title: Diabetes care related process modelling using Process Mining techniques. Lessons learned in the application of Interactive Pattern Recognition: coping with the Spaghetti Effect.
abstract: Diabetes is one of the metabolic disorders with more growth expectations in next decades. The literature points to a correct self-management, to an appropriate treatment and to an adequate healthy lifestyle as a way to dramatically improve the quality of life of patients with diabetes. The implementation of a holistic diabetes care system, using rising information technologies for deploying cares based on the thesis of the Evidence-Based Medicine can be a effective solution to provide an adequate and continuous care to patients. However, the design and deployment of computer readable careflows is not a easy task. In this paper, we propose the use of Interactive Pattern Recognition techniques for the iterative design of those protocols and we analyze the problems of using Process Mining to infer careflows and how to how to cope with the resulting Spaghetti Effect.
authors.forename: Carlos
authors.initials: C
authors.lastname: Fernandez-Llatas
authors.forename: Antonio
authors.initials: A
authors.lastname: Martinez-Millana
authors.forename: Alvaro
authors.initials: A
authors.lastname: Martinez-Romero
authors.forename: Jose Miguel
authors.initials: JM
authors.lastname: Benedi
authors.forename: Vicente
authors.initials: V
authors.lastname: Traver
mesh_terms: D000465:Algorithms; D057225:Data Mining / Q000379:methods*; D003920:Diabetes Mellitus / Q000628:therapy*; D019317:Evidence-Based Medicine; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D011788:Quality of Life; D012648:Self Care; D057188:Workflow