Probability distribution analysis and forecasting of patients arriving at regional referral hospital Dodoma, Tanzania (during the year 2017-2018)

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dc.contributor.authorLoibor, Julius Moinget
dc.date.accessioned2020-08-25T08:28:59Z
dc.date.available2020-08-25T08:28:59Z
dc.date.issued2019
dc.descriptionDissertation (Msc. Statistics)en_US
dc.description.abstractHealth care is essential to the general welfare of society. Studying the hospital patients' data distribution through the probability distribution analysis and forecasting time series 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. 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. The study identified ARIMA (1, 1, 0) model as the best predictive model for the daily average number of outpatients visiting the hospital outpatient department for two years. In order to prepare adequate facilities for the overwhelming outpatients in the outpatient department at the hospital, the DRRH administration should make use of the probability distributions and forecasted figures to plan further development activities for the hospital.en_US
dc.identifier.citationLoibor, J. M. (2019). Probability distribution analysis and forecasting of patients arriving at regional referral hospital Dodoma, Tanzania (during the year 2017-2018). (Master's Dissertation). The University of Dodoma, Dodoma.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12661/2408
dc.language.isoenen_US
dc.publisherThe University of Dodomaen_US
dc.subjectHealth careen_US
dc.subjectHealth servicesen_US
dc.subjectHealth informationen_US
dc.subjectProbability distributionen_US
dc.subjectProbability distribution analysisen_US
dc.subjectProbability distribution forecastingen_US
dc.subjectReferral hospitalen_US
dc.subjectRegional hospitalen_US
dc.subjectDodoma hospitalen_US
dc.subjectHealth systemen_US
dc.subjectPatientsen_US
dc.subjectOutpatienten_US
dc.subjectInpatienten_US
dc.titleProbability distribution analysis and forecasting of patients arriving at regional referral hospital Dodoma, Tanzania (during the year 2017-2018)en_US
dc.typeDissertationen_US
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