Commentary on Bertagnolli et al.: Leveraging electronic health record data for clinical trials

Abstract

Get full access to this article

View all access options for this article.

References

U.S. Food and Drug Administration. Guidance for Industry and Food and Drug Administration Staff: use of real-world evidence to support regulatory decision-making for medical devices, https://www.fda.gov/downloads/medicaldevices/deviceregulationandguidance/guidancedocuments/ucm513027.pdf (2017, accessed 21 January 2020).

Schulz

Young

Coppi

, et al. Temporal relationship of computed and structured diagnoses in electronic health record data, https://www.medrxiv.org/content/10.1101/2019.12.28.19015628v1 (2020, accessed 21 January 2020).

Bartlett

Dhruva

Shah

, et al. Feasibility of using real-world data to replicate clinical trial evidence. JAMA Netw Open 2019; 2(10): e1912869.

Phillips

Desai

Krumholz

, et al. Association of the FDA Amendment Act with trial registration, publication, and outcome reporting. Trials 2017; 18(1): Article 333.

Zou

Becker

Phillips

, et al. Registration, results reporting, and publication bias of clinical trials supporting FDA approval of neuropsychiatric drugs before and after FDAAA: a retrospective cohort study. Trials 2018; 19(1): Article 581.

Observational Health Data Sciences and Informatics (OHDSI). Welcome to OHDSI! https://www.ohdsi.org/ (accessed 21 January 2020).

Suchard

Schuemie

Krumholz

, et al. Comprehensive comparative effectiveness and safety of first-line antihypertensive drug classes: a systematic, multinational, large-scale analysis. Lancet 2019; 394(10211): 1816–1826.

Duke Margolis Center for Health Policy. Real-world evidence collaborative, https://healthpolicy.duke.edu/real-world-evidence-collaborative (accessed 21 January 2020).

Corrigan-Curay

Sacks

Woodcock

Real-world evidence and real-world data for evaluating drug safety and effectiveness. JAMA 2018; 320(9): 867–868.

10.

Jarow

LaVange

Woodcock

Multidimensional evidence generation and FDA regulatory decision making: defining and using “real-world” data. JAMA 2017; 318(8): 703–704.

11.

Hernandez

Fleurence

Rothman

RL.

The ADAPTABLE trial and PCORnet: shining light on a new research paradigm. Ann Intern Med 2015; 163(8): 635–636.

12.

Choudhry

NK.

Randomized, controlled trials in health insurance systems. N Engl J Med 2017; 377(10): 957–964.

13.

Lauer

D’Agostino

Sr . The randomized registry trial —the next disruptive technology in clinical research. N Engl J Med 2013; 369(17): 1579–1581.

14.

Bertagnolli

Anderson

Quina

, et al. The electronic health record as a clinical trials tool: opportunities and challenges. Clin Trials 2020; 17(3): 237–242.

15.

Dhruva

Ross

Akar

, et al. Aggregating multiple real-world data sources using a patient-centered health data sharing platform: an 8-week cohort study among patients undergoing bariatric surgery or catheter ablation of atrial fibrillation. NPJ Digit Med 2020, https://www.medrxiv.org/content/10.1101/19010348v1

Commentary on Bertagnolli et al.: Leveraging electronic health record data for clinical trials—a brave new world

Abstract

Get full access to this article

References