Analysis of Claims and Reimbursements made under Mediclaim Policy of the General Insurance Corporation of India

Mediclaim insurance run by government owned insurance company General Insurance Corporation of India (GIC) is the only private voluntary health insurance scheme available in India currently. This scheme has been in operation since 1986 and from time to time a number of revisions have been carried out to address the needs of their clients. The documentation on claims and reimbursement of this scheme is scanty. This paper analyses 621 claims and reimbursements data pertaining to policy initiation years 1997-98 and 1998-99 of Ahmedabad branch of one of the subsidiary companies of the General Insurance Corporation of India. The analysis suggests that the number of policies and premiums collected have grown at significant rates, more than 30 per cent during 1998-99 and 50 per cent during the year 1999-00. The growth had implications for the management of scheme in terms of problems of adverse selection or provider induced demand and falling premiums per insured person. It was found that the number of claims increased by about 93 per cent during the year 1998-99 when polices sold grew at 32 per cent. The study estimates that about 1/3rd of claim amount increase is because of the problems of adverse selection or provider induced demand. The analysis of break-up of reimbursements suggests that about 40 per cent of reimbursements are made towards doctors fees. This is followed by diagnostic charges, which accounts for about 30 per cent. This makes the insurance claims highly vulnerable to provider-induced use of resources. The findings also suggest that the insurance company took on an average 121 days to settle the claim. It is pointed out given the demand side and supply side imperfections in the healthcare markets and absence of appropriate regulatory mechanisms in place, the Insurance and Development Regulatory Authoritys proposal to ensure payment settlement within 7 days is highly ambitious. The study also analyses reasons for the delay and cases where reimbursements have been less than claims submitted.

Hospital Efficiency: An Empirical Analysis of District and Grant-in-Aid Hospitals in Gujarat

This study focuses on analysing the hospital efficiency of district level government hospitals and grant-in-aid hospitals in Gujarat. The study makes an attempt to provide an overview of the general status of the health care services provided by hospitals in the state of Gujarat in terms of their technical and allocative efficiency. One of the two thrusts behind addressing the issue of efficiency was to take stock of the state of healthcare services (in terms of efficiency) provided by grant-in-aid hospitals and district hospitals in Gujarat. The motivation behind addressing the efficiency issue is to provide empirical analysis of governments policy to provide grants to not-for-profit making institutions which in turn provide hospital care in the state. The study addresses the issue whether grant-in-aid hospitals are relatively more efficient than public hospitals. This comparison between grant-in-aid hospitals and district hospitals in terms of their efficiency has been of interest to many researchers in countries other than India, and no consensus has been reached so far as to which category is more efficient. The relative efficiency of government and not-for-profit sector has been reviewed in this paper. It is expected that the findings of the study would be useful to evaluate this policy and help policy makers to develop benchmarks in providing the grants to such institutions.

Cost drivers for voluntary medical male circumcision using primary source data from sub-Saharan Africa.

BACKGROUND:As voluntary medical male circumcision (VMMC) programs scale up, there is a pressing need for information about the important cost drivers, and potential efficiency gains. We examine those cost drivers here, and estimate the potential efficiency gains through an econometric model. METHODS AND FINDINGS:We examined the main cost drivers (i.e., personnel and consumables) associated with providing VMMC in sub-Saharan Africa along a number of dimensions, including facility type and service provider. Primary source facility level data from Kenya, Namibia, South Africa, Tanzania, Uganda, and Zambia were utilized throughout. We estimated the efficiency gains by econometrically estimating a cost function in order to calculate the impact of scale and other relevant factors. Personnel and consumables were estimated at 36% and 28%, respectively, of total costs across countries. Economies of scale (EOS) is estimated to be eight at the median volume of VMMCs performed, and EOS falls from 23 at the 25th percentile volume of VMMCs performed to 5.1 at the 75th percentile. CONCLUSIONS:The analysis suggests that there is significant room for efficiency improvement as indicated by declining EOS as VMMC volume increases. The scale of the fall in EOS as VMMC volume increases suggests that we are still at the ascension phase of the scale-up of VMMC, where continuing to add new sites results in additional start-up costs as well. A key aspect of improving efficiency is task sharing VMMC procedures, due to the large percentage of overall costs associated with personnel costs. In addition, efficiency improvements in consumables are likely to occur over time as prices and distribution costs decrease

Predicted average and marginal cost of VMMC programs.

<p>Red square: Average cost. Blue diamond: Marginal cost.</p

Descriptive statistics for regression variables by country: Averages and (standard deviations).

<p>All costs are in 2012 US$ and adjusted to the sub-Saharan Africa region using the ratio of the country PPP-adjusted GNI per capita to the region PPP-adjusted GNI per capita.</p

Components of unit costs, by country and selected characteristics.

<p>All figures are in percentages except those in the first row, which are in 2012 US$ and PPP-adjusted to the sub-Saharan Africa region.</p

Predicted economies of scale of VMMC programs.

<p>Blue diamond: predicted economies of scale.</p

Cost function estimate.

<p>Source: Authors' calculations.</p