Examining Geographic Variation of Opioid Use Disorder Encounters in the USA

Abstract

Objectives: The objectives were (1) to characterize patient encounters of opioid use disorder (OUD) using Health Facts^® database; and (2) to identify geographic variation, patient characteristics, and facility characteristics impacting patients' reduced OUD encounters over time.

Methods: Patient encounters were included if the patient (1) was 18 years old or greater; (2) had an index encounter; (3) survived at least 30 days after the discharge. The OUD encounter was based on ICD-10 codes. The date at which a patient first had an OUD encounter was the index date. For the first objective, OUD encounters were described according to patient characteristics, facility characteristics, and geographic variation. Patient characteristics were age, gender, marital status, race, health insurance coverage, discharge disposition, and patient type. Facility characteristics were care setting, medical specialty, census region, census division, urban vs. rural, acute vs. non-acute, and teaching hospital status. For the second objective, patients were examined 1 year prior to through 1 year after the index date. A logistic regression was used to determine the likelihood of reduced OUD encounters over time, conditional upon geographic variation, patient characteristics, and facility characteristics.

Results: A total of 265,643 OUD encounters were identified. East South Central was associated with the highest population-based rate of OUD among nine census divisions. In the logistic regression (n = 10,762), discharged to home, outpatient, emergency room, psychiatry, East North Central, West North Central, and urban areas were significant positive predictors for reduced OUD encounters over time, whereas age and Mountain were significant negative predictors.

Conclusions: East South Central was associated with the highest population-based rate of OUD. Compared with East South Central, East North Central and West North Central had a significantly positive impact on fewer encounters of OUD over time.

Keywords: Census division; Geographic variation; Health facts; Opioid use disorder; Patient encounter.