Bringing digital scribes into orthopedic consultations

Towards AI-assisted clinical documentation

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Abstract

Clinical documentation takes up 40% of clinicians’ time. To ease the administrative burden of clinicians, digital scribes offer the potential to automate clinical note taking. Digital scribes are intelligent documentation softwares that combine automated speech recognition (ASR) and natural language processing (NLP). Digital scribes transcribe clinician-patient consultations and convert the conversation into structured clinical notes. Attendi, the client is developing a digital scribe for orthopedics: the Assistant. Hip arthrosis consultations have a well-structured anamnesis, therefore a promising use case for the digital scribe.

This Master thesis investigates the clinician perspective of implementing the Assistant. Literature was reviewed to understand the problem space and the design implications of the enabling technologies. Core concepts in human-AI collaboration such as system transparency and human control were identified to design for hybrid documentation. Also, the perspectives of recording consultations were translated into values for hospitals, clinicians and patients. The findings lead to both mutual benefits and tensions for the clinician-patient relationship and obstacles for implementation.

To contribute to developing the Assistant, user research was carried out in context by shadowing orthopedic surgeons to see their day-to-day workflow and understand the current cycle of clinical documentation. Several surgeons were interviewed to gain more in-depth views about the digital scribe. As synthesis, personas and journey maps were created both for a typical consultation cycle and a daily workflow. From the research phase, a list of user requirements were gathered in order to aid the design phase and future development. Finally, the envisioned user journey is presented in a service blueprint with the developed interface of the Assistant.