Validity of inpatient electronic health record-based measures of oxygen-related therapy in the United States: Lessons applicable for studying COVID-19 endpoints.

INTRODUCTION: During the COVID-19 pandemic, inpatient electronic health records (EHRs) have been used to conduct public health surveillance and assess treatments and outcomes. Invasive mechanical ventilation (MV) and supplemental oxygen (O2) use are markers of severe illness in hospitalized COVID-19 patients. In a large US system (n = 142 hospitals), we assessed documentation of MV and O2 use during COVID-19 hospitalization in administrative data versus nursing documentation. METHODS: We identified 319 553 adult hospitalizations with a COVID-19 diagnosis, February 2020-October 2022, and extracted coded, administrative data for MV or O2. Separately, we developed classification rules for MV or O2 supplementation from semi-structured nursing documentation. We assessed MV and O2 supplementation in administrative data versus nursing documentation and calculated ordinal endpoints of decreasing COVID-19 disease severity. Nursing documentation was considered the gold standard in sensitivity and positive predictive value (PPV) analyses. RESULTS: In nursing documentation, the prevalence of MV and O2 supplementation among COVID-19 hospitalizations was 14% and 75%, respectively. The sensitivity of administrative data was 83% for MV and 41% for O2, with both PPVs above 91%. Concordance between sources was 97% for MV (κ = 0.85), and 54% for O2 (κ = 0.21). For ordinal endpoints, administrative data accurately identified intensive care and MV but underestimated hospitalizations with O2 requirements (42% vs. 18%). CONCLUSIONS: In comparison to nursing documentation, administrative data under-ascertained O2 supplementation but accurately estimated severe endpoints such as MV. Nursing documentation improved ascertainment of O2 among COVID-19 hospitalizations and can capture oxygen requirements in adults hospitalized with COVID-19 or other respiratory illnesses.

Targeted Learning with an Undersmoothed Lasso Propensity Score Model for Large-Scale Covariate Adjustment in Healthcare Database Studies.

Lasso regression is widely used for large-scale propensity score (PS) estimation in healthcare database studies. In these settings, previous work has shown that undersmoothing (overfitting) Lasso PS models can improve confounding control, but it can also cause problems of non-overlap in covariate distributions. It remains unclear how to select the degree of undersmoothing when fitting large-scale Lasso PS models to improve confounding control while avoiding issues that can result from reduced covariate overlap. Here, we used simulations to evaluate the performance of using collaborative-controlled targeted learning to data-adaptively select the degree of undersmoothing when fitting large-scale PS models within both singly and doubly robust frameworks to reduce bias in causal estimators. Simulations showed that collaborative learning can data-adaptively select the degree of undersmoothing to reduce bias in estimated treatment effects. Results further showed that when fitting undersmoothed Lasso PS-models, the use of cross-fitting was important for avoiding non-overlap in covariate distributions and reducing bias in causal estimates.

Risk of Arterial and Venous Thrombotic Events Among Patients with COVID-19: A Multi-National Collaboration of Regulatory Agencies from Canada, Europe, and United States.

