Publications

BACKGROUND: Florida's House Bill 21 (HB21), implemented into law on July 1, 2018, limited opioid prescriptions for acute pain to a 3-day supply. While the law has been associated with a decrease in opioid prescribing for acute pain, its effect on opioid volume dispensed at the plan level remains unknown. OBJECTIVES: To assess the impact of HB21 on the total volume dispensed of oral Schedule II opioids. We evaluated the change from before to after the law's implementation in (1) total number of opioid units dispensed per month and (2) total morphine milligram equivalent (MMEs) dispensed per month. METHODS: Pharmacy claims from July 2017 to June 2019 were analyzed from a private health plan serving a large Florida employer. We summed the number of units and the total MMEs dispensed for each month per 1,000 enrollees. Units were defined as the total quantity of tablets/capsules dispensed for each Schedule II oral opioid prescription. We used interrupted time series (ITS) models, accounting for autocorrelation, to determine any immediate change after the policy implementation and to estimate trends before and after the policy. RESULTS: We identified 16,226 prescriptions of oral Scheduled II opioids dispensed to 6,315 enrollees over a 2-year period. The HB21 law was associated with an immediate but not statistically significant decrease of 110.25 units dispensed per 1,000 enrollees in the month after implementation (95% CI: -218.84, -1.67; P = 0.06). There was an immediate but not statistically significant decrease of 1,456.29 MMEs dispensed per 1,000 enrollees following HB21 implementation (95% CI: -2,983.87, 71.29; P = 0.07). There were no significant changes in the slopes of the trends for total number of opioid units and total MMEs dispensed after HB21. CONCLUSIONS: Despite substantial lower quantities, there were no significant immediate reductions in total opioid units and MMEs dispensed in the year following the implementation of HB21. Our findings can inform other health plans on the potential effect of such restrictive laws and policies in other states where preexisting declining trends might have a higher impact than restriction policies. Future studies are needed to evaluate long-term intended and unintended consequences, including effects on patients' access to care, resulting from this type of restrictive law. DISCLOSURES: No outside funding supported this study. The authors report no conflicts of interest. Preliminary results of this study were presented at the Virtual ISPOR 2020 Conference held May 18-20, 2020.

BACKGROUND: Survivors of opioid overdose have substantially increased mortality risk, although this risk is not evenly distributed across individuals. No study has focused on predicting an individual's risk of death after a nonfatal opioid overdose.

OBJECTIVE: To predict risk of death after a nonfatal opioid overdose.

DESIGN AND PARTICIPANTS: This retrospective cohort study included 9686 Pennsylvania Medicaid beneficiaries with an emergency department or inpatient claim for nonfatal opioid overdose in 2014-2016. The index date was the first overdose claim during this period.

EXPOSURES, MAIN OUTCOME, AND MEASURES: Predictor candidates were measured in the 180 days before the index overdose. Primary outcome was 180-day all-cause mortality. Using a gradient boosting machine model, we classified beneficiaries into six subgroups according to their risk of mortality (< 25th percentile of the risk score, 25th to < 50th, 50th to < 75th, 75th to < 90th, 90th to < 98th, ≥ 98th). We then measured receipt of medication for opioid use disorder (OUD), risk mitigation interventions (e.g., prescriptions for naloxone), and prescription opioids filled in the 180 days after the index overdose, by risk subgroup.

KEY RESULTS: Of eligible beneficiaries, 347 (3.6%) died within 180 days after the index overdose. The C-statistic of the mortality prediction model was 0.71. In the highest risk subgroup, the observed 180-day mortality rate was 20.3%, while in the lowest risk subgroup, it was 1.5%. Medication for OUD and risk mitigation interventions after overdose were more commonly seen in lower risk groups, while opioid prescriptions were more likely to be used in higher risk groups (both p trends < .001).

CONCLUSIONS: A risk prediction model performed well for classifying mortality risk after a nonfatal opioid overdose. This prediction score can identify high-risk subgroups to target interventions to improve outcomes among overdose survivors.

BACKGROUND AND AIMS: Little is known about opioid and gabapentinoid (OPI-GABA) use duration and dose patterns' associations with adverse outcome risks. We examined associations between OPI-GABA dose and duration trajectories and subsequent drug overdose.

DESIGN: Retrospective cohort study.

SETTING: US Medicare.

PARTICIPANTS: Using a 5% sample (2011-16), we identified 71 005 fee-for-service Medicare beneficiaries with fibromyalgia, low back pain, neuropathy and/or osteoarthritis initiating OPIs and/or GABAs [mean age ± standard deviation (SD) = 65.5 ± 14.5 years, female = 68.1%, white = 76.8%].

MEASUREMENTS: Group-based multi-trajectory models identified distinct OPI-GABA use patterns during the year of OPI and/or GABA initiation, based on weekly average standardized daily dose (i.e. OPIs = morphine milligram equivalent, GABAs = minimum effective daily dose). We estimated models with three to 12 trajectories and selected the best model based on Bayesian information criterion (BIC) and Nagin's criteria. We estimated risk of time to first drug overdose diagnosis within 12 months following the index year, adjusting for socio-demographic and health factors using inverse probability of treatment weighted multivariable Cox proportional hazards models.

