How does comorbidity influence healthcare costs? A population-based cross-sectional study of depression, back pain and osteoarthritis

OBJECTIVES: To analyse how comorbidity among patients with back pain, depression and osteoarthritis influences healthcare costs per patient. A special focus was made on the distribution of costs for primary healthcare compared with specialist care, hospital care and drugs. DESIGN: Population-based cross-sectional study. SETTING: The County of Östergötland, Sweden. PATIENTS: Data on diagnoses and healthcare costs for all 266 354 individuals between 20 and 75 years of age, who were residents of the County of Östergötland, Sweden, in the year 2006, were extracted from the local healthcare register and the national register of drug prescriptions. MAIN OUTCOME MEASURES: The effects of comorbidity on healthcare costs were estimated as interactions in regression models that also included age, sex, number of other health conditions and education. RESULTS: The largest diagnosed group was back pain (11 178 patients) followed by depression (7412 patients) and osteoarthritis (5174 patients). The largest comorbidity subgroup was the combination of back pain and depression (772 patients), followed by the combination of back pain and osteoarthritis (527 patients) and the combination of depression and osteoarthritis (206 patients). For patients having both a depression diagnosis and a back pain diagnosis, there was a significant negative interaction effect on total healthcare costs. The average healthcare costs among patients with depression and back pain was SEK 11 806 lower for a patient with both diagnoses. In this comorbidity group, there were tendencies of a positive interaction for general practitioner visits and negative interactions for all other visits and hospital days. Small or no interactions at all were seen between depression diagnoses and osteoarthritis diagnoses. CONCLUSIONS: A small increase in primary healthcare visits in comorbid back pain and depression patients was accompanied with a substantial reduction in total healthcare costs and in hospital costs. Our results can be of value in analysing the cost effects of comorbidity and how the coordination of primary and secondary care may have an impact on healthcare costs.