AI-Assisted Clinical Documentation in Nurse-Led Telehealth Contacts
Effect of AI-Assisted Clinical Documentation on Nurse Productivity, Professional Experience, and Documentation Quality: A Randomized Repeated Crossover Trial in Primary Care Telehealth
Background: No randomized controlled trial evidence currently exists on the effectiveness of ambient artificial intelligence (AI)-assisted clinical documentation.
Objective: To evaluate the effect of AI-assisted documentation on nurse productivity, professional experience, and documentation quality in nurse-led telehealth (telephone and chat) contacts in Finnish primary care (Wellbeing Services County of Kanta-Häme, OmaHäme).
Methods: In this randomized, open-label, repeated crossover trial, approximately 64 nurses are allocated 1:1 to an ABAB or BABA sequence of four two-week periods (A = AI-assisted documentation, B = standard manual documentation) over eight weeks. The primary outcome is the number of patient contacts handled per nurse, analyzed with a generalized linear mixed-effects model for count data with nurse as a random effect; the treatment effect is expressed as an incidence rate ratio (IRR). A Monte Carlo simulation-based power analysis indicated 85% power to detect an IRR of 1.15 at a two-sided alpha of 0.05. Secondary outcomes include self-reported work-time savings, nurse experience and satisfaction, and patient satisfaction. Discrepancies between AI-generated draft notes, and final signed notes are analyzed to characterize the frequency, type, and clinical criticality of AI errors and omissions.
The trial is investigator-initiated (OmaHäme, HUS Helsinki University Hospital, University of Helsinki) and funded by the Strategic Research Council (GAINS project). The technology provider (Tandem Health) supplies the technical solution and participates in study design and manuscript preparation; responsibility for the study design, data analysis, and conclusions rests with the academic study group.
연구 개요
상태
정황
연구 유형
등록 (추정된)
단계
- 해당 없음
연락처 및 위치
연구 연락처
- 이름: Ville Vartiainen, MD, PhD, MSc
- 전화번호: +358 50 430 6414
- 이메일: ville.vartiainen@hus.fi
연구 장소
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Hämeenlinna, 핀란드
- Wellbeing Services County of Kanta-Häme (OmaHäme)
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연락하다:
- Suvi Hämäläinen, MD, PhD
- 전화번호: +35850 5917 162
- 이메일: suvi.hamalainen@omahame.fi
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참여기준
자격 기준
공부할 수 있는 나이
- 어린이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
설명
Inclusion Criteria:
- Nurses at OmaHäme (Wellbeing Services County of Kanta-Häme) handling telephone or chat patient contacts
Exclusion Criteria:
- None
공부 계획
연구는 어떻게 설계됩니까?
디자인 세부사항
- 주 목적: 건강 서비스 연구
- 할당: 무작위
- 중재 모델: 크로스오버 할당
- 마스킹: 없음(오픈 라벨)
무기와 개입
참가자 그룹 / 팔 |
개입 / 치료 |
|---|---|
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실험적: Sequence ABAB
Nurses randomized to begin with AI-assisted documentation (A), alternating with standard manual documentation (B) in four consecutive two-week periods (A-B-A-B).
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During AI-assisted periods, nurses use an ambient AI scribe that transcribes the patient contact and generates a draft clinical note, which the nurse reviews, edits, and approves.
During control periods, nurses document contacts manually according to standard practice.
All other aspects of care follow normal clinical routines.
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실험적: Sequence BABA.
Nurses randomized to begin with standard manual documentation (B), alternating with AI-assisted documentation (A) in four consecutive two-week periods (B-A-B-A).
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During AI-assisted periods, nurses use an ambient AI scribe that transcribes the patient contact and generates a draft clinical note, which the nurse reviews, edits, and approves.
During control periods, nurses document contacts manually according to standard practice.
All other aspects of care follow normal clinical routines.
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연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
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Number of patient contacts handled per nurse per working day/hour.
기간: Daily/hourly, over four 2-week periods (8 weeks).
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Count of telehealth (telephone/chat) contacts handled per nurse per working day/hour during time of excess demand extracted from routine service data.
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Daily/hourly, over four 2-week periods (8 weeks).
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2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
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Self-reported work-time savings.
기간: Week 8 (end of study).
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Nurses' estimate of the effect of AI-assisted documentation on time spent on documentation, assessed with a study-specific end-of-study questionnaire (5-point Likert scale).
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Week 8 (end of study).
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Nurse-reported experience and satisfaction.
기간: Baseline (week 0) and week 8 (end of study).
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Perceived workflow, efficiency, workload, and job satisfaction, assessed with study-specific baseline and end-of-study questionnaires (5-point Likert scales).
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Baseline (week 0) and week 8 (end of study).
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공동 작업자 및 조사자
연구 기록 날짜
연구 주요 날짜
연구 시작 (추정된)
기본 완료 (추정된)
연구 완료 (추정된)
연구 등록 날짜
최초 제출
QC 기준을 충족하는 최초 제출
처음 게시됨 (실제)
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
QC 기준을 충족하는 마지막 업데이트 제출
마지막으로 확인됨
추가 정보
이 연구와 관련된 용어
기타 연구 ID 번호
- OMAHAME-AISCRIBE-2026
개별 참가자 데이터(IPD) 계획
개별 참가자 데이터(IPD)를 공유할 계획입니까?
IPD 계획 설명
약물 및 장치 정보, 연구 문서
미국 FDA 규제 의약품 연구
미국 FDA 규제 기기 제품 연구
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