Comparative Effectiveness of Aspirin Dosing in Cardiovascular Disease.

BACKGROUND: The appropriate dose of aspirin to lower the risk of death, myocardial infarction, and stroke and to minimize major bleeding in patients with established atherosclerotic cardiovascular disease is a subject of controversy. METHODS: Using an open-label, pragmatic design, we randomly assigned patients with established atherosclerotic cardiovascular disease to a strategy of 81 mg or 325 mg of aspirin per day. The primary effectiveness outcome was a composite of death from any cause, hospitalization for myocardial infarction, or hospitalization for stroke, assessed in a time-to-event analysis. The primary safety outcome was hospitalization for major bleeding, also assessed in a time-to-event analysis. RESULTS: A total of 15,076 patients were followed for a median of 26.2 months (interquartile range [IQR], 19.0 to 34.9). Before randomization, 13,537 (96.0% of those with available information on previous aspirin use) were already taking aspirin, and 85.3% of these patients were previously taking 81 mg of daily aspirin. Death, hospitalization for myocardial infarction, or hospitalization for stroke occurred in 590 patients (estimated percentage, 7.28%) in the 81-mg group and 569 patients (estimated percentage, 7.51%) in the 325-mg group (hazard ratio, 1.02; 95% confidence interval [CI], 0.91 to 1.14). Hospitalization for major bleeding occurred in 53 patients (estimated percentage, 0.63%) in the 81-mg group and 44 patients (estimated percentage, 0.60%) in the 325-mg group (hazard ratio, 1.18; 95% CI, 0.79 to 1.77). Patients assigned to 325 mg had a higher incidence of dose switching than those assigned to 81 mg (41.6% vs. 7.1%) and fewer median days of exposure to the assigned dose (434 days [IQR, 139 to 737] vs. 650 days [IQR, 415 to 922]). CONCLUSIONS: In this pragmatic trial involving patients with established cardiovascular disease, there was substantial dose switching to 81 mg of daily aspirin and no significant differences in cardiovascular events or major bleeding between patients assigned to 81 mg and those assigned to 325 mg of aspirin daily. (Funded by the Patient-Centered Outcomes Research Institute; ADAPTABLE ClinicalTrials.gov number, NCT02697916.).

Incidence, Prevalence, and Racial and Ethnic Distribution of Inflammatory Bowel Disease in the United States.

BACKGROUND & AIMS: We sought to estimate the incidence, prevalence, and racial-ethnic distribution of physician-diagnosed inflammatory bowel disease (IBD) in the United States. METHODS: The study used 4 administrative claims data sets: a 20% random sample of national fee-for-service Medicare data (2007 to 2017); Medicaid data from Florida, New York, Pennsylvania, Ohio, and California (1999 to 2012); and commercial health insurance data from Anthem beneficiaries (2006 to 2018) and Optum's deidentified Clinformatics Data Mart (2000 to 2017). We used validated combinations of medical diagnoses, diagnostic procedures, and prescription medications to identify incident and prevalent diagnoses. We computed pooled age-, sex-, and race/ethnicity-specific insurance-weighted estimates and pooled estimates standardized to 2018 United States Census estimates with 95% confidence intervals (CIs). RESULTS: The age- and sex-standardized incidence of IBD per 100,000 person-years was 10.9 (95% CI, 10.6-11.2). The incidence of IBD peaked in the third decade of life, decreased to a relatively stable level across the fourth to eighth decades, and declined further. The age-, sex- and insurance-standardized prevalence of IBD was 721 per 100,000 population (95% CI, 717-726). Extrapolated to the 2020 United States Census, an estimated 2.39 million Americans are diagnosed with IBD. The prevalence of IBD per 100,000 population was 812 (95% CI, 802-823) in White, 504 (95% CI, 482-526) in Black, 403 (95% CI, 373-433) in Asian, and 458 (95% CI, 440-476) in Hispanic Americans. CONCLUSIONS: IBD is diagnosed in >0.7% of Americans. The incidence peaks in early adulthood and then plateaus at a lower rate. The disease is less commonly diagnosed in Black, Asian, and Hispanic Americans.

Assessing Real-World Data From Electronic Health Records for Health Technology Assessment: The SUITABILITY Checklist: A Good Practices Report of an ISPOR Task Force.

