To catch a killer: electronic sepsis alert tools reaching a fever pitch?
作者信息
Ruppel Halley, Liu Vincent
机构信息
Systems Research Initiative, Kaiser Permanente Division of Research, Oakland, California, USA.
Systems Research Initiative, Kaiser Permanente Division of Research, Oakland, California, USA
出版信息
BMJ Qual Saf. 2019 Sep;28(9):693-696. doi: 10.1136/bmjqs-2019-009463. Epub 2019 Apr 23.
Abstract
摘要
相似文献
1
To catch a killer: electronic sepsis alert tools reaching a fever pitch?
BMJ Qual Saf. 2019 Sep;28(9):693-696. doi: 10.1136/bmjqs-2019-009463. Epub 2019 Apr 23.
2
Validation of Test Performance and Clinical Time Zero for an Electronic Health Record Embedded Severe Sepsis Alert.
Appl Clin Inform. 2016 Jun 22;7(2):560-72. doi: 10.4338/ACI-2015-11-RA-0159. eCollection 2016.
3
Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.
Acad Emerg Med. 2016 Mar;23(3):269-78. doi: 10.1111/acem.12876. Epub 2016 Feb 13.
4
Testing modes of computerized sepsis alert notification delivery systems.
BMC Med Inform Decis Mak. 2016 Dec 9;16(1):156. doi: 10.1186/s12911-016-0396-y.
5
Medical alert management: a real-time adaptive decision support tool to reduce alert fatigue.
AMIA Annu Symp Proc. 2014 Nov 14;2014:845-54. eCollection 2014.
6
Diagnostic accuracy of a screening electronic alert tool for severe sepsis and septic shock in the emergency department.
BMC Med Inform Decis Mak. 2014 Dec 5;14:105. doi: 10.1186/s12911-014-0105-7.
7
A machine learning approach for predicting urine output after fluid administration.
Comput Methods Programs Biomed. 2019 Aug;177:155-159. doi: 10.1016/j.cmpb.2019.05.009. Epub 2019 May 13.
8
The Nature and Variability of Automated Practice Alerts Derived from Electronic Health Records in a U.S. Nationwide Critical Care Research Network.
Ann Am Thorac Soc. 2016 Oct;13(10):1784-1788. doi: 10.1513/AnnalsATS.201603-172BC.
9
Interoperability of clinical decision-support systems and electronic health records using archetypes: a case study in clinical trial eligibility.
J Biomed Inform. 2013 Aug;46(4):676-89. doi: 10.1016/j.jbi.2013.05.004. Epub 2013 May 22.
10
Monitoring clinical decision support in the electronic health record.
Am J Health Syst Pharm. 2017 Aug 1;74(15):1130-1133. doi: 10.2146/ajhp160819.
引用本文的文献
1
Views and Uses of Sepsis Digital Alerts in National Health Service Trusts in England: Qualitative Study With Health Care Professionals.
JMIR Hum Factors. 2024 Oct 15;11:e56949. doi: 10.2196/56949.
2
Human-machine teaming is key to AI adoption: clinicians' experiences with a deployed machine learning system.
NPJ Digit Med. 2022 Jul 21;5(1):97. doi: 10.1038/s41746-022-00597-7.
3
Electronic nudge tool technology used in the critical care and peri-anaesthetic setting: a scoping review protocol.
BMJ Open. 2022 Jul 12;12(7):e057026. doi: 10.1136/bmjopen-2021-057026.
4
The Role of Genome Sequencing in Neonatal Intensive Care Units.
Annu Rev Genomics Hum Genet. 2022 Aug 31;23:427-448. doi: 10.1146/annurev-genom-120921-103442. Epub 2022 Jun 8.
5
Design and Implementation of a Real-time Monitoring Platform for Optimal Sepsis Care in an Emergency Department: Observational Cohort Study.
J Med Internet Res. 2021 Jun 24;23(6):e26946. doi: 10.2196/26946.
6
Early Detection of Sepsis With Machine Learning Techniques: A Brief Clinical Perspective.
Front Med (Lausanne). 2021 Feb 12;8:617486. doi: 10.3389/fmed.2021.617486. eCollection 2021.
7
Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials.
BMJ. 2020 Sep 17;370:m3216. doi: 10.1136/bmj.m3216.
8
Postimplementation Evaluation of a Machine Learning-Based Deterioration Risk Alert to Enhance Sepsis Outcome Improvements.
Nurs Adm Q. 2020 Oct/Dec;44(4):336-346. doi: 10.1097/NAQ.0000000000000438.
9
Comparison of Automated Sepsis Identification Methods and Electronic Health Record-based Sepsis Phenotyping: Improving Case Identification Accuracy by Accounting for Confounding Comorbid Conditions.
Crit Care Explor. 2019 Oct 30;1(10):e0053. doi: 10.1097/CCE.0000000000000053. eCollection 2019 Oct.
10
Evaluating a digital sepsis alert in a London multisite hospital network: a natural experiment using electronic health record data.
J Am Med Inform Assoc. 2020 Feb 1;27(2):274-283. doi: 10.1093/jamia/ocz186.
本文引用的文献
1
Electronic health record-based clinical decision support alert for severe sepsis: a randomised evaluation.
BMJ Qual Saf. 2019 Sep;28(9):762-768. doi: 10.1136/bmjqs-2018-008765. Epub 2019 Mar 14.
2
Epidemiology and Costs of Sepsis in the United States-An Analysis Based on Timing of Diagnosis and Severity Level.
Crit Care Med. 2018 Dec;46(12):1889-1897. doi: 10.1097/CCM.0000000000003342.
3
Automated monitoring compared to standard care for the early detection of sepsis in critically ill patients.
Cochrane Database Syst Rev. 2018 Jun 25;6(6):CD012404. doi: 10.1002/14651858.CD012404.pub2.
4
Big Data and Machine Learning in Health Care.
JAMA. 2018 Apr 3;319(13):1317-1318. doi: 10.1001/jama.2017.18391.
5
Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial.
BMJ Open Respir Res. 2017 Nov 9;4(1):e000234. doi: 10.1136/bmjresp-2017-000234. eCollection 2017.
6
Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU.
BMJ Open. 2018 Jan 26;8(1):e017833. doi: 10.1136/bmjopen-2017-017833.
7
What This Computer Needs Is a Physician: Humanism and Artificial Intelligence.
JAMA. 2018 Jan 2;319(1):19-20. doi: 10.1001/jama.2017.19198.
8
Discrimination and Calibration of Clinical Prediction Models: Users' Guides to the Medical Literature.
JAMA. 2017 Oct 10;318(14):1377-1384. doi: 10.1001/jama.2017.12126.
9
Incidence and Trends of Sepsis in US Hospitals Using Clinical vs Claims Data, 2009-2014.
JAMA. 2017 Oct 3;318(13):1241-1249. doi: 10.1001/jama.2017.13836.
10
Combining Biomarkers with EMR Data to Identify Patients in Different Phases of Sepsis.
Sci Rep. 2017 Sep 7;7(1):10800. doi: 10.1038/s41598-017-09766-1.
Zotero 插件