Abstract
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.
Highlights
Frequency-severity models are foundational to insurance claims’ modeling for actuarial applications
Our work focuses on the prediction problem, yet we are interested in the coefficient estimates of certain explanatory variables to understand their relationship with the response variables
We have presented two unique analysis and modeling endeavors, (1) store-level sales modeling project and (2) a medical treatment-healthcare expenditure modeling project
Summary
Frequency-severity models are foundational to insurance claims’ modeling for actuarial applications. The modeler is able to understand the factors that influence the frequency and the severity of insurance claims. This paper illustrates how the frequency-severity modeling approach can be extended, so that it is capable of modeling healthcare expenditures at the treatment level. The idea is to consider the frequency of the patients, and the frequency of the treatments incurred by each patient at each department of a healthcare network. This allows the analyst to understand the variation of the frequency of patients, the frequency of treatments at each department, as well as the severity of the expenditures, via the coefficients estimated from the analysis
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