This ISPOR Good Practices report provides a framework for assessing the suitability of electronic health records data for use in health technology assessments (HTAs). Although electronic health record (EHR) data can fill evidence gaps and improve decisions, several important limitations can affect its validity and relevance. The ISPOR framework includes 2 components: data delineation and data fitness for purpose. Data delineation provides a complete understanding of the data and an assessment of its trustworthiness by describing (1) data characteristics; (2) data provenance; and (3) data governance. Fitness for purpose comprises (1) data reliability items, ie, how accurate and complete the estimates are for answering the question at hand and (2) data relevance items, which assess how well the data are suited to answer the particular question from a decision-making perspective. The report includes a checklist specific to EHR data reporting: the ISPOR SUITABILITY Checklist. It also provides recommendations for HTA agencies and policy makers to improve the use of EHR-derived data over time. The report concludes with a discussion of limitations and future directions in the field, including the potential impact from the substantial and rapid advances in the diffusion and capabilities of large language models and generative artificial intelligence. The report's immediate audiences are HTA evidence developers and users. We anticipate that it will also be useful to other stakeholders, particularly regulators and manufacturers, in the future.

Real-World Evidence Comparing Vedolizumab and Ustekinumab in Antitumor Necrosis Factor-Experienced Patients With Crohn's Disease.

INTRODUCTION: Many patients with Crohn's disease (CD) lose response or become intolerant to antitumor necrosis factor (TNF) therapy and subsequently switch out of class. We compared the effectiveness and safety of ustekinumab to vedolizumab in a large, geographically diverse US population of TNF-experienced patients with CD. METHODS: We conducted a retrospective cohort study using longitudinal claims data from a large US insurer (Anthem, Inc.). We identified patients with CD initiating vedolizumab or ustekinumab with anti-TNF treatment in the prior 6 months. Our primary outcome was treatment persistence for >52 weeks. Secondary outcomes included (i) all-cause hospitalization, (ii) hospitalization for CD with surgery, (iii) hospitalization for CD without surgery, and (iv) hospitalization for infection. Propensity score fine stratification was used to control for demographic and baseline clinical characteristics and prior treatments. RESULTS: Among 885 new users of ustekinumab and 490 new users of vedolizumab, we observed no difference in treatment persistence (adjusted risk ratio 1.09 [95% confidence interval 0.95-1.25]). Ustekinumab was associated with a lower rate of all-cause hospitalization (adjusted hazard ratio 0.73 [0.59-0.91]), nonsurgical CD hospitalization (adjusted hazard ratio 0.58 [0.40-0.83]), and hospitalization for infection (adjusted hazard ratio 0.56 [0.34-0.92]). DISCUSSION: This real-world comparative effectiveness study of anti-TNF-experienced patients with CD initiating vedolizumab or ustekinumab showed similar treatment persistence rates beyond 52 weeks, although secondary outcomes such as all-cause hospitalizations, nonsurgical CD hospitalizations, and hospitalizations for infection favored ustekinumab initiation. We, therefore, advocate for individualized decision making in this medically refractory population, considering patient preference and other factors such as cost and route of administration.

Pragmatic guidance for embedding pragmatic clinical trials in health plans: Large simple trials aren't so simple.

BACKGROUND: There are unique opportunities related to the design and conduct of pragmatic trials embedded in health insurance plans, which have longitudinal data on member/patient demographics, dates of coverage, and reimbursed medical care, including prescription drug dispensings, vaccine administrations, behavioral healthcare encounters, and some laboratory results. Such trials can be large and efficient, using these data to identify trial-eligible patients and to ascertain outcomes. METHODS: We use our experience primarily with the National Institutes of Health Pragmatic Trials Collaboratory Distributed Research Network, which comprises health plans that participate in the US Food & Drug Administration's Sentinel System, to describe lessons learned from the conduct and planning of embedded pragmatic trials. RESULTS: Information is available for research on more than 75 million people with commercial or Medicare Advantage health plans. We describe three studies that have used or plan to use the Network, as well as a single health plan study, from which we glean our lessons learned. CONCLUSIONS: Studies that are conducted in health plans provide much-needed evidence to drive clinically meaningful changes in care. However, there are many unique aspects of these trials that must be considered in the planning, implementation, and analytic phases. The type of trial best suited for studies embedded in health plans will be those that require large sample sizes, simple interventions that could be disseminated through health plans, and where data available to the health plan can be leveraged. These trials hold potential for substantial long-term impact on our ability to generate evidence to improve care and population health.

