Abstract: Personal health assessments (PHA) are surveys consisting of questions related to an individual's health history, current health status, and lifestyle behaviors. Employers and health insurance companies commonly administer annual PHAs to understand the health risks of employees/covered entities and provide customized programs to reduce these risks. PHA questions are grouped under different categories that focus on distinct lifestyle behaviors e.g. physical activity, nutrition, smoking, alcohol, stress and well being; and health status e.g. chronic conditions. These questions are asked on a Likert scale of 1 (strongly agree) to 5 (strongly disagree), a scale commonly used in many social science questionnaires. Due to incentives offered to complete the PHA, they have a large response rate thus providing large amount of data with potential for use in predicting future health risks and healthcare expenses. However, to the best of our knowledge, PHA data have not been analytically tested to determine their value in predictive and outcomes research. In this abstract, we outline methodology for determining the experimental usefulness of PHA data, specifically focusing on how a cancer diagnosis can affect patterns of responses to PHA questions.
Learning Objective 1: Audiences will learn about the relationship between personal health assessment data and cancer as well as the overall utility of personal health assessment data.
Zach Abrams (Presenter)
The Ohio State University
Hetian Bai, The Ohio State University
Kevin Coombes, The Ohio State University
Tasneem Motiwala, The Ohio State University