Computer Interpretation of the ECG Raising Awareness CIERA Trial (CIERA)
The Effect of Three Educational Interventions on Emergency and Critical Nurses Proficiency in Computer Interpretation of the ECG: Results of the CIERA Trial
Background: Practice guidelines require emergency and critical care nurses (ECC) to be skillful in ECG and cardiac monitoring. Evidence suggests that nurses' proficiency is still inadequate with this regard. Computer interpretation of the ECG (CIE) is accurate and improves clinicians' accuracy in ECG interpretation. Unfortunately, nurses are not taught or trained to use this technology. Through this study the investigators aim to evaluate the effectiveness of three educational interventions to improve ECC nurses' proficiency in CIE.
Methods. The investigators applied a randomized mixed, crossover and parallel, design. Linear mixed model analysis was used to examine differences in CIE test score among groups and across time. There were three interventional groups (G0, no intervention then flyer; G1, face-to-face then online; and G2, online then face-to-face) with three points of time measurement (T0, baselines; T1, after first intervention, and T2 after second intervention).
調査の概要
状態
詳細な説明
Nurses working in the emergency department and critical care units spend a great deal of their time reading or recording ECGs. Practice guidelines require nurses working in units where cardiac monitoring is essential to be skillful in electrocardiography and cardiac monitoring. However, evidence suggests that nurses are still far from achieving this goal. In a study conducted in 65 cardiac care units from three different countries, nurses' (n, 3013) mean total score on an online ECG test was below 50%. However, nurses' mean total score significantly improved after receiving an online ECG monitoring education program. In another study published recently, emergency department and critical care nurses' (n, 210) mean total score in an ECG proficiency test was 18.1 out of 34 with only 61.9% of nurses scoring equal to or higher than 50% of the maximum score. Inadequate nurses' performance on ECG interpretation and cardiac monitoring skills can delay or even prevent lifesaving treatment.
One way of improving emergency and critical care nurses' (ECC) ECG interpretation accuracy is through the utilization of the computer interpretation of the ECG (CIE). This tool is incredibly accurate for certain interpretation algorithms to an extent comparable to a cardiologist, which is considered the gold standard for ECG interpretation. The CIE overall accuracy is estimated to be 90 to 93%. CIE combined with an "over-read" by a well-trained interpreter represents the most accurate form currently available for ECG interpretation. Existing evidence supports CIE ability to improve health care professionals' interpretation accuracy. In a recent study, CIE improved nurses' interpretation accuracy by 16.2%, improved cardiology fellows accuracy by 10.9% , resident physicians by 14.4%, and medical students by 19.9%. In the same study, CIE increased interpretation confidence by 0.06 on a scale from 0 to 1 for all study participants.
In addition to accuracy and improving clinicians' interpretation, especially for less experienced readers, CIE has several other advantages. CIE is especially useful when access to an interpretation expert is not possible; it minimizes expenses; does not fatigue; does not become distracted by outside pressure; objective; not affected by intra or inter-observer variability; decreases interpretation time, on average, by 52 seconds and by 24-28% for the experience reader; makes interpretation easier because it requires no deep knowledge; can take into account age, gender, race, and medication therapy; capable of doing automated serial ECG comparisons; capable of applying multiple and complex criteria, for example in diagnosing left ventricular hypertrophy, that would be difficult or impossible to apply otherwise; leads to faster diagnoses and earlier treatment; can unify diagnostic statements terminology through the following of the terminology adopted by practice guidelines. Such unification of terminology in electrocardiography would facilitate better patient care and unify teaching curriculum all over the world. CIE also continues to improve over time especially with AI evolving technology.
CIE has also several limitations. CIE is generally inaccurate in diagnosing arrhythmia, conduction disturbances, and pace maker rhythms. It is also inaccurate in diagnosing ischemia and myocardial infarction. It is inaccurate in measuring the QT interval, diagnosing long QT interval, and measuring QRS duration. It is inaccurate in diagnosing atrial fibrillation. It misdiagnoses atrial fibrillation and atrial flutter. It does not identify left and right arm lead reversal. The wide variability among different interpretation software with regard to accuracy and employed measurement criteria is another major limitation. However, even with these limitations, the CIE is still considered overall to be accurate.
