gms | German Medical Science

73. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC)
Joint Meeting mit der Griechischen Gesellschaft für Neurochirurgie

Deutsche Gesellschaft für Neurochirurgie (DGNC) e. V.

29.05. - 01.06.2022, Köln

Predictive analytics in clinical practice

Predictive analytics im klinischen Alltag

Meeting Abstract

Suche in Medline nach

  • presenting/speaker Hendrik-Jan Mijderwijk - Universitätsklinikum Düsseldorf, Klinik für Neurochirurgie, Düsseldorf, Deutschland
  • Hans-Jakob Steiger - Kantonsspital Aarau, Klinik für Neurochirurgie, Aarau, Schweiz

Deutsche Gesellschaft für Neurochirurgie. 73. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit der Griechischen Gesellschaft für Neurochirurgie. Köln, 29.05.-01.06.2022. Düsseldorf: German Medical Science GMS Publishing House; 2022. DocP003

doi: 10.3205/22dgnc319, urn:nbn:de:0183-22dgnc3190

Veröffentlicht: 25. Mai 2022

© 2022 Mijderwijk et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.


Gliederung

Text

Objective: Predictive analytics are increasingly reported by clinicians. These tools aim to improve patient-outcomes in terms of quality, safety, and efficiency. However, deploying predictive analytics in clinical practice remains challenging today.

Methods: We performed a topic review to highlight several advantages and disadvantages of the application of predictive analytics in clinical practice.

Results: To foster the progress of predictive analytics into the clinical workflow of the neurosurgeon, 1) the used data sets should be more refined to the clinical scenario studied, 2) predictive analytics should ideally be used to study patients in equipoise regarding optimal management, not to study the available data, and 3) neurosurgeons should have knowledge on effective implementation of the designed predictive tools for the right patients.

Conclusion: To flourish and reach its potential, predictive analytics need data that is of adequate quantity and quality, ideally tailored to clinical scenarios in equipoise regarding optimal management. Adequate reporting of predictive analytic tools is incumbent for uptake into clinical workflows. At least for now, the neurosurgeons' knowledge, experience and vigilance remain imperative for applying predictive analytics in clinical practice.

Table 1 [Tab. 1]

Notes: The paper related to this abstract has been published recently [1].


References

1.
Mijderwijk HJ, Steiger HJ. Predictive Analytics in Clinical Practice: Advantages and Disadvantages. In: Staartjes VE, Regli L, Serra C, editors. Machine Learning in Clinical Neuroscience. (Acta Neurochirurgica Supplement; 134). Cham: Springer. pp. 263-268. DOI: 10.1007/978-3-030-85292-4_30 Externer Link