Key result
The 3M Potentially Preventable Readmission software demonstrated 85% sensitivity and 28% specificity compared to manual review, identifying 78% of readmissions as preventable versus 47% manually.
Why the study?
Does automated classification accurately identify potentially preventable readmissions compared to manual review?
Cross-Sectional (n=459)
Yes
Does automated classification accurately identify potentially preventable readmissions compared to manual review?
Effect estimate: Sensitivity 85%, Specificity 28%
Absolute Event Rate: 78% vs 47%
Automated classification of preventable readmissions has high sensitivity but low specificity compared to manual review, limiting its utility as a standalone tool for quality improvement.
Low concordance between automated and manual methods for preventable readmissions; leaves open which approach best informs quality improvement.
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.
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Jackson et al. (2014) conducted a cross-sectional in 30-day all-cause hospital readmissions (n=459). Automated classification (3M Potentially Preventable Readmission software) vs. Manual review was evaluated on Identification of potentially preventable readmissions (Sensitivity 85%, Specificity 28%). The 3M Potentially Preventable Readmission software demonstrated 85% sensitivity and 28% specificity compared to manual review, identifying 78% of readmissions as preventable versus 47% manually.
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