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Can we accurately forecast non-elective bed occupancy and admissions in the NHS? A time-series MSARIMA analysis of longitudinal data from an NHS Trust
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  • Published on:
    Possible ways to improve the MSARIMA forecasts
    • Rodney Jones, Statistical Advisor Healthcare Analysis & Forecasting

    It is highly likely that the use of the Office for National Statistics output area classification (OAC) may improve the MSARIMA forecasts. This is based on the observation that different social groups exhibit different health care behaviours [1-4]. Hopefully this approach will be of benefit.

    1. Beeknoo N, Jones R. Factors influencing A&E attendance, admissions and waiting times at two London hospitals. Journal of Advances in Medicine and Medical Research 2016;17(10): 1-29.

    2. Beeknoo N, Jones R. Using Social Groups to Locate Areas with High Emergency Department Attendance, Subsequent Inpatient Admission and Need for Critical Care. Journal of Advances in Medicine and Medical Research 2016; 18(6): 1-23. http://www.sciencedomain.org/abstract/16693

    3. Beeknoo N, Jones R Using Social Groups to Locate Areas with High Emergency Department Attendance, Subsequent Inpatient Admission and Need for Critical Care. Journal of Advances in Medicine and Medical Research2016; 18(6): 1-23.

    4. Beeknoo N, Jones R (2016) Using social groups to locate areas of high utilization of critical care. Brit J Healthc Manage 2016; 22(11): 551-560.

    Conflict of Interest:
    None declared.