.50
0.21±0.41
0.27±0.45
0.35±0.48
0.46±0.50
0.13±0.33
0.36±0.48
0.32±0.47
0.45±0.50
0.16±0.37
0.31±0.46
0.33±0.47
Middle by MPCE (tertile 2)
0.32±0.47
0.31±0.46
0.39±0.49
0.35±0.48
0.33±0.47
0.34±0.47
0.33±0.47
0.33±0.47
0.32±0.47
0.33±0.47
0.40±0.49
0.36±0.48
Rich by MPCE (tertile 3)
0.15±0.36
0.48±0.50
0.34±0.47
0.30±0.46
0.21±0.41
0.53±0.50
0.31±0.46
0.35±0.48
0.23±0.42
0.51±0.50
0.30±0.46
0.31±0.46
344±792
298±699
Economic status
Monthly per capita financial liability
256±407
448±957
363±905
539±855
565±749
474±775
245±322
491±661
403±446
370±462
6.26±2.42
5.83±1.83
5.66±1.85
5.89±2.07 6.58±3.36 6.05±2.11 Head of Household Characteristics
5.57±1.95
6.02±2.55
6.18±3.09
5.76±1.82
5.65±1.87
5.82±2.29
Illiterate
0.35±0.48
0.28±0.45
0.46±0.50
0.39±0.49
0.36±0.48
0.24±0.43
0.45±0.50
0.36±0.48
0.34±0.48
0.24±0.43
0.47±0.50
0.40±0.49
Primary
0.18±0.38
0.13±0.34
0.18±0.39
0.17±0.38
0.14±0.35
0.17±0.38
0.13±0.34
0.15±0.35
0.18±0.38
0.05±0.22
0.18±0.38
0.16±0.36
Middle
0.18±0.38
0.16±0.37
0.14±0.34
0.16±0.36
0.13±0.33
0.21±0.41
0.18±0.38
0.17±0.38
0.12±0.33
0.24±0.43
0.14±0.35
0.15±0.36
Secondary and above
0.30±0.46
0.42±0.49
0.22±0.41
0.28±0.45
0.36±0.48
0.38±0.48
0.24±0.43
0.32±0.47
0.36±0.48
0.46±0.50
0.21±0.41
0.29±0.46
Employed in agriculture
0.23±0.42
0.66±0.47
0.17±0.38
0.28±0.45
0.27±0.45
0.59±0.49
0.25±0.44
0.36±0.48
0.16±0.37
0.66±0.48
0.33±0.47
0.31±0.46
Employed in non-agri.
0.12±0.33
0.06±0.24
0.12±0.33
0.11±0.31
0.18±0.39
0.08±0.27
0.13±0.34
0.13±0.34
0.16±0.37
0.03±0.17
0.06±0.24
0.09±0.28
Other works
0.39±0.49
0.16±0.37
0.53±0.50
0.41±0.49
0.33±0.47
0.11±0.32
0.33±0.47
0.27±0.44
0.42±0.50
0.18±0.39
0.39±0.49
0.37±0.48
Not working
0.26±0.44
0.11±0.32
0.18±0.38
0.19±0.40 0.21±0.41 0.22±0.41 Scheme Related Characteristics
0.27±0.45
0.24±0.43
0.25±0.44
0.13±0.34
0.23±0.42
0.22±0.42
0.17±0.37
0.08±0.28
0.68±0.47
0.40±0.49
0.19±0.39
0.04±0.20
0.70±0.46
0.46±0.50
Household size Years of education
Employment
Claimed in previous year (1)
Claimed in previous year (2)
0.05±0.22 0.15±0.36 Household Insurance Understanding
0.47±0.50
0.25±0.43
0.14±0.35
0.08±0.27
0.52±0.50
0.35±0.48
Insurance knowledge Below average
0.35±0.48
0.38±0.49
0.33±0.47
0.34±0.48
0.34±0.47
0.35±0.48
0.31±0.46
0.33±0.47
0.27±0.44
0.17±0.38
0.29±0.45
0.27±0.44
Above average
0.65±0.48
0.62±0.49
0.67±0.47
0.66±0.48
0.66±0.47
0.65±0.48
0.69±0.46
0.67±0.47
0.73±0.44
0.83±0.38
0.71±0.45
0.73±0.44
CBHI understanding
8
Table 3 Descriptive statistics (mean and standard deviation) Variable
