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Impact of a district-wide health center strengthening intervention on healthcare utilization in rural Rwanda: Use of interrupted time series analysis

BACKGROUND: Evaluations 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 inve...

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Autores principales: Iyer, Hari S., Hirschhorn, Lisa R., Nisingizwe, Marie Paul, Kamanzi, Emmanuel, Drobac, Peter C., Rwabukwisi, Felix C., Law, Michael R., Muhire, Andrew, Rusanganwa, Vincent, Basinga, Paulin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5538651/
https://www.ncbi.nlm.nih.gov/pubmed/28763505
http://dx.doi.org/10.1371/journal.pone.0182418
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author Iyer, Hari S.
Hirschhorn, Lisa R.
Nisingizwe, Marie Paul
Kamanzi, Emmanuel
Drobac, Peter C.
Rwabukwisi, Felix C.
Law, Michael R.
Muhire, Andrew
Rusanganwa, Vincent
Basinga, Paulin
author_facet Iyer, Hari S.
Hirschhorn, Lisa R.
Nisingizwe, Marie Paul
Kamanzi, Emmanuel
Drobac, Peter C.
Rwabukwisi, Felix C.
Law, Michael R.
Muhire, Andrew
Rusanganwa, Vincent
Basinga, Paulin
author_sort Iyer, Hari S.
collection PubMed
description BACKGROUND: Evaluations 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. METHODS: We 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. RESULTS: PHIT 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]). CONCLUSION: We 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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spelling pubmed-55386512017-08-07 Impact of a district-wide health center strengthening intervention on healthcare utilization in rural Rwanda: Use of interrupted time series analysis Iyer, Hari S. Hirschhorn, Lisa R. Nisingizwe, Marie Paul Kamanzi, Emmanuel Drobac, Peter C. Rwabukwisi, Felix C. Law, Michael R. Muhire, Andrew Rusanganwa, Vincent Basinga, Paulin PLoS One Research Article BACKGROUND: Evaluations 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. METHODS: We 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. RESULTS: PHIT 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]). CONCLUSION: We 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. Public Library of Science 2017-08-01 /pmc/articles/PMC5538651/ /pubmed/28763505 http://dx.doi.org/10.1371/journal.pone.0182418 Text en © 2017 Iyer et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Iyer, Hari S.
Hirschhorn, Lisa R.
Nisingizwe, Marie Paul
Kamanzi, Emmanuel
Drobac, Peter C.
Rwabukwisi, Felix C.
Law, Michael R.
Muhire, Andrew
Rusanganwa, Vincent
Basinga, Paulin
Impact of a district-wide health center strengthening intervention on healthcare utilization in rural Rwanda: Use of interrupted time series analysis
title Impact of a district-wide health center strengthening intervention on healthcare utilization in rural Rwanda: Use of interrupted time series analysis
title_full Impact of a district-wide health center strengthening intervention on healthcare utilization in rural Rwanda: Use of interrupted time series analysis
title_fullStr Impact of a district-wide health center strengthening intervention on healthcare utilization in rural Rwanda: Use of interrupted time series analysis
title_full_unstemmed Impact of a district-wide health center strengthening intervention on healthcare utilization in rural Rwanda: Use of interrupted time series analysis
title_short Impact of a district-wide health center strengthening intervention on healthcare utilization in rural Rwanda: Use of interrupted time series analysis
title_sort impact of a district-wide health center strengthening intervention on healthcare utilization in rural rwanda: use of interrupted time series analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5538651/
https://www.ncbi.nlm.nih.gov/pubmed/28763505
http://dx.doi.org/10.1371/journal.pone.0182418
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