Effects of the valsartan recall on heart failure patients: A nationwide analysis.

BACKGROUND: Valsartan is commonly used for cardiac conditions. In 2018, the Food and Drug Administration recalled generic valsartan due to the detection of impurities. Our objective was to determine if heart failure patients receiving valsartan at the recall date had a greater likelihood of unfavorable outcomes than patients using comparable antihypertensives. METHODS: We conducted a cohort study of Optum's de-identified Clinformatics® Datamart (July 2017-January 2019). Heart failure patients with commercial or Medicare Advantage insurance who received valsartan were compared to persons who received non-recalled angiotensin receptor blockers (ARBs) and angiotensin converting enzyme-inhibitors (ACE-Is) for 1 year prior and including the recall date. Outcomes included a composite for all-cause hospitalization, emergency department (ED), and urgent care (UC) use and a measure of cardiac events which included hospitalizations for acute myocardial infarction and hospitalizations/ED/UC visits for stroke/transient ischemic attack, heart failure or hypertension at 6-months post-recall. Cox proportional hazard models with propensity score weighting compared the risk of outcomes between groups. RESULTS: Of the 87 130 adherent patients, 15% were valsartan users and 85% were users of non-recalled ARBs/ACE-Is. Valsartan use was not associated with an increased risk of all-cause hospitalization/ED/UC use six-months post-recall (HR 1.00; 95% CI 0.96-1.03), compared with individuals taking non-recalled ARBs/ACE-Is. Similarly, cardiac events 6-months post-recall did not differ between individuals on valsartan and non-recalled ARBs/ACE-Is (HR 1.04; 95% CI 0.97-1.12). CONCLUSIONS: The valsartan recall did not affect short-term outcomes of heart failure patients. However, the recall potentially disrupted the medication regimens of patients, possibly straining the healthcare system.

Facility-Level Variation in Racial Disparities in Anticoagulation for Atrial Fibrillation: The REACH-AF Study.

BACKGROUND: Oral anticoagulation reduces stroke risk for patients with atrial fibrillation (AF). Prior research demonstrates lower anticoagulant prescribing in Black than in White individuals but few studies have examined racial differences in facility-level anticoagulant prescribing for AF. OBJECTIVE: To assess variation in anticoagulant initiation by race within Veterans Health Administration (VA) facilities. DESIGN: Retrospective cohort study. PARTICIPANTS: Black and White patients enrolled in the VA with incident AF from 2020 through 2021. MAIN MEASURES: The primary outcome was rate of any anticoagulant initiation (i.e., warfarin or direct oral anticoagulant [DOAC]) or any DOAC therapy within 90 days of an AF diagnosis, overall and for Black and White patients at each facility. We also estimated the adjusted Black-White risk difference. KEY RESULTS: In 82 VA facilities serving 26,832 Black and White patients, overall unadjusted rates of any anticoagulant therapy ranged from 56.8 to 87.1% across facilities; the corresponding ranges for Black and White patients were 47.6 to 91.3% and 58.2 to 87.1%, respectively. Overall unadjusted rates of DOAC therapy ranged from 55.1 to 85.5% by facility; ranges for Black and White patients were 42.8 to 86.9% and 56.4 to 85.5%, respectively. The adjusted risk difference between Black and White patients ranged from - 29.9 (95% CI, - 54.9 to - 4.8) to 14.2 (95% CI, - 9.1 to 25.0) across facilities for any anticoagulant therapy and from - 28.8 (95% CI, - 58.3 to 0.8) to 15.0 (95% CI, - 8.0 to 38.1) for DOAC therapy. For any anticoagulant therapy there were 3 facilities where prescribing was statistically higher in White than Black patients; for DOAC therapy there were 5 such facilities. CONCLUSIONS: In a national cohort of patients with AF, we observed large facility-level variation and adjusted risk differences in any anticoagulant and DOAC initiation, overall and by race. These findings represent a target for local quality improvement in AF care.

Trends in Phenylephrine and Pseudoephedrine Sales in the US.

