Sepsis Among Medicare Beneficiaries: 3. The Methods, Models, and Forecasts of Sepsis, 2012-2018
Autor: | Kristen P Finne, Timothy G. Buchman, Gary L. Disbrow, Tyler G. Merkeley, Steven Q Simpson, Nicole Sowers, Aathira Santhosh, Robyn Woodbury, Michael Collier, Thomas E. MaCurdy, Steve Chu, Meghan E. Pennini, Ibijoke Oke, Kimberly L Sciarretta, Rick A Bright, Jeffrey A. Kelman, Marie Wax, Saurabh Chavan |
---|---|
Rok vydání: | 2020 |
Předmět: |
Male
medicine.medical_specialty forecast Psychological intervention Comorbidity Critical Care and Intensive Care Medicine Logistic regression Medicare Severity of Illness Index Centers for Medicare and Medicaid Services U.S Article Late Breaker Articles methods Sepsis models 03 medical and health sciences 0302 clinical medicine Acute care Medicine Humans Aged Aged 80 and over Acute leukemia Models Statistical business.industry Septic shock Age Factors 030208 emergency & critical care medicine Fee-for-Service Plans Odds ratio Health Services medicine.disease Shock Septic United States Hospitalization 030228 respiratory system Emergency medicine ComputingMethodologies_DOCUMENTANDTEXTPROCESSING Costs and Cost Analysis Quality of Life Medicare Part C Female Health Expenditures business Medicaid |
Zdroj: | Crit Care Med Critical Care Medicine |
ISSN: | 1530-0293 |
Popis: | Supplemental Digital Content is available in the text. 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. |
Databáze: | OpenAIRE |
Externí odkaz: |