Journal:Clinical note creation, binning, and artificial intelligence
| Full article title | Clinical note creation, binning, and artificial intelligence |
|---|---|
| Journal | JMIR Medical Informatics |
| Author(s) | Deliberato, Rodrigo Octávio; Celi, Leo Anthony; Stone, David J. |
| Author affiliation(s) |
Massachusetts Institute of Technology, Hospital Israelita Albert Einstein, Beth Israel Deaconess Medical Center, University of Virginia School of Medicine |
| Primary contact | Email: lceli at mit dot edu; Phone: 1 6172537937 |
| Editors | Eysenbach, G. |
| Year published | 2017 |
| Volume and issue | 5 (3) |
| Page(s) | e24 |
| DOI | 10.2196/medinform.7627 |
| ISSN | 2291-9694 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | http://medinform.jmir.org/2017/3/e24/ |
| Download | http://medinform.jmir.org/2017/3/e24/pdf (PDF) |
Abstract
The creation of medical notes in software applications poses an intrinsic problem in workflow as the technology inherently intervenes in the processes of collecting and assembling information, as well as the production of a data-driven note that meets both individual and healthcare system requirements. In addition, the note writing applications in currently available electronic health records (EHRs) do not function to support decision making to any substantial degree. We suggest that artificial intelligence (AI) could be utilized to facilitate the workflows of the data collection and assembly processes, as well as to support the development of personalized, yet data-driven assessments and plans.
Keywords: electronic health records, artificial Intelligence, clinical informatics
Introduction
Many doctors find the creation of the same note more onerous in an electronic health record (EHR) than on paper.[1] The following quote from a senior physician reflects the dissatisfaction doctors have with EHRs: “My experience with the EHR is that it is the biggest waste of time, interferes with patient care, forces the physician to collect thousands of pieces of useless information, and produces marginal improvements in quality.” For this and many other reasons, the quality of EHR documentation has ranged from suboptimal to dismal.[2][3] This paper explores and envisions how artificial intelligence (AI), which is increasingly transforming facets of daily living, could support the currently burdensome process of gathering and organizing the elements necessary for the creation of a clinical note.
References
- ↑ Hingle, S. (2016). "Electronic Health Records: An Unfulfilled Promise and a Call to Action". Annals of Internal Medicine 165 (11): 818-819. doi:10.7326/M16-1757. PMID 27595501.
- ↑ Markel, A. (2010). "Copy and paste of electronic health records: A modern medical illness". American Journal of Medicine 123 (5): e9. doi:10.1016/j.amjmed.2009.10.012. PMID 20399309.
- ↑ Hirschtick, R.E. (2012). "A piece of my mind: John Lennon's elbow". JAMA 308 (5): 463–4. doi:10.1001/jama.2012.8331. PMID 22851112.
Abbreviations
AI: artificial intelligence
EHR: electronic health record
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. In several cases the PubMed ID was missing and was added to make the reference more useful.
Per the distribution agreement, the following copyright information is also being added:
©Rodrigo Octávio Deliberato, Leo Anthony Celi, David J Stone. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 03.08.2017.