This study examines purchasing patterns regarding oral decongestants, concerns about their efficacy, and the need for timelier postmarket evaluation.

Estimated Changes in Insulin Prices and Discounts After Entry of New Insulin Products, 2012-2019.

Importance: Despite the political salience of insulin prices, no study to date has quantified trends in insulin prices that account for manufacturer discounts (net prices). Objective: To describe trends in insulin list prices and net prices faced by payers from 2012 to 2019 and estimate changes in net prices after the 2015 to 2017 entry of new insulin products. Design, Setting, and Participants: This longitudinal study included an analysis of Medicare, Medicaid, and SSR Health drug pricing data from January 1, 2012, to December 31, 2019. Data analyses were performed from June 1, 2022, to October 31, 2022. Exposures: US sales of insulin products. Main Outcomes and Measures: Net prices faced by payers were estimated for insulin products as list prices minus manufacturer discounts negotiated in commercial and Medicare Part D markets (ie, commercial discounts). Trends in net prices were evaluated before and after the entry of new insulin products. Results: Net prices of long-acting insulin products increased at an annual rate of 23.6% from 2012 to 2014 but decreased at an annual rate of 8.3% after the introduction of insulin glargine (Toujeo and Basaglar) and degludec (Tresiba) in 2015. Net prices of short-acting insulin increased at an annual rate of 5.6% from 2012 to 2017 but then decreased from 2018 to 2019 after the introduction of insulin aspart (Fiasp) and lispro (Admelog). For human insulin products, which did not experience entry of new products, net prices increased at an annual rate of 9.2% from 2012 to 2019. From 2012 to 2019, commercial discounts increased from 22.7% to 64.8% for long-acting insulin products, from 37.9% to 66.1% for short-acting insulin products, and from 54.9% to 63.1% for human insulin products. Conclusions and Relevance: In this longitudinal study of US insulin products, results suggest that insulin prices substantially increased from 2012 to 2015, even after accounting for discounts. The introduction of new insulin products was followed by substantial discounting practices that lowered net prices faced by payers.

Evaluation of Out-of-Pocket Costs and Treatment Intensification With an SGLT2 Inhibitor or GLP-1 RA in Patients With Type 2 Diabetes and Cardiovascular Disease.

Importance: The latest guidelines continue to recommend sodium-glucose cotransporter 2 (SGLT2) inhibitors and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) for patients with type 2 diabetes (T2D) and established cardiovascular disease (CVD). Despite this, overall use of these 2 drug classes has been suboptimal. Objective: To assess the association of high out-of-pocket (OOP) costs and the initiation of an SGLT2 inhibitor or GLP-1 RA among adults with T2D and established CVD who are treated with metformin-treated. Design, Setting, and Participants: This retrospective cohort study used 2017 to 2021 data from the Optum deidentified Clinformatics Data Mart Database. Each individual in the cohort was categorized into quartiles of OOP costs for a 1-month supply of SGLT2 inhibitor and GLP-1 RA based on their health plan assignment. Data were analyzed from April 2021 to October 2022. Exposures: OOP cost for SGLT2 inhibitors and GLP-1 RA. Main Outcomes and Measures: The primary outcome was treatment intensification, defined as a new dispensing (ie, initiation) of either an SGLT2 inhibitor or GLP-1 RA, among patients with T2D previously treated with metformin monotherapy. For each drug class separately, Cox proportional hazards models were used to adjust for demographic, clinical, plan, clinician, and laboratory characteristics to estimate the hazard ratios of treatment intensification comparing the highest vs the lowest quartile of OOP costs. Results: Our cohort included 80 807 adult patients (mean [SD] age, 72 [9.5] years, 45 129 [55.8%] male; 71 128 [88%] were insured with Medicare Advantage) with T2D and established CVD on metformin monotherapy. Patients were followed for a median (IQR) of 1080 days (528 to 1337). The mean (SD) of OOP costs in the highest vs lowest quartile was $118 [32] vs $25 [12] for GLP-1 RA, and $91 [25] vs $23 [9] for SGLT2 inhibitors. Compared with patients in plans with the lowest quartile (Q1) of OOP costs, patients in plans with the highest quartile (Q4) of costs were less likely to initiate a GLP-1 RA (adjusted HR, 0.87 [95% CI, 0.78 to 0.97]) or an SGLT2 inhibitor (adjusted HR, 0.80 [95% CI, 0.73 to 0.88]). The median (IQR) number of days to initiating a GLP-1 RA was 481 (207-820) days in Q1 and 556 (237-917) days in Q4 of OOP costs and 520 (193-876) days in Q1 vs 685 (309-1017) days in Q4 for SGLT2 inhibitors. Conclusions and Relevance: In this cohort study of more than 80 000 older adults with T2D and established CVD covered by Medicare Advantage and commercial plans, those in the highest quartile of OOP cost were 13% and 20% less likely to initiate a GLP-1 RA or SGLT2 inhibitor, respectively, when compared with those in the lowest quartile of OOP costs.

