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骨科在线计算机辅助病史调查问卷的完成率与满意度:多中心实施报告

Completion Rate and Satisfaction With Online Computer-Assisted History Taking Questionnaires in Orthopedics: Multicenter Implementation Report.

作者信息

Craamer Casper, Timmers Thomas, Siebelt Michiel, Kool Rudolf Bertijn, Diekerhof Carel, Caron Jan Jacob, Gosens Taco, van der Weegen Walter

机构信息

Research and Development Department, Interactive Studios, 's-Hertogenbosch, Netherlands.

IQ Health Science Department, Radboud University Medical Center, Kapittelweg 54, Nijmegen, 6525, Netherlands, 31 243615305.

出版信息

JMIR Med Inform. 2024 Nov 13;12:e60655. doi: 10.2196/60655.

DOI:10.2196/60655
PMID:39622699
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11611801/
Abstract

BACKGROUND

Collecting the medical history during a first outpatient consultation plays an important role in making a diagnosis. However, it is a time-consuming process, and time is scarce in today's health care environment. The computer-assisted history taking (CAHT) systems allow patients to share their medical history electronically before their visit. Although multiple advantages of CAHT have been demonstrated, adoption in everyday medical practice remains low, which has been attributed to various barriers.

OBJECTIVE

This study aimed to implement a CAHT questionnaire for orthopedic patients in preparation for their first outpatient consultation and analyze its completion rate and added value.

METHODS

A multicenter implementation study was conducted in which all patients who were referred to the orthopedic department were invited to self-complete the CAHT questionnaire. The primary outcome of the study is the completion rate of the questionnaire. Secondary outcomes included patient and physician satisfaction. These were assessed via surveys and semistructured interviews.

UNLABELLED

In total, 5321 patients were invited, and 4932 (92.7%) fully completed the CAHT questionnaire between April 2022 and July 2022. On average, participants (n=224) rated the easiness of completing the questionnaire at 8.0 (SD 1.9; 0-10 scale) and the satisfaction of the consult at 8.0 (SD 1.7; 0-10 scale). Satisfaction with the outpatient consultation was higher in cases where the given answers were used by the orthopedic surgeon during this consultation (median 8.3, IQR 8.0-9.1 vs median 8.0, IQR 7.0-8.5; P<.001). Physicians (n=15) scored the average added value as 7.8 (SD 1.7; 0-10 scale) and unanimously recognized increased efficiency, better patient engagement, and better medical record completeness. Implementing the patient's answers into the electronic health record was deemed necessary.

CONCLUSIONS

In this study, we have shown that previously recognized barriers to implementing and adapting CAHT can now be effectively overcome. We demonstrated that almost all patients completed the CAHT questionnaire. This results in reported improvements in both the efficiency and personalization of outpatient consultations. Given the pressing need for personalized health care delivery in today's time-constrained medical environment, we recommend implementing CAHT systems in routine medical practice.

摘要

背景

在首次门诊咨询时收集病史对做出诊断起着重要作用。然而,这是一个耗时的过程,而在当今的医疗环境中时间很稀缺。计算机辅助病史采集(CAHT)系统允许患者在就诊前以电子方式分享他们的病史。尽管CAHT的多种优势已得到证明,但在日常医疗实践中的采用率仍然很低,这归因于各种障碍。

目的

本研究旨在为骨科患者准备首次门诊咨询实施CAHT问卷,并分析其完成率和附加值。

方法

进行了一项多中心实施研究,邀请所有转诊至骨科的患者自行完成CAHT问卷。该研究的主要结果是问卷的完成率。次要结果包括患者和医生的满意度。这些通过调查和半结构化访谈进行评估。

未标记

总共邀请了5321名患者,在2022年4月至2022年7月期间,4932名(92.7%)患者完全完成了CAHT问卷。平均而言,参与者(n = 224)对完成问卷的难易程度评分为8.0(标准差1.9;0 - 10分制),对咨询的满意度评分为8.0(标准差1.7;0 - 10分制)。在骨科医生在此次咨询中使用了所提供答案的情况下,对门诊咨询的满意度更高(中位数8.3,四分位距8.0 - 9.1 vs中位数8.0,四分位距7.0 - 8.5;P <.001)。医生(n = 15)对平均附加值的评分为7.8(标准差1.7;0 - 10分制),并一致认可效率提高、患者参与度更好以及病历完整性更好。将患者的答案录入电子健康记录被认为是必要的。

结论

在本研究中,我们表明先前公认的实施和应用CAHT的障碍现在可以有效克服。我们证明几乎所有患者都完成了CAHT问卷。这导致门诊咨询的效率和个性化都有改善。鉴于在当今时间紧迫的医疗环境中对个性化医疗服务的迫切需求,我们建议在常规医疗实践中实施CAHT系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b85/11611801/68dbf952381b/medinform-v12-e60655-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b85/11611801/e99e72e4ae04/medinform-v12-e60655-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b85/11611801/68dbf952381b/medinform-v12-e60655-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b85/11611801/e99e72e4ae04/medinform-v12-e60655-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b85/11611801/f2066de39511/medinform-v12-e60655-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b85/11611801/78c41e82d506/medinform-v12-e60655-g003.jpg
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Improving Emergency Department Patient-Physician Conversation Through an Artificial Intelligence Symptom-Taking Tool: Mixed Methods Pilot Observational Study.通过人工智能症状采集工具改善急诊科医患对话:混合方法试点观察性研究
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PLoS One. 2021 Sep 27;16(9):e0257677. doi: 10.1371/journal.pone.0257677. eCollection 2021.
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