Publications

Suicide is a leading cause of death in the US. Patients with pain conditions have higher suicidal risks. In a systematic review searching observational studies from multiple sources (e.g., MEDLINE) from 1 January 2000-12 September 2020, we evaluated existing suicide prediction models' (SPMs) performance and identified risk factors and their derived data sources among patients with pain conditions. The suicide-related outcomes included suicidal ideation, suicide attempts, suicide deaths, and suicide behaviors. Among the 87 studies included (with 8 SPM studies), 107 suicide risk factors (grouped into 27 categories) were identified. The most frequently occurring risk factor category was depression and their severity (33%). Approximately 20% of the risk factor categories would require identification from data sources beyond structured data (e.g., clinical notes). For 8 SPM studies (only 2 performing validation), the reported prediction metrics/performance varied: C-statistics (n = 3 studies) ranged 0.67-0.84, overall accuracy(n = 5): 0.78-0.96, sensitivity(n = 2): 0.65-0.91, and positive predictive values(n = 3): 0.01-0.43. Using the modified Quality in Prognosis Studies tool to assess the risk of biases, four SPM studies had moderate-to-high risk of biases. This systematic review identified a comprehensive list of risk factors that may improve predicting suicidal risks for patients with pain conditions. Future studies need to examine reasons for performance variations and SPM's clinical utility.

BACKGROUND: The Veterans Health Administration (VHA) developed the Stratification Tool for Opioid Risk Mitigation (STORM) dashboard to assist in identifying Veterans at risk for adverse opioid overdose or suicide-related events. In 2018, a policy was implemented requiring VHA facilities to complete case reviews of Veterans identified by STORM as very high risk for adverse events. Nationally, facilities were randomized in STORM implementation to four arms based on required oversight and by the timing of an increase in the number of required case reviews. To help evaluate this policy intervention, we aimed to (1) identify barriers and facilitators to implementing case reviews; (2) assess variation across the four arms; and (3) evaluate associations between facility characteristics and implementation barriers and facilitators.

METHOD: Using the Consolidated Framework for Implementation Research (CFIR), we developed a semi-structured interview guide to examine barriers to and facilitators of implementing the STORM policy. A total of 78 staff from 39 purposefully selected facilities were invited to participate in telephone interviews. Interview transcripts were coded and then organized into memos, which were rated using the -2 to + 2 CFIR rating system. Descriptive statistics were used to evaluate the mean ratings on each CFIR construct, the associations between ratings and study arm, and three facility characteristics (size, rurality, and academic detailing) associated with CFIR ratings. We used the mean CFIR rating for each site to determine which constructs differed between the sites with highest and lowest overall CFIR scores, and these constructs were described in detail.

RESULTS: Two important CFIR constructs emerged as barriers to implementation: Access to knowledge and information and Evaluating and reflecting. Little time to complete the CASE reviews was a pervasive barrier. Sites with higher overall CFIR scores showed three important facilitators: Leadership engagement, Engaging, and Implementation climate. CFIR ratings were not significantly different between the four study arms, nor associated with facility characteristics.Plain Language Summary: The Veterans Health Administration (VHA) created a tool called the Stratification Tool for Opioid Risk Mitigation dashboard. This dashboard shows Veterans at risk for opioid overdose or suicide-related events. In 2018, a national policy required all VHA facilities to complete case reviews for Veterans who were at high risk for these events. To evaluate this policy implementation, 78 staff from 39 facilities were interviewed. The Consolidated Framework for Implementation Research (CFIR) implementation framework was used to create the interview. Interview transcripts were coded and organized into site memos. The site memos were rated using CFIR's -2 to +2 rating system. Ratings did not differ for four study arms related to oversight and timing. Ratings were not associated with facility characteristics. Leadership, engagement and implementation climate were the strongest facilitators for implementation. Lack of time, knowledge, and feedback were important barriers.

