Kim Rose Olsen1, Torben Højmark Sørensen, Dorte Gyrd-Hansen. 1. Dansk Sundhedsinstitut, Forskningsenheden for Sundhedsøkonomi, Institut for Sundhedstjenesteforskning, Syddansk Universitet, Dampfaergevej 27-29, DK-2100 København Ø, Denmark. kro@dsi.dk
Abstract
INTRODUCTION: Due to shortage of general practitioners, it may be necessary to improve productivity. We assess the association between productivity, list size and patient- and practice characteristics. MATERIAL AND METHODS: A regression approach is used to perform productivity analysis based on national register data and survey data for 1,758 practices. Practices are divided into four groups according to list size and productivity. Statistical tests are used to assess differences in patient- and practice characteristics. RESULTS: There is a significant, positive correlation between list size and productivity (p < 0.01). Nevertheless, 19% of the practices have a list size below and a productivity above mean sample values. These practices have relatively demanding patients (older, low socioeconomic status, high use of pharmaceuticals) and they are frequently located in areas with limited access to specialized care and have a low use of assisting personnel. 13% of the practices have a list size above and a productivity below mean sample values. These practices have relatively less demanding patients, are located in areas with good access to specialized care, and have a high use of assisting personnel. CONCLUSIONS: Lists and practice characteristics have substantial influence on both productivity and list size. Adjusting list size to external factors seems to be an effective tool to increase productivity in general practice.
INTRODUCTION: Due to shortage of general practitioners, it may be necessary to improve productivity. We assess the association between productivity, list size and patient- and practice characteristics. MATERIAL AND METHODS: A regression approach is used to perform productivity analysis based on national register data and survey data for 1,758 practices. Practices are divided into four groups according to list size and productivity. Statistical tests are used to assess differences in patient- and practice characteristics. RESULTS: There is a significant, positive correlation between list size and productivity (p < 0.01). Nevertheless, 19% of the practices have a list size below and a productivity above mean sample values. These practices have relatively demanding patients (older, low socioeconomic status, high use of pharmaceuticals) and they are frequently located in areas with limited access to specialized care and have a low use of assisting personnel. 13% of the practices have a list size above and a productivity below mean sample values. These practices have relatively less demanding patients, are located in areas with good access to specialized care, and have a high use of assisting personnel. CONCLUSIONS: Lists and practice characteristics have substantial influence on both productivity and list size. Adjusting list size to external factors seems to be an effective tool to increase productivity in general practice.
Authors: Kim Rose Olsen; Dorte Gyrd-Hansen; Torben Højmark Sørensen; Troels Kristensen; Peter Vedsted; Andrew Street Journal: Eur J Health Econ Date: 2011-12-06
Authors: Søren F Birkeland; Anders K Haakonsson; Susanne S Pedersen; Nina Rottmann; Michael J Barry; Sören Möller Journal: J Med Internet Res Date: 2020-09-02 Impact factor: 5.428