Knowledge, practice and attitudes regarding substance use disorder treatment and harm reduction strategies among pharmacists: a scoping review protocol.

INTRODUCTION: Pharmacists provide a spectrum of services and comprehensive medication management for patients with substance use disorders (SUDs) with many providing timely and increased access to care for patients. Prior studies have evaluated other healthcare professionals' attitudes, knowledge and practice in regard to SUD treatment and harm reduction services. However, no reviews to date summarise the available literature on the attitudes, knowledge and practice in regard to SUD treatment and harm reduction services from the pharmacist perspective. This scoping review aims to systematically map the extent, range and nature of available evidence and identify and describe gaps in knowledge, practice and attitudes towards SUD treatment among pharmacists with the goal of providing information for meaningful integration of pharmacists into SUD care. METHODS AND ANALYSIS: We will use the framework proposed by Arksey and O'Malley (2005) updated with recommendations by Levac et al (2010) and the Joanna Briggs Institute (2020). The protocol is registered via Open Science Framework (https://osf.io/92dek). We will search for peer-reviewed literature containing empirical evidence investigating SUD treatment or harm reduction with outcomes pertaining to the knowledge, practice or attitudes of pharmacists. Findings will be guided and assessed by research objectives and summarised using descriptive statistics and thematically for quantitative and qualitative findings, respectively. This review will be conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews. ETHICS AND DISSEMINATION: Our findings will provide crucial information and support for future interventions and programmes which aim to meaningfully integrate pharmacists into SUD care. We will disseminate findings at conferences and publish in a peer-reviewed journal. In addition, we will integrate feedback on search strategy, data extraction and our dissemination approach from multidisciplinary collaborators including those within our team's institution and outside experts with clinical or administrative knowledge in SUD care.

The Role of Physician Networks and Receipt of Opioid-Related Payments.

BACKGROUND: Opioid-related promotional payments are associated with increased prescribing of the promoted drug, but little is known about whether physicians receiving payments influence peers to accept similar payments. OBJECTIVE: We examine the association of physician network-level position among peers and the acceptance of opioid-related promotional payments using national publicly available datasets from 2015. Design National cross-sectional data from the Centers for Medicare and Medicaid Services (CMS) National Downloadable File and Open Payment data. SUBJECTS: Physicians who shared Medicare patients with at least two other physicians in 2015. MAIN MEASURES: Modified Poisson's regressions are used to estimate the adjusted incidence rate ratio (aIRR) for social network position (i.e., degree, betweenness, and transitivity) and number of peers with payments as a function of individual receipt of opioid-related promotional payment and among those with payments, those who have five or more payments, and those who have $100 or more in payments. KEY RESULTS: Physicians with opioid-related payments were significantly more likely to have at least one peer with an opioid-related payment (IRR: 2.5, 95% CI: 2.3-2.8), but had fewer shared patients (i.e., top quartile compared to the first quartile for degree centrality: 0.4, 95% CI: 0.3-0.4) and belonged to less cohesive networks (i.e., top quartile compared to the first quartile for betweenness centrality: 0.9, 95% CI: 0.8-0.9). CONCLUSIONS: Our study demonstrates that physicians receiving opioid-related payments are more likely to cluster within physician networks.

Characterizing industry payments to US teaching hospitals and affiliated physicians: a cross-sectional analysis of the Open Payments datasets from 2016 to 2022.

Industry payments to US teaching hospitals are common; however, little is known about whether these financial relationships influence affiliated physicians to engage in similar financial relationships with industry. Using national hospital, physician, and industry payment data we investigated trends in industry payments made to US teaching hospitals and affiliated physicians to characterize the magnitude and nature of payments. In addition, we assessed if physicians may be influenced to accept higher value industry payments depending on the value of promotional payments accepted by the teaching hospital they affiliate with. We found that physicians with a US teaching hospital affiliation are associated with accepting higher value industry payments as the total value of industry payments of the teaching hospital increases. Our findings varied by specialty, with surgeons accepting the highest value payments. These results highlight the need for greater public disclosure and awareness of payments to better manage and mitigate industry-biased clinical decision making.

