Predictive model for predicting emergency department patients at risk of generating hospital’s uncompensated care

Abstract

Introduction
Some of patients create uncompensated hospital care. Many negative effects to hospital, patients and staffs occurred with uncompensated hospital care.

Objectives
For create predictive model for identifying patients who is at risk for uncompensated hospital care.

Method
This retrospective cohort study occurred in emergency department of King Chulalongkorn Memorial Hospital. Data was collected from electronic medical record from 1 Jun 2018 to 31 May 2020 and create predictive model.

Results
There were 93,753 patients included in this study. For multivariate analysis, risk of patients at risk of generating hospital’s uncompensated care are; age group 25-40 and 41-59 years are 1.38 times higher than that below 25 years, male patient is 1.46 times higher than female, patient who present on night shift is 1.21 higher than others, patient with universal health coverage(UC) other than Chulalongkorn hospital is 2.32 times higher and with self-pay is 2.28 times higher than Chulalongkorn hospital universal health coverage, government enterprise officer and social security fund, Asian and American patient is 1.28 and 1.62 times higher than others, patient who visit zone holding area, non-trauma, resuscitation and trauma is 3.25, 2.26, 2.52 and 1.65 times higher than urgent care. Predictive model for identifying patients who is at risk for uncompensated hospital care more than 1,000 Baht classified by risk score and optimal cut off value by Youden’s index is 20. So we divided patients in low risk group who’s risk score is 0-19, and high risk group who’s risk is more than or equal 20. Comparing high with low risk group OR 8.42 (6.77 – 10.5), sensitivity 76.7, specificity 71.9, PPV 4.3, NPV 99.5, AUC 0.74

Conclusion
Risk of patients at risk of generating hospital’s uncompensated care are age group 25-40 and 41-59 years, male, patient who present on night shift, Patient with patient with universal health coverage(UC) other than Chulalongkorn hospital and with self-pay, Asian and American and patient who visit zone other than urgent care. Predictive model for identifying patients who is at risk for uncompensated hospital care more than 1,000 Baht classified who’s risk score is more than 19 as high risk patient.