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Open Access Highly Accessed Research article

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

Ana H Jackson1*, Emily Fireman1, Paul Feigenbaum2, Estee Neuwirth1, Patricia Kipnis3 and Jim Bellows1

Author Affiliations

1 Care Management Institute, Kaiser Permanente, Oakland, California, USA

2 The Permanente Medical Group, Oakland, California, USA

3 Management Information and Analysis, Kaiser Permanente Northern California, Oakland, California, USA

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BMC Medical Informatics and Decision Making 2014, 14:28  doi:10.1186/1472-6947-14-28

Published: 5 April 2014

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.

Keywords:
Qualitative research; Quality assurance; Health care/methods; Patient readmission/statistics & numerical data