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Type II diabetes patients in primary care : profiles of healthcare utilization obtained from observational data

By C.E. van Dijk, T. Hoekstra, R.A. Verheij, J.W.R. Twisk, P.P. Groenewegen, F.G. Schellevis and [No Value] et al

Abstract

Background The high burden of diabetes for healthcare costs and their impact on quality of life and management of the disease have triggered the design and introduction of disease management programmes (DMPs) in many countries. The extent to which diabetes patients vary with regard to their healthcare utilisation and costs is largely unknown and could impact on the design of DMPs. The objectives of this study are to develop profiles based on both the diabetes-related healthcare utilisation and total healthcare utilisation in primary care, to investigate which patient and disease characteristics determine ‘membership’ of each profile, and to investigate the association between these profiles. Methods Data were used from electronic medical records of 6721 known type II diabetes patients listed in 48 Dutch general practices. Latent Class Analyses were conducted to identify profiles of healthcare and regression analyses were used to analyse the characteristics of the profiles. Results For both diabetes-related healthcare utilisation and total healthcare utilisation three profiles could be distinguished: for the diabetes-related healthcare utilisation these were characterised as ‘high utilisation and frequent home visits’ (n=393), ‘low utilisation, GP only’ (n=3231) and ‘high utilisation, GP and nurse’ (n=3097). Profiles differed with respect to the patients’ age and type of medication; the oldest patients using insulin were dominant in the ‘high utilisation, GP and nurse’ profile. High total healthcare utilisation was not associated with high diabetes-related healthcare utilisation. Conclusions Healthcare utilisation of diabetes patients is heterogeneous. This challenges the development of distinguishable DMPs

Topics: Type II diabetes mellitus, Healthcare utilisation profiles, Primary care, Latent Class Analyses
Year: 2013
OAI identifier: oai:dspace.library.uu.nl:1874/306895
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