Evaluation of AI-Generated Documentation Software to Improve Pediatric Physician
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 21
- 试验地点
- 2
- 主要终点
- Pajama Time
研究概览
简要总结
This randomized quality improvement pilot project aims to assess whether the implementation of generative AI software for documentation, Microsoft Nuance's Digital Ambient eXperience (DAX) Copilot, enhances physician documentation efficiency and reduces burnout.
详细描述
Background: While electronic health record (EHR) systems have contributed to advances in patient safety and quality of care, they have also been associated with a significant increase in documentation burden, contributing to burnout among clinicians [1]. This is particularly true for physicians with insufficient time for documentation. In some cases, it has resulted in a reduction in appointment slots to allow for additional documentation time, which in turn decreases patient access to care and physician productivity [2,3].
Microsoft Nuance© has recently announced general availability of a new generative artificial intelligence (AI) solution called Digital Ambient eXperience (DAX) DAX CoPilot [4], in which the visit is recorded with patient/parental consent, but a note is generated through the AI along with a visit transcript in near-real time that the provider can use and edit as they see fit. In addition, it allows providers to continue to use their documentation templates while adding the generative AI to "smart sections" within their note. This approach has the potential to substantially reduce documentation burden while maintaining documentation preferences of many providers.
This randomized quality improvement pilot project aims to assess whether the implementation of generative AI software for documentation, Microsoft Nuance's DAX Copilot, can enhance physician documentation efficiency and reduce burnout.
Objectives
Quality Improvement Global Aim: To increase provider documentation efficiency and reduce provider burnout related to documentation burden.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Health Services Research
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Practices at Children's in a specialty supported by DAX Copilot product and with available documentation efficiency metrics from Epic's Signal product.
- •>0.5 clinical full time equivalent (cFTE)
- •2 or more half days per week on average seeing outpatients as the primary provider (not overseeing trainees or APPs).
- •Agrees to use the Children's EHR mobile application (Haiku) on their personal device.
- •Agrees to offer use of the DAX Copilot generative AI software for all eligible patient visit encounters for the duration of the project period
- •Sufficient and stable EHR data on documentation efficiency from Epic's Signal product, defined as:
- •Having populated data available for at least 40 of the last 52 weeks.
- •Having stable metrics for pajama time and time in notes in the last 6 months as determined by two physician informaticists based on visual inspection.
- •>75% of ambulatory documentation completed by the provider themselves (as opposed to taking over a note of a trainee or advanced practice provider).
- •Visits: In person office visits in which interactions occur in English. For example, a visit with an interpreter present who translates verbally into English during the visit would be eligible. A visit in which all interactions occur in another language (i.e. the provider speaks the language the family uses as well) would not be eligible as the AI has not been developed yet for other languages.
排除标准
- •Poor WiFi and cellular coverage in the clinic.
结局指标
主要结局
Pajama Time
时间窗: 12 months prior to study through end of study period.
Per Epic Signal: Average number of minutes per scheduled day spent in charting activities outside 7 AM to 5:30 PM on weekdays, time outside scheduled hours on weekends, and time on unscheduled holidays. Numerator: Minutes spent in charting activities outside 7 AM to 5:30 PM on weekdays and outside scheduled hours on weekends. Denominator: Scheduled days where time was spent in the system within the reporting period.
Time in Notes per Appointment
时间窗: 12 months prior to study through end of study period.
Per Epic Signal: Time spent writing notes per appointment. Numerator: Minutes providers spent in a notes activity or navigator section within the reporting period. Denominator: Appointments within the reporting period. Excludes data from days where the User Action Log data was not submitted.
次要结局
- Progress Note Length (characters)(12 months prior to study through end of study period.)
- Note Contribution(12 months prior to study through end of study period.)
- Time to Appointment Closure(12 months prior to study through end of study period.)
- Proportion of notes completed using DAX copilot generative AI software(12 months prior to study through end of study period.)
- Patient Volume(12 months prior to study through end of study period.)
- Electronic Health Record satisfaction(Pre-test within 2 months prior to study period and post-test within 2 months after study end.)
- Patient Experience(12 months prior to study through end of study period.)