Assessment of Commercial and Mandatory Discounts in the Gross-to-Net Bubble for the Top Insulin Products From 2012 to 2019.

Importance: Insulin list prices have grown substantially since 2010, but net prices have declined since 2015 because of manufacturer discounts, leading to an increasingly large difference between list and net prices of drugs often called the gross-to-net bubble. It remains unclear to what extent the gross-to-net bubble represents voluntary manufacturer discounts negotiated in commercial and Medicare Part D markets (hereafter called commercial discounts) vs mandatory discounts under the Medicare Part D coverage gap, Medicaid, and the 340B program. Objective: To decompose the overall gross-to-net bubble of leading insulin products into discount types. Design, Setting, and Participants: This economic evaluation obtained data from Medicare and Medicaid claims and spending dashboards, Medicare Part D Prescriber Public Use File, and SSR Health for the top 4 commonly used insulin products: Lantus, Levemir, Humalog, and Novolog. The gross-to-net bubble, which represents total discounts, was estimated for each insulin product and year (from 2012 to 2019). Analyses were conducted in June to December 2022. Main Outcomes and Measures: The gross-to-net bubble was decomposed into 4 discount types: (1) Medicare Part D coverage gap discounts, (2) Medicaid discounts, (3) 340B discounts, and (4) commercial discounts. Coverage gap discounts were estimated using Medicare Part D claims data. Medicaid and 340B discounts were estimated using a novel algorithm that accounted for best prices set by commercial discounts. Results: Total discounts for the 4 insulin products increased from $4.9 billion to $22.0 billion. Commercial discounts represented a majority of all discounts, increasing from 71.7% of the gross-to-net bubble in 2012 ($3.5 billion) to 74.3% ($16.4 billion) in 2019. Among mandatory discounts, coverage gap discounts remained relatively consistent as a proportion of discounts (5.4% in 2012 vs 5.3% in 2019). Medicaid rebates decreased as a proportion of total discounts, from 19.7% in 2012 to 10.6% in 2019. The 340B discounts increased as a proportion of total discounts from 3.3% in 2012 to 9.8% in 2019. Results for the contribution of discount types to the gross-to-net bubble were consistent across insulin products. Conclusions and Relevance: Results of a decomposition of the gross-to-net bubble for leading insulin products suggest that commercial discounts play a growing role in lowering net sales compared with mandatory discounts.

Prevalence and Cost of Care Cascades Following Low-Value Preoperative Electrocardiogram and Chest Radiograph Within the Veterans Health Administration.

