Journal of Computer Science & Systems Biology

Augmentation of Patient Health Care Choices for Morbid Obesity by Use of Computer Decision Analysis

Abstract

Yaw Sarpong, Jodi Ryder and Scott Litofsky N

Introduction: Many patients state that they frequently make the wrong choices when it comes to their healthcare treatment. These patients reported poor knowledge about the medical alternatives, physician biases, and lack of consideration of their goals and concerns in the treatment alternatives available led to these poor choices. However, current studies suggest that if patients are given aids that improve their knowledge and address their goals and concerns, they are able to make choices that are medically recommended as well as being right for them. We hypothesized that a computer model designed to improve knowledge and take into account patients’ concerns and goals will be able to aid patients in making such decisions. Methods: Using the Expert Choice Comparion system, we designed a program to assist morbidly obese patients in deciding which treatment options will be best suited for them. This system incorporated treatment objectives, treatment alternatives, pros and cons of each alternative, utility curves, and dynamic and performance sensitivity graphs to reach treatment recommendations. Patients were surveyed about their choices. Results: 8 patients from a convenience sample participated in decision analysis. Most chose reduction of co-morbidities, followed by treatment safety, followed by weight loss as their primary objectives. All patients were satisfied with their choice, all 8 felt their concerns were addressed and 7 of 8 were likely to follow recommendations. The program provided them with choices that meet national guidelines. Five of 8 patients described the ease of use of the program as moderate, 2 described it as excellent, and 1 described it as poor. Conclusions: Patients can use computer modeling to assist in making health choices for themselves.