Characteristics of US Medicare Beneficiaries with Chronic Cough vs. Non-Chronic Cough: 2011-2018.

Background: Chronic cough (CC), characterized as a cough lasting >8 weeks, is a common multi-factorial syndrome in the community, especially in older adults. Methods: Using a pre-existing algorithm to identify patients with CC within the 2011-2018 Medicare beneficiaries, we examined trends in gabapentinoid use through repeated cross-sectional analyses and identified distinct utilization trajectories using group-based trajectory modeling (GBTM) in a retrospective cohort study. Individuals without CC but with any respiratory conditions related to cough served as a comparator group. Results: Among patients with CC, gabapentinoid use increased from 18.6% in 2011 to 24.1% in 2018 (p = 0.002), with a similar upward trend observed in the non-CC cohort but with overall lower usage (14.7% to 18.4%; p < 0.001). Patients with CC had significantly higher burdens of respiratory and non-respiratory comorbidities, as well as greater healthcare service and medication use compared to the non-CC cohort. The GBTM analyses identified three distinct gabapentinoid utilization trajectories for CC and non-CC patients: no use (77.3% vs. 84.5%), low use (13.9% vs. 10.3%), and high use (8.8% vs. 5.2%). Conclusions: Future studies are needed to evaluate the safety and effectiveness of gabapentinoid use in patients with refractory or unexplained CC in real-world settings.

Association between Opioid-Benzodiazepine Trajectories and Injurious Fall Risk among US Medicare Beneficiaries.

Background/Objectives: Concurrent opioid (OPI) and benzodiazepine (BZD) use may exacerbate injurious fall risk (e.g., falls and fractures) compared to no use or use alone. Yet, patients may need concurrent OPI-BZD use for co-occurring conditions (e.g., pain and anxiety). Therefore, we examined the association between longitudinal OPI-BZD dosing patterns and subsequent injurious fall risk. Methods: We conducted a retrospective cohort study including non-cancer fee-for-service Medicare beneficiaries initiating OPI and/or BZD in 2016-2018. We identified OPI-BZD use patterns during the 3 months following OPI and/or BZD initiation (i.e., trajectory period) using group-based multi-trajectory models. We estimated the time to first injurious falls within the 3-month post-trajectory period using inverse-probability-of-treatment-weighted Cox proportional hazards models. Results: Among 622,588 beneficiaries (age ≥ 65 = 84.6%, female = 58.1%, White = 82.7%; having injurious falls = 0.45%), we identified 13 distinct OPI-BZD trajectories: Group (A): Very-low OPI-only (early discontinuation) (44.9% of the cohort); (B): Low OPI-only (rapid decline) (15.1%); (C): Very-low OPI-only (late discontinuation) (7.7%); (D): Low OPI-only (gradual decline) (4.0%); (E): Moderate OPI-only (rapid decline) (2.3%); (F): Very-low BZD-only (late discontinuation) (11.5%); (G): Low BZD-only (rapid decline) (4.5%); (H): Low BZD-only (stable) (3.1%); (I): Moderate BZD-only (gradual decline) (2.1%); (J): Very-low OPI (rapid decline)/Very-low BZD (late discontinuation) (2.9%); (K): Very-low OPI (rapid decline)/Very-low BZD (increasing) (0.9%); (L): Very-low OPI (stable)/Low BZD (stable) (0.6%); and (M): Low OPI (gradual decline)/Low BZD (gradual decline) (0.6%). Compared with Group (A), six trajectories had an increased 3-month injurious falls risk: (C): HR = 1.78, 95% CI = 1.58-2.01; (D): HR = 2.24, 95% CI = 1.93-2.59; (E): HR = 2.60, 95% CI = 2.18-3.09; (H): HR = 2.02, 95% CI = 1.70-2.40; (L): HR = 2.73, 95% CI = 1.98-3.76; and (M): HR = 1.96, 95% CI = 1.32-2.91. Conclusions: Our findings suggest that 3-month injurious fall risk varied across OPI-BZD trajectories, highlighting the importance of considering both dose and duration when assessing injurious fall risk of OPI-BZD use among older adults.

