Understanding challenges of using routinely collected health data to address clinical care gaps: a case study in Alberta, Canada

High-quality data are fundamental to healthcare research, future applications of artificial intelligence and advancing healthcare delivery and outcomes through a learning health system. Although routinely collected administrative health and electronic medical record data are rich sources of informat...

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Bibliographic Details
Published in:BMJ open quality 2022-01, Vol.11 (1), p.e001491
Main Authors: McGuckin, Taylor, Crick, Katelynn, Myroniuk, Tyler W, Setchell, Brock, Yeung, Roseanne O, Campbell-Scherer, Denise
Format: Article
Language:English
Subjects:
Alberta
Artificial Intelligence
data accuracy
Electronic Health Records
Emergency medical care
health services research
healthcare quality improvement
Humans
Information systems
Medical records
Quality control
Quality Improvement
quality improvement methodologies
Research & Reporting Methodology
Routinely Collected Health Data
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Summary:High-quality data are fundamental to healthcare research, future applications of artificial intelligence and advancing healthcare delivery and outcomes through a learning health system. Although routinely collected administrative health and electronic medical record data are rich sources of information, they have significant limitations. Through four example projects from the Physician Learning Program in Edmonton, Alberta, Canada, we illustrate barriers to using routinely collected health data to conduct research and engage in clinical quality improvement. These include challenges with data availability for variables of clinical interest, data completeness within a clinical visit, missing and duplicate visits, and variability of data capture systems. We make four recommendations that highlight the need for increased clinical engagement to improve the collection and coding of routinely collected data. Advancing the quality and usability of health systems data will support the continuous quality improvement needed to achieve the quintuple aim.
ISSN:2399-6641
2399-6641
DOI:10.1136/bmjoq-2021-001491