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EFFECTS OF INTERVENTIONS TO RAISE VOLUNTARY ENROLLMENT IN A SOCIAL HEALTH INSURANCE SCHEME IN THE PHILIPPINES
Last registered on December 22, 2019

Pre-Trial

Trial Information
General Information
Title
EFFECTS OF INTERVENTIONS TO RAISE VOLUNTARY ENROLLMENT IN A SOCIAL HEALTH INSURANCE SCHEME IN THE PHILIPPINES
RCT ID
AEARCTR-0004977
Initial registration date
Not yet registered
Last updated
December 22, 2019 10:13 AM EST
Location(s)
Primary Investigator
Affiliation
University of the Philippines
Other Primary Investigator(s)
PI Affiliation
University of the Philippines
PI Affiliation
University of the Philippines
PI Affiliation
World Bank
PI Affiliation
University of the Philippines
Additional Trial Information
Status
Completed
Start date
2011-02-01
End date
2012-05-31
Secondary IDs
Abstract
In this study, we present evidence from two randomized experiments conducted in the Philippines, where the informal sector remains the population group with the lowest health insurance coverage rate, despite numerous initiatives. One of our objectives is to see how far voluntary enrollment in a government-run SHI program responds to information and premium subsidies, because cost and lack of information about how the program works are obvious reasons why a family may choose not to enroll. Another objective is to see how far non-enrollment among families given information and offered a premium subsidy might be because of the transactions costs – broadly defined – associated with enrollment.

A cluster randomized experiment was undertaken testing two sets of interventions encouraging enrollment in the Individually Paying Program (IPP), the voluntary component of the Philippines’ social health insurance program (also known as PhilHealth). In early 2011, 1037 unenrolled IPP-eligible families in 179 randomly selected intervention municipalities were given an information kit and offered a 50% premium subsidy valid until the end of 2011; 383 IPP-eligible families in 64 control municipalities were not. In February 2012, the 787 families in the intervention sites who were still IPP-eligible but had not enrolled had their vouchers extended, were resent the enrollment kits and received SMS reminders. Half the group also received a ‘handholding’ intervention: in the endline interview, the enumerator offered to help complete the enrollment form, deliver it to the insurer’s office in the provincial capital, and mail the membership card.

Our main experiment tested the effectiveness, in terms of its impact on enrollment in the voluntary government-run Individually Paying Program (IPP), of a combination of information and a 50% premium subsidy. We found that the intervention raised enrollment by three percentage points (37%), but the effect is not quite significant at the 10% level (p = 0.11). We found no evidence of adverse selection: households experiencing an adverse health event in the 12 months before the baseline survey were no more (or less) likely to enroll after receiving the information and being offered the subsidy. We did, however, find a significantly larger (p = 0.00) effect among city-dwellers (the marginal effect in this group was nine percentage points (p = 0.00)) which we argue is consistent with this group facing lower transport costs to the provincial health insurance agency office where enrollment takes place.

Shortly before the end of the main experiment we planned a sub-experiment on those who had been given the information package and the offer of a 50% subsidy but after 9–10 months had still chosen not to enroll. In the control group we extended the voucher and resent the information package. In the intervention group, we provided a package of measures that drastically reduced the amount of effort a family has to make to enroll. This group received assistance in person at their home in completing the enrollment form, had their form delivered to the insurance agency office for them, and had their membership card mailed to them.

Compared to the control group, the intervention group recorded a 29 percentage point increase in enrollment, significant at less than the 1% level (p = 0.00). In this case, we found a significantly smaller (p = 0.00) (but still significant (p = 0.00)) impact among city-dwellers. We argue this is consistent with city-dwellers finding this second intervention less valuable than rural households, given their greater proximity to the health insurance agency office, and their greater ability to complete unaided a health insurance enrollment form because of their higher educational attainment (in our sample 19% of urban households have a college-educated household head; only 9% of rural households do).
External Link(s)
Registration Citation
Citation
Capuno, Joseph et al. 2019. "EFFECTS OF INTERVENTIONS TO RAISE VOLUNTARY ENROLLMENT IN A SOCIAL HEALTH INSURANCE SCHEME IN THE PHILIPPINES." AEA RCT Registry. December 22. https://doi.org/10.1257/rct.4977-1.1.
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Experimental Details
Interventions
Intervention(s)
Intervention I comprises an insurance voucher, an information kit, and several SMS messages. Valid for 11 months initially and worth 600 pesos (US$13.66), the voucher pays for 50% (or 25% if the individual’s average monthly family income is greater than 25 000 pesos) of the annual insurance premium. The kit includes a PhilHealth membership application form, a membership data record form, and leaflets covering enrollment, insurance claims, and various frequently asked questions. During the voucher’s validity period, SMS reminders are sent by the study team at regular intervals to the households reminding them to submit their completed application forms and vouchers to a local PhilHealth office, to pay the balance of their premiums, and to take advantage of their benefit entitlements as SHI beneficiaries.

