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Mortality rate, patient length of stay and medical cost prediction in different priority levels for patient admission to an intensive care unit

Bibliographic Data

ID6150818
AuthorsFariba Hosseinpour (Qazvin University of Medical Sciences), Mahyar Seddighi (0000-0002-0824-0215, Qazvin University of Medical Sciences), Mohammad Amerzadeh (Qazvin University of Medical Sciences), Sima Rafiei (0000-0002-7502-7078, Qazvin University of Medical Sciences)
Year2022
Volume17
Issue1
Pages87-97
Publication date2022-08-19
Open AccessYes
TypeARTICLE
VenueInternational Journal of Human Rights in Healthcare (JOURNAL)
Journal identifiersISSN: 2056-4902 • E-ISSN: 2056-4910
PublisherEmerald Publishing Limited (PUBLISHER • GB)
DOI10.1108/ijhrh-10-2021-0192
OpenAlexW4292379788
LanguageEN
References cited24

Purpose This study aimed to compare mortality rate, length of stay (LOS) and hospitalization costs at different priority levels for a patient admitted to an intensive care unit (ICU) at a public tertiary hospital in Qazvin, Iran. This study also aimed to predict influencing factors on patients’ mortality, ICU LOS and hospitalization costs in different admission groups. Design/methodology/approach The authors conducted a retrospective cohort study among patients who mainly suffered from internal diseases admitted to an ICU of a public hospital. This study was conducted among 127 patients admitted to ICU from July to September 2019. The authors categorized patients into four groups based on two crucial hemodynamic and respiratory status criteria. The authors used a logistic regression model to predict the likelihood of mortality in ICU admitted patients during hospitalizations for the four prioritization groups. Furthermore, the authors conducted a multivariate analysis using the “enter” method to identify risk factors for LOS. Findings Results showed a statistically significant relationship between the priority of being admitted to ICU and hospitalization costs. The authors’ findings revealed that age, LOS and levels of consciousness had a predictability role in determining in-hospital mortality. Besides, age, gender, consciousness level of patients and type of the disease were mentioned as affecting factors of LOS. Originality/value This study’s findings emphasize the necessity of categorizing patients according to specific criteria to efficiently use available resources to help health-care authorities reduce the costs and allocate the budget to different health sectors

Health care · Intensive care medicine · Intensive care unit · Logistic regression · Mortality rate · Public health · Public hospital · Retrospective cohort study · Emergency and Acute Care Studies · Global Health Care Issues · Medicine · Sepsis Diagnosis and Treatment · Emergency Medicine · Internal Medicine

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