Development and evaluation of a data-driven integrated management app for perioperative adverse events: protocol for a mixed-design study Article Swipe
Peiyi Li
,
Ce Wang
,
Ruihao Zhou
,
Lingcan Tan
,
Xiaoqian Deng
,
Tao Zhu
,
Guo Chen
,
Weimin Li
,
Xuechao Hao
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1136/bmjopen-2022-069754
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1136/bmjopen-2022-069754
Introduction A patient record review study conducted in 2006 in a random sample of 21 Dutch hospitals found that 51%–77% of adverse events are related to perioperative care, while Centers for Disease Control and Prevention data in USA in 2013 estimated that the medical error is the third-leading cause of mortality. To capitalise on the potential of apps to enhance perioperative medical quality, there is a need for interventions developed in consultation with real-world users designed to support integrated management for perioperative adverse events (PAEs). This study aims: (1) to access the knowledge, attitude and practices for PAEs among physicians, nurses and administrators, and to identify the needs of healthcare providers for a mobile-based PAEs tool; (2) to develop a data-driven app for integrated PAE management that meets those needs and (3) to test the usability, clinical efficacy and cost-effectiveness of the developed app. Methods and analysis We will adopt an embedded mixed-methods research technique; qualitative data will be used to assess user needs and app adoption, while quantitative data will provide crucial insights to establish the demand for the app, and measure the app effects. Phase 1 will enrol surgery-related healthcare providers from the West China Hospital and identify their latent demand for mobile-based PAEs management using a self-designed questionnaire underpinned by the knowledge, attitude and practice model, as well as expert interviews. In phase 2, we will develop the app for integrated PAE management and test its effectiveness and sustainability. In phase 3, the effects on the total number and severity of reported PAEs will be evaluated using Poisson regression with interrupted time-series analysis over a 2-year period, while users’ engagement, adherence, process evaluation and cost-effectiveness will be evaluated using quarterly surveys and interviews. Ethics and dissemination The West China Hospital of Sichuan University’s Institutional Review Board authorised this study after approving the study protocol, permission forms and questionnaires (number: 2022-1364). Participants will be provided with study information, and informed written consent will be obtained. Study findings will be disseminated through peer-reviewed publications and conference presentations.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1136/bmjopen-2022-069754
- https://bmjopen.bmj.com/content/bmjopen/13/5/e069754.full.pdf
- OA Status
- gold
- Cited By
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- References
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- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4376872790
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4376872790Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1136/bmjopen-2022-069754Digital Object Identifier
- Title
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Development and evaluation of a data-driven integrated management app for perioperative adverse events: protocol for a mixed-design studyWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-05-01Full publication date if available
- Authors
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Peiyi Li, Ce Wang, Ruihao Zhou, Lingcan Tan, Xiaoqian Deng, Tao Zhu, Guo Chen, Weimin Li, Xuechao HaoList of authors in order
- Landing page
-
https://doi.org/10.1136/bmjopen-2022-069754Publisher landing page
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https://bmjopen.bmj.com/content/bmjopen/13/5/e069754.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://bmjopen.bmj.com/content/bmjopen/13/5/e069754.full.pdfDirect OA link when available
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Medicine, Protocol (science), Perioperative, Adverse effect, Data management, Research design, Alternative medicine, Database, Surgery, Pharmacology, Pathology, Social science, Computer science, SociologyTop concepts (fields/topics) attached by OpenAlex
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3Total citation count in OpenAlex
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2025: 2, 2024: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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