Introduction of QUIP (quality information program) as a semi-automated quality assessment endeavor allowing retrospective review of errors in cross-sectional abdominal imaging

Acad Radiol. 2011 Nov;18(11):1358-64. doi: 10.1016/j.acra.2011.06.012. Epub 2011 Sep 8.

Abstract

Rationale and objectives: The aims of this study were to review the role of a quality information program (QUIP) as a semiautomated educational feedback mechanism and to review common errors in cross-sectional abdominal and pelvic studies as an initiative for continuing medical education and improving patient care.

Materials and methods: Abdominal and pelvic errors identified by QUIP and cases collected from morbidity and mortality conferences were reviewed. Errors were classified and graded to levels of morbidity.

Results: There were 222 errors in 218 patients over 4 years in this study. One hundred thirteen (51%) were identified after the introduction of QUIP (January to December 2009). One hundred thirty-eight studies (61%) were read independently, while 84 (39%) were double-read. Sixty-five percent of errors (145 of 222) were false-negatives, of which 45 (31%) were "satisfaction-of-search" errors. There were 62 cognitive errors (28%), nine technical errors (4%), eight communication errors (4%), six ordering errors (3%), and five false-positives identified. Seventy-six percent of errors were identified on computed tomography (n = 168); fewer cases involved ultrasound (n = 20 [9%]) and magnetic resonance (n = 34 [15%]). Forty-one percent resulted in no changes to patient outcomes. Forty-percent caused minor patient morbidity, and 19% caused major patient morbidity, including three cases (1%) that likely contributed to patient death.

Conclusions: Most abdominopelvic errors in this study were classified as false-negatives. Many can be attributed to satisfaction-of-search errors. Implementing a simple, semiautomated QUIP allows timely feedback regarding errors to radiologists. This may improve the quality of health care while allowing radiologists the opportunity to learn from each case they are involved in.

MeSH terms

  • Adult
  • Aged
  • Diagnostic Errors / statistics & numerical data*
  • Female
  • Humans
  • Magnetic Resonance Imaging / standards
  • Male
  • Middle Aged
  • Quality Assurance, Health Care*
  • Radiography, Abdominal / standards*
  • Risk Factors
  • Tomography, X-Ray Computed / standards