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Our goal was to examine the association between mental health disorders (MHD) and subsequent risk of opioid use among commercially insured youth and adults (aged 14-64 years) with comorbid chronic noncancer pain (CNCP) conditions. We conducted a retrospective cohort study using IQVIA Health Plan Claims database from January 1, 2006, to December 31, 2015. Chronic noncancer pain was defined as any diagnosis of back, head, neck, arthritis, or chronic pain (index date). Mental health disorders were assessed in the 12 months before the index pain diagnosis. Based on days supply (none, acute, and chronic) and average daily dose (none, low, medium, and high), we constructed a 7-level categorical dependent measure of opioid use. We estimated the overall prevalence of MHD and opioid receipt. Among those with CNCP, multinomial logistic regression (AOR; 95 confidence interval) was used to estimate the association of MHD with opioid receipt. Among 879,815 individuals diagnosed with CNCP, 143,923 (16.4%) had comorbid MHD. Chronic/high-dose use of opioids was more common among those with CNCP and MHD compared to those with only CNCP. After adjusting for demographic and clinical factors, individuals with comorbid CNCP and MHD were significantly more likely to be prescribed opioids compared to those with only CNCP conditions. This effect varied by average daily dose and days supply: acute/low dose (1.08; 1.07-1.08); chronic/low dose (1.49; 1.49-1.50); acute/medium dose (1.07; 1.07-1.08); chronic/medium dose (1.61; 1.61-1.62); acute/high dose (1.03; 1.02-1.03); and chronic/high dose (1.53; 1.53-1.54). In individuals with CNCP, having a MHD was a strong predictor of prescription opioid use, particularly chronic use.

Aim: To evaluate the impact of chronic non-cancer pain (CNCP) on healthcare use and costs among individuals diagnosed with obstructive sleep apnea (OSA). Materials & methods: Using the IQVIA PharMetrics® Plus database, we identified individuals (18–64 years old) during 2007–2014, divided into two groups: OSA + CNCP versus OSA-only. Generalized linear models were used to analyze binary and count outcomes. Results: Relative to OSA-only controls, OSA + CNCP cases had increased odds for inpatient and emergency department visits and higher rates for physician office visits, non-physician outpatient visits, and prescription drug fills. Relative to controls, direct healthcare costs for cases were higher, primarily driven by inpatient and non-physician outpatient visit costs. Conclusion: Relative to OSA-only controls, OSA + CNCP cases displayed increased healthcare use and costs across all points of service.

Little is known about the associations between insomnia severity, insomnia symptoms, and key health outcomes. Using 2020 United States National Health and Wellness Survey (NHWS) data, we conducted a retrospective, cross-sectional analysis to determine the associations between insomnia severity and a number of health outcomes germane to patients (health-related quality of life (HRQoL), employers and government (workplace productivity), and healthcare payers (healthcare resource utilization (HCRU)). The Insomnia Severity Index (ISI) questionnaire was used to evaluate overall insomnia severity. HRQoL was assessed using the physical and mental component summary scores of the Short Form-36v2 (SF-36v2) questionnaire, and health utility status was measured using the Short Form-6D (SF-6D) and EuroQoL-5D (EQ-5D) questionnaires. Workplace productivity was measured using the Work Productivity and Activity Impairment (WPAI) questionnaire. After adjusting for confounders, greater insomnia severity was significantly associated with worsened quality of life, decreased productivity, and increased HCRU in an apparent linear fashion. These findings have important implications for future research, including the need for specific assessment of insomnia symptoms and their impact on key health outcomes.

Objective This study aimed to map the Insomnia Severity Index (ISI) to the EQ-5D-3L utility values from a UK perspective. Methods Source data were derived from the 2020 National Health and Wellness Survey (NHWS) for France, Germany, Italy, Spain, the UK and the US. Ordinary least squares regression, generalised linear model (GLM), censored least absolute deviation, and adjusted limited dependent variable mixture model (ALDVMM) were employed to explore the relationship between ISI total summary score and EQ-5D utility while accounting for adjustment covariates derived from the NHWS. Fitting performance was assessed using standard metrics, including mean-squared error (MSE) and coefficient of determination (R 2 ). Results A total of 17,955 respondent observations were included, with a mean ISI score of 12.12 ± 5.32 and a mean EQ-5D-3L utility (UK tariff) of 0.71 ± 0.23. GLM gamma-log and ALDVMM were the two best performing models. The ALDVMM had better fitting performance (R 2 = 0.320, MSE 0.0347) than the GLM gamma-log (R 2 = 0.303, MSE 0.0353); in train-test split-sample validation, ALDVMM also slightly outperformed the GLM gamma-log model, with an MSE of 0.0351 versus 0.0355. Based on fitting performance, ALDVMM and GLM gamma-log were the preferred models. Conclusions In the absence of preference-based measures, this study provides an updated mapping algorithm for estimating EQ-5D-3L utilities from the ISI summary total score. This new mapping not only draws its strengths from the use of a large international dataset but also the incorporation of adjustment variables (including sociodemographic and general health characteristics) to reduce the effects of confounders.