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临床试验/NCT06286865
NCT06286865已完成不适用

Improving Quality of ICD-10 (International Statistical Classification of Diseases, Tenth Revision) Coding Using AI: Protocol for a Crossover Randomized Controlled Trial

University Hospital of North Norway1 个研究点 分布在 1 个国家目标入组 15 人开始时间: 2023年10月20日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
已完成
发起方
入组人数
15
试验地点
1
主要终点
Time

研究概览

简要总结

The goal of this randomised trial is to learn about the role of AI in clinical coding practice. The main question it aims to answer is:

Can the AI-based CAC system reduce the burden of clinical coding and also improve the quality of such coding? Participants will be asked to code clinical texts both while they use our CAC system and while they do not.

详细描述

Once participants are recruited, they are randomly allocated to 2 groups without allocation concealment. Allocation concealment will not be relevant for clinical coders since it is known whether a participant is assisted or not, and we will not develop a placebo coding assistant. We will, however, conceal the allocation of subjects for the analyses.

In total, participants will code 20 clinical notes, where each note belongs to a single patient. The participants are asked to complete the experiment in 1 sitting without interruptions, and they cannot revisit or go back to previous notes. In the event that participants are interrupted, they are asked to exit the experiment, and any incomplete records are discarded as invalid.

The user study process can be summarized in the following steps:

  1. Study participants are randomly allocated to group 1 and group 2.
  2. To prepare participants for the experiment, a short video tutorial is played after the consent form is signed and right before the clinical coding task commences.
  3. In period 1 with 10 clinical notes, group 1 uses the control interface, while group 2 uses the intervention interface.
  4. Data are logged in the background using button presses (eg. time, assigned codes, and comments).
  5. Then, there is an immediate crossover to period 2 for the last 10 clinical notes.
  6. Data continue to be logged in the background using button presses.
  7. At the end, participants in both groups will complete the system usability scale.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Crossover
主要目的
Diagnostic
盲法
Single (Participant)

入排标准

性别
All
接受健康志愿者
是

入选标准

  • •participant has coded clinical texts before, preferably ICD-10 coding
  • •is a healthcare professional, eg. clinician, nurse, professional coders
  • •can understand Swedish

排除标准

  • •participants outside Norway and Sweden

研究组 & 干预措施

Easy-ICD interface

Active Comparator

This arm uses our AI-based computer-assisted clinical coding (CAC) system, Easy-ICD

干预措施: Easy-ICD (Other)

Control interface

No Intervention

This control arm uses an interface similar to Easy-ICD, but without the AI functionality

结局指标

主要结局

Time

时间窗: 1 hour

Time in seconds taken to assign ICD-10 codes to each of the 20 clinical notes.

Accuracy

时间窗: 1 hour

Accuracy is calculated by dividing the number of correct ICD-10 codes by the total number of codes assigned.

次要结局

未报告次要终点

研究者

发起方
University Hospital of North Norway
申办方类型
Other
责任方
Principal Investigator
主要研究者

Taridzo Chomutare

Senior Researcher

University Hospital of North Norway

研究点 (1)

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