Purpose: Few studies have examined how the absolute risk of thromboembolism with COVID-19 has evolved over time across different countries. Researchers from the European Medicines Agency, Health Canada, and the United States (US) Food and Drug Administration established a collaboration to evaluate the absolute risk of arterial (ATE) and venous thromboembolism (VTE) in the 90 days after diagnosis of COVID-19 in the ambulatory (eg, outpatient, emergency department, nursing facility) setting from seven countries across North America (Canada, US) and Europe (England, Germany, Italy, Netherlands, and Spain) within periods before and during COVID-19 vaccine availability. Patients and Methods: We conducted cohort studies of patients initially diagnosed with COVID-19 in the ambulatory setting from the seven specified countries. Patients were followed for 90 days after COVID-19 diagnosis. The primary outcomes were ATE and VTE over 90 days from diagnosis date. We measured country-level estimates of 90-day absolute risk (with 95% confidence intervals) of ATE and VTE. Results: The seven cohorts included 1,061,565 patients initially diagnosed with COVID-19 in the ambulatory setting before COVID-19 vaccines were available (through November 2020). The 90-day absolute risk of ATE during this period ranged from 0.11% (0.09-0.13%) in Canada to 1.01% (0.97-1.05%) in the US, and the 90-day absolute risk of VTE ranged from 0.23% (0.21-0.26%) in Canada to 0.84% (0.80-0.89%) in England. The seven cohorts included 3,544,062 patients with COVID-19 during vaccine availability (beginning December 2020). The 90-day absolute risk of ATE during this period ranged from 0.06% (0.06-0.07%) in England to 1.04% (1.01-1.06%) in the US, and the 90-day absolute risk of VTE ranged from 0.25% (0.24-0.26%) in England to 1.02% (0.99-1.04%) in the US. Conclusion: There was heterogeneity by country in 90-day absolute risk of ATE and VTE after ambulatory COVID-19 diagnosis both before and during COVID-19 vaccine availability.

Treatment and care received by children hospitalized with COVID-19 in a large hospital network in the United States, February 2020 to September 2021.

We described care received by hospitalized children with COVID-19 or multi-system inflammatory syndrome (MIS-C) prior to the 2021 COVID-19 Omicron variant surge in the US. We identified hospitalized children <18 years of age with a COVID-19 or MIS-C diagnosis (COVID-19 not required), separately, from February 2020-September 2021 (n = 126 hospitals). We described high-risk conditions, inpatient treatments, and complications among these groups. Among 383,083 pediatric hospitalizations, 2,186 had COVID-19 and 395 had MIS-C diagnosis. Less than 1% had both COVID-19 and MIS-C diagnosis (n = 154). Over half were >6 years old (54% COVID-19, 70% MIS-C). High-risk conditions included asthma (14% COVID-19, 11% MIS-C), and obesity (9% COVID-19, 10% MIS-C). Pulmonary complications in children with COVID-19 included viral pneumonia (24%) and acute respiratory failure (11%). In reference to children with COVID-19, those with MIS-C had more hematological disorders (62% vs 34%), sepsis (16% vs 6%), pericarditis (13% vs 2%), myocarditis (8% vs 1%). Few were ventilated or died, but some required oxygen support (38% COVID-19, 45% MIS-C) or intensive care (42% COVID-19, 69% MIS-C). Treatments included: methylprednisolone (34% COVID-19, 75% MIS-C), dexamethasone (25% COVID-19, 15% MIS-C), remdesivir (13% COVID-19, 5% MIS-C). Antibiotics (50% COVID-19, 68% MIS-C) and low-molecular weight heparin (17% COVID-19, 34% MIS-C) were frequently administered. Markers of illness severity among hospitalized children with COVID-19 prior to the 2021 Omicron surge are consistent with previous studies. We report important trends on treatments in hospitalized children with COVID-19 to improve the understanding of real-world treatment patterns in this population.

Switching patterns of immediate-release forms of generic mixed amphetamine salts products among privately and publicly insured individuals aged 15-64 years in the United States, 2013-2019.

PURPOSE: Immediate-release forms of generic mixed amphetamine salts (MAS) have been the subject of passive surveillance reports signaling lack of effectiveness. We examined switching patterns that might suggest whether long-term users of specific MAS are more likely to switch away or switch back after use of the MAS of interest in the FDA's Sentinel Distributed Database. METHODS: We required at least 60-day continuous supply of selected MAS grouped by Abbreviated New Drug Application (ANDA) to describe patterns of switching away from and to generics approved under the ANDAs of interest among individuals ages 15-64 years with attention deficit hyperactivity disorder or narcolepsy during 2013-2019. RESULTS: We observed the greatest number of treatment episodes for ANDA 040422 (n = 525 771), followed by ANDA 202424 (n = 181 693), ANDA 040439 (n = 62 363), ANDA 040440 (n = 21 143), and ANDA 040480 (n = 8792). Of those with switches away from their original ANDA, episodes initiated on generic products under ANDA 040422 (48.6%) and ANDA 202424 (43.0%) were most likely to switch back, while those initiated on generic product under ANDA 040480 were least likely (24.1%). Of those episodes with switches to a generic under an ANDA of interest, about one-third (range 27.1% to 37.0%) switched back to the same product. These switches back had a median time to switch of about 30 days. CONCLUSIONS: These descriptive analyses, although subject to limitations, did not suggest increased switching away or switching back after use of the generics of interest. Continued post-marketing surveillance is warranted.

