Scholarlink

Objective <p>To analyze the hospitalization expenses and identify their influencing factors in patients undergoing radical prostatectomy (RP), in order to inform strategies for controlling hospitalization costs and reducing the direct economic burden on patients.</p> Methods <p>A retrospective study was conducted on 4,264 inpatients who underwent radical prostatectomy (RP) in the urology department of a tertiary hospital in Zhejiang Province between January 2022 and October 2025. Basic patient demographics and detailed hospitalization cost data were extracted from hospital records. The Mann‑Whitney <i>U</i> and Kruskal‑Wallis <i>H</i> tests were performed for univariate analysis using SPSS 27.0 and StataSE 15. Subsequently, quantile regression and the CHAID decision tree model were applied to analyze hospitalization costs.</p> Results <p>The total hospitalization expenses for the 4,264 RP patients were US$ 30,617,940.09, with an out-of-pocket proportion of 48.83%. Surgical costs constituted the major component. Univariate analysis identified several factors associated with expenses, including lymph node dissection (LND), blood transfusion, operative time, age, length of stay (LOS), pathological stage, choice of robotic surgery, Gleason score, Charlson Comorbidity Index (CCI), and different surgical team. Quantile regression analysis revealed that LND, blood transfusion, Barthel Index score (≤ 40), LOS (8–14 days and &gt;14 days), robotic surgery, and surgical team (Team 2 and Team 4) had a significant impact on the three quantiles of total hospitalization cost (<i>Q</i><sub><i>10</i></sub>, <i>Q</i><sub><i>50</i></sub>, <i>Q</i><sub><i>90</i></sub>) (<i>P</i> &lt; 0.05). Both quantile regression and the Chi-squared Automatic Interaction Detection (CHAID) decision tree model identified LOS, choice of robotic surgery, and Gleason score as primary influencing factors.</p> Conclusions <p>The economic burden of hospitalization for RP patients in this study was substantial, with surgical costs accounting for a large proportion and out‑of‑pocket payments representing nearly half of total expenses. LOS, robotic surgery, and Gleason score were identified as the primary drivers. These findings underscore the importance of implementing cost-containment strategies that address the key contributors to expenses, while ensuring that the quality of care is not compromised.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Hospitalization expenses for radical prostatectomy in a tertiary hospital in China: a quantile regression and CHAID decision tree analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月7日

查看全文
  • Feiyue Su,
  • Hualian Pei,
  • Yichao Hu,
  • Yiping Li,
  • Weihong Wang,
  • Qinhong Xu

摘要

Objective

To analyze the hospitalization expenses and identify their influencing factors in patients undergoing radical prostatectomy (RP), in order to inform strategies for controlling hospitalization costs and reducing the direct economic burden on patients.

Methods

A retrospective study was conducted on 4,264 inpatients who underwent radical prostatectomy (RP) in the urology department of a tertiary hospital in Zhejiang Province between January 2022 and October 2025. Basic patient demographics and detailed hospitalization cost data were extracted from hospital records. The Mann‑Whitney U and Kruskal‑Wallis H tests were performed for univariate analysis using SPSS 27.0 and StataSE 15. Subsequently, quantile regression and the CHAID decision tree model were applied to analyze hospitalization costs.

Results

The total hospitalization expenses for the 4,264 RP patients were US$ 30,617,940.09, with an out-of-pocket proportion of 48.83%. Surgical costs constituted the major component. Univariate analysis identified several factors associated with expenses, including lymph node dissection (LND), blood transfusion, operative time, age, length of stay (LOS), pathological stage, choice of robotic surgery, Gleason score, Charlson Comorbidity Index (CCI), and different surgical team. Quantile regression analysis revealed that LND, blood transfusion, Barthel Index score (≤ 40), LOS (8–14 days and >14 days), robotic surgery, and surgical team (Team 2 and Team 4) had a significant impact on the three quantiles of total hospitalization cost (Q10, Q50, Q90) (P < 0.05). Both quantile regression and the Chi-squared Automatic Interaction Detection (CHAID) decision tree model identified LOS, choice of robotic surgery, and Gleason score as primary influencing factors.

Conclusions

The economic burden of hospitalization for RP patients in this study was substantial, with surgical costs accounting for a large proportion and out‑of‑pocket payments representing nearly half of total expenses. LOS, robotic surgery, and Gleason score were identified as the primary drivers. These findings underscore the importance of implementing cost-containment strategies that address the key contributors to expenses, while ensuring that the quality of care is not compromised.