Developing an instrument for assessing determinants of data use in evidence-based decision making: a principal component analysis at public primary health centres in Haryana, India
DOI:
https://doi.org/10.18203/2394-6040.ijcmph20243660Keywords:
Data use, Determinants, Medical officer in charges, Evidence-based decision making, Principal component analysisAbstract
Background: Evidence-based decision making (EBDM) by frontline health managers is the need of the hour in India and similar low- and middle-income countries (LMICs) for effective health policies and programs and factors affecting it needs to be ascertained. This study aims to develop an instrument for assessing determinants of data use for EBDM by frontline managers at public primary health centres.
Methods: We conducted a cross-sectional and analytical study using interview schedules capturing quantitative data from 120 medical officer in charges (MOICs) positioned at 120 primary health care units across 6 selected districts of Haryana, India. Principal component analysis (PCA) was used to generate clustered factors and reliability was tested.
Results: An instrument with three broad categories of determinants – organizational, technical, and individual (behaviour and technical) was generated. Within these, 154 variables were clustered into 27 factors. Each of the eight factors generated for organizational, technical, individual behaviour and three for individual technical determinants explained 60.5%, 59.8%, 57.7% and 68% of the total variance and had reliability of 0.75, 0.75, 0.78 and 0.80 respectively. Organizational, technical, and individual factors pertained to management meetings with superiors/subordinates, stakeholders influence, trainings in data sources, data quality and check mechanism, information adequacy, training seeking behaviour, involvement in multiple programs, incentivization, computer/software skills and knowledge.
Conclusions: The developed instrument comprised of generated factors which were rigorous, practicable, sorted, reliable and comprehensive, and effectively captured diverse determinants of data use for EBDM by frontline managers in peripheral health centres. The determinants resonate with the public health system scenario and has applicability in further analysis/settings.
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