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The Body Mass Index (BMI) is a numerical value derived from a person's weight and height, used to categorize individuals into weight ranges. It is calculated using the formula: weight in kilograms divided by height in meters squared. Obesity is a health condition characterized by excessive accumulation of adipose tissue that poses health risks, often diagnosed with a BMI ≥ 30. This excess fat storage occurs when surplus dietary calories are converted into triglycerides and stored in...
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A machine learning framework for optimizing obesity care by simulating clinical trajectories and targeted

Jacob Nudel1, Kelly M Kenzik1, Iniya Rajendran2

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Identifying weight loss surgery (WLS) bottlenecks is key to increasing access. This study found significant attrition points and risk factors, suggesting interventions could boost WLS procedures.

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Area of Science:

  • Bariatric Surgery
  • Obesity Management
  • Healthcare Systems Analysis

Background:

  • Weight loss surgery (WLS) is an effective treatment for obesity, yet its utilization remains suboptimal.
  • Clinical management pathways present bottlenecks that hinder patient progression towards WLS.
  • Understanding attrition risks is crucial for improving access to bariatric procedures.

Purpose of the Study:

  • To identify critical clinical management bottlenecks contributing to the underuse of weight loss surgery (WLS).
  • To assess patient-specific risk factors associated with attrition at each stage of the WLS pathway.
  • To evaluate the potential impact of interventions aimed at optimizing the WLS referral process.

Main Methods:

  • Development of a multistate conceptual model to map patient progression from primary care to WLS.
  • Analysis of a cohort of eligible adults (n=5876) seen by primary care providers (PCPs) between 2016-2017.
  • Kaplan-Meier estimates were used to determine 2-year outcomes for progression through defined care states.

Main Results:

  • The 2-year WLS rate from an initial PCP visit was only 1.0% (69/5876 patients).
  • Significant attrition occurred at multiple stages, including PCP visit (35%), endocrine referral (15.6%), endocrine visit (6.3%), and WLS referral (4.7%).
  • Female sex, younger age, higher BMI, and care by trainees were associated with increased progression; provider referral practices varied significantly.

Conclusions:

  • Low rates of weight loss surgery are driven by specific, identifiable bottlenecks within the clinical management pathway.
  • The developed methodology allows for in silico testing of interventions to optimize obesity care and increase WLS utilization.
  • Targeted interventions, such as increasing PCP referrals, could significantly increase the number of WLS procedures performed.