BACKGROUND: Low-value care cascades, defined as the receipt of downstream health services potentially related to a low-value service, can result in harm to patients and wasteful healthcare spending, yet have not been characterized within the Veterans Health Administration (VHA). OBJECTIVE: To examine if the receipt of low-value preoperative testing is associated with greater utilization and costs of potentially related downstream health services in Veterans undergoing low or intermediate-risk surgery. DESIGN: Retrospective cohort study using VHA administrative data from fiscal years 2017-2018 comparing Veterans who underwent low-value preoperative electrocardiogram (EKG) or chest radiograph (CXR) with those who did not. PARTICIPANTS: National cohort of Veterans at low risk of cardiopulmonary disease undergoing low- or intermediate-risk surgery. MAIN MEASURES: Difference in rate of receipt and attributed cost of potential cascade services in Veterans who underwent low-value preoperative testing compared to those who did not KEY RESULTS: Among 635,824 Veterans undergoing low-risk procedures, 7.8% underwent preoperative EKG. Veterans who underwent a preoperative EKG experienced an additional 52.4 (95% CI 47.7-57.2) cascade services per 100 Veterans, resulting in $138.28 (95% CI 126.19-150.37) per Veteran in excess costs. Among 739,005 Veterans undergoing low- or intermediate-risk surgery, 3.9% underwent preoperative CXR. These Veterans experienced an additional 61.9 (95% CI 57.8-66.1) cascade services per 100 Veterans, resulting in $152.08 (95% CI $146.66-157.51) per Veteran in excess costs. For both cohorts, care cascades consisted largely of repeat tests, follow-up imaging, and follow-up visits, with low rates invasive services. CONCLUSIONS: Among a national cohort of Veterans undergoing low- or intermediate-risk surgeries, low-value care cascades following two routine low-value preoperative tests are common, resulting in greater unnecessary care and costs beyond the initial low-value service. These findings may guide de-implementation policies within VHA and other integrated healthcare systems that target those services whose downstream effects are most prevalent and costly.

Assessment of Care Cascades Following Low-Value Prostate-Specific Antigen Testing Among Veterans Dually Enrolled in the US Veterans Health Administration and Medicare Systems.

Importance: Older US veterans commonly receive health care outside of the US Veterans Health Administration (VHA) through Medicare, which may increase receipt of low-value care and subsequent care cascades. Objective: To characterize the frequency, cost, and source of low-value prostate-specific antigen (PSA) testing and subsequent care cascades among veterans dually enrolled in the VHA and Medicare and to determine whether receiving a PSA test through the VHA vs Medicare is associated with more downstream services. Design, Setting, and Participants: This retrospective cohort study used VHA and Medicare administrative data from fiscal years (FYs) 2017 to 2018. The study cohort consisted of male US veterans dually enrolled in the VHA and Medicare who were aged 75 years or older without a history of prostate cancer, elevated PSA, prostatectomy, radiation therapy, androgen deprivation therapy, or a urology visit. Data were analyzed from December 15, 2020, to October 20, 2022. Exposures: Receipt of low-value PSA testing. Main Outcomes and Measures: Differences in the use and cost of cascade services occurring 6 months after receipt of a low-value PSA test were assessed for veterans who underwent low-value PSA testing in the VHA and Medicare compared with those who did not, adjusted for patient- and facility-level covariates. Results: This study included 300 393 male US veterans at risk of undergoing low-value PSA testing. They had a mean (SD) age of 82.6 (5.6) years, and the majority (264 411 [88.0%]) were non-Hispanic White. Of these veterans, 36 459 (12.1%) received a low-value PSA test through the VHA, which was associated with 31.2 (95% CI, 29.2 to 33.2) additional cascade services per 100 veterans and an additional $24.5 (95% CI, $20.8 to $28.1) per veteran compared with the control group. In the same cohort, 17 981 veterans (5.9%) received a PSA test through Medicare, which was associated with 39.3 (95% CI, 37.2 to 41.3) additional cascade services per 100 veterans and an additional $35.9 (95% CI, $31.7 to $40.1) per veteran compared with the control group. When compared directly, veterans who received a PSA test through Medicare experienced 9.9 (95% CI, 9.7 to 10.1) additional cascade services per 100 veterans compared with those who underwent testing within the VHA. Conclusions and Relevance: The findings of this cohort study suggest that US veterans dually enrolled in the VHA and Medicare commonly experienced low-value PSA testing and subsequent care cascades through both systems in FYs 2017 and 2018. Care cascades occurred more frequently through Medicare compared with the VHA. These findings suggest that low-value PSA testing has substantial downstream implications for patients and may be especially challenging to measure when care occurs in multiple health care systems.

