Screening Medications for Association with Progression to Wet Age-Related Macular Degeneration.

PURPOSE: There is an urgent need for treatments that prevent or delay development to advanced age-related macular degeneration (AMD). Drugs already on the market for other conditions could affect progression to neovascular AMD (nAMD). If identified, these drugs could provide insights for drug development targets. The objective of this study was to use a novel data mining method that can simultaneously evaluate thousands of correlated hypotheses, while adjusting for multiple testing, to screen for associations between drugs and delayed progression to nAMD. DESIGN: We applied a nested case-control study to administrative insurance claims data to identify cases with nAMD and risk-set sampled controls that were 1:4 variable ratio matched on age, gender, and recent healthcare use. PARTICIPANTS: The study population included cases with nAMD and risk set matched controls. METHODS: We used a tree-based scanning method to evaluate associations between hierarchical classifications of drugs that patients were exposed to within 6 months, 7 to 24 months, or ever before their index date. The index date was the date of first nAMD diagnosis in cases. Risk-set sampled controls were assigned the same index date as the case to which they were matched. The study was implemented using Medicare data from New Jersey and Pennsylvania, and national data from IBM MarketScan Research Database. We set an a priori threshold for statistical alerting at P ≤ 0.01 and focused on associations with large magnitude (relative risks ≥ 2.0). MAIN OUTCOME MEASURES: Progression to nAMD. RESULTS: Of approximately 4000 generic drugs and drug classes evaluated, the method detected 19 distinct drug exposures with statistically significant, large relative risks indicating that cases were less frequently exposed than controls. These included (1) drugs with prior evidence for a causal relationship (e.g., megestrol); (2) drugs without prior evidence for a causal relationship, but potentially worth further exploration (e.g., donepezil, epoetin alfa); (3) drugs with alternative biologic explanations for the association (e.g., sevelamer); and (4) drugs that may have resulted in statistical alerts due to their correlation with drugs that alerted for other reasons. CONCLUSIONS: This exploratory drug-screening study identified several potential targets for follow-up studies to further evaluate and determine if they may prevent or delay progression to advanced AMD.

Comparative effectiveness of generic and brand-name medication use: A database study of US health insurance claims.

BACKGROUND: To the extent that outcomes are mediated through negative perceptions of generics (the nocebo effect), observational studies comparing brand-name and generic drugs are susceptible to bias favoring the brand-name drugs. We used authorized generic (AG) products, which are identical in composition and appearance to brand-name products but are marketed as generics, as a control group to address this bias in an evaluation aiming to compare the effectiveness of generic versus brand medications. METHODS AND FINDINGS: For commercial health insurance enrollees from the US, administrative claims data were derived from 2 databases: (1) Optum Clinformatics Data Mart (years: 2004-2013) and (2) Truven MarketScan (years: 2003-2015). For a total of 8 drug products, the following groups were compared using a cohort study design: (1) patients switching from brand-name products to AGs versus generics, and patients initiating treatment with AGs versus generics, where AG use proxied brand-name use, addressing negative perception bias, and (2) patients initiating generic versus brand-name products (bias-prone direct comparison) and patients initiating AG versus brand-name products (negative control). Using Cox proportional hazards regression after 1:1 propensity-score matching, we compared a composite cardiovascular endpoint (for amlodipine, amlodipine-benazepril, and quinapril), non-vertebral fracture (for alendronate and calcitonin), psychiatric hospitalization rate (for sertraline and escitalopram), and insulin initiation (for glipizide) between the groups. Inverse variance meta-analytic methods were used to pool adjusted hazard ratios (HRs) for each comparison between the 2 databases. Across 8 products, 2,264,774 matched pairs of patients were included in the comparisons of AGs versus generics. A majority (12 out of 16) of the clinical endpoint estimates showed similar outcomes between AGs and generics. Among the other 4 estimates that did have significantly different outcomes, 3 suggested improved outcomes with generics and 1 favored AGs (patients switching from amlodipine brand-name: HR [95% CI] 0.92 [0.88-0.97]). The comparison between generic and brand-name initiators involved 1,313,161 matched pairs, and no differences in outcomes were noted for alendronate, calcitonin, glipizide, or quinapril. We observed a lower risk of the composite cardiovascular endpoint with generics versus brand-name products for amlodipine and amlodipine-benazepril (HR [95% CI]: 0.91 [0.84-0.99] and 0.84 [0.76-0.94], respectively). For escitalopram and sertraline, we observed higher rates of psychiatric hospitalizations with generics (HR [95% CI]: 1.05 [1.01-1.10] and 1.07 [1.01-1.14], respectively). The negative control comparisons also indicated potentially higher rates of similar magnitude with AG compared to brand-name initiation for escitalopram and sertraline (HR [95% CI]: 1.06 [0.98-1.13] and 1.11 [1.05-1.18], respectively), suggesting that the differences observed between brand and generic users in these outcomes are likely explained by either residual confounding or generic perception bias. Limitations of this study include potential residual confounding due to the unavailability of certain clinical parameters in administrative claims data and the inability to evaluate surrogate outcomes, such as immediate changes in blood pressure, upon switching from brand products to generics. CONCLUSIONS: In this study, we observed that use of generics was associated with comparable clinical outcomes to use of brand-name products. These results could help in promoting educational interventions aimed at increasing patient and provider confidence in the ability of generic medicines to manage chronic diseases.

