Evidence map›Paper›PMID 37192808›Full record

ArticleBMJ open2023

Development and evaluation of a data-driven integrated management app for perioperative adverse events: protocol for a mixed-design study.

Peiyi Li, Ce Wang, Ruihao Zhou, Lingcan Tan, Xiaoqian Deng, Tao Zhu, Guo Chen, Weimin Li, Xuechao Hao

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Peiyi LiDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.ORCID 0000-0002-2380-2562
Ce WangDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Ruihao ZhouDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.ORCID 0000-0002-2119-0945
Lingcan TanDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Xiaoqian DengDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.ORCID 0000-0001-6694-8513
Tao ZhuDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.ORCID 0000-0002-4557-8872
Guo ChenDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Weimin LiDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.ORCID 0000-0003-0985-0311
Xuechao HaoDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China aneshxc@163.com.ORCID 0000-0002-8312-7060
Chinese Academy of Medical Sciences & Peking Union Medical College · CNSichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionA 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.

Indexed as

Mobile ApplicationsChinaHumansResearch DesignSurveys and QuestionnairesTreatment OutcomeAdverse eventsHEALTH SERVICES ADMINISTRATION & MANAGEMENTProtocols & guidelines

Identifiers

PMID37192808
PMCPMC10193061
OpenAlexW4376872790

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.