Six Years of the US Food and Drug Administration's Postmarket Active Risk Identification and Analysis System in the Sentinel Initiative: Implications for Real World Evidence Generation.

Congress mandated the creation of a postmarket Active Risk Identification and Analysis (ARIA) system containing data on 100 million individuals for monitoring risks associated with drug and biologic products using data from disparate sources to complement the US Food and Drug Administration's (FDA's) existing postmarket capabilities. We report on the first 6 years of ARIA utilization in the Sentinel System (2016-2021). The FDA has used the ARIA system to evaluate 133 safety concerns; 54 of these evaluations have closed with regulatory determinations, whereas the rest remain in progress. If the ARIA system and the FDA's Adverse Event Reporting System are deemed insufficient to address a safety concern, then the FDA may issue a postmarket requirement to a product's manufacturer. One hundred ninety-seven ARIA insufficiency determinations have been made. The most common situation for which ARIA was found to be insufficient is the evaluation of adverse pregnancy and fetal outcomes following in utero drug exposure, followed by neoplasms and death. ARIA was most likely to be sufficient for thromboembolic events, which have high positive predictive value in claims data alone and do not require supplemental clinical data. The lessons learned from this experience illustrate the continued challenges using administrative claims data, especially to define novel clinical outcomes. This analysis can help to identify where more granular clinical data are needed to fill gaps to improve the use of real-world data for drug safety analyses and provide insights into what is needed to efficiently generate high-quality real-world evidence for efficacy.

Risk of admission to hospital with arterial or venous thromboembolism among patients diagnosed in the ambulatory setting with covid-19 compared with influenza: retrospective cohort study.

Objective: To measure the 90 day risk of arterial thromboembolism and venous thromboembolism among patients diagnosed with covid-19 in the ambulatory (ie, outpatient, emergency department, or institutional) setting during periods before and during covid-19 vaccine availability and compare results to patients with ambulatory diagnosed influenza. Design: Retrospective cohort study. Setting: Four integrated health systems and two national health insurers in the US Food and Drug Administration's Sentinel System. Participants: Patients with ambulatory diagnosed covid-19 when vaccines were unavailable in the US (period 1, 1 April-30 November 2020; n=272 065) and when vaccines were available in the US (period 2, 1 December 2020-31 May 2021; n=342 103), and patients with ambulatory diagnosed influenza (1 October 2018-30 April 2019; n=118 618). Main outcome measures: Arterial thromboembolism (hospital diagnosis of acute myocardial infarction or ischemic stroke) and venous thromboembolism (hospital diagnosis of acute deep venous thrombosis or pulmonary embolism) within 90 days after ambulatory covid-19 or influenza diagnosis. We developed propensity scores to account for differences between the cohorts and used weighted Cox regression to estimate adjusted hazard ratios of outcomes with 95% confidence intervals for covid-19 during periods 1 and 2 versus influenza. Results: 90 day absolute risk of arterial thromboembolism with covid-19 was 1.01% (95% confidence interval 0.97% to 1.05%) during period 1, 1.06% (1.03% to 1.10%) during period 2, and with influenza was 0.45% (0.41% to 0.49%). The risk of arterial thromboembolism was higher for patients with covid-19 during period 1 (adjusted hazard ratio 1.53 (95% confidence interval 1.38 to 1.69)) and period 2 (1.69 (1.53 to 1.86)) than for patients with influenza. 90 day absolute risk of venous thromboembolism with covid-19 was 0.73% (0.70% to 0.77%) during period 1, 0.88% (0.84 to 0.91%) during period 2, and with influenza was 0.18% (0.16% to 0.21%). Risk of venous thromboembolism was higher with covid-19 during period 1 (adjusted hazard ratio 2.86 (2.46 to 3.32)) and period 2 (3.56 (3.08 to 4.12)) than with influenza. Conclusions: Patients diagnosed with covid-19 in the ambulatory setting had a higher 90 day risk of admission to hospital with arterial thromboembolism and venous thromboembolism both before and after covid-19 vaccine availability compared with patients with influenza.

