Defining a typology of primary care practices: a novel approach.

Details

Serval ID
serval:BIB_E1E096F4CEC0
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Defining a typology of primary care practices: a novel approach.
Journal
International journal for quality in health care : journal of the International Society for Quality in Health Care
Author(s)
Senn N., Cohidon C., Zuchuat J.C.
ISSN
1464-3677 (Electronic)
ISSN-L
1353-4505
Publication state
Published
Issued date
12/09/2016
Peer-reviewed
Oui
Volume
28 (6)
Number
6
Pages
734-741
Language
english
Notes
Publication types: Journal Article

Abstract
To define a typology of primary care (PC) practices based on a mixed inductive/deductive approach that uses a large number of variables describing organizational and demographic characteristics of practices and a priori hierarchical structuring of the data.
Secondary analysis of the Swiss part of the QUALICOPC study using a multiple factor analysis approach incorporating 74 variables hierarchically structured and including information on infrastructures, clinical care, workforces, accessibility and geographic location of PC practices.
Switzerland.
Two hundred randomly selected PC practices.
Typology of PC practices based on axes identified through the multiple factorial approach.
The factorial analysis extracted two uncorrelated axes summarizing 17% of the global variance. The first axis is mainly associated with two dimensions related to the comprehensiveness of services, namely 'clinical care provided' (Pearson's r = 0.73) and 'available infrastructures' (r = 0.78). The second axis is mainly associated with the workforce in the practice such as the number of general practitioners or other health workers (r = 0.69). Swiss PC practices were mapped using these two axes.
This innovative approach allows defining a global typology of PC practices. Based upon Swiss data, two axes were identified to globally describe PC organization: comprehensiveness of services and workforces development. This exploratory study demonstrates a promising way, first to characterize globally one or several PC models that emerge from complex features, second to compare more accurately PC organization between countries and finally to assess how these models might be associated with patients' outcomes.

Pubmed
Web of science
Open Access
Yes
Create date
23/09/2016 19:04
Last modification date
20/08/2019 17:05
Usage data