Underprescribing vs underfilling to oral anticoagulation: An analysis of linked medical record and claims data for a nationwide sample of patients with atrial fibrillation.

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.

Use and Cost of Low-Value Health Services Delivered or Paid for by the Veterans Health Administration.

Importance: Within the Veterans Health Administration (VA), the use and cost of low-value services delivered by VA facilities or increasingly by VA Community Care (VACC) programs have not been comprehensively quantified. Objective: To quantify veterans' overall use and cost of low-value services, including VA-delivered care and VA-purchased community care. Design, Setting, and Participants: This cross-sectional study assessed a national population of VA-enrolled veterans. Data on enrollment, sociodemographic characteristics, comorbidities, and health care services delivered by VA facilities or paid for by the VA through VACC programs were compiled for fiscal year 2018 from the VA Corporate Data Warehouse. Data analysis was conducted from April 2020 to January 2022. Main Outcomes and Measures: VA administrative data were applied using an established low-value service metric to quantify the use of 29 potentially low-value tests and procedures delivered in VA facilities and by VACC programs across 6 domains: cancer screening, diagnostic and preventive testing, preoperative testing, imaging, cardiovascular testing and procedures, and other procedures. Sensitive and specific criteria were used to determine the low-value service counts per 100 veterans overall, by domain, and by individual service; count and percentage of each low-value service delivered by each setting; and estimated cost of each service. Results: Among 5.2 million enrolled veterans, the mean (SD) age was 62.5 (16.0) years, 91.7% were male, 68.0% were non-Hispanic White, and 32.3% received any service through VACC. By specific criteria, 19.6 low-value services per 100 veterans were delivered in VA facilities or by VACC programs, involving 13.6% of veterans at a total cost of $205.8 million. Overall, the most frequently delivered low-value service was prostate-specific antigen testing for men aged 75 years or older (5.9 per 100 veterans); this was also the service with the greatest proportion delivered by VA facilities (98.9%). The costliest low-value services were spinal injections for low back pain ($43.9 million; 21.4% of low-value care spending) and percutaneous coronary intervention for stable coronary disease ($36.8 million; 17.9% of spending). Conclusions and Relevance: This cross-sectional study found that among veterans enrolled in the VA, more than 1 in 10 have received a low-value service from VA facilities or VACC programs, with approximately $200 million in associated costs. Such information on the use and costs of low-value services are essential to guide the VA's efforts to reduce delivery and spending on such care.

Developing and validating a machine-learning algorithm to predict opioid overdose in Medicaid beneficiaries in two US states: a prognostic modelling study.

BACKGROUND: Little is known about whether machine-learning algorithms developed to predict opioid overdose using earlier years and from a single state will perform as well when applied to other populations. We aimed to develop a machine-learning algorithm to predict 3-month risk of opioid overdose using Pennsylvania Medicaid data and externally validated it in two data sources (ie, later years of Pennsylvania Medicaid data and data from a different state). METHODS: This prognostic modelling study developed and validated a machine-learning algorithm to predict overdose in Medicaid beneficiaries with one or more opioid prescription in Pennsylvania and Arizona, USA. To predict risk of hospital or emergency department visits for overdose in the subsequent 3 months, we measured 284 potential predictors from pharmaceutical and health-care encounter claims data in 3-month periods, starting 3 months before the first opioid prescription and continuing until loss to follow-up or study end. We developed and internally validated a gradient-boosting machine algorithm to predict overdose using 2013-16 Pennsylvania Medicaid data (n=639 693). We externally validated the model using (1) 2017-18 Pennsylvania Medicaid data (n=318 585) and (2) 2015-17 Arizona Medicaid data (n=391 959). We reported several prediction performance metrics (eg, C-statistic, positive predictive value). Beneficiaries were stratified into risk-score subgroups to support clinical use. FINDINGS: A total of 8641 (1·35%) 2013-16 Pennsylvania Medicaid beneficiaries, 2705 (0·85%) 2017-18 Pennsylvania Medicaid beneficiaries, and 2410 (0·61%) 2015-17 Arizona beneficiaries had one or more overdose during the study period. C-statistics for the algorithm predicting 3-month overdoses developed from the 2013-16 Pennsylvania training dataset and validated on the 2013-16 Pennsylvania internal validation dataset, 2017-18 Pennsylvania external validation dataset, and 2015-17 Arizona external validation dataset were 0·841 (95% CI 0·835-0·847), 0·828 (0·822-0·834), and 0·817 (0·807-0·826), respectively. In external validation datasets, 71 361 (22·4%) of 318 585 2017-18 Pennsylvania beneficiaries were in high-risk subgroups (positive predictive value of 0·38-4·08%; capturing 73% of overdoses in the subsequent 3 months) and 40 041 (10%) of 391 959 2015-17 Arizona beneficiaries were in high-risk subgroups (positive predictive value of 0·19-1·97%; capturing 55% of overdoses). Lower risk subgroups in both validation datasets had few individuals (≤0·2%) with an overdose. INTERPRETATION: A machine-learning algorithm predicting opioid overdose derived from Pennsylvania Medicaid data performed well in external validation with more recent Pennsylvania data and with Arizona Medicaid data. The algorithm might be valuable for overdose risk prediction and stratification in Medicaid beneficiaries. FUNDING: National Institute of Health, National Institute on Drug Abuse, National Institute on Aging.

