Can Solo Practitioners Survive in Value-Based Healthcare? Validating a Predicative Model for ED Utilization.

Area of Science:

• Health Services Research
• Predictive Analytics in Healthcare
• Public Health

Background:

• The healthcare industry is shifting towards value-based care models.
• Accurate prediction of emergency room (ER) utilization is crucial for resource allocation and cost management.
• Identifying high-risk patient populations can optimize healthcare interventions.

Purpose of the Study:

• To validate a predictive model for determining emergency room utilization.
• To identify key patient factors associated with increased ER visits.
• To support the implementation of value-based healthcare strategies.

Main Methods:

• Analysis of data from 2991 patient records.
• Validation of a predictive model using Poisson and random forest models.
• Statistical analysis to identify predictors of ER utilization.

Main Results:

• Patients with one of six specific chronic conditions were more likely to utilize the ER.
• Missed scheduled appointments significantly increased the likelihood of ER utilization.
• Higher body mass index (BMI) was correlated with increased ER visits.

Conclusions:

• The validated predictive model can effectively identify patients at high risk for ER utilization.
• Chronic conditions, appointment adherence, and BMI are significant factors influencing ER use.
• Findings can inform targeted interventions within value-based care frameworks to reduce unnecessary ER visits.