Literature DB >> 16945465

Hospital-wide physiological surveillance-a new approach to the early identification and management of the sick patient.

Gary B Smith1, David R Prytherch, Paul Schmidt, Peter I Featherstone, Debbie Knight, Gill Clements, Mohammed A Mohammed.   

Abstract

Hospitalised patients, who suffer cardiac arrest and require unanticipated intensive care unit (ICU) admission or die, often exhibit premonitory abnormalities in vital signs. Sometimes, the deterioration is well documented, though there is little discernable evidence of intervention. In other cases, monitoring and recording of vital signs is infrequent or incomplete. Healthcare providers have introduced "track and trigger" systems to allow early identification of patients with physiological abnormalities, and rapid response teams to facilitate rapid and appropriate management. However, even when "track and trigger" systems are used, the recording of vital signs, patient chart completion and team activation remain sub-optimal. We have developed a system for collecting routine vital signs data at the bedside using standard personal digital assistants (PDA). The PDAs act as "thin clients" linked by a wireless local area network (W-LAN) to the hospital's intranet system, where raw and derived data are integrated with other patient information, e.g., name, hospital number, laboratory results. It is possible for raw physiology data, early warning scores (EWS), vital signs charts and oxygen therapy records to be made instantaneously available to any member of the hospital healthcare team via the W-LAN or hospital intranet. Early and direct contact with members of the patient's primary clinical team or rapid response team can be made through an automated alerting system, triggered by the EWS data. The ability to capture physiological data at the bedside, and to make these available to anyone with appropriate access rights at any time and in any place, should provide previously unattainable, clinical and administrative benefits. Analysis of the raw physiological data and patient outcomes will also make it possible to validate existing and future "track and trigger" systems.

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Year:  2006        PMID: 16945465     DOI: 10.1016/j.resuscitation.2006.03.008

Source DB:  PubMed          Journal:  Resuscitation        ISSN: 0300-9572            Impact factor:   5.262


  33 in total

1.  Computer-aided National Early Warning Score to predict the risk of sepsis following emergency medical admission to hospital: a model development and external validation study.

Authors:  Muhammad Faisal; Donald Richardson; Andrew J Scally; Robin Howes; Kevin Beatson; Kevin Speed; Mohammed A Mohammed
Journal:  CMAJ       Date:  2019-04-08       Impact factor: 8.262

Review 2.  Health technology assessment review: remote monitoring of vital signs--current status and future challenges.

Authors:  Vishal Nangalia; David R Prytherch; Gary B Smith
Journal:  Crit Care       Date:  2010-09-24       Impact factor: 9.097

Review 3.  Monitoring cardiorespiratory instability: Current approaches and implications for nursing practice.

Authors:  Eliezer Bose; Leslie Hoffman; Marilyn Hravnak
Journal:  Intensive Crit Care Nurs       Date:  2016-02-28       Impact factor: 3.072

4.  Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.

Authors:  B R Matam; Heather Duncan; David Lowe
Journal:  J Clin Monit Comput       Date:  2018-09-27       Impact factor: 2.502

5.  The National Early Warning Score and its subcomponents recorded within ±24 h of emergency medical admission are poor predictors of hospital-acquired acute kidney injury.

Authors:  Muhammad Faisal; Andy Scally; Musab Ahmed Elgaali; Donald Richardson; Kevin Beatson; Mohammed A Mohammed
Journal:  Clin Med (Lond)       Date:  2018-02       Impact factor: 2.659

6.  Automated detection of physiologic deterioration in hospitalized patients.

Authors:  R Scott Evans; Kathryn G Kuttler; Kathy J Simpson; Stephen Howe; Peter F Crossno; Kyle V Johnson; Misty N Schreiner; James F Lloyd; William H Tettelbach; Roger K Keddington; Alden Tanner; Chelbi Wilde; Terry P Clemmer
Journal:  J Am Med Inform Assoc       Date:  2014-08-27       Impact factor: 4.497

7.  A stochastic model of acute-care decisions based on patient and provider heterogeneity.

Authors:  Muge Capan; Julie S Ivy; James R Wilson; Jeanne M Huddleston
Journal:  Health Care Manag Sci       Date:  2015-10-21

8.  A ward-based time study of paper and electronic documentation for recording vital sign observations.

Authors:  David Wong; Timothy Bonnici; Julia Knight; Stephen Gerry; James Turton; Peter Watkinson
Journal:  J Am Med Inform Assoc       Date:  2017-07-01       Impact factor: 4.497

Review 9.  Trends in postpartum hemorrhage in high resource countries: a review and recommendations from the International Postpartum Hemorrhage Collaborative Group.

Authors:  Marian Knight; William M Callaghan; Cynthia Berg; Sophie Alexander; Marie-Helene Bouvier-Colle; Jane B Ford; K S Joseph; Gwyneth Lewis; Robert M Liston; Christine L Roberts; Jeremy Oats; James Walker
Journal:  BMC Pregnancy Childbirth       Date:  2009-11-27       Impact factor: 3.007

10.  Index blood tests and national early warning scores within 24 hours of emergency admission can predict the risk of in-hospital mortality: a model development and validation study.

Authors:  Mohammed A Mohammed; Gavin Rudge; Duncan Watson; Gordon Wood; Gary B Smith; David R Prytherch; Alan Girling; Andrew Stevens
Journal:  PLoS One       Date:  2013-05-29       Impact factor: 3.240

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