Association between trajectories of adherence to endocrine therapy and risk of treated breast cancer recurrence among US nonmetastatic breast cancer survivors.

BACKGROUND: Endocrine therapy is the mainstay treatment for breast cancer (BC) to reduce BC recurrence risk. During the first year of endocrine therapy use, nearly 30% of BC survivors are nonadherent, which may increase BC recurrence risk. This study is to examine the association between endocrine therapy adherence trajectories and BC recurrence risk in nonmetastatic BC survivors. METHODS: This retrospective cohort study included Medicare beneficiaries in the United States (US) with incident nonmetastatic BC followed by endocrine therapy initiation in 2010-2019 US Surveillance, Epidemiology, and End Results linked Medicare data. We calculated monthly fill-based proportion of days covered in the first year of endocrine therapy. We applied group-based trajectory models to identify distinct endocrine therapy adherence patterns. After the end of the first-year endocrine therapy trajectory measurement period, we estimated the risk of time to first treated BC recurrence within 4 years using Cox proportional hazards models. RESULTS: We identified 5 trajectories of adherence to endocrine therapy in BC Stages 0-I subgroup (n = 28,042) and in Stages II-III subgroup (n = 7781). A trajectory of discontinuation before 6 months accounted for 7.0% in Stages 0-I and 5.8% in Stages II-III subgroups, and this trajectory was associated with an increased treated BC recurrence risk compared to nearly perfect adherence (Stages 0-I: adjusted hazard [aHR] = 1.84, 95% CI = 1.46-2.33; Stages II-III: aHR = 1.38, 95% CI = 1.07-1.77). CONCLUSIONS: Nearly 7% of BC survivors who discontinued before completing 6 months of treatment was associated with an increased treated BC recurrence risk compared to those with nearly perfect adherence among Medicare nonmetastatic BC survivors.

Association between trajectories of prescription opioid use and risk of opioid use disorder and overdose among US nonmetastatic breast cancer survivors.

PURPOSE: To examine the association between prescription opioid use trajectories and risk of opioid use disorder (OUD) or overdose among nonmetastatic breast cancer survivors by treatment type. METHODS: This retrospective cohort study included female nonmetastatic breast cancer survivors with at least 1 opioid prescription fill in 2010-2019 Surveillance, Epidemiology and End Results linked Medicare data. Opioid mean daily morphine milligram equivalents (MME) calculated within 1.5 years after initiating active breast cancer therapy. Group-based trajectory models identified distinct opioid use trajectory patterns. Risk of time to first OUD/overdose event within 1 year after the trajectory period was calculated for distinct trajectory groups using Cox proportional hazards models. Analyses were stratified by treatment type. RESULTS: Four opioid use trajectories were identified for each treatment group. For 38,030 survivors with systemic endocrine therapy, 3 trajectories were associated with increased OUD/overdose risk compared with early discontinuation: minimal dose (< 5 MME; adjusted hazard ratio [aHR] = 1.73 [95% CI 1.43-2.09]), very low dose (5-25 MME; 2.67 [2.05-3.48]), and moderate dose (51-90 MME; 6.20 [4.69-8.19]). For 9477 survivors with adjuvant chemotherapy, low-dose opioid use was associated with higher OUD/overdose risk (aHR = 7.33 [95% CI 2.52-21.31]) compared with early discontinuation. For 3513 survivors with neoadjuvant chemotherapy, the differences in OUD/OD risks across the 4 trajectories were not significant. CONCLUSIONS: Among Medicare nonmetastatic breast cancer survivors receiving systemic endocrine therapy or adjuvant chemotherapy, compared with early discontinuation, low-dose or moderate-dose opioid use were associated with six- to sevenfold higher OUD/overdose risk. Breast cancer survivors at high-risk of OUD/overdose may benefit from targeted interventions (e.g., pain clinic referral).

The Unseen Hand: AI-Based Prescribing Decision Support Tools and the Evaluation of Drug Safety and Effectiveness.

