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Do practice characteristics explain differences in morbidity estimates between electronic health record based general practice registration networks?

BACKGROUND: General practice based registration networks (GPRNs) provide information on population health derived from electronic health records (EHR). Morbidity estimates from different GPRNs reveal considerable, unexplained differences. Previous research showed that population characteristics coul...

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Autores principales: van den Dungen, C, Hoeymans, N, van den Akker, M, Biermans, MCJ, van Boven, K, Joosten, JHK, Verheij, RA, de Waal, MWM, Schellevis, FG, van Oers, JAM
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4231185/
https://www.ncbi.nlm.nih.gov/pubmed/25358247
http://dx.doi.org/10.1186/s12875-014-0176-7
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author van den Dungen, C
Hoeymans, N
van den Akker, M
Biermans, MCJ
van Boven, K
Joosten, JHK
Verheij, RA
de Waal, MWM
Schellevis, FG
van Oers, JAM
author_facet van den Dungen, C
Hoeymans, N
van den Akker, M
Biermans, MCJ
van Boven, K
Joosten, JHK
Verheij, RA
de Waal, MWM
Schellevis, FG
van Oers, JAM
author_sort van den Dungen, C
collection PubMed
description BACKGROUND: General practice based registration networks (GPRNs) provide information on population health derived from electronic health records (EHR). Morbidity estimates from different GPRNs reveal considerable, unexplained differences. Previous research showed that population characteristics could not explain this variation. In this study we investigate the influence of practice characteristics on the variation in incidence and prevalence figures between general practices and between GPRNs. METHODS: We analyzed the influence of eight practice characteristics, such as type of practice, percentage female general practitioners, and employment of a practice nurse, on the variation in morbidity estimates of twelve diseases between six Dutch GPRNs. We used multilevel logistic regression analysis and expressed the variation between practices and GPRNs in median odds ratios (MOR). Furthermore, we analyzed the influence of type of EHR software package and province within one large national GPRN. RESULTS: Hardly any practice characteristic showed an effect on morbidity estimates. Adjusting for the practice characteristics did also not alter the variation between practices or between GPRNs, as MORs remained stable. The EHR software package ‘Medicom’ and the province ‘Groningen’ showed significant effects on the prevalence figures of several diseases, but this hardly diminished the variation between practices. CONCLUSION: Practice characteristics do not explain the differences in morbidity estimates between GPRNs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12875-014-0176-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-42311852014-11-15 Do practice characteristics explain differences in morbidity estimates between electronic health record based general practice registration networks? van den Dungen, C Hoeymans, N van den Akker, M Biermans, MCJ van Boven, K Joosten, JHK Verheij, RA de Waal, MWM Schellevis, FG van Oers, JAM BMC Fam Pract Research Article BACKGROUND: General practice based registration networks (GPRNs) provide information on population health derived from electronic health records (EHR). Morbidity estimates from different GPRNs reveal considerable, unexplained differences. Previous research showed that population characteristics could not explain this variation. In this study we investigate the influence of practice characteristics on the variation in incidence and prevalence figures between general practices and between GPRNs. METHODS: We analyzed the influence of eight practice characteristics, such as type of practice, percentage female general practitioners, and employment of a practice nurse, on the variation in morbidity estimates of twelve diseases between six Dutch GPRNs. We used multilevel logistic regression analysis and expressed the variation between practices and GPRNs in median odds ratios (MOR). Furthermore, we analyzed the influence of type of EHR software package and province within one large national GPRN. RESULTS: Hardly any practice characteristic showed an effect on morbidity estimates. Adjusting for the practice characteristics did also not alter the variation between practices or between GPRNs, as MORs remained stable. The EHR software package ‘Medicom’ and the province ‘Groningen’ showed significant effects on the prevalence figures of several diseases, but this hardly diminished the variation between practices. CONCLUSION: Practice characteristics do not explain the differences in morbidity estimates between GPRNs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12875-014-0176-7) contains supplementary material, which is available to authorized users. BioMed Central 2014-10-30 /pmc/articles/PMC4231185/ /pubmed/25358247 http://dx.doi.org/10.1186/s12875-014-0176-7 Text en © van den Dungen et al.; licensee BioMed Central Ltd. 2014 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 work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
van den Dungen, C
Hoeymans, N
van den Akker, M
Biermans, MCJ
van Boven, K
Joosten, JHK
Verheij, RA
de Waal, MWM
Schellevis, FG
van Oers, JAM
Do practice characteristics explain differences in morbidity estimates between electronic health record based general practice registration networks?
title Do practice characteristics explain differences in morbidity estimates between electronic health record based general practice registration networks?
title_full Do practice characteristics explain differences in morbidity estimates between electronic health record based general practice registration networks?
title_fullStr Do practice characteristics explain differences in morbidity estimates between electronic health record based general practice registration networks?
title_full_unstemmed Do practice characteristics explain differences in morbidity estimates between electronic health record based general practice registration networks?
title_short Do practice characteristics explain differences in morbidity estimates between electronic health record based general practice registration networks?
title_sort do practice characteristics explain differences in morbidity estimates between electronic health record based general practice registration networks?
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4231185/
https://www.ncbi.nlm.nih.gov/pubmed/25358247
http://dx.doi.org/10.1186/s12875-014-0176-7
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