Artificial Intelligence for Supporting Decisions on Referral of Cases in Health Systems: a Protocol for a Scoping Review
Creators: name: Pachito, Daniela
name: de Faria Leao, Beatriz
name: , Angela
name: Gadenz, Sabrina
name: Kersanach, Maria
Publisher: name: Open Science Framework
Year: 2022
Subjects: subject: Medicine and Health Sciences

description: Scoping review aiming at the identification of studies in which Artificial Intelligence (AI) had been applied to support decision on referral of cases, and synthesis of findings. This scoping review will be developed in five stages comprised of definition of the research questions; elaboration of search strategies; assessment of study eligibility; data extraction; and summary of findings. The study report will be structured in adherence to PRISMA extension for scoping reviews (PRISMA-ScR). The following research questions were a priori defined: How has AI been used in the context of managing patient flow between different levels of health care / health services? In what contexts is AI used for this purpose? (types of health care system, types of medical specialty, elective x emergency care) What is the methodology used for the development of AI? (features, types of AI, modelling characteristics) How can AI be validated and implemented? Searches were conducted on PubMed, Cochrane Library, Lilacs and Embase in April 2021. Search strategy for PubMed is presented below. # 1 "Artificial Intelligence"[Mesh] OR (Intelligence, Artificial) OR (Computational Intelligence) OR (Intelligence, Computational) OR (Machine Intelligence) OR (Intelligence, Machine) OR (Computer Reasoning) OR (Reasoning, Computer) OR (AI (Artificial Intelligence)) OR (Computer Vision Systems) OR (Computer Vision System) OR (System, Computer Vision) OR (Systems, Computer Vision) OR (Vision System, Computer) OR (Vision Systems, Computer) OR (Knowledge Acquisition (Computer)) OR (Acquisition, Knowledge (Computer)) OR (Knowledge Representation (Computer)) OR (Knowledge Representations (Computer)) OR (Representation, Knowledge Computer) #2 "Machine Learning"[Mesh] OR (Learning, Machine) OR (Transfer Learning) OR (Learning, Transfer) #3 "Deep Learning"[Mesh] OR (Learning, Deep) OR (Hierarchical Learning) OR (Learning, Hierarchical) #4 "Natural Language Processing"[Mesh] OR (Language Processing, Natural) OR (Language Processings, Natural) OR (Natural Language Processings) OR (Processing, Natural Language) OR (Processings, Natural Language) #5 "Decision Support Systems, Clinical"[Mesh] OR (Clinical Decision Support Systems) OR (Clinical Decision Support System) OR (Clinical Decision Support) OR (Clinical Decision Supports) OR (Decision Supports, Clinical) OR (Support, Clinical Decision) OR (Supports, Clinical Decision) OR (Decision Support, Clinical) #6 "Decision Support Techniques"[Mesh] OR (Decision Support Technique) OR (Technique, Decision Support) OR (Techniques, Decision Support) OR (Decision Support Technics) OR (Decision Support Technic) OR (Technic, Decision Support) OR (Technics, Decision Support) OR (Models, Decision Support) OR (Decision Support Model) OR (Decision Support Models) OR (Model, Decision Support) OR (Decision Modeling) OR (Modeling, Decision) OR (Decision Aids) OR (Aid, Decision) OR (Aids, Decision) OR (Decision Aid) OR (Decision Analysis) OR (Analyses, Decision) OR (Decision Analyses) OR (Analysis, Decision) #7 "Decision Making, Computer-Assisted"[Mesh] OR (Decision Making, Computer Assisted) OR (Computer-Assisted Decision Making) OR (Computer Assisted Decision Making) OR (Medical Decision Making, Computer-Assisted) OR (Medical Decision Making, Computer Assisted) #8 #1 OR #2 OR #3 OR #4 OR #5 OR #6 OR #7 #9 "Referral and Consultation"[Mesh] OR (Gatekeepers, Health Service) OR (Health Service Gatekeepers) OR (Gatekeeper, Health Service) OR (Health Service Gatekeeper) OR (Referral) OR (Referrals) #10 #8 AND #9 Inclusion criteria: Studies that applied Artificial Intelligence, including Machine Learning, Deep Learning, Natural Language Processing, neural networks, among other techniques for the development of predictive models, in order to support decision making on navigating cases to specialized care, regardless of the type of medical specialty; the elective or urgent character; as well as the type of the health system (public or private). Hybrid systems, using symbolic AI, will be considered for inclusion. Exclusion Criteria: Studies in which the use of Artificial Intelligence has the sole intention of diagnosing any health condition, or determining the prognosis of such condition, through the analysis of images or other techniques, without the evaluation of this strategy as support for case management across the different levels of care in a health system. Decision support systems using purely statistical methods, such as Bayesian probabilistic methods, will not be included. References will be screened in Rayyan by two independent reviewers in two stages. First abastract and titles will be assessed. At a second stage, full texts will be appraised considering the eligibility criteria. Data extraction will be performed in a previously developed spreadsheet. Data to be extracted will include, but will not be limited to, study objective, country, medical specialty, setting, type of health assistance (elective vs urgent), type of data applied in the model, number of observations, type of AI, methods for validation, accuracy of model. Results will be presented narratively. If many studies are identified, results will be presented in evidence maps.