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Sepsis Among Medicare Beneficiaries: 3. The Methods, Models, and Forecasts of Sepsis, 2012–2018*
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 c...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7017950/ https://www.ncbi.nlm.nih.gov/pubmed/32058368 http://dx.doi.org/10.1097/CCM.0000000000004225 |
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author | Buchman, Timothy G. Simpson, Steven Q. Sciarretta, Kimberly L. Finne, Kristen P. Sowers, Nicole Collier, Michael Chavan, Saurabh Oke, Ibijoke Pennini, Meghan E. Santhosh, Aathira Wax, Marie Woodbury, Robyn Chu, Steve Merkeley, Tyler G. Disbrow, Gary L. Bright, Rick A. MaCurdy, Thomas E. Kelman, Jeffrey A. |
author_facet | Buchman, Timothy G. Simpson, Steven Q. Sciarretta, Kimberly L. Finne, Kristen P. Sowers, Nicole Collier, Michael Chavan, Saurabh Oke, Ibijoke Pennini, Meghan E. Santhosh, Aathira Wax, Marie Woodbury, Robyn Chu, Steve Merkeley, Tyler G. Disbrow, Gary L. Bright, Rick A. MaCurdy, Thomas E. Kelman, Jeffrey A. |
author_sort | Buchman, Timothy G. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7017950 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-70179502020-03-10 Sepsis Among Medicare Beneficiaries: 3. The Methods, Models, and Forecasts of Sepsis, 2012–2018* Buchman, Timothy G. Simpson, Steven Q. Sciarretta, Kimberly L. Finne, Kristen P. Sowers, Nicole Collier, Michael Chavan, Saurabh Oke, Ibijoke Pennini, Meghan E. Santhosh, Aathira Wax, Marie Woodbury, Robyn Chu, Steve Merkeley, Tyler G. Disbrow, Gary L. Bright, Rick A. MaCurdy, Thomas E. Kelman, Jeffrey A. Crit Care Med Late Breaker Articles 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. Lippincott Williams & Wilkins 2020-03 2020-02-13 /pmc/articles/PMC7017950/ /pubmed/32058368 http://dx.doi.org/10.1097/CCM.0000000000004225 Text en Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government. |
spellingShingle | Late Breaker Articles Buchman, Timothy G. Simpson, Steven Q. Sciarretta, Kimberly L. Finne, Kristen P. Sowers, Nicole Collier, Michael Chavan, Saurabh Oke, Ibijoke Pennini, Meghan E. Santhosh, Aathira Wax, Marie Woodbury, Robyn Chu, Steve Merkeley, Tyler G. Disbrow, Gary L. Bright, Rick A. MaCurdy, Thomas E. Kelman, Jeffrey A. Sepsis Among Medicare Beneficiaries: 3. The Methods, Models, and Forecasts of Sepsis, 2012–2018* |
title | Sepsis Among Medicare Beneficiaries: 3. The Methods, Models, and Forecasts of Sepsis, 2012–2018* |
title_full | Sepsis Among Medicare Beneficiaries: 3. The Methods, Models, and Forecasts of Sepsis, 2012–2018* |
title_fullStr | Sepsis Among Medicare Beneficiaries: 3. The Methods, Models, and Forecasts of Sepsis, 2012–2018* |
title_full_unstemmed | Sepsis Among Medicare Beneficiaries: 3. The Methods, Models, and Forecasts of Sepsis, 2012–2018* |
title_short | Sepsis Among Medicare Beneficiaries: 3. The Methods, Models, and Forecasts of Sepsis, 2012–2018* |
title_sort | sepsis among medicare beneficiaries: 3. the methods, models, and forecasts of sepsis, 2012–2018* |
topic | Late Breaker Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7017950/ https://www.ncbi.nlm.nih.gov/pubmed/32058368 http://dx.doi.org/10.1097/CCM.0000000000004225 |
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