1. Making mortality data more meaningful

Making mortality data more meaningful

Recording the causes of mortality and using that data to drive public health interventions like drug and vaccine procurement, running screening and awareness campaigns, and providing secondary and tertiary care under health insurance schemes can help public health achieve better outcomes.

By: | New Delhi | Published: May 22, 2018 3:36 AM
mortality data, mortality rate
The most important change can be aligning funds with trends and mortality and morbidity outcomes.

Epidemiological findings from morbidities and mortalities play an important role in health policy. Information of total deaths or “all-cause mortality” are helpful in getting a broad understanding of the overall disease pattern and health of the population, as well as strengths of health systems. This helps in a detailed understanding of mediating mechanisms and factors that caused or prevented the deaths. Both these factors have great implication for public health and are one of the biggest tools for developing understanding of disease burden and mortality of the population.

In 1660s, John Graunt, a layperson interested in understanding mortality data of London, analysed the causes of deaths in London from burial records in various churches. This analysis of causes of mortality was published titled “Bills of Mortality of London.” Such mortality analysis was done weekly and summed up annually every year in those periods. Such analysis of cause of mortality helped tremendously to improve public health in London and later on in Europe. In India, no urban body produces any annual report on causes of death like the Bills of Mortality of London did, yet. That can and should change.

Disease incidence data is currently only available from public health facilities, and that too is not compiled well by cause and never made public. There is almost no data from the private sector on hospital days, inpatient days, drug and vaccine consumption, as per different procedures. Outpatient data from the private sector is a far cry when government hospital data is not properly available. Several states have started insurance-based healthcare delivery schemes to plug the shortage of doctors and facilities in rural areas. Such schemes have data captured for all the empanelled hospitals under the scheme, including from empanelled private hospitals, which, if analysed periodically, can help understand the causes of morbidity and mortality. However, it would be a fraction of all the data with private hospitals in those states. Some data is also available with cancer registries, which can help define protocols and campaigns for early screening and interventions for cancer, for which treatment is also expensive.

In addition, it is necessary to integrate all the databases currently available with health departments across the country. Each scheme has its own database. New scheme has new database. Hence, the data does not link to each other, there is no standard taxonomy or coding of the various fields or variables, and there is no data triangulation. As a result, different databases have different variables, which are not standardised. Substantial funds are spent on capturing data under each scheme, which leads to duplication, and no effort is made to build a common, publicly-accessible database. For example, public health, women and child, social justice and tribal departments should be using the same set of variables for data compilation. Any scheme that offers benefits or cash incentives can be linked to the common database and should be in public domain for increased transparency. Now, Aadhaar number can help, like various records of the same individual across departments and same department over time.

It is also important to have a national grid of all data with common fields, and there is an urgent need to build that data architecture now more than ever before—with the imminent roll-out of the largest-ever insurance-based healthcare scheme in the country, we have an opportunity to build this data architecture. Employment State Insurance Scheme (ESIS), Rashtriya Swasthya Bima Yojna (RSBY), Central Government Health Scheme (CGHS), Railways, central PSUs, LIC of India, government insurance companies … all have a large number of beneficiaries and data which is never made public, or used, for public policy-making.

There is no uniform system for death registration based on state-level laws in the country. This needs to be streamlined and improved in implementation. Even in advanced states such as Gujarat, Kerala, Maharashtra and Tamil Nadu, the cause of death is not mentioned correctly, and many a time it is left blank. There is no analysis done and data is not published. As a result, death certificates are issued only for administrative purposes. As causes are neither recorded nor analysed, there is little public health purpose served by recording death registration.

The most important change can be aligning funds with trends and mortality and morbidity outcomes. We can have village- and block-level profiles of morbidity and mortality by cause of death, which can form the basis for budget allocations. It is time we moved away from state plans to village plans, and also target delivery and outcomes using village/block as a unit. The gains of following such a methodology shall be a targeted approach to real numbers, with village panchayats as the pivot around which all delivery of programmes will revolve. Experience from developed countries in Asia and other parts of the globe do show that such targeted approaches based on data are far more effective.

India is a huge subcontinent. The population estimate for 2030 is 1.5 billion, and 60% will be in the average age group of 29 years, compared to 35 years in China and 48 years in Japan. India is moving towards a decade of huge demographic dividend due to its youth population. The other side is the growing burden of non-communicable diseases in an ageing population. It is very important to guide people towards a healthy lifestyle to contain the spread of non-communicable, chronic and lifestyle diseases due to the increase in lifespan. In addition, there is increased lifespan of women, both in rural and urban areas of the country, and this will require public health interventions for better access to quality healthcare. Recording all-cause mortality and using that data to drive public health interventions like drug and vaccine procurement, running screening and awareness campaigns, and providing secondary and tertiary care under health insurance schemes can help public health departments across the country to use evidence for priority setting. Time is ripe to roll out reforms that are long overdue and very much required for improving the health of the nation.

By Sujata Saunik and Dileep Mavalankar. Saunik, an IAS officer and former public health secretary Maharashtra, is currently at Harvard University. Dr Mavalankar is director, Indian Institute of Public Health Gandhinagar. Views are personal

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