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Regression Models to Study the Total LOS Related to Valvuloplasty

Author

Listed:
  • Arianna Scala

    (Department of Public Health, University of Naples “Federico II”, 80131 Naples, Italy)

  • Teresa Angela Trunfio

    (Department of Advanced Biomedical Sciences, University of Naples ‘Federico II’, 80131 Naples, Italy)

  • Lucia De Coppi

    (Department of Public Health, University of Naples “Federico II”, 80131 Naples, Italy)

  • Giovanni Rossi

    (Hospital Directorate, “San Giovanni di Dio e Ruggi d’Aragona” University Hospital of Salerno, 84125 Salerno, Italy)

  • Anna Borrelli

    (Hospital Directorate, “San Giovanni di Dio e Ruggi d’Aragona” University Hospital of Salerno, 84125 Salerno, Italy)

  • Maria Triassi

    (Department of Public Health, University of Naples “Federico II”, 80131 Naples, Italy
    Interdepartmental Center for Research in Healthcare Management and Innovation in Healthcare (CIRMIS), University of Naples “Federico II”, 80131 Naples, Italy)

  • Giovanni Improta

    (Department of Public Health, University of Naples “Federico II”, 80131 Naples, Italy
    Interdepartmental Center for Research in Healthcare Management and Innovation in Healthcare (CIRMIS), University of Naples “Federico II”, 80131 Naples, Italy)

Abstract

Background: Valvular heart diseases are diseases that affect the valves by altering the normal circulation of blood within the heart. In recent years, the use of valvuloplasty has become recurrent due to the increase in calcific valve disease, which usually occurs in the elderly, and mitral valve regurgitation. For this reason, it is critical to be able to best manage the patient undergoing this surgery. To accomplish this, the length of stay (LOS) is used as a quality indicator. Methods: A multiple linear regression model and four other regression algorithms were used to study the total LOS function of a set of independent variables related to the clinical and demographic characteristics of patients. The study was conducted at the University Hospital “San Giovanni di Dio e Ruggi d’Aragona” of Salerno (Italy) in the years 2010–2020. Results: Overall, the MLR model proved to be the best, with an R 2 value of 0.720. Among the independent variables, age, pre-operative LOS, congestive heart failure, and peripheral vascular disease were those that mainly influenced the output value. Conclusions: LOS proves, once again, to be a strategic indicator for hospital resource management, and simple linear regression models have shown excellent results to analyze it.

Suggested Citation

  • Arianna Scala & Teresa Angela Trunfio & Lucia De Coppi & Giovanni Rossi & Anna Borrelli & Maria Triassi & Giovanni Improta, 2022. "Regression Models to Study the Total LOS Related to Valvuloplasty," IJERPH, MDPI, vol. 19(5), pages 1-13, March.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:5:p:3117-:d:765447
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    References listed on IDEAS

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    1. Arianna Scala & Alfonso Maria Ponsiglione & Ilaria Loperto & Antonio Della Vecchia & Anna Borrelli & Giuseppe Russo & Maria Triassi & Giovanni Improta, 2021. "Lean Six Sigma Approach for Reducing Length of Hospital Stay for Patients with Femur Fracture in a University Hospital," IJERPH, MDPI, vol. 18(6), pages 1-13, March.
    2. Giovanni Improta & Giuseppe Converso & Teresa Murino & Mosè Gallo & Antonietta Perrone & Maria Romano, 2019. "Analytic Hierarchy Process (AHP) in Dynamic Configuration as a Tool for Health Technology Assessment (HTA): The Case of Biosensing Optoelectronics in Oncology," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1533-1550, September.
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    Cited by:

    1. Jialiang Yang & Wen Yin & Yi Jin, 2023. "Analyzing Public Environmental Concerns at the Threshold to Reduce Urban Air Pollution," Sustainability, MDPI, vol. 15(21), pages 1-17, October.
    2. Arianna Scala & Ilaria Loperto & Maria Triassi & Giovanni Improta, 2022. "Risk Factors Analysis of Surgical Infection Using Artificial Intelligence: A Single Center Study," IJERPH, MDPI, vol. 19(16), pages 1-10, August.

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