Breast cancer-specific survival by age: Worse outcomes for the oldest patients.

BACKGROUND: Although breast cancer often is perceived to be indolent in older women, breast cancer outcomes in the oldest patients are variable. In the current study, the authors examined breast cancer-specific death by age, stage, and disease subtype in a large, population-based cohort. METHODS: Using Surveillance, Epidemiology, and End Results data, a total of 486,118 women diagnosed with American Joint Committee on Cancer stage I to IV breast cancer between 2000 and 2012 were identified. Using a series of Fine and Gray regression models to account for competing risk, the authors examined the risk of breast cancer-specific death by age and stage (I-IV) for subcohorts with hormone receptor (HR)-positive, HR-negative, human epidermal growth factor receptor 2-positive, and triple-negative disease, adjusting for demographic and clinical variables. RESULTS: Overall, 18% of women were aged 65 to 74 years, 13% were aged 75 to 84 years, and 4% were aged ≥85 years. Regardless of stage of disease within the HR-positive and HR-negative cohorts, patients aged ≥75 years (vs those aged 55-64 years) experienced a higher adjusted hazard of breast cancer-specific death, which was particularly evident for those with early-stage, HR-positive disease (hazard ratio for those aged 75-84 years, 1.88 [95% confidence interval, 1.68-2.09] and hazard ratio for those aged ≥85 years, 3.59 [95% confidence interval, 3.12-4.13] [both for stage I disease]). In the cohorts with human epidermal growth factor receptor 2-positive and triple-negative disease, women aged ≥70 years had a consistently higher risk of breast cancer-specific death across disease stages (vs those aged 51-60 years), with the exception of stage IV triple-negative disease. CONCLUSIONS: Older patients experience worse breast cancer outcomes, regardless of disease subtype and stage. With an increasing number of older patients anticipated to develop breast cancer in the future, addressing disparities for older patients must emerge as a clinical and research priority. Cancer 2018;124:2184-91. © 2018 American Cancer Society.

Out-of-system Care and Recording of Patient Characteristics Critical for Comparative Effectiveness Research.

BACKGROUND: It is unclear how out-of-system care or electronic health record (EHR) discontinuity (i.e., receiving care outside of an EHR system) may affect validity of comparative effectiveness research using these data. We aimed to compare the misclassification of key variables in patients with high versus low EHR continuity. METHODS: The study cohort comprised patients ages ≥65 identified in electronic health records from two US provider networks linked with Medicare insurance claims data from 2007 to 2014. By comparing electronic health records and claims data, we quantified EHR continuity by the proportion of encounters captured by the EHRs (i.e., "capture proportion"). Within levels of EHR continuity, for 40 key variables, we quantified misclassification by mean standardized differences between coding based on EHRs alone versus linked claims and EHR data. RESULTS: Based on 183,739 patients, we found that mean capture proportion in a single electronic health record system was 16%-27% across two provider networks. Patients with highest level of EHR continuity (capture proportion ≥ 80%) had 11.4- to 17.4-fold less variable misclassification, when compared with those with lowest level of EHR continuity (capture proportion< 10%). Capturing at least 60% of the encounters in an EHR system was required to have reasonable variable classification (mean standardized difference <0.1). We found modest differences in comorbidity profiles between patients with high and low EHR continuity. CONCLUSIONS: EHR discontinuity may lead to substantial misclassification in key variables. Restricting comparative effectiveness research to patients with high EHR continuity may confer a favorable benefit (reducing information bias) to risk (losing generalizability) ratio.