The use of artificial intelligence (AI)-based tools to guide prescribing decisions is full of promise and may enhance patient outcomes. These tools can perform actions such as choosing the 'safest' medication, choosing between competing medications, promoting de-prescribing or even predicting non-adherence. These tools can exist in a variety of formats; for example, they may be directly integrated into electronic medical records or they may exist in a stand-alone website accessible by a web browser. One potential impact of these tools is that they could manipulate our understanding of the benefit-risk of medicines in the real world. Currently, the benefit risk of approved medications is assessed according to carefully planned agreements covering spontaneous reporting systems and planned surveillance studies. But AI-based tools may limit or even block prescription to high-risk patients or prevent off-label use. The uptake and temporal availability of these tools may be uneven across healthcare systems and geographies, creating artefacts in data that are difficult to account for. It is also hard to estimate the 'true impact' that a tool had on a prescribing decision. International borders may also be highly porous to these tools, especially in cases where tools are available over the web. These tools already exist, and their use is likely to increase in the coming years. How they can be accounted for in benefit-risk decisions is yet to be seen.

Computational phenotyping within electronic healthcare data to identify transgender people in the United States: A narrative review.

PURPOSE: With the expansion of research utilizing electronic healthcare data to identify transgender (TG) population health trends, the validity of computational phenotype (CP) algorithms to identify TG patients is not well understood. We aim to identify the current state of the literature that has utilized CPs to identify TG people within electronic healthcare data and their validity, potential gaps, and a synthesis of future recommendations based on past studies. METHODS: Authors searched the National Library of Medicine's PubMed, Scopus, and the American Psychological Association PsycInfo's databases to identify studies published in the United States that applied CPs to identify TG people within electronic healthcare data. RESULTS: Twelve studies were able to validate or enhance the positive predictive value (PPV) of their CP through manual chart reviews (n = 5), hierarchy of code mechanisms (n = 4), key text-strings (n = 2), or self-surveys (n = 1). CPs with the highest PPV to identify TG patients within their study population contained diagnosis codes and other components such as key text-strings. However, if key text-strings were not available, researchers have been able to find most TG patients within their electronic healthcare databases through diagnosis codes alone. CONCLUSION: CPs with the highest accuracy to identify TG patients contained diagnosis codes along with components such as procedural codes or key text-strings. CPs with high validity are essential to identifying TG patients when self-reported gender identity is not available. Still, self-reported gender identity information should be collected within electronic healthcare data as it is the gold standard method to better understand TG population health patterns.

Medications for Opioid Use Disorder and Mortality and Hospitalization Among People With Opioid Use-related Infections.

BACKGROUND: Severe skin and soft tissue infections related to injection drug use have increased in concordance with a shift to heroin and illicitly manufactured fentanyl. Opioid agonist therapy medications (methadone and buprenorphine) may improve long-term outcomes by reducing injection drug use. We aimed to examine the association of medication use with mortality among people with opioid use-related skin or soft tissue infections. METHODS: An observational cohort study of Medicaid enrollees aged 18 years or older following their first documented medical encounters for opioid use-related skin or soft tissue infections during 2007-2018 in North Carolina. The exposure was documented medication use (methadone or buprenorphine claim) in the first 30 days following initial infection compared with no medication claim. Using Kaplan-Meier estimators, we examined the difference in 3-year incidence of mortality by medication use, weighted for year, age, comorbidities, and length of hospital stay. RESULTS: In this sample, there were 13,286 people with opioid use-related skin or soft tissue infections. The median age was 37 years, 68% were women, and 78% were white. In Kaplan-Meier curves for the total study population, 12 of every 100 patients died during the first 3 years. In weighted models, for every 100 people who used medications, there were four fewer deaths over 3 years (95% confidence interval = 2, 6). CONCLUSION: In this study, people with opioid use-related skin and soft tissue infections had a high risk of mortality following their initial healthcare visit for infections. Methadone or buprenorphine use was associated with reductions in mortality.

Patterns of Cough Medication Prescribing among Patients with Chronic Cough in Florida: 2012-2021.