Impact of the COVID-19 Pandemic on the Management of Juvenile Idiopathic Arthritis: Analysis of United States Commercial Insurance Data.

BACKGROUND/OBJECTIVE: Given limited information on health care and treatment utilization for juvenile idiopathic arthritis (JIA) during the pandemic, we studied JIA-related health care and treatment utilization in a commercially insured retrospective US cohort. METHODS: We studied rates of outpatient visits, new disease-modifying antirheumatic drug (DMARD) initiations, intra-articular glucocorticoid injections (iaGC), dispensed oral glucocorticoids and opioids, DMARD adherence, and DMARD discontinuation by quarter in March 2018-February 2021 (Q1 started in March). Incident rate ratios (IRR, pandemic vs prepandemic) with 95% confidence intervals (CIs) were estimated using multivariable Poisson or Quasi-Poisson models stratified by diagnosis recency (incident JIA, <12 months ago; prevalent JIA, ≥12 months ago). RESULTS: Among 1294 children diagnosed with JIA, total and in-person outpatient visits for JIA declined during the pandemic (IRR, 0.88-0.90), most markedly in Q1 2020. Telemedicine visits, while higher during the pandemic, declined from 21% (Q1) to 13% (Q4) in 2020 to 2021. During the pandemic, children with prevalent JIA, but not incident JIA, had lower usage of iaGC (IRR, 0.60; 95% CI, 0.34-1.07), oral glucocorticoids (IRR, 0.47; 95% CI, 0.33-0.67), and opioids (IRR, 0.44; 95% CI, 0.26-0.75). Adherence to and discontinuation of DMARDs was similar before and during the pandemic. CONCLUSIONS: In the first year of the pandemic, visits for JIA dropped by 10% to 12% in commercially insured children in the United States, declines partly mitigated by use of telemedicine. Pandemic-related declines in intra-articular glucocorticoids, oral glucocorticoids, and opioids were observed for children with prevalent, but not incident, JIA. These changes may have important implications for disease control and quality of life.

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.

Utility of fertility procedures and prenatal tests to estimate gestational age for live-births and stillbirths in electronic health plan databases.

PURPOSE: Current algorithms to evaluate gestational age (GA) during pregnancy rely on hospital coding at delivery and are not applicable to non-live births. We developed an algorithm using fertility procedures and fertility tests, without relying on delivery coding, to develop a novel GA algorithm in live-births and stillbirths. METHODS: Three pregnancy cohorts were identified from 16 health-plans in the Sentinel System: 1) hospital admissions for live-birth, 2) hospital admissions for stillbirth, and 3) medical chart-confirmed stillbirths. Fertility procedures and prenatal tests, recommended within specific GA windows were evaluated for inclusion in our GA algorithm. Our GA algorithm was developed against a validated delivery-based GA algorithm in live-births, implemented within a sample of chart-confirmed stillbirths, and compared to national estimates of GA at stillbirth. RESULTS: Our algorithm, including fertility procedures and 11 prenatal tests, assigned a GA at delivery to 97.9% of live-births and 92.6% of stillbirths. For live-births (n = 4 701 207), it estimated GA within 2 weeks of a reference delivery-based GA algorithm in 82.5% of pregnancies, with a mean difference of 3.7 days. In chart-confirmed stillbirths (n = 49), it estimated GA within 2 weeks of the clinically recorded GA at delivery for 80% of pregnancies, with a mean difference of 11.1 days. Implementation of the algorithm in a cohort of stillbirths (n = 40 484) had an increased percentage of deliveries after 36 weeks compared to national estimates. CONCLUSIONS: In a population of primarily commercially-insured pregnant women, fertility procedures and prenatal tests can estimate GA with sufficient sensitivity and accuracy for utility in pregnancy studies.

Digoxin use is associated with pancreatic cancer risk but does not affect survival.

