Determinants of Hospital Length of Stay in Respiratory Infections: Insights from Cheras, Malaysia

Respiratory virus infections pose a significant public health concern, contributing to increase morbidity and mortality rates. This study investigated the determinants of hospital length of stay (LOS) for patients with Influenza-like illness (ILI) and Severe Acute Respiratory Infection (SARI). A qua...

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Veröffentlicht in:Medicine & health (Kuala Lumpur, Malaysia) Malaysia), 2024-03, Vol.19 (1), p.245-256
1. Verfasser: Department of Public Health Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia (UKM), Jalan Ya’acob Latiff, Bandar Tun Razak, Cheras, Kuala Lumpur, Malaysia
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Sprache:eng
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Zusammenfassung:Respiratory virus infections pose a significant public health concern, contributing to increase morbidity and mortality rates. This study investigated the determinants of hospital length of stay (LOS) for patients with Influenza-like illness (ILI) and Severe Acute Respiratory Infection (SARI). A quantitative study was conducted in Cheras, Kuala Lumpur, Malaysia, from 1 September 2022 until 28 February 2023. Demographic data, viral infection status (influenza A, influenza B, and COVID-19), and environmental factors (temperature, humidity, wind speed, and particulate matter levels) were collected for 632 patients. The data were analysed using ordinal logistic regression in Statistical Package for Social Sciences (SPSS) version 22.0. The results revealed that older age and higher body mass index (BMI) were associated with longer hospital stays, highlighting their significance as risk factors during respiratory outbreaks. Unexpectedly, patients tested positive for the investigated viruses experienced shorter LOS, indicating potential comorbidities or co-infections. Environmental factors played a critical role, with temperature, humidity, and wind speed significantly influencing LOS. These findings provided valuable insights for healthcare resource allocation during epidemics and underscored the need for comprehensive diagnostic tools and further research to enhance prediction accuracy.
ISSN:2289-5728
2289-5728
DOI:10.17576/MH.2024.1901.17