FINDINGS: We identified 10 distinct trajectories (BIC = -1 176 954; OPI-only = 3, GABA-only = 3, OPI-GABA = 4). Compared with OPI-only early discontinuers (40.6% of the cohort), 1-year drug overdose risk varied by trajectory group: consistent low-dose OPI-only users [16.6%; hazard ratio (HR) = 1.47, 95% confidence interval (CI) = 1.19-1.82], consistent high-dose OPI-only users (1.8%; HR = 4.57, 95% CI = 2.99-6.98), GABA-only early discontinuers (12.5%; HR = 1.39, 95% CI = 1.09-1.77), consistent low-dose GABA-only users (11.0%; HR = 1.44, 95% CI = 1.12-1.85), consistent high-dose GABA-only users (3.1%; HR = 1.43, 95% CI = 0.94-2.17), early discontinuation of OPIs and consistent low-dose GABA users (6.9%; HR = 1.24, 95% CI = 0.90-1.69), consistent low-dose OPI-GABA users (3.4%; HR = 2.49, 95% CI = 1.76-3.52), consistent low-dose OPI and high-dose GABA users (3.2%; HR = 2.46, 95% CI = 1.71-3.53) and consistent high-dose OPI and moderate-dose GABA users (0.9%; HR = 7.22, 95% CI = 4.46-11.69).

CONCLUSIONS: Risk of drug overdose varied substantially among US Medicare beneficiaries on different use trajectories of opioids and gabapentinoids. High-dose opioid-only users and all consistent opioid and gabapentinoid users (regardless of doses) had more than double the risk of subsequent drug overdose compared with opioid-only early discontinuers.

We examined the prevalence trends of non-human immunodeficiency virus (HIV) sexually transmitted infections (STI) and associated patient characteristics in U.S. ambulatory-care settings from 2005-2016. We conducted a retrospective repeated cross-sectional analysis using data from the National Ambulatory Medical Care Survey (NAMCS) for individuals aged 15-64 with a non-HIV STI-related visit. Data were combined into three periods (2005-2008, 2009-2012, and 2013-2016) to obtain reliable estimates. Logistic regression was used for analysis. A total of 19.5 million weighted, non-HIV STI-related ambulatory visits from 2005-2016 were identified. STI-related visits per 100,000 ambulatory care visits increased significantly over the study period: 206 (95% CI = 153-259), 343 (95% CI = 279-407), and 361 (95% CI = 277-446) in 2005-2008, 2009-2012, and 2013-2016, respectively (Ptrend = 0.003). These increases were mainly driven by increases in HPV-related visits (56 to 163 per 100,000 visits) from 2005-2008 to 2009-2012, followed by syphilis- or gonorrhea-related visits (30 to 67 per 100,000 visits) from 2009-2012 to 2013-2016. Higher odds of having STI-related visit were associated with younger age (aged 15-24: aOR = 4.45; 95% CI = 3.19-6.20 and aged 25-44: aOR = 3.59; 95% CI = 2.71-4.77) vs. 45-64-year-olds, Black race (aOR = 2.41; 95% CI = 1.78-3.25) vs. White, and HIV diagnosis (aOR = 10.60; 95% CI = 5.50-20.27) vs. no HIV diagnosis. STI-related office visits increased by over 75% from 2005-2016, and were largely driven by HPV-related STIs and syphilis- or gonorrhea-related STIs.

BACKGROUND AND AIMS: Our aim was to evaluate the impact of direct-acting antivirals (DAAs) on decompensated cirrhosis (DCC) and HCC in patients with chronic HCV and substance use disorder (SUD) compared with those without an SUD.

APPROACH AND RESULTS: This retrospective cohort study used the MarketScan database (2013-2018) to identify 29,228 patients with chronic HCV, where 22% (n = 6,385) had ≥1 SUD diagnosis. The inverse probability of treatment weighted multivariable Cox proportional hazard models were used to compare the risk of developing DCC and HCC. Among the those who were noncirrhotic, treatment reduced the DCC risk among SUD (adjusted hazard ratio [aHR] 0.13; 95% CI, 0.06-0.30) and non-SUD (aHR 0.11; 95% CI, 0.07-0.18), whereas the risk for HCC was not reduced for the SUD group (aHR 0.91; 95% CI, 0.33-2.48). For those with cirrhosis, compared with patients who were untreated, treatment reduced the HCC risk among SUD (aHR, 0.33; 95% CI, 0.13-0.88) and non-SUD (aHR, 0.40; 95% CI, 0.25-0.65), whereas the risk for DCC was not reduced for the SUD group (aHR, 0.64; 95% CI, 0.37-1.13). Among patients with cirrhosis who were untreated, the SUD group had a higher risk of DCC (aHR, 1.52; 95% CI, 1.03-2.24) and HCC (aHR, 1.69; 95% CI, 1.05-2.72) compared with non-SUD group.