Association of COVID-19 vs Influenza With Risk of Arterial and Venous Thrombotic Events Among Hospitalized Patients.

Importance: The incidence of arterial thromboembolism and venous thromboembolism in persons with COVID-19 remains unclear. Objective: To measure the 90-day risk of arterial thromboembolism and venous thromboembolism in patients hospitalized with COVID-19 before or during COVID-19 vaccine availability vs patients hospitalized with influenza. Design, Setting, and Participants: Retrospective cohort study of 41 443 patients hospitalized with COVID-19 before vaccine availability (April-November 2020), 44 194 patients hospitalized with COVID-19 during vaccine availability (December 2020-May 2021), and 8269 patients hospitalized with influenza (October 2018-April 2019) in the US Food and Drug Administration Sentinel System (data from 2 national health insurers and 4 regional integrated health systems). Exposures: COVID-19 or influenza (identified by hospital diagnosis or nucleic acid test). Main Outcomes and Measures: Hospital diagnosis of arterial thromboembolism (acute myocardial infarction or ischemic stroke) and venous thromboembolism (deep vein thrombosis or pulmonary embolism) within 90 days. Outcomes were ascertained through July 2019 for patients with influenza and through August 2021 for patients with COVID-19. Propensity scores with fine stratification were developed to account for differences between the influenza and COVID-19 cohorts. Weighted Cox regression was used to estimate the adjusted hazard ratios (HRs) for outcomes during each COVID-19 vaccine availability period vs the influenza period. Results: A total of 85 637 patients with COVID-19 (mean age, 72 [SD, 13.0] years; 50.5% were male) and 8269 with influenza (mean age, 72 [SD, 13.3] years; 45.0% were male) were included. The 90-day absolute risk of arterial thromboembolism was 14.4% (95% CI, 13.6%-15.2%) in patients with influenza vs 15.8% (95% CI, 15.5%-16.2%) in patients with COVID-19 before vaccine availability (risk difference, 1.4% [95% CI, 1.0%-2.3%]) and 16.3% (95% CI, 16.0%-16.6%) in patients with COVID-19 during vaccine availability (risk difference, 1.9% [95% CI, 1.1%-2.7%]). Compared with patients with influenza, the risk of arterial thromboembolism was not significantly higher among patients with COVID-19 before vaccine availability (adjusted HR, 1.04 [95% CI, 0.97-1.11]) or during vaccine availability (adjusted HR, 1.07 [95% CI, 1.00-1.14]). The 90-day absolute risk of venous thromboembolism was 5.3% (95% CI, 4.9%-5.8%) in patients with influenza vs 9.5% (95% CI, 9.2%-9.7%) in patients with COVID-19 before vaccine availability (risk difference, 4.1% [95% CI, 3.6%-4.7%]) and 10.9% (95% CI, 10.6%-11.1%) in patients with COVID-19 during vaccine availability (risk difference, 5.5% [95% CI, 5.0%-6.1%]). Compared with patients with influenza, the risk of venous thromboembolism was significantly higher among patients with COVID-19 before vaccine availability (adjusted HR, 1.60 [95% CI, 1.43-1.79]) and during vaccine availability (adjusted HR, 1.89 [95% CI, 1.68-2.12]). Conclusions and Relevance: Based on data from a US public health surveillance system, hospitalization with COVID-19 before and during vaccine availability, vs hospitalization with influenza in 2018-2019, was significantly associated with a higher risk of venous thromboembolism within 90 days, but there was no significant difference in the risk of arterial thromboembolism within 90 days.

