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Transcript

PRESENTATION BY: GODFRED MAKUMATOR

The future of Clinical Notes Using Voice-to-text Solutions

SEERS HEALTH

06/10/18

HINF 4301HEALTH INFORMATICS MODULE 10

Thank you

References

Meeting Meaningful use

Benefit to workforce

Meeting standards

Value to EHR

Features

Introduction- why now!

Index

The next best thing for Seers health is a new voice-to-text feature on our E.H.R. 1. Increase efficiency. 2. Increase the workflow of clinicians. 3. Reduce cost of care. (Robert et al. 2014)

WHY NOW!

The future of clinical note is voice-to-text recognition

06/10/18

1. Speech Recognition 2. Real-time transcription 3. Natural Language Processing(NLP) 4. Offline mode 5. Voice commands(Smith-Goodson n.d.)

Features

06/10/18

1. Captures complete information(Kumah-Crystal et al. 2018). 2. Clinical notes are readily available for other clinicians. 3. Improves and Encourages E.H.R. use. 4. Support billing and claims management(O’Connor, n.d.).. 5. Improves treatment quality.

Value to EHR

1. Captures patient data more accurately. 2. Clinical notes are readily available for patients. 3. Increase patient-centered care . 4. Reduces patient wait time. (Saxena et al. 2018)

Meeting Meaningful use

1. Reduces clinician’s burnout. 2. Instant availability of clinical notes 3. Notes are more accurate for nurses and other clinicians to infer from for verification. 4. Improves workflow(O’Connor, n.d.).

Benefit to workforce

(Basil et al. 2022)

Regular updates and running of checks.

The vendor follows security best practices and standards

The use of the technology is HIPAA compliance through training of all clinicians

Encryption of the end-to-end voice data.

How It Meets Security Standards

Benefit to Seers Health

1. Reduce time spent on typing and increase time spent on patient- improve patient-centered care. 2. Reduce the cost of care ( reduce misdiagnosis, litigations, and mortality ). 3. Makes workplace enjoyable as it reduces workload. 4. Daily increase in the number of patients seen.

References

Avendano, John P, Daniel O Gallagher, Joseph D Hawes, Joseph Boyle, Laurie Glasser, Jomar Aryee, and Brian M Katt. 2022. “Interfacing with the Electronic Health Record (EHR): A Comparative Review of Modes of Documentation.” Cureus, June (June). https://doi.org/10.7759/cureus.26330. Basil, Nduma N., Solomon Ambe, Chukwuyem Ekhator, and Ekokobe Fonkem. 2022. “Health Records Database and Inherent Security Concerns: A Review of the Literature.” Cureus 14, no. 10 (October). https://doi.org/10.7759/cureus.30168. Kumah-Crystal, Yaa, Claude Pirtle, Harrison Whyte, Edward Goode, Shilo Anders, and Christoph Lehmann. 2018. “Electronic Health Record Interactions through Voice: A Review.” Applied Clinical Informatics 09, no. 03 (July): 541–52. https://doi.org/10.1055/s-0038-1666844. O’Connor, Stephen. n.d. “4 Ways an EHR’s Voice Recognition Feature Makes You More Efficient.” Www.adsc.com. Accessed November 19, 2023. https://www.adsc.com/blog/4-ways-an-ehrs-voice-recognition-feature-makes-you-more-efficient. Robert, Hoyt, Ann Yoshihashi. 2014. “Lessons Learned from Implementation of Voice Recognition for Documentation in the Military Electronic Health Record System.” American Health Information Management Association.2014. https://library.ahima.org/doc?oid=106704. Saxena, Kshitij, Robert Diamond, Reid F. Conant, Terri H. Mitchell, ir. Guido Gallopyn, and Kristin E. Yakimow. 2018. “Provider Adoption of Speech Recognition and Its Impact on Satisfaction, Documentation Quality, Efficiency, and Cost in an Inpatient EHR.” AMIA Summits on Translational Science Proceedings 2018, no. May (May): 186–95. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961784/. Smith-Goodson, Paul. n.d. “AWS HealthScribe Uses Generative AI and Real-Time Doctor-Patient Conversations to Update Medical Charts.” Forbes. Accessed November 19, 2023. https://www.forbes.com/sites/moorinsights/2023/07/28/aws-healthscribe-uses-generative-ai-and-real-time-doctor-patient-conversations-to-update-medical-charts/?sh=1006dc9e5dc1.

Thank you!