Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

A multi-echelon menu item forecasting system for hospitals.

A M Messersmith, A N Moore, L W Hoover

    Journal of the American Dietetic Association
    |May 1, 1978
    PubMed
    Summary
    This summary is machine-generated.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    Ex Vivo Modeling of Multidomain Peptide Hydrogels with Intact Dental Pulp.

    Journal of dental research·2015
    Same author

    Histone deactylase inhibition combined with behavioral therapy enhances learning and memory following traumatic brain injury.

    Neuroscience·2009
    Same author

    Persistent working memory dysfunction following traumatic brain injury: evidence for a time-dependent mechanism.

    Neuroscience·2009
    Same author

    Performance in long-term memory tasks is augmented by a phosphorylated growth factor receptor fragment.

    Journal of neuroscience research·2004
    Same author

    Expression of cytochromes P450 4F4 and 4F5 in infection and injury models of inflammation.

    Biochimica et biophysica acta·2003
    Same author

    The role of extracellular signal-regulated kinase in cognitive and motor deficits following experimental traumatic brain injury.

    Neuroscience·2002

    This study developed a multi-echelon forecasting system for hospital menu-item demand, reducing forecast error costs by 40% compared to manual methods. The system improves accuracy for patient meal services up to 28 days in advance.

    Area of Science:

    • Operations Research
    • Healthcare Management
    • Statistical Forecasting

    Background:

    • Accurate demand forecasting is crucial for efficient hospital food service operations.
    • Existing manual forecasting methods can be labor-intensive and prone to significant errors.
    • Optimizing menu-item demand prediction impacts inventory management and waste reduction.

    Purpose of the Study:

    • To design and evaluate a multi-echelon statistical forecasting system for hospital menu-item demand.
    • To compare the cost-efficiency of the developed system against traditional manual forecasting techniques.
    • To analyze diet category distribution and menu-item preferences for improved demand prediction.

    Main Methods:

    • A three-echelon system was developed: patient census forecasting, diet category census estimation, and menu-item demand calculation.

    Related Experiment Videos

  • Adaptive exponential smoothing and Box-Jenkins formulations were employed for statistical forecasting.
  • A cost function evaluated system performance over a nine-week period using eighteen weeks of historical supper data.

    • Main Results:

    • The multi-echelon forecasting system demonstrated a significant reduction in forecast error costs, approximately 40% lower than manual methods.
    • Analysis of historical data provided insights into diet category distribution and menu-item preferences.
    • The system effectively forecasts demand for menu items from one to twenty-eight days prior to service.

    Conclusions:

    • Statistical forecasting systems offer a more cost-effective approach to predicting hospital menu-item demand compared to manual techniques.
    • The developed multi-echelon system enhances operational efficiency in hospital food services.
    • Accurate demand forecasting is essential for minimizing costs and improving resource allocation in healthcare settings.