Evaluating Confounding Control in Estimations of Influenza Antiviral Effectiveness in Electronic Health Plan Data.

Observational studies of oseltamivir use and influenza complications could suffer from residual confounding. Using negative control risk periods and a negative control outcome, we examined confounding control in a health-insurance-claims-based study of oseltamivir and influenza complications (pneumonia, all-cause hospitalization, and dispensing of an antibiotic). Within the Food and Drug Administration's Sentinel System, we identified individuals aged ≥18 years who initiated oseltamivir use on the influenza diagnosis date versus those who did not, during 3 influenza seasons (2014-2017). We evaluated primary outcomes within the following 1-30 days (the primary risk period) and 61-90 days (the negative control period) and nonvertebral fractures (the negative control outcome) within days 1-30. We estimated propensity-score-matched risk ratios (RRs) per season. During the 2014-2015 influenza season, oseltamivir use was associated with a reduction in the risk of pneumonia (RR = 0.72, 95% confidence interval (CI): 0.70, 0.75) and all-cause hospitalization (RR = 0.54, 95% CI: 0.53, 0.55) in days 1-30. During days 61-90, estimates were near-null for pneumonia (RR = 1.04, 95% CI: 0.95, 1.15) and hospitalization (RR = 0.94, 95% CI: 0.91, 0.98) but slightly increased for antibiotic dispensing (RR = 1.14, 95% CI: 1.08, 1.21). The RR for fractures was near-null (RR = 1.09, 95% CI: 0.99, 1.20). Estimates for the 2016-2017 influenza season were comparable, while the 2015-2016 season had conflicting results. Our study suggests minimal residual confounding for specific outcomes, but results differed by season.

Validation of diagnosis codes to identify hospitalized COVID-19 patients in health care claims data.

PURPOSE: Health plan claims may provide complete longitudinal data for timely, real-world population-level COVID-19 assessment. However, these data often lack laboratory results, the standard for COVID-19 diagnosis. METHODS: We assessed the validity of ICD-10-CM diagnosis codes for identifying patients hospitalized with COVID-19 in U.S. claims databases, compared to linked laboratory results, among six Food and Drug Administration Sentinel System data partners (two large national insurers, four integrated delivery systems) from February 20-October 17, 2020. We identified patients hospitalized with COVID-19 according to five ICD-10-CM diagnosis code-based algorithms, which included combinations of codes U07.1, B97.29, general coronavirus codes, and diagnosis codes for severe symptoms. We calculated the positive predictive value (PPV) and sensitivity of each algorithm relative to laboratory test results. We stratified results by data source type and across three time periods: February 20-March 31 (Time A), April 1-30 (Time B), May 1-October 17 (Time C). RESULTS: The five algorithms identified between 34 806 and 47 293 patients across the study periods; 23% with known laboratory results contributed to PPV calculations. PPVs were high and similar across algorithms. PPV of U07.1 alone was stable around 93% for integrated delivery systems, but declined over time from 93% to 70% among national insurers. Overall PPV of U07.1 across all data partners was 94.1% (95% CI, 92.3%-95.5%) in Time A and 81.2% (95% CI, 80.1%-82.2%) in Time C. Sensitivity was consistent across algorithms and over time, at 94.9% (95% CI, 94.2%-95.5%). CONCLUSION: Our results support the use of code U07.1 to identify hospitalized COVID-19 patients in U.S. claims data.

Using inpatient electronic medical records to study influenza for pandemic preparedness.