PURPOSE: Digoxin affects several cellular pathways involved in tumorigenesis. We sought to determine the association between digoxin use and pancreatic cancer risk and survival. METHODS: A nested case-control study using The Health Improvement Network (THIN), a population-representative database from the United Kingdom (UK). Cases included all individuals with incident diagnosis of pancreatic cancer. Each case was matched to up to four controls using incidence density sampling based on age, sex, practice site, calendar time, and duration of follow-up. Exposure of interest was digoxin therapy before cancer diagnosis. Odds ratios (ORs) and 95% confidence intervals (CIs) for the association between digoxin use and pancreatic cancer risk were estimated using conditional logistic regression. We further conducted a retrospective cohort study among pancreatic cancer cases using Cox regression model in order to evaluate the association between digoxin use and overall survival. RESULTS: We identified 4,113 cases with incident pancreatic cancer and 16,072 matched controls. The adjusted OR for diagnosis of pancreatic cancer among active digoxin users was 1.41 (95% CI 1.16-1.72). The risk did not change among active users with duration of therapy of more than 1 year (adjusted OR of 1.39, 95% CI 1.11-1.76). Digoxin was not associated with change in overall survival with an adjusted hazard ratio of 0.97 (95% CI 0.81-1.18). CONCLUSIONS: Digoxin use was associated with modestly increased pancreatic cancer risk but did not affect overall survival.

Validation of an ICD-10-based algorithm to identify stillbirth in the Sentinel System.

PURPOSE: To develop and validate an International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify cases of stillbirth using electronic healthcare data. METHODS: We conducted a retrospective study using claims data from three Data Partners (healthcare systems and insurers) in the Sentinel Distributed Database. Algorithms were developed using ICD-10-CM diagnosis codes to identify potential stillbirths among females aged 12-55 years between July 2016 and June 2018. A random sample of medical charts (N = 169) was identified for chart abstraction and adjudication. Two physician adjudicators reviewed potential cases to determine whether a stillbirth event was definite/probable, the date of the event, and the gestational age at delivery. Positive predictive values (PPVs) were calculated for the algorithms. Among confirmed cases, agreement between the claims data and medical charts was determined for the outcome date and gestational age at stillbirth. RESULTS: Of the 110 potential cases identified, adjudicators determined that 54 were stillbirth events. Criteria for the algorithm with the highest PPV (82.5%; 95% CI, 70.9%-91.0%) included the presence of a diagnosis code indicating gestational age ≥20 weeks and occurrence of either >1 stillbirth-related code or no other pregnancy outcome code (i.e., livebirth, spontaneous abortion, induced abortion) recorded on the index date. We found ≥90% agreement within 7 days between the claims data and medical charts for both the outcome date and gestational age at stillbirth. CONCLUSIONS: Our results suggest that electronic healthcare data may be useful for signal detection of medical product exposures potentially associated with stillbirth.

Identifying prescribing cascades in Alzheimer's disease and related dementias: The calcium channel blocker-diuretic prescribing cascade.

PURPOSE: Prescribing cascades occur when a physician prescribes a new drug to address the side-effect of another drug. Persons with Alzheimer's disease and related dementias (ADRD) are at increased risk for prescribing cascades. Our objective was to develop an approach to estimating the proportion of calcium channel blocker-diuretic (CCB-diuretic) prescribing cascades among persons with ADRD in two U.S. health plans. METHODS: We identified patients aged ≥50 on January 1, 2017, dispensed a drug to treat ADRD in the 365-days prior to/on cohort entry date. Patients had medical/pharmacy coverage for 1 year before and through cohort entry. We excluded individuals with an institutional stay encounter in the 45 days prior to cohort entry and censored patients based on: disenrollment from coverage, death, or end of data. We identified incident and prevalent CCB use in the 183-days following cohort entry, and identified subsequent incident diuretic use among incident and prevalent CCB-users within 365-days from cohort entry. RESULTS: There were 121 538 eligible patients. Approximately 62% were female, with a mean age of 79.5 (SD ±8.6). Overall 2.1% of the cohort experienced a prevalent CCB-diuretic prescribing cascade with 1586 incident diuretic-users among 36 462 prevalent CCB-users (4.3%, 95% CI 4.1-4.6%]); and there were161 incident diuretic-users among 3304 incident CCB-users (4.9%, 95% CI 4.2-5.7%) (incident CCB-diuretic cascade). CONCLUSIONS: We describe an approach to identify prescribing cascades in persons with ADRD, which can be used to assess the proportion of prescribing cascades in large cohorts. We determined the proportion of CCB-diuretic prescribing cascades was low.

Characterization of bariatric surgery and outcomes using administrative claims data in the research network of a nationwide commercial health plan.

