Utility of catastrophizing, body symptom diagram score and history of opioid use to predict future health care utilization after a primary care visit for musculoskeletal pain.

backgroundSelf-report information about pain and pain beliefs are often collected during initial consultation for musculoskeletal pain. These data may provide utility beyond the initial encounter, helping provide further insight into prognosis and long-term interactions of the patient with the health system.

objectiveThe aim of this study was to determine if pain catastrophizing and pain-related body symptoms can predict future health care utilization.

methodsThis was a longitudinal cohort study. Baseline data were collected after receiving initial care for a musculoskeletal disorder in a multidisciplinary clinic within a large military hospital. Subjects completed the Pain Catastrophizing Scale, a region-specific disability measure, numeric pain rating scale and a body symptom diagram. Health care utilization data for 1 year prior and after the visit were extracted from the Military Health System Data Repository. Multivariable regression models appropriate for skewed and count data were developed to predict (i) musculoskeletal-specific medical visits, (ii) 12-month opioid use, (iii) musculoskeletal-specific medical costs and (iv) total medical costs. We investigated whether a pain catastrophizing × body symptom diagram interaction improved prediction, and developed separate models for opioid-naïve individuals and those with a history of opioid use in an exploratory analysis.

resultsPain catastrophizing but not body symptom diagram was a significant predictor of musculoskeletal visits, musculoskeletal costs and total medical costs. Exploratory analyses suggest these relationships are most robust for patients with a history of opioid use.

conclusionsPain catastrophizing can identify risk of high health care utilization and costs, even after controlling for common clinical variables. Addressing pain catastrophizing in the primary care setting may help to mitigate future health care utilization and costs, while improving clinical outcomes. These results provide direction for future validation studies in larger and more traditional primary care settings.