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Organisational factors associated with implementing action plans informed by routine health information system data
Nami Kawakyu1,2, Bradley H Wagenaar3,4, Orvalho Augusto3,5
1Department of Global Health, University of Washington, Seattle, Washington, USA nkawakyu@uw.edu.
Introduction:
Routine health information system (RHIS) data use remains limited in many low- and middle-income countries, with little evidence on factors that promote or hinder its use for improving health facility performance. This study examined patterns of translating RHIS data into action and explored organisational factors associated with successful implementation.
Methods:
Data come from a sample of 36 facilities in Mozambique that participated in a data-to-action strategy from 2016 to 2020. The strategy united provincial, district and facility staff at semiannual meetings to analyse and review RHIS data and develop action plans to improve health facility services. Data included the number of planned and implemented actions and facility characteristics such as staff size, management practices and RHIS data completeness. Generalised mixed effects logistic regression was used to identify factors associated with successful implementation of planned actions.
Results:
From 2016 to 2020, facilities implemented 64% (1567 of 2462) of planned actions. On average, facilities planned nine actions per meeting, with the highest number of actions planned during the first meeting and plateauing to five actions per meeting. The likelihood of implementing an action increased by 2% for each additional action planned (aOR 1.02, CI 1.01 to 1.03). Facilities reporting limited staff or financial resources as top barriers were significantly less likely to implement planned actions (aOR 0.52, CI 0.36 to 0.75; aOR 0.42, CI 0.23 to 0.76, respectively).
Conclusion:
Findings suggest that supporting health facilities to develop RHIS data-informed action plans and strengthening management capacity may promote implementation of actions. Addressing staffing and financial resource constraints remains critical for successfully translating RHIS data into action to improve health facility performance.
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