Grøntved, Simon

Jensen, Christina Mohr

Johnsen, Søren Paaske

Kirkeby, Mette Jørgine

Mainz, Jan

Valentin, Jan Brink

English

    Aalborg UniversitetP89 Forecasting models for healthcare planning suffers from inadequate performanceevaluationGrøntved, Simon; Kirkeby, Mette Jørgine; Johnsen, Søren Paaske; Jensen, Christina Mohr;Mainz, Jan; Valentin, Jan BrinkCreative Commons LicenseUnspecifiedPublication date:2022Document VersionPublisher's PDF, also known as Version of recordLink to publication from Aalborg UniversityCitation for published version (APA):Grøntved, S., Kirkeby, M. J., Johnsen, S. P., Jensen, C. M., Mainz, J., & Valentin, J. B. (2022). P89 Forecastingmodels for healthcare planning suffers from inadequate performance evaluation. Poster presented at 43rdAnnual Conference of the International Society for Clinical Biostatistics, Newcastle upon Tyne, United Kingdom.General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.            - Users may download and print one copy of any publication from the public portal for the purpose of private study or research.            - You may not further distribute the material or use it for any profit-making activity or commercial gain            - You may freely distribute the URL identifying the publication in the public portal -Take down policyIf you believe that this document breaches copyright please contact us at vbn@aub.aau.dk providing details, and we will remove access tothe work immediately and investigate your claim.Downloaded from vbn.aau.dk on: November 19, 2022dacs.aau.dkMost of these models are not properly validated!Simon Grøntved1,2, Mette Jørgine Kirkeby2, Søren Paaske Johnsen2, Christina Mohr Jensen1, Jan Mainz1, Jan Brink Valentin21: Region North Denmark Psychiatry, Aalborg, Denmark2: Danish Center for Clinical Health Care Research, Department of Clinical Medicine, Aalborg University, Aalborg, DenmarkP89 Forecasting models for healthcare planning suffers from inadequate performance evaluationIntroduction: The prediction of future health care capacity needs continuous to be of high demand. Many such models have been developed for disease incidence and prevalence, covering viral diseases such as COVID-19 as well as circulatory and neurological diseases. However, the usefulness and successful implementation of such models in health care planning remains unclear. Thus, following a systematic review and evidence mapping of health care planning, we aimed to describe to which extent such models are validated. Methods: All publications retrieved from PubMed and Embase, matching our predefined search strings, were screened for relevance by two independent reviewers using the Rayyan online tool. All publications that could not be excluded by title and abstract were retrieved for full text synthetization.Results: Of 5415 articles screened 263 were read in full text, of those 105 were deemed eligible for the review. Of the 105 forecasting models 45 was not at all validated, 3 claimed to be validated, but there was no indication of validation in the article. 11 models were only validated by some form of model fit assessment (apparent validation). Temporal validation was performed for 39 models, 4 models were geographically validated, and 3 models were validated with random splits. The most common disease groups are cancer (22 models) and infectious disease (27 models).Discussion: Most forecasting models for health care capacity needs are not properly validated. Temporal validation is an appropriate method for evaluating performance of a time trend extrapolation, it is also the most commonly used approach. Implementing a model that is not properly validated, can lead to capacity planning decisions that wrongfully allocates resources such that waiting lists in some fields grow, while other fields waste resources on overcapacity.Conclusion: The research on prediction models in health care planning is of limited scope. Meantime, the use of performance evaluation for these models is inadequate. Thus, more research on performance and implementation of forecasting models for health care capacity needs are warranted.sigro@rn.dk/SimonGrontved@SimonGrontvedISCB43 August 2022 Newcastle EnglandRecords identified from:PubMed (n = 1998)Embase (n = 3575)Records removed before screening:Duplicate records removed  (n = 158)Records screened(n = 5415)Records excluded(n = 5153)Reports sought for retrieval(n = 262 )Reports not retrieved(n = 5)Reports assessed for eligibility(n = 257)Reports excluded:Not forecast study (n = 46)Conf. Abstract (n = 27)No forecast in article (n = 27)Foreign language (n = 26)Forecast not aim (n = 13)Not hospital setting (n = 6)Outcome not capacity (n = 5)Already included (n = 2)Studies included in review(n = 105)Identification of studies via PubMed and EmbaseIdentificationScreeningIncludedNo validation (n = 45)No indication of validation (n = 3)Only model fit (n = 11)Temporal validation (n = 39)Geographical validation (n = 4)Random split (n = 3)

P89 Forecasting models for healthcare planning suffers from inadequate performance evaluation

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P89 Forecasting models for healthcare planning suffers from inadequate performance evaluation

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