Data Quality Assessment Pilot Highlights Focus on Improving HMIS Data Quality and Use in India - Ms. Deepti Srivastava
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The document discusses a data quality assessment pilot aimed at improving the Health Management and Information System (HMIS) in India, led by Ms. Deepti Srivastava from the Ministry of Health and Family Welfare. It emphasizes the need for reliable data for effective public health decision-making and underscores the importance of standardized training for staff involved in data collection. The pilot highlighted gaps in data completeness and the necessity for enhanced capacity-building efforts to foster better data use at block and facility levels, while recognizing the support from USAID's Health Finance and Governance project.
Data Quality Assessment Pilot Highlights Focus on Improving HMIS Data Quality and Use in India - Ms. Deepti Srivastava
- 1. DATA QUALITY ASSESSMENT PILOT HIGHLIGHTS FOCUS ON IMPROVING HMIS DATA QUALITY AND USE IN INDIA As Director of the Statistics Division within India’s Ministry of Health and Family Welfare (MoHFW), Ms. Deepti Srivastava held responsibility for the country’s health management and information system (HMIS). Ms. Srivastava worked closely with USAID’s Health Finance and Governance (HFG) project team on conducting a data quality assessment pilot. She spoke with the HFG team about the findings of the pilot following the Technical Advisory Group meeting conducted by the MoHFW. Tell us about your role at the MoHFW ? Ms. Deepti Srivastava I am a statistician by training. My professional career as a statistician began in 2000 when I joined the Indian Statistics Service. I have also managed statistical and monitoring and evaluation assignments at the Central Water Commission and had a long and enriching tenure at the Planning Commission. I joined the MoHFW in December 2010 as Joint Director at the Statistics Division, which is the central office for HMIS in India. This position gave me sole administrative responsibility for HMIS at a time when HMIS shifted to facility-based reporting. I was promoted to the position of Director in 2013, where I continued the focus on strengthening the HMIS.. India is a vast country with a complex health landscape. To successfully plan and implement realistic schemes, we need very organized and structured data, at least for the district level. Reliable data is also a prerequisite for monitoring, to help us understand how public money is being spent and whether the investment is yielding results. Most importantly, accurate data must be the only basis for effective decision making and management of health programs. I feel assessments can play a critical role in strengthening the HMIS. Assessment is an important mechanism not only from the perspective of data quality, but also to establish the integrity and external validity of the data. Assessments can address any doubts about data reliability among government decision makers. We can communicate findings of such assessments to all stakeholders to create awareness regarding data authenticity and the gaps that need to be addressed. Assessments should be unbiased from the outset, otherwise they lose their validity and value. The MoHFW places strong emphasis on improving the quality of public health data in the country. How crucial is reliable data for strengthening public health service delivery? A structured assessment of the HMIS, especially on the quality of the data it generates, is seen as an important mechanism for highlighting data quality issues. How do such assessments contribute to strengthening the HMIS?
- 2. We came to know of RDQA because HFG had successfully applied it in Haryana state. Haryana has better data quality than many of its neighboring states. The methodology is well-rounded, incorporating field visits, supervision, guidance, and training. The five- district pilot of the methodology at the national level has also shown its feasibility and strength in assessing the quality of reported data. RDQA is a good tool and has provided some cogent findings that will help build consensus on the steps to improve data quality. One gap that we identified is that while the methodology verified the data in the service delivery registers, it did not assess the completeness of the data. We need to understand the completeness of recording in service delivery registers, for example, on live births and home deliveries. Another aspect that the methodology could have addressed is comparison of HMIS data with survey data, like the National Family Health Survey data. It would be useful to have the tool updated to address these aspects. I think that training should be the priority right now. Training auxiliary nurse midwives and data entry operators (DEOs) should be at the top of the list. In 2011, when HMIS shifted from district-level reporting to facility-based reporting, the central government provided resources like DEOs, hardware and software, and internet access. The government has also allocated funds to states for training of state, district, and block- level staff. However, staff require more robust and exhaustive training, especially on data items and data definitions. MoHFW is working to address this gap and planning to digitize the training content so that standardized training materials, videos, and PowerPoint presentations can be easily accessed. The next stage could be online certifications. Evidently, our current training format is not supporting the development of a culture of information use at the block and facility level, unlike at state and district levels where the higher level staff are more conversant with HMIS concepts and vocabulary. We need to address this issue to strengthen evidence-based decision making because increased data use contributes to improved data quality. We need to understand the block and facility level challenges related to data use and identify their unique data needs for managerial action. In addition to the fixed reports the HMIS currently generates, the system could, going forward, be updated to also generate the required customized reports, instead of forcing staff to build a query and sift through more data than they need. USAID has been a strong development partner that has contributed very good resources. The Government of India developed the HMIS, and USAID contributed manpower to strengthen it. The ministry acknowledges this valuable contribution. Going forward, states may require support in establishing the integrated hospital information system. Perhaps the development partners could focus on that, as it would really contribute to health information strengthening. A flagship project of USAID’s Office of Health Systems, the Health Finance and Governance (HFG) Project supports its partners in low- and middle-income countries to strengthen the health finance and governance functions of their health systems, expanding access to life- saving health services. The HFG project is a five-year (2012-2017), $209 million global health project. The project builds on the achievements of the Health Systems 20/20 project. To learn more, please visit www.hfgproject.org. The HFG project is led by Abt Associates in collaboration with Avenir Health, Broad Branch Associates, Development Alternatives Inc., Johns Hopkins Bloomberg School of Public Health, Results for Development Institute, RTI International, and Training Resources Group, Inc. Agreement Officer Representative Team: Scott Stewart (GH/OHS) sstewart@usaid.gov Jodi Charles (GH/OHS) jcharles@usaid.gov Abt Associates www.abtassociates.com 4550 Montgomery Avenue, Suite 800 North Bethesda, MD 20814 DISCLAIMER The author’s views expressed here do not necessarily reflect the views of the U.S. Agency for International Development or the U.S. Government HFG’s pilot using the Routine Data Quality Assessment (RDQA) methodology has provided insights on HMIS systemic components and reporting processes. In what way can this inform the MoHFW’s efforts to improve data quality and use? Another important finding is the low level of data use at the block and facility level to inform day-to-day functioning of public health facilities. What actions can be taken on this front? For over three years now, the HFG project has been supporting the MoHFW and states like Haryana through structured assessments, capacity building, and use of technology to improve access to data. How has this support bolstered the governments efforts to improve the performance of the HMIS? One key finding of the RDQA exercise was the need to strengthen the health information workforce, particularly training on data collection guidelines and formats. What are your thoughts on this issue and what can be done to address this?