Nevertheless, despite its great usefulness and potential to advance nursing practice and patient's care, unfortunately nurses are not taught or trained to use this technology. Formal undergraduate, graduate, and clinical education and textbooks do not talk about CIE. Even in research studies evaluating nurses' knowledge and proficiency in electrocardiography, researchers do not include testing items concerning CIE. As far as the investigators know, there is no previous study that has ever specifically evaluated nurses' knowledge in CIE.
The investigators aim from this project which we call "Computer Interpretation of the ECG Raising Awareness CIERA" to raise awareness among nurse practitioners, educators, and managers about the utilization of this technology. Specifically, the investigators aim to introduce three educational interventions (face-to-face, online, and flyer) and assess their effectiveness in improving ECC nurses' proficiency in computer interpretation of the ECG.
The investigators followed the "CONSORT 2010 statement: extension to randomized crossover trials" guidelines in reporting the findings of this trial.
研究の種類
入学 (実際)
段階
- 適用できない
連絡先と場所
研究場所
-
-
-
Amman、ヨルダン、11942
- the university of Jordan
-
-
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:
- Every nurse working in the emergency department and critical care units of the participating hospitals
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:他の
- 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 |
|---|---|
|
実験的:no intervention then a flyer
the flyer was a small, palm-sized, crafted from fine-quality material, thoughtfully designed to be colorful, visually inviting, and easy going, featuring carefully selected introductory images, ample whitespace, and minimal text to ensure clarity, quick engagement, and polished first impression.
|
the flyer was a small, palm-sized, crafted from fine-quality material, thoughtfully designed to be colorful, visually inviting, and easy going, featuring carefully selected introductory images, ample whitespace, and minimal text to ensure clarity, quick engagement, and polished first impression.
|
|
実験的:Face-to-face then online lectures
the face-to-face content included audiovisual aids, case scenarios, and immediate feedback discussions.
The online content included artificial intelligence enhanced audiovisual aids (videos and images), integrated interactive feedback mechanisms (e.g., requiring the participant to scan a QR code and respond to real-time MCQ questions).
The face-to-face lecture time was totally 45 minutes.
The online total lecture time was 25 minutes.
|
the face-to-face content included audiovisual aids, case scenarios, and immediate feedback discussions.
The face-to-face lecture time was totally 45 minutes
The online content included artificial intelligence enhanced audiovisual aids (videos and images), integrated interactive feedback mechanisms (e.g., requiring the participant to scan a QR code and respond to real-time MCQ questions).
The online total lecture time was 25 minutes.
|
|
実験的:Online then face-to-face lectures
the face-to-face content included audiovisual aids, case scenarios, and immediate feedback discussions.
The online content included artificial intelligence enhanced audiovisual aids (videos and images), integrated interactive feedback mechanisms (e.g., requiring the participant to scan a QR code and respond to real-time MCQ questions).
The face-to-face lecture time was totally 45 minutes.
The online total lecture time was 25 minutes.
|
the face-to-face content included audiovisual aids, case scenarios, and immediate feedback discussions.
The face-to-face lecture time was totally 45 minutes
The online content included artificial intelligence enhanced audiovisual aids (videos and images), integrated interactive feedback mechanisms (e.g., requiring the participant to scan a QR code and respond to real-time MCQ questions).
The online total lecture time was 25 minutes.
|
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 |
|---|---|---|
|
Emergency and Critical Care Nurses Proficiency in Computer Interpretation of the ECG
時間枠:From enrollment to the end of treatment at 5 months
|
Emergency and Critical Care Nurses scores on the "Computer Interpretation of the ECG" test score.
The test is scored out of 28 (range 0 to 28), with higher scores indicating greater proficiency.
The test scale name is "Computer Interpretation of the ECG" test scale
|
From enrollment to the end of treatment at 5 months
|
協力者と研究者
スポンサー
捜査官
- 主任研究者:Amer M Hasanien, PhD、the university of Jordan
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (実際)
研究の完了 (実際)
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
キーワード
追加の関連 MeSH 用語
その他の研究ID番号
- 2289\2024\19 (その他の助成金/資金番号:The University of Jordan, Deanship of Scientific Research)
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
IPD 共有時間枠
IPD 共有アクセス基準
IPD 共有サポート情報タイプ
- STUDY_PROTOCOL
- SAP
- ICF
- ANALYTIC_CODE
- CSR
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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