Gastrointestinal DiseasesClinCodeNCT06286865
Improving Quality of ICD-10 Coding Using AI: Protocol for a Crossover Randomized Controlled Trial
A study testing Easy-ICD in people with Gastrointestinal Diseases, run by University Hospital of North Norway at 1 site in Norway.
Trial summary
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… Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Gastrointestinal Diseases
- What is being tested?
- Easy-ICD
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 15 participants
- Where
- 1 siteNorway
- Study dates
- 20 Oct 2023to 31 May 2024
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- participant has coded clinical texts before, preferably ICD-10 coding
- is a healthcare professional, eg. clinician, nurse, professional coders
- can understand Swedish
Who cannot join
- participants outside Norway and Sweden
Trial locations and contacts
1 site in 1 country.
About this study
Official title: 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.
Read the 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:
- Study participants are randomly allocated to group 1 and group 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.
- In period 1 with 10 clinical notes, group 1 uses the control interface, while group 2 uses the intervention interface.
- Data are logged in the background using button presses (eg. time, assigned codes, and comments).
- Then, there is an immediate crossover to period 2 for the last 10 clinical notes.
- Data continue to be logged in the background using button presses.
- At the end, participants in both groups will complete the system usability scale.
- Conditions
- Gastrointestinal Diseases
- Being tested
- Easy-ICD
- Medical subject headings
- Gastrointestinal Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Easy-ICDOther
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.
| Study group | Role | What they receive |
|---|---|---|
| Easy-ICD interface | Active comparator | This arm uses our AI-based computer-assisted clinical coding (CAC) system, Easy-ICD Receives: Other: Easy-ICD |
| Control interface | No intervention | This control arm uses an interface similar to Easy-ICD, but without the AI functionality |
What is being measured
The primary outcome is the main question the study is designed to answer.
Time
Time in seconds taken to assign ICD-10 codes to each of the 20 clinical notes.
Measured: 1 hour
Accuracy
Accuracy is calculated by dividing the number of correct ICD-10 codes by the total number of codes assigned.
Measured: 1 hour
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Feb 2024
- Study start20 Oct 2023
- Primary completion31 May 2024
- Study completion31 May 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Gastrointestinal DiseasesStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 15 participants (actual)
Sponsor and investigators
- Lead sponsor
- University Hospital of North Norway
- Sponsor type
- University, hospital or other
- Collaborators
- The Research Council of Norway
- Responsible party
- Principal investigator, Taridzo Chomutare, University Hospital of North Norway
- Investigators
- Hercules Dalianis, PhD, Principal investigator, Norwegian Centre for E-health Research
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06286865
- Sponsor's protocol ID
- 260972(REK)
- Acronym
- ClinCode
- Status last verified
- Feb 2024
- First submitted
- 16 Feb 2024
- Last updated
- 25 Jun 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: The data we collect in the study are all anonymous and will be shared publicly after the user study is published.
Publications
Chomutare T, Lamproudis A, Budrionis A, Svenning TO, Hind LI, Ngo PD, Mikalsen KO, Dalianis H. Improving Quality of ICD-10 (International Statistical Classification of Diseases, Tenth Revision) Coding Using AI: Protocol for a Crossover Randomized Controlled Trial. JMIR Res Protoc. 2024 Mar 12;13:e54593. doi: 10.2196/54593.
PubMed 38470476
Study at a glance
From the registry record, last updated by the sponsor on 25 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Improving Quality of ICD-10 (International Statistical Classification of Diseases, Tenth Revision) Coding Using AI: Protocol for a Crossover Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT06286865
- Acronym / sponsor ID
- ClinCode / 260972(REK)
- Conditions
- Gastrointestinal Diseases
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 15 participants (actual)
- Lead sponsor
- University Hospital of North NorwayUniversity, hospital or other
- Collaborators
- The Research Council of Norway
- Study start
- 20 Oct 2023 (actual)
- Primary completion
- 31 May 2024 (actual)
- Study completion
- 31 May 2024 (actual)
- First posted
- 29 Feb 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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:
- Study participants are randomly allocated to group 1 and group 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.
- In period 1 with 10 clinical notes, group 1 uses the control interface, while group 2 uses the intervention interface.
- Data are logged in the background using button presses (eg. time, assigned codes, and comments).
- Then, there is an immediate crossover to period 2 for the last 10 clinical notes.
- Data continue to be logged in the background using button presses.
- At the end, participants in both groups will complete the system usability scale.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- Single blind (participant)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Easy-ICD interface | Active comparator | Other: Easy-ICDThis arm uses our AI-based computer-assisted clinical coding (CAC) system, Easy-ICD |
| Control interface | No intervention | –This control arm uses an interface similar to Easy-ICD, but without the AI functionality |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (3 listed)
- participant has coded clinical texts before, preferably ICD-10 coding
- is a healthcare professional, eg. clinician, nurse, professional coders
- can understand Swedish
Key exclusion criteria (1 listed)
- participants outside Norway and Sweden
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Easy-ICDEasy-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. | Other | Easy-ICD interface |
Primary outcome
Time
Time frame: 1 hour
Time in seconds taken to assign ICD-10 codes to each of the 20 clinical notes.
Accuracy
Time frame: 1 hour
Accuracy is calculated by dividing the number of correct ICD-10 codes by the total number of codes assigned.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 25 Jun 2026.
- Derived from this study: PubMed 38470476Chomutare T, Lamproudis A, Budrionis A, Svenning TO, Hind LI, Ngo PD, Mikalsen KO, Dalianis H. Improving Quality of ICD-10 (International Statistical Classification of Diseases, Tenth Revision) Coding Using AI: Protocol for a Crossover Randomized Controlled Trial. JMIR Res Protoc. 2024 Mar 12;13:e54593. doi: 10.2196/54593.
- Individual participant dataSharing planned: Yes. The data we collect in the study are all anonymous and will be shared publicly after the user study is published.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Hercules Dalianis, PhD principal investigator
Norwegian Centre for E-health Research
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Easy-ICD in people with Gastrointestinal Diseases, run by University Hospital of North Norway at 1 site in Norway.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 25 Jun 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Norway. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Time (time frame: 1 hour). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06286865, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 25 Jun 2026.