Association of formulary restrictions and initiation of an SGLT2i or GLP1-RA among Medicare beneficiaries with type 2 diabetes.

BACKGROUND: Use of SGLT2 inhibitors (SGLT2i) and GLP-1 receptor agonists (GLP1-RA) among older adults with type 2 diabetes (T2D) has been limited. OBJECTIVE: To examine factors associated with initiation of an SGLT2i or GLP-1RA among Medicare beneficiaries with T2D in the early years after their market approval, with a particular focus on formulary restrictions (e.g. prior authorization, step therapy requirements, higher co-pays). METHODS: A retrospective cohort study using data from a 5% random sample of Medicare beneficiaries with T2D followed from 1/1/2015-12/31/16. Formulary restrictiveness was defined as: (1) the number of target drugs (i.e. SGLT2is or GLP1-RAs) included in tiers 1-3 of a beneficiary's formulary (greater number of drugs in tiers 1-3 being less restrictive) and (2) the number of drugs without prior authorization or step therapy (requirement to try less expensive drugs prior to "stepping up" to more expensive therapies). We used multivariable logistic regression models to estimate the association between measures of formulary restrictiveness and initiation of a target drug, controlling for patient demographics, diabetes duration, clinical comorbidities, and provider specialty. RESULTS: Among 112,985 beneficiaries with T2D, 5,619 (5%) initiated an SGLT2i or GLP1-RA. After adjusting for baseline characteristics, patients enrolled in formularies with ≥ 2 target drugs available in tiers 1-3 had 17% higher odds of initiating an SGLT2i or GLP1-RA (aOR 1.17, 95% CI 1.05-1.31) compared to patients enrolled in formularies with 0 drugs available in tiers 1-3. There was no significant association between the number of drugs without prior authorization or step therapy requirements and initiation of a target drug (aOR 0.96, 95% CI, 0.85-1.09). Age 75 years or older (vs < 65, aOR 0.23, 95% CI 0.21-0.26) and black race (vs white, aOR 0.65, 95% CI 0.59-0.71) were associated with lower odds of initiating a target drug. CONCLUSIONS: Having a greater number of target drugs available on less expensive formulary tiers is associated with increased odds of initiating an SGLT2i or GLP-1RA among Medicare beneficiaries with T2D.

Changes in predicted opioid overdose risk over time in a state Medicaid program: a group-based trajectory modeling analysis.

