An Update to the Kaiser Permanente Inpatient Risk Adjustment Methodology Accurately Predicts In-Hospital Mortality: a Retrospective Cohort Study
Author:
Publisher
Springer Science and Business Media LLC
Subject
Internal Medicine
Link
https://link.springer.com/content/pdf/10.1007/s11606-023-08245-w.pdf
Reference39 articles.
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2. Escobar GJ, Gardner MN, Greene JD, Draper D, Kipnis P. Risk-Adjusting Hospital Mortality Using a Comprehensive Electronic Record in an Integrated Health Care Delivery System. Med Care 2013;51:446–53. https://doi.org/10.1097/MLR.0B013E3182881C8E.
3. Van Walraven C, Wong J, Bennett C, Forster AJ. The Procedural Index for Mortality Risk (PIMR): an Index Calculated Using Administrative Data to Quantify the Independent Influence of Procedures on Risk of Hospital Death. BMC Health Serv Res 2011;11:1–11. https://doi.org/10.1186/1472-6963-11-258/TABLES/5.
4. Liu V, Kipnis P, Gould MK, Escobar GJ. Length of Stay Predictions: Improvements Through the Use of Automated Laboratory and Comorbidity Variables. Med Care 2010;48:739–44. https://doi.org/10.1097/MLR.0B013E3181E359F3.
5. Lagu T, Pekow PS, Shieh MS, Stefan M, Pack QR, Kashef MA, et al. Validation and Comparison of Seven Mortality Prediction Models for Hospitalized Patients With Acute Decompensated Heart Failure. Circ Heart Fail 2016;9. https://doi.org/10.1161/CIRCHEARTFAILURE.115.002912.
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