BACKGROUND: The supplementation of electronic health records data with administrative claims data may be used to capture outcome events more comprehensively in longitudinal observational studies. This study investigated the utility of administrative claims data to identify outcomes across health systems using a comparative effectiveness study of different types of bariatric surgery as a model. METHODS: This observational cohort study identified patients who had bariatric surgery between 2007 and 2015 within the HealthCore Anthem Research Network (HCARN) database in the National Patient-Centered Clinical Research Network (PCORnet) common data model. Patients whose procedures were performed in a member facility affiliated with PCORnet Clinical Research Networks (CRNs) were selected. The outcomes included a 30-day composite adverse event (including venous thromboembolism, percutaneous/operative intervention, failure to discharge and death), and all-cause hospitalization, abdominal operation or intervention, and in-hospital death up to 5 years after the procedure. Outcomes were classified as occurring within or outside PCORnet CRN health systems using facility identifiers. RESULTS: We identified 4899 patients who had bariatric surgery in one of the PCORnet CRN health systems. For 30-day composite adverse event, the inclusion of HCARN multi-site claims data marginally increased the incidence rate based only on HCARN single-site claims data for PCORnet CRNs from 3.9 to 4.2%. During the 5-year follow-up period, 56.8% of all-cause hospitalizations, 31.2% abdominal operations or interventions, and 32.3% of in-hospital deaths occurred outside PCORnet CRNs. Incidence rates (events per 100 patient-years) were significantly lower when based on claims from a single PCORnet CRN only compared to using claims from all health systems in the HCARN: all-cause hospitalization, 11.0 (95% Confidence Internal [CI]: 10.4, 11.6) to 25.3 (95% CI: 24.4, 26.3); abdominal operations or interventions, 4.2 (95% CI: 3.9, 4.6) to 6.1 (95% CI: 5.7, 6.6); in-hospital death, 0.2 (95% CI: 0.11, 0.27) to 0.3 (95% CI: 0.19, 0.38). CONCLUSIONS: Short-term inclusion of multi-site claims data only marginally increased the incidence rate computed from single-site claims data alone. Longer-term follow up captured a notable number of events outside of PCORnet CRNs. The findings suggest that supplementing claims data improves the outcome ascertainment in longitudinal observational comparative effectiveness studies.

Underuse of oral anticoagulants in privately insured patients with atrial fibrillation: A population being targeted by the IMplementation of a randomized controlled trial to imProve treatment with oral AntiCoagulanTs in patients with Atrial Fibrillation (IMPACT-AFib).

BACKGROUND: Many studies showing underuse of oral anticoagulants (OACs) in patients with atrial fibrillation (AF) predated the advent of the non-vitamin K antagonist OACs. We retrospectively examined use of OACs in a large commercially insured population. METHODS: Administrative claims data from 4 research partners participating in FDA-Catalyst, a program of the Sentinel Initiative, were queried in September 2017. Patients were included if they were ≥30 years old with ≥365 days of medical/pharmacy coverage, and had ≥2 diagnosis codes for AF, a CHA2DS2-VASc score ≥2, absence of contraindications to OAC use, and no evidence of OAC use in the 365 days before the index AF diagnosis. The main outcome measures of the current analysis were rates of OAC use in the prior 12 months of cohort identification and factors associated with non-use. RESULTS: A total of 197,806 AF patients met the eligibility criteria prior to assessment of OAC treatment. Of these, 179,580 (91%) patients were ≥65 years old and 73,286 (37%) patients were ≥80 years old. Half of the patients (98,903) were randomized to the early intervention arm in the IMPACT-AFib trial and constitute the cohort for this analysis. Of these, 32,295 (33%) had no evidence of OAC use in the prior 12 months. Compared with patients with evidence of OAC use in the prior 12 months, patients without OAC use were more likely to be ≥80 years old, women, and have a history of anemia (51% vs 47%) and less likely to have diabetes (41% vs 44%), history of stroke or TIA (15% vs 19%), and history of heart failure (39% vs 48%). CONCLUSIONS: Despite a high risk of stroke, one-third of privately insured patients with AF and no obvious contraindications to an OAC were not treated with an OAC. There is an unmet need for evidence-based interventions that could lead to greater use of OACs in patients with AF at risk for stroke.

Linking electronic health data in pharmacoepidemiology: Appropriateness and feasibility.

