Interactive Weight Loss Calculator

Do you or someone you know has a child who is severely obese and is considering undergoing Bariatric Surgery but are unsure how the child may lose weight post-surgery?  Wait no further, use this interactive weight loss calculator to see the weight loss progress for every 6 months until 3 years after the surgery.

Bariatric surgery (weight-loss surgery) is a treatment for severe obesity in which specialists modify the stomach and its connections to help teens lose weight. For severely obese adolescents who have not had success with behavioral and nutritional approaches to weight loss, bariatric surgery is another effective tool for weight management [1].

Using predictive modeling techniques, Pavan Kumar Chundi, designed this unique interactive weight loss prediction tool that not only serves as an informational tool for patients and families but also is utilized by the clinical staff to monitor the progress and motivate patients to follow a treatment plan to achieve the desired outcomes. This tool can be accessed online on Cincinnati Children's website ( Weight Loss Calculator).

"Bariatric Surgery data and data for all subsequent visits post-surgery was extracted and formatted to get the required time stamps. Along with the inputs from the clinical team, literature was reviewed to obtain a comprehensive list of factors that could affect the weight loss over time. Upon review, the data followed a monotone missing pattern (i.e. if a patient failed to show up a certain visit then the patient fails to show up at all the other subsequent visit). Before applying any kind of imputation technique, a review of the patient medical record was performed to track weight for the required time stamp. At each time stamp, a three-month time interval was used to check to see if the patient weight was recorded elsewhere in the hospital. 5 different regression models were created i.e. one for each time stamp using Piecewise Linear Regression technique. A 5-fold cross validation was performed to measure the performance of the model " explained Pavan Chundi summarizing the model.

Linda M. Kollar  MSN, APRN, CNP who is the Bariatric Clinical Director at Cincinnati Children's Hospital Medical Center says "I want to tell you again that this tool has been very helpful for our patients in clinic. I've had some great discussions with patients starting the process to prepare for surgery. It really helps them to get a sense of what they should expect…the majority say they want to do better than average, will be interesting to see what happens. I have found it to be helpful to reassure or motivate those who have had surgery as well. Including a nervous provider that thought a patient was losing weight too fast."

The weight loss prediction tool is currently being utilized by patients and families to better understand how they can lose weight post Bariatric Surgery and by Clinicians to motivate the patients by comparing their weight loss with that of the average at their follow up visit and help plan early interventions for better care management.

This is a phenomenal example that showcases how data and data analytics methods can be employed to generate valuable and actionable insights that aid in improving patient outcomes.

Reference:

1. Bariatric Surgery | Surgical Weight Loss Program for Teens (cincinnatichildrens.org)
2. Interactive Weight Loss Calculator (cincinnatichildrens.org)

Pavan K Chundi Bio:

Pavan Kumar Chundi is a BI & Analytics Manager at UC Health. Prior to joining UC Health, Pavan worked as a Lead Data Analytics Manager at Cincinnati Children's Hospital Medical Center for 8 years where he managed a team of 6 analysts and provided analytical solutions to network hospitals across United States and Canada. Learning Health Networks are multisite, practice-based clinical networks that use data for research and improvement. He has been associated with the Healthcare Industry for over 15 years and holds master's degrees in Biomedical Engineering (University of Surrey, UK) and Business Analytics (University of Cincinnati, USA). As a data analytics leader, Pavan has been instrumental in interpreting and analyzing data to develop analytics tools to improve outcomes and patient family experience. He serves on the Advisory Board for graduate program in Health Informatics at University of Cincinnati. His areas of expertise include Healthcare Analytics, Business Intelligence, Process Improvement, Data Visualization, Product Development, and Innovation.