Little Consistency In Evidence Cited By Commercial Plans For Specialty Drug Coverage.

We found wide variation in the evidence that US commercial health plans reported reviewing in their specialty drug coverage policies. There was little consistency in the numbers or types of studies cited by health plans. On average, only 15 percent of health plans' coverage policies cited the same study evaluating a specific drug for a specific indication.

Discrepancies Between FDA-Required Labeling and Evidence that Payers Cite in Drug Coverage Policies.

BACKGROUND: FDA-required labeling summarizes certain data that the FDA relies on in its drug approval process. However, when determining coverage of specialty drugs, health care payers may consider dissimilar evidence. OBJECTIVE: To compare evidence cited by the largest U.S. commercial payers in their specialty drug coverage policies with evidence featured in the labeling of the indicated drugs. METHODS: We used the Tufts Medical Center Specialty Drug Evidence and Coverage Database (SPEC)-a database of specialty drug coverage policies issued by 17 of the 20 largest U.S. commercial health care payers-to identify coverage policies for drugs indicated for multiple sclerosis, rheumatoid arthritis, juvenile idiopathic arthritis, ankylosing spondylitis, and non-small cell lung cancer (NSCLC). These disease categories were selected because each was represented by multiple drugs. For each drug, we identified endpoints included in the clinical studies presented in the FDA-required labeling. Using SPEC, we identified randomized controlled trials (RCTs) and other clinical studies that at least 1 payer cited in its coverage policies for the included drugs. We reviewed the full text of each study to identify the endpoints reported. We categorized endpoints as identical to endpoints in the FDA-required labeling of the drugs; similar (e.g., a different measurement scale was used to evaluate the same endpoint); and different (the endpoint was not featured in the FDA-required labeling). RESULTS: We included 41 drugs and reviewed 348 studies (246 RCTs and 102 other clinical studies). Of 2,237 endpoints, 63% were categorized as identical, 26% as similar, and 12% as different. Rheumatoid arthritis was the indication with the largest proportion of endpoints categorized as identical (74% of endpoints in the RCTs cited by payers; 59% of endpoints in the other clinical studies cited by payers). NSCLC was the indication with the largest proportion of endpoints categorized as different (33% of end-points in the RCTs cited by payers; 37% of endpoints in the other clinical studies cited by payers). CONCLUSIONS: Payers often report reviewing clinical evidence that goes beyond information included in FDA-required labeling. Our findings suggest that the FDA should continue engaging with the manufacturer and payer communities to appropriately facilitate communication of information necessary to allow for informed coverage decisions. DISCLOSURES: This study was funded by an unrestricted grant from the Pharmaceutical Research and Manufacturers of America. The authors work with The Center for the Evaluation of Value and Risk in Health, which is partially supported through the CEA Registry Sponsorship program; the CEA Registry has received funding from the National Science Foundation, National Library of Medicine, Agency for Healthcare Research and Quality, Centers for Disease Control and Prevention, and a variety of pharmaceutical and device companies that subscribe to the data. Chambers reports personal fees from Health Advances, Ernst & Young, Magellan Health, Summit Therapeutics, and Sanofi-Aventis, unrelated to this study. Neumann reports past advisory board work with Amgen, Avexis, Axovant, Bayer, Bluebird, Congressional Budget Office, Janssen, Merck, Novo Nordisk, Pacira, Paratek, and Sage; consulting work for Boston Health Economics, GSK, Precision Health Economics, Veritech, and Vertex; speaker fees from AbbVie, Celgene, and Roche; and grants from the Alzheimer's Association, Amgen, Gates, Lundbeck, NIH, NPC, and Sage, all unrelated to this study. The other authors have nothing to disclose.

Comorbidity Type and Health Care Costs in Type 2 Diabetes: A Retrospective Claims Database Analysis.

