Treatment level and store level analyses of healthcare data - Kaiwen Wang; Jiehui Ding; Kristen R. Lidwell; Scott Manski; Gee Lee; Emilio Xavier Esposito (Risks, 2019)
The presented research discusses general approaches to analyze and model healthcare data at the treatment level and at the store level. The paper consists of two parts: (1) a general analysis method for store-level product sales of an organization and (2) a treatment-level analysis method of healthcare expenditures. In the first part, our goal is to develop a modeling framework to help understand the factors influencing the sales volume of stores maintained by a healthcare organization. In the second part of the paper, we demonstrate a treatment-level approach to modeling healthcare expenditures. In this part, we aim to improve the operational-level management of a healthcare provider by predicting the total cost of medical services. From this perspective, treatment-level analyses of medical expenditures may help provide a micro-level approach to predicting the total amount of expenditures for a healthcare provider. We present a model for analyzing a specific type of medical data, which may arise commonly in a healthcare provider's standardized database. We do this by using an extension of the frequency-severity approach to modeling insurance expenditures from the actuarial science literature.
Keywords: 330; medical data analysis; store sales analysis; predictivemodeling; generalized additivemodels