Identifying heavy health care users among primary care patients with chronic non-cancer pain

Objective: The objective of this study was to identify biopsychosocial factors predicting primary care chronic non-cancer pain (CNCP) patients’ risk of being heavy health care users. Methods: Patients reporting moderate to severe CNCP for at least 6 months with an active analgesic prescription from a primary care physician were recruited in community pharmacies. Recruited patients completed questionnaires documenting biopsychosocial characteristics. Using administrative databases, direct costs were estimated for health care services used by each patient in the year preceding and following the recruitment. Heavy health care users were defined as patients in the highest annual direct health care costs quartile. Logistic multivariate regression models using the Akaike information criterion were developed to identify predictors of heavy health care use. Results: The median annual direct health care cost incurred by heavy health care users (n = 63) was CAD (Canadian dollars) 7627, versus CAD 1554 for standard health care users (n = 188). The final predictive model of the risks of being a heavy health care user included pain located in the lower body (odds ratio [OR] = 3.03; 95% confidence interval [CI], 1.20–7.65), pain-related disability (OR = 1.24; 95% CI, 1.03–1.48), and health care costs incurred in the year prior to recruitment (OR = 17.67; 95% CI, 7.90–39.48). Variables in the model also included sex, comorbidity, patients’ depression level, and attitudes toward medical pain cure. Conclusion: Patients suffering from CNCP in the lower body and showing greater disability were more likely to be heavy health care users, even after adjusting for previous-year direct health care costs. Improving pain management for these patients could have positive impacts on health care use and costs.