Cost Effectiveness and Resource Allocation (Nov 2024)

Assessing diagnosis-related groups based direct medical expenditures of chronic disease patients in general hospital of lower southern Thailand

  • Akemat Wongpairin,
  • Apiradee Lim,
  • Phattrawan Tongkumchum,
  • Wichayaporn Thongpeth,
  • Haris Khurram

DOI
https://doi.org/10.1186/s12962-024-00596-3
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 6

Abstract

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Abstract Background Assessment of the cost-related burden of chronic diseases is important for making informed decisions. An effective and efficient methodology for examining medical expenditures is one of the most significant challenges for stakeholders. The objective of this study was to examine the role of the variables of diagnosis-related group (DRG) in determining the direct expense of chronic diseases in lower southern Thailand and suggest the determinants having high explainability. Methods The records of 6,147 patients admitted to Satun Hospital from 2014 to 2018 and diagnosed with chronic conditions were analyzed in this study. Descriptive analysis was used to summarize the main characteristics. Correlation was used to analyze the strength of the relationship. A log-linear regression model was used to evaluate the adjusted mean cost using determinants of DRG. Results The overall average medical expense for chronic disease was Thailand Baht (THB) 17,985. Chronic kidney and chronic obstructive pulmonary diseases were the most expensive chronic diseases with an average expense of about THB 20,000 and 25,000. All the determinants were significantly contributing to overall expense of chronic disease with a p-value < 0.001. However, the length of stay, number of diagnoses, and number of procedures had high explainability in the expense model. Conclusions The expense assessment model plays a significant role in controlling and preventing the medical costs associated with chronic diseases. Healthcare administrators, stakeholders, and researchers need to make strategies by considering the results of this study to improve the DRGs-based hospital cost model.

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