CONCLUSIONS: Among the HCV SUD group, DAA treatment reduced the risk of DCC but not HCC for those who were noncirrhotic, whereas DAA treatment reduced the risk of HCC but not DCC for those with cirrhosis. Among the nontreated, patients with an SUD had a significantly higher risk of DCC and HCC compared with those without an SUD. Thus, DAA treatment should be considered for all patients with HCV and an SUD while also addressing the SUD.

BACKGROUND: Although analgesics are initiated on hospital discharge in millions of adults each year, studies quantifying the risks of opioids and nonsteroidal anti-inflammatory drugs (NSAIDs) among older adults during this transition are limited. We sought to determine the incidence and risk of post-discharge adverse events among older adults with an opioid claim in the week after hospital discharge, compared to those with NSAID claims only.

METHODS AND FINDINGS: We performed a retrospective cohort study using a national sample of Medicare beneficiaries age 65 and older, hospitalized in United States hospitals in 2016. We excluded beneficiaries admitted from or discharged to a facility. We derived a propensity score that included over 100 factors potentially related to the choice of analgesic, including demographics, diagnoses, surgeries, and medication coadministrations. Using 3:1 propensity matching, beneficiaries with an opioid claim in the week after hospital discharge (with or without NSAID claims) were matched to beneficiaries with an NSAID claim only. Primary outcomes included death, healthcare utilization (emergency department [ED] visits and rehospitalization), and a composite of known adverse effects of opioids or NSAIDs (fall/fracture, delirium, nausea/vomiting, complications of slowed colonic motility, acute renal failure, and gastritis/duodenitis) within 30 days of discharge. After propensity matching, there were 13,385 beneficiaries in the opioid cohort and 4,677 in the NSAID cohort (mean age: 74 years, 57% female). Beneficiaries receiving opioids had a higher incidence of death (1.8% versus 1.1%; relative risk [RR] 1.7 [1.3 to 2.3], p < 0.001, number needed to harm [NNH] 125), healthcare utilization (19.0% versus 17.4%; RR 1.1 [1.02 to 1.2], p = 0.02, NNH 59), and any potential adverse effect (25.2% versus 21.3%; RR 1.2 [1.1 to 1.3], p < 0.001, NNH 26), compared to those with an NSAID claim only. Specifically, they had higher relative risk of fall/fracture (4.5% versus 3.4%; RR 1.3 [1.1 to 1.6], p = 0.002), nausea/vomiting (9.2% versus 7.3%; RR 1.3 [1.1 to 1.4], p < 0.001), and slowed colonic motility (8.0% versus 6.2%; RR 1.3 [1.1 to 1.4], p < 0.001). Risks of delirium, acute renal failure, and gastritis/duodenitis did not differ between groups. The main limitation of our study is the observational nature of the data and possibility of residual confounding.

CONCLUSIONS: Older adults filling an opioid prescription in the week after hospital discharge were at higher risk for mortality and other post-discharge adverse outcomes compared to those filling an NSAID prescription only.

STUDY OBJECTIVES: To investigate the risk of in-hospital falls among patients receiving medications commonly used for insomnia in the hospital setting.

METHODS: Retrospective cohort study of all adult hospitalizations to a large academic medical center from January, 2007 to July, 2013. We excluded patients admitted for a primary psychiatric disorder. Medication exposures of interest, defined by pharmacy charges, included benzodiazepines, non-benzodiazepine benzodiazepine receptor agonists, trazodone, atypical antipsychotics, and diphenhydramine. In-hospital falls were ascertained from an online patient safety reporting system.

RESULTS: Among the 225,498 hospitalizations (median age = 57 years; 57.9% female) in our cohort, 84,911 (37.7%) had exposure to at least one of the five medication classes of interest; benzodiazepines were the most commonly used (23.5%), followed by diphenhydramine (8.3%), trazodone (6.6%), benzodiazepine receptor agonists (6.4%), and atypical antipsychotics (6.3%). A fall occurred in 2,427 hospitalizations (1.1%). The rate of falls per 1,000 hospital days was greater among hospitalizations with exposure to each of the medications of interest, compared to unexposed: 3.6 versus 1.7 for benzodiazepines (adjusted hazard ratio [aHR] 1.8, 95%CI 1.6-1.9); 5.4 versus 1.8 for atypical antipsychotics (aHR 1.6, 95%CI 1.4-1.8); 3.0 versus 2.0 for benzodiazepine receptor agonists (aHR 1.5, 95%CI 1.3-1.8); 3.3 versus 2.0 for trazodone (aHR 1.2, 95%CI 1.1-1.5); and 2.5 versus 2.0 for diphenhydramine (aHR 1.2, 95%CI 1.03-1.5).

CONCLUSIONS: In this large cohort of hospitalizations at an academic medical center, we found an association between each of the sedating medications examined and in-hospital falls. Benzodiazepines, benzodiazepine receptor agonists, and atypical antipsychotics had the strongest associations.

This cross-sectional study examines patterns of use of direct oral anticoagulants and their association with Medicare spending.

This study evaluates whether patients enrolled in trials of aducanumab, EMERGE and ENGAGE, were representative of patients with dementia enrolled in Medicare by estimating the proportions of Medicare beneficiaries with Alzheimer disease (AD) or mild cognitive impairment (MCI) who would have been excluded from these trials.