Towards a Data-driven Public Health System

Changing Paradigm of Public Health

Over the last few decades, the public health system has undergone many changes. With the use of technology, huge volumes of data get generated at the health facilities every day. There has been an increased acceptance among the global health community that data can play a big role in influencing health policy.

In a country like India, where myriad problems plague the public health system, the availability of quality data can really make a difference. It can direct the scare resources towards the right problem at the right time. Based on the evidence, the public health programmes can be made more target-oriented.

HMIS and MCTS

In India, the Health Management Information System (HMIS) and the Mother and Child Tracking System (MCTS) are two primary sources of public health data. HMIS was launched in 2008 by the Ministry of Health & Family Welfare (MoHFW) to meet the growing demand of micro-level data on population and health for use in monitoring, planning and programme implementation. Currently, around 1.79 lakh health facilities are reporting monthly data to HMIS. HMIS provides capability of data reporting and analysis in the form of dashboards and serves as a key input to health policy formulation and interventions.

Mother and Child Tracking System (MCTS), launched in 2009 by MoHFW, is a name-based application which facilitates monitoring of universal access to maternal and child health services by all pregnant women and children. Its aim is to help reduce maternal, infant and child mortality by ensuring that all the pregnant women and children receive a full set of medical services. MCTS tracks all pregnant women right from conception up to 42 days postpartum and all newborn up to five years of age.

Data Quality Issues

However, data quality issues have reduced the usefulness of HMIS data. The low quality of the HMIS is evident from three factors: high percentage of missing data, high occurrence of invalid entries and the presence of outliers. Moreover, HMIS has failed to ensure reporting from all private health facilities. Also, instances of repeat entries are common at the lower levels of reporting. Over the past few years, the quality of data has improved. Yet, it still falls short of the requirements of evidence-based health policy planning. Data quality has to increase substantially before it can be used for monitoring and planning in the health sector.

Encouraging Data Use at the Micro-level

Having stated the problem of data quality, one question remains, “What could be done to make the health information systems more reliable?” One way to achieve this is to encourage the use of HMIS data at the micro-level. This will improve the understanding about HMIS among the field level workers. HMIS reporting starts with the auxiliary nurse and midwives (ANM). As they become aware of the usefulness of HMIS data, the quality of reporting is going to improve. Another way is to encourage discussions on HMIS data in regular community meetings. If these small steps are taken, the quality of HMIS reports can be improved substantially.