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4. Discussion and conclusions The remaining chapters of this book describe many examples of theories or principles which have been tested in health informatics, with mixed results. However, for the reasons identified in section 1 above, we need to accelerate our progress on theory-based informatics, which requires three specific actions. First, we need to identify more theories that seem relevant to our work from the many existing sources, and derive predictive principles from them for testing. We should also not hesitate to formulate our own testable, generic principles (perhaps to explain failures in a clinical information system we developed, by analogy with the aeronautical engineers investigating the Comet disaster in the 1950s, described above in box 2). Second, we need to test the applicability of each principle in a variety of contexts, to build confidence that the principle – and the theory from which it was derived - does indeed lead to more effective systems [10]. Finally, whether the result of the testing process is positive or negative, we need to work with research and professional organizations at the national and international scale to share that principle and the test results with students and system developers, to encourage them to adopt useful, relevant principles and to drop any that testing shows to be unhelpful, or even harmful. Only this way, in my view, can we move our discipline out of the shadows of authoritarian tradition, superstition or even mysticism, where systems are as likely to harm as to help [13, 14], into the bright light of professionalism where robust, scientifically tested theories and principles guide our work, resulting in predictably usable, safe and effective information systems [15]. Teaching questions for reflection 1. How can the use of tested theories and principles move the health informatics discipline forward as a scientific discipline? 2. What are the potential risks and downsides of a greater reliance on theory? 3. Why are theories or principles advocated by experts not necessarily useful to guide the development of better clinical information systems? 4. How would you test the impact of a new principle that claims to guide the design of safer ePrescribing systems? 5. Will we ever have a Grand Theory of health informatics? If so, could it pass all five criteria for a useful predictive principle listed in the table in section 2? References [1] P. Nilsen. Making sense of implementation theories, models and frameworks. Implement Science 10 (2015), 53. [2] User interface design principles. Section 3.3.4 in B. Shneiderman, C. Plaisant, M. Cohen, S. Jacobs, and N. Elmqvist. Designing the User Interface: Strategies for Effective Human-Computer Interaction: Sixth Edition, Pearson (May 16). [3] S. Michie, M.M. van Stralen, R. West. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Science 6 (2011), 42. [4] J. van der Lei. Use and abuse of computer-stored medical records. Methods Inf Med. 2 (1991), 79-80. [5] K. Kidholm, A.G. Ekeland, L.K. Jensen, J. Rasmussen, C.D. Pedersen, A. Bowes, S.A. Flottorp, M. Bech. A model for assessment of telemedicine applications: mast. Int J Technol Assess Health Care. 1 (2012), 44-51. J.C.Wyatt /TheNeed forTheory to InformClinical InformationSystems 7