{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,9]],"date-time":"2026-08-09T10:11:33Z","timestamp":1786270293574,"version":"build-2736575974"},"reference-count":57,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Res Protoc"],"abstract":"\n Background<\/jats:title>\n The use of technologies has had a significant impact on patient safety and the quality of care and has increased globally. In the literature, it has been reported that people die annually due to adverse events (AEs), and various methods exist for investigating and measuring AEs. However, some methods have a limited scope, data extraction, and the need for data standardization. In Brazil, there are few studies on the application of trigger tools, and this study is the first to create automated triggers in ambulatory care.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aims to develop a machine learning (ML)\u2013based automated trigger for outpatient health care settings in Brazil.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n A mixed methods research will be conducted within a design thinking framework and the principles will be applied in creating the automated triggers, following the stages of (1) empathize and define the problem, involving observations and inquiries to comprehend both the user and the challenge at hand; (2) ideation, where various solutions to the problem are generated; (3) prototyping, involving the construction of a minimal representation of the best solutions; (4) testing, where user feedback is obtained to refine the solution; and (5) implementation, where the refined solution is tested, changes are assessed, and scaling is considered. Furthermore, ML methods will be adopted to develop automated triggers, tailored to the local context in collaboration with an expert in the field.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n This protocol describes a research study in its preliminary stages, prior to any data gathering and analysis. The study was approved by the members of the organizations within the institution in January 2024 and by the ethics board of the University of S\u00e3o Paulo and the institution where the study will take place. in May 2024. As of June 2024, stage 1 commenced with data gathering for qualitative research. A separate paper focused on explaining the method of ML will be considered after the outcomes of stages 1 and 2 in this study.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n After the development of automated triggers in the outpatient setting, it will be possible to prevent and identify potential risks of AEs more promptly, providing valuable information. This technological innovation not only promotes advances in clinical practice but also contributes to the dissemination of techniques and knowledge related to patient safety. Additionally, health care professionals can adopt evidence-based preventive measures, reducing costs associated with AEs and hospital readmissions, enhancing productivity in outpatient care, and contributing to the safety, quality, and effectiveness of care provided. Additionally, in the future, if the outcome is successful, there is the potential to apply it in all units, as planned by the institutional organization.<\/jats:p>\n <\/jats:sec>\n \n International Registered Report Identifier (IRRID)<\/jats:title>\n PRR1-10.2196\/55466<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/55466","type":"journal-article","created":{"date-parts":[[2024,6,17]],"date-time":"2024-06-17T15:33:28Z","timestamp":1718638408000},"page":"e55466","source":"Crossref","is-referenced-by-count":2,"title":["Development of Automated Triggers in Ambulatory Settings in Brazil: Protocol for a Machine Learning\u2013Based Design Thinking Study"],"prefix":"10.2196","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0290-2166","authenticated-orcid":false,"given":"Claire Nierva","family":"Herrera","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5174-112X","authenticated-orcid":false,"given":"Fernanda Raphael Escobar","family":"Gimenes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7532-6090","authenticated-orcid":false,"given":"Jo\u00e3o Paulo","family":"Herrera","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5010-4914","authenticated-orcid":false,"given":"Ricardo","family":"Cavalli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2024,8,12]]},"reference":[{"key":"ref1","unstructured":"Global action on patient safety: report by the Director-GeneralWorld Health Organization20192024-07-25https:\/\/apps.who.int\/gb\/ebwha\/pdf_files\/WHA72\/A72_R6-em.pdf"},{"key":"ref2","unstructured":"Global patient safety action plan 2021\u20132030: towards eliminating avoidable harm in health careWorld Health Organization20212024-07-25https:\/\/apps.who.int\/iris\/handle\/10665\/343477"},{"key":"ref3","unstructured":"SlawomirskiLKlazingaNOECD iLibraryThe economics of patient safety : from analysis to action20202024-07-25Parishttps:\/\/www.oecd-ilibrary.org\/social-issues-migration-health\/the-economics-of-patient-safety_761f2da8-en"},{"key":"ref4","unstructured":"World Health OrganizationAssessing and tackling patient harm: a methodological guide for data-poor hospitals2024-07-25http:\/\/www.who.int\/substance_abuse\/research_tools\/translation\/em\/"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.2147\/TCRM.S282294"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1590\/1983-1447.2020.20190364"},{"key":"ref7","unstructured":"GriffinFAResarRKIHI global trigger tool for measuring adverse eventsInstitute for Healthcare Improvement20092024-07-25https:\/\/www.ihi.org\/resources\/Pages\/IHIWhitePapers\/IHIGlobalTriggerToolWhitePaper.aspx"},{"key":"ref8","unstructured":"IHI global trigger tool for measuring adverse eventsInstitute for Healthcare Improvement20232024-07-25https:\/\/www.ihi.org\/resources\/Pages\/Tools\/IHIGlobalTriggerToolforMeasuringAEs.aspx"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.9901"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0272853"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2003.08.003"},{"key":"ref12","unstructured":"IHI outpatient adverse events trigger tool. 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