Complementary Medicine Research

Editorial

Free Access

Digital Integrative Medicine – Just Knocking on Wood or a Bit More?

Ostermann T.

Author affiliations

Department of Psychology and Psychotherapy, Witten/Herdecke University, Witten, Germany

Corresponding Author

Thomas Ostermann

Department of Psychology and Psychotherapy, Witten/Herdecke University

Alfred-Herrhausen-Straße 50

DE–58448 Witten (Germany)

E-Mail thomas.ostermann@uni-wh.de

Related Articles for ""

Complement Med Res 2019;26:1–2

Digital health according to the position paper of the Working Group “Digital Health” of the German Network for Healthcare Research (DNVF) summarizes “information and communication technologies in healthcare, including e-health, mobile health, telemedicine, big data, health apps and others” [1]. By using new approaches of data analysis in fields like deep learning, causal modeling, or data mining, digital health is considered as a complementary source for evidence-based medicine alongside the traditional clinical trial approach [2] and a promising area in the field of integrative medicine [3].

Although one would generally not expect the field of integrative medicine to be on the cutting edge of digitalization, a glance at the history of such applications reveals surprising facts about the interaction between integrative medicine and information technology: almost at the same time when Babbage’s Analytical Machine came out in the 1830s, Semen Korsakov, an official working at the Statistics Department of the Police Ministry who is known in homeopathy for his potentisation approach, constructed the so called “Homeoscope” [4]. Based on the method of information storage in punch cards, he was the first to apply a mechanic binary storage in patient care almost a century before the first punch card computers were used in algebraic problem solving and 130 years before Steinbuch invented his concept of the Learning Matrix [5]. Urged by the cholera epidemics in Russia to facilitate the search for information, he “stored” characteristic symptoms of a disease as a hole in the columns of a wooden plate. When a patient described his symptoms, pins were placed in a wooden bar. When moving the bar over the plate it snaps if and only if all symptoms correspond to a certain disease. Unfortunately Korsakov’s innovation was ignored by the Academy of Sciences in St. Petersburg stating that “Mr. Korsakov wasted too much intelligence, in order to teach other people to live without intelligence” [6].

But also in the early application of information technology, integrative medicine found its place at the very cutting edge of research: in 1966, Pirtkien and Kenzelmann [7] described a computer program for homeopathic case taking using an IBM 1401 computer. Some 20 years later, Tani and Akahori [8] in 1985 implemented an advanced computer-based information retrieval in the field of traditional Chinese medicine based on 830 traditional remedies, while in music therapy Hasselbring and Duffus [9] described “Using Microcomputer Technology in Music Therapy for Analyzing Therapist and Client Behavior.”

Never heard of these applications before? Well, they never really made it into daily patient care. And this is a major obstacle for almost all digital innovations: there is “no consistent association” between the use of e-health systems and better quality in patient care if they are used isolated and are not integrated in routine daily care, as Romano and Stafford [10] found in their review on electronic health records and clinical decision support systems. Thus integrative medicine, if “integrative” also includes modern technologies, could be a blueprint for a patient centered environment for digital health applications and thus would attract scientists from fields like data analytics or health informatics for joint projects. As a desired side effect this would also underpin the underlying scientific attitude of integrative medical approaches.

For the patient, digital health at first sight might be associated with alienation from the physician. But in particular in the field of shared decision-making projects such as OpenNotes make medical records more accessible for the patient [11]. Thus patients’ interest in reading the medical notes may increase and in the long run strengthen the therapeutic alliance of patient and physician.

Still not convinced? Well, let’s have a look at the original German statement from the publication of Pirtkien and Kenzelmann [7] from 1966: “Die Rechenmaschine ersetzt nicht den Arzt! Er muss wie bisher die Anamnese erheben und seinen Befund festlegen. Für die Diagnose erhält er dann eine Gedächtnisstütze, Entscheidungen werden ihm aber nicht abgenommen! Die Technik verdummt den Arzt nicht, sondern vergrößert sein Wissen durch den Zwang, sich mit einer größeren Zahl von Möglichkeiten in der Diagnostik – auch in der der Arzneimittel – auseinanderzusetzen.” Isn’t that really integrative? Perhaps more than a bit!



