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Mortality risks associated with emergency admissions during weekends and public holidays: an analysis of electronic health records

BACKGROUND: Weekend hospital admission is associated with increased mortality, but the contributions of varying illness severity and admission time to this weekend effect remain unexplored. METHODS: We analysed unselected emergency admissions to four Oxford University National Health Service hospita...

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Autores principales: Walker, A Sarah, Mason, Amy, Quan, T Phuong, Fawcett, Nicola J, Watkinson, Peter, Llewelyn, Martin, Stoesser, Nicole, Finney, John, Davies, Jim, Wyllie, David H, Crook, Derrick W, Peto, Tim E A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5494289/
https://www.ncbi.nlm.nih.gov/pubmed/28499548
http://dx.doi.org/10.1016/S0140-6736(17)30782-1
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author Walker, A Sarah
Mason, Amy
Quan, T Phuong
Fawcett, Nicola J
Watkinson, Peter
Llewelyn, Martin
Stoesser, Nicole
Finney, John
Davies, Jim
Wyllie, David H
Crook, Derrick W
Peto, Tim E A
author_facet Walker, A Sarah
Mason, Amy
Quan, T Phuong
Fawcett, Nicola J
Watkinson, Peter
Llewelyn, Martin
Stoesser, Nicole
Finney, John
Davies, Jim
Wyllie, David H
Crook, Derrick W
Peto, Tim E A
author_sort Walker, A Sarah
collection PubMed
description BACKGROUND: Weekend hospital admission is associated with increased mortality, but the contributions of varying illness severity and admission time to this weekend effect remain unexplored. METHODS: We analysed unselected emergency admissions to four Oxford University National Health Service hospitals in the UK from Jan 1, 2006, to Dec 31, 2014. The primary outcome was death within 30 days of admission (in or out of hospital), analysed using Cox models measuring time from admission. The primary exposure was day of the week of admission. We adjusted for multiple confounders including demographics, comorbidities, and admission characteristics, incorporating non-linearity and interactions. Models then considered the effect of adjusting for 15 common haematology and biochemistry test results or proxies for hospital workload. FINDINGS: 257 596 individuals underwent 503 938 emergency admissions. 18 313 (4·7%) patients admitted as weekday energency admissions and 6070 (5·1%) patients admitted as weekend emergency admissions died within 30 days (p<0·0001). 9347 individuals underwent 9707 emergency admissions on public holidays. 559 (5·8%) died within 30 days (p<0·0001 vs weekday). 15 routine haematology and biochemistry test results were highly prognostic for mortality. In 271 465 (53·9%) admissions with complete data, adjustment for test results explained 33% (95% CI 21 to 70) of the excess mortality associated with emergency admission on Saturdays compared with Wednesdays, 52% (lower 95% CI 34) on Sundays, and 87% (lower 95% CI 45) on public holidays after adjustment for standard patient characteristics. Excess mortality was predominantly restricted to admissions between 1100 h and 1500 h (p(interaction)=0·04). No hospital workload measure was independently associated with mortality (all p values >0·06). INTERPRETATION: Adjustment for routine test results substantially reduced excess mortality associated with emergency admission at weekends and public holidays. Adjustment for patient-level factors not available in our study might further reduce the residual excess mortality, particularly as this clustered around midday at weekends. Hospital workload was not associated with mortality. Together, these findings suggest that the weekend effect arises from patient-level differences at admission rather than reduced hospital staffing or services. FUNDING: NIHR Oxford Biomedical Research Centre.
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spelling pubmed-54942892017-07-13 Mortality risks associated with emergency admissions during weekends and public holidays: an analysis of electronic health records Walker, A Sarah Mason, Amy Quan, T Phuong Fawcett, Nicola J Watkinson, Peter Llewelyn, Martin Stoesser, Nicole Finney, John Davies, Jim Wyllie, David H Crook, Derrick W Peto, Tim E A Lancet Articles BACKGROUND: Weekend hospital admission is associated with increased mortality, but the contributions of varying illness severity and admission time to this weekend effect remain unexplored. METHODS: We analysed unselected emergency admissions to four Oxford University National Health Service hospitals in the UK from Jan 1, 2006, to Dec 31, 2014. The primary outcome was death within 30 days of admission (in or out of hospital), analysed using Cox models measuring time from admission. The primary exposure was day of the week of admission. We adjusted for multiple confounders including demographics, comorbidities, and admission characteristics, incorporating non-linearity and interactions. Models then considered the effect of adjusting for 15 common haematology and biochemistry test results or proxies for hospital workload. FINDINGS: 257 596 individuals underwent 503 938 emergency admissions. 18 313 (4·7%) patients admitted as weekday energency admissions and 6070 (5·1%) patients admitted as weekend emergency admissions died within 30 days (p<0·0001). 9347 individuals underwent 9707 emergency admissions on public holidays. 559 (5·8%) died within 30 days (p<0·0001 vs weekday). 15 routine haematology and biochemistry test results were highly prognostic for mortality. In 271 465 (53·9%) admissions with complete data, adjustment for test results explained 33% (95% CI 21 to 70) of the excess mortality associated with emergency admission on Saturdays compared with Wednesdays, 52% (lower 95% CI 34) on Sundays, and 87% (lower 95% CI 45) on public holidays after adjustment for standard patient characteristics. Excess mortality was predominantly restricted to admissions between 1100 h and 1500 h (p(interaction)=0·04). No hospital workload measure was independently associated with mortality (all p values >0·06). INTERPRETATION: Adjustment for routine test results substantially reduced excess mortality associated with emergency admission at weekends and public holidays. Adjustment for patient-level factors not available in our study might further reduce the residual excess mortality, particularly as this clustered around midday at weekends. Hospital workload was not associated with mortality. Together, these findings suggest that the weekend effect arises from patient-level differences at admission rather than reduced hospital staffing or services. FUNDING: NIHR Oxford Biomedical Research Centre. Elsevier 2017-07-01 /pmc/articles/PMC5494289/ /pubmed/28499548 http://dx.doi.org/10.1016/S0140-6736(17)30782-1 Text en © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Articles
Walker, A Sarah
Mason, Amy
Quan, T Phuong
Fawcett, Nicola J
Watkinson, Peter
Llewelyn, Martin
Stoesser, Nicole
Finney, John
Davies, Jim
Wyllie, David H
Crook, Derrick W
Peto, Tim E A
Mortality risks associated with emergency admissions during weekends and public holidays: an analysis of electronic health records
title Mortality risks associated with emergency admissions during weekends and public holidays: an analysis of electronic health records
title_full Mortality risks associated with emergency admissions during weekends and public holidays: an analysis of electronic health records
title_fullStr Mortality risks associated with emergency admissions during weekends and public holidays: an analysis of electronic health records
title_full_unstemmed Mortality risks associated with emergency admissions during weekends and public holidays: an analysis of electronic health records
title_short Mortality risks associated with emergency admissions during weekends and public holidays: an analysis of electronic health records
title_sort mortality risks associated with emergency admissions during weekends and public holidays: an analysis of electronic health records
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5494289/
https://www.ncbi.nlm.nih.gov/pubmed/28499548
http://dx.doi.org/10.1016/S0140-6736(17)30782-1
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