Comparative risk of incident venous thromboembolism in patients with inflammatory bowel disease initiating tumour necrosis factor-α inhibitors or nonbiologic agents: a cohort study.

BACKGROUND: Inflammatory bowel disease (IBD) increases the risk of venous thromboembolism (VTE) by 2 to 3 times. We compared the reduction in risk of incident VTE associated with use of tumour necrosis factor-α (TNF-α) inhibitors versus nonbiologic immunomodulatory agents in patients with IBD. METHODS: This observational cohort study used data from public (Medicaid, 2000-2010; Medicare, 2007-2013) and private (Optum Clinformatics, 2004-2013) health insurance programs in the United States. We included a total of 21 671 patients who had IBD without a prior diagnosis of cancer or VTE. The exposure of interest was treatment initiation with TNF-α inhibitor or nonbiologic (azathioprine, mercaptopurine, methotrexate, cyclosporine). The outcome of interest was admission to hospital with VTE as the principal diagnosis. We used Cox proportional hazard regression models to estimate hazard ratios (HRs) separately for each database after risk adjustment for more than 50 covariables using propensity score fine stratification. We used inverse variance meta-analytic methods to pool the adjusted HRs across the 3 databases. RESULTS: We included a total of 5173 patients who started TNF-α inhibitor therapy (1439 in the Medicaid database, 1480 in Medicare and 2254 in Optum Clinformatics) and 16 498 who initiated a nonbiologic agent (5041 in Medicaid, 5166 in Medicare, 6291 in Optum Clinformatics). The adjusted pooled HR for VTE risk with TNF-α inhibitor versus a nonbiologic agent was 0.78 (95% confidence interval [CI] 0.60 to 1.02). The HR was lower in patients with Crohn disease (pooled HR 0.62, 95% CI 0.44 to 0.86) and younger patients (18-44 yr; pooled HR 0.55, 95% CI 0.34 to 0.87). INTERPRETATION: We did not find a statistically significant association between risk of VTE and use of TNF-α inhibitors, relative to nonbiologics, in patients with IBD overall. However, an association was evident for patients younger than 45 years and those with Crohn disease.

Treatment of early-stage human epidermal growth factor 2-positive cancers among medicare enrollees: age and race strongly associated with non-use of trastuzumab.

Adjuvant trastuzumab for human epidermal growth factor receptor-2 (HER2)-positive breast cancer is highly efficacious regardless of age. Recent data suggested that many older patients with HER2-positive disease do not receive adjuvant trastuzumab. Nevertheless, some of this 'under-treatment' may be clinically appropriate. We used Surveillance, Epidemiology and End Results (SEER)-Medicare data to identify patients aged ≥ 66 with stage ≥ Ib-III, HER2-positive breast cancer diagnosed during 2010-2011 (HER2 status available) who did not have a history of congestive heart failure. We described all systemic treatments received and sociodemographic and clinical characteristics associated with treatment patterns. Among 770 women 44.4 % did not receive trastuzumab, including 21.8 % who received endocrine therapy only, 6.3 % who received chemotherapy (±endocrine therapy) and 16.2 % who did not receive any systemic therapy. In addition to age and grade, race was strongly associated with non-use of trastuzumab (64.4 % of Non-Hispanic blacks vs. 43.6 % of whites did not receive trastuzumab, adjusted ORNon-Hispanic black vs. white = 3.14, 95 %CI = 1.38-7.17), and many patients with stage III disease did not receive trastuzumab. Further, 16.2 % of patients did not receive any systemic treatment and this occurred more frequently for black patients. Over 40 % of older patients with indication to receive adjuvant trastuzumab did not receive it and nearly 20 % of these patients did not receive any other treatment. Although treatment omission may be appropriate in some cases, we observed concerning differences in trastuzumab receipt, particularly for black women. Strategies to optimize care for older patients and to eliminate treatment disparities are urgently needed.

Switch-backs associated with generic drugs approved using product-specific determinations of therapeutic equivalence.

