Daily Current Affairs – 14th January, 2017DEVENDRA VISHWAKARMA
Healthcare Data – Challenges and Reforms
Apart from the increasing burden of communicable and non communicable diseases in India, another major challenge that needs to be taken care of is the quality of health sector data.
Health sector data in India is not of top notch quality and even suffers from consistency in terms of periodicity and coverage. There is also a major mismatch between the type of information available and what is required by various stakeholders in the health sector such as planners, scientists and researchers.
Government officials in India accept that data collection system needs to be completely revamped. More cohesion has to be present because different data sources lead to different conclusions. Even data from national level surveys such as the National Family Health Survey (NFHS)-4 and data under National Rural Health Mission suffer from inconsistency.
Healthcare Data Challenges
According to research and studies it has been observed that major gaps in the area of health sector data are as follows. Challenges and problems which need to be addressed are as follows:
- Lack of data at the sub-State or the district level which makes planning for targeted interventions at the grass root level difficult.
- Data collection at irregular intervals makes it tough to incorporate changes and reforms in the policy on a mid-term basis.
- Incomplete data is a problem which increases the burden in terms of effectiveness and efficiency. Especially when data is incomplete in hospitals and health facilities in the smaller towns and districts it becomes difficult to get best results from policies.
- The need for information to pass through multiple levels increases chances of discrepancies and delays.
- Absence of health-care data from the private sector is a major problem especially at a time when 70 per cent of the health expenditure is related to private sector facilities.
Addressing the Challenges
- As data quality is one of the prime concerns, there is a need to establish an independent quality control body that monitors the quality of available data vis-a-vis the utility of the data.
- To ensure credibility and reliability of data systemic reforms are a must.
- An important area that needs to be addressed is the need to match the reason for data collection with the manner in which it is collected. Personal professional targets and window dressing of figures should not be considered as the purpose of data collection.
- Human resource development, capacity building and training of the enumerators of large-scale surveys will go a long way in improving the quality of data.
- Irrespective of the organisation conducting surveys and creating policies, definitions for various health indicators need to be standardised across surveys.
- Routine capturing of disaggregated data, without duplication is essential for reducing the efforts of data producers and ensuring results with higher efficiency.
- Data should be collected in a manner that makes it useful for decision making, This can be done through proper training as well.
In addition to the above solutions we need to ensure that good quality data is also used by the people in an effective manner. Data quality is improving but the same is not being used by stakeholders. This low utilization of data reduces the encouragement and motivation to improve the data quality.
Good quality data is quite crucial for efficient allocation of our limited resources and
evidence-based, informed health policies require efficient data. Generating and maintaining high standards of data is essential for making health-care accessible and available to all.
Connecting the dots:
- Health sector suffers majorly in terms of data collection and management. Discuss the problems in the area of healthcare data and suggest measures to overcome the same.
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In the recent Indian Science Congress held in Tirupati, Andhra Pradesh (earlier this month), Prime minister Narendra Modi pledged to place India among the top three countries in the world in the field of science and technology (S&T) by 2030.