Framework of the strengths and challenges of clinically integrated trials: An expert panel report.

The limitations of the explanatory clinical trial framework include the high expense of implementing explanatory trials, restrictive entry criteria for participants, and redundant logistical processes. These limitations can result in slow evidence generation that is not responsive to population health needs, yielding evidence that is not generalizable. Clinically integrated trials, which integrate clinical research into routine care, represent a potential solution to this challenge and an opportunity to support learning health systems. The operational and design features of clinically integrated trials include a focused scope, simplicity in design and requirements, the leveraging of existing data structures, and patient participation in the entire trial process. These features are designed to minimize barriers to participation and trial execution and reduce additional research burdens for participants and clinicians alike. Broad adoption and scalability of clinically integrated trials are dependent, in part, on continuing regulatory, healthcare system, and payer support. This analysis presents a framework of the strengths and challenges of clinically integrated trials and is based on a multidisciplinary expert "Think Tank" panel discussion that included representatives from patient populations, academia, non-profit funding agencies, the U.S. Food and Drug Administration, and industry.

Drug development for major chronic health conditions-aligning with growing public health needs: Proceedings from a multistakeholder think tank.

The global pharmaceutical industry portfolio is skewed towards cancer and rare diseases due to more predictable development pathways and financial incentives. In contrast, drug development for major chronic health conditions that are responsible for a large part of mortality and disability worldwide is stalled. To examine the processes of novel drug development for common chronic health conditions, a multistakeholder Think Tank meeting, including thought leaders from academia, clinical practice, non-profit healthcare organizations, the pharmaceutical industry, the Food and Drug Administration (FDA), payors as well as investors, was convened in July 2022. Herein, we summarize the proceedings of this meeting, including an overview of the current state of drug development for chronic health conditions and key barriers that were identified. Six major action items were formulated to accelerate drug development for chronic diseases, with a focus on improving the efficiency of clinical trials and rapid implementation of evidence into clinical practice.

Why Evidence Generation Should Matter to Payers and How They Can Help.

Importance: The US leads the world in bringing new medical products to market, but the ability to generate evidence to inform clinical practice in postmarket settings needs improvement. Although a diverse group of stakeholders is working to improve postmarket evidence generation, the role of private payers has been underappreciated. Observations: Payers are crucial allies in improving evidence generation because better data would better inform coverage decisions, their policies and practices influence the conduct of care and research, and their claims data are a source of real-world evidence used in medical product evaluation. In addition, payers have a stake in improving evidence generation because the kinds of evidence needed to inform health care and coverage decisions are often not available when a product enters the market and may not be generated without their involvement. Here, we describe several key steps payers could take to improve evidence generation, including participating in efforts to reduce administrative and financial barriers to the conduct of clinical trials, directly incentivizing evidence generation on high-priority questions by funding potential cost-saving trials, increasing engagement with the medical products industry on evidentiary needs for coverage decisions, and improving usability of claims data by reducing data lags and routinely recording unique device identifiers. Broad payer engagement with US Food and Drug Administration recommendations regarding evidence generation will ensure that the opportunities to participate in clinical research are extended to all communities and that evidence needed to inform care is generated in trials and surveillance systems that reflect the clinical reality across the US. Conclusions and Relevance: Increasing payer involvement in evidence generation can benefit all participants in the medical innovation ecosystem. The importance of payers in these efforts will continue to grow in response to imperatives to increase integration of care and research, engage a diverse set of communities in clinical research, and move toward alternative payment models.

Why Should the FDA Focus on Pragmatic Clinical Research?

This Viewpoint from the FDA discusses how pragmatic clinical research­assessment that uses real-world data, often in combination with research data, after initial marketing approval­can help in evaluation of new technologies, benefit research sites in underresourced settings, and better inform regulatory decisions and clinical practice.

Incorporating Acute Conditions into Risk-Adjustment for Provider Profiling: The Case of the US News and World Report Best Hospitals Rankings Methodology.

Several years ago, the US News and World Report changed their risk-adjustment methodology, now relying almost exclusively on chronic conditions for risk adjustment. The impacts of adding selected acute conditions like pneumonia, sepsis, and electrolyte disorders ("augmented") to their current risk models ("base") for 4 specialties-cardiology, neurology, oncology, and pulmonology-on estimates of hospital performance are reported here. In the augmented models, many acute conditions were associated with substantial risks of mortality. Compared to the base models, the discrimination and calibration of the augmented models for all specialties were improved. While estimated hospital performance was highly correlated between the 2 models, the inclusion of acute conditions in risk-adjustment models meaningfully improved the predictive ability of those models and had noticeable effects on hospital performance estimates. Measures or conditions that address disease severity should always be included when risk-adjusting hospitalization outcomes, especially if the goal is provider profiling.

Contribution of Clinical Trial Event Data by Data Source: A Prespecified Analysis of the ADAPTABLE Randomized Clinical Trial.

Importance: Pragmatic randomized clinical trials (RCTs) often use multiple data sources to examine clinical events, but the relative contribution of data sources to clinical end-point rates is understudied. Objective: To assess the contribution of data sources (electronic health records [EHRs], public/private insurance claims, and/or participant-reported data) to clinical end points among ADAPTABLE participants who had available data. Design, Setting, and Participants: The ADAPTABLE study was an open-label, pragmatic RCT from April 2016 through June 2019 conducted in research networks within clinical practice. Participants had existing atherosclerotic cardiovascular disease and available data to analyze. The characteristics of patients by combinations of data source availability were compared to examine the contribution of each of the data sources to end-point ascertainment. Data for this prespecified analysis were examined from January 2022 to June 2023. Exposures: Randomized exposure to 81 mg or 325 mg of aspirin daily. Main Outcomes and Measures: Number of events for the primary end point (composite of death, hospitalization for myocardial infarction, and hospitalization for stroke) that were contributed by EHR or claims data and then number of events contributed by each additional data source. Results: Of 15 006 participants randomized with at least 1 other source of data available beyond participant-reported data, there were 8756 (58.3%) with participant-reported and EHR data; 4291 (28.6%) with participant-reported, EHR, and claims data; 1412 (9.4%) with EHR-only data; 262 (1.7%) with participant-reported and claims data; 202 (1.3%) with EHR and claims data; and 83 (0.6%) with claims-only data. Participants with EHR-only data were younger (median age, 63.7 years; IQR, 55.8-71.4) compared with the other groups (range, 65.6-71.9 years). Among participants with both EHR and claims data, with or without participant-reported data (n = 4493), for each outcome, most events (92%-100%) were identified in the EHR or in claims data. For all clinical end points, participant-reported data contributed less than 10% of events not otherwise available from claims or EHR data. Conclusions and Relevance: In this analysis of a pragmatic RCT, claims and EHR data provided the most clinical end-point data when compared with participant-reported events. These findings provide a framework for collecting end points in pragmatic clinical trials. Further work is needed to understand the data source combinations that most effectively provide clinical end-point data in RCTs.