PURPOSE: US Food and Drug Administration approval for generic drugs relies on demonstrating pharmaceutical equivalence and bioequivalence; however, some drug products have unique attributes that necessitate product-specific approval pathways. We evaluated rates of patients' switching back to brand-name versions from generic versions of four drugs approved via such approaches. METHODS: We used data from Optum LifeSciences Research Database to identify patients using a brand-name version of a study drug (acarbose tablets, salmon calcitonin nasal spray, enoxaparin sodium injection, and venlafaxine extended release tablets) or a control drug. We followed patients to identify switching to generic versions and then followed those who switched to identify whether they switched back to brand-name versions. We calculated switch and switch-back rates and used Kaplan-Meier and log-rank tests to compare rates between study and control drugs. RESULTS: Our cohort included 201 959 eligible patients. Brand-to-generic switch rates ranged from 66 to 106 switches per 100 person-years for study drugs and 80 to 110 for control drugs. Rates of switch-back to brand-name versions ranged from 5 to 37 among study drugs and 3 to 53 among control drugs. Switch-back rates were higher for venlafaxine vs. sertraline (p < 0.01) and calcitonin vs. alendronate (p = 0.01). Switch-back rates were lower for venlafaxine vs. paroxetine (p < 0.01) and acarbose vs. nateglinide (p < 0.01). Rates were similar for acarbose vs. glimepiride (p = 0.97) and for enoxaparin vs. fondiparinux (p = 0.11). CONCLUSION: As compared to control drugs, patients were not more likely to systematically switch back from generic to brand-name versions of the four study drugs. Copyright © 2016 John Wiley & Sons, Ltd.

Trends in Use and Evidence of Adherence to Risk Evaluation and Mitigation Strategy Pregnancy Testing Requirements for Thalidomide, Lenalidomide, and Pomalidomide in the USA, 2000-2020.

INTRODUCTION: Lenalidomide, pomalidomide, and thalidomide are effective treatments for multiple myeloma but are teratogenic. To mitigate this risk, the US Food and Drug Administration (FDA) required risk evaluation and mitigation strategy (REMS) programs for these drugs, which include pregnancy testing among women of childbearing potential-twice before initiation, weekly in the first month on treatment, and every 2-4 weeks thereafter. OBJECTIVE: We evaluated dispensing trends of lenalidomide, pomalidomide, and thalidomide and assessed adherence to REMS pregnancy testing requirements among at-risk patients taking these drugs. METHODS: Using three US health insurance claims databases (Optum Clinformatics® [2004-2020], Merative Marketscan [2003-2019], and Medicaid [2000-2018]), we assessed monthly use of the drugs, patient characteristics and treatment persistence among drug initiators, and claims-based evidence for adherence to pregnancy testing requirements among initiators with child-bearing potential. RESULTS: Lenalidomide was the most prescribed agent following its approval in 2006 and through the end of the study period. A total of 48,311 lenalidomide (mean age = 59 years [standard deviation (SD) = 16]), 17,550 thalidomide (mean age = 65 years [SD = 12]), and 6560 pomalidomide initiators (mean age = 65 years [SD = 11]) were identified; 45% of initiators of each drug were women. Among initiators under follow-up on day 90, 70% were still on therapy. Initiators of childbearing potential comprised 3% (N = 1,920) of all initiators; among this cohort, 12% had evidence in claims data of two pregnancy tests before initiation, and 9% with at least 33 days of follow-up of four tests during the first month of treatment. By contrast, 52% who received a refill had claims-based evidence of a pregnancy test within 7 days of dispensing. CONCLUSION: Although most patients who initiated lenalidomide, pomalidomide, and thalidomide were not of child-bearing potential, further investigation into actual non-adherence to pregnancy testing is needed.

Heart failure risk among patients with rheumatoid arthritis starting a TNF antagonist.

BACKGROUND: While heart failure (HF) is associated with elevations in tumor necrosis factor (TNF)α, several trials of TNF antagonists showed no benefit and possibly worsening of disease in those with known severe HF. We studied the risk of new or recurrent HF among a group of patients receiving these agents to treat rheumatoid arthritis (RA). METHODS: We used data from four different US healthcare programmes. Subjects with RA receiving methotrexate were eligible to enter the study cohort if they added or switched to a TNF antagonist or another non-biological disease modifying antirheumatic drug (nbDMARD). These groups were compared in Cox regression models stratified by propensity score decile and adjusted for oral glucocorticoid dosage, prior HF hospitalisations, and the use of loop diuretics. RESULTS: We compared 8656 new users of a nbDMARD with 11 587 new users of a TNF antagonist with similar baseline covariates. The HR for the TNF antagonists compared with nbDMARD was 0.85 (95% CI 0.63 to 1.14). The HR was also not elevated in subjects with a history of HF. But, it was elevated prior to 2002 (HR 2.17, 95% CI 0.45 to 10.50, test for interaction p=0.036). Oral glucocorticoids were associated with a dose-related gradient of HF risk: compared with no use, 1≤5 mg HR 1.30 (95% CI 0.91 to 1.85), ≥5 mg HR 1.54 (95% CI 1.09 to 2.19). CONCLUSIONS: TNF antagonists were not associated with a risk of HF hospital admissions compared with nbDMARDs in this RA population.

