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

Forecasting patient census: commonalities in time series models

S D Wood

    Health Services Research
    |January 1, 1976
    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

    An Investigation of the Stability of Thermistors.

    Journal of research of the National Bureau of Standards (1977)·2021
    Same author

    Our approach to changing the culture of caring for the acutely unwell patient at a large UK teaching hospital: A service improvement focus on Early Warning Scoring tools.

    Intensive & critical care nursing·2015
    Same author

    Experience of implementing an adult educational approach to treating anxiety disorders.

    Journal of psychiatric and mental health nursing·2005
    Same author

    Structure of the native (unligated) mannose-specific bulb lectin from Scilla campanulata (bluebell) at 1.7 A resolution.

    Acta crystallographica. Section D, Biological crystallography·1999
    Same author

    Strategies for improving health plan member retention.

    Healthcare financial management : journal of the Healthcare Financial Management Association·1999
    Same author

    Crystallization and preliminary structural studies of Scilla campanulata lectin complexed with alpha1-6 mannobiose.

    Acta crystallographica. Section D, Biological crystallography·1998
    Same journal

    Attrition of the Midwifery Workforce: Understanding Factors Associated With Leaving the Profession.

    Health services research·2026
    Same journal

    Engaging Families in Pediatric Care Management: A Qualitative Study From the North Carolina Integrated Care for Kids Model.

    Health services research·2026
    Same journal

    The Effect of Hospital-Physician Vertical Integration on Utilization-Driven Changes in Healthcare Spending for an All-Payer Population With Multiple Chronic Conditions.

    Health services research·2026
    Same journal

    The Association Between Sepsis Coding and Payment to U.S. Hospitals.

    Health services research·2026
    Same journal

    Stagnation in Achieving Recommended Methadone Doses in Opioid Use Disorder Treatment.

    Health services research·2026
    Same journal

    Promoting Transplant Access Through Dialysis Facility Performance Metrics: A Double-Edged Sword.

    Health services research·2026
    See all related articles

    Accurate patient census forecasting is achieved using integrated autoregressive moving average (IARMA) models. A general model, applicable across hospitals, shows comparable accuracy to institution-specific forecasts.

    Area of Science:

    • Healthcare management
    • Operations research
    • Time series analysis

    Background:

    • Accurate patient census forecasting is crucial for hospital resource allocation and operational efficiency.
    • Existing forecasting methods may lack generalizability across different healthcare institutions.
    • Integrated Autoregressive Moving Average (IARMA) models offer a potential framework for robust forecasting.

    Purpose of the Study:

    • To develop and validate highly accurate patient census forecasting models for five distinct hospitals.
    • To establish a general IARMA forecasting model applicable across multiple institutions.
    • To compare the performance of the general model against institution-specific models.

    Main Methods:

    • Specification of five hospital-specific patient census forecasting models using a general equation for Integrated Autoregressive Moving Average (IARMA) forecasts.

    Related Experiment Videos

  • Development of a generalized IARMA census forecasting model based on common features identified across the five institutional models.
  • Comparative analysis of forecast accuracy between the general model and the institution-specific models.

    • Main Results:

    • Highly accurate patient census forecasts were achieved for all five hospitals using the specified IARMA models.
    • The general IARMA forecasting model demonstrated comparable accuracy to the institution-specific models.
    • The study validates the utility of a generalized approach to patient census forecasting.

    Conclusions:

    • A general Integrated Autoregressive Moving Average (IARMA) model can provide highly accurate patient census forecasts across multiple hospitals.
    • The generalized model offers a potentially more efficient and scalable solution compared to developing numerous institution-specific models.
    • This approach supports improved hospital resource management and operational planning.