An evaluation study of direct economic losses from surgical site infections in adults: structural equation modeling
IntroductionSurgical site infection (SSI) represents a significant postoperative complication, resulting in extended hospital stays and substantial economic burdens. Previous research on the direct economic impact of SSIs using recursive systems modeling is limited. This study aims to quantify the d...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2024.1514444/full |
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| author | Qiuxia Zuo Di Liu Baoji Dong Yuan Zhou Kexin Zhao Ping Tian Ping Tian |
| author_facet | Qiuxia Zuo Di Liu Baoji Dong Yuan Zhou Kexin Zhao Ping Tian Ping Tian |
| author_sort | Qiuxia Zuo |
| collection | DOAJ |
| description | IntroductionSurgical site infection (SSI) represents a significant postoperative complication, resulting in extended hospital stays and substantial economic burdens. Previous research on the direct economic impact of SSIs using recursive systems modeling is limited. This study aims to quantify the direct economic losses attributable to SSIs and to dissect the various factors to these losses.MethodsA retrospective 1:1 matched case–control study was conducted from January 2023 to March 2024 in three tertiary hospitals in Xinjiang, China. Patients with SSIs were matched on a 1:1 basis by hospital, department, age (±5 years), sex, primary diagnosis, and procedure with controls to form case and control groups. Wilcoxon Signed Ranks Test was utilized to quantify the direct economic loss from SSIs. Influencing factors were analyzed using a recursive system model.ResultsAmong the 74,258 patients surveyed, 226 developed SSIs, resulting in an infection rate of 0.3%. The total direct economic loss from SSIs at three hospitals was $467,867, with an average loss of $1,364.37 per SSI patient. SSI patients experienced hospital stays 11 days longer than uninfected patients. Multivariate linear regression identified the duration of hospital stay, catheter and ventilator usage, age, number of surgeries, and duration of antibiotic treatment as influencing factors. Recursive system modeling revealed the indirect contributions of the number of surgeries (indirect effect: 0.074), antibiotic use for 17–36 days (indirect effect: 0.063) and ≥ 37 days (indirect effect: 0.045), and debridement procedures (indirect effect: 0.054), as well as the direct contributions of hospital days (direct effect: 0.276), indwelling catheter days (direct effect: 0.260), ventilator days (direct effect: 0.221), and age (direct effect: 0.182).ConclusionRecursive system modeling helped identify the key factors influencing the economic losses from SSIs. These findings provide a theoretical basis for healthcare departments to develop targeted policies. |
| format | Article |
| id | doaj-art-a0c0bfe5bfe44637a51a8626a2a3f389 |
| institution | DOAJ |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Public Health |
| spelling | doaj-art-a0c0bfe5bfe44637a51a8626a2a3f3892025-08-20T02:40:43ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-01-011210.3389/fpubh.2024.15144441514444An evaluation study of direct economic losses from surgical site infections in adults: structural equation modelingQiuxia Zuo0Di Liu1Baoji Dong2Yuan Zhou3Kexin Zhao4Ping Tian5Ping Tian6School of Nursing, Xinjiang Medical University, Urumqi, Xinjiang, ChinaInfection Management Department, The Fifth Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, ChinaInfection Management Department, The Sixth Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, ChinaInfection Management Department, Xinjiang Uygur Autonomous Region People's Hospital, Urumqi, Xinjiang, ChinaSchool of Nursing, Xinjiang Medical University, Urumqi, Xinjiang, ChinaInfection Management Department, The Fifth Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, ChinaHealth Care Research Center for Xinjiang Regional Population, Urumqi, Xinjiang, ChinaIntroductionSurgical site infection (SSI) represents a significant postoperative complication, resulting in extended hospital stays and substantial economic burdens. Previous research on the direct economic impact of SSIs using recursive systems modeling is limited. This study aims to quantify the direct economic losses attributable to SSIs and to dissect the various factors to these losses.MethodsA retrospective 1:1 matched case–control study was conducted from January 2023 to March 2024 in three tertiary hospitals in Xinjiang, China. Patients with SSIs were matched on a 1:1 basis by hospital, department, age (±5 years), sex, primary diagnosis, and procedure with controls to form case and control groups. Wilcoxon Signed Ranks Test was utilized to quantify the direct economic loss from SSIs. Influencing factors were analyzed using a recursive system model.ResultsAmong the 74,258 patients surveyed, 226 developed SSIs, resulting in an infection rate of 0.3%. The total direct economic loss from SSIs at three hospitals was $467,867, with an average loss of $1,364.37 per SSI patient. SSI patients experienced hospital stays 11 days longer than uninfected patients. Multivariate linear regression identified the duration of hospital stay, catheter and ventilator usage, age, number of surgeries, and duration of antibiotic treatment as influencing factors. Recursive system modeling revealed the indirect contributions of the number of surgeries (indirect effect: 0.074), antibiotic use for 17–36 days (indirect effect: 0.063) and ≥ 37 days (indirect effect: 0.045), and debridement procedures (indirect effect: 0.054), as well as the direct contributions of hospital days (direct effect: 0.276), indwelling catheter days (direct effect: 0.260), ventilator days (direct effect: 0.221), and age (direct effect: 0.182).ConclusionRecursive system modeling helped identify the key factors influencing the economic losses from SSIs. These findings provide a theoretical basis for healthcare departments to develop targeted policies.https://www.frontiersin.org/articles/10.3389/fpubh.2024.1514444/fullsurgical site infectionsdirect economic lossrecursive system modelinginfluencing factorsstructural equation |
| spellingShingle | Qiuxia Zuo Di Liu Baoji Dong Yuan Zhou Kexin Zhao Ping Tian Ping Tian An evaluation study of direct economic losses from surgical site infections in adults: structural equation modeling Frontiers in Public Health surgical site infections direct economic loss recursive system modeling influencing factors structural equation |
| title | An evaluation study of direct economic losses from surgical site infections in adults: structural equation modeling |
| title_full | An evaluation study of direct economic losses from surgical site infections in adults: structural equation modeling |
| title_fullStr | An evaluation study of direct economic losses from surgical site infections in adults: structural equation modeling |
| title_full_unstemmed | An evaluation study of direct economic losses from surgical site infections in adults: structural equation modeling |
| title_short | An evaluation study of direct economic losses from surgical site infections in adults: structural equation modeling |
| title_sort | evaluation study of direct economic losses from surgical site infections in adults structural equation modeling |
| topic | surgical site infections direct economic loss recursive system modeling influencing factors structural equation |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2024.1514444/full |
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