Comparison of EHR Data-Completeness in Patients with Different Types of Medical Insurance Coverage in the United States.

Prior studies have demonstrated that misclassification of study variables due to electronic health record (EHR)-discontinuity can be mitigated by restricting EHR-based analyses to subjects with high predicted EHR-continuity based on a simple algorithm. In this study, we compared EHR continuity in populations covered by Medicare, Medicaid, or commercial insurance. Using claims-linked EHRs from a multicenter network in Massachusetts, including Medicare (MA EHR-Medicare cohort) and Medicaid (MA EHR-Medicaid cohort) claims data; and TriNetX (TriNetX cohort) claims-linked EHR data from 11 US-based healthcare organizations, we assessed (1) EHR-continuity quantified by proportion of encounters captured by EHR (capture proportion (CP)); (2) area under receiver operating curve (AUROC) of previously validated model to identify patients with high EHR-continuity (CP ≥ 0.6); (3) misclassification of 40 patient characteristics, quantified by average standardized absolute mean difference (ASAMD). Study participants were ≥ 65 years (Medicare) or ≥ 18 years (Medicaid, TriNetX) with ≥ 365 days of continuous insurance enrollment overlapping with an EHR encounter. We found that the mean CP was 0.30, 0.18, and 0.19 and AUROC of the prediction model to identify patients with high EHR-continuity was 0.92, 0.89, and 0.77 in the MA EHR-Medicare, MA EHR-Medicaid, and TriNetX cohorts, respectively. Restricting to patients with predicted EHR-continuity percentile of top 20%, 50%, and 50% in MA EHR-Medicare, MA EHR-Medicaid, and TriNetX cohorts resulted in acceptable levels of misclassification (ASAMD < 0.1). Using a prediction model to identify cohorts with high EHR-continuity can improve validity, but cutoffs to achieve this goal vary by population.

Patient Characteristics Associated With Being Offered or Choosing Telephone vs Video Virtual Visits Among Medicare Beneficiaries.

Importance: After the rapid expansion of telemedicine during the COVID-19 pandemic, there is debate about the role and reimbursement of telephone vs video visits. Missing is an understanding of what type of virtual visits clinicians may offer or patients may choose when given the option. Objective: To evaluate characteristics of Medicare beneficiaries associated with practices and clinicians offering telephone visits only and patients receiving telephone visits only, when both telephone and video were available. Design, Setting, and Participants: This survey study used 2019-2020 nationally representative Medicare Current Beneficiary Survey data. Participants included community-dwelling Medicare beneficiaries with a usual source of medical care who attended a practice offering telemedicine. Data were analyzed from May 3 to August 23, 2022. Main Outcomes and Measures: Multivariable regression analysis was used to identify patient sociodemographic (age, sex, race, ethnicity, educational level, income, English proficiency, housing type, and number living at home), clinical (dementia, mental illness, self-rated health, hearing impairment, and vision impairment), and technology (technology access and prior use of video visits) factors associated with respondents' report of (1) practices offering telephone virtual visits only, (2) being offered telephone visits only when both video and telephone visits were available, and (3) receiving telephone visits only when both video and telephone visits were offered. Results: Of 4691 respondents (representing 27 887 642 Medicare beneficiaries; mean [SD] age, 71.3[8.1] years; 55.0% female) reporting that their practice offered telemedicine, 1234 (23.3% weighted) reported that their practices offered telephone virtual visits only; factors associated with being in a practice offering telephone only included older age (adjusted odds ratio [aOR], 1.62 [95% CI, 1.10-2.39] for those aged ≥85 years vs 18-64 years), male sex (aOR, 1.36 [95% CI, 1.12-1.64]), Hispanic ethnicity (aOR, 1.41 [95% CI, 1.03-1.95]), lower income (aOR, 1.89 [95% CI, 1.43-2.49] for those with income ≤100% vs >200% of the federal poverty level), poor self-rated health (aOR, 1.25 [95% CI, 1.01-1.56]), and less technology access (aOR, 2.05 [95% CI, 1.61-2.60] for those with low vs high access). Of the 1593 patients in practices offering both video and telephone visits, 297 (16.7% weighted) were themselves offered telephone visits only; factors associated with being offered telephone only included Hispanic ethnicity (aOR, 1.96 [95% CI, 1.13-3.41]), limited English proficiency (aOR, 3.05 [95% CI, 1.28-7.31]), and less technology access (aOR, 1.68 [95% CI, 1.00-2.81] for those with low vs high access). Finally, of the 711 respondents who were themselves offered both video and telephone visits, 304 (43.1% weighted) had a telephone visit; factors associated with receiving telephone visits only were older age (aOR, 2.68 [95% CI, 1.21-5.92] for those aged 75-84 years vs 18-64 years) and less technology access (aOR, 2.65 [95% CI, 1.12-6.25] for those with moderate vs high access]). Among those who used video calls in other settings and were offered a choice, 122 (28.5%, weighted) chose telephone visits. Conclusions and Relevance: In this survey study of Medicare beneficiaries, respondents often reported being offered or choosing telephone visits even when video visits were available. Study findings suggest that policy makers and clinical leaders should support the use of telephone visits to the extent that telephone is appropriate, while addressing both practice-level and patient-level barriers to video visits.