Among patients with chronic cough (CC) in the 2012-2021 statewide OneFlorida Clinical Research Consortium database, we examined trends in cough medication (CM) prescribing prevalence over time in repeated cross-sectional analyses and identified distinct CM utilization trajectories using group-based trajectory modeling (GBTM) in a retrospective cohort study. Among eligible adults (≥18 years) without cancer/benign respiratory tumor diagnoses, we identified CC patients and non-CC patients with any cough-related diagnosis. In the GBTM analysis, we calculated the number of monthly prescriptions for any CMs (excluding gabapentinoids) during the 12 months from the first qualifying cough event to identify distinct utilization trajectories. From 2012 to 2021, benzonatate (9.6% to 26.1%), dextromethorphan (5.2% to 8.6%), and gabapentinoid (5.3% to 14.4%) use increased among CC patients, while opioid antitussive use increased from 2012 to 2015 and decreased thereafter (8.4% in 2012, 14.7% in 2015, 6.7% in 2021; all p < 0.001). Of 15,566 CC patients and 655,250 non-CC patients identified in the GBTM analysis, CC patients had substantial burdens of respiratory/non-respiratory comorbidities and healthcare service and concomitant medication use compared to non-CC patients. Among CC patients, GBTM identified three distinct CM utilization trajectories: (1) no CM use (n = 11,222; 72.1%); (2) declining CM use (n = 4105; 26.4%); and (3) chronic CM use (n = 239; 1.5%). CC patients in Florida had limited CM use with increasing trends in use of benzonatate, dextromethorphan, and gabapentinoids and a decreasing trend in opioid antitussive use. CC patients, particularly with chronic prescription CM use, experienced substantial disease burden.

Mortality associated with bacterial and fungal infections and overdose among people with drug use diagnoses.

PURPOSE: Hospital visits for drug use-related bacterial and fungal infections have increased alongside overdose deaths. The incidence of mortality from these infections and the comparison to overdose mortality is not established. METHODS: This cohort study examined mortality outcomes among adults with drug use diagnoses who were insured by public and private plans during 2007 through 2018 in North Carolina. We examined bacterial- and fungal infection-related mortality and overdose mortality using cumulative incidence functions. RESULTS: Among 131,522 people with drug use diagnoses, the median age was 45 years (interquartile range: 31-57), 58% were women and 65% had an opioid use disorder diagnosis. The 1-year incidence of bacterial and fungal infection-associated mortality was progressively higher as age increased (35-49 years: 9 per 10,000 people, 50-64 years: 23 per 10,000, 65+ years: 50 per 10,000 people). Conversely, the 1-year incidence of overdose mortality was markedly lower among older adults compared to those under the age of 65 (18-34 years: 34 deaths per 10,000 people; 35-49 years: 47 per 10,000; 50-64 years: 41 per 10,000; 65+ years: 9 per 10,000). CONCLUSIONS: Bacterial and fungal infections and overdose were notable causes of death among adults with drug use diagnoses, and varied by age group.

Pragmatic Model and Faculty Toolkit for PharmD Student Engagement in Social and Administrative Pharmacy Research.

OBJECTIVE: We aim to describe the development of a pharmacy student workgroup as an experiential education model to provide social and administrative pharmacy research opportunities and provide a toolkit for faculty seeking to increase student research engagement via this model. METHODS: Three pharmacy faculty with diverse training backgrounds but a common interest in opioid medications established a workgroup named the Opioid Research Workgroup. The workgroup consisted of first-year pharmacy students, research interns, and advanced graduate trainees. A hierarchical leadership model of supervision was implemented, whereby students reported progress on research tasks directly to an advanced graduate trainee leading a project team. To understand students' perspectives on the research experience and educational outcomes, students were asked to complete an anonymous voluntary survey after a year of participation. RESULTS: Since its establishment, the workgroup has published multiple conference abstracts, manuscripts, and grants. Students' overall satisfaction with the Workgroup on a scale of 1-5, 5 being very high, was 4.69. The successful scalability and longevity of this model are dependent on administrative support that protects faculty resources. The toolkit provided offers resources for those interested in adapting this model. CONCLUSION: Our experience with the pragmatic model of pharmacy student engagement in research proved successful in terms of research output and student training experience. Although the model can be applied across a variety of health science clinical and research topics, and faculty can leverage this approach to increase productivity in research output, faculty must ensure that resources are available to support this effort.