Individuals who joined CBHI in 2011 and renewed/dropped out in 2012 PratapKanpur Vaishali All garh Dehat
Individuals who joined CBHI in 2012 and renewed/dropped out in 2013 PratapKanpur Vaishali All garh Dehat
Individuals who joined CBHI in 2011, renewed in 2012 and renewed/dropped out in 2013 PratapKanpur Vaishali All garh Dehat
Below average
0.54±0.50
0.24±0.43
0.45±0.50
0.44±0.50
0.63±0.48
0.61±0.49
0.62±0.48
0.39±0.49
0.31±0.47
0.57±0.50
0.48±0.50
Above average
0.46±0.50
0.76±0.43
0.55±0.50
0.56±0.50 0.36±0.48 0.37±0.48 Individual Health Events
0.39±0.49
0.38±0.48
0.61±0.49
0.69±0.47
0.43±0.50
0.52±0.50
No of long-term illnesses
0.24±0.43
0.30±0.46
0.26±0.44
0.26±0.44
0.36±0.48
0.37±0.49
0.27±0.45
0.33±0.47
0.33±0.47
0.40±0.49
0.29±0.45
0.32±0.47
No of short-term illnesses
0.25±0.44
0.24±0.43
0.26±0.44
0.25±0.44
0.36±0.48
0.35±0.49
0.40±0.52
0.37±0.50
0.37±0.48
0.52±0.52
0.36±0.48
0.38±0.49
No of hospitalization events
0.06±0.24
0.03±0.16
0.03±0.17
0.04±0.20 0.02±0.15 0.05±0.22 Other Individual Characteristics
0.04±0.20
0.04±0.19
0.05±0.22
0.02±0.14
0.03±0.17
0.03±0.18
SHG member
0.29±0.45
0.32±0.47
0.29±0.45
0.29±0.46
0.37±0.48
0.27±0.44
0.33±0.47
0.32±0.47
0.41±0.49
0.39±0.49
0.29±0.46
0.34±0.47
Age
25.9±19.0
28.2±18.0
21.7±17.1
24.3±18.1
30.6±19.5
28.3±18.7
24.4±18.2
27.4±18.9
29.4±18.4
29.0±17.7
22.3±17.7
25.4±18.2
Male
0.44±0.50
0.43±0.50
0.43±0.50
0.43±0.50
0.39±0.49
0.47±0.50
0.38±0.49
0.41±0.49
0.34±0.47
0.37±0.49
0.39±0.49
0.37±0.48
Married
0.47±0.50
0.55±0.50
0.41±0.49
0.46±0.50
0.56±0.50
0.50±0.50
0.49±0.50
0.51±0.50
0.59±0.49
0.54±0.50
0.45±0.50
0.50±0.50
Self
0.22±0.41
0.25±0.43
0.20±0.40
0.21±0.41
0.27±0.45
0.23±0.42
0.23±0.42
0.24±0.43
0.27±0.44
0.27±0.45
0.21±0.41
0.24±0.43
Spouse of head
0.19±0.39
0.26±0.44
0.17±0.38
0.19±0.40
0.25±0.43
0.23±0.42
0.23±0.42
0.23±0.42
0.26±0.44
0.30±0.46
0.19±0.39
0.23±0.42
Child of head
0.42±0.49
0.41±0.49
0.52±0.50
0.47±0.50
0.29±0.45
0.41±0.49
0.41±0.49
0.37±0.48
0.36±0.48
0.40±0.49
0.44±0.50
0.41±0.49
Others
0.17±0.37
0.09±0.28
0.12±0.32
0.13±0.33
0.20±0.40 0.13±0.34 Subscription to RSBY
0.13±0.34
0.15±0.36
0.12±0.32
0.02±0.14
0.15±0.36
0.12±0.33
Household enrolled in RSBY
0.12±0.33
0.32±0.47
0.43±0.49
0.31±0.46 0.33±0.47 0.68±0.47 Access to Health Facilities
0.71±0.46
0.58±0.49
0.38±0.49
0.56±0.50
0.73±0.44
0.60±0.49
Travel time for inpatient service
49.9±41.2
130±95.9
37.1±32.3
58.9±63.3
42.3±28.9
123.±72.7
30.4±30.2
60.8±61.1
40.7±23.4
132.±77.7
35.4±33.3
51.1±52.9
Travel time for outpatient service Observations
23.0±22.2
32.0±24.7
19.0±27.9
22.8±26.0
