Key result
Potentially preventable pneumonia readmissions show no difference in quality-of-care scores compared with nonpreventable cases.
Why the study?
Does the 3M PPR software flag identify pneumonia readmissions associated with poorer quality of care in US veterans?
Cross-Sectional (n=100)
Does the 3M PPR software flag identify pneumonia readmissions associated with poorer quality of care in US veterans?
Effect estimate: ES >0.30
Absolute Event Rate: 71.2% vs 65.8%
p-value: p=0.14
The 3M Potentially Preventable Readmissions software failed to accurately identify readmissions associated with worse process-of-care quality among VA pneumonia patients.
PPR flags do not identify poorer-quality pneumonia readmissions; challenges their validity as quality metrics and leaves open need for validated alternatives.
BACKGROUND: In the USA, administrative data-based readmission rates such as the Centers for Medicare and Medicaid Services' all-cause readmission measures are used for public reporting and hospital payment penalties. To improve this measure and identify better quality improvement targets, 3M developed the Potentially Preventable Readmissions (PPRs) measure. It matches clinically related index admission and readmission diagnoses that may indicate readmissions resulting from admission- or post-discharge-related quality problems. OBJECTIVE: To examine whether PPR software-flagged pneumonia readmissions are associated with poorer quality of care. METHODS: Using a retrospective observational study design and Veterans Health Administration (VA) data, we identified pneumonia discharges associated with 30-day readmissions, and then flagged cases as PPR-yes or PPR-no using the PPR software. To assess quality of care, we abstracted electronic medical records of 100 random readmissions using a tool containing explicit care processes organised into admission work-up, in-hospital evaluation/treatment, discharge readiness and post-discharge period. We derived quality scores, scaled to a maximum of 25 per section (maximum total score=100) and compared cases by total and section-specific mean scores using t tests and effect size (ES) to characterise the clinical significance of findings. RESULTS: Our abstraction sample was selected from 11,278 pneumonia readmissions (readmission rate=16.5%) during 1 October 2005-30 September 2010; 77% were flagged as PPR-yes. Contrary to expectations, total and section mean quality scores were slightly higher, although non-significantly, among PPR-yes (N=77) versus PPR-no (N=23) cases (respective total scores, 71.2±8.7 vs 65.8±11.5, p=0.14); differences demonstrated ES >0.30 overall and for admission work-up and post-discharge period sections. CONCLUSIONS: Among VA pneumonia readmissions, PPR categorisation did not produce the expected quality of care findings. Either PPR-yes cases are not more preventable, or preventability assessment requires other data collection methods to capture poorly documented processes (eg, direct observation).
No takes yet. Share an insight, caveat, or question.
Borzecki et al. (2015) conducted a cross-sectional in Pneumonia (n=100). Potentially Preventable Readmissions (PPR) software flag (PPR-yes) vs. PPR-no flag was evaluated on Mean total quality of care score (maximum 100) (ES >0.30, p=0.14). Among VA pneumonia readmissions, cases flagged as potentially preventable (PPR-yes) did not demonstrate poorer quality of care, with mean total quality scores non-significantly higher than PPR-no cases (71.2 vs 65.8, p=0.14).
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: