Pub Date : 2002-01-01DOI: 10.1201/9781420006834.AXA1
C. Hansen
Lancet. 2018 Nov 24;392(10161):22632264. doi: 10.1016/S01406736(18)32819-8. Epub 2018 Nov 6 2018 UK / Australia None Expert opinion / correspondence Symptom checkers have great potential to improve diagnosis, quality of care, and health system performance worldwide. However, systems that are poorly designed or lack rigorous clinical evaluation can put patients at risk and likely increase the load on health systems. Evaluation guidelines specific to symptom checkers have three benefits. First, they would provide system creators with a fixed set of criteria, ahead of time, on which they will be assessed. Second, they would allow external observers to assess the comprehensiveness and quality of evaluation, discouraging system creators from inflating the importance of their results. Finally, they would facilitate policy makers in determining a minimum level of evidence required before wide-scale use of a system. Academic writing using references Evidence considered on level of expert opinion It is not possible to determine how well the Babylon Diagnostic and Triage System would perform on a broader randomized set of cases or with data entered by patients instead of doctors. Babylon’s study does not offer convincing evidence that its Babylon Diagnostic and Triage System can perform better than doctors in any realistic situation, and there is a possibility that it might perform significantly worse. Evaluation of symptom checkers should follow a multistage process of Paper Review: the Babylon Chatbot[Internet]. The Guide to Health Informatics 3rd Edition. 2018 [cited 2019 May 29]. Available from: https://coiera.com/2018/06/29/paperreview-the-babylon-chatbot/ 2018 Australia (from reference list) None Critical review / expert opinion The used vignettes were designed to test known capabilities of the system. Independently created vignettes exploring other diagnoses would likely have resulted in a much poorer performance. This tests Babylon on what it knows not what it might find ‘in the wild. It seems the presentation of information was in the OSCE format, which is artificial and not how patients might present. So there was no real testing of consultation and listening skills that would be needed to manage a real world patient presentation. A better evaluation model would have been to draw a random subset of cases and present them to both GPs and Babylon. Important views from expert Evidence considered on level of expert opinion The reviewed study are considered a very preliminary and artificial test of a Bayesian reasoner on cases for which it has already been trained. In machine learning this would be roughly equivalent to in-sample reporting of performance on the data used to develop the algorithm. Good practice is to report out of sample performance on previously unseen cases. The results are confounded by artificial conditions and use of few and non-independent assessors. There is lack of clarity in the way data are analyzed and there are numerous ris
{"title":"Table 2","authors":"C. Hansen","doi":"10.1201/9781420006834.AXA1","DOIUrl":"https://doi.org/10.1201/9781420006834.AXA1","url":null,"abstract":"Lancet. 2018 Nov 24;392(10161):22632264. doi: 10.1016/S01406736(18)32819-8. Epub 2018 Nov 6 2018 UK / Australia None Expert opinion / correspondence Symptom checkers have great potential to improve diagnosis, quality of care, and health system performance worldwide. However, systems that are poorly designed or lack rigorous clinical evaluation can put patients at risk and likely increase the load on health systems. Evaluation guidelines specific to symptom checkers have three benefits. First, they would provide system creators with a fixed set of criteria, ahead of time, on which they will be assessed. Second, they would allow external observers to assess the comprehensiveness and quality of evaluation, discouraging system creators from inflating the importance of their results. Finally, they would facilitate policy makers in determining a minimum level of evidence required before wide-scale use of a system. Academic writing using references Evidence considered on level of expert opinion It is not possible to determine how well the Babylon Diagnostic and Triage System would perform on a broader randomized set of cases or with data entered by patients instead of doctors. Babylon’s study does not offer convincing evidence that its Babylon Diagnostic and Triage System can perform better than doctors in any realistic situation, and there is a possibility that it might perform significantly worse. Evaluation of symptom checkers should follow a multistage process of Paper Review: the Babylon Chatbot[Internet]. The Guide to Health Informatics 3rd Edition. 2018 [cited 2019 May 29]. Available from: https://coiera.com/2018/06/29/paperreview-the-babylon-chatbot/ 2018 Australia (from reference list) None Critical review / expert opinion The used vignettes were designed to test known capabilities of the system. Independently created vignettes exploring other diagnoses would likely have resulted in a much poorer performance. This tests Babylon on what it knows not what it might find ‘in the wild. It seems the presentation of information was in the OSCE format, which is artificial and not how patients might present. So there was no real testing of consultation and listening skills that would be needed to manage a real world patient presentation. A better evaluation model would have been to draw a random subset of cases and present them to both GPs and Babylon. Important views from expert Evidence considered on level of expert opinion The reviewed study are considered a very preliminary and artificial test of a Bayesian reasoner on cases for which it has already been trained. In machine learning this would be roughly equivalent to in-sample reporting of performance on the data used to develop the algorithm. Good practice is to report out of sample performance on previously unseen cases. The results are confounded by artificial conditions and use of few and non-independent assessors. There is lack of clarity in the way data are analyzed and there are numerous ris","PeriodicalId":187396,"journal":{"name":"Equality and Non-Discrimination under the European Convention on Human Rights","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133397997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2002-01-01DOI: 10.1163/9789004481534_008
{"title":"Strictness of Review and the Necessity of Review","authors":"","doi":"10.1163/9789004481534_008","DOIUrl":"https://doi.org/10.1163/9789004481534_008","url":null,"abstract":"","PeriodicalId":187396,"journal":{"name":"Equality and Non-Discrimination under the European Convention on Human Rights","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122105176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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