Intervention II involves re-sending (by mail) the membership application forms, along with letters and SMS messages from the study team saying that the voucher’s validity is extended up to the end of February 2012.

Intervention III involves the enumerator visiting the family for the endline survey offering to help the family complete the application form. The letters that were sent to those eligible for Intervention III also mentioned that the vouchers remain valid during the period March–May 2012. The completed form is then sent to PhilHealth, and the family’s IPP membership card is sent by mail to the family.

In the main experiment, households in the control sites do not receive Intervention I.
Intervention Start Date
2011-02-01
Intervention End Date
2012-05-31
Primary Outcomes
Primary Outcomes (end points)
Enrollment in PhilHealth’s Individually Paying Program (IPP)
Primary Outcomes (explanation)
The primary outcome for those who received intervention I (voucher, information kit and SMS reminders) in the main experiment was initially measured from a list data obtained from PhilHealth in 2011. Their enrollment status and that of the rest of the participants were finally measured using the results of the endline survey.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We sought to obtain experiment participants from a random sample of households that is representative at the national level excluding the conflict area of Autonomous Region of Muslim Mindanao. To achieve this, we obtained a random sample of 2950 households distributed in 590 ‘barangay’ (sub-municipality) clusters distributed across most of the Philippines. The sample households were obtained using a multi-stage cluster design. First, we stratified by broad regions (5: the National Capital Region, North-Central Luzon, South Luzon, Visayas, and Mindanao). From the broad regions, we then selected specific regions (15) using proportionate sampling. Provinces (62 out of 80) were drawn using systematic sampling. From these provinces, municipalities and cities (243 out of 1395) and the barangays (590 out of 37 165) within these municipalities and cities were likewise selected using systematic sampling. Finally, for each barangay cluster we drew five households using simple random sampling
.
In our main experiment, three quarters of the sampled municipalities within each broad region were assigned via randomization as treatment sites; the rest became control sites. The municipality of the sample household (rather than the barangay or household) was selected as the unit for the experimental cluster to reduce the risk of contamination between the treatment and control groups: treatment households could have more easily passed on the details of the information leaflets to households in the control group. We interviewed, on average, 12 households per municipality.

All sampled households in the intervention sites who were eligible for the IPP program (Group I) were given the first intervention; sampled households in the control sites, including those who are IPP-eligible (Group II), were not. We considered households eligible for IPP if the household head or the spouse claims not to be covered is unsure whether the family is covered, or claims to be covered but has not paid a premium in the preceding six months (the PhilHealth criterion to be considered an active member). Households in Group I who had still not enrolled by January 2012 (9–11 months after the baseline survey – became the sample for our sub-experiment (Group III). This sub-experiment was at the household level, not the municipality level.

Power calculations were done with a view to the main experiment only. We fixed the sampling of municipalities and households within municipalities to achieve at least 80% power at the 5% level to detect enrollment rate increases (compared to the control group rate of 10%) of 7.5 percentage points in the main experiment. This effect was chosen because it was felt to be the minimum impact that might be considered meaningful from a policy perspective; a 50% subsidy combined with an information packet is a serious policy effort, and an effect of less than 7.5 percentage points would raise serious questions about their usefulness as a mechanism to help achieve UHC. In our calculations, we assumed a PhilHealth overall coverage rate of 53% and an IPP-coverage rate of 33%2 a standard deviation in the enrollment rate of 0.25, an intra-cluster correlation coefficient (ICC) of 0.16 (the municipality is our cluster), and a ratio of intervention to control households of just under 3 (we have 243 municipalities in total of which 179 were assigned to the intervention group).