BACKGROUND: For atrial fibrillation (AF) patients, oral anticoagulants (OACs) can reduce the risk of stroke by 60%; however, nearly 50% of patients recommended to receive OACs do not receive therapy. Integrated insurers that cover pharmacy and medical benefits may be incentivized to improve OAC use and adherence because they benefit from offsets in medical costs associated with prevented strokes. OBJECTIVE: To compare OAC use and adherence between AF patients enrolled in Medicare stand-alone prescription drug plans (PDPs), which only cover pharmacy benefits, and those enrolled in Medicare Advantage prescription drug (MAPD) plans, which cover medical and pharmacy benefits. METHODS: This was a retrospective cohort study, conducted using 2014-2016 Medicare claims data from the Centers for Medicare & Medicaid Services and a large regional health plan in Pennsylvania. Primary outcomes included OAC use and OAC adherence. OAC use was measured as filling at least 1 prescription for an OAC after AF diagnosis. OAC adherence was defined as having greater than or equal to 80% of days covered with an OAC. We constructed conditional logistic regression models in propensity score-matched samples to test the association between enrollment in PDPs or MAPD plans and outcomes. RESULTS: There were 2,551 AF patients enrolled in PDPs and 4,502 in MAPD plans before propensity score matching. The propensity score-matched sample included 2,537 patients in each group. OAC use was higher among MAPD beneficiaries (74%-76%) compared with PDP beneficiaries (70%; P < 0.001), and 41%-42% of MAPD beneficiaries were adherent to OACs, compared with 34% of PDP beneficiaries (P < 0.001). In adjusted analyses among propensity score-matched samples, PDP enrollment was associated with lower odds of OAC use (OR = 0.67, 95% CI = 0.56-0.81) and adherence (OR = 0.68, 95% CI = 0.59-0.78) compared with MAPD enrollment. CONCLUSIONS: AF patients enrolled in MAPD plans were more likely to use and adhere to OACs compared with PDP enrollees. These results may reflect the financial incentives of MAPD plans to improve guideline-recommended OAC use, since MAPD insurers bear the risk of pharmacy and medical costs and thus may benefit from cost savings associated with averted stroke events. As efforts to improve use and adherence of OACs in AF patients increase, focus should be given to how insurance benefit designs can affect medication use. DISCLOSURES: No outside funding supported this study. Hernandez has received personal fees from BMS and Pfizer, unrelated to this study. The other authors have nothing to disclose.

BACKGROUND: Oral anticoagulants (OAC) is indicated for stroke prevention in patients with atrial fibrillation (AF) with a moderate or high risk of stroke. Despite the benefits of stroke prevention, only 50%-60% of Americans with nonvalvular AF and a moderate or high risk of stroke receive OAC medication. OBJECTIVE: To understand the extent to which low OAC use by patients with AF is attributed to underprescribing or underfilling once the medication is prescribed. METHODS: This is a retrospective cohort study that used linked claims data and electronic health records from Optum Integrated data. Participants were adults (aged ≥ 18 years) with first AF between January 2013 and June 2017. The outcomes included (1) being prescribed OACs within 180 days of AF diagnosis or not and (2) filling an OAC prescription or not among patients with AF who were prescribed an OAC within 150 days of AF diagnosis. Multivariable logistic regression models were constructed to determine factors associated with underprescribing and underfilling. RESULTS: Of the 6,141 individuals in the study cohort, 51% were not prescribed OACs within 6 months of their AF diagnosis. Of the 2,956 patients who were prescribed, 19% did not fill it at the pharmacy. In the final adjusted model, younger age, location (Northeast and South), a low CHA2DS2-VASc score, and a high HAS-BLED score were associated with a lower likelihood of being prescribed OACs. Among patients who were prescribed, Medicare enrollment (odds ratio [OR] [95% CI] = 2.2 [1.3-3.7]) and having a direct oral anticoagulant prescription (1.5 [1.2-1.9]) were associated with a lower likelihood of filling the prescription. CONCLUSIONS: Both underprescribing and underfilling are major drivers of low OAC use among patients with AF, and solutions to increase OAC use must address both prescribing and filling. DISCLOSURES: Research reported in this study was supported by the National Heart, Lung and Blood Institute (K01HL142847 and R01HL157051). Dr Guo is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK133465), PhMRA Foundation Research Starter Award, and the University of Florida Research Opportunity Seed Fund. Dr Hernandez reports scientific advisory board fees from Pfizer and Bristol Myers Squibb, outside of the submitted work.

BACKGROUND AND AIMS: Barrett's esophagus (BE) screening is not highly utilized in the United States, and there are few data describing providers' approach to screening. To fill this gap and guide the implementation of future BE screening strategies, we studied evaluation practice patterns for gastroesophageal reflux disease (GERD) by nongastroenterologists.

