Literature DB >> 21644875

Clinical deterioration in the condition of patients with acute medical illness in Australian hospitals: improving detection and response.

Paul F Jenkins1, Campbell H Thompson, Lorna L Barton.   

Abstract

Medical Assessment Units (MAUs) provide an opportunity for multidisciplinary staff to manage recently admitted acutely unwell patients with complex medical illnesses. We propose concerted development of robust mechanisms for identifying and managing patients whose condition is unstable as they move through hospital departments. Track, trigger and response (TTR) systems (eg, medical emergency team calls and early warning scores) have been introduced to hospital practice, but evidence for their effectiveness is, so far, incomplete. The current variation in TTR systems within and between hospitals impairs intersite comparisons. A range of outcome measures, including risk of physiological deterioration, mortality and projected hospital length of stay, could be usefully investigated by future intersite collaborative research. More deliberate, systematic, evidence-based design of "response" in TTR systems may help in identifying patients who need early attention from skilled medical staff. We need more uniform TTR systems, more research on TTR systems and more multisite research; MAUs are ideally situated to address this important area.

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Year:  2011        PMID: 21644875

Source DB:  PubMed          Journal:  Med J Aust        ISSN: 0025-729X            Impact factor:   7.738


  3 in total

Review 1.  Risk stratification of hospitalized patients on the wards.

Authors:  Matthew M Churpek; Trevor C Yuen; Dana P Edelson
Journal:  Chest       Date:  2013-06       Impact factor: 9.410

2.  Using electronic health record data to develop and validate a prediction model for adverse outcomes in the wards*.

Authors:  Matthew M Churpek; Trevor C Yuen; Seo Young Park; Robert Gibbons; Dana P Edelson
Journal:  Crit Care Med       Date:  2014-04       Impact factor: 7.598

3.  Decision tree model for predicting in-hospital cardiac arrest among patients admitted with acute coronary syndrome.

Authors:  Hong Li; Ting Ting Wu; Dong Liang Yang; Yang Song Guo; Pei Chang Liu; Yuan Chen; Li Ping Xiao
Journal:  Clin Cardiol       Date:  2019-09-11       Impact factor: 2.882

  3 in total

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