PURPOSE: To provide guidance on data linkage appropriateness and feasibility to plan purposeful and sustainable new linkages that advance pharmacoepidemiology and healthcare research. Planning a new data linkage requires careful evaluation to weigh the resources required with the potential overall benefits. METHODS: In response to an International Society for Pharmacoepidemiology (ISPE) call for manuscripts, a working group comprised of members from academic, industry, and government determined priority content areas; appropriateness and feasibility of data linkage was selected. Within this topic, scientific and operational considerations were determined, reviewed, and formulated into key areas, and translated into 12 consensus recommendations. RESULTS: Guidance for feasibility assessment was categorized into five key areas: (1) research objectives and justification; (2) data quality and completeness; (3) the linkage process; (4) data ownership and governance; and (5) overall value added by linkage. Within these key areas, recommendations to consider prior to initiation were developed to evaluate suitability of the linkage to meet research objectives, assess source data completeness and population coverage, and ensure well-defined data governance standards and protections. When creating novel linked datasets, researchers must assess the feasibility of both scientific (data quality and linkage methods) and operational (access, data use and transfer, governance, and cost) aspects. CONCLUSIONS: The data linkage feasibility assessment considerations outlined can be used as a guide when designing sustainable linked data resources to generate actionable evidence in healthcare research. These recommendations were constructed for wide applicability and can be adapted depending on the geographic, structural, and data components of the linkage.

Capture of biologic and biosimilar dispensings in a consortium of U.S.-based claims databases: Utilization of national drug codes and Healthcare Common Procedure Coding System modifiers in medical claims.

PURPOSE: To assess the capture of biologics (originator and biosimilar) in the Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) Distributed Research Network (DRN), with a focus on medical claim National Drug Code (NDC), a new data field, and Healthcare Common Procedure Coding System (HCPCS) modifier. METHODS: We conducted a repeated cross-sectional study among patients with medical and pharmacy benefits enrolled in insurance plans participating in the BBCIC DRN between 1 January 2013 and 30 September 2017. We calculated the proportion of medical claims with ≥1 NDC and identified select biologics using four different approaches: (a) specific HCPCS alone, (b) specific HCPCS and NDC, (c) non-specific HCPCS with NDC, and (d) HCPCS with modifiers (applicable to biosimilars). Numbers of dispensings were calculated for each biologic by approach and select patient and claim characteristics. RESULTS: More than 1.5 million eligible participants contributed approximately 4 million person-years of data, including 1.2 billion medical claims. The proportion of medical claims with ≥1 NDC increased from 1.2% in 2013 to 3.0% in 2017. Medical claim NDCs identified 39% and 28% of vedolizumab dispensed in 2014 and 2015 and 30% of Epogen/Procrit dispensed overall. Out of 26,381 filgrastim biosimilar dispensings identified, 51% had a HCPCS modifier and 12% had a medical claim NDC for Zarxio. HCPCS modifiers and medical claim NDCs were present for 38% and 3% of all infliximab biosimilars dispensed (total n = 1,244). CONCLUSIONS: Medical claim NDC and HCPCS modifier improves identification of select biologics without product-specific HCPCS code, thereby facilitating product-specific biologic research.

Role of health plan administrative claims data in participant recruitment for pragmatic clinical trials: An Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-term Effectiveness (ADAPTABLE) example.

AIM: The purpose of this study is to evaluate HealthCore/Anthem Research Network recruitment strategies, compare response and enrollment rates for different recruitment strategies, and describe demographic and clinical characteristics of responders and enrollees. METHODS: HealthCore/Anthem Research Network, a part of the Health Plan Research Network of the Patient-Centered Clinical Data Research Network, used administrative claims data to identify eligible health plan members for potential participation in the Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-term Effectiveness study. We approached health plan members, identified with a validated Patient-Centered Clinical Data Research Network common data model computable phenotype, and their clinical providers during November 2017 to August 2018. Providers were offered the option to exclude their patients' participation in Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-term Effectiveness prior to our direct patient (member) outreach. Member identification was in two phases: Phase 1: 1 January 2006 to 1 April 2017, and Phase 2: 1 January 2006 to 2 February 2018. Phase 1 consisted of two batches of mail and one phone call per patient. In Phase 2, which included two similar batches of patients, outreach was via either mail or brochure and one phone call. RESULTS: Phase 1 and Phase 2 included 133,373 and 51,777 members, respectively. We engaged 28,593 providers in Phase 1, and 5077 in Phase 2. In Phase 1, 264,158 mixed email/mail messages were delivered to 133,373 members, followed by 90,481 phone calls from November 2017 to February 2018. In Phase 2, after simple randomization to letter or brochure, 51,777 members were sent email/mail or mailed brochure in three waves from May 2018 to July 2018. In this 9-week period, 51,623 communications were sent to 25,914 members in the email/mail group, and 50,160 brochures to 25,863 in the brochure group. Following email/mail or mailed brochure outreach, 16,624 and 16,580 calls were made to the groups, respectively. Overall, 1549 health plan members visited the study portal by 1 September 2018; 355 electronically signed the Informed Consent Form and enrolled. Mailed brochures drove more portal visits in Phase 2, but a lower percentage of responders enrolled. Recruitment was better in Phase 2-2.3 enrollees per 1000 outreach members versus 1.8 in Phase 1. CONCLUSION: This study showed the ability of a health plan within Patient-Centered Clinical Data Research Network to identify potential study participants with administrative claims, and use different outreach methods to facilitate recruitment and enrollment for pragmatic clinical trials.

