Intelligent Conversational Agents in Healthcare: Hype or Hope? · 2019-04-16 · 2019;259:101-104...

BFH | Medizininformatik | Klinische Studien

Intelligent Conversational Agents in Healthcare:

Hype or Hope?

Kerstin Denecke, Mauro Tschanz, Tim Dorner, Richard May

▶ Technik und Informatik / Medizininformatik

BFH | Medizininformatik | Healthcare of the Future Conference 2019

Intelligent healthcare assistants

2

CLAIRE eMMA Ana


CLAIRE – Patient education in a virtual reality

3


Electronic Medication Management Assistant with eMMA

4

Record reasons for

non-compliance

Documentation

Clarify importance of

medication


Self anamnesis with Ana


Research question

6

What are opportunities and

challenges of chatbots in

healthcare?


▶ Strengths and weaknesses

▶ Internal features: features of the chatbots

themselves

▶ Opportunities

▶ External features: economic, technical,

social, political, legal, and environmental

features representing the context within

which the chatbots are implemented

▶ Threats

▶ External features: that may prevent the

real-world implementation of chatbots in

healthcare

SWOT analysis

7


▶ Guided conversation; complete

data collection

▶ Address user needs

▶ Explain, motivate

▶ Bond of trust with the system

▶ Integration into care process

Strengths

8


▶ Too many interactions for simple tasks

▶ Too much conversation

▶ Manually built knowledge bases restrict

conversation capabilities

▶ Inflexibility / Clear scope of chatbot

Weaknesses

9


▶ Tailored functions (e.g. reading QR code,

retrieving data)

▶ Support repetitive tasks

▶ Natural, human-like interaction

▶ Support of care process and become part

of interdisciplinary treatment path

Opportunities

10


▶ Effects on patient-doctor relationship

▶ Reservations of physicians

▶ Gaining interest of patients

▶ Dependency on third party services (speech

recognition)

▶ Data protection, medical device regulations

Threats

11


▶ Use cases for chatbots in healthcare exist

▶ Bridge the gap between patient and doctor

▶ Natural language understanding is crucial

▶ Limit the complexity of the conversations

▶ Collect symptoms or patient history

▶ Monitor health status

▶ Integrate with healthcare IT

Conclusion and roadmap

12


▶ Denecke K, Pöpel A, Lutz Hochreutener S, May R: Self anamnesis with a

Conversational User Interface: Concept and Usability Study. Methods Inf Med. 2018

Nov;57(5-06):243-252

▶ Tschanz M, Dorner TL, Denecke K. eMedication Meets eHealth with the Electronic

Medication Management Assistant (eMMA). Stud Health Technol

Inform.2017;236:196-203

▶ Hess G, Fricker G, Denecke K: Improving and evaluating eMMA’s communication

skills: A chatbot for managing medication, Stud Health Technol Inform.

2019;259:101-104

▶ Bürkle T, Denecke K, Lehmann M, Zetz E, Holm J. Integrated Care Processes

Designed for the Future Healthcare System. Stud Health Technol Inform.

2017;245:20-24

▶ Denecke K, Lutz Hochreutener S, Pöpel A, May R. Talking to Ana: A Mobile Self-

Anamnesis Application with Conversational User Interface. In Proceedings of the

2018 International Conference on Digital Health (DH '18). ACM, New York, NY,

USA, 2018: 85-89

References

13


Intelligent Conversational Agents in Healthcare: Hype or Hope?

14

Thank you for yourattention!

Kerstin Denecke

[email protected] University of Applied Sciences

Intelligent Conversational Agents in Healthcare: Hype or Hope? · 2019-04-16 · 2019;259:101-104...

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