An architecture for research computing in health to support clinical and translational investigators with electronic patient data

Thomas R Campion; Evan T Sholle; Jyotishman Pathak; Stephen B Johnson; John P Leonard; Curtis L Cole

doi:10.1093/jamia/ocab266

An architecture for research computing in health to support clinical and translational investigators with electronic patient data

J Am Med Inform Assoc. 2022 Mar 15;29(4):677-685. doi: 10.1093/jamia/ocab266.

Authors

Thomas R Campion^{1

2

3

4}, Evan T Sholle^{1

3

4}, Jyotishman Pathak^{1

4}, Stephen B Johnson⁵, John P Leonard⁶, Curtis L Cole^{1

3

4

6}

Affiliations

¹ Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA.
² Department of Pediatrics, Weill Cornell Medicine, New York, New York, USA.
³ Information Technologies & Services Department, Weill Cornell Medicine, New York, New York, USA.
⁴ Clinical and Translational Science Center, Weill Cornell Medicine, New York, New York, USA.
⁵ Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA.
⁶ Department of Medicine, Weill Cornell Medicine, New York, New York, USA.

Abstract

Objective: Obtaining electronic patient data, especially from electronic health record (EHR) systems, for clinical and translational research is difficult. Multiple research informatics systems exist but navigating the numerous applications can be challenging for scientists. This article describes Architecture for Research Computing in Health (ARCH), our institution's approach for matching investigators with tools and services for obtaining electronic patient data.

Materials and methods: Supporting the spectrum of studies from populations to individuals, ARCH delivers a breadth of scientific functions-including but not limited to cohort discovery, electronic data capture, and multi-institutional data sharing-that manifest in specific systems-such as i2b2, REDCap, and PCORnet. Through a consultative process, ARCH staff align investigators with tools with respect to study design, data sources, and cost. Although most ARCH services are available free of charge, advanced engagements require fee for service.

Results: Since 2016 at Weill Cornell Medicine, ARCH has supported over 1200 unique investigators through more than 4177 consultations. Notably, ARCH infrastructure enabled critical coronavirus disease 2019 response activities for research and patient care.

Discussion: ARCH has provided a technical, regulatory, financial, and educational framework to support the biomedical research enterprise with electronic patient data. Collaboration among informaticians, biostatisticians, and clinicians has been critical to rapid generation and analysis of EHR data.

Conclusion: A suite of tools and services, ARCH helps match investigators with informatics systems to reduce time to science. ARCH has facilitated research at Weill Cornell Medicine and may provide a model for informatics and research leaders to support scientists elsewhere.

Keywords: CTSA; EHR; data collection; data warehouse; secondary use.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Biomedical Research*
COVID-19*
Electronic Health Records
Electronics
Humans
Information Storage and Retrieval
Research Personnel

Abstract

Publication types

MeSH terms

Grants and funding