[Evaluation of a future scenario concerning the use of big data applications to improve the care of people with rare diseases].

Evaluation eines Zukunftsszenarios zur Nutzung von Big-Data-Anwendungen für die Verbesserung der Versorgung von Menschen mit seltenen Erkrankungen.
Acceptance Akzeptanz Barrieren Barriers Befragung Benefits Big Data Big data Evaluation Nutzen Rare diseases Scenario Seltene Erkrankungen Survey Szenario

Journal

Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen
ISSN: 2212-0289
Titre abrégé: Z Evid Fortbild Qual Gesundhwes
Pays: Netherlands
ID NLM: 101477604

Informations de publication

Date de publication:
Dec 2020
Historique:
received: 02 09 2020
revised: 02 11 2020
accepted: 04 11 2020
pubmed: 1 12 2020
medline: 29 12 2020
entrez: 30 11 2020
Statut: ppublish

Résumé

In Germany there are about 4 million people living with a rare disease. Studies have shown that big data applications can improve diagnosis of and research on rare diseases more effectively. However, no concrete comprehensive concept for the use of big data in the care of people with rare diseases has so far been established in Germany. As part of the project "BIDA-SE", which is funded by the German Ministry of Health, a first scenario has been designed to show how big data applications can be usefully incorporated into the care of people with rare diseases. The aim of the present study was to evaluate this scenario with regard to acceptance, (clinical) benefits, economic aspects, and limitations and barriers to its implementation. To evaluate the scenario, an online survey was conducted in Germany in October/November 2019 amongst a total of N = 9 physicians, N = 69 patients with rare diseases/patient representatives, N = 14 IT experts and N = 21 health care researchers. The online questionnaire consisted of both standardized, validated questions taken from already tested survey instruments and additional questions which were constructed on the basis of a preceding literature analysis. The evaluation of the survey was primarily descriptive, with a calculation of frequencies, mean values and standard deviations. The results of the evaluation show that the scenario has been accepted by a majority of all groups surveyed (physicians, patients/patient representatives, IT experts and health care researchers). From the point of view of physicians, patients/patient representatives and health care researchers, the scenario has the potential to accelerate the diagnosis and initiation of therapy and to improve cross-sectoral treatment. From the physician's and health care researcher's perspective, investments in the application presented in the scenario would be profitable. Financing the scenario would, however, require adjusting the reimbursement situation. The limitations and barriers identified by all groups for a medium-term implementation of the scenario can be grouped into seven thematic areas where action is needed: (1) financing and investment, (2) data protection and data security, (3) standards/data sources/data quality, (4) acceptance of technology, (5) integration into the daily work routine, (6) knowledge about availability as well as (7) habits and preferences/physician's role. With the present study, a first interdisciplinary, practical scenario using big data applications was evaluated with regard to acceptance, benefits and limitations/barriers. The scenario is widely accepted among the majority of all surveyed target groups and is considered (clinically) useful, although legal, organisational and technical barriers still need to be overcome for its medium-term implementation. The evaluation results contribute to the derivation of recommendations for action to ensure the medium-term implementation of the scenario and to channel access to the Centres for Rare Diseases in the future. Many activities have been initiated at a national level to improve the health care situation of people with rare diseases. The scenario developed in the "BIDA-SE" project complements these research activities and illustrates how big data applications can be usefully implemented into practice to improve the diagnosis and therapy of people with rare diseases in a sustainable way.

Identifiants

pubmed: 33250393
pii: S1865-9217(20)30174-4
doi: 10.1016/j.zefq.2020.11.002
pii:
doi:

Types de publication

Journal Article

Langues

ger

Sous-ensembles de citation

IM

Pagination

81-91

Informations de copyright

Copyright © 2020. Published by Elsevier GmbH.

Auteurs

Brita Sedlmayr (B)

Zentrum für Evidenzbasierte Gesundheitsversorgung, Universitätsklinikum und Medizinische Fakultät Carl Gustav Carus der Technischen Universität Dresden, Dresden, Deutschland; Institut für Medizinische Informatik und Biometrie, Medizinische Fakultät Carl Gustav Carus, Technische Universität Dresden, Dresden, Deutschland. Electronic address: brita.sedlmayr@tu-dresden.de.

Andreas Knapp (A)

Zentrum für Evidenzbasierte Gesundheitsversorgung, Universitätsklinikum und Medizinische Fakultät Carl Gustav Carus der Technischen Universität Dresden, Dresden, Deutschland.

Michéle Kümmel (M)

Institut für Medizinische Informatik und Biometrie, Medizinische Fakultät Carl Gustav Carus, Technische Universität Dresden, Dresden, Deutschland.

Franziska Bathelt (F)

Institut für Medizinische Informatik und Biometrie, Medizinische Fakultät Carl Gustav Carus, Technische Universität Dresden, Dresden, Deutschland.

Martin Sedlmayr (M)

Institut für Medizinische Informatik und Biometrie, Medizinische Fakultät Carl Gustav Carus, Technische Universität Dresden, Dresden, Deutschland.

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