Measurement System Analysis in Healthcare: Attribute Data
Delivery of Health Care
Medical care, Attribute focusing (Data mining)
Industrial Engineering | Mechanical Engineering
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.
Arani, Omid M. and Erdil, Nadiye O., "Measurement System Analysis in Healthcare: Attribute Data" (2017). Mechanical and Industrial Engineering Faculty Publications. 46.
Arani, O. M., & Erdil, N. O. (2017). Measurement system analysis in healthcare: Attribute data. IIE Annual Conference.Proceedings, 1109-1114.