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Lancet. 2006 Dec 2;368(9551):1984-90.

Inpatient disposition classification for the creation of hospital surge capacity: a multiphase study.

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  • 1Department of Emergency Medicine, Johns Hopkins University, Baltimore, MD 21287, USA. gkelen@jhmi.edu

Abstract

BACKGROUND:

The ability to provide medical care during sudden increases in patient volume during a disaster or other high-consequence event is a serious concern for health-care systems. Identification of inpatients for safe early discharge (ie, reverse triage) could create additional hospital surge capacity. We sought to develop a disposition classification system that categorises inpatients according to suitability for immediate discharge on the basis of risk tolerance for a subsequent consequential medical event.

METHODS:

We did a warfare analysis laboratory exercise using evidence-based techniques, combined with a consensus process of 39 expert panellists. These panellists were asked to define the categories of a disposition classification system, assign risk tolerance of a consequential medical event to each category, identify critical interventions, and rank each (using a scale of 1-10) according to the likelihood of a resultant consequential medical event if a critical intervention is withdrawn or withheld because of discharge.

FINDINGS:

The panellists unanimously agreed on a five-category disposition classification system. The upper limit of risk tolerance for a consequential medical event in the lowest risk group if discharged early was less than 4%. The next categories had upper limits of risk tolerance of about 12% (IQR 8-15%), 33% (25-50%), 60% (45-80%) and 100% (95-100%), respectively. The expert panellists identified 28 critical interventions with a likelihood of association with a consequential medical event if withdrawn, ranging from 3 to 10 on the 10-point scale.

INTERPRETATION:

The disposition classification system allows conceptual classification of patients for suitable disposition, including those deemed safe for early discharge home during surges in demand. Clinical criteria allowing real-time categorisation of patients are awaited.

Comment in

PMID:
17141705
[PubMed - indexed for MEDLINE]
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