A ICD-10 predictive model to improve hospital income in inpatient


  • Darigar Darojn Ubonratchathani Cancer Hospital
  • Wansa Paoin Faculty of Medicine, Thammasat University


Profit, Loss, Hospital analysis, ICD-10, Predictive model


This research was designed to search for inpatient disease groups. Which has a high influence on profit making or hospital loss by classifying the ICD-10 disease code and writing it out as a model to be a model for finding the groups that have a high influence on profit and loss? Research Methodology: Ordering disease groups that made a lot of profits or losses to the hospital from high to low. Procure forms of profit or loss. Then try to simulate events to increase hospital profits by various methods to find out which method is appropriate for which disease group to increase profits or reduce losses to the hospital. Then create a model to select the appropriate disease groups to increase hospital revenue. Research results: The most profitable diseases for hospitals are diseases with a high volume of patients, resulting in huge profits. But when simulating an event to find ways to increase revenue for the hospital, it was found that the increased income is not sorted by the group of diseases that make a profit for the hospital but is more in line with the model of profit or loss. Discussion: This research therefore has formulated a formula to find the pattern of profit and loss as an alternative in choosing to find the disease code to increase hospital revenue.




How to Cite

Darojn, D. ., & Paoin, W. . (2022). A ICD-10 predictive model to improve hospital income in inpatient . Journal of the Thai Medical Informatics Association, 6(2), 75–81. Retrieved from https://he03.tci-thaijo.org/index.php/jtmi/article/view/117