Validation of a claims-based algorithm identifying eligible study subjects in the ADAPTABLE pragmatic clinical trial

Fishman, Ezra; Barron, John; Dinh, Jade; Jones, W. Schuyler; Marshall, Amanda; Merkh, Rebecca; Robertson, Holly R.; Haynes, Kevin

doi:10.1016/j.conctc.2018.11.001

Cited by 17 publications

(14 citation statements)

References 14 publications

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“…Incident CHD was defined as a new diagnosis of myocardial infarction (MI), angina, coronary revascularization, or other ischemic heart disease using validated ICD definitions, which have demonstrated high levels of agreement with expert chart review (Supplementary Methods) (26)(27)(28)(29). was not noted in the medical record until sometime shortly after baseline; therefore, people with CHD diagnosed within 90 days of the baseline date were excluded.…”

Section: Incident Chdmentioning

confidence: 99%

Comparative Risk of Incident Coronary Heart Disease Across Chronic Inflammatory Diseases

Sinha

Rivera

Chadha

et al. 2021

Front. Cardiovasc. Med.

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Background: Chronic inflammatory diseases (CIDs) are considered risk enhancing factors for coronary heart disease (CHD). However, sparse data exist regarding relative CHD risks across CIDs.Objective: Determine relative differences in CHD risk across multiple CIDs: psoriasis, rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), human immunodeficiency virus (HIV), systemic sclerosis (SSc), and inflammatory bowel disease (IBD).Methods: The cohort included patients with CIDs and controls without CID in an urban medical system from 2000 to 2019. Patients with CIDs were frequency-matched with non-CID controls on demographics, hypertension, and diabetes. CHD was defined as myocardial infarction (MI), ischemic heart disease, and/or coronary revascularization based on validated administrative codes. Multivariable-adjusted Cox models were used to determine the risk of incident CHD and MI for each CID relative to non-CID controls. In secondary analyses, we compared CHD risk by disease severity within each CID.Results: Of 17,049 patients included for analysis, 619 had incident CHD (202 MI) over an average of 4.4 years of follow-up. The multivariable-adjusted risk of CHD was significantly higher for SLE [hazard ratio (HR) 1.9, 95% confidence interval (CI) 1.2, 3.2] and SSc (HR 2.1, 95% CI 1.2, 3.9). Patients with SLE also had a significantly higher risk of MI (HR 3.6, 95% CI 1.9, 6.8). When CIDs were categorized by markers of disease severity (C-reactive protein for all CIDs except HIV, for which CD4 T cell count was used), greater disease severity was associated with higher CHD risk across CIDs.Conclusions: Patients with SLE and SSc have a higher risk of CHD. CHD risk with HIV, RA, psoriasis, and IBD may only be elevated in those with greater disease severity. Clinicians should personalize CHD risk and treatment based on type and severity of CID.

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Section: Incident Chdmentioning

confidence: 99%

Comparative Risk of Incident Coronary Heart Disease Across Chronic Inflammatory Diseases

Sinha

Rivera

Chadha

et al. 2021

Front. Cardiovasc. Med.

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“…This computable phenotype was previously validated. 13 For inclusion, eligible members were also required to have enrollment eligibility as of 1 April 2017 and a cardiologist or primary care visit during the 12 months prior to 1 April 2017. Members diagnosed with coronary artery disease only were excluded from Phase 1.…”

Section: Methodsmentioning

confidence: 99%

“…[7][8][9] Furthermore, when acquired from a variety of sources and repurposed for research, electronic medical record data may have key missing information. 5,6,10 Cognizant of the challenges, researchers are incorporating health plan claims data to complement other data sources for the identification of eligible research study participants, [11][12][13][14][15] in pragmatic clinical trial designs. [14][15][16][17] Health plan data are drawn from administrative claims submitted from multiple healthcare systems and providers and contain a broader set of information on members' utilization histories compared with electronic medical record-based profiles from individual health systems.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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“…This computable phenotype algorithm was validated in our administrative claims data environment. 44 From the resulting population, we conducted a retrospective, observational cohort study within HealthCore Intergraded Research Database (HIRD ® )—a repository of longitudinal claims data for HealthCore Anthem Research Network enrollees representative of the commercially insured population in the United States. 45 Compared to the PCORnet common data model, HealthCore Intergraded Research Database contains more patient-level data for a member’s visit, such as provider and facility information, enabling characterization of care across healthcare delivery systems.…”

Section: Methodsmentioning

confidence: 99%

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

Chung

Shambhu

et al. 2019

Clinical Trials

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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.

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Validation of a claims-based algorithm identifying eligible study subjects in the ADAPTABLE pragmatic clinical trial

Cited by 17 publications

References 14 publications

Comparative Risk of Incident Coronary Heart Disease Across Chronic Inflammatory Diseases

Comparative Risk of Incident Coronary Heart Disease Across Chronic Inflammatory Diseases

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

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

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