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Observational Study
. 2016 Sep 6;16(1):473.
doi: 10.1186/s12913-016-1731-9.

Risk-adjustment models for heart failure patients' 30-day mortality and readmission rates: the incremental value of clinical data abstracted from medical charts beyond hospital discharge record

Jacopo Lenzi  1 , Vera Maria Avaldi  1 , Tina Hernandez-Boussard  2 , Carlo Descovich  3 , Ilaria Castaldini  4 , Stefano Urbinati  5 , Giuseppe Di Pasquale  6 , Paola Rucci  1 , Maria Pia Fantini  7
Affiliations
Observational Study

Risk-adjustment models for heart failure patients' 30-day mortality and readmission rates: the incremental value of clinical data abstracted from medical charts beyond hospital discharge record

Jacopo Lenzi et al. BMC Health Serv Res. .

Abstract

Background: Hospital discharge records (HDRs) are routinely used to assess outcomes of care and to compare hospital performance for heart failure. The advantages of using clinical data from medical charts to improve risk-adjustment models remain controversial. The aim of the present study was to evaluate the additional contribution of clinical variables to HDR-based 30-day mortality and readmission models in patients with heart failure.

Methods: This retrospective observational study included all patients residing in the Local Healthcare Authority of Bologna (about 1 million inhabitants) who were discharged in 2012 from one of three hospitals in the area with a diagnosis of heart failure. For each study outcome, we compared the discrimination of the two risk-adjustment models (i.e., HDR-only model and HDR-clinical model) through the area under the ROC curve (AUC).

Results: A total of 1145 and 1025 patients were included in the mortality and readmission analyses, respectively. Adding clinical data significantly improved the discrimination of the mortality model (AUC = 0.84 vs. 0.73, p < 0.001), but not the discrimination of the readmission model (AUC = 0.65 vs. 0.63, p = 0.08).

Conclusions: We identified clinical variables that significantly improved the discrimination of the HDR-only model for 30-day mortality following heart failure. By contrast, clinical variables made little contribution to the discrimination of the HDR-only model for 30-day readmission.

Keywords: Heart failure; Mortality; Readmissions; Risk-adjustment.

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Figures

Fig. 1
Fig. 1
Patients’ flow diagram
Fig. 2
Fig. 2
Predicted probabilities of 30-day mortality and readmission for each of the continuous variables retained in the HDR-plus-clinical multivariable risk-adjustment models
Fig. 3
Fig. 3
ROC curves for 30-day mortality models based on HDRs only (#1) and HDR plus clinical data (#2). Note: The ROC curve is a plot of sensitivity versus 1 − specificity (often called the false-positive rate) that offers a summary of sensitivity and specificity across a range of cut points for a continuous predictor. The area under the curve (AUC) ranges from 0.5 (no discrimination) to a theoretical maximum of 1 (perfect discrimination). Abbreviations: ROC, receiver operation characteristic; Model #1 AUC, area under curve for model based on HDR variables; Model #2 AUC, area under curve for model based on HDR plus OPD plus medical charts variables
Fig. 4
Fig. 4
ROC curves for 30-day readmission models based on HDRs only (#1) and HDR plus clinical data (#2)
See this image and copyright information in PMC

References

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