Sepsis Among Medicare Beneficiaries: 3. The Methods, Models, and Forecasts of Sepsis, 2012-2018

• Type of Material: Article
• Authors: Timothy Buchman, Emory University; Steven Q. Simpson, U.S. Department of Health and Human Services; Kimberly L. Sciarretta, U.S. Department of Health and Human Services; Kristen P. Finne, U.S. Department of Health and Human Services; Nicole Sowers, Acumen LLC; Michael Collier, Acumen LLC; Saurabh Chavan, Acumen LLC; Ibijoke Oke, Acumen LLC; Meghan E. Pennini, U.S. Department of Health and Human Services; Aathira Santhosh, Acumen LLC; Marie Wax, U.S. Department of Health and Human Services; Robyn Woodbury, U.S. Department of Health and Human Services; Steve Chu, U.S. Department of Health and Human Services; Tyler G. Merkeley, U.S. Department of Health and Human Services; Gary L. Disbrow, U.S. Department of Health and Human Services; Rick A. Bright, U.S. Department of Health and Human Services; Thomas E. MaCurdy, Acumen LLC; Jeffrey A. Kelman, U.S. Department of Health and Human Services
• Language: English
• Date: 2020-03-01
• Publisher: Lippincott Williams & Wilkins
• Publication Version: Final Published Version
• Copyright Statement: © 2020 the Society of Critical Care Medicine and Wolters Kluwer Health, Inc.
• License: Creative Commons Universal : Public Domain Dedication
• Final Published Version (URL): http://dx.doi.org/10.1097/CCM.0000000000004225
• Title of Journal or Parent Work: Critical Care Medicine
• Volume: 48
• Issue: 3
• Start Page: 302
• End Page: 318
• Grant/Funding Information: None declared
• Keywords: models; United States; Life Sciences & Biomedicine; sepsis; forecast; methods; Influenza; General & Internal Medicine; Science & Technology; Critical Care Medicine
• Research Categories: Health Sciences, Health Care Management; Health Sciences, Medicine and Surgery; Health Sciences, Public Health

Abstract

Objective: To evaluate the impact of sepsis, age, and comorbidities on death following an acute inpatient admission and to model and forecast inpatient and skilled nursing facility costs for Medicare beneficiaries during and subsequent to an acute inpatient sepsis admission. Design: Analysis of paid Medicare claims via the Centers for Medicare & Medicaid Services DataLink Project (CMS) and leveraging the CMS-Hierarchical Condition Category risk adjustment model. Setting: All U.S. acute care hospitals, excepting federal hospitals (Veterans Administration and Defense Health Agency). Patients: All Part A/B (fee-for-service) Medicare beneficiaries with an acute inpatient admission in 2017 and who had no inpatient sepsis admission in the prior year. Interventions: None. Measurements and Main Results: Logistic regression models to determine covariate risk contribution to death following an acute inpatient admission; conventional regression to predict Medicare beneficiary sepsis costs. Using the Hierarchical Condition Category risk adjustment model to illuminate influence of illness on outcome of inpatient admissions, representative odds ratios (with 95% CIs) for death within 6 months of an admission (referenced to beneficiaries admitted but without the characteristic) are as follows: septic shock, 7.27 (7.19-7.35); metastatic cancer and acute leukemia (Hierarchical Condition Category 8), 6.76 (6.71-6.82); all sepsis, 2.63 (2.62-2.65); respiratory arrest (Hierarchical Condition Category 83), 2.55 (2.35-2.77); end-stage liver disease (Hierarchical Condition Category 27), 2.53 (2.49-2.56); and severe sepsis without shock, 2.48 (2.45-2.51). Models of the cost of sepsis care for Medicare beneficiaries forecast arise approximately 13% over 2 years owing the rising enrollments in Medicare offset by the cost of care per admission. Conclusions: A sepsis inpatient admission is associated with marked increase in risk of death that is comparable to the risks associated with inpatient admissions for other common and serious chronic illnesses. The aggregate costs of sepsis care for Medicare beneficiaries will continue to increase.