References

  1. Vollmar HC, Kramer U, Müller H, Griemmert M, Noelle G, Schrappe M. Digitale Gesundheitsanwendungen – Rahmenbedingungen zur Nutzung in Versorgung, Strukturentwicklung und Wissenschaft – Positionspapier der AG Digital Health des DNVF. Gesundheitswesen. 2017 Dec;79(12):1080–92.
  2. Sim I. Two ways of knowing: big data and evidence-based medicine. Ann Intern Med. 2016 Apr;164(8):562–3.
  3. Li GZ, Liu BY. Big data is essential for further development of integrative medicine. Chin J Integr Med. 2015 May;21(5):323–31.
  4. Velminski W. Ernst W. Semën Karsakov. Ideenmaschine: Von der Homöopathie zum Computer. Berlin: Kadmos-Verlag; 2008.
  5. Ostermann T. Telemedizin, E-Health und M-Health. In: Walach H, Michael S, Schlett S, editors. Das große Komplementär-Handbuch: für Apotheker und Ärzte. Stuttgart: Wissenschaftliche Verlagsgesellschaft; 2017. p. 386–93.
  6. Shilov VV, Silantiev SS. ‘Machines à Comparer les Idées’ of Semen Korsakov: First Step Towards AI. In: IFIP International Conference on the History of Computing. Heidelberg: Springer International Publishing; p. 71–86.
    External Resources
  7. Pirtkien R, Kenzelmann E. Die Arzneifindung in der Homöotherapie mit Hilfe eines Computers. AHZ. 1966;211(2):62–9.
  8. Tani S, Akahori Y. An approach to advanced computer-based information retrieval in the field of traditional Chinese medicine. I. Making a data base in the field of Chinese herbal medicine. J Tradit Chin Med. 1985 Jun;5(2):107–14.
    External Resources
  9. Hasselbring TS, Duffus NA. Using microcomputer technology in music therapy for analyzing therapist and client behavior. J Music Ther. 1981;18(4):156–65.
  10. Romano MJ, Stafford RS. Electronic health records and clinical decision support systems: impact on national ambulatory care quality. Arch Intern Med. 2011 May;171(10):897–903.
  11. Esch T: OpenNotes, Patient Narratives, and Their Transformative Effects on Patient-Centered Care. NEJM Catalyst. 2018 Oct 4.

Author Contacts

Thomas Ostermann

Department of Psychology and Psychotherapy, Witten/Herdecke University

Alfred-Herrhausen-Straße 50

DE–58448 Witten (Germany)

E-Mail thomas.ostermann@uni-wh.de


Article / Publication Details

Received: January 17, 2019
Accepted: January 18, 2019
Published online: February 18, 2019
Issue release date: February 2019

Number of Print Pages: 2
Number of Figures: 0
Number of Tables: 0

ISSN: 2504-2092 (Print)
eISSN: 2504-2106 (Online)

For additional information: https://beta.karger.com/CMR


Copyright / Drug Dosage / Disclaimer

Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

References

  1. Vollmar HC, Kramer U, Müller H, Griemmert M, Noelle G, Schrappe M. Digitale Gesundheitsanwendungen – Rahmenbedingungen zur Nutzung in Versorgung, Strukturentwicklung und Wissenschaft – Positionspapier der AG Digital Health des DNVF. Gesundheitswesen. 2017 Dec;79(12):1080–92.
  2. Sim I. Two ways of knowing: big data and evidence-based medicine. Ann Intern Med. 2016 Apr;164(8):562–3.
  3. Li GZ, Liu BY. Big data is essential for further development of integrative medicine. Chin J Integr Med. 2015 May;21(5):323–31.
  4. Velminski W. Ernst W. Semën Karsakov. Ideenmaschine: Von der Homöopathie zum Computer. Berlin: Kadmos-Verlag; 2008.
  5. Ostermann T. Telemedizin, E-Health und M-Health. In: Walach H, Michael S, Schlett S, editors. Das große Komplementär-Handbuch: für Apotheker und Ärzte. Stuttgart: Wissenschaftliche Verlagsgesellschaft; 2017. p. 386–93.
  6. Shilov VV, Silantiev SS. ‘Machines à Comparer les Idées’ of Semen Korsakov: First Step Towards AI. In: IFIP International Conference on the History of Computing. Heidelberg: Springer International Publishing; p. 71–86.
    External Resources
  7. Pirtkien R, Kenzelmann E. Die Arzneifindung in der Homöotherapie mit Hilfe eines Computers. AHZ. 1966;211(2):62–9.
  8. Tani S, Akahori Y. An approach to advanced computer-based information retrieval in the field of traditional Chinese medicine. I. Making a data base in the field of Chinese herbal medicine. J Tradit Chin Med. 1985 Jun;5(2):107–14.
    External Resources
  9. Hasselbring TS, Duffus NA. Using microcomputer technology in music therapy for analyzing therapist and client behavior. J Music Ther. 1981;18(4):156–65.
  10. Romano MJ, Stafford RS. Electronic health records and clinical decision support systems: impact on national ambulatory care quality. Arch Intern Med. 2011 May;171(10):897–903.
  11. Esch T: OpenNotes, Patient Narratives, and Their Transformative Effects on Patient-Centered Care. NEJM Catalyst. 2018 Oct 4.
Stay Up to Date Banner Stay Up to Date Banner
TOP