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.

Social determinants of health and high-cost utilization among commercially insured population.

OBJECTIVES: To assess the impact of adding neighborhood social determinants of health (SDOH) data to demographic and clinical characteristics for predicting high-cost utilizers and to examine variations across age groups. STUDY DESIGN: Using US Census data and 2017-2018 commercial claims from a large national insurer, we estimated association between neighborhood-level SDOH and the probability of being a high-cost utilizer. METHODS: Observational study using administrative claims from a national insurer and US Census data. Data included a 50% random sample of commercially insured individuals who were younger than 89 years and had 1 year of continuous eligibility in 2017 and at least 30 days in 2018. Probit models assessed impact of SDOH and neighborhood conditions on predicting cost status. RESULTS: SDOH did not improve predictive power of evaluated models. However, disadvantaged neighborhood residence was still associated with being a high-cost utilizer. Adults 65 years and older in disadvantaged neighborhoods had increased likelihood of high-cost utilization. Children and younger adults in disadvantaged neighborhoods had lower risk of becoming high-cost utilizers. CONCLUSIONS: Policy makers and industry stakeholders should be aware of the mechanisms behind the relationship between neighborhood social conditions and health outcomes and how the relationship differs across age groups.

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.

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.

Development and Validation of Claims-Based Definitions to Identify Incident and Prevalent Inflammatory Bowel Disease in Administrative Healthcare Databases.

BACKGROUND: To facilitate inflammatory bowel disease (IBD) research in the United States, we developed and validated claims-based definitions to identify incident and prevalent IBD diagnoses using administrative healthcare claims data among multiple payers. METHODS: We used data from Medicare, Medicaid, and the HealthCore Integrated Research Database (Anthem commercial and Medicare Advantage claims). The gold standard for validation was review of medical records. We evaluated 1 incidence and 4 prevalence algorithms based on a combination of International Classification of Diseases codes, National Drug Codes, and Current Procedural Terminology codes. The claims-based incident diagnosis date needed to be within ±90 days of that recorded in the medical record to be valid. RESULTS: We reviewed 111 charts of patients with a potentially incident diagnosis. The positive predictive value (PPV) of the claims algorithm was 91% (95% confidence interval [CI], 81%-97%). We reviewed 332 charts to validate prevalent case definition algorithms. The PPV was 94% (95% CI, 86%-98%) for ≥2 IBD diagnoses and presence of prescriptions for IBD medications, 92% (95% CI, 85%-97%) for ≥2 diagnoses without any medications, 78% (95% CI, 67%-87%) for a single diagnosis and presence of an IBD medication, and 35% (95% CI, 25%-46%) for 1 physician diagnosis and no IBD medications. CONCLUSIONS: Through a combination of diagnosis, procedural, and medication codes in insurance claims data, we were able to identify incident and prevalent IBD cases with high accuracy. These algorithms can be useful for the ascertainment of IBD cases in future studies.

Association of Cancer Screening Deficit in the United States With the COVID-19 Pandemic.

Importance: The COVID-19 pandemic led to sharp declines in cancer screening. However, the total deficit in screening in the US associated with the pandemic and the differential impact on individuals in different geographic regions and by socioeconomic status (SES) index have yet to be fully characterized. Objectives: To quantify the screening rates for breast, colorectal, and prostate cancers associated with the COVID-19 pandemic in different geographic regions and for individuals in different SES index quartiles and estimate the overall cancer screening deficit in 2020 across the US population. Design, Setting, and Participants: This retrospective cohort study uses the HealthCore Integrated Research Database, which comprises single-payer administrative claims data and enrollment information covering approximately 60 million people in Medicare Advantage and commercial health plans from across geographically diverse regions of the US. Participants were individuals in the database in January through July of 2018, 2019, and 2020 without diagnosis of the cancer of interest prior to the analytic index month. Exposures: Analytic index month and year. Main Outcomes and Measures: Receipt of breast, colorectal, or prostate cancer screening. Results: Screening for all 3 cancers declined sharply in March through May of 2020 compared with 2019, with the sharpest decline in April (breast, -90.8%; colorectal, -79.3%; prostate, -63.4%) and near complete recovery of monthly screening rates by July for breast and prostate cancers. The absolute deficit across the US population in screening associated with the COVID-19 pandemic was estimated to be 3.9 million (breast), 3.8 million (colorectal), and 1.6 million (prostate). Geographic differences were observed: the Northeast experienced the sharpest declines in screening, while the West had a slower recovery compared with the Midwest and South. For example, percentage change in breast cancer screening rate (2020 vs 2019) for the month of April ranged from -87.3% (95% CI, -87.9% to -86.7%) in the West to -94.5% (95% CI, -94.9% to -94.1%) in the Northeast (decline). For the month of July, it ranged from -0.3% (95% CI, -2.1% to 1.5%) in the Midwest to -10.6% (-12.6% to -8.4%) in the West (recovery). By SES, the largest screening decline was observed in individuals in the highest SES index quartile, leading to a narrowing in the disparity in cancer screening by SES in 2020. For example, prostate cancer screening rates per 100 000 enrollees for individuals in the lowest and highest SES index quartiles, respectively, were 3525 (95% CI, 3444 to 3607) and 4329 (95% CI, 4271 to 4386) in April 2019 compared with 1535 (95% CI, 1480 to 1589) and 1338 (95% CI, 1306 to 1370) in April 2020. Multivariable analysis showed that telehealth use was associated with higher cancer screening. Conclusions and Relevance: Public health efforts are needed to address the large cancer screening deficit associated with the COVID-19 pandemic, including increased use of screening modalities that do not require a procedure.

