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Probability distribution analysis of patients arriving at Regional Referral hospital Dodoma, Tanzania (2017-2018).

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dc.creator Balan, Ramkumar T.
dc.creator Loibor, Julius Moinget
dc.date 2022-03-23T08:40:27Z
dc.date 2022-03-23T08:40:27Z
dc.date 2021
dc.date.accessioned 2022-10-20T13:25:33Z
dc.date.available 2022-10-20T13:25:33Z
dc.identifier Balan, R. T., & Loibor, J. M. (2021). Probability distribution analysis of patients arriving at Regional Referral hospital Dodoma, Tanzania (2017-2018). International Journal of Scientific Research, 10(6), 1-4
dc.identifier DOI: 10.36106/ijsr/8432443
dc.identifier http://hdl.handle.net/20.500.12661/3509
dc.identifier.uri http://hdl.handle.net/20.500.12661/3509
dc.description Full text article. Also available athttps://www.worldwidejournals.com/international-journal-of-scientific-research-(IJSR)/fileview/probability-distribution-analysis-of-patients-arriving-at-regional-referral-hospital-dodoma-tanzania-20172018_June_2021_2176297101_8432443.pdf
dc.description Health care is essential to the general welfare of society. Studying the hospital patients' data distribution through the probability distribution analysis model is very important in the health care system. This study has examined the hospital inpatients and outpatients' daily data for two years taken from DRRH through the hospital electronic health management information system. This study seeks to identify comprehensively the appropriate statistical distributions on inpatient and outpatient data of the DRR hospital. The primary fitting of the distributions to inpatient and outpatient data was performed by the Easyfit 5.5 Profession statistical software. The software deals with 61 continuous distributions, including three goodness of fit test for raw data and two for frequency data. Kolmogorov- Smirnov test, Anderson- Darling test and Chi-Square test only for raw data. The parameters of the selected distributions were estimated by the maximum likelihood method. The final selection of fittest distribution was done with respect to the minimum calculated value of log-likelihood and hence AIC and BIC values. The research work revealed that Generalized Extreme Value distribution is the best-fit distribution model for the hospital inpatient daily data. Also, the Dagum distribution followed by Log logistic (3P) distribution was selected to be the best-fit distribution model representing the hospital outpatients' daily data.
dc.language en
dc.publisher World Wide Journals PVT LTD
dc.subject Health care
dc.subject Hospital patients
dc.subject Probability distribution
dc.subject Hospital data
dc.subject Health care system
dc.subject Health management
dc.title Probability distribution analysis of patients arriving at Regional Referral hospital Dodoma, Tanzania (2017-2018).
dc.type Article


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