On these assumptions, we could, in fact, have sampled fewer municipalities and fewer households and still achieved 80% power to detect a 7.5 percentage point effect. Or equivalently with our sample we could detect a somewhat smaller effect with 80% power: we could reduce the target effect to 7.25 percentage points and still have 80% power; below 7.25, the number of municipalities in the intervention group becomes too small. We chose to sample so many municipalities and so many households per municipality in part because we were uncertain how many sampled households would be IPP-eligible. In the event we sampled slightly more households than necessary to achieve 80% power given our assumptions.

The full sample at baseline is 2950 households. By design three quarters of these live in intervention municipalities. Of these, 1183 (53.3%) proved ineligible for the experiment, already being an IPP member or in another PhilHealth scheme. (The fraction of the sample with some form of PhilHealth coverage already was somewhat lower in the control group: 47.5%.)

The 1037 eligible families in the intervention sites (referred as Group I) were offered Intervention I sometime during the period February–April 2011; the 383 IPP-eligible families in the control sites (referred as Group II) were not. Of the 918 families in Group I who – as of January 2012 – had not enrolled in the IPP scheme, 787 were still eligible for IPP, not having moved during the course of 2011 to another PhilHealth target group, e.g. becoming a formal-sector worker or becoming eligible for the indigent scheme. These families (referred as Group III) were randomly assigned into two groups, with 392 receiving Intervention II only, and 395 receiving both Interventions II and III.
Experimental Design Details
Randomization Method
The sample municipalities were randomly assigned as intervention or control sites by the study team in office by computer.
Randomization Unit
Municipality
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
243 municipalities
Sample size: planned number of observations
2950 individuals (household head or spouse)
Sample size (or number of clusters) by treatment arms
179 municipalities treatment,
64 municipalities control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Minimum detectable effect size for main outcome in the main experiment (accounting for sampling design and clustering) is 7.5 percentage points.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Committee on Human Research, UPecon Foundation, Inc.
IRB Approval Date
2010-10-01
IRB Approval Number
Institutional Review Board Approval (Dated 11 October 2010)
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
Yes
Intervention Completion Date
May 31, 2012, 12:00 AM +00:00
Is data collection complete?
Yes
Data Collection Completion Date
May 31, 2012, 12:00 AM +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
243 municipalities
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
Main experiment: Final sample size is 1420
Sub-experiment: Final sample size is 787
Final Sample Size (or Number of Clusters) by Treatment Arms
Main experiment: 1037 treatment participants (given Intervention I), 383 control participants Sub-experiment: 395 treatment participants (given Interventions II and III), 392 control participants (given Intervention II only)
Data Publication
Data Publication
Is public data available?
No

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Program Files
Program Files
No
Reports, Papers & Other Materials
Relevant Paper(s)
Abstract
A cluster randomized experiment was undertaken testing two sets of interventions encouraging enrollment in the
Individually Paying Program (IPP), the voluntary component of the Philippines’ social health insurance program. In
early 2011, 1037 unenrolled IPP-eligible families in 179 randomly selected intervention municipalities were given an
information kit and offered a 50% premium subsidy valid until the end of 2011; 383 IPP-eligible families in 64 control
municipalities were not. In February 2012, the 787 families in the intervention sites who were still IPP-eligible but had
not enrolled had their vouchers extended, were resent the enrollment kits and received SMS reminders. Half the group
also received a ‘handholding’ intervention: in the endline interview, the enumerator offered to help complete the
enrollment form, deliver it to the insurer’s office in the provincial capital, and mail the membership cards. The main
intervention raised the enrollment rate by 3 percentage points (ppts) (p = 0.11), with an 8 ppt larger effect (p<0.01)
among city-dwellers, consistent with travel time to the insurance office affecting enrollment. The handholding
intervention raised enrollment by 29 ppts (p<0.01), with a smaller effect (p<0.01) among city-dwellers, likely
because of shorter travel times, and higher education levels facilitating unaided completion of the enrollment form.
Citation
Capuno, J. J., Kraft, A. D., Quimbo, S., Jr. Tan, C. R., and Wagstaff, A. (2016) Effects of price, information, and transactions cost interventions to raise voluntary enrollment in a social health insurance scheme: a randomized experiment in the Philippines. Health Economics, 25(6), 650–662.
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