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Does variation in GP practice matter for the length of sick leave? A multilevel analysis based on Norwegian GP—patient data

Arild Aakvik, Tor Helge Holmås () and M. Kamrul Islam ()
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Tor Helge Holmås: Stein Rokkan Centre for Social Studies, Postal: Nygårdsgt. 5, N-5015 Bergen, Norway

No 17/08, Working Papers in Economics from University of Bergen, Department of Economics

Abstract: In many countries, the social insurance system is under pressure from an ageing population. An increasing number of people are on sickness benefits and disability pensions in Norway. The general practitioner (GP) is responsible for assessing work capacity and issuing certificates for sick leave based on an evaluation of the patient. Although many studies have analysed certified sickness absence and predictive factors, very few studies focus on the length of sick leave and no studies assess its variation between patients, GPs or geographical areas within a multilevel framework. This study aims to analyse factors explaining the variation in the length of certified sick leave and to disentangle patients, GPs and municipality sources of variation in sickness durations for the whole population of Norwegian workers in 2003. This study uses a unique Norwegian administrative data set that merges data from different sources. The study uses amatched patient—GP data set, and employs amultilevel random intercept model to separate out patient, GP and municipality-level explained and unexplained parts of the variation in the certified sickness durations. We find that all observed patient and GP characteristics are significantly associated with the length of sick leaves (LSL). However, 98% of the variation in the LSL is attributed to patient factors rather than influenced by variations in GP practice or differences in municipality-level characteristics. Medical diagnosis is an important observed factor explaining certified sickness durations. Low variations across GPs may imply that the gatekeeping role of Norwegian GPs is weak compared with their advocate role.

Keywords: general practitioners (GPs); length of sick leave; multilevel regression models; matched GP—patient data (search for similar items in EconPapers)
JEL-codes: I11 I12 I18 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2011-03-24
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