BACKGROUND AND AIMS: The time lag encountered when accessing health-care data is one major barrier to implementing opioid overdose prediction measures in practice. Little is known regarding how one's opioid overdose risk changes over time. We aimed to identify longitudinal patterns of individual predicted overdose risks among Medicaid beneficiaries after initiation of opioid prescriptions. DESIGN, SETTING AND PARTICIPANTS: A retrospective cohort study in Pennsylvania, USA among Pennsylvania Medicaid beneficiaries aged 18-64 years who initiated opioid prescriptions between July 2017 and September 2018 (318 585 eligible beneficiaries (mean age = 39 ± 12 years, female = 65.7%, White = 62.2% and Black = 24.9%). MEASUREMENTS: We first applied a previously developed and validated machine-learning algorithm to obtain risk scores for opioid overdose emergency room or hospital visits in 3-month intervals for each beneficiary who initiated opioid therapy, until disenrollment from Medicaid, death or the end of observation (December 2018). We performed group-based trajectory modeling to identify trajectories of these predicted overdose risk scores over time. FINDINGS: Among eligible beneficiaries, 0.61% had one or more occurrences of opioid overdose in a median follow-up of 15 months. We identified five unique opioid overdose risk trajectories: three trajectories (accounting for 92% of the cohort) had consistent overdose risk over time, including consistent low-risk (63%), consistent medium-risk (25%) and consistent high-risk (4%) groups; another two trajectories (accounting for 8%) had overdose risks that substantially changed over time, including a group that transitioned from high- to medium-risk (3%) and another group that increased from medium- to high-risk over time (5%). CONCLUSIONS: More than 90% of Medicaid beneficiaries in Pennsylvania USA with one or more opioid prescriptions had consistent, predicted opioid overdose risks over 15 months. Applying opioid prediction algorithms developed from historical data may not be a major barrier to implementation in practice for the large majority of individuals.

Dosing profiles of concurrent opioid and benzodiazepine use associated with overdose risk among US Medicare beneficiaries: group-based multi-trajectory models.

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.

Comparison of oral anticoagulation use and adherence among Medicare beneficiaries enrolled in stand-alone prescription drug plans vs Medicare Advantage prescription drug plans.

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.

Provider and Patient-panel Characteristics Associated With Initial Adoption and Sustained Prescribing of Medication for Opioid Use Disorder.

OBJECTIVES: Limited information is available regarding provider- and patient panel-level factors associated with primary care provider (PCP) adoption/prescribing of medication for opioid use disorder (MOUD). METHODS: We assessed a retrospective cohort from 2015 to 2018 within the Pennsylvania Medicaid Program. Participants included PCPs who were Medicaid providers, with no history of MOUD provision, and who treated ≥10 Medicaid enrollees annually. We assessed initial MOUD adoption, defined as an index buprenorphine/buprenorphine-naloxone or oral/extended release naltrexone fill and sustained prescribing, defined as ≥1 MOUD prescription(s) for 3 consecutive quarters from the PCP. Independent variables included provider- and patient panel-level characteristics. RESULTS: We identified 113 rural and 782 urban PCPs who engaged in initial adoption and 36 rural and 288 urban PCPs who engaged in sustained prescribing. Rural/urban PCPs who issued increasingly larger numbers of antidepressant and antipsychotic medication prescriptions had greater odds of initial adoption and sustained prescribing (P < 0.05) compared to those that did not prescribe these medications. Further, each additional patient out of 100 with opioid use disorder diagnosed before MOUD adoption increased the adjusted odds for initial adoption 2% to 4% (95% confidence interval [CI] = 1.01-1.08) and sustained prescribing by 4% to 7% (95% CI = 1.01-1.08). New Medicaid providers in rural areas were 2.52 (95% CI = 1.04-6.11) and in urban areas were 2.66 (95% CI = 1.94, 3.64) more likely to engage in initial MOUD adoption compared to established PCPs. CONCLUSIONS: MOUD prescribing adoption was concentrated among PCPs prescribing mental health medications, caring for those with OUD, and new Medicaid providers. These results should be leveraged to test/implement interventions targeting MOUD adoption among PCPs.

Opioid-related emergency department visits and hospitalizations among patients with chronic gastrointestinal symptoms and disorders dually enrolled in the Department of Veterans Affairs and Medicare Part D.

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.