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Defining and measuring suspicion of sepsis: an analysis of routine data
OBJECTIVES: To define the target population of patients who have suspicion of sepsis (SOS) and to provide a basis for assessing the burden of SOS, and the evaluation of sepsis guidelines and improvement programmes. DESIGN: Retrospective analysis of routinely collected hospital administrative data. S...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5734411/ https://www.ncbi.nlm.nih.gov/pubmed/28601825 http://dx.doi.org/10.1136/bmjopen-2016-014885 |
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author | Inada-Kim, Matthew Page, Bethan Maqsood, Imran Vincent, Charles |
author_facet | Inada-Kim, Matthew Page, Bethan Maqsood, Imran Vincent, Charles |
author_sort | Inada-Kim, Matthew |
collection | PubMed |
description | OBJECTIVES: To define the target population of patients who have suspicion of sepsis (SOS) and to provide a basis for assessing the burden of SOS, and the evaluation of sepsis guidelines and improvement programmes. DESIGN: Retrospective analysis of routinely collected hospital administrative data. SETTING: Secondary care, eight National Health Service (NHS) Acute Trusts. PARTICIPANTS: Hospital Episode Statistics data for 2013–2014 was used to identify all admissions with a primary diagnosis listed in the ‘suspicion of sepsis’ (SOS) coding set. The SOS coding set consists of all bacterial infective diagnoses. RESULTS: We identified 47 475 admissions with SOS, equivalent to a rate of 17 admissions per 1000 adults in a given year. The mortality for this group was 7.2% during their acute hospital admission. Urinary tract infection was the most common diagnosis and lobar pneumonia was associated with the most deaths. A short list of 10 diagnoses can account for 85% of the deaths. CONCLUSIONS: Patients with SOS can be identified in routine administrative data. It is these patients who should be screened for sepsis and are the target of programmes to improve the detection and treatment of sepsis. The effectiveness of such programmes can be evaluated by examining the outcomes of patients with SOS. |
format | Online Article Text |
id | pubmed-5734411 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-57344112017-12-20 Defining and measuring suspicion of sepsis: an analysis of routine data Inada-Kim, Matthew Page, Bethan Maqsood, Imran Vincent, Charles BMJ Open Infectious Diseases OBJECTIVES: To define the target population of patients who have suspicion of sepsis (SOS) and to provide a basis for assessing the burden of SOS, and the evaluation of sepsis guidelines and improvement programmes. DESIGN: Retrospective analysis of routinely collected hospital administrative data. SETTING: Secondary care, eight National Health Service (NHS) Acute Trusts. PARTICIPANTS: Hospital Episode Statistics data for 2013–2014 was used to identify all admissions with a primary diagnosis listed in the ‘suspicion of sepsis’ (SOS) coding set. The SOS coding set consists of all bacterial infective diagnoses. RESULTS: We identified 47 475 admissions with SOS, equivalent to a rate of 17 admissions per 1000 adults in a given year. The mortality for this group was 7.2% during their acute hospital admission. Urinary tract infection was the most common diagnosis and lobar pneumonia was associated with the most deaths. A short list of 10 diagnoses can account for 85% of the deaths. CONCLUSIONS: Patients with SOS can be identified in routine administrative data. It is these patients who should be screened for sepsis and are the target of programmes to improve the detection and treatment of sepsis. The effectiveness of such programmes can be evaluated by examining the outcomes of patients with SOS. BMJ Publishing Group 2017-06-09 /pmc/articles/PMC5734411/ /pubmed/28601825 http://dx.doi.org/10.1136/bmjopen-2016-014885 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Infectious Diseases Inada-Kim, Matthew Page, Bethan Maqsood, Imran Vincent, Charles Defining and measuring suspicion of sepsis: an analysis of routine data |
title | Defining and measuring suspicion of sepsis: an analysis of routine data |
title_full | Defining and measuring suspicion of sepsis: an analysis of routine data |
title_fullStr | Defining and measuring suspicion of sepsis: an analysis of routine data |
title_full_unstemmed | Defining and measuring suspicion of sepsis: an analysis of routine data |
title_short | Defining and measuring suspicion of sepsis: an analysis of routine data |
title_sort | defining and measuring suspicion of sepsis: an analysis of routine data |
topic | Infectious Diseases |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5734411/ https://www.ncbi.nlm.nih.gov/pubmed/28601825 http://dx.doi.org/10.1136/bmjopen-2016-014885 |
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