Confronting "confounding by health system use" in Medicare Part D: comparative effectiveness of propensity score approaches to confounding adjustment.

PURPOSE: Under Medicare Part D, patient characteristics influence plan choice, which in turn influences Part D coverage gap entry. We compared predefined propensity score (PS) and high-dimensional propensity score (hdPS) approaches to address such "confounding by health system use" in assessing whether coverage gap entry is associated with cardiovascular events or death. METHODS: We followed 243,079 Medicare patients aged 65+ years with linked prescription, medical, and plan-specific data in 2005-2007. Patients reached the coverage gap and were followed until an event or year's end. Exposed patients were responsible for drug costs in the gap; unexposed patients (patients with non-Part D drug insurance and Part D patients receiving a low-income subsidy) received financial assistance. Exposed patients were 1:1 PS-matched or hdPS-matched to unexposed patients. The PS model included 52 predefined covariates; the hdPS model added 400 empirically identified covariates. Hazard ratios for death and any of five cardiovascular outcomes were compared. In sensitivity analyses, we explored residual confounding using only low-income subsidy patients in the unexposed group. RESULTS: In unadjusted analyses, exposed patients had no greater hazard of death (HR = 1.00; 95%CI, 0.84-1.20) or other outcomes. PS-matched (HR = 1.29; 0.99-1.66) and hdPS-matched (HR = 1.11; 0.86-1.42) analyses showed elevated but non-significant hazards of death. In sensitivity analyses, the PS analysis showed a protective effect (HR = 0.78; 0.61-0.98), whereas the hdPS analysis (HR = 1.06; 0.82-1.37) confirmed the main hdPS findings. CONCLUSION: Although the PS-matched analysis suggested elevated but non-significant hazards of death among patients with no financial assistance during the gap, the hdPS analysis produced lower estimates that were stable across sensitivity analyses.

An algorithm to predict data completeness in oncology electronic medical records for comparative effectiveness research.

INTRODUCTION: Electronic health record (EHR) discontinuity (missing out-of-network encounters) can lead to information bias. We sought to construct an algorithm that identifies high EHR-continuity among oncology patients. METHODS: Using a linked Medicare-EHR database and regression, we sought to 1) measure how often Medicare claims for outpatient encounters were substantiated by visits recorded in the EHR, and 2) predict continuity ratio, defined as the yearly proportion of outpatient encounters reported to Medicare that were captured by EHR data. The prediction model...s performance was evaluated with the coefficient of determination and Spearman...s correlation. We quantified variable misclassification by decile of continuity ratio using standardized difference and sensitivity. RESULTS: A total of 79,678 subjects met all eligibility criteria. Predicted and observed continuity was highly correlated (σSpearman=0.86). On average across all variables measured, MSD was reduced by a factor of 1/7th and sensitivity was improved 35-fold comparing subjects in the highest vs. lowest decile of CR. CONCLUSION: In the oncology population, restricting EHR-based study cohorts to subjects with high continuity may reduce misclassification without greatly impacting representativeness. Further work is needed to elucidate the best manner of implementing continuity prediction rules in cohort studies.

Advancing an Algorithm for the Identification of Patients with High Data-Continuity in Electronic Health Records.

