Is artificial intelligence for medical professionals serving the patients? : Protocol for a systematic review on patient-relevant benefits and harms of algorithmic decision-making.
Christoph Wilhelm, Anke Steckelberg, Felix G Rebitschek
{"title":"Is artificial intelligence for medical professionals serving the patients? : Protocol for a systematic review on patient-relevant benefits and harms of algorithmic decision-making.","authors":"Christoph Wilhelm, Anke Steckelberg, Felix G Rebitschek","doi":"10.1186/s13643-024-02646-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Algorithmic decision-making (ADM) utilises algorithms to collect and process data and develop models to make or support decisions. Advances in artificial intelligence (AI) have led to the development of support systems that can be superior to medical professionals without AI support in certain tasks. However, whether patients can benefit from this remains unclear. The aim of this systematic review is to assess the current evidence on patient-relevant benefits and harms, such as improved survival rates and reduced treatment-related complications, when healthcare professionals use ADM systems (developed using or working with AI) compared to healthcare professionals without AI-related ADM (standard care)-regardless of the clinical issues.</p><p><strong>Methods: </strong>Following the PRISMA statement, MEDLINE and PubMed (via PubMed), Embase (via Elsevier) and IEEE Xplore will be searched using English free text terms in title/abstract, Medical Subject Headings (MeSH) terms and Embase Subject Headings (Emtree fields). Additional studies will be identified by contacting authors of included studies and through reference lists of included studies. Grey literature searches will be conducted in Google Scholar. Risk of bias will be assessed by using Cochrane's RoB 2 for randomised trials and ROBINS-I for non-randomised trials. Transparent reporting of the included studies will be assessed using the CONSORT-AI extension statement. Two researchers will screen, assess and extract from the studies independently, with a third in case of conflicts that cannot be resolved by discussion.</p><p><strong>Discussion: </strong>It is expected that there will be a substantial shortage of suitable studies that compare healthcare professionals with and without ADM systems concerning patient-relevant endpoints. This can be attributed to the prioritisation of technical quality criteria and, in some cases, clinical parameters over patient-relevant endpoints in the development of study designs. Furthermore, it is anticipated that a significant portion of the identified studies will exhibit relatively poor methodological quality and provide only limited generalisable results.</p><p><strong>Systematic review registration: </strong>This study is registered within PROSPERO (CRD42023412156).</p>","PeriodicalId":22162,"journal":{"name":"Systematic Reviews","volume":null,"pages":null},"PeriodicalIF":6.3000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11378383/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Systematic Reviews","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13643-024-02646-6","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Algorithmic decision-making (ADM) utilises algorithms to collect and process data and develop models to make or support decisions. Advances in artificial intelligence (AI) have led to the development of support systems that can be superior to medical professionals without AI support in certain tasks. However, whether patients can benefit from this remains unclear. The aim of this systematic review is to assess the current evidence on patient-relevant benefits and harms, such as improved survival rates and reduced treatment-related complications, when healthcare professionals use ADM systems (developed using or working with AI) compared to healthcare professionals without AI-related ADM (standard care)-regardless of the clinical issues.
Methods: Following the PRISMA statement, MEDLINE and PubMed (via PubMed), Embase (via Elsevier) and IEEE Xplore will be searched using English free text terms in title/abstract, Medical Subject Headings (MeSH) terms and Embase Subject Headings (Emtree fields). Additional studies will be identified by contacting authors of included studies and through reference lists of included studies. Grey literature searches will be conducted in Google Scholar. Risk of bias will be assessed by using Cochrane's RoB 2 for randomised trials and ROBINS-I for non-randomised trials. Transparent reporting of the included studies will be assessed using the CONSORT-AI extension statement. Two researchers will screen, assess and extract from the studies independently, with a third in case of conflicts that cannot be resolved by discussion.
Discussion: It is expected that there will be a substantial shortage of suitable studies that compare healthcare professionals with and without ADM systems concerning patient-relevant endpoints. This can be attributed to the prioritisation of technical quality criteria and, in some cases, clinical parameters over patient-relevant endpoints in the development of study designs. Furthermore, it is anticipated that a significant portion of the identified studies will exhibit relatively poor methodological quality and provide only limited generalisable results.
Systematic review registration: This study is registered within PROSPERO (CRD42023412156).
期刊介绍：
Systematic Reviews encompasses all aspects of the design, conduct and reporting of systematic reviews. The journal publishes high quality systematic review products including systematic review protocols, systematic reviews related to a very broad definition of health, rapid reviews, updates of already completed systematic reviews, and methods research related to the science of systematic reviews, such as decision modelling. At this time Systematic Reviews does not accept reviews of in vitro studies. The journal also aims to ensure that the results of all well-conducted systematic reviews are published, regardless of their outcome.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
