RT Journal Article
SR Electronic
T1 Understanding challenges of using routinely collected health data to address clinical care gaps: a case study in Alberta, Canada
JF BMJ Open Quality
JO BMJ Open Qual
FD British Medical Journal Publishing Group
SP e001491
DO 10.1136/bmjoq-2021-001491
VO 11
IS 1
A1 Taylor McGuckin
A1 Katelynn Crick
A1 Tyler W Myroniuk
A1 Brock Setchell
A1 Roseanne O Yeung
A1 Denise Campbell-Scherer
YR 2022
UL http://bmjopenquality.bmj.com/content/11/1/e001491.abstract
AB 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.