INTRODUCTION: Previous studies suggest that the type and combination of comorbidities may impact diabetes care, but their cost implications are less clear. This study characterized how diabetes patients' health care utilization and costs may vary according to comorbidity type classified on the basis of the Piette and Kerr framework. METHODS: We conducted a retrospective observational study of privately insured US adults newly diagnosed with type 2 diabetes (n = 138,466) using the 2014-2016 Optum Clinformatics® Data Mart. Diabetes patients were classified into five mutually exclusive comorbidity groups: concordant only, discordant only, both concordant and discordant, any dominant, and none. We estimated average health care costs of each comorbidity group by using generalized linear models, adjusting for patient demographics, region, insurance type, and prior-year costs. RESULTS: Most type 2 diabetes patients had discordant conditions only (27%), dominant conditions (25%), or both concordant and discordant conditions (24%); 7% had concordant conditions only. In adjusted analyses, comorbidities were significantly associated with higher health care costs (p < 0.0001) and the magnitude of the association varied with comorbidity type. Diabetes patients with dominant comorbidities incurred substantially higher costs ($38,168) compared with individuals with both concordant and discordant conditions ($20,401), discordant conditions only ($9173), concordant conditions only ($9000), and no comorbidities ($3365). More than half of the total costs in our sample (53%) were attributable to 25% of diabetes patients who had dominant comorbidities. CONCLUSIONS: Diabetes patients with both concordant and discordant conditions and with clinically dominant conditions incurred substantially higher health costs than other diabetes patients. Our findings suggest that diabetes management programs must explicitly address concordant, discordant, and dominant conditions because patients may have distinctly different health care needs and utilization patterns depending on their comorbidity profiles. The Piette and Kerr framework may serve as a screening tool to identify high-need, high-cost diabetes patients and suggest targets for tailored interventions. FUNDING: Sanofi.

Specialty Drug Coverage Varies Across Commercial Health Plans In The US.

We analyzed specialty drug coverage decisions issued by the largest US commercial health plans to examine variation in coverage and the consistency of those decisions with indications approved by the Food and Drug Administration (FDA). Across 3,417 decisions, 16 percent of the 302 drug-indication pairs were covered the same way by all of the health plans, and 48 percent were covered the same way by 75 percent of the plans. Specifically, 52 percent of the decisions were consistent with the FDA label, 9 percent less restrictive, 2 percent mixed (less restrictive in some ways but more restrictive in others), and 33 percent more restrictive, while 5 percent of the pairs were not covered. Health plans restricted coverage of drugs indicated for cancer less often than they did coverage of drugs indicated for other diseases. Using multivariate regression, we found that several drug-related factors were associated with less restrictive coverage, including indications for orphan diseases or pediatric populations, absence of safety warnings, time on the market, lack of alternatives, and expedited FDA review. Variations in coverage have implications for patients' access to treatment and health system costs.

A Comparison of Coverage Restrictions for Biopharmaceuticals and Medical Procedures.

BACKGROUND: Differences in payer evaluation and coverage of pharmaceuticals and medical procedures suggest that coverage may differ for medications and procedures independent of their clinical benefit. We hypothesized that coverage for medications is more restricted than corresponding coverage for nonmedication interventions. METHODS: We included top-selling medications and highly utilized procedures. For each intervention-indication pair, we classified value in terms of cost-effectiveness (incremental cost per quality-adjusted life-year), as reported by the Tufts Medical Center Cost-Effectiveness Analysis Registry. For each intervention-indication pair and for each of 10 large payers, we classified coverage, when available, as either "more restrictive" or as "not more restrictive," compared with a benchmark. The benchmark reflected the US Food and Drug Administration label information, when available, or pertinent clinical guidelines. We compared coverage policies and the benchmark in terms of step edits and clinical restrictions. Finally, we regressed coverage restrictiveness against intervention type (medication or nonmedication), controlling for value (cost-effectiveness more or less favorable than a designated threshold). RESULTS: We identified 392 medication and 185 procedure coverage decisions. A total of 26.3% of the medication coverage and 38.4% of the procedure coverage decisions were more restrictive than their corresponding benchmarks. After controlling for value, the odds of being more restrictive were 42% lower for medications than for procedures. Including unfavorable tier placement in the definition of "more restrictive" greatly increased the proportion of medication coverage decisions classified as "more restrictive" and reversed our findings. CONCLUSIONS: Therapy access depends on factors other than cost and clinical benefit, suggesting potential health care system inefficiency.

