Derivation and Validation of an In-Hospital Mortality Prediction Model Suitable for Profiling Hospital Performance in Heart Failure.

Autor: Lagu T; Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School-Baystate, Springfield, MA tara.lagu@baystatehealth.org.; University of Massachusetts Medical School-Baystate, Springfield, MA.; Department of Medicine, Baystate Medical Center, Springfield, MA., Pekow PS; Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School-Baystate, Springfield, MA.; School of Public Health and Health Sciences, University of Massachusetts-Amherst, Amherst, MA., Stefan MS; Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School-Baystate, Springfield, MA.; University of Massachusetts Medical School-Baystate, Springfield, MA.; Department of Medicine, Baystate Medical Center, Springfield, MA., Shieh MS; Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School-Baystate, Springfield, MA., Pack QR; Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School-Baystate, Springfield, MA.; University of Massachusetts Medical School-Baystate, Springfield, MA.; Division of Cardiology, Baystate Medical Center, Springfield, MA., Kashef MA; University of Massachusetts Medical School-Baystate, Springfield, MA.; Division of Cardiology, Baystate Medical Center, Springfield, MA., Atreya AR; University of Massachusetts Medical School-Baystate, Springfield, MA.; Division of Cardiology, Baystate Medical Center, Springfield, MA.; Frankel Cardiovascular Center, University of Michigan, Ann Arbor, MI., Valania G; University of Massachusetts Medical School-Baystate, Springfield, MA.; Division of Cardiology, Baystate Medical Center, Springfield, MA., Slawsky MT; University of Massachusetts Medical School-Baystate, Springfield, MA.; Division of Cardiology, Baystate Medical Center, Springfield, MA., Lindenauer PK; Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School-Baystate, Springfield, MA.; University of Massachusetts Medical School-Baystate, Springfield, MA.; Department of Medicine, Baystate Medical Center, Springfield, MA.
Jazyk: angličtina
Zdroj: Journal of the American Heart Association [J Am Heart Assoc] 2018 Feb 08; Vol. 7 (4). Date of Electronic Publication: 2018 Feb 08.
DOI: 10.1161/JAHA.116.005256
Abstrakt: Background: Comparing heart failure (HF) outcomes across hospitals requires adequate risk adjustment. We aimed to develop and validate a model that can be used to compare quality of HF care across hospitals.
Methods and Results: We included patients with HF aged ≥18 years admitted to one of 433 hospitals that participated in the Premier Inc Data Warehouse. This model (Premier) contained patient demographics, comorbidities, and acute conditions present on admission, derived from administrative and billing records. In a separate data set derived from electronic health records, we validated the Premier model by comparing hospital risk-standardized mortality rates calculated with the Premier model to those calculated with a validated clinical model containing laboratory data (LAPS [Laboratory-Based Acute Physiology Score]). Among the 200 832 admissions in the Premier Inc Data Warehouse, inpatient mortality was 4.0%. The model showed acceptable discrimination in the warehouse data (C statistic 0.75; 95% confidence interval, 0.74-0.76). In the validation data set, both the Premier model and the LAPS models showed acceptable discrimination (C statistic: Premier: 0.76 [95% confidence interval, 0.74-0.77]; LAPS: 0.78 [95% confidence interval, 0.76-0.80]). Risk-standardized mortality rates for both models ranged from 2% to 7%. A linear regression equation describing the association between Premier- and LAPS-specific mortality rates revealed a regression line with a slope of 0.71 (SE: 0.07). The correlation coefficient of the standardized mortality rates from the 2 models was 0.82.
Conclusions: Compared with a validated model derived from clinical data, an HF mortality model derived from administrative data showed highly correlated risk-standardized mortality rate estimates, suggesting it could be used to identify high- and low-performing hospitals for HF care.
(© 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.)
Databáze: MEDLINE
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