Several factors influenced general practitioner participation in the implementation of a disease management programme

Dan Med J. 2014 Sep;61(9):A4901.


Introduction: Disease management programmes (DMPs) require a high degree of participation from general practitioners (GPs) in order to succeed. We aimed to describe the participation among Danish GPs in a DMP.

Material and methods: A quality improvement project entitled the Chronic Care Compass (CCC) was introduced in 2010 by the Central Denmark Region. The project was based on DMPs targeting persons suffering from three chronic diseases (diabetes, chronic obstructive pulmonary disease and acute coronary syndrome). All GPs in the region were invited to participate. We obtained data from administrative registries and studied the participation and its association with characteristics of practices and patients. Differences in participation were assessed using binomial regression models.

Results: A total of 271 (69.1%) practices participated in the CCC. The participation was 28.9 percentage points (pp) (confidence interval (CI): 14.3; 43.6) lower among GPs who were older than 60 years versus younger than 50 years, 32.2 pp (CI: 19.1; 45.2) lower among GPs who provided few versus many chronic care consultations, 13.7 pp (CI: 1.7; 25.6) lower among GPs with lower versus medium practice gross income, and 16.9 pp (CI:6.1; 27.8) lower among GPs with a patient population with medium versus low degree of socio-economic deprivation.

Conclusion: Participation in the CCC was lower among GPs who provided less chronic care, had a lower practice gross income and had a patient population with a higher degree of deprivation.

Funding: The project was supported by the Research Unit for General Practice, Aarhus University, and the Lundbeck Foundation.

Trial registration: not relevant.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Chronic Disease / therapy*
  • Denmark
  • Disease Management*
  • Female
  • General Practice / methods
  • General Practice / organization & administration*
  • General Practice / statistics & numerical data
  • Humans
  • Linear Models
  • Male
  • Middle Aged
  • Program Evaluation
  • Quality Improvement / organization & administration*