The influence of population characteristics on variation in general practice based morbidity estimations
<p>Abstract</p> <p>Background</p> <p>General practice based registration networks (GPRNs) provide information on morbidity rates in the population. Morbidity rate estimates from different GPRNs, however, reveal considerable, unexplained differences. We studied the range...
Main Authors: | , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2011-11-01
|
Series: | BMC Public Health |
Subjects: | |
Online Access: | http://www.biomedcentral.com/1471-2458/11/887 |
id |
doaj-902c29777273481bbd0b7f07bad43cc0 |
---|---|
record_format |
Article |
spelling |
doaj-902c29777273481bbd0b7f07bad43cc02020-11-25T01:32:31ZengBMCBMC Public Health1471-24582011-11-0111188710.1186/1471-2458-11-887The influence of population characteristics on variation in general practice based morbidity estimationsvan den Dungen CHoeymans NBoshuizen HCvan den Akker MBiermans MCJvan Boven KBrouwer HJVerheij RAde Waal MWMSchellevis FGWestert GP<p>Abstract</p> <p>Background</p> <p>General practice based registration networks (GPRNs) provide information on morbidity rates in the population. Morbidity rate estimates from different GPRNs, however, reveal considerable, unexplained differences. We studied the range and variation in morbidity estimates, as well as the extent to which the differences in morbidity rates between general practices and networks change if socio-demographic characteristics of the listed patient populations are taken into account.</p> <p>Methods</p> <p>The variation in incidence and prevalence rates of thirteen diseases among six Dutch GPRNs and the influence of age, gender, socio economic status (SES), urbanization level, and ethnicity are analyzed using multilevel logistic regression analysis. Results are expressed in median odds ratios (MOR).</p> <p>Results</p> <p>We observed large differences in morbidity rate estimates both on the level of general practices as on the level of networks. The differences in SES, urbanization level and ethnicity distribution among the networks' practice populations are substantial. The variation in morbidity rate estimates among networks did not decrease after adjusting for these socio-demographic characteristics.</p> <p>Conclusion</p> <p>Socio-demographic characteristics of populations do not explain the differences in morbidity estimations among GPRNs.</p> http://www.biomedcentral.com/1471-2458/11/887Family practiceIncidenceMedical recordsPopulation characteristicsPublic healthPrevalence |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
van den Dungen C Hoeymans N Boshuizen HC van den Akker M Biermans MCJ van Boven K Brouwer HJ Verheij RA de Waal MWM Schellevis FG Westert GP |
spellingShingle |
van den Dungen C Hoeymans N Boshuizen HC van den Akker M Biermans MCJ van Boven K Brouwer HJ Verheij RA de Waal MWM Schellevis FG Westert GP The influence of population characteristics on variation in general practice based morbidity estimations BMC Public Health Family practice Incidence Medical records Population characteristics Public health Prevalence |
author_facet |
van den Dungen C Hoeymans N Boshuizen HC van den Akker M Biermans MCJ van Boven K Brouwer HJ Verheij RA de Waal MWM Schellevis FG Westert GP |
author_sort |
van den Dungen C |
title |
The influence of population characteristics on variation in general practice based morbidity estimations |
title_short |
The influence of population characteristics on variation in general practice based morbidity estimations |
title_full |
The influence of population characteristics on variation in general practice based morbidity estimations |
title_fullStr |
The influence of population characteristics on variation in general practice based morbidity estimations |
title_full_unstemmed |
The influence of population characteristics on variation in general practice based morbidity estimations |
title_sort |
influence of population characteristics on variation in general practice based morbidity estimations |
publisher |
BMC |
series |
BMC Public Health |
issn |
1471-2458 |
publishDate |
2011-11-01 |
description |
<p>Abstract</p> <p>Background</p> <p>General practice based registration networks (GPRNs) provide information on morbidity rates in the population. Morbidity rate estimates from different GPRNs, however, reveal considerable, unexplained differences. We studied the range and variation in morbidity estimates, as well as the extent to which the differences in morbidity rates between general practices and networks change if socio-demographic characteristics of the listed patient populations are taken into account.</p> <p>Methods</p> <p>The variation in incidence and prevalence rates of thirteen diseases among six Dutch GPRNs and the influence of age, gender, socio economic status (SES), urbanization level, and ethnicity are analyzed using multilevel logistic regression analysis. Results are expressed in median odds ratios (MOR).</p> <p>Results</p> <p>We observed large differences in morbidity rate estimates both on the level of general practices as on the level of networks. The differences in SES, urbanization level and ethnicity distribution among the networks' practice populations are substantial. The variation in morbidity rate estimates among networks did not decrease after adjusting for these socio-demographic characteristics.</p> <p>Conclusion</p> <p>Socio-demographic characteristics of populations do not explain the differences in morbidity estimations among GPRNs.</p> |
topic |
Family practice Incidence Medical records Population characteristics Public health Prevalence |
url |
http://www.biomedcentral.com/1471-2458/11/887 |
work_keys_str_mv |
AT vandendungenc theinfluenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT hoeymansn theinfluenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT boshuizenhc theinfluenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT vandenakkerm theinfluenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT biermansmcj theinfluenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT vanbovenk theinfluenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT brouwerhj theinfluenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT verheijra theinfluenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT dewaalmwm theinfluenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT schellevisfg theinfluenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT westertgp theinfluenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT vandendungenc influenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT hoeymansn influenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT boshuizenhc influenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT vandenakkerm influenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT biermansmcj influenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT vanbovenk influenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT brouwerhj influenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT verheijra influenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT dewaalmwm influenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT schellevisfg influenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations AT westertgp influenceofpopulationcharacteristicsonvariationingeneralpracticebasedmorbidityestimations |
_version_ |
1725081499435270144 |