Developing electronic clinical quality measures to assess the cancer diagnostic process

J Am Med Inform Assoc. 2023 Aug 18;30(9):1526-1531. doi: 10.1093/jamia/ocad089.


Objective: Measures of diagnostic performance in cancer are underdeveloped. Electronic clinical quality measures (eCQMs) to assess quality of cancer diagnosis could help quantify and improve diagnostic performance.

Materials and methods: We developed 2 eCQMs to assess diagnostic evaluation of red-flag clinical findings for colorectal (CRC; based on abnormal stool-based cancer screening tests or labs suggestive of iron deficiency anemia) and lung (abnormal chest imaging) cancer. The 2 eCQMs quantified rates of red-flag follow-up in CRC and lung cancer using electronic health record data repositories at 2 large healthcare systems. Each measure used clinical data to identify abnormal results, evidence of appropriate follow-up, and exclusions that signified follow-up was unnecessary. Clinicians reviewed 100 positive and 20 negative randomly selected records for each eCQM at each site to validate accuracy and categorized missed opportunities related to system, provider, or patient factors.

Results: We implemented the CRC eCQM at both sites, while the lung cancer eCQM was only implemented at the VA due to lack of structured data indicating level of cancer suspicion on most chest imaging results at Geisinger. For the CRC eCQM, the rate of appropriate follow-up was 36.0% (26 746/74 314 patients) in the VA after removing clinical exclusions and 41.1% at Geisinger (1009/2461 patients; P < .001). Similarly, the rate of appropriate evaluation for lung cancer in the VA was 61.5% (25 166/40 924 patients). Reviewers most frequently attributed missed opportunities at both sites to provider factors (84 of 157).

Conclusions: We implemented 2 eCQMs to evaluate the diagnostic process in cancer at 2 large health systems. Health care organizations can use these eCQMs to monitor diagnostic performance related to cancer.

Keywords: colon cancer; diagnostic delays; diagnostic errors; lung cancer; quality measures; triggers.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Affect
  • Delivery of Health Care
  • Electronic Health Records
  • Humans
  • Lung Neoplasms* / diagnosis
  • Quality Indicators, Health Care*