A Review of progress and impact of Health Management Information System (HMIS) in Public Health Care system of India
Journal Title: MedPulse -International Medical Journal - Year 2017, Vol 4, Issue 1
Abstract
The Government of India’s initiatives in public health have recorded noteworthy successes over time. Unfortunately, Indian health system is still ranked 118 among 191 Who Health Organization (WHO) member countries on overall health performance (WHO, 2000). One of the reasons is poor management of health programs. The hurdles found in DHIS includes poor data quality, the unfulfilled promise of integration and a continuing weak culture of information use. Some key strategies identified to address these challenges included the promotion of decentralization of information to support decentralized action, the adoption of a data warehouse approach and strengthening collaborative networks. There was an urgent need to create data processes and supervision guidelines that complement existing workflows and service delivery priorities. Health staff should be trained to implement these guidelines. MCTS outputs, such as service delivery planning tools, should replace existing tools once data quality improves. In HMIS there was a very strong bias with policy makers (though slowly disappearing) on the use of computers. Cost escalation of major projects by 50% to 100% delays of programs by 2 to 5 years, non- achievement of objectives of programs are the common features of the projects. This means that the billions of public money invested in this programs are producing (has produced) half or less than half the results. By employing computers, by building databases, by monitoring effectively and by improving the planning ability to focus and attack issues, we will be able to reduce the wastages, time delays and save few billions in the minimum. The Health Information Systems like DHIS, MCTS, HMIS, have definitely improved the Public health system in India but still lagging in desired objectives like proper, adequate and quality data collection, timely reporting etc. The most important part is to train the health workers at gross root level to generate more efficient data production in these health information systems.
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