Practical challenges in the conduct of pragmatic trials embedded in health plans: Lessons of IMPACT-AFib, an FDA-Catalyst trial.

IMPACT-AFib was an 80,000-patient randomized clinical trial implemented by five US insurance companies (health plans) aimed at increasing the use of oral anticoagulants by individuals with atrial fibrillation who were at high risk of stroke and not on treatment. The underlying thesis was that patients could be change agents to initiate prescribing discussions with their providers. We tested the effect of mailing information to both patients and their providers. We used administrative medical claims and pharmacy dispensing data to identify eligible patients, to randomize them to an early or delayed intervention, and to assess clinical outcomes. The core data were analysis-ready datasets each site had created and curated for the FDA's Sentinel System, supplemented by updated "fresh" pharmacy and enrollment data to ensure eligibility at the time of intervention. Following mutually agreed upon procedures, sites linked to additional internal source data to implement the intervention-educational information mailed to patients and their providers in the early intervention arm, and to providers of patients in the delayed intervention arm approximately 12 months later. The primary analysis compares the early intervention arm to the delayed intervention arm, prior to the delayed intervention being conducted (i.e. compares intervention to non-intervention). The endpoints of interest were evidence of initiation of anticoagulation (primary) as well as clinical endpoints, including stroke and hospitalization for bleeding. Major challenges, some unanticipated, identified during the planning phase include convening multi-stakeholder investigator teams and advisors, addressing ethical concerns about not intervening in a usual care comparison group, and identifying and avoiding interference with sites' routine programs that were similar to the intervention. Needs and challenges during the implementation phase included the fact that even limited site-specific programming greatly increased time and effort, the need to refresh research data extracts immediately before outreach to patients and providers, potential difficulty identifying low-cost medications such as warfarin that may not be reimbursed by health plans and so not discoverable in dispensing data, the need to develop workarounds when "providers" in claims data were facilities, difficulty addressing clustering of patients by provider because providers can have multiple identifiers within and between health plans, and the need to anticipate loss to follow up because of health plan disenrollment or change in benefits. As pragmatic trials begin to shape evidence generation within clinical practice, investigators should anticipate issues inherent to claims data and working with multiple large sites. In IMPACT-AFib, we found that investing in collaboration and communication among all parties throughout all phases of the study helped ensure common understanding, early identification of challenges, and streamlined actual implementation.

Harnessing health plan enrollee data to boost membership in patient-powered research networks.

BACKGROUND: Patient-powered research networks (PPRNs) have been employing and exploring different methods to engage patients in research activities specific to their conditions. One way to intensify patient engagement is to partner with payer stakeholders. The objective of this study was to evaluate the effectiveness of two common payer-initiated outreach methods (postal mail versus email) for inviting prospective candidates to participate in their initiatives. METHODS: This descriptive study linked members of a nationally-representative private insurance network to four disease-specific PPRN registries. Eligible members meeting diagnostic criteria who were not registered in any of the four PPRNs by 02/28/2018 were identified, and randomly assigned to either the mail or email group. They were contacted in two outreach efforts: first on 04/23/2018, and one follow-up on 05/23/2018. New registration rates by outreach method as of 8/31/2018 were determined by relinking. We compared registrants and non-registrants using bivariate analysis. RESULTS: A total of 14,571 patients were assigned to the mail group, and 14,574 to the email group. Invitations were successfully delivered to 13,834 (94.9%) mail group and 10,205 (70.0%) email group members. A small but significantly larger proportion of mail group members, (n = 78; 0.54, 95% Confidence Interval [CI] {0.42-0.67%}) registered in PPRNs relative to the email group (n = 24; 0.16, 95% CI {0.11-0.25%}), p < 0.001. Members who registered had more comorbidities, were more likely to be female, and had marginally greater medical utilization, especially emergency room visits, relative to non-registrants (52.0% vs. 42.5%, p = 0.05). CONCLUSION: A health plan outreach to invite members to participate in PPRNs was modestly effective. Regular mail outperformed less costly email. Providing more value-add to participants may be a possible way to increase recruitment success.