Background: Identifying high data-continuity patients in an electronic health record (EHR) system may facilitate selecting cohorts with a lower degree of variable misclassification and promote study validity. We updated a previously developed algorithm for identifying patients with high EHR data-completeness by adding demographic and health utilization factors to improve adaptability to networks serving patients of diverse backgrounds. We also expanded the algorithm to accommodate data in the ICD-10 era. Methods: We used Medicare claims linked with EHR data to identify individuals aged ≥65 years. EHR-continuity was defined as the proportion of encounters captured in EHR data relative to claims. We compared the model with additional demographic factors and their interaction terms with other predictors with the original algorithm and assessed the performance by area under the ROC curve (AUC) and net reclassification index (NRI). Results: The study cohort consisted of 264,099 subjects. The updated prediction model had an AUC of 0.93 in the validation set. Compared to the previous model, the new model had an NRI of 37.4% (p<0.001) for EHR-continuity classification. Interaction terms between demographic variables and other predictors did not improve the performance. Patients within the top 20% of predicted EHR-continuity had four times less misclassification of key variables compared to the remaining population. Conclusion: Adding demographic and healthcare utilization variables significantly improved the model performance. Patients with high predicted EHR-continuity had less misclassification of study variables compared to the remaining population in both ICD-9 and 10 eras.

Downstream Mammary and Extramammary Cascade Services and Spending Following Screening Breast Magnetic Resonance Imaging vs Mammography Among Commercially Insured Women.

Importance: Increasing use of screening breast magnetic resonance imaging (MRI), including among women at low or average risk of breast cancer, raises concerns about resulting mammary and extramammary cascades (downstream services and new diagnoses) of uncertain value. Objective: To estimate rates of cascade events (ie, laboratory tests, imaging tests, procedures, visits, hospitalizations, and new diagnoses) and associated spending following screening breast MRI vs mammography among commercially insured US women. Design, Setting, and Participants: This cohort study used 2016 to 2018 data from the MarketScan research database (IBM Corporation), which includes claims and administrative data from large US employers and commercial payers. Participants included commercially insured women aged 40 to 64 years without prior breast cancer who received an index bilateral screening breast MRI or mammogram between January 1, 2017, and June 30, 2018. We used propensity scores based on sociodemographic, clinical, and utilization variables to match MRI recipients to mammogram recipients in each month of index service use. Data were analyzed from October 8, 2020, to October 28, 2021. Exposures: Breast MRI vs mammography. Main Outcomes and Measures: Mammary and extramammary cascade event rates and associated total and patient out-of-pocket spending in the 6 months following the index test. Results: In this study, 9208 women receiving breast MRI were matched with 9208 women receiving mammography (mean [SD] age, 51.4 [6.7] years). Compared with mammogram recipients, breast MRI recipients had 39.0 additional mammary cascade events per 100 women (95% CI, 33.7-44.2), including 5.0 additional imaging tests (95% CI, 3.8-6.2), 17.3 additional procedures (95% CI, 15.5-19.0), 13.0 additional visits (95% CI, 9.4-17.2), 0.34 additional hospitalizations (95% CI, 0.18-0.50), and 3.0 additional new diagnoses (95% CI, 2.5-3.6). For extramammary cascades, breast MRI recipients had 19.6 additional events per 100 women (95% CI, 8.6-30.7) including 15.8 additional visits (95% CI, 10.2-21.4) and no statistically significant differences in other events. Breast MRI recipients had higher total spending for mammary events ($564 more per woman; 95% CI, $532-$596), extramammary events ($42 more per woman; 95% CI, $16-$69), and overall ($1404 more per woman; 95% CI, $1172-$1636). They also had higher overall out-of-pocket spending ($31 more per woman; 95% CI, $6-$55). Conclusions and Relevance: In this cohort study of commercially insured women, breast MRI was associated with more mammary and extramammary cascade events and spending relative to mammography. These findings can inform cost-benefit assessments and coverage policies to ensure breast MRI is reserved for patients for whom benefits outweigh harms.

Development of a Medicare Claims-Based Model to Predict Persistent High-Dose Opioid Use After Total Knee Replacement.

