Due to the prevalence of personal health tracking, cases of self-logged data being utilized in the clinic are gradually increasing. However, obstacles to clinicians' ability to further adopt such data-driven medical consultations in the existing workflow remain, such as lack of time and poor interoperability. In this paper, we conducted a workshop to design a clinician interface supporting the integration of data-driven consultation into the existing workflow and investigate the role of the interface in situ. After implementing the clinician interface designed based on the workshop results, we observed 32 cases of actual use within the clinical context. We found that our interface, DataMD, helped the clinician construct a new workflow, enhanced the clinician's counseling skills, and facilitated more in-depth conversation. This paper contributes to empirically identifying the role of a clinician interface through a user-centered design approach.

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Prescribing 10,000 Steps like Aspirin
Designing a Novel Interface for Data-Driven Medical Consultation
Yoojung Kim, Eunyoung Heo, Hyunjeong Lee, Sookyoung Ji,
Jueun Choi, Jeong-Whun Kim, Joongseek Lee, Sooyoung Yoo
CHI 2017
User Experience Lab, Seoul National University, Seoul, South Korea
Department of Otorhinolaryngology, Seoul National University Bundang Hospital, Seongnam, South Korea
Center for Medical Informatics, Seoul National University Bundang Hospital, Seongnam, South Korea

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Let’s suppose you are suffering from chronic diesease
BACKGROUND DESIGN WORKSHOP IN-SITU FIELD STUDY DISCUSSION CONCLUSION

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Your doctor knows you binged from your data
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The benefits are obvious: lifestyle modification
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But you might know the reality
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Doctors are too busy
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Can design solve these problems?
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Can design solve these problems?
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Design workshop process
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Brief summary: Design Goals & Guidelines
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All-in-one Interface is more efficient
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Sensemaking at a glance with hierarchical structures
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Prefer to familiar ones due to the medical culture
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Medical knowledge and experiences are criteria
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Numeric input fields for prescribing goals

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BACKGROUND DESIGN WORKSHOP IN-SITU FIELD STUDY DISCUSSION CONCLUSION
Numeric input fields for prescribing goals

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Finally, we implement DataMD
and embedded it in the current EMR system.

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Field study process
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Field study process
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Field study process
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Brief summary: Findings from observations
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The workflow is changed

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Counseling skills with data is improved

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Facilitate In-depth conversation
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Facilitate In-depth conversation
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Is it possible? Is it feasible? Is it better?

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Doctors consider PGD and medical data is different
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How to deal with prescribing goals

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We are preparing next steps
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42. Summary
Yoojung Kim tendtoyj@gmail.com
www.yoojung.kim
+82 10 3830 1297
Ph.D. Student
User Experience Lab
Seoul Nation Univ.

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Potential Risks of Using PGD in Clinical Settings
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Potential Risks of Using PGD in Clinical Settings
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Disparity between Expectations and Actual Use
BACKGROUND DESIGN WORKSHOP IN-SITU FIELD STUDY DISCUSSION CONCLUSION