Manual and automated methods for identifying potentially preventable readmissions: a comparison in a large healthcare system

BMC Med Inform Decis Mak. 2014 Apr 5;14:28. doi: 10.1186/1472-6947-14-28.

Abstract

Background: Identification of potentially preventable readmissions is typically accomplished through manual review or automated classification. Little is known about the concordance of these methods.

Methods: We manually reviewed 459 30-day, all-cause readmissions at 18 Kaiser Permanente Northern California hospitals, determining potential preventability through a four-step manual review process that included a chart review tool, interviews with patients, their families, and treating providers, and nurse reviewer and physician evaluation of findings and determination of preventability on a five-point scale. We reassessed the same readmissions with 3 M's Potentially Preventable Readmission (PPR) software. We examined between-method agreement and the specificity and sensitivity of the PPR software using manual review as the reference.

Results: Automated classification and manual review respectively identified 78% (358) and 47% (227) of readmissions as potentially preventable. Overall, the methods agreed about the preventability of 56% (258) of readmissions. Using manual review as the reference, the sensitivity of PPR was 85% and specificity was 28%.

Conclusions: Concordance between methods was not high enough to replace manual review with automated classification as the primary method of identifying preventable 30-day, all-cause readmission for quality improvement purposes.

Publication types

  • Comparative Study

MeSH terms

  • Aged
  • California
  • Delivery of Health Care / methods*
  • Delivery of Health Care / standards
  • Female
  • Hospital Information Systems / standards*
  • Humans
  • Male
  • Patient Readmission / standards*
  • Qualitative Research
  • Quality Assurance, Health Care / methods*
  • Quality Assurance, Health Care / standards
  • Sensitivity and Specificity