Data Quality Assessment Pilot Highlights Focus on Improving HMIS Data Quality and Use in India
Categories: Announcements, Where We Work
Dr. Vishnu Kant Srivastava
Dr. Vishnu Kant Srivastava leads the Statistics Division at India’s Ministry of Health and Family Welfare (MoHFW). Having managed statistical initiatives at different departments and levels of the government, Dr. Srivastava recognizes the value of quality data for effective decision making. He spoke with USAID’s Health Finance and Governance (HFG) project on the findings of the data quality assessment pilot the HFG team conducted.
Tell us about your role at the MoHFW. How long have you been working in this capacity?
I was appointed Chief Director of the MoHFW’s Statistics Division in July 2015. Since then, I have been supporting the MoHFW’s data programs and initiatives in meeting their data needs. I have dealt with data all my professional life, having worked with the national Indian Statistics Service, the National Sample Survey Office, the customs and excise department, and the animal husbandry department, among others.
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?
Reliable data is the backbone of planning and is especially critical for the public health system. Health planners and practitioners can—and should—make decisions based on examination of timely and comprehensive data. The MoHFW is committed to strengthening the health management and information system (HMIS), the repository of India’s public health data on crucial health services, especially those for women and children: pregnancy care, antenatal care, childbirth, and newborn care.
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?
We have processes in place to verify and validate the reported data for the HMIS. For example, we have consultants who go into the field to review the data and provide feedback. We also organize regional and national training workshops to build capacity around data quality and to discuss data quality issues. Even with our review mechanisms, audits by an independent third party play a critical role, ensuring a focused, objective, and bias-free assessment. The HFG team has undertaken such an assessment and has also trained district officials on a methodology for regular structured assessment of data quality and use.
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?
HFG has truly done a great job. Two important things have come out of the pilot: first, it has shown that RDQA is a feasible strategy; and second, it has reaffirmed the preliminary ideas we had about data quality issues. Though we had some prior understanding of the need for a greater focus on training in relation to data quality assurance, the pilot findings helped to highlight the aspects we need to focus on, like building the capacity of health facility staff on data definitions. The pilot also indicated that out of the 28 health indicators assessed for data quality, field staff may be placing greater emphasis on data reporting, supervision, verification, and validation for some indicators than on others. We now need to explore why field staff prefer these indicators, and what lessons we can derive to bring similar attention to all other indicators.
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?
The monitoring and evaluation workforce is already in place in all states, districts, and blocks across the country. These personnel are regularly trained in regional and national workshops. However, the data quality assessment pilot indicates clear gaps in capacity building that we need to address. The learning is not successfully reaching the facility staff that are actually responsible for recording the data and reporting it. One vital intervention on this front that I think we can easily undertake is complementing the current presentation-based training methodology with more comprehensive hands-on training.
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?
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.
One positive development is that the use of data generated by the HMIS at the highest level—Parliament—has increased year after year. When HMIS data is seen as reliable and useful at such a high level this sends a positive message.
Based on your association with the MoHFW, what do you see as its key priorities?
In my view, the MoHFW’s priority vis-à-vis HMIS is on revising the HMIS reporting formats to include new data items, including for non-communicable diseases. An appendix to this initiative would be the use of newer technologies, such as cloud servers and application program interfaces (APIs), so that the system could handle the increased data load, and interact seamlessly with other systems. Something should also be done to increase the coverage of private practitioners in the HMIS; the private sector is the biggest healthcare provider in India and the huge amount of data it holds must be available to decision makers.
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?
HFG has contributed significantly to the MoHFW’s efforts to strengthen HMIS performance. The data quality assessment pilot is an important piece of work that will inform our efforts to address data quality problems and future independent third-party assessments. While I do not have many insights on HFG’s work at the state level, I do know that Haryana is doing well in terms of data quality. HFG has undertaken considerable work at the state level, particularly in Haryana, and these initiatives have lent vital support to our data quality and use initiatives.
Download in PDFMs. Deepti Srivastava
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.
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.
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?
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.
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?
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.
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?
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.
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?
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.
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?
This aspect requires rigorous focus because the ultimate purpose of this database is to facilitate functioning at the local level. The national health ministry been interacting with the states and insisting on data use. Even though many data reports have been made available to them, data use remains abysmally low at the block and facility level. MoHFW has now decided to interact with officials at these levels to ask them how they monitor their programs, and what kind of information they need for day-to-day functioning. It is hoped that feeding this information into the design of HMIS reports can better serve the needs at these levels, improving their data use.
Based on your association with the MoHFW, what do you see as its key priorities?
The national agenda is clear: creation of a ‘Digital India’. The Statistics Division at MoHFW has been working towards this vision. MoHFW has statisticians at all levels. Top levels of health leadership place value on generating a rich database that can inform planning and management. The focus is on strengthening this aspect further. The first priority must be capacity building and improving data use. The ministry is working to leverage mobile technology for training and viewing dashboards, and perhaps later even for direct data entry.
Another priority could be to expand the data that HMIS captures. Currently, HMIS mostly has data on reproductive and child health services, but it should also be capturing data on non-communicable diseases. Another focus area could be developing an integrated hospital information system, beginning at the district hospital level through to the community health center level. The ultimate goal must be to build a robust system that addresses the needs of different stakeholders.
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?
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.
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