“A report by the National Academy of Medicine concluded that ‘most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences’. In primary care, GPs have the difficult task of detecting potentially serious but uncommon disease among predominantly non-serious complaints. Being reflective or considering alternatives is common advice to guard against diagnostic error; however, timing is crucial. First impressions — that is, the first hypotheses that come to mind — can exert a strong influence on subsequent diagnosis and management decisions. For example, using a think-aloud methodology, Kostopoulou and colleagues found that, if GPs did not explicitly acknowledge the possibility of cancer after reading a short patient description and the presenting problem, they were significantly less likely to diagnose cancer at the end of the consultation and refer to a specialist. In two studies in the UK and Greece, Kostopoulou and colleagues also found that providing GPs with a list of diagnostic suggestions at the start of online simulated consultations was associated with increased diagnostic accuracy and better management, in comparison with unaided control. Taken together, these findings attest to the importance of the initial stage of hypothesis generation for the final outcome of the diagnostic process, and the importance of intervening as early as possible to influence this initial stage, before GPs embark on testing hypotheses.”
The foregoing quote from the British Journal of General Practice article entitled “Diagnostic accuracy of GPs when using an early-intervention decision support system: a high-fidelity simulation” (
Please read the white paper at http://bit.ly/2me38s5, validate the content to your own satisfaction by reviewing the details of CHARTSaaS and the CHARTSaaS RA in these presentations, and then imagine CHARTSaaS-enabled IT solution:
Decision management in healthcare and its relations to BPM is very interesting topic. There are at least two aspects complicating timely and precise decisions in medical field. First, it is objective complexity of medicine making it immensely difficult to deduce right decisions from available facts. Secondly, dispersed information and insufficient awareness of medical professional about concrete patient impede correct diagnostics and treatment. While the first part of the problem merely relates to artificial intelligence and unlikely to be resolved fast, the second aspect is much more plausible to application of modern BPM technologies. Close integration of versatile concurrent workflows associated with any patient through intelligent process orchestration based on singular case aggregation could radically improve decision base for all health professionals and elevate quality of medical decisions to higher professional standards.