Palivizumab Prophylaxis for Respiratory Syncytial Virus: Examining the Evidence Around Value.

Respiratory syncytial virus (RSV) infection is the most common cause of lower respiratory tract infection and the leading cause of hospitalization among young children, incurring high annual costs among US children under the age of 5 years. Palivizumab has been found to be effective in reducing hospitalization and preventing serious lower respiratory tract infections in high-risk infants. This paper presents a systematic review of the cost-effectiveness studies of palivizumab and describes the main highlights of a round table discussion with clinical, payer, economic, research method, and other experts. The objectives of the discussion were to (1) review the current state of clinical, epidemiology, and economic data related to severe RSV disease; (2) review new cost-effectiveness estimates of RSV immunoprophylaxis in US preterm infants, including a review of the field's areas of agreement and disagreement; and (3) identify needs for further research.

Comparing the cost-per-QALYs gained and cost-per-DALYs averted literatures.

Background: We examined the similarities and differences between studies using two common metrics used in cost-effectiveness analyses (CEAs): cost per quality-adjusted life year (QALY) gained and cost per disability-adjusted life year (DALY) averted. Methods: We used the Tufts Medical Center CEA Registry, which contains English-language cost-per-QALY gained studies, and the Global Cost-Effectiveness Analysis (GHCEA) Registry, which contains cost-per-DALY averted studies. We examined study characteristics, including intervention type, sponsor, country, and primary disease, and also compared the number of published CEAs to disease burden for major diseases and conditions across geographic regions. Results: We identified 6,438 cost-per-QALY and 543 cost-per-DALY studies published through 2016 and observed rapid growth for both literatures. Cost-per-QALY studies most often examined pharmaceuticals and interventions in high-income countries. Cost-per-DALY studies predominantly focused on infectious disease interventions and interventions in low and lower-middle income countries. We found that while diseases imposing a larger burden tend to receive more attention in the cost-effectiveness analysis literature, the number of publications for some diseases and conditions deviates from this pattern, suggesting "under-studied" conditions (e.g., neonatal disorders) and "over-studied" conditions (e.g., HIV and TB). Conclusions: The CEA literature has grown rapidly, with applications to diverse interventions and diseases.  The publication of fewer studies than expected for some diseases given their imposed burden suggests funding opportunities for future cost-effectiveness research.

The influence of time horizon on results of cost-effectiveness analyses.

BACKGROUND: Debates persist on the appropriate time horizon from a payer's perspective and how the time horizon in cost-effectiveness analysis (CEA) influences the value assessment. METHODS: We systematically reviewed the Tufts Medical Center CEA Registry and identified US-based studies that used a payer perspective from 2005-2014. We classified the identified CEAs as short-term (time horizon ≤ 5 years) and long-term (> 5 years), and examined associations between study characteristics and the specified time horizon. We also developed case studies with selected interventions to further explore the relationship between time horizon and projected costs, benefits, and incremental cost-effectiveness ratios (ICER). RESULTS: Among 782 identified studies that met our inclusion criteria, 552 studies (71%) utilized a long-term time horizon while 198 studies (25%) used a short-term horizon. Among studies that employed multiple time horizons, the extension of the time horizon yielded more favorable ICERs in 19 cases and less favorable ICERs in 4 cases. Case studies showed the use of a longer time horizon also yielded more favorable ICERs. CONCLUSION: The assumed time horizon in CEAs can substantially influence the value assessment of medical interventions. To capture all consequences, we encourage the use of time horizons that extend sufficiently into the future.