A Conceptual Framework for Decision-making Support in Uncertainty- and Risk-based Diagnosis of Rare Clinical Cases by Specialist Physicians.
Mitigating uncertainty and risks faced by specialist physicians in analysis of rare clinical cases is something desired by anyone who needs health services. The number of clinical cases never seen by these experts, with little documentation, may introduce errors in decision-making. Such errors negatively affect well-being of patients, increase procedure costs, rework, health insurance premiums, and impair the reputation of specialists and medical systems involved. In this context, IT and Clinical Decision Support Systems (CDSS) play a fundamental role, supporting decision-making process, making it more efficient and effective, reducing a number of avoidable medical errors and enhancing quality of treatment given to patients. An investigation has been initiated to look into characteristics and solution requirements of this problem, model it, propose a general solution in terms of a conceptual risk-based, automated framework to support rare-case medical diagnostics and validate it by means of case studies. A preliminary validation study of the proposed framework has been carried out by interviews conducted with experts who are practicing professionals, academics, and researchers in health care. This paper summarizes the investigation and its positive results. These results motivate continuation of research towards development of the conceptual framework and of a software tool that implements the proposed model.
Graduate Program in Computer Science from the Federal University of Campina Grande - UFCG Centro de Ensino Superior e Desenvolvimento - CESED Campina Grande - PB, Brazil.
Adriano A
AA
Santos
Systems and Computing Department - Federal University of Campina Grande - DSC/UFCG, Brazil.
J Antão B
JA
Moura
Systems and Computing Department - Federal University of Campina Grande - DSC/UFCG, Brazil.
Joseana Macêdo Fechine Régis
JM
de Araújo
D020000:Decision Support Systems, Clinical / Q000458:organization & administration / Q000592:standards; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003951:Diagnostic Errors / Q000517:prevention & control; D006801:Humans; D008511:Medicine / Q000379:methods*; D008962:Models, Theoretical; D035583:Rare Diseases / Q000175:diagnosis*; D012306:Risk; D035501:Uncertainty