METHODS: We performed a retrospective cohort study of patients with chronic GERD using health claims data from the United States between 2005 and 2019. We used up to 5 years of data after the diagnosis of chronic GERD to determine patient factors associated with completion of a gastroenterology encounter. We also identified patient factors associated with whether the first gastroenterology encounter was a direct-access upper endoscopy or an office visit.

RESULTS: We identified 484,023 patients diagnosed with chronic GERD by a nongastroenterology provider. The cumulative incidence of completing a gastroenterology encounter within 5 years was 38.7%. Gastrointestinal symptoms, such as dysphagia (adjusted hazard ratio [aHR] = 2.11, 95% confidence interval [CI] = 1.94-2.30), abdominal pain (aHR = 1.89, 95% CI = 1.85-1.94), and melena (aHR = 1.73, 95% CI = 1.65-1.82), were strongly associated with completion of a gastroenterology encounter. The patient factors strongly associated with direct-access upper endoscopy included dysphagia (aHR = 1.68, 95% CI = 1.52-1.85), weight loss (aHR = 1.46, 95% CI = 1.28-1.63), and melena (aHR = 1.42, 95% CI = 1.28-1.56).

CONCLUSION: A total of 38.7% of patients with chronic GERD complete a gastroenterology encounter within 5 years of diagnosis, and gastrointestinal alarm symptoms are the most strongly associated factors for receiving gastroenterology care. These findings highlight the importance of incorporating primary care providers in the development of new BE screening programs.

PURPOSE: We examined the prevalence of, and factors associated with, serious opioid-related adverse drug events (ORADEs) that led to an emergency department (ED) visit or hospitalization among patients with chronic gastrointestinal (GI) symptoms and disorders dually enrolled in the Department of Veterans Affairs (VA) and Medicare Part D.

METHODS: In this retrospective cohort study, we used linked national patient-level data (April 1, 2011, to October 31, 2014) from the VA and Centers for Medicare and Medicaid Services to identify serious ORADEs among dually enrolled veterans with a chronic GI symptom or disorder. Outcome measures included serious ORADEs, defined as an ED visit attributed to an ORADE or a hospitalization where the principal or secondary reason for admission involved an opioid. We used multiple logistic regression models to determine factors independently associated with a serious ORADE.

RESULTS: We identified 3,430 veterans who had a chronic GI symptom or disorder; were dually enrolled in the VA and Medicare Part D; and had a serious ORADE that led to an ED visit, hospitalization, or both. The period prevalence of having a serious ORADE was 2.4% overall and 4.4% among veterans with chronic opioid use (≥90 consecutive days). Veterans with serious ORADEs were more likely to be less than 40 years old, male, white, and to have chronic abdominal pain, functional GI disorders, chronic pancreatitis, or Crohn's disease. They were also more likely to have used opioids chronically and at higher daily doses.

CONCLUSION: There may be a considerable burden of serious ORADEs among patients with chronic GI symptoms and disorders. Future quality improvement efforts should target this vulnerable population.

BACKGROUND AND AIMS: One-third of opioid (OPI) overdose deaths involve concurrent benzodiazepine (BZD) use. Little is known about concurrent opioid and benzodiazepine use (OPI-BZD) most associated with overdose risk. We aimed to examine associations between OPI-BZD dose and duration trajectories, and subsequent OPI or BZD overdose in US Medicare.

DESIGN: Retrospective cohort study.

SETTING: US Medicare.

PARTICIPANTS: Using a 5% national Medicare data sample (2013-16) of fee-for-service beneficiaries without cancer initiating OPI prescriptions, we identified 37 879 beneficiaries (age ≥ 65 = 59.3%, female = 71.9%, white = 87.6%, having OPI overdose = 0.3%).

MEASUREMENTS: During the 6 months following OPI initiation (i.e. trajectory period), we identified OPI-BZD dose and duration patterns using group-based multi-trajectory models, based on average daily morphine milligram equivalents (MME) for OPIs and diazepam milligram equivalents (DME) for BZDs. To label dose levels in each trajectory, we defined OPI use as very low (< 25 MME), low (25-50 MME), moderate (51-90 MME), high (91-150 MME) and very high (>150 MME) dose. Similarly, we defined BZD use as very low (< 10 DME), low (10-20 DME), moderate (21-40 DME), high (41-60 DME) and very high (> 60 DME) dose. Our primary analysis was to estimate the risk of time to first hospital or emergency department visit for OPI overdose within 6 months following the trajectory period using inverse probability of treatment-weighted Cox proportional hazards models.