Gaps in Evidence-Based Therapy Use in Insured Patients in the United States With Type 2 Diabetes Mellitus and Atherosclerotic Cardiovascular Disease.

Background Evidence-based therapies are generally underused for cardiovascular risk reduction; however, less is known about contemporary patients with type 2 diabetes mellitus and atherosclerotic cardiovascular disease. Methods and Results Pharmacy and medical claims data from within Anthem were queried for patients with established atherosclerotic cardiovascular disease and type 2 diabetes mellitus. Using an index date of April 18, 2018, we evaluated the proportion of patients with a prescription claim for any of the 3 evidence-based therapies on, or covering, the index date ±30 days: high-intensity statin, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, and sodium glucose cotransporter-2 inhibitor or glucagon-like peptide-1 receptor agonist. The potential benefit of achieving 100% adoption of all 3 evidence-based therapies was simulated using pooled treatment estimates from clinical trials. Of the 155 958 patients in the sample, 24.7% were using a high-intensity statin, 53.1% were using an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, and 9.9% were using either an sodium glucose cotransporter-2 inhibitor or glucagon-like peptide-1 receptor agonists. Overall, only 2.7% of the population were covered by prescriptions for all 3 evidence-based therapies, and 37.4% were on none of them. Over a 12-month period, 70.6% of patients saw a cardiologist, while only 18% saw an endocrinologist. Increasing the use of evidence-based therapies to 100% over 3 years of treatment could be expected to reduce 4546 major atherosclerotic cardiovascular events (myocardial infarction, stroke, or cardiovascular death) in eligible but untreated patients. Conclusions Alarming gaps exist in the contemporary use of evidence-based therapies in this large population of insured patients with type 2 diabetes mellitus and atherosclerotic cardiovascular disease. These data provide a call to action for patients, providers, industry, regulators, professional societies, and payers to close these gaps in care.

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.

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.

Incidence of Serious Infections and Design of Utilization and Safety Studies for Biologic and Biosimilar Surveillance.

