Burnout, Clinical Documentation Efficiency
Conditions
Keywords
clinical documentation, burnout, scribe, ambient AI, DAX CoPilot, randomized control trial, electronic health record, acceptance and use of technology, patient satisfaction
Brief summary
This clinical trial aims to evaluate the effectiveness of an ambient listening AI product, DAX CoPilot, in improving clinical documentation efficiency and reducing clinician burnout in primary care settings. Researchers will compare results from a group who was given a license to use DAX CoPilot to a group who was not given a license. Participants in the DAX group will use DAX CoPilot system for EHR documentation and participants in the control group will use use standard EHR documentation methods. Participants will also be asked to complete surveys and assessments related to their views on technology and experiences of burnout.
Detailed description
This pilot study aims to evaluate the effectiveness of an ambient listening AI product in improving clinical documentation efficiency and patient satisfaction, reducing clinician burnout in primary care settings, and improving operational implementation strategies by harnessing end-user psychology. Employing a randomized, prospective design, the study involved 25 clinicians who were given an ambient listening AI product (DAX CoPilot) after a 1 month baseline period and asked to use it for clinical documentation with a focus on problem-focused visits over a 3-month period, with a control group of 20 clinicians continuing traditional documentation methods. The primary outcomes include changes in documentation efficiency (measured through metrics such as time spent on documentation per patient) and clinician burnout (assessed using the validated Mini-Z 2.0 burnout inventory). Secondary outcomes involve patient satisfaction with clinicians' use of the AI tool and examining end-user technology acceptance among clinicians using a survey based on the Unified Theory of Acceptance and Use of Technology (UTAUT). The study aims to provide insights into the potential of AI-assisted documentation tools in enhancing clinical workflow and addressing the growing concern of clinician burnout.
Interventions
BEHAVIORALDAX CoPilot Group
Participants in this group were given a license for DAX CoPilot and asked to use it for clinical documentation.
Sponsors
Samaritan Health Services
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE
Intervention model description
Randomized control trial
Eligibility
Sex/Gender
ALL
Healthy volunteers
Yes
Inclusion criteria
1. Licensed Clinicians: Independently licensed clinicians (MDs, DOs, NPs, PAs) who have been actively practicing at Samaritan Health Services for at least 6 months. 2. Primary Care Only: Providers must have a listed specialty of family medicine, internal medicine, or pediatrics, and currently practice primarily in a primary or urgent care clinic. 3. Provider has an Apple iPhone and is willing to install Epic Haiku.
Exclusion criteria
1. Inpatient-Only Clinicians: Exclude clinicians who only, or primarily, work in inpatient settings, as documentation needs and challenges may differ significantly from those in outpatient settings. 2. Trainees: Exclude medical students and residents due to their varying levels of experience and dependence on supervisory oversight. 3. Minimum Outpatient Encounters: Exclude clinicians with fewer than 100 outpatient encounters per month to focus on those with a significant workload in outpatient settings. 4. Android Smartphones Users: Clinicians may not use Android, or generally any non-Apple or non-iOS smartphones, given the software limitations of the selected intervention technology. 5. Corrective Action: Exclude clinicians facing dismissal, corrective, or disciplinary action. 6. Scheduled leave longer than 3 weeks during the study period
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Documentation efficiency | From baseline to the end of the 3 month experimental period | Compare average documentation, workload, and InBasket metrics (tracked by Epic Signal and through a custom data pull for SHS) before and after the implementation of ambient AI among the intervention and control groups; time in notes per appointment, time in notes per scheduled day, progress note length, note composition, time outside scheduled hours, time outside of 7 AM to 7 PM, pajama time, visits closed same day, time in InBasket per appointment, InBasket message turnaround time |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Burnout | From baseline to the end of the 3 month experimental period | Clinician burnout as assessed using the Mini-Z 2.0 burnout inventory |
Other
| Measure | Time frame | Description |
|---|---|---|
| Patient satisfaction | 3 months experimental period | Patient satisfaction with the experience of the clinician using DAX CoPilot via a patient survey after a visit in which it was used |
Countries
United States
Outcome results
None listed