From the Editor Journal of the Royal Society of Medicine; 2017, Vol. 110(8) 303 DOI: 10.1177/0141076817724926
Research methods for new technologies Kamran Abbasi Editor, JRSM
Any push for higher levels of evidence faces practical difficulties. One of these is resourcing. Randomised controlled trials and systematic reviews, when done properly, require money and infrastructure. A second and more complex matter is that these potentially robust methodologies are not always appropriate. In this issue, we highlight two such scenarios. Cresswell et al.1 discuss the challenges posed by evaluations of health information technology. As every aspect of clinical care and health service design is transformed, the health information technology industry is projected to be worth $230 billion by 2020. The effects of these changes can be small and diffuse, and the context of any innovation is important to its evaluation. The rapid evolution of health technology poses another riddle for investigators. One possible solution is to draw on something the authors describe as human factors engineering. This takes several forms, but one example is to use iterative methods that allow fast development and testing of technological prototypes in real-world settings informed by user feedback. The authors argue that these methods overcome the drawbacks of more traditional evaluative techniques and involve users throughout the development process. The explosion of genetic information opens up possibilities for personalised therapies, which by their individual nature create problems for evaluators. Trials of therapy to assess a patient’s response are long established in medical practice, although the push for greater rigour, by evaluating therapies in
! The Royal Society of Medicine 2017 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav
larger numbers of patients means, that this approach is sometimes questioned. With the clamour for personalised therapies, N-of-1 trials are being proposed as one way forward. Technology may also play a role here, and Mirza et al.2 describe the history and development of N-of-1 trials. If these methodological concerns are a little too intense for a summer’s day, you might wish to turn to the latest article in our health policy series which examines the benefits of international health partnerships in our interconnected world.3 It is a world that is also offering governing opportunities to populist politicians. If you are wondering how to respond as a medical or public health professional, Scott Greer4 proposes five ways to think your way through. References 1. Cresswell KM, Blandford A and Sheikh A. Drawing on human factors engineering to evaluate the effectiveness of health information technology. J R Soc Med 2017; 110: 309–315. 2. Mirza RD, Punja S, Vohra S and Guyatt G. The history and development of N-of-1 trials. J R Soc Med 2017; 110: 330–340. 3. Issa H, Kulasabanathan K, Darzi A and Harris M. Shared learning in an interconnected world: the role of international health partnerships. J R Soc Med 2017; 110: 316–319. 4. Greer SL. Medicine, public health and the populist radical right. J R Soc Med 2017; 110: 305–308.
Research methods for new technologies Kamran Abbasi Editor, JRSM
Any push for higher levels of evidence faces practical difficulties. One of these is resourcing. Randomised controlled trials and systematic reviews, when done properly, require money and infrastructure. A second and more complex matter is that these potentially robust methodologies are not always appropriate. In this issue, we highlight two such scenarios. Cresswell et al.1 discuss the challenges posed by evaluations of health information technology. As every aspect of clinical care and health service design is transformed, the health information technology industry is projected to be worth $230 billion by 2020. The effects of these changes can be small and diffuse, and the context of any innovation is important to its evaluation. The rapid evolution of health technology poses another riddle for investigators. One possible solution is to draw on something the authors describe as human factors engineering. This takes several forms, but one example is to use iterative methods that allow fast development and testing of technological prototypes in real-world settings informed by user feedback. The authors argue that these methods overcome the drawbacks of more traditional evaluative techniques and involve users throughout the development process. The explosion of genetic information opens up possibilities for personalised therapies, which by their individual nature create problems for evaluators. Trials of therapy to assess a patient’s response are long established in medical practice, although the push for greater rigour, by evaluating therapies in
! The Royal Society of Medicine 2017 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav
larger numbers of patients means, that this approach is sometimes questioned. With the clamour for personalised therapies, N-of-1 trials are being proposed as one way forward. Technology may also play a role here, and Mirza et al.2 describe the history and development of N-of-1 trials. If these methodological concerns are a little too intense for a summer’s day, you might wish to turn to the latest article in our health policy series which examines the benefits of international health partnerships in our interconnected world.3 It is a world that is also offering governing opportunities to populist politicians. If you are wondering how to respond as a medical or public health professional, Scott Greer4 proposes five ways to think your way through. References 1. Cresswell KM, Blandford A and Sheikh A. Drawing on human factors engineering to evaluate the effectiveness of health information technology. J R Soc Med 2017; 110: 309–315. 2. Mirza RD, Punja S, Vohra S and Guyatt G. The history and development of N-of-1 trials. J R Soc Med 2017; 110: 330–340. 3. Issa H, Kulasabanathan K, Darzi A and Harris M. Shared learning in an interconnected world: the role of international health partnerships. J R Soc Med 2017; 110: 316–319. 4. Greer SL. Medicine, public health and the populist radical right. J R Soc Med 2017; 110: 305–308.