Trends in Prescribing of Non-steroidal Anti-inflammatory Medications in the US Ambulatory Care Setting From 2006 to 2016.

While opioid prescribing has significantly decreased from a peak in 2012, less is known about the national utilization of non-opioid analgesics such as non-steroidal anti-inflammatory drugs (NSAIDs) and acetaminophen (APAP) in the context of the opioid crisis. The objective of this study is to characterize the prescribing trends of NSAIDs and APAP in the US ambulatory care setting. We conducted repeated cross-sectional analyses using the 2006-2016 National Ambulatory Medical Care Survey. NSAID-involved visits were defined as patient visits among adults in which NSAIDs were ordered, supplied, administered, or continued. We used similarly-defined APAP visits as a referent group for context. After excluding aspirin and other NSAID/APAP combination products containing opioids, we calculated the annual proportion of NSAID-involved visits among all ambulatory visits. We conducted trend analyses using multivariable logistic regression adjusted for years, patient, and prescriber characteristics. From 2006 to 2016, there were 775.7 million NSAID-involved visits and 204.3 million APAP-involved visits. Most NSAIDs-involved visits were from patients aged 46-64 years (39.6%), female (60.4%), White (83.2%), and having commercial insurance (49.0%). There were significant increasing trends for the proportion of NSAID-involved visits (8.1-9.6%) and APAP-involved visits (1.7-2.9%) (both P < .0001). We observed an overall increase in NSAID and APAP-involved visits in US ambulatory care settings from 2006 to 2016. This trend may be attributed to decreasing opioid prescribing and raises safety concerns related to acute or chronic NSAID and APAP use. PERSPECTIVE: This study shows an overall increasing trend in NSAID use reported in nationally representative ambulatory care visits in the United States. This increase coincides with previously reported significant decreases in opioid analgesic use, particularly after 2012. Given the safety concerns related to chronic or acute NSAID use, there is a need to continue monitoring the use trends of this class of medication.

Enhancing active learning of medication errors in the PharmD curriculum through a multi-perspective video-based experience.

INTRODUCTION: We created and assessed an immersive instructional series of video-based activities for pharmacy student evaluation of medication errors via root cause analysis (RCA). METHODS: A novel series of video vignettes showed a medication error from the perspectives of each healthcare team member involved. Students were engaged in a series of activities to guide them through RCA interspersed with the vignettes. A pre/post-assessment tool measured student-perceived skills and attitudes in medication error prevention and handling. Per item pre/post-mean scores were compared using Mann-Whitney U tests with Bonferroni correction. RESULTS: From N = 270 students, 231 and 163 completed the anonymous pre- and post-assessment, respectively. Most students positively endorsed attitude items at both assessment intervals, with no significant changes in mean for "learning how to improve patient safety is an appropriate use of time in pharmacy school" (pre-assessment = 4.26; post-assessment = 4.23). However, there were significant improvements in the skills items "I am confident in my ability to analyze a case to find the root causes of an error" (pre = 3.44; post = 3.85) and "I can identify the key factors in systems and processes that could lead to a medication error" (pre = 3.55; post = 3.88). CONCLUSIONS: Pharmacy students reported significantly improved self-perceived skills in handling and preventing medication errors, but not in attitudes, following the immersive instructional activity. There are opportunities to expand such an immersive instructional series in an interprofessional setting, which may yield different findings.

Trends, characteristics, race, and ethnicity associated with nonadherence to antidepressants among breast cancer survivors with depression.

