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The Department of General Medicine caters to patients with diverse acute or chronic conditions, receiving cases domestic environment, the urgent care facility or dedicated specialized ward. The Length of Stay (LOS) serves as a valuable metric for patient monitoring and assessing service efficiency and quality. This study aimed to provide LOS data of subjects in the General Medicine Department at the University Hospital Federico II of Naples and to compare these results with those obtained in a prior study conducted on the same group using different data crawled from the University Hospital “San Giovanni di Dio e Ruggi d’Aragona” in Salerno (Italy) and the A.O.R.N. “Antonio Cardarelli” in Naples (Italy). The objective of the proposed analysis revolves around comparing the Length of Stay (LOS) estimates among the three different hospitals located in the Campania Region by using the Multiple Linear Regression model to forecast LOS. Results show that Age and Presence of Comorbidities had a statistically significant impact on the total LOS value (p-value < 0.005).

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Multiple Linear Regression Based LOS Analysis in the General Medicine Department

  • 会议论文

  • 发表日期：

    2025年

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  • Marta Rosaria Marino,
  • Anna Borrelli,
  • Maria Triassi,
  • Giovanni Improta

摘要

The Department of General Medicine caters to patients with diverse acute or chronic conditions, receiving cases domestic environment, the urgent care facility or dedicated specialized ward. The Length of Stay (LOS) serves as a valuable metric for patient monitoring and assessing service efficiency and quality. This study aimed to provide LOS data of subjects in the General Medicine Department at the University Hospital Federico II of Naples and to compare these results with those obtained in a prior study conducted on the same group using different data crawled from the University Hospital “San Giovanni di Dio e Ruggi d’Aragona” in Salerno (Italy) and the A.O.R.N. “Antonio Cardarelli” in Naples (Italy). The objective of the proposed analysis revolves around comparing the Length of Stay (LOS) estimates among the three different hospitals located in the Campania Region by using the Multiple Linear Regression model to forecast LOS. Results show that Age and Presence of Comorbidities had a statistically significant impact on the total LOS value (p-value < 0.005).