OBJECTIVE: To develop a claims-based model to predict persistent high-dose opioid use among patients undergoing total knee replacement (TKR). METHODS: Using Medicare claims (2010-2014), we identified patients ages ≥65 years who underwent TKR with no history of high-dose opioid use (mean >25 morphine milligram equivalents [MMEs]/day) in the year prior to TKR. We used group-based trajectory modeling to identify distinct opioid use patterns. The primary outcome was persistent high-dose opioid use in the year after TKR. We split the data into training (2010-2013) and test (2014) sets and used logistic regression with least absolute shrinkage and selection operator regularization, utilizing a total of 83 preoperative patient characteristics as candidate predictors. A reduced model with 10 prespecified variables, which included demographic characteristics, opioid use, and medication history was also considered. RESULTS: The final study cohort included 142,089 patients who underwent TKR. The group-based trajectory model identified 4 distinct trajectories of opioid use (group 1: short-term, low-dose; group 2: moderate-duration, low-dose; group 3: moderate-duration, high-dose; and group 4: persistent high-dose). The model predicting persistent high-dose opioid use achieved high discrimination (receiver operating characteristic area under the curve [AUC] 0.85 [95% confidence interval (95% CI) 0.84-0.86]) in the test set. The reduced model with 10 predictors performed equally well (AUC 0.84 [95% CI 0.84-0.85]). CONCLUSION: In this cohort of older patients, 10.6% became persistent high-dose (mean 22.4 MME/day) opioid users after TKR. Our model with 10 readily available clinical factors may help identify patients at high risk of future adverse outcomes from persistent opioid use after TKR.

Study design for a comprehensive assessment of biologic safety using multiple healthcare data systems.

BACKGROUND: Although biologic treatments have excellent efficacy for many autoimmune diseases, safety concerns persist. Understanding the absolute and comparative risks of adverse events in patient and disease subpopulations is critical for optimal prescribing of biologics. PURPOSE: The Safety Assessment of Biologic Therapy collaborative was federally funded to provide robust estimates of rates and relative risks of adverse events among biologics users using data from national Medicaid and Medicare plus Medicaid dual-eligible programs, Tennessee Medicaid, Kaiser Permanente, and state pharmaceutical assistance programs supplementing New Jersey and Pennsylvania Medicare programs. This report describes the organizational structure of the collaborative and the study population and methods. METHODS: This retrospective cohort study (1998-2007) examined risks of seven classes of adverse events in relation to biologic treatments prescribed for seven autoimmune diseases. Propensity scores were used to control for confounding and enabled pooling of individual-level data across data systems while concealing personal health information. Cox proportional hazard modeling was used to analyze study hypotheses. RESULTS: The cohort was composed of 159,000 subjects with rheumatic diseases, 33,000 with psoriasis, and 46,000 with inflammatory bowel disease. This report summarizes demographic characteristics and drug exposures. Separate reports will provide outcome definitions and estimated hazard ratios for adverse events. CONCLUSION: This comprehensive research will improve understanding of the safety of these treatments. The methods described may be useful to others planning similar evaluations.

Non-Visit-Based and Non-Infection-Related Antibiotic Use in the US: A Cohort Study of Privately Insured Patients During 2016-2018.

BACKGROUND: Ambulatory antibiotic prescriptions without a clinic visit or without documentation of infection could represent overuse and contribute to adverse outcomes. We aim to describe US ambulatory antibiotic prescribing, including those without an associated visit or infection diagnosis. METHODS: We conducted an observational cohort study using data of all patients receiving antibacterial, antibiotic prescriptions from 04/01/2016 to 06/30/2018 in a large US private health insurance plan. We identified outpatient antibiotic prescriptions as (1) associated with a clinician visit and an infection-related diagnosis; (2) associated with a clinician visit but no infection-related diagnosis; or (3) not associated with an in-person clinician visit in the 7 days before the prescription (non-visit-based). We then assessed whether non-visit-based antibiotic prescriptions (NVBAPs) differed from visit-based antibiotics by patient, clinician, or antibiotic characteristics using multivariable models. RESULTS: The cohort included 8.6M enrollees who filled 22.3M antibiotic prescriptions. NVBAP accounted for 31% (6.9M) of fills, and non-infection-related prescribing accounted for 22% (4.9M). NVBAP rates were lower for children than for adults (0-17 years old, 16%; 18-64 years old, 33%; >65 years old, 34%). Among most commonly prescribed antibiotic classes, NVBAP was highest for penicillins (36%) and lowest for cephalosporins (25%) and macrolides (25%). Specialist physicians had the highest rate of NVBAP (38%), followed by internists (28%), family medicine (20%), and pediatricians (10%). In multivariable models, NVBAP was associated with increasing age, and NVBAP was less likely for patients in the South, those with more baseline clinical visits, or those with chronic lung disease. CONCLUSIONS: Over half of ambulatory antibiotic use was either non-visit-based or non-infection-related. Particularly given health care changes due to the coronavirus disease 2019 pandemic, efforts to improve antibiotic prescribing must account for non-visit-based and non-infection-related prescribing.