Model-Free Organization of Patient Reported Outcomes Data: Geometrical Rep-resentation of the Modified Compartmen-talization Method

Manasi Sheth^1,2, N. Rao Chaganty³

1. Department of Mathematics, University of Wisconsin – Whitewater, WI, USA.
2. Department of Computer Science, University of Wisconsin – Whitewater,WI, USA.
3. Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA, USA.

Abstract:

There is a recent advancement in the field of mathematics and statistics to understand the geometry or connectedness of the data due to the massive amounts of data being generated. The data provided for analyses are usually very large and need to be organized and minimized in order to make it more useful and meaningful. In biostatistics or medical field, it is important for patients to have access to high-quality, safe and effective and/ or efficacious medical products. It is quite necessary to ascertain that the patients and their care-partners stay at the center of the regulatory decision-making process. In order to do so, it becomes necessary to partner with the patients by incorporating the patient perspective as evidence in the decision-making process, including patient-reported outcomes (PROs). PROs are often relevant in assessing diagnostic evaluations and can be used to capture a patient’s everyday experience with a medical product, including experience outside of the clinician’s office and the effects of the treatment on a patient’s activities of daily living and functionality. In some cases, PRO measures enable us to measure important health status information that cannot yet be detected by other measures, such as pain and mobility. Here, we present the geometrical representations of a novel approach of analyzing PROs using Modified Compartmentalization Method.

Keywords: Compartmentalization Method, Patient Reported Outcomes, Geom-etry, Transition Proportion Matrix, Repeated Measures, Longitudinal Data.

Pages: 87 – 96 | Full PDF Paper