BACKGROUND: Many studies have been conducted that highlight the prevalence of misdiagnoses within the medical profession and the statistically poor diagnostic accuracy rates associated with junior clinicians. OBJECTIVE: There is evidence that crowdsourcing and multiple medical opinions can improve the veracity of a diagnosis. This paper proposes a cloud based prototype that makes use of interactive web technologies along with the concepts of crowdsourcing and e-learning to improve diagnostic accuracy rates amongst junior doctors. METHODS: Existing approaches in this field are analysed to identify potential gaps and opportunities. Sample representations of both junior and senior clinicians are surveyed to establish the feasibility of adopting collaborative diagnostics. It is theorised that the prototype developed in this work will harness the experience and knowledge of expert clinicians. RESULTS: The prototype is a fully responsive web-based and feature-rich interactive system that has been developed using the latest Internet technologies. It has been evaluated using usability tests and a one month long trial involving a sample of end-users. CONCLUSIONS: Crowdsourcing is an innovative process in its infancy but the results being produced indicate a promising future for its use within medicine. The results offer an inclination that the prototype's usage could be attributed to improved diagnostic ability. However the findings need to be replicated in larger, independent samples.
BACKGROUND: Many studies have been conducted that highlight the prevalence of misdiagnoses within the medical profession and the statistically poor diagnostic accuracy rates associated with junior clinicians. OBJECTIVE: There is evidence that crowdsourcing and multiple medical opinions can improve the veracity of a diagnosis. This paper proposes a cloud based prototype that makes use of interactive web technologies along with the concepts of crowdsourcing and e-learning to improve diagnostic accuracy rates amongst junior doctors. METHODS: Existing approaches in this field are analysed to identify potential gaps and opportunities. Sample representations of both junior and senior clinicians are surveyed to establish the feasibility of adopting collaborative diagnostics. It is theorised that the prototype developed in this work will harness the experience and knowledge of expert clinicians. RESULTS: The prototype is a fully responsive web-based and feature-rich interactive system that has been developed using the latest Internet technologies. It has been evaluated using usability tests and a one month long trial involving a sample of end-users. CONCLUSIONS: Crowdsourcing is an innovative process in its infancy but the results being produced indicate a promising future for its use within medicine. The results offer an inclination that the prototype's usage could be attributed to improved diagnostic ability. However the findings need to be replicated in larger, independent samples.
Keywords:
Collaborative diagnosis; crowdsourcing; e-learning; human computer interaction; medical education; medical informatics