"There Is No Link Between Resource Allocation and Use of Local Data": A Qualitative Study of District-Based Health Decision-Making in West Bengal, India.
Bhattacharyya, Sanghita;
Issac, Anns;
Girase, Bhushan;
Guha, Mayukhmala;
Schellenberg, Joanna;
Iqbal Avan, Bilal;
(2020)
"There Is No Link Between Resource Allocation and Use of Local Data": A Qualitative Study of District-Based Health Decision-Making in West Bengal, India.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 17 (21).
p. 8283.
ISSN 1661-7827
DOI: https://doi.org/10.3390/ijerph17218283
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BACKGROUND: Effective coordination among multiple departments, including data-sharing, is needed for sound decision-making for health services. India has a district planning process involving departments for local resource-allocation based on shared data. This study assesses the decision-making process at the district level, with a focus on the extent of local data-use for resource allocation for maternal and child health. METHODS: Direct observations of key decision-making meetings and qualitative interviews with key informants were conducted in two districts in the State of West Bengal, India. Content analysis of the data maintained within the district health system was done to understand the types of data available and sharing mechanisms. This information was triangulated thematically based on WHO health system blocks. RESULTS: There was no structured decision-making process and only limited inter-departmental data-sharing. Data on all 21 issues discussed in the district decision-making meetings observed were available within the information systems. Yet indicators for only nine issues-such as institutional delivery and immunisation services were discussed. Discussions about infrastructure and supplies were not supported by data, and planning targets were not linked to health outcomes. CONCLUSION: Existing local data is highly under-used for decision-making at the district level. There is strong potential for better interaction between departments and better use of data for priority-setting, planning and follow-up.