PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
December 8, 2010Circulation Cardiovascular Quality and Outcomes115 citationsOpen Access

Incremental Value of Clinical Data Beyond Claims Data in Predicting 30-Day Outcomes After Heart Failure Hospitalization

View Full Paper
BHBradley G. HammillLCLesley H. CurtisGFGregg C. Fonarow

Key Result

Adding clinical data to claims data significantly improved the prediction of 30-day mortality (AUC 0.761 vs 0.718) but not readmission (AUC 0.599 vs 0.587) after heart failure hospitalization.

Study Design

Type

Observational (n=25,766)

Multicenter

Yes

Structured PICO

Does adding clinical data to claims data improve the prediction of 30-day mortality and readmission in patients hospitalized for heart failure?

P
Population
25,766 patients from 308 hospitals (mortality analysis) and 24,163 patients from 307 hospitals (readmission analysis) hospitalized for heart failure, discharged between January 1, 2004, and December 31, 2006, from the Get With The Guidelines-Heart Failure registry linked with Medicare claims data.
I
Intervention
Claims-clinical regression models (adding clinical data to claims data)
C
Comparator
Claims-only regression models
O
Outcome
30-day mortality and 30-day readmissionhard clinical

Adding clinical data to administrative claims significantly improves 30-day mortality prediction and alters hospital performance rankings for heart failure, but does not meaningfully improve readmission prediction.

Main Result

Absolute Event Rate: 0.761% vs 0.718%

Abstract

BACKGROUND: Administrative claims data are used routinely for risk adjustment and hospital profiling for heart failure outcomes. As clinical data become more readily available, the incremental value of adding clinical data to claims-based models of mortality and readmission is unclear. METHODS AND RESULTS: We linked heart failure hospitalizations from the Get With The Guidelines-Heart Failure registry with Medicare claims data for patients discharged between January 1, 2004, and December 31, 2006. We evaluated the performance of claims-only and claims-clinical regression models for 30-day mortality and readmission, and compared hospital rankings from both models. There were 25 766 patients from 308 hospitals in the mortality analysis, and 24 163 patients from 307 hospitals in the readmission analysis. The claims-clinical mortality model (area under the curve AUC, 0.761; generalized R(2)=0.172) had better fit than the claims-only mortality model (AUC, 0.718; R(2)=0.113). The claims-only readmission model (AUC, 0.587; R(2)=0.025) and the claims-clinical readmission model (AUC, 0.599; R(2)=0.031) had similar performance. Among hospitals ranked as top or bottom performers by the claims-only mortality model, 12% were not ranked similarly by the claims-clinical model. For the claims-only readmission model, 3% of top or bottom performers were not ranked similarly by the claims-clinical model. CONCLUSIONS: Adding clinical data to claims data for heart failure hospitalizations significantly improved prediction of mortality, and shifted mortality performance rankings for a substantial proportion of hospitals. Clinical data did not meaningfully improve the discrimination of the readmission model, and had little effect on performance rankings.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Hammill et al. (2010) conducted an observational in Heart failure (n=25,766). Claims-clinical regression model vs. Claims-only regression model was evaluated on 30-day mortality prediction (AUC). Adding clinical data to claims data significantly improved the prediction of 30-day mortality (AUC 0.761 vs 0.718) but not readmission (AUC 0.599 vs 0.587) after heart failure hospitalization.

synapsesocial.com/papers/6a127410e407b2669634eba3https://doi.org/10.1161/circoutcomes.110.954693
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1The Hazards of Using Administrative Data to Measure Surgical Quality2006 · 27 citations
  2. 2Care in U.S. Hospitals — The Hospital Quality Alliance Program2005 · 490 citations
  3. 3An Administrative Claims Measure Suitable for Profiling Hospital Performance on the Basis of 30-Day All-Cause Readmission Rates Among Patients With Heart Failure2008 · 509 citations
  4. 4Early and Long-term Outcomes of Heart Failure in Elderly Persons, 2001-20052008 · 179 citations
  5. 5Recent National Trends in Readmission Rates After Heart Failure Hospitalization2009 · 450 citations