BACKGROUND: Breast cancer is the most diagnosed cancer in the United States, and half of breast cancer survivors experience major depressive disorders (hereafter depression). Healthcare Effectiveness Data and Information Set (HEDIS) quality measures evaluating depression treatment practices recommend uninterrupted antidepressant treatment for 3 months in the acute phase and 3 months in the continuation phase for the general population. However, little is known about the extent of and trends in antidepressant nonadherence among breast cancer survivors with depression, which may impact adherence to breast cancer treatment, potentially leading to breast cancer recurrence and other adverse outcomes. OBJECTIVE: To examine the trends and characteristics associated with antidepressant nonadherence among breast cancer survivors with depression in the United States. METHODS: We conducted cross-sectional analyses of Surveillance, Epidemiology, and End Results linked with Medicare data (2010-2019) for women with breast cancer and depression who newly initiated antidepressant use. Using HEDIS measures of nonadherence (ie, antidepressant prescription coverage ≤84 days of the 114-day acute phase or ≤180 days of the 231-day continuation phase), we calculated the annual crude prevalence of antidepressant nonadherence and examined trends using unadjusted logistic regression. Multivariable logistic regression identified characteristics associated with antidepressant nonadherence. RESULTS: Among 9,452 eligible breast cancer survivors with depression (aged ≥65 years = 84% and White race = 82%), the crude prevalence of antidepressant nonadherence decreased from 2010 to 2019 for both the acute (49% to 40%; Ptrend<0.001) and continuation (67% to 57%; Ptrend<0.001) phases. Factors significantly associated with higher odds of antidepressant nonadherence in both the acute and continuation phases included Black race (odds ratios [ORs] [95% CI] for the acute/continuation phases: 2.0 [1.7-2.4]/2.0 [1.7-2.3]) and Hispanic ethnicity (1.5 [1.1-1.9]/2.2 [1.6-2.9]) compared with White race; receiving the first antidepressant from an oncologist vs a psychiatrist (1.4 [1.1-1.8]/1.6 [1.2-2.0]); and using antidepressants not recommended for older adults by the Beers criteria (2.2 [1.6-2.9]/2.0 [1.4-2.7]). Factors associated with lower odds of antidepressant nonadherence in both phases included receiving lymph node dissection (0.7 [0.5-0.9]/0.7 [0.5-0.9]), receiving endocrine therapy (0.9 [0.8-0.9]/0.8 [0.7-0.9]), having a higher National Cancer Institute comorbid index (0.8 [0.7-0.8]/0.9 [0.8-0.9]), having a follow-up visit with a psychiatrist (0.9 [0.8-0.9]/0.9 [0.8-0.9]), and switching to different antidepressants (0.7 [0.6-0.8]/0.7 [0.7-0.8]). CONCLUSIONS: Despite antidepressant nonadherence prevalence decreasing from 2010 to 2019, over half of breast cancer survivors with depression and Medicare were nonadherent in the continuation phase. Patients with identified nonadherence risk factors may benefit from close monitoring and targeted interventions. DISCLOSURES: Wei-Hsuan Lo-Ciganic reported grants from the National Institute on Drug Abuse (R01DA044985 and R01DA050676), the National Institute on Aging (R21AG060308), the National Institute of Mental Health (R01MH121907), Merck Sharp & Dohme, Bristol Myers Squibb, the Richard King Mellon Foundation at the University of Pittsburgh, the Clinical and Translational Science Institute of the University of Florida, the Pharmaceutical Research and Manufacturers of America (PhRMA) Foundation, and the US Department of Veterans Affairs outside the submitted work; in addition, Wei-Hsuan Lo-Ciganic has a patent pending for U1195.70174US00. Haesuk Park reported grants from Bristol Myers Squibb/Pfizer Alliance American Thrombosis Investigator Initiated Research Program (ARISTA-USA) outside the submitted work. Juan M. Hincapie-Castillo reported grants from Merck outside the submitted work. Debbie Wilson reported grants from the National Institute on Drug Abuse, the National Institute on Aging, Merck Sharp & Dohme, and Bristol Myers Squibb outside the submitted work; and serving as an editorial board member for the Journal of Pharmacy Technology. Ching-Yuan Chang's contributions to this manuscript were made while at the University of Florida College of Pharmacy. Ching-Yuan Chang is currently employed by Vertex Pharmaceuticals, Inc. Vertex did not fund or have any involvement in this study or publication. Vakaramoko Diaby is currently employed by Otsuka, Inc. Otsuka did not fund or have any involvement in this study or publication. No other disclosures were reported.