BACKGROUND: We assessed the ability to identify key data relevant to influenza and other respiratory virus surveillance in a large-scale US-based hospital electronic medical record (EMR) dataset using seasonal influenza as a use case. We describe characteristics and outcomes of hospitalized influenza cases across three seasons. METHODS: We identified patients with an influenza diagnosis between March 2017 and March 2020 in 140 US hospitals as part of the US FDA's Sentinel System. We calculated descriptive statistics on the presence of high-risk conditions, influenza antiviral administrations, and severity endpoints. RESULTS: Among 5.1 million hospitalizations, we identified 29,520 hospitalizations with an influenza diagnosis; 64% were treated with an influenza antiviral within 2 days of admission, and 25% were treated >2 days after admission. Patients treated >2 days after admission had more comorbidities than patients treated within 2 days of admission. Patients never treated during hospitalization had more documentation of cardiovascular and other diseases than treated patients. We observed more severe endpoints in patients never treated (death = 3%, mechanical ventilation [MV] = 9%, intensive care unit [ICU] = 26%) or patients treated >2 days after admission (death = 2%, MV = 14%, ICU = 32%) than in patients treated earlier (treated on admission: death = 1%, MV = 5%, ICU = 23%, treated within 2 days of admission: death = 1%, MV = 7%, ICU = 27%). CONCLUSIONS: We identified important trends in influenza severity related to treatment timing in a large inpatient dataset, laying the groundwork for the use of this and other inpatient EMR data for influenza and other respiratory virus surveillance.

Who gets treated for influenza: A surveillance study from the US Food and Drug Administration's Sentinel System.

OBJECTIVE: We describe the baseline characteristics and complications of individuals with influenza in the US FDA's Sentinel System by antiviral treatment timing. DESIGN: Retrospective cohort design. PATIENTS: Individuals aged ≥6 months with outpatient diagnoses of influenza in June 2014-July 2017, 3 influenza seasons. METHODS: We identified the comorbidities, vaccination history, influenza testing, and outpatient antiviral dispensings of individuals with influenza using administrative claims data from 13 data partners including the Centers for Medicare and Medicaid Services, integrated delivery systems, and commercial health plans. We assessed complications within 30 days: hospitalization, oxygen use, mechanical ventilation, critical care, ECMO, and death. RESULTS: There were 1,090,333 influenza diagnoses in 2014-2015; 1,005,240 in 2016-2017; and 578,548 in 2017-2018. Between 49% and 55% of patients were dispensed outpatient treatment within 5 days. In all periods >80% of treated individuals received treatment on the day of diagnosis. Those treated on days 1-5 after diagnosis had higher prevalences of diabetes, chronic obstructive pulmonary disease, asthma, and obesity compared to those treated on the day of diagnosis or not treated at all. They also had higher rates of hospitalization, oxygen use, and critical care. In 2014-2015, among those aged ≥65 years, the rates of hospitalization were 45 per 1,000 diagnoses among those treated on day 0; 74 per 1,000 among those treated on days 1-5; and 50 per 1,000 among those who were untreated. CONCLUSIONS: In a large, national analysis, approximately half of people diagnosed with influenza in the outpatient setting were treated with antiviral medications. Delays in outpatient dispensed treatment were associated with higher prevalence of comorbidities and higher rates of complication.

Validation of an electronic algorithm for Hodgkin and non-Hodgkin lymphoma in ICD-10-CM.