FINDINGS: We identified nine distinct OPI-BZD trajectories: group A: very low OPI (early discontinuation)-very low declining BZD (n = 10 598; 28.0% of the cohort); B: very low OPI (early discontinuation)-very low stable BZD (n = 4923; 13.0%); C: very low OPI (early discontinuation)-medium BZD (n = 4997; 13.2%); D: low OPI-low BZD (n = 5083; 13.4%); E: low OPI-high BZD (n = 3906; 10.3%); F: medium OPI-low BZD (n = 3948; 10.4%); G: very high OPI-high BZD (n = 1371; 3.6%); H: very high OPI-very high BZD (n = 957; 2.5%); and I: very high OPI-low BZD (n = 2096; 5.5%). Compared with group A, five trajectories (32.3% of the study cohort) were associated with increased 6-month OPI overdose risks: E: low OPI-high BZD [hazard ratio (HR) = 3.27, 95% confidence interval (CI) = 1.61-6.63]; F: medium OPI-low BZD (HR = 4.04, 95% CI = 2.06-7.95); G: very high OPI-high BZD (HR = 6.98, 95% CI = 3.11-15.64); H: very high OPI-very high BZD (HR = 4.41, 95% CI = 1.51-12.85); and I: very high OPI-low BZD (HR = 6.50, 95% CI = 3.15-13.42).

CONCLUSIONS: Patterns of concurrent opioid and benzodiazepine use most associated with overdose risk among fee-for-service US Medicare beneficiaries initiating opioid prescriptions include very high-dose opioid use (MME > 150), high-dose benzodiazepine use (DME > 40) or medium-dose opioid with low-dose benzodiazepine use.

IMPORTANCE: Prescription opioids can treat acute pain in primary care but have potential for unsafe use and progression to prolonged opioid prescribing.

OBJECTIVE: To compare clinician-facing interventions to prevent unsafe opioid prescribing in opioid-naive primary care patients with acute noncancer pain.

DESIGN SETTING AND PARTICIPANTS: We conducted a multisite, cluster-randomized, 2 × 2 factorial, clinical trial in 3 health care systems that comprised 48 primary care practices and 525 participating clinicians from September 2018 through January 2021. Patient participants were opioid-naive outpatients, 18 years or older, who presented for a qualifying clinic visit with acute noncancer musculoskeletal pain or nonmigraine headache.

INTERVENTIONS: Practices randomized to: (1) control; (2) opioid justification; (3) monthly clinician comparison emails; or (4) opioid justification and clinician comparison. All groups received opioid prescribing guidelines via the electronic health record at the time of a new opioid prescription.

MAIN OUTCOMES AND MEASURES: Primary outcome measures were receipt of an initial opioid prescription at the qualifying clinic visit. Other outcomes were opioid prescribing for more than 3 months and a concurrent opioid/benzodiazepine prescription over 12-month follow-up.

RESULTS: Among 22 616 enrolled patient participants (9740 women [43.1%]; 64 American Indian/Alaska Native [0.3%]; 590 Asian [2.6%], 1120 Black/African American [5.0%], 1777 Hispanic [7.9%], 225 Native Hawaiian/Pacific Islander [1.0%], and 18 981 White [83.9%] individuals), the initial opioid prescribing rates at the qualifying clinic visit were 3.1% in the total sample, 4.2% in control, 3.6% in opioid justification, 2.6% in clinician comparison, and 1.9% in opioid justification and clinician comparison. Compared with control, the adjusted odds ratio (aOR) for a new opioid prescription was 0.74 (95% CI, 0.46-1.18; P = .20) for opioid justification and 0.60 (95% CI, 0.38-0.96; P = .03) for clinician comparison. Compared with control, clinician comparison was associated with decreased odds of opioid therapy of more than 3 months (aOR, 0.79; 95% CI, 0.69-0.91; P = .001) and concurrent opioid/benzodiazepine prescription (aOR, 0.85; 95% CI, 0.72-1.00; P = .04), whereas opioid justification did not have a significant effect.

CONCLUSIONS AND RELEVANCE: In this cluster randomized clinical trial, comparison emails decreased the proportion of opioid-naive patients with acute noncancer pain who received an opioid prescription, progressed to treatment with long-term opioid therapy, or were exposed to concurrent opioid and benzodiazepine therapy. Health care systems can consider adding clinician-targeted nudges to other initiatives as an efficient, scalable approach to further decrease potentially unsafe opioid prescribing.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03537573.