ArticlePloS one2017
Impact of a district-wide health center strengthening intervention on healthcare utilization in rural Rwanda: Use of interrupted time series analysis.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 3 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
10 citing papers in PubMed, 3 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- Understanding pathways from primary health care to universal health coverage outcomes: a realist review.Frontiers in public health · 2026Pooled it
- Using routine health information data for research in low- and middle-income countries: a systematic review.BMC health services research · 2020Pooled it
- Routine Health Information System (RHIS) improvements for strengthened health system management.The Cochrane database of systematic reviews · 2020Pooled it
- Utilization of routine health information system and its determinants among healthcare professionals in public health facilities of Banadir region, Somalia: A cross-sectional study.BMC health services research · 2026Article
- Article
- Association between the quality of care and continuous maternal and child health service utilisation in Angola: Longitudinal data analysis.Journal of global health · 2023Article
- Health impacts of a scale-up of supervised injection services in a Canadian setting: an interrupted time series analysis.Addiction (Abingdon, England) · 2022Article
- Evaluation of quality and use of health management information system in primary health care units of east Wollega zone, Oromia regional state, Ethiopia.BMC medical informatics and decision making · 2020Article
- Health management information system (HMIS) data verification: A case study in four districts in Rwanda.PloS one · 2020Article
- Health system resilience: quantifying the dynamic impact of environmental shocks on health service utilization using an interrupted time series and time-series forecasting approach in Western Province, Zambia.The journal of climate change and healthArticle
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Authors and funding
10 authors at 7 institutions in 3 countries.
Funding
Abstract
backgroundEvaluations of health systems strengthening (HSS) interventions using observational data are rarely used for causal inference due to limited data availability. Routinely collected national data allow use of quasi-experimental designs such as interrupted time series (ITS). Rwanda has invested in a robust electronic health management information system (HMIS) that captures monthly healthcare utilization data. We used ITS to evaluate impact of an HSS intervention to improve primary health care facility readiness on health service utilization in two rural districts of Rwanda.
methodsWe used controlled ITS analysis to compare changes in healthcare utilization at health centers (HC) that received the intervention (n = 13) to propensity score matched non-intervention health centers in Rwanda (n = 86) from January 2008 to December 2012. HC support included infrastructure renovation, salary support, medical equipment, referral network strengthening, and clinical training. Baseline quarterly mean outpatient visit rates and population density were used to model propensity scores. The intervention began in May 2010 and was implemented over a twelve-month period. We used monthly healthcare utilization data from the national Rwandan HMIS to study changes in the (1) number of facility deliveries per 10,000 women, (2) number of referrals for high risk pregnancy per 100,000 women, and (3) the number of outpatient visits performed per 1,000 catchment population.
resultsPHIT HC experienced significantly higher monthly delivery rates post-HSS during the April-June season than comparison (3.19/10,000, 95% CI: [0.27, 6.10]). In 2010, this represented a 13% relative increase, and in 2011, this represented a 23% relative increase. The post-HSS change in monthly rate of high-risk pregnancies referred increased slightly in intervention compared to control HC (0.03/10,000, 95% CI: [-0.007, 0.06]). There was a small immediate post-HSS increase in outpatient visit rates in intervention compared to control HC (6.64/1,000, 95% CI: [-13.52, 26.81]).
conclusionWe failed to find strong evidence of post-HSS increases in outpatient visit rates or referral rates at health centers, which could be explained by small sample size and high baseline nation-wide health service coverage. However, our findings demonstrate that high quality routinely collected health facility data combined with ITS can be used for rigorous policy evaluation in resource-limited settings.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.