BACKGROUND: There is a need for postmarketing evidence generation for novel biologics and biosimilars. OBJECTIVE: To assess the feasibility, strengths, and limitations of the Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) Distributed Research Network (DRN) to examine the utilization and comparative safety of immune-modulating agents among patients with autoimmune diseases. METHODS: We conducted a retrospective cohort study among patients enrolled in health insurance plans participating in the BBCIC DRN between January 1, 2006, and September 30, 2015. Eligible patients were adult (≥18 years) new users of a disease-modifying nonbiologic and/or biologic agent with a prior diagnosis of rheumatoid arthritis (RA), other inflammatory conditions (psoriasis, psoriatic arthritis, ankylosing spondylitis), or inflammatory bowel disease (IBD). Follow-up started at treatment initiation and ended at the earliest of outcome occurrence (serious infection); treatment discontinuation; or switching, death, disenrollment, or end of study period. The study leveraged the FDA Sentinel System infrastructure for data management and analysis; descriptive statistics of patient characteristics and unadjusted incidence rates of study outcomes during follow-up were calculated. RESULTS: Eligible patient drug episodes included 111,611 with RA (75% female), 61,050 with other inflammatory conditions (51% female), and 30,628 with IBD (52% female). Across all 3 cohorts, approximately half of the patient drug episodes initiated a biologic (50% in RA; 60% in psoriasis, psoriatic arthritis, ankylosing spondylitis; and 55% in IBD). The crude incidence rate of serious infection was 9.8 (9.5-10.0) cases per 100 person-years in RA, 7.1 (6.8-7.5) in other inflammatory conditions, and 14.2 (13.6-14.8) in IBD patients. CONCLUSIONS: This study successfully identified large numbers of new users of biologics and produced results that were consistent with those from earlier published studies. The BBCIC DRN is a potential resource for surveillance of biologics. DISCLOSURES: This study was funded by the Biologics and Biosimilars Collective Intelligence Consortium (BBCIC). HealthCore conducted this study in collaboration with Harvard Pilgrim Health Care. Zhang and Sridhar were employed by HealthCore at the time of this study. Haynes is employed by HealthCore funded by PCORI, the NIH, and the FDA. Barr and Eichelberger were employed by AMCP at the time of this study. Lockhart is employed by the BBCIC. Holmes and Clewell are employed by AbbVie. Accrott is an employee of and shareholder in Amgen. Marshall and Brown are employed by Harvard Pilgrim Health Care. Barr is a shareholder in Roche/Genentech. Curtis has received research grants from and consults with the following: Amgen, AbbVie, BMS, CORRONA, Lilly, Janssen, Myriad, Pfizer, Roche, Regeneron, and UCB. Brown has received research grants from GSK and Pfizer and consulting fees from Bayer, Roche, and Jazz Pharmaceuticals, along with funding from the Reagan-Udall Foundation for the FDA to conduct studies for medical product manufacturers, including Eli Lilly, Novartis, Abbvie, and Merck. Brown is also funded by PCORI, the NIH, and the FDA. McMahill-Walraven subcontracts with Harvard Pilgrim Health Care Institute for public health and safety surveillance distributed data network activtities and with the FDA, GSK, and Pfizer. She also reports fees from Reagan Udall Foundation for the FDA and the Patient Centered Outcomes Research Institute.

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.

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.

Advance Care Planning Claims and Health Care Utilization Among Seriously Ill Patients Near the End of Life.

Importance: Although advance care planning is known to increase patient and caregiver satisfaction, its association with health care utilization is not well understood. Objective: To examine the association between billed advance care planning encounters and subsequent health care utilization among seriously ill patients. Design, Setting, and Participants: This retrospective cohort study conducted from October 1, 2015, to May 31, 2018, used a national commercial insurance claims database to retrieve data from 18 484 Medicare Advantage members 65 years or older who had a claim that contained a serious illness diagnosis. Exposure: A claim that contained an advance care planning billing code between October 1, 2016, and November 30, 2017. Main Outcomes and Measures: Receipt of intensive therapies, hospitalization, emergency department use, hospice use, costs, and death during the 6-month follow-up period. Results: The final study sample included 18 484 seriously ill patients (mean [SD] age, 79.7 [7.9] years; 10 033 [54.3%] female), 864 (4.7%) of whom had a billed advanced care planning encounter between October 1, 2016, and November 30, 2017. In analyses adjusted for patient characteristics and a propensity score for advance care planning, the presence of a billed advance care planning encounter was associated with a higher likelihood of hospice enrollment (incidence rate ratio [IRR], 2.52; 95% CI, 2.22-2.86) and mortality (hazard ratio, 2.27; 95% CI, 1.79-2.88) compared with no billed advance care planning encounter. Although patients with billed advance care planning encounters were also more likely to be hospitalized (IRR, 1.37; 95% CI, 1.26-1.49), including in the intensive care unit (IRR, 1.25; 95% CI, 1.08-1.45), they were less likely to receive any intensive therapies (IRR, 0.85; 95% CI, 0.78-0.92), such as chemotherapy (IRR, 0.65; 95% CI, 0.55-0.78). Similar results were observed in a propensity score-matched analysis (99% matched) and in a decedent analysis of patients who died during the 6-month follow-up period. Conclusions and Relevance: Patients with billed advance care planning encounters were more likely than those without these encounters to receive hospice services and less likely to receive any intensive therapies, such as chemotherapy. However, they were also hospitalized more frequently than patients without billed advance care planning encounters. Although these findings were robust to multiple analytic methods, the results may be attributable to residual confounding because of a higher unmeasured severity of illness in the advance care planning group. Additional evidence appears to be needed to understand the effect of advance care planning on these outcomes.

