Manual and automated methods for identifying potentially preventable readmissions: a comparison in a large healthcare system
| Autor: | Esther B. Neuwirth, Paul Feigenbaum, Patricia Kipnis, Ana H Jackson, Emily Fireman, Jim Bellows |
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| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
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Quality Assurance Health Care Concordance Health Informatics Health informatics Patient Readmission Sensitivity and Specificity California Qualitative research medicine Humans Aged business.industry Health Policy medicine.disease Quality assurance Health care/methods Computer Science Applications Identification (information) Hospital Information Systems Female Medical emergency Patient readmission/statistics & numerical data business Delivery of Health Care Healthcare system Research Article |
| Zdroj: | BMC Medical Informatics and Decision Making |
| ISSN: | 1472-6947 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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