Using Joinpoint regression for drug utilization research: Tutorial and case study of prescription opioid use in the United States.

PURPOSE: Drug utilization researchers are often interested in evaluating prescribing and medication use patterns and trends over a specified period of time. Joinpoint regression is a useful methodology to identify any deviations in secular trends without a preconceived notion of where these break points might occur. This article provides a tutorial on the use of joinpoint regression, within Joinpoint software, for the analysis of drug utilization data. METHODS: The statistical considerations for whether a joinpoint regression analytical technique is a suitable approach are discussed. Then, we offer a tutorial as an introduction on conducting joinpoint regression (within Joinpoint software) through a step-by-step application, which is a case study developed using opioid prescribing data from the United States. Data were obtained from public files available through the Centers for Disease Control and Prevention from 2006 to 2018. The tutorial provides parameters and sample data needed to replicate the case study and it concludes with general considerations for the reporting of results using joinpoint regression in drug utilization research. RESULTS: The case study evaluated the trend of opioid prescribing in the United States from 2006 to 2018, where time points of significant variation (one in 2012 and another in 2016) are detected and interpreted. CONCLUSIONS: Joinpoint regression is a helpful methodology for drug utilization for the purposes of conducting descriptive analyses. This tool also assists with corroborating assumptions and identifying parameters for fitting other models such as interrupted time series. The technique and accompanying software are user-friendly; however, researchers interested in using joinpoint regression should exercise caution and follow best practices for correct measurement of drug utilization.

Buprenorphine Use Trends Following Removal of Prior Authorization Policies for the Treatment of Opioid Use Disorder in 2 State Medicaid Programs.

Importance: State Medicaid programs have implemented initiatives to expand treatment coverage for opioid use disorder (OUD); however, some Medicaid programs still require prior authorizations (PAs) for filling buprenorphine prescriptions. Objective: To evaluate the changes in buprenorphine use for OUD among Medicaid enrollees in states that completely removed buprenorphine PA requirements. Design Setting and Participants: This retrospective cross-sectional study analyzed the immediate and trend changes on buprenorphine use during 2013 to 2020 associated with removal of PA requirements using a controlled interrupted time series analysis to account for autocorrelation. Data were collected from Medicaid State Drug Utilization Data for 2 states (California and Illinois) that completely removed a buprenorphine PA during the study period, and buprenorphine prescriptions for OUD treatment were identified among Medicaid enrollees. Main Outcomes and Measures: Quarterly total number of buprenorphine prescriptions for each state was calculated, and stratification analyses were conducted by dosage form (films and tablets). Results: Among the 2 state Medicaid programs (California and Illinois) that removed buprenorphine PAs, there was a total of 702 643 and 415 115 eligible buprenorphine prescription claims, respectively. After removing PA requirements for buprenorphine, there was an immediate increase that was not statistically significant (rate ratio [RR], 1.11; 95% CI, 0.76-1.61) in the number of all buprenorphine prescriptions in California and a statistically significant increase (RR, 6.99; 95% CI, 4.67-10.47) in the number of all buprenorphine prescriptions in Illinois relative to the change in the control states (Alabama, Florida, Idaho, Kansas, Mississippi, Nevada, South Dakota, and Wyoming). Additionally, there was a statistically significant decreasing trend in the number of all buprenorphine prescriptions in California (RR, 0.88; 95% CI, 0.82-0.94) and a statistically significant increasing trend in Illinois (RR, 1.11; 95% CI, 1.05-1.19) relative to the trend in control states. Conclusions and Relevance: In this cross-sectional study, removal of buprenorphine PA requirements was associated with a statistically significant increase in the number of buprenorphine prescription fills among Medicaid populations in 1 of the 2 included states.

Environmental scan of COVID-19 infection dashboards in the Florida public school system.

