The Centre had launched the Pradhan Mantri Jan Arogya Yojana (PMJAY) in September last year as a step towards providing universal health coverage.

In the first six months of its roll-out, questions were raised by sections of public health experts, economists and doctors on the efficiency of the scheme.

At an event two months ago at the All India Institute of Medical Sciences, several doctors too expressed reservations on the scheme, some calling it “old wine in a new bottle”, others wondered if it was a channel for public money to go into private hands and still others urged the government to improve and strengthen public health infrastructure since direct Government services were a better option than insurance.

Nobel Laureate and economist Amartya Sen too had argued that the scheme neglected primary healthcare.

Given the scrutiny the programme receives, the Government needs to share data on the performance of such schemes to put to rest doubts on its efficiency.

For instance, data sharing and analytics could help in assessing the percentage of claims approved and rejected and the reasons thereof. Given that premiums paid by the government to the insurers are much lower in PMJAY than market rate for equivalent health insurance schemes, insurers may be rejecting claims due to financial unviability. These metrices should be measured at hospital, region and State-level to compare performances.

The National Health Agency recently roped in five data analytical firms for pro-active fraud detection. Instead, the government could itself start measuring and reporting the amount of claims submitted by hospitals and families, which is the starting metric to look at frauds.

Measuring care provided

Additionally, it should start measuring the quality of care provided by empanelled hospitals. Quality could be measured in terms of structure, process and outcome, all taken together. Structural measures such as ratio of providers to patients or whether they use electronic medical records give a sense of the healthcare provider’s capacity to provide high-quality care.

Process measures indicate what a provider does to maintain or improve health. These measures inform customers about medical care they may expect to receive for a particular condition or disease.

Outcome measures reflect the impact of service provided or intervention done on the health status of patients. Rate of surgical complications or hospital-acquired infections or percentage of patients who died as a result of surgery are some important metrics under the outcome measures that must be measured and reported at hospital-level.

The process map for availing care under PMJAY also mentions getting beneficiary feedback at the time of claim settlement.

Looking at the beneficiary feedback along with the performance metrices will provide a 360-degree view of the scheme’s operations and also opportunities to pro-actively address issues in real time.

Another challenge in the current scenario is that we have different insurers in various cities and States.

This has restricted the mobility of patients in getting treatment outside of their home State. This scenario is not uncommon given the volume of patients referred every day from small towns to metropolitan cities. This problem can be avoided if the scheme establishes an advanced data analytics framework, enabled to track movement requests by patients so that premiums could be transferred. These measures could be published regularly to help assess the performance of the scheme. The Centers for Medicare and Medicaid Services (CMS), a federal agency of the US Department of Health and Human Services, shares a variety of data on its website to facilitate better decision-making by patients in choosing a hospital or provider.

India has a long way to go, from merely sharing individual success stories on the website to sharing detailed data leading to advanced data analytics. This will help provide detailed insights to the public, thereby enabling them to make informed choices about their health.

Goel is Assistant Professor in the Jindal School of Banking and Finance and Sharan is a senior data scientist at Optum Global Solutions, a part of the US-based UnitedHealth Group.

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