Identification of potential drug name confusion errors in the Sentinel System.

PURPOSE: In July 2015, the US Food and Drug Administration (FDA) published a drug safety communication regarding errors in prescribing and dispensing of the antidepressant Brintellix (vortioxetine) and the antiplatelet Brilinta (ticagrelor) that arose due to proprietary drug name confusion. Brintellix is indicated for major depressive disorder; Brilinta is indicated to reduce cardiovascular death, myocardial infarction, and stroke in patients with acute coronary syndrome or history of myocardial infarction. Brintellix was renamed to Trintellix in May 2016. Using Brilinta and Brintellix as a proof-of-concept feasibility use case, we assessed whether drug name confusion errors between the pair could be identified in electronic health care data via the combination of a claims-based algorithm and limited manual claims data review. METHODS: Using data from the Sentinel System, we defined potential errors as Brintellix users without an on- or off-label indication for Brintellix, without a dispensing for a drug with the same indications as Brintellix, and with an on- or off-label indication for Brilinta between -365 and +30 days after index Brintellix dispensing; the reverse was done for Brilinta. We manually reviewed claims profiles of potential cases. RESULTS: We identified 27 (0.1%) potential errors among 21 208 Brintellix users; 16 appeared to be likely errors based on claims profile review. Fifty-one (0.3%) of the 16 779 Brilinta users were identified as potential errors, and four appeared to be likely errors. CONCLUSIONS: A claims-based algorithm combined with manual review of claims profiles could identify potential drug name confusion errors, and narrow down likely errors that warrant further investigation.

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.

Harnessing the Biologics and Biosimilars Collective Intelligence Consortium to Evaluate Patterns of Care.

INTRODUCTION: As clinical trials test efficacy rather than effectiveness of medications, real-world effectiveness data often vary from clinical trial data. Given the recent market entry of multiple biologics and biosimilars, a dedicated assessment of these diverse agents is needed to build the evidence base regarding efficacy and safety of innovator biologics and biosimilars. PROGRAM DESCRIPTION: The Academy of Managed Care Pharmacy's Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) was convened to address the lack of real-world, postmarket outcome evidence generation for innovator biologics and corresponding biosimilars. The BBCIC is a multistakeholder scientific research consortium whose participants prioritize topics and collaboratively conduct research studies. The BBCIC conducts a wide range of analyses, including population characterization, epidemiologic studies, and active observational studies, and develops best practices for conducting large-scale studies to provide real-world evidence. OBSERVATIONS: Over the past 3 years, we undertook multiple descriptive analyses with the goal of characterizing data availability and demonstrating the feasibility and efficacy of using the BBCIC distributed research network (DRN), which includes commercial claims data from 2008-2018 covering approximately 100 million lives, with approximately 20 million active members in 2017 from 2 major U.S. health plans and 3 regional integrated delivery networks. We analyzed 4 medication classes of particular interest to biologics and biosimilars development: insulins, granulocyte colony-stimulating factors, erythropoietic-stimulating agents, and anti-inflammatories. We were able to identify exposures and user characteristics in all 4 categories. Herein we describe the successes and challenges of conducting some of our analyses, specifically among insulin users with type 1 diabetes mellitus. IMPLICATIONS: Our results demonstrate the BBCIC DRN's ability to identify and characterize exposures, cohorts, and outcomes that can contribute to more sophisticated comparative surveillance of biosimilars and innovator biologics in the future. Additional linkages to laboratory data and a wider range of insurance carriers will further strengthen the BBCIC DRN. DISCLOSURES: This study was coordinated and funded by the Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) and represents the independent findings of the BBCIC Insulins Principal Investigator and the BBCIC Insulins Research Team. Lockhart is employed by the BBCIC; Eichelberger was employed by the BBCIC at the time of this study. McMahill-Walraven is employed by Aetna, a CVS Health business. Panozzo, Marshall, and Brown are employed by Harvard Pilgrim Healthcare Institute. Aetna receives external funding through research grants and subcontracts with Harvard Pilgrim Healthcare Institute, which are funded by the FDA, NIH, PCORI, BBCIC, Pfizer, and GSK; the Reagan-Udall Foundation for IMEDS; and PCORI for the ADAPTABLE Study. Aetna was reimbursed for data and analytic support from Harvard Pilgrim Healthcare Institute and the Reagan Udall Foundation for the U.S. Food and Drug Administration. This work was presented as a poster at AMCP Nexus 2018; October 22-25, 2018; in Orlando, FL.

