Characteristics of High-Cost Patients Diagnosed with Opioid Abuse.

Abstract

Prescription opioid abuse is associated with substantial economic burden, with estimates of incremental annual per-patient health care costs of diagnosed opioid abuse exceeding $10,000 in prior literature. A subset of patients diagnosed with opioid abuse has disproportionately high health care costs, but little is known about the characteristics of these patients. To describe the characteristics of a subset of patients diagnosed with opioid abuse with disproportionately high health care costs to assist physicians and managed care organizations in targeting interventions at the costliest patients. This retrospective claims data analysis identified patients aged 12 to 64 years diagnosed with opioid abuse/dependence in the OptumHealth Reporting and Insights medical and pharmacy claims database, Quarter 1 (Q1) 1999-Q1 2012. Inclusion criteria required that patients had a diagnosis of opioid abuse during or after Q1 2006, no prior diagnoses of opioid abuse, and continuous non-HMO coverage over an 18-month study period. The study period comprised a 12-month observation period centered on the date of the first opioid abuse diagnosis (index date) and a 6-month baseline period immediately preceding the observation period. Patients in the top 20% of total health care costs in the observation period were classified as "high-cost patients," and the remaining patients were classified as "lower-cost patients." Patient characteristics, comorbidities, health care resource use, and health care costs were compared between high-cost patients and lower-cost patients using chi-square tests for dichotomous variables and Wilcoxon rank-sum tests for continuous variables. In addition, multivariate regression was used to assess the relationship between patient characteristics in the baseline period and total health care costs in the observation period among all patients diagnosed with opioid abuse. 9,291 patients diagnosed with opioid abuse met the inclusion criteria. The 20% of patients classified as high-cost patients accounted for approximately two thirds of the total health care costs of patients diagnosed with opioid abuse. Compared with lower-cost patients, high-cost patients were older (42.5 vs. 36.1; P less than 0.001) and more likely to be female (55.9% vs. 42.9%; P less than 0.001). They had a higher comorbidity burden at baseline, as reflected in the Charlson Comorbidity Index (0.8 vs. 0.2; P less than 0.001), and rates of conditions such as chronic pulmonary disease (12.9% vs. 5.6%; P less than 0.001) and mild/moderate diabetes (8.4% vs. 3.4%; P less than 0.001). High-cost patients also had higher rates of nonopioid substance abuse diagnoses (12.4% vs. 8.9%; P less than 0.001) and psychotic disorders (26.5% vs. 13.6%; P less than 0.001). In the observation period, high-cost patients continued to have higher rates of nonopioid substance abuse diagnoses (53.0% vs. 47.2%; P less than 0.001) and psychotic disorders (67.1% vs. 47.5%; P less than 0.001). In addition, they had greater medical resource use across all places of service (i.e., inpatient, emergency department, outpatient, drug/alcohol rehabilitation facility, and other) compared with lower-cost patients. The mean observation period health care costs of high-cost patients was $89,177 compared with $11,653 for lower-cost patients (P less than 0.001). High-cost patients had higher medical costs linked to claims with an opioid abuse diagnosis in absolute terms, but the share of total medical costs attributed to such claims was lower among high-cost patients than among lower-cost patients. While many baseline characteristics were found to have a statistically significant (P less than 0.05) association with observation period health care costs, only 27.3% of the variation in observation period health care costs was explained by patient characteristics in the baseline period. This study found that the costliest patients diagnosed with opioid abuse had high rates of preexisting and concurrent chronic comorbidities and mental health conditions, suggesting potential indicators for targeted intervention and a need for greater awareness and screening of comorbid conditions. Opioid abuse may exacerbate existing conditions and make it difficult for patients to adhere to treatment plans for those underlying conditions. Baseline patient characteristics explained only a small share of the variation in observation period health care costs, however. Future research should explore the degree to which other factors not captured in administrative claims data (e.g., severity of abuse) can explain the wide variation in health care costs among opioid abusers.