PURPOSE: Lymphoma is a health outcome of interest for drug safety studies. Studies using administrative claims data require the accurate identification of lymphoma cases. We developed and validated an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify lymphoma in healthcare claims data. METHODS: We developed a three-component algorithm to identify patients aged ≥15 years who were newly diagnosed with Hodgkin (HL) or non-Hodgkin (NHL) lymphoma from January 2016 through July 2018 among members of four Data Partners within the FDA's Sentinel System. The algorithm identified potential cases as patients with ≥2 ICD-10-CM lymphoma diagnosis codes on different dates within 183 days; ≥1 procedure code for a diagnostic procedure (e.g., biopsy, flow cytometry) and ≥1 procedure code for a relevant imaging study within 90 days of the first lymphoma diagnosis code. Cases identified by the algorithm were adjudicated via chart review and a positive predictive value (PPV) was calculated. RESULTS: We identified 8723 potential lymphoma cases via the algorithm and randomly sampled 213 for validation. We retrieved 138 charts (65%) and adjudicated 134 (63%). The overall PPV was 77% (95% confidence interval: 69%-84%). Most cases also had subtype information available, with 88% of cases identified as NHL and 11% as HL. CONCLUSIONS: Seventy-seven percent of lymphoma cases identified by an algorithm based on ICD-10-CM diagnosis and procedure codes and applied to claims data were true cases. This novel algorithm represents an efficient, cost-effective way to target an important health outcome of interest for large-scale drug safety and public health surveillance studies.

Comparative Effectiveness of Generic vs Brand-Name Levothyroxine in Achieving Normal Thyrotropin Levels.

Importance: Whether the use of generic vs brand levothyroxine affects thyrotropin levels remains unclear. Objective: To compare the effectiveness of generic vs brand levothyroxine in achieving and maintaining normal thyrotropin levels among new users. Design, Setting, and Participants: This retrospective, 1:1 propensity score-matched longitudinal cohort study used the OptumLabs Data Warehouse administrative claims database linked to laboratory results from commercially insured and Medicare Advantage enrollees throughout the United States. Eligible patients were adults (aged ≥18 years) with thyrotropin levels ranging from 4.5 to 19.9 mIU/L who initiated use of generic or brand-name levothyroxine from January 1, 2008, to October 1, 2017. Data were analyzed from August 13, 2018, to October 25, 2019. Exposure: Patients received generic or brand-name levothyroxine. Main Outcomes and Measures: Proportion of patients with normal vs markedly abnormal thyrotropin levels (<0.1 or >10 mIU/L) within 3 months and with stable thyrotropin levels within 3 months after the thyrotropin value fell into the normal range. Results: A total of 17 598 patients were included (69.0% female; 74.0% White; mean [SD] age, 55.1 [16.0] years), of whom 15 299 filled generic and 2299 filled brand-name levothyroxine prescriptions during the study period. Among 4570 propensity score-matched patients (mean [SD] age, 50.3 [13.8] years; 3457 [75.6%] female; 3510 [76.8%] White), the proportion with normal thyrotropin levels within 3 months of filling levothyroxine prescriptions was similar for patients who received generic vs brand-name levothyroxine (1722 [75.4%; 95% CI, 71.9%-79.0%] vs 1757 [76.9%; 95% CI, 73.4%-80.6%]; P = .23), as was the proportion with markedly abnormal levels (94 [4.1%; 95% CI, 3.4%-5.0%] vs 88 [3.9%; 95% CI, 3.1%-4.7%]; P = .65). Among 1034 propensity score-matched patients who achieved a normal thyrotropin value within 3 months of initiation of levothyroxine, the proportion maintaining subsequent normal thyrotropin levels during the next 3 months was similar for patients receiving generic vs brand-name levothyroxine (427 [82.6%] vs 433 [83.8%]; P = .62). Conclusions and Relevance: Initiation of generic vs brand-name levothyroxine formulations was associated with similar rates of normal and stable thyrotropin levels. These results suggest that generic levothyroxine as initial therapy for mild thyroid dysfunction is as effective as brand-name levothyroxine.

Preferences for and experiences with pill appearance changes: national surveys of patients and pharmacists.