Bystander Ethics and Good Samaritanism: A Paradox for Learning Health Organizations.

In 2012, a U.S. Institute of Medicine report called for a different approach to health care: "Left unchanged, health care will continue to underperform; cause unnecessary harm; and strain national, state, and family budgets." The answer, they suggested, would be a "continuously learning" health system. Ethicists and researchers urged the creation of "learning health organizations" that would integrate knowledge from patient-care data to continuously improve the quality of care. Our experience with an ongoing research study on atrial fibrillation-a trial known as IMPACT-AFib-gave us some insight into one of the challenges that will have to be dealt with in creating these organizations. Although the proposed educational intervention study placed no restrictions on what providers and health plans could do, the oversight team argued that the ethical principle of beneficence did not allow the researchers to be "bystanders" in relation to a control group receiving suboptimal care. In response, the researchers designed a "workaround" that allowed the project to go forward. We believe the experience suggests that what we call "bystander ethics" will create challenges for the kinds of quality improvement research that LHOs are designed to do.

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.

Administrative claims data to support pragmatic clinical trial outcome ascertainment on cardiovascular health.

BACKGROUND/AIMS: Health plan administrative claims data present a cost-effective complement to traditional trial-specific ascertainment of clinical events typically conducted through patient report or a single health system electronic health record. We aim to demonstrate the value of health plan claims data in improving the capture of endpoints in longitudinal pragmatic clinical trials. METHODS: This retrospective cohort study paralleled the design of the ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness) trial designed to compare the effectiveness of two doses of aspirin. We applied the ADAPTABLE identification query in claims data from Anthem, an American health insurance company, and identified health plan members who met the ADAPTABLE trial criteria. Among the ADAPTABLE eligible members, we selected overlapping members with PCORnet Clinical Data Research Networks in the 2 years prior to the index date (1 April 2014). PCORnet Clinical Data Research Networks consist of network partners (or healthcare systems) that store their electronic health record data in the same format to support multi-institutional research. ADAPTABLE outcome events-cardiovascular hospitalizations including admissions for myocardial infarction, stroke, or cardiac procedures; hospitalizations for major bleeding; and in-hospital deaths-were evaluated for a 2-year follow-up period. Events were classified as within or outside PCORnet Clinical Data Research Networks using facility identifiers affiliated with each hospital stay. Patient characteristics were examined with descriptive statistics, and incidence rates were reported for available Clinical Data Research Networks and claims data. RESULTS: Among 884,311 ADAPTABLE eligible health plan members, 11,101 patients overlapped with PCORnet Clinical Data Research Networks. Average age was 70 years, 71% were male, and average follow-up was 20.7 months. Patients had 1521 cardiovascular hospitalizations (571 (37.5%) occurred outside PCORnet Clinical Data Research Networks), 710 for major bleeding (296 (41.7%) outside PCORnet Clinical Data Research Networks), and 196 in-hospital deaths (67 (34.2%) outside PCORnet Clinical Data Research Networks). Incidence rates (events per1000 patient-months) differed between available network partners and claims data: cardiovascular hospitalizations, 4.1 (95% confidence interval: 3.9, 4.4) versus 6.6 (95% confidence interval: 6.3, 7.0), major bleeding, 1.8 (95% confidence interval: 1.6, 2.0) versus 3.1 (95% confidence interval: 2.9, 3.3), and in-hospital death, 0.56 (95% confidence interval: 0.47, 0.67) versus 0.85 (95% confidence interval: 0.74, 0.98), respectively. CONCLUSION: This study demonstrated the value of supplementing longitudinal site-based clinical studies with administrative claims data. Our results suggest that claims data together with network partner electronic health record data constitute an effective vehicle to capture patient outcomes since >30% of patients have non-fatal and fatal events outside of enrolling sites.