Associations between patient and system characteristics and MET review within 48 h of admission to a teaching hospital: A retrospective cohort study.


Deakin University, Centre for Quality and Patient Safety Research, School of Nursing and Midwifery, Faculty of Health, Geelong, VIC 3220, Australia. Electronic address: [Email]


The Medical Emergency Team (MET) has enhanced the recognition and response to clinical deterioration in acute healthcare. However, patients reviewed by the MET are at increased risk of in-hospital death. Identifying patients at risk of deterioration may improve patient outcomes. AIM: To identify patient demographic, medical characteristics and healthcare systems and processes at the time of admission (baseline), associated with Medical Emergency Team (MET) review within 48 h (MET-48 h) of admission. METHODS: Single-site, year-long, retrospective cohort comprising patients admitted for at least 24 h, using routinely collected hospital data. A three-stage modelling approach was used to identify baseline factors associated with MET-48 h RESULTS: The study included 15,695 patients with mean age 62.1 years (SD 19.6), male (53.5%), born in Australia or New Zealand (60.9%) and 51.6% held a low-income concession card. A total of 4.3% of patients received a MET review within 48 h of admission. Variables independently associated with MET-48 h in a fully adjusted logistic model included age of 80 years or more (OR = 1.37); ≥3 previous emergency admissions (OR = 1.59); Charlson Comorbidity Index 1 or 2 (OR = 1.47), or ≥ 3 (OR = 1.99); history of alcohol-related behaviour concerns (OR = 2.04), chronic heart failure (OR = 1.48); chronic obstructive pulmonary disease (OR = 1.35); admission for colorectal (OR = 2.66) or upper gastro-intestinal (OR = 1.94) surgery, respiratory or tracheostomy (OR = 2.24); immunology and infections (OR = 1.90); emergency admission (OR = 1.36); admission at night (OR = 1.74), or summer (OR = 1.41) CONCLUSIONS: This is the first study to demonstrate the potential to predict clinical deterioration using data that is readily accessible at the time of admission to hospital.