Improving Quality of ICD-10 Coding Using AI: Protocol for a Crossover Randomized Controlled Trial (ClinCode)

June 22, 2026 updated by: Taridzo Chomutare, University Hospital of North Norway

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

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.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

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.

Study Type

Interventional

Enrollment (Actual)

15

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Norway
    • Troms
      • Tromsø, Troms, Norway, 9019
        • Norwegian Centre for E-health Research

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

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

Exclusion Criteria:

  • participants outside Norway and Sweden

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Randomized
  • Interventional Model: Crossover Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Active Comparator: Easy-ICD interface
This arm uses our AI-based computer-assisted clinical coding (CAC) system, Easy-ICD
Other: Easy-ICD
Easy-ICD is an AI-based computer-assisted clinical coding (CAC) system that helps clinical coder assign ICD-10 codes to clinical notes such as discharge summaries.
No Intervention: Control interface
This control arm uses an interface similar to Easy-ICD, but without the AI functionality

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Time
Time Frame: 1 hour
Time in seconds taken to assign ICD-10 codes to each of the 20 clinical notes.
1 hour
Accuracy
Time Frame: 1 hour
Accuracy is calculated by dividing the number of correct ICD-10 codes by the total number of codes assigned.
1 hour

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University Hospital of North Norway

Collaborators

The Research Council of Norway

Investigators

  • Principal Investigator: Hercules Dalianis, PhD, Norwegian Centre for E-health Research

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

October 20, 2023

Primary Completion (Actual)

May 31, 2024

Study Completion (Actual)

May 31, 2024

Study Registration Dates

First Submitted

February 16, 2024

First Submitted That Met QC Criteria

February 23, 2024

First Posted (Actual)

February 29, 2024

Study Record Updates

Last Update Posted (Actual)

June 25, 2026

Last Update Submitted That Met QC Criteria

June 22, 2026

Last Verified

February 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 260972(REK)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

The data we collect in the study are all anonymous and will be shared publicly after the user study is published.

IPD Sharing Time Frame

At the publishing of the user study.

IPD Sharing Access Criteria

The anonymous data will be publicly available.

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP
  • ICF

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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