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Need-based care of multi-morbid patients – supporting general practitioners with algorithm-generated recommendations of healthcare services (telemedicine-project ATMoSPHÄRE)

BACKGROUND: The patient-oriented and need-based care of multi-morbid patients with healthcare services and assistive products can be a highly complex task for the general practitioners (GPs). An algorithm-based digital recommendation system (DRS) for healthcare services was developed within the cont...

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Autores principales: Borchers, Peggy, Piller, Steve, Böhme, Mandy, Voigt, Karen, Bergmann, Antje
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8499564/
https://www.ncbi.nlm.nih.gov/pubmed/34625053
http://dx.doi.org/10.1186/s12875-021-01537-2
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author Borchers, Peggy
Piller, Steve
Böhme, Mandy
Voigt, Karen
Bergmann, Antje
author_facet Borchers, Peggy
Piller, Steve
Böhme, Mandy
Voigt, Karen
Bergmann, Antje
author_sort Borchers, Peggy
collection PubMed
description BACKGROUND: The patient-oriented and need-based care of multi-morbid patients with healthcare services and assistive products can be a highly complex task for the general practitioners (GPs). An algorithm-based digital recommendation system (DRS) for healthcare services was developed within the context of the telemedicine research project ATMoSPHÄRE. The plausibility of the DRS was tested and the results used to examine if, and to what degree, the DRS provides useful assistance to GPs. METHODS: The plausibility of the recommendations of the DRS were tested with the Delphi procedure (n = 8) and Interviews (n = 4) in collaboration with the GPs. They proposed services and assistive products they considered appropriate for two multi-morbid patients. Furthermore, GPs had to report whether, and to what degree they deemed the algorithm-generated recommendations appropriate. Significant quantitative differences between the GPs’, and the algorithm-generated, recommendations were evaluated with paired-samples-Wilcoxon-test. RESULTS: The first Delphi round revealed a high variability regarding the amount and character of services recommended by the physicians (1 to 10 recommendations, mean = 5.6, sd = 2.8). These professional recommendations converged after consideration of the algorithm-generated recommendations. The number of algorithm-generated recommendations which were judged as appropriate ranged between 7 and 17 of a total of 20 (mean = 11.9, sd = 2.5). The interviews revealed that the additional algorithm-generated recommendations which were judged appropriate contained mainly social care services. CONLUSION: The DRS provides GPs with additional appropriate recommendations for the need-based care of patients, which may not have been previously considered. It can therefore be assessed as a helpful complement in the primary care of multi-morbid patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12875-021-01537-2.
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spelling pubmed-84995642021-10-08 Need-based care of multi-morbid patients – supporting general practitioners with algorithm-generated recommendations of healthcare services (telemedicine-project ATMoSPHÄRE) Borchers, Peggy Piller, Steve Böhme, Mandy Voigt, Karen Bergmann, Antje BMC Fam Pract Research Article BACKGROUND: The patient-oriented and need-based care of multi-morbid patients with healthcare services and assistive products can be a highly complex task for the general practitioners (GPs). An algorithm-based digital recommendation system (DRS) for healthcare services was developed within the context of the telemedicine research project ATMoSPHÄRE. The plausibility of the DRS was tested and the results used to examine if, and to what degree, the DRS provides useful assistance to GPs. METHODS: The plausibility of the recommendations of the DRS were tested with the Delphi procedure (n = 8) and Interviews (n = 4) in collaboration with the GPs. They proposed services and assistive products they considered appropriate for two multi-morbid patients. Furthermore, GPs had to report whether, and to what degree they deemed the algorithm-generated recommendations appropriate. Significant quantitative differences between the GPs’, and the algorithm-generated, recommendations were evaluated with paired-samples-Wilcoxon-test. RESULTS: The first Delphi round revealed a high variability regarding the amount and character of services recommended by the physicians (1 to 10 recommendations, mean = 5.6, sd = 2.8). These professional recommendations converged after consideration of the algorithm-generated recommendations. The number of algorithm-generated recommendations which were judged as appropriate ranged between 7 and 17 of a total of 20 (mean = 11.9, sd = 2.5). The interviews revealed that the additional algorithm-generated recommendations which were judged appropriate contained mainly social care services. CONLUSION: The DRS provides GPs with additional appropriate recommendations for the need-based care of patients, which may not have been previously considered. It can therefore be assessed as a helpful complement in the primary care of multi-morbid patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12875-021-01537-2. BioMed Central 2021-10-08 /pmc/articles/PMC8499564/ /pubmed/34625053 http://dx.doi.org/10.1186/s12875-021-01537-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Borchers, Peggy
Piller, Steve
Böhme, Mandy
Voigt, Karen
Bergmann, Antje
Need-based care of multi-morbid patients – supporting general practitioners with algorithm-generated recommendations of healthcare services (telemedicine-project ATMoSPHÄRE)
title Need-based care of multi-morbid patients – supporting general practitioners with algorithm-generated recommendations of healthcare services (telemedicine-project ATMoSPHÄRE)
title_full Need-based care of multi-morbid patients – supporting general practitioners with algorithm-generated recommendations of healthcare services (telemedicine-project ATMoSPHÄRE)
title_fullStr Need-based care of multi-morbid patients – supporting general practitioners with algorithm-generated recommendations of healthcare services (telemedicine-project ATMoSPHÄRE)
title_full_unstemmed Need-based care of multi-morbid patients – supporting general practitioners with algorithm-generated recommendations of healthcare services (telemedicine-project ATMoSPHÄRE)
title_short Need-based care of multi-morbid patients – supporting general practitioners with algorithm-generated recommendations of healthcare services (telemedicine-project ATMoSPHÄRE)
title_sort need-based care of multi-morbid patients – supporting general practitioners with algorithm-generated recommendations of healthcare services (telemedicine-project atmosphäre)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8499564/
https://www.ncbi.nlm.nih.gov/pubmed/34625053
http://dx.doi.org/10.1186/s12875-021-01537-2
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