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Electronic Health Records as Valuable Data Sources in the Health Care Quality Improvement Process

BACKGROUND: In North Karelia, Finland, the regional electronic health records (EHRs) enable flexible data retrieval and area-level analyses. The aim of this study was to assess the early detection of type 2 diabetes (T2D) in the region and to evaluate the performed activities in order to improve the...

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Autores principales: Wikström, Katja, Toivakka, Maija, Rautiainen, Päivi, Tirkkonen, Hilkka, Repo, Teppo, Laatikainen, Tiina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6545647/
https://www.ncbi.nlm.nih.gov/pubmed/31211180
http://dx.doi.org/10.1177/2333392819852879
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author Wikström, Katja
Toivakka, Maija
Rautiainen, Päivi
Tirkkonen, Hilkka
Repo, Teppo
Laatikainen, Tiina
author_facet Wikström, Katja
Toivakka, Maija
Rautiainen, Päivi
Tirkkonen, Hilkka
Repo, Teppo
Laatikainen, Tiina
author_sort Wikström, Katja
collection PubMed
description BACKGROUND: In North Karelia, Finland, the regional electronic health records (EHRs) enable flexible data retrieval and area-level analyses. The aim of this study was to assess the early detection of type 2 diabetes (T2D) in the region and to evaluate the performed activities in order to improve the processes between the years 2012 and 2017. METHODS: Patients with T2D were identified from the EHRs using the ICD-10 codes registered during any visit to either primary or specialized care. The prevalence of T2D was calculated for the years 2012, 2015, and 2017 on the municipality level. The number of people found in the EHRs with diabetes was compared with the number found in the national register of medication reimbursement rights. RESULTS: In 2012, the age-adjusted prevalence of T2D in North Karelia varied considerably between municipalities (5.5%-8.6%). These differences indicate variation in the processes of early diagnosis. The findings were discussed in the regional network of health professionals treating patients with T2D, resulting in sharing experiences and best practices. In 2017, the differences had notably diminished, and in most municipalities, the prevalence exceeded 8%. The regional differences in the prevalence and their downward trend were observed both in the EHRs and in the medication reimbursement rights register. CONCLUSION: Clear differences in the prevalence of T2D were detected between municipalities. After visualizing these differences and providing information for the professionals, the early detection of T2D improved and the regional differences decreased. The EHRs are a valuable data source for knowledge-based management and quality improvement.
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spelling pubmed-65456472019-06-17 Electronic Health Records as Valuable Data Sources in the Health Care Quality Improvement Process Wikström, Katja Toivakka, Maija Rautiainen, Päivi Tirkkonen, Hilkka Repo, Teppo Laatikainen, Tiina Health Serv Res Manag Epidemiol Case Study BACKGROUND: In North Karelia, Finland, the regional electronic health records (EHRs) enable flexible data retrieval and area-level analyses. The aim of this study was to assess the early detection of type 2 diabetes (T2D) in the region and to evaluate the performed activities in order to improve the processes between the years 2012 and 2017. METHODS: Patients with T2D were identified from the EHRs using the ICD-10 codes registered during any visit to either primary or specialized care. The prevalence of T2D was calculated for the years 2012, 2015, and 2017 on the municipality level. The number of people found in the EHRs with diabetes was compared with the number found in the national register of medication reimbursement rights. RESULTS: In 2012, the age-adjusted prevalence of T2D in North Karelia varied considerably between municipalities (5.5%-8.6%). These differences indicate variation in the processes of early diagnosis. The findings were discussed in the regional network of health professionals treating patients with T2D, resulting in sharing experiences and best practices. In 2017, the differences had notably diminished, and in most municipalities, the prevalence exceeded 8%. The regional differences in the prevalence and their downward trend were observed both in the EHRs and in the medication reimbursement rights register. CONCLUSION: Clear differences in the prevalence of T2D were detected between municipalities. After visualizing these differences and providing information for the professionals, the early detection of T2D improved and the regional differences decreased. The EHRs are a valuable data source for knowledge-based management and quality improvement. SAGE Publications 2019-05-30 /pmc/articles/PMC6545647/ /pubmed/31211180 http://dx.doi.org/10.1177/2333392819852879 Text en © The Author(s) 2019 http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Case Study
Wikström, Katja
Toivakka, Maija
Rautiainen, Päivi
Tirkkonen, Hilkka
Repo, Teppo
Laatikainen, Tiina
Electronic Health Records as Valuable Data Sources in the Health Care Quality Improvement Process
title Electronic Health Records as Valuable Data Sources in the Health Care Quality Improvement Process
title_full Electronic Health Records as Valuable Data Sources in the Health Care Quality Improvement Process
title_fullStr Electronic Health Records as Valuable Data Sources in the Health Care Quality Improvement Process
title_full_unstemmed Electronic Health Records as Valuable Data Sources in the Health Care Quality Improvement Process
title_short Electronic Health Records as Valuable Data Sources in the Health Care Quality Improvement Process
title_sort electronic health records as valuable data sources in the health care quality improvement process
topic Case Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6545647/
https://www.ncbi.nlm.nih.gov/pubmed/31211180
http://dx.doi.org/10.1177/2333392819852879
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