Patient classification based on volume and case-mix in the emergency department and their association with performance.

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ID: 14022
2019
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Abstract
Predicting daily patient volume is necessary for emergency department (ED) strategic and operational decisions, such as resource planning and workforce scheduling. For these purposes, forecast accuracy requires understanding the heterogeneity among patients with respect to their characteristics and reasons for visits. To capture the heterogeneity among ED patients (case-mix), we present a patient coding and classification scheme (PCCS) based on patient demographics and diagnostic information. The proposed PCCS allows us to mathematically formalize the arrival patterns of the patient population as well as each class of patients. We can then examine the volume and case-mix of patients presenting to an ED and investigate their relationship to the ED's quality and time-based performance metrics. We use data from five hospitals in February, July and November for the years of 2007, 2012, and 2017 in the city of Calgary, Alberta, Canada. We find meaningful arrival time patterns of the patient population as well as classes of patients in EDs. The regression results suggest that patient volume is the main predictor of time-based ED performance measures. Case-mix is, however, the key predictor of quality of care in EDs. We conclude that considering both patient volume and the mix of patients are necessary for more accurate strategic and operational planning in EDs.
Reference Key
zaerpour2019patienthealth Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Zaerpour, Farzad;Bischak, Diane P;Menezes, Mozart B C;McRae, Andrew;Lang, Eddy S;
Journal health care management science
Year 2019
DOI
10.1007/s10729-019-09495-z
URL
Keywords Keywords not found

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