{"title":"为什么工程师和临床医生说的不是同一种语言?对此该怎么办?","authors":"J. Wyatt","doi":"10.1109/CBMS.2013.6627753","DOIUrl":null,"url":null,"abstract":"In my experience, presentations at AIME, IEEE or EFMI conferences often describe work by academic engineers using patients as a source of data to explore new modelling methods, and few demonstrate convincing solutions to real world clinical problems. One reason for this is that many doctors make themselves inaccessible, so engineers find it hard to engage them in projects. Since healthcare and medical work are very complex, it takes years of exposure to clinicians and healthcare settings for an engineer to understand real-world patient management problems in sufficient detail to help solve them. This means that sometimes, an engineer might believe they have solved the problem, while to a clinician they have only explored an irrelevant simplification of it. Another explanation is that some engineering academics have had their fingers burned by clinicians, who expect the engineer to carry out an everyday system development task with no research payload. Such engineers will become suspicious of engaging too closely with doctors. Cynics might be less fair, observing that since medical research is well funded, there is a tendency for engineers to apply any novel engineering method to a simplified health data as this is more likely to attract funding than applying their method to, say, linguistics data. However, I believe there is a deeper explanation of why so few bioengineering projects seem to bear clinically digestible fruit: there are fundamental differences in motivation, research focus and research methods between engineering and healthcare research domains, and in the kind of problems they address. For example, the engineering approaches used in the Virtual Physiological Human programme mainly involve data mining and modelling, while clinicians emphasise using psychological, social or other theories to understand and formalise a complex problem first, then use empirical testing to find out whether a theory-based solution works - the evidence based approach. It is clearly unhelpful for engineers to criticise doctors as being poor collaborators in multidisciplinary projects, just as it is for doctors to criticise engineers. So, the aim of this talk is to move beyond name calling to explore common ground constructively and to provoke useful reflection and discussion, both within and across these disciplines. This talk will therefore explore some of the similarities and differences between engineering and healthcare as research disciplines, their respective approaches to problem solving and attempt to build bridges between these two very different worlds. In conclusion, unless we describe the features of this uneasy stand-off between engineers and clinicians, confront it head on and provoke debate, it looks set to continue. This will reduce productivity on both sides and limit the enormous scientific, economic and social benefits that novel, clinically appropriate and collaboratively engineered systems can generate.","PeriodicalId":74567,"journal":{"name":"Proceedings. IEEE International Symposium on Computer-Based Medical Systems","volume":"11 1","pages":"1"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Why don't engineers and clinicians talk the same language - And what to do about it?\",\"authors\":\"J. Wyatt\",\"doi\":\"10.1109/CBMS.2013.6627753\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In my experience, presentations at AIME, IEEE or EFMI conferences often describe work by academic engineers using patients as a source of data to explore new modelling methods, and few demonstrate convincing solutions to real world clinical problems. One reason for this is that many doctors make themselves inaccessible, so engineers find it hard to engage them in projects. Since healthcare and medical work are very complex, it takes years of exposure to clinicians and healthcare settings for an engineer to understand real-world patient management problems in sufficient detail to help solve them. This means that sometimes, an engineer might believe they have solved the problem, while to a clinician they have only explored an irrelevant simplification of it. Another explanation is that some engineering academics have had their fingers burned by clinicians, who expect the engineer to carry out an everyday system development task with no research payload. Such engineers will become suspicious of engaging too closely with doctors. Cynics might be less fair, observing that since medical research is well funded, there is a tendency for engineers to apply any novel engineering method to a simplified health data as this is more likely to attract funding than applying their method to, say, linguistics data. However, I believe there is a deeper explanation of why so few bioengineering projects seem to bear clinically digestible fruit: there are fundamental differences in motivation, research focus and research methods between engineering and healthcare research domains, and in the kind of problems they address. For example, the engineering approaches used in the Virtual Physiological Human programme mainly involve data mining and modelling, while clinicians emphasise using psychological, social or other theories to understand and formalise a complex problem first, then use empirical testing to find out whether a theory-based solution works - the evidence based approach. It is clearly unhelpful for engineers to criticise doctors as being poor collaborators in multidisciplinary projects, just as it is for doctors to criticise engineers. So, the aim of this talk is to move beyond name calling to explore common ground constructively and to provoke useful reflection and discussion, both within and across these disciplines. This talk will therefore explore some of the similarities and differences between engineering and healthcare as research disciplines, their respective approaches to problem solving and attempt to build bridges between these two very different worlds. In conclusion, unless we describe the features of this uneasy stand-off between engineers and clinicians, confront it head on and provoke debate, it looks set to continue. This will reduce productivity on both sides and limit the enormous scientific, economic and social benefits that novel, clinically appropriate and collaboratively engineered systems can generate.\",\"PeriodicalId\":74567,\"journal\":{\"name\":\"Proceedings. IEEE International Symposium on Computer-Based Medical Systems\",\"volume\":\"11 1\",\"pages\":\"1\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 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Why don't engineers and clinicians talk the same language - And what to do about it?
In my experience, presentations at AIME, IEEE or EFMI conferences often describe work by academic engineers using patients as a source of data to explore new modelling methods, and few demonstrate convincing solutions to real world clinical problems. One reason for this is that many doctors make themselves inaccessible, so engineers find it hard to engage them in projects. Since healthcare and medical work are very complex, it takes years of exposure to clinicians and healthcare settings for an engineer to understand real-world patient management problems in sufficient detail to help solve them. This means that sometimes, an engineer might believe they have solved the problem, while to a clinician they have only explored an irrelevant simplification of it. Another explanation is that some engineering academics have had their fingers burned by clinicians, who expect the engineer to carry out an everyday system development task with no research payload. Such engineers will become suspicious of engaging too closely with doctors. Cynics might be less fair, observing that since medical research is well funded, there is a tendency for engineers to apply any novel engineering method to a simplified health data as this is more likely to attract funding than applying their method to, say, linguistics data. However, I believe there is a deeper explanation of why so few bioengineering projects seem to bear clinically digestible fruit: there are fundamental differences in motivation, research focus and research methods between engineering and healthcare research domains, and in the kind of problems they address. For example, the engineering approaches used in the Virtual Physiological Human programme mainly involve data mining and modelling, while clinicians emphasise using psychological, social or other theories to understand and formalise a complex problem first, then use empirical testing to find out whether a theory-based solution works - the evidence based approach. It is clearly unhelpful for engineers to criticise doctors as being poor collaborators in multidisciplinary projects, just as it is for doctors to criticise engineers. So, the aim of this talk is to move beyond name calling to explore common ground constructively and to provoke useful reflection and discussion, both within and across these disciplines. This talk will therefore explore some of the similarities and differences between engineering and healthcare as research disciplines, their respective approaches to problem solving and attempt to build bridges between these two very different worlds. In conclusion, unless we describe the features of this uneasy stand-off between engineers and clinicians, confront it head on and provoke debate, it looks set to continue. This will reduce productivity on both sides and limit the enormous scientific, economic and social benefits that novel, clinically appropriate and collaboratively engineered systems can generate.