Preventing Medication Dispensing Errors in Pharmacy Practice with Interpretable Machine Intelligence: Wave 2
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 30
- 试验地点
- 1
- 主要终点
- Decision accuracy
研究概览
简要总结
Pharmacists currently perform an independent double-check to identify drug-selection errors before they can reach the patient. However, the use of machine intelligence (MI) to support this cognitive decision-making work by pharmacists does not exist in practice. This research is being conducted to examine the effectiveness machine intelligence (MI) advice on to determine if its impact on pharmacists' work performance and cognitive demand.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Other
- 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
- 否
入选标准
- •Licensed pharmacist in the United States
- •Age 18 years and older at screening
- •PC/Laptop with Microsoft Windows 10 or Mac (Macbook, iMac) with MacOS with Google Chrome or Firefox web browser installed on the device
- •Screen resolution of 1024x968 pixels or more
- •A laptop integrated webcam or USB webcam is also required for the eye tracking purpose.
排除标准
- •Eyeglasses with more than one power (bifocals, trifocals, progressives, layered lenses, or regression lenses)
- •Cataracts, intraocular implants, glaucoma, or permanently dilated pupil
- •Require a screen reader/magnifier or other assistive technology to use the computer
- •Eye surgery (e.g., corneal)
- •Eye movement or alignment abnormalities (lazy eye, strabismus, nystagmus)
研究组 & 干预措施
Interpretable MI
Participants receive interpretable machine intelligence to complete the medication verification task.
干预措施: Interpretable MI (Behavioral)
Uninterpretable MI
Participants receive uninterpretable (i.e., black-box) machine intelligence to complete the medication verification task.
干预措施: No MI Help (Behavioral)
Interpretable MI
Participants receive interpretable machine intelligence to complete the medication verification task.
干预措施: No MI Help (Behavioral)
Uninterpretable MI
Participants receive uninterpretable (i.e., black-box) machine intelligence to complete the medication verification task.
干预措施: Uninterpretable MI (Behavioral)
结局指标
主要结局
Decision accuracy
时间窗: 1 day - Single study visit
Difference in detection rate measured by number of medication verification errors
Cognitive effort
时间窗: 1 day - Single study visit
Difference in cognitive effort measured by duration of fixation and fixation count
Trust change
时间窗: 1 day - Single study visit
Difference in trust as measured by visual analog scale will be calculated based on AI advice accuracy. Participants will indicate their level of trust in the AI advice after every trial on a scale from 1-100, with higher scores indicating greater levels of trust.
次要结局
- Reaction time(1 day - Single study visit)
研究者
Corey Lester
Assistant Professor of Clinical Pharmacy
University of Michigan
