Physician progress notes contain information essential to patient care, including findings from history and physical exam, interpretation of tests, assessment and treatment plans. However in the transition from paper to electronic physician notes, many physicians spend more time creating them, which has led to the use of time-saving measures such as copy/paste and templates that have degraded note accuracy and quality. This threatens the usefulness of notes not only for their most important use-patient care-but also for research, quality improvement, and in supporting reimbursement. To address these problems, we propose a project with the following specific aims: 1. To refine and implement a new voice-generated enhanced electronic note system (VGEENS) integrating voice recognition with natural language processing and links to the electronic medical record (EMR) to improve note accuracy and timeliness. 2. To evaluate VGEENS using a randomized trial with 30 internal medicine physicians in each arm to assess electronic note accuracy, quality, timeliness, and user satisfaction. Intervention physicians will use VGEENS, while the control physicians will continue with note creation as they normally would. This novel approach has the potential to improve note accuracy while reducing delays in making progress notes in EMRs available to other clinicians. It leverages rapidly improving voice recognition and NLP technologies to permit physicians to use a natural, fast method-human voice-to convey their observation and thoughts into the EMR record.
Physician documentation of a patient visit contains information that is used in that patient's care. This information includes findings from a patient'history and physical exam, interpretation of necessary tests, the problem assessment and treatment plan. However, in the transition from paper to electronic physician notes, many physicians are spending more time creating these notes. This has led to use of time-saving measures that have degraded the accuracy and ease of use of patient notes. By the end of this project, we expect to have developed, used and evaluated a new method for creating electronic physician notes that both improve accuracy and timely availability of inpatient progress notes.
|Payne, Thomas H; Alonso, W David; Markiel, J Andrew et al. (2018) Using voice to create hospital progress notes: Description of a mobile application and supporting system integrated with a commercial electronic health record. J Biomed Inform 77:91-96|
|Lybarger, Kevin; Ostendorf, Mari; Yetisgen, Meliha (2017) Automatically Detecting Likely Edits in Clinical Notes Created Using Automatic Speech Recognition. AMIA Annu Symp Proc 2017:1186-1195|