Patient Diagnostic State Evolution During Hospitalization: Developing a Model for Measuring Clinical Diagnostic Dynamics

Yariv N. Marmor () and Emil Bashkansky ()
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Yariv N. Marmor: ORT Braude College of Engineering
Emil Bashkansky: ORT Braude College of Engineering

A chapter in Recent Advances in Multi-state Systems Reliability, 2018, pp 343-354 from Springer

Abstract: Abstract Patient health is represented by a set of diagnoses, which determines personal health status. Each set corresponds to a certain health state and so, can be treated as an individual performance in this state and individual health can be considered as a corresponding multi-state system. Appropriate metrics for measuring patient’s state diagnosis changes during hospitalization are proposed. The first metric determines the dissimilarity between two single diagnoses, each of which is based on internationally recognized classification scheme. The second metric is aimed to compare between two sets of diagnoses with respect to the same patient and is based on the first metric, but uses additional, recently proposed, ideas of measuring heterogeneity/segregation between sets of categorical data. A numerical example and a real world illustration of the above measures are provided. The ultimate goal is the analysis of multistate health status data in order to improve the accuracy and quality of medical diagnostics.

Keywords: Medical diagnosis; Accuracy; Misclassification; Dissimilarity; Healthcare quality (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-3-319-63423-4_18

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DOI: 10.1007/978-3-319-63423-4_18

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