Illness severity characteristics and outcomes of patients remaining on an acute ward following medical emergency team review: a latent profile analysis

Author:

Batterbury AnthonyORCID,Douglas ClintORCID,Jones LeeORCID,Coyer FionaORCID

Abstract

BackgroundPatients requiring medical emergency team (MET) review have complex clinical needs, and most remain on the ward after review. Current detection instruments cannot identify post-MET patient requirements, meaning patients remain undistinguished, potentially resulting in missed management opportunities. We propose that deteriorating patients will cluster along dimensions of illness severity and that these clusters may be used to strengthen patient risk management practices.ObjectiveTo identify and define the number of illness severity clusters and report outcomes among ward patients following MET review.Study design and settingThis retrospective cohort study examined the clinical records of 1500 adult ward patients following MET review at an Australian quaternary hospital. Three-step latent profile analysis methods were used to determine clusters using Sequential Organ Failure Assessment (SOFA) and Nursing Activities Score (NAS) as illness severity indicators. Study outcomes were (1) hospital mortality, (2) unplanned intensive care unit (ICU) admission and (3) subsequent MET review.ResultsPatients were unplanned (73.9%) and medical (57.5%) admissions with at least one comorbidity (51.4%), and complex combinations of acuity (SOFA range 1–17) and dependency (NAS range 22.4%–148.5%). Five clusters are reported. Patients in cluster 1 were equivalent to clinically stable general ward patients. Organ failure and complexity increased with cluster progression—clusters 2 and 3 were equivalent to subspecialty/higher-dependency wards, and clusters 4 and 5 were equivalent to ICUs. Patients in cluster 5 had the greatest odds for death (OR 26.2, 95% CI 23.3 to 31.3), unplanned ICU admission (OR 3.1, 95% CI 3.0 to 3.1) and subsequent MET review (OR 2.4, 95% CI 2.4 to 2.6).ConclusionThe five illness severity clusters may be used to define patients at risk of poorer outcomes who may benefit from enhanced levels of monitoring and targeted care.

Funder

State of Queensland Department of Health

Australian Commonwealth Research Training Programme

Publisher

BMJ

Subject

Health Policy

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