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Validation of autom...
Validation of automated sepsis surveillance based on the Sepsis-3 clinical criteria against physician record review in a general hospital population : observational study using electronic health records data
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- Karlsson Valik, John (författare)
- Karolinska Institutet
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Ward, Logan (författare)
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- Tanushi, Hideyuki (författare)
- Karolinska Institutet
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Müllersdorf, Kajsa (författare)
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- Ternhag, Anders (författare)
- Karolinska Institutet
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Aufwerber, Ewa (författare)
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- Färnert, Anna (författare)
- Karolinska Institutet
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- Johansson, Anders, 1966- (författare)
- Umeå universitet,Molekylär Infektionsmedicin, Sverige (MIMS)
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Lause Mogensen, Mads (författare)
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Pickering, Brian (författare)
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- Dalianis, Hercules (författare)
- Stockholms universitet,Institutionen för data- och systemvetenskap
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- Henriksson, Aron (författare)
- Stockholms universitet,Institutionen för data- och systemvetenskap
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Herasevich, Vitaly (författare)
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- Nauclér, Pontus (författare)
- Karolinska Institutet
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(creator_code:org_t)
- 2020-02-06
- 2020
- Engelska.
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Ingår i: BMJ Quality and Safety. - : BMJ Publishing Group Ltd. - 2044-5415 .- 2044-5423. ; 29:9, s. 735-745
- Relaterad länk:
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https://doi.org/10.1...
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https://umu.diva-por... (primary) (Raw object)
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https://qualitysafet...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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http://kipublication...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- Background: Surveillance of sepsis incidence is important for directing resources and evaluating quality-of-care interventions. The aim was to develop and validate a fully-automated Sepsis-3 based surveillance system in non-intensive care wards using electronic health record (EHR) data, and demonstrate utility by determining the burden of hospital-onset sepsis and variations between wards.Methods: A rule-based algorithm was developed using EHR data from a cohort of all adult patients admitted at an academic centre between July 2012 and December 2013. Time in intensive care units was censored. To validate algorithm performance, a stratified random sample of 1000 hospital admissions (674 with and 326 without suspected infection) was classified according to the Sepsis-3 clinical criteria (suspected infection defined as having any culture taken and at least two doses of antimicrobials administered, and an increase in Sequential Organ Failure Assessment (SOFA) score by >2 points) and the likelihood of infection by physician medical record review.Results: In total 82 653 hospital admissions were included. The Sepsis-3 clinical criteria determined by physician review were met in 343 of 1000 episodes. Among them, 313 (91%) had possible, probable or definite infection. Based on this reference, the algorithm achieved sensitivity 0.887 (95% CI: 0.799 to 0.964), specificity 0.985 (95% CI: 0.978 to 0.991), positive predictive value 0.881 (95% CI: 0.833 to 0.926) and negative predictive value 0.986 (95% CI: 0.973 to 0.996). When applied to the total cohort taking into account the sampling proportions of those with and without suspected infection, the algorithm identified 8599 (10.4%) sepsis episodes. The burden of hospital-onset sepsis (>48 hour after admission) and related in-hospital mortality varied between wards.Conclusions: A fully-automated Sepsis-3 based surveillance algorithm using EHR data performed well compared with physician medical record review in non-intensive care wards, and exposed variations in hospital-onset sepsis incidence between wards.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Infektionsmedicin (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Infectious Medicine (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Information Systems (hsv//eng)
Nyckelord
- adverse events
- epidemiology and detection
- critical care
- nosocomial infections
- information technology
- continuous quality improvement
- Computer and Systems Sciences
Publikations- och innehållstyp
- ref (ämneskategori)
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Karlsson Valik, ...
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Ward, Logan
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Tanushi, Hideyuk ...
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Müllersdorf, Kaj ...
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Ternhag, Anders
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Aufwerber, Ewa
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visa fler...
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Färnert, Anna
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Johansson, Ander ...
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Lause Mogensen, ...
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Pickering, Brian
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Dalianis, Hercul ...
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Henriksson, Aron
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Herasevich, Vita ...
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Nauclér, Pontus
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visa färre...
- Om ämnet
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- MEDICIN OCH HÄLSOVETENSKAP
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MEDICIN OCH HÄLS ...
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och Klinisk medicin
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och Infektionsmedici ...
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- NATURVETENSKAP
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NATURVETENSKAP
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och Data och informa ...
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och Systemvetenskap ...
- Artiklar i publikationen
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BMJ Quality and ...
- Av lärosätet
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Umeå universitet
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Karolinska Institutet
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Stockholms universitet