Development of a large urban longitudinal HIV clinical cohort using a web-based platform to merge electronically and manually abstracted data from disparate medical record systems: technical challenges and innovative solutions

Abstract

Objective: Electronic medical records (EMRs) are being increasingly utilized to conduct clinical and epidemiologic research in numerous fields. To monitor and improve care of HIV-infected patients in Washington, DC, one of the most severely affected urban areas in the United States, we developed a city-wide database across 13 clinical sites using electronic data abstraction and manual data entry from EMRs.

Materials and methods: To develop this unique longitudinal cohort, a web-based electronic data capture system (Discovere®) was used. An Agile software development methodology was implemented across multiple EMR platforms. Clinical informatics staff worked with information technology specialists from each site to abstract data electronically from each respective site's EMR through an extract, transform, and load process.

Results: Since enrollment began in 2011, more than 7000 patients have been enrolled, with longitudinal clinical data available on all patients. Data sets are produced for scientific analyses on a quarterly basis, and benchmarking reports are generated semi-annually enabling each site to compare their participants' clinical status, treatments, and outcomes to the aggregated summaries from all other sites.

Discussion: Numerous technical challenges were identified and innovative solutions developed to ensure the successful implementation of the DC Cohort. Central to the success of this project was the broad collaboration established between government, academia, clinics, community, information technology staff, and the patients themselves.

Conclusions: Our experiences may have practical implications for researchers who seek to merge data from diverse clinical databases, and are applicable to the study of health-related issues beyond HIV.

Keywords: DC Cohort; EMR; HIV; cohort; electronic medical record.

© The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Figures

Figure 1:

DC Cohort organizational structure. DC PFAP EC: District of Columbia Partnership for AIDS Progress executive committee; DC Cohort PI: District of Columbia Cohort principal investigator; DSCC: Data and Statistics Coordinating Center; DC Cohort EC: DC Cohort executive committee; Site PIs: site principal investigators; GW: George Washington University; NIH: National Institutes of Health; DC DOH: District of Columbia Department of Health; Patient CAB: Patient Community Advocacy Board.

Figure 2:

Overall view of agile data abstraction from EMR platforms. Gap analysis is an assessment of the EMR at each DC Cohort site EMR to determine which variables of interest to the DC Cohort can be captured electronically through the export programs, and which will need to be entered manually. Scrum master is a rugby analogy for the facilitating role that Cerner plays in the development and maintenance of the export programs through regular calls and meetings with the IT staff at each DC Cohort site. EMR: electronic medical record.

Figure 3:

Typical workflow of participant data entry into Discovere and process efficiency outline. PID: participant identification number; EMR: electronic medical record.

Figure 4

Cumulative enrollment in the DC cohort, January 2011 through April 2015. aWithdrawn: 14 patients have withdrawn to date. bUndecided; Patients who have not yet decided whether to consent or refuse. Site staff may approach patients up to four times for consent.