18.2±11.6
24.9±27.4
15.9±17.6
19.2±19.9
15.9±10.6
19.2±22.7
14.0±11.8
15.3±13.8
545
314
806
1665
419
386
534
1339
194
99
381
674
0.64±0.48
Relationship to head of household
9
Thus, the probability of renewing membership in the CBHI schemes may be written as: 𝑅𝐸𝑁𝐸𝑊𝑖ℎ𝑡 = 𝛼 ′ 𝑆𝐸𝑆 ℎ𝑡−1 + 𝛽 ′ 𝑆𝑈𝑖ℎ𝑡−1 + 𝛾 ′ 𝐾𝑈ℎ𝑡−1 + 𝛿 ′ 𝐻𝐸𝑖ℎ𝑡−1 + µ′ 𝐴𝐶ℎ𝑡−1 + 𝜀𝑖ℎ𝑡 .
(1)
Marginal effects based on a logit specification of (1) are estimated for each of the three schemes separately and also for the pooled data. We provide three sets of estimates of equation (1). These correspond to individuals who joined the CBHI schemes in 2011 and renewed or dropped out in 2012 (or those who joined in 2012 and dropped out in 2013) and those who stayed in the scheme for two years, that is, joined in 2011 and renewed/dropped out in 2013. Estimates for those who were followed for one year are provided in Table 4 and those who were followed for two years is presented in Table 5. Instead of estimating a logit model for each of these sub-samples, at least for those who joined the scheme in 2011, it is also possible to estimate an ordered logit model to estimate the probability of staying in the scheme for one, two or three years. However, such an approach is perhaps rather restrictive as the role played by different variables in determining renewal may change over time. Hence, we persist with a standard logit model.
Data Analysis of the factors that determine renewal is based on combining information from three household surveys with information on enrolment, renewal, premium payments and claims obtained from MIA’s Management Information System (MIS). The three household surveys were conducted between March and May of 2010, 2012 and 2013. The first survey covered 3685 households of which 3318 were resurveyed in 2012 and 3307 were revisited in 2013. In all, 3034 households were covered in all three survey rounds. The survey gathered information on various socio-economic indicators, including demographic details of each household member, household consumption expenditures, and household assets. Data were collected on self-reported illness events for a 30-day recall period and for hospitalization or pregnancy in the 12 months, preceding the survey. Information was also gathered on the treatment sought for illnesses and expenditure incurred. A detailed module was used to obtain information on understanding of insurance and knowledge of the CBHI schemes. The analysis is based on individuals who enrolled in the scheme in 2011 and in 2012.
