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Administrative Data Linkage to Evaluate a Quality Improvement Program in Acute Stroke Care, Georgia, 2006–2009

INTRODUCTION: Tracking the vital status of stroke patients through death data is one approach to assessing the impact of quality improvement in stroke care. We assessed the feasibility of linking Georgia hospital discharge data with mortality data to evaluate the effect of participation in the Georg...

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Autores principales: Ido, Moges Seyoum, Bayakly, Rana, Frankel, Michael, Lyn, Rodney, Okosun, Ike S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Centers for Disease Control and Prevention 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4307832/
https://www.ncbi.nlm.nih.gov/pubmed/25590599
http://dx.doi.org/10.5888/pcd12.140238
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author Ido, Moges Seyoum
Bayakly, Rana
Frankel, Michael
Lyn, Rodney
Okosun, Ike S.
author_facet Ido, Moges Seyoum
Bayakly, Rana
Frankel, Michael
Lyn, Rodney
Okosun, Ike S.
author_sort Ido, Moges Seyoum
collection PubMed
description INTRODUCTION: Tracking the vital status of stroke patients through death data is one approach to assessing the impact of quality improvement in stroke care. We assessed the feasibility of linking Georgia hospital discharge data with mortality data to evaluate the effect of participation in the Georgia Coverdell Acute Stroke Registry on survival rates among acute ischemic stroke patients. METHODS: Multistage probabilistic matching, using a fine-grained record integration and linkage software program and combinations of key variables, was used to link Georgia hospital discharge data for 2005 through 2009 with mortality data for 2006 through 2010. Data from patients admitted with principal diagnoses of acute ischemic stroke were analyzed by using the extended Cox proportional hazard model. The survival times of patients cared for by hospitals participating in the stroke registry and of those treated at nonparticipating hospitals were compared. RESULTS: Average age of the 50,579 patients analyzed was 69 years, and 56% of patients were treated in Georgia Coverdell Acute Stroke Registry hospitals. Thirty-day and 365-day mortality after first admission for stroke were 8.1% and 18.5%, respectively. Patients treated at nonparticipating facilities had a hazard ratio for death of 1.14 (95% confidence interval, 1.03–1.26; P = .01) after the first week of admission compared with patients cared for by hospitals participating in the registry. CONCLUSION: Hospital discharge data can be linked with death data to assess the impact of clinical-level or community-level chronic disease control initiatives. Hospitals need to undertake quality improvement activities for a better patient outcome.
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spelling pubmed-43078322015-02-06 Administrative Data Linkage to Evaluate a Quality Improvement Program in Acute Stroke Care, Georgia, 2006–2009 Ido, Moges Seyoum Bayakly, Rana Frankel, Michael Lyn, Rodney Okosun, Ike S. Prev Chronic Dis Original Research INTRODUCTION: Tracking the vital status of stroke patients through death data is one approach to assessing the impact of quality improvement in stroke care. We assessed the feasibility of linking Georgia hospital discharge data with mortality data to evaluate the effect of participation in the Georgia Coverdell Acute Stroke Registry on survival rates among acute ischemic stroke patients. METHODS: Multistage probabilistic matching, using a fine-grained record integration and linkage software program and combinations of key variables, was used to link Georgia hospital discharge data for 2005 through 2009 with mortality data for 2006 through 2010. Data from patients admitted with principal diagnoses of acute ischemic stroke were analyzed by using the extended Cox proportional hazard model. The survival times of patients cared for by hospitals participating in the stroke registry and of those treated at nonparticipating hospitals were compared. RESULTS: Average age of the 50,579 patients analyzed was 69 years, and 56% of patients were treated in Georgia Coverdell Acute Stroke Registry hospitals. Thirty-day and 365-day mortality after first admission for stroke were 8.1% and 18.5%, respectively. Patients treated at nonparticipating facilities had a hazard ratio for death of 1.14 (95% confidence interval, 1.03–1.26; P = .01) after the first week of admission compared with patients cared for by hospitals participating in the registry. CONCLUSION: Hospital discharge data can be linked with death data to assess the impact of clinical-level or community-level chronic disease control initiatives. Hospitals need to undertake quality improvement activities for a better patient outcome. Centers for Disease Control and Prevention 2015-01-15 /pmc/articles/PMC4307832/ /pubmed/25590599 http://dx.doi.org/10.5888/pcd12.140238 Text en https://creativecommons.org/licenses/by/4.0/This is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited.
spellingShingle Original Research
Ido, Moges Seyoum
Bayakly, Rana
Frankel, Michael
Lyn, Rodney
Okosun, Ike S.
Administrative Data Linkage to Evaluate a Quality Improvement Program in Acute Stroke Care, Georgia, 2006–2009
title Administrative Data Linkage to Evaluate a Quality Improvement Program in Acute Stroke Care, Georgia, 2006–2009
title_full Administrative Data Linkage to Evaluate a Quality Improvement Program in Acute Stroke Care, Georgia, 2006–2009
title_fullStr Administrative Data Linkage to Evaluate a Quality Improvement Program in Acute Stroke Care, Georgia, 2006–2009
title_full_unstemmed Administrative Data Linkage to Evaluate a Quality Improvement Program in Acute Stroke Care, Georgia, 2006–2009
title_short Administrative Data Linkage to Evaluate a Quality Improvement Program in Acute Stroke Care, Georgia, 2006–2009
title_sort administrative data linkage to evaluate a quality improvement program in acute stroke care, georgia, 2006–2009
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4307832/
https://www.ncbi.nlm.nih.gov/pubmed/25590599
http://dx.doi.org/10.5888/pcd12.140238
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