Measurement System Analysis in Healthcare: Attribute Data

Document Type

Conference Proceeding

Publication Date

2017

MeSH Terms

Delivery of Health Care

Subject: LCSH

Medical care, Attribute focusing (Data mining)

Disciplines

Industrial Engineering | Mechanical Engineering

Abstract

Variation in a process can stem from one or more sources that are broadly categorized under 5 Ms: man, machine, material, methods and measurements. This research focuses on process variation resulting from measurements and provides guidelines to implement attribute measurement system analysis (MSA) in healthcare. If the measurement contributes to the variation observed in the process, then it is difficult to separate the true process variation, and this could lead to bad decision-making. MSA determines how much of the observed variability is due to the measurement system. MSA has received significant attention to date, however, much research in this field focuses on variables (continuous) data and MSA finds vast applications in manufacturing. Attributes (discrete/qualitative) data is also abundant in many processes. In industries such as healthcare, attribute MSA can play an important role in identifying variation. Medical errors resulting from system or human errors could possibly be linked to measurement. In this paper, we discuss considerations and factors in application of attribute MSA in healthcare, describe key elements for successful implementation, and show why it is worth the effort. We, then provide guidelines to implement attribute MSA in healthcare setting.

Comments

© 2017 Institute of Industrial and Systems Engineers

Paper appeared in the Proceedings of the 2017 Industrial and Systems Engineering Conference.

Full-text access is available to the University of New Haven community.

Publisher Citation

Arani, O. M., & Erdil, N. O. (2017). Measurement system analysis in healthcare: Attribute data. IIE Annual Conference.Proceedings, 1109-1114.

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