Public dashboards have been one of the most effective tools to provide critical information about COVID-19 cases during the pandemic. However, dashboards for COVID-19 that have not received a lot of scrutiny are those from the public school system. We conducted an environmental scan of published dashboards that report and track new COVID-19 infections in the Florida public school system. We found that thirty-four percent of counties do not provide any public dashboard, and there was significant heterogeneity in the data quality and framework of existing systems. There were poor interfaces without visual tools to trace the trend of COVID-19 cases in public schools and significant limitations for data extraction. Given these observations, it is impossible to conduct meaningful policy evaluations and proper surveillance. Additional work and oversight are needed to improve public data reported.

Evaluation of Cough Medication Use Patterns in Ambulatory Care Settings in the United States: 2003-2018.

Using 2003−2018 National Ambulatory Medical Care Survey data for office-based visits and 2003−2018 National Hospital Ambulatory Medical Care Survey data for emergency department (ED) visits, we conducted cross-sectional analyses to examine cough medication (CM) use trends in the United States (US) ambulatory care settings. We included adult (≥18 years) patient visits with respiratory-infection-related or non-infection-related cough as reason-for-visit or diagnosis without malignant cancer or benign respiratory tumor diagnoses. Using multivariable logistic regressions, we examined opioid antitussive, benzonatate, dextromethorphan-containing antitussive, and gabapentinoid use trends. From 2003−2005 to 2015−2018, opioid antitussive use decreased in office-based visits (8.8% to 6.4%, Ptrend = 0.03) but remained stable in ED visits (6.3% to 5.9%, Ptrend = 0.99). In both settings, hydrocodone-containing antitussive use declined over 50%. Benzonatate use more than tripled (office-based:1.6% to 4.8%; ED:1.5% to 8.0%; both Ptrend < 0.001). Dextromethorphan-containing antitussive use increased in ED visits (1.8% to 2.6%, Ptrend = 0.003) but stayed unchanged in office-based visits (3.8% to 2.7%; Ptrend = 0.60). Gabapentinoid use doubled in office-based visits (1.1% in 2006−2008 to 2.4% in 2015−2018, Ptrend < 0.001) but was negligible in ED visits. In US office-based and ED ambulatory care settings, hydrocodone-containing antitussive use substantially declined from 2003 to 2018, while benzonatate use more than tripled, and dextromethorphan-containing antitussive and gabapentinoid use remained low (<3%).

Prescription Patterns of Adjuvant Pain Medications Following an Opioid Supply Restriction Law: An Interrupted Time Series Analysis.

BACKGROUND: Florida House Bill 21 (HB21) was implemented in July 2018 to limit prescriptions of Schedule II opioids for acute pain patients, but it is unclear whether such restrictions have a collateral influence on the utilization of commonly prescribed adjuvant pain medications. OBJECTIVE: The objective of this study was to assess whether this law was associated with a change in use patterns of gabapentinoids, benzodiazepines, and muscle relaxants. METHODS: We obtained prescription claims for medications dispensed from January 1, 2015, to June 31, 2019, from a health plan serving a large Florida employer. Interrupted time series analyses were conducted to compare pre-HB21 and post-HB21 implementation changes in the mean monthly number of users and prescriptions for gabapentinoids, benzodiazepines, and muscle relaxants. RESULTS: There was a 6% immediate increase (relative risk: 1.06; 95% confidence interval: 1.02, 1.11) in the monthly proportion of gabapentinoid users, and an 11% immediate increase in the monthly proportion of gabapentinoids prescriptions (relative risk: 1.11; 95% confidence interval: 1.04, 1.18) per 1000 patients following law implementation. However, after the law, we observed a significant reduction in trend for the monthly proportion of muscle relaxants and benzodiazepine users. CONCLUSIONS: An increased number of patients and prescriptions were observed for gabapentinoids, while fewer patients received benzodiazepines and muscle relaxants after HB21. In previous studies, opioid prescription restriction laws are shown to reduce opioids, but this work suggests that these laws may also have unintended consequences for the use of adjunctive medications that were not intended to be affected.