10
Table 4 Logit regression marginal effect estimates (standard errors) (Renewal / drop out after one year in CBHI) Individuals who joined CBHI in 2011 and Individuals who joined CBHI in 2012 and renewed/dropped out in 2012 renewed/dropped out in 2013 Variable Kanpur Kanpur Pratapgarh Vaishali All Pratapgarh Vaishali All Dehat Dehat Household Socio-Economic Indicators Schedule caste/Schedule tribe 0.0792 0.0140 0.0297 0.0468 -0.0272 0.156 0.0786 0.0675 Economic status - Middle by MPCE (tertile 2) Economic status - Rich by MPCE (tertile 3) Monthly per capita financial liability Household size Head of Household Characteristics Years of education - primary
Years of eductaion - middle Years of education - secondary & above Occupation - employed in agriculture Occupation - employed in non-agriculture Occupation - other works
Scheme Related Characteristics Claimed in previous year Household Insurance Understanding Insurance knowledge - Above average CBHI understanding - Above average
(0.0818) 0.0571 (0.0899) 0.0981 (0.113) -1.78e-06 (9.46e-05) 0.00161 (0.0144)
(0.114) 0.110 (0.148) -0.00247 (0.137) -0.000154* (8.55e-05) 0.0167 (0.0327)
(0.0728) -0.0976 (0.0804) -0.0359 (0.0989) 8.13e-06 (2.76e-05) -0.0141 (0.0207)
(0.0470) -0.0182 (0.0533) 0.0168 (0.0621) -1.74e-05 (3.14e-05) -0.00351 (0.0108)
(0.0698) -0.0366 (0.0778) 0.0510 (0.104) -7.72e-05 (6.28e-05) -0.00133 (0.0121)
(0.142) 0.161 (0.181) 0.321** (0.148) -9.69e-06 (5.34e-05) -0.00934 (0.0236)
(0.0761) 0.0336 (0.0908) 0.181* (0.0965) -5.37e-06 (3.81e-05) 0.0331* (0.0190)
(0.0504) 0.0304 (0.0590) 0.170*** (0.0629) -1.38e-05 (2.54e-05) 0.00576 (0.00991)
-0.00135 (0.126) -0.000943 (0.119) 0.0753 (0.107) -0.0995 (0.105) -0.191* (0.101) -0.0295 (0.102)
-0.00816 (0.151) 0.337** (0.171) -0.0299 (0.130) 0.170 (0.120) 0.364 (0.273) 0.325 (0.201)
-0.0317 (0.0952) -0.0333 (0.0961) -0.0712 (0.0948) -0.0682 (0.116) -0.286** (0.119) -0.164* (0.0899)
-0.0243 (0.0650) 0.0675 (0.0651) -0.00761 (0.0587) -0.0416 (0.0649) -0.143* (0.0814) -0.0576 (0.0604)
-0.0967 (0.0848) -0.0227 (0.0981) 0.0712 (0.0852) 0.113 (0.123) 0.0114 (0.109) 0.120 (0.117)
-0.0692 (0.156) -0.107 (0.140) 0.0952 (0.144) -0.273** (0.124) -0.00170 (0.180) -0.180 (0.153)
-0.116 (0.0867) 0.0223 (0.0945) 0.249** (0.103) -0.0606 (0.0909) 0.0772 (0.129) -0.00754 (0.100)
-0.0578 (0.0682) -0.0107 (0.0623) 0.149** (0.0613) -0.0353 (0.0608) 0.0503 (0.0790) -0.0170 (0.0632)
0.145 (0.121)
-0.142 (0.152)
0.129* (0.0687)
0.0724 (0.0529)
0.278 (0.204)
0.191 (0.152)
0.428*** (0.0627)
0.345*** (0.0590)
-0.0336 (0.0829) 0.0606
0.0323 (0.107) -0.0905
0.0511 (0.0740) -0.0720
0.0389 (0.0472) -0.0205
0.177*** (0.0569) 0.0408
0.0103 (0.112) 0.0693
0.0285 (0.0832) 0.248***
0.0799 (0.0487) 0.144***
11