OBJECTIVES: To better understand patients' and pharmacists' preferences for and experiences with changes in pill appearance (size, shape, color, and markings). STUDY DESIGN: Cross-sectional. METHODS: We conducted independent national surveys of patients 50 years and older taking generic drugs for depression, diabetes, epilepsy, HIV, hyperlipidemia, or hypertension and of licensed pharmacists practicing in chain, franchise, or independent pharmacies. Responses were collected between January and April 2016. RESULTS: Of 1000 patient respondents (30% response rate), most reported experiencing changes in pill appearance (51%) and preferred to be notified about them (82%), but less than half recalled being notified (verbally: 36%; via sticker: 45%). Among patients who reported experiencing a change, 12% reported stopping their medication or using it less frequently. Of 710 pharmacist respondents (33% response rate), many reported changes in pill appearance occurring frequently in their pharmacies (47% reported that changes occurred 6 or more times per month) and more than three-fourths reported notifying patients about them often (verbally: 88%; via sticker: 77%). CONCLUSIONS: Our findings reveal opportunities to improve patients' experiences with pill appearance changes through better notification practices and patient education.

Determinants of Generic Drug Substitution in the United States.

BACKGROUND: Some classes of drugs have lower than optimal uptake of generic products. We aimed to understand the determinants of generic drug substitution across classes. METHODS: We conducted a cross-sectional analysis of data from the 2013 MarketScan Commercial Claims and Encounters Database from Truven Health Analytics. We quantified generic substitution rates (GSR) for 26 drug classes, choosing one representative week in November 2013. We used mixed-effects logistic regression to estimate the independent relationship between the determinants of interest and generic substitution for 8 classes with low generic utilization. RESULTS: The GSRs for most classes exceeded 90%, although some were much lower including thyroid hormones (64%), androgens (74%), estrogens (71%), and hydantoin-type anticonvulsants (72%). The determinants of generic substitution varied across classes, albeit with important patterns. Patients using a mail order pharmacy had significantly less generic substitution than patients filling at retail pharmacies for 5 of the 8 studied classes; two additional classes showed no relationship between pharmacy type and generic use. Men relative to women and patients taking more medications were more likely to use generics for most classes. State substitution laws and patient consent laws were largely inconsequential regarding generic substitution. CONCLUSIONS: Policies are needed to support the use of safe, effective and often lower cost generic drugs, when available. Mail order pharmacies, as often required by pharmacy benefits managers, lessen generic use for many classes. These pharmacies may require additional regulatory oversight if this adversely impacts patients.

Generic levothyroxine initiation and substitution among Medicare and Medicaid populations: a new user cohort study.

PURPOSE: Generic levothyroxine has been approved and available since 2004 but its substitution remains controversial. Therefore, the objective was to examine patterns of and identify factors associated with initiation and substitution of generic levothyroxine treatment. METHODS: This was a retrospective observational study, including new users of brand and generic levothyroxine in 2013-2015 Medicare (n = 15,877) or 2011-2012 Medicaid (n = 9390) administrative claim databases. The primary outcomes included (1) generic levothyroxine initiation, and (2) among brand-new users, generic levothyroxine substitution in 12 months. The factors associated with generic levothyroxine initiation and substitution were measured. RESULTS: Among all levothyroxine new users, Medicare beneficiaries had a higher proportion of generic levothyroxine initiation than Medicaid beneficiaries (66.40% vs. 44.04%, respectively). Medicare beneficiaries' demographic factors, and health service utilizations were associated with generic levothyroxine initiation. Medicaid beneficiaries who were male and residing in the northeast region and rural areas were more likely to initiate generic levothyroxine. Among brand levothyroxine new users, the generic substitution rate was higher in the Medicare than the Medicaid cohort (18.26 vs. 3.88%). Medicare brand levothyroxine new users' demographic factors and health service utilizations were associated with generic levothyroxine substitution. Medicaid brand levothyroxine new users who were residing in the northeast region, with more prior hospitalization, and initiating a lower dosage of brand levothyroxine, had higher rates of generic substitution. CONCLUSION: Patient demographic factors and health service utilizations are associated with generic levothyroxine initiation and substitution. Educational outreach programs targeted to increase generic levothyroxine use and prescription savings should be tailored based on different patient populations.