BackgroundIndia’s Mother and Child Tracking System (MCTS)1 is an information system for tracking maternal and child health beneficiaries in India’s public health system, and improving service delivery planning and outcomes. This ambitious project was launched in 2009 and currently covers all states in India, but no in-depth assessment of the system has been conducted. This study by the Public Health Foundation of India (PHFI) evaluated the performance of MCTS and identified implementation challenges in areas in Rajasthan and Uttar Pradesh (UP) in December 2012.MethodsTwo assessment methods were employed: a Data Quality Assessment (DQA) to evaluate data quality and an assessment survey to identify implementation challenges. The survey comprised semi-structured questionnaires for health staff in the sampled districts, observation checklists and survey investigator notes. Purposive sampling was used for selecting two districts in each state and two blocks in each district. For the DQA, 45 mothers who became pregnant and 84 children born within the stipulated timeframes were randomly sampled.ResultsDQA overall performance numbers were 34 % for pregnant women and 33 % for children in the Rajasthan study areas, while UP’s performance numbers were 18 % for pregnant women and 25 % for children. Weaknesses in the MCTS' data completeness accounted for much of this performance shortfall. The beneficiary profiles for Rajasthan were largely incomplete, and the MCTS in UP struggled to register beneficiaries. Shared challenges in both states were the absence of clear processes and guidelines governing data processes, and the lack of systematic monitoring and supervision frameworks for MCTS implementation. As a result, Front Line Health Workers (FHWs) were overburdened with data documentation work, and there were long delays in data capturing. FHWs and block level health officials were not adequately trained in using the MCTS. UP staff reported unreliable internet and electricity availability, lack of dedicated data entry personnel, and a shortage of consumables such as MCTS registers.ConclusionsThere is 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.
Information on population health indicators in India come from a number of surveys that vary in periodicity, scope and detail. In the case of immunization, the most recent coverage indicators are derived from the first round of Annual Health Survey (AHS-1, 2010-11), but these were conducted only in 9 of 35 states and union territories. The most recent national surveys of immunization coverage were conducted in 2009 (Coverage Evaluation Survey) by UNICEF. Therefore, reliable immunization coverage data for the entire country since 2009 is lacking. We used an established approach of small area estimation to predict coverage rates of several vaccinations for the remaining 26 states (not covered by AHS-1) in 2011. In our method, we considered a linear mixed model that combines data from five cross sectional surveys representing five different time points. Our model encompasses sampling error of the survey estimates, area specific random effects, autocorrelated area by time random effects and hence, borrows strength across areas and time points both. Model-based estimates for 2011 are almost identical to the AHS-1 estimates for the nine states, suggesting that our model provides reliable prediction of vaccination coverage as AHS-1 estimates are highly precise because of their large sample size. Results indicate that coverage inequality between rural and urban areas has been reduced significantly for most states in India. The National Rural Health Mission has had both supply side and demand side effects on the immunization programme in rural India. In combination, these effects may have contributed to the reduction of vaccination coverage gaps between urban and rural areas.
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