Chart validation of an algorithm for identifying hereditary progressive muscular dystrophy in healthcare claims.

BACKGROUND: Muscular dystrophies (MDs) are a group of inherited conditions characterized by progressive muscle degeneration and weakness. The rarity and heterogeneity of the population with MD have hindered therapeutic developments as well as epidemiological and health outcomes research. The objective of the study was to develop and validate a case-finding algorithm utilizing administrative claims data to identify and characterize patients with MD. METHODS: This retrospective cohort study used medical chart validation to evaluate an ICD-9/10 coding algorithm in a large commercial claims database. Patients were identified who had ≥2 office visits with a diagnosis of hereditary progressive MDs from January 1, 2013 through December 31, 2016, were male, and younger than 18 years at the time of first MD diagnosis. Cases who met the algorithm were then validated against medical charts. Diagnoses of MD and specific type (Duchenne, Becker, or other MD) were confirmed by medical chart review by trained reviewers. Positive predictive value (PPV) and 95% confidence intervals (CI) were calculated using a 2 × 2 contingence table. Patient demographic, clinical, and health utilization characteristics were summarized using basic descriptive statistics. RESULTS: Charts were obtained and reviewed for 109 patients who met the algorithm. The PPV of the case-identifying algorithm for MD was 95% (95% CI 88-98%). Of the 103 confirmed MD cases, 87 patients (85%, 95% CI 76-91%) had Duchenne or Becker MD; 76 patients (74%, 95% CI 64-82%) had Duchenne MD, and 11 patients (11%, 95% CI 5-18%) had Becker MD. A total of 74 (67.9%) patients had ≥1 pediatric complex chronic condition (other than neurologic/neuromuscular disease); 54 (49.5%) had cardiovascular conditions; 14 (12.8%) had respiratory conditions; 50 (45.9%) had bone-related issues; 11 (10.1%) had impaired growth; and 6 (5.5%) had puberty delay. CONCLUSIONS: The results of this study demonstrate that the case-finding algorithm accurately identified patients with MD, primarily Duchenne MD, within a large administrative database. The algorithm, which was constructed using a few items easily accessible from claims, can be used to facilitate epidemiological and health outcomes research in the Duchenne patient population.

Association between early-childhood antibiotic exposure and subsequent asthma in the US Medicaid population.

BACKGROUND: Although socioeconomically disadvantaged children have an increased risk of asthma, the association between early-childhood antibiotics and the incidence of asthma among such children has had limited study. OBJECTIVE: To examine the association between antibiotic fills in the first 2 years of life and risk of developing asthma among children enrolled in Medicaid plans. METHODS: This retrospective cohort study of children with continuous medical and pharmacy coverage from birth to 2.5 years of age was performed from July 1, 2012, to November 31, 2018. We excluded children with a diagnosis of asthma before 2.5 years of age. Hazard ratios (HRs) and 95% CIs were estimated from Cox proportional hazards regression models. Covariates included sex, preterm birth, cesarean delivery, and mother's asthma status. RESULTS: There were 79,582 children in the study cohort of whom 29,931 (37.6%) had 0 antibiotic prescriptions filled, 27,403 (34.4%) had 1 or 2 prescriptions filled, and 22,248 (28.0%) had 3 or more prescriptions filled. A total of 2381 new cases of asthma were observed in 89,545 person-years of follow-up. After adjustment, receipt of 1 or 2 antibiotics was associated with an increased risk of developing asthma, relative to 0 antibiotics (HR, 1.34; 95% CI, 1.21-1.49), and receipt of 3 or more antibiotics was associated with greater increased risk relative to 0 antibiotics (HR, 1.71; 95% CI, 1.54-1.90). After adjustment, the absolute risk of developing asthma by age 4.0 years increased from 2.7% (0 antibiotics) to 3.6% (1-2 antibiotics) and 4.5% (≥3 antibiotics). CONCLUSION: Antibiotic prescriptions filled in the first 2 years of life were associated with an increased risk of asthma diagnosis from 2.5 to 5 years of age in a Medicaid population.