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.
調査の概要
状態
条件
研究の種類
入学 (推定)
段階
- 適用できない
連絡先と場所
研究連絡先
- 名前：Ville Vartiainen, MD, PhD, MSc
- 電話番号：+358 50 430 6414
- メール：ville.vartiainen@hus.fi
研究場所
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Hämeenlinna、フィンランド
- Wellbeing Services County of Kanta-Häme (OmaHäme)
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コンタクト：
- Suvi Hämäläinen, MD, PhD
- 電話番号：+35850 5917 162
- メール：suvi.hamalainen@omahame.fi
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参加基準
適格基準
就学可能な年齢
- 子
- 大人
- 高齢者
健康ボランティアの受け入れ
説明
Inclusion Criteria:
- Nurses at OmaHäme (Wellbeing Services County of Kanta-Häme) handling telephone or chat patient contacts
Exclusion Criteria:
- None
研究計画
研究はどのように設計されていますか？
デザインの詳細
- 主な目的：ヘルスサービス研究
- 割り当て：ランダム化
- 介入モデル：クロスオーバー割り当て
- マスキング：なし（オープンラベル）
武器と介入
参加者グループ / アーム |
介入・治療 |
|---|---|
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実験的：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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実験的：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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この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Number of patient contacts handled per nurse per working day/hour.
時間枠：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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二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Self-reported work-time savings.
時間枠：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.
時間枠：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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協力者と研究者
研究記録日
主要日程の研究
研究開始 (推定)
一次修了 (推定)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
その他の研究ID番号
- OMAHAME-AISCRIBE-2026
個々の参加者データ (IPD) の計画
個々の参加者データ (IPD) を共有する予定はありますか?
IPD プランの説明
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
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