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    Forecasting Patient Needs in a Donor Funded Health Care Project in Kenya

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    Date
    2013-08
    Author
    Wainaina, Gituro
    Njoroge, Brian M.
    Type
    Article
    Language
    en
    Metadata
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    Abstract
    Forecasts are crucial for practically all economic and business decisions. The focus of this research paper is in the area of forecasting. The research approach adopted is a case study of the Nutrition and HIV Program (NHP), which is a donor funded public health project. The general objective of this paper was to forecast the demand for patient needs in a donor funded project. Specifically, this paper sought to establish a suitable forecasting method that can accurately predict demand for nutrition commodities. In order to establish a more suitable forecasting method, Univariate Box – Jenkins (UBJ) methodology was used and two models were tested and Auto Regressive Integrated Moving Average (ARIMA (0, 1, 2)) model provided a better fit and was chosen as the model of choice for a short run forecast horizon. The main conclusion drawn from this paper is that, UBJ-ARIMA models are useful as benchmarks for forecasting and therefore they should be viewed as complements to a reliable forecasting process. This paper recommends that public health projects need to consider adopting business forecasting methods that will provide a better glimpse of the future based on historical events rather than relying on disease morbidity data trends.
    URI
    http://journals.uonbi.ac.ke/damr/article/view/1162
    http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/56364
    Citation
    DBA Africa Management Review, August 2013, Vol 3 No 2. Pp. 24-39
    Sponsorhip
    University of Nairobi, School of Business
    Publisher
    DBA Africa Management Review
     
    School of Business, University of Nairobi
     
    Subject
    Auto-correlation function
    Partial auto-correlation function
    Residual auto-correlations short run forecast
    Public health project
    Un-differenced
    Stationarity
    ARIMA
    UBJ
    Description
    Full Text Article
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    • Faculty of Arts & Social Sciences (FoA&SS / FoL / FBM) [6704]

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