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A design methodology for medical processes

By Simona Ferrante, Stefano Bonacina, Giuseppe Pozzi, Francesco Pinciroli and Sara Marceglia


BACKGROUND: Healthcare processes, especially those belonging to the clinical domain, are acknowledged as complex and characterized by the dynamic nature of the diagnosis, the variability of the decisions made by experts driven by their experiences, the local constraints, the patient's needs, the uncertainty of the patient's response, and the indeterminacy of patient's compliance to treatment. Also, the multiple actors involved in patient's care need clear and transparent communication to ensure care coordination.\ud OBJECTIVES:\ud In this paper, we propose a methodology to model healthcare processes in order to break out complexity and provide transparency.\ud METHODS:\ud The model is grounded on a set of requirements that make the healthcare domain unique with respect to other knowledge domains. The modeling methodology is based on three main phases: the study of the environmental context, the conceptual modeling, and the logical modeling.\ud RESULTS:\ud The proposed methodology was validated by applying it to the case study of the rehabilitation process of stroke patients in the specific setting of a specialized rehabilitation center. The resulting model was used to define the specifications of a software artifact for the digital administration and collection of assessment tests that was also implemented.\ud CONCLUSIONS:\ud Despite being only an example, our case study showed the ability of process modeling to answer the actual needs in healthcare practices. Independently from the medical domain in which the modeling effort is done, the proposed methodology is useful to create high-quality models, and to detect and take into account relevant and tricky situations that can occur during process execution

Topics: Computing methodologies, Critical pathways, Healthcare process modeling and design, Patient care management, Patient-centered care, Humans, Medical Informatics, Software, Stroke Rehabilitation, Delivery of Health Care, Computer Science Applications1707 Computer Vision and Pattern Recognition, Health Informatics, Health Information Management
Year: 2016
DOI identifier: 10.4338/ACI-2015-08-RA-0111
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