Resources allocation and health care needs in diabetes care in Danish GP clinics

Health Policy. 2013 Nov;113(1-2):206-15. doi: 10.1016/j.healthpol.2013.09.006. Epub 2013 Sep 25.

Abstract

Background: In several countries, morbidity burdens have prompted authorities to change the system for allocating resources among patients from a demographic-based to a morbidity-based casemix system. In Danish general practice clinics, there is no morbidity-based casemix adjustment system.

Aim: The aim of this paper was to assess what proportions of the variation in fee-for-service (FFS) expenditures are explained by type 2 diabetes mellitus (T2DM) patients' co-morbidity burden and illness characteristics.

Methods and data: We use patient morbidity characteristics such as diagnostic markers and co-morbidity casemix adjustments based on resource utilisation bands and FFS expenditures for a sample of 6706 T2DM patients in 59 general practices for the year 2010. We applied a fixed-effect approach.

Results: Average annual FFS expenditures were approximately 398 euro per T2DM patient. Expenditures increased progressively with the patients' degree of co-morbidity and were higher for patients who suffered from diagnostic markers. A total of 17-25% of the expenditure variation was explained by age, gender and patients' morbidity patterns.

Conclusion: T2DM patient morbidity characteristics are significant patient related FFS expenditure drivers in diabetes care. To address the specific health care needs of T2DM patients in GP clinics, our study indicates that it may be advisable to introduce a morbidity based casemix adjustment system.

Keywords: Expenditure variation; Fee-for-service; General practice; Resource utilisation band; The Johns Hopkins Adjusted Clinical Groups (ACG) System.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Comorbidity
  • Denmark / epidemiology
  • Diabetes Mellitus, Type 2 / epidemiology
  • Diabetes Mellitus, Type 2 / therapy*
  • Diagnosis-Related Groups
  • Female
  • General Practice / economics*
  • Health Expenditures / statistics & numerical data*
  • Health Services Needs and Demand*
  • Humans
  • Male
  • Middle Aged
  • Resource Allocation*
  • Risk Factors