Table 4 Logit regression marginal effect estimates (standard errors) (Renewal / drop out after one year in CBHI) Individuals who joined CBHI in 2011 and Individuals who joined CBHI in 2012 and renewed/dropped out in 2012 renewed/dropped out in 2013 Variable Kanpur Kanpur Pratapgarh Vaishali All Pratapgarh Vaishali Dehat Dehat Individual Health Events Health events - No of long-term illness events Health events - No of short-term illness events Health events - No of hospitalization events Other Individual Characteristics Individual is SHG member Age
Male Married Relation to head - Self Relation to head - Spouse of head Relation to head - Child of head
Subscription to RSBY Household enrolled in RSBY Access to Health Facilities Average travel time for inpatient service Average travel time for outpatient service
All
(0.0794)
(0.116)
(0.0656)
(0.0458)
(0.0792)
(0.109)
(0.0739)
(0.0466)
0.133** (0.0598) 0.0873 (0.0563) -0.126 (0.102)
-0.0346 (0.0755) 0.0256 (0.0736) -0.111 (0.209)
0.0328 (0.0522) -0.000403 (0.0453) 0.0806 (0.105)
0.0423 (0.0336) 0.0499 (0.0319) -0.0381 (0.0667)
0.0478 (0.0547) -0.0844* (0.0451) -0.126* (0.0688)
-0.147** (0.0710) -0.0448 (0.0651) -0.121 (0.124)
0.0165 (0.0646) 0.0978** (0.0487) 0.00849 (0.110)
-0.00749 (0.0370) -0.00441 (0.0303) -0.146** (0.0566)
0.159** (0.0773) 0.00393 (0.00254) -0.0325 (0.0558) 0.147** (0.0714) -0.134 (0.0954) -0.127 (0.100) 0.0766 (0.0970)
0.156 (0.125) 0.00134 (0.00304) -0.0635 (0.0695) -0.372** (0.146) 0.314 (0.211) 0.201 (0.204) -0.0838 (0.108)
0.190** (0.0743) -0.00303 (0.00235) 0.00458 (0.0407) 0.133 (0.0893) -0.306*** (0.0993) -0.392*** (0.0985) -0.241*** (0.0822)
0.165*** (0.0457) 0.00102 (0.00150) -0.0288 (0.0308) 0.0193 (0.0499) -0.116* (0.0624) -0.181*** (0.0636) -0.0805 (0.0580)
0.0307 (0.0677) -0.000237 (0.00205) -0.0126 (0.0527) -0.108 (0.0702) 0.161 (0.110) 0.166 (0.128) -0.0665 (0.0661)
0.353*** (0.0857) -0.00834** (0.00327) 0.00476 (0.0780) -0.0326 (0.103) 0.417*** (0.144) 0.208 (0.177) 0.0888 (0.119)
0.237*** (0.0719) 0.00188 (0.00294) 0.00630 (0.0623) -0.00984 (0.100) 0.00263 (0.133) -0.0493 (0.124) -0.00515 (0.111)
0.208*** (0.0471) -0.00147 (0.00147) 0.0121 (0.0375) -0.0451 (0.0513) 0.139* (0.0799) 0.0668 (0.0814) -0.00424 (0.0570)
-0.0537 (0.114)
-0.145 (0.106)
-0.0453 (0.0686)
-0.0378 (0.0485)
-0.110* (0.0638)
0.202** (0.100)
-0.00443 (0.0801)
-0.0148 (0.0495)
0.000734 (0.000844) 0.00116
-0.000831 (0.000656) -0.00477**
0.00209** (0.00101) 0.000216
-0.000161 (0.000413) -0.000181
-0.000358 (0.00117) -0.000798
0.000793 (0.000687) -0.00315
-0.00103 (0.00120) -0.00663**
0.000492 (0.000519) -0.00393*
12
Table 4 Logit regression marginal effect estimates (standard errors) (Renewal / drop out after one year in CBHI) Individuals who joined CBHI in 2011 and Individuals who joined CBHI in 2012 and renewed/dropped out in 2012 renewed/dropped out in 2013 Variable Kanpur Kanpur Pratapgarh Vaishali All Pratapgarh Vaishali Dehat Dehat (0.00155)
(0.00240)
(0.000990)
Locational Characteristics Pratapgarh
(0.00295)
(0.00251)
(0.00290)
0.0233 (0.0780) 0.143* (0.0808)
Vaishali Observations Pseudo R-Square Note: ***P
