Table 1.

Modeling requirements to represent the characteristic features of the clinical domain; R= requirements.

Clinical process complexity areas	Sub-areas	Modeling requirement to represent the sub-area	Ref.
Medical knowledge	Evidence based medicine, guidelines, recommendations	R1: Compliance to guidelines	[8,14,15,20,34-40]
		R2: Deal with dynamic evolution of medical evidence-based knowledge	[8,41]
	Local practices	R3: Manage flexibility (from meta-model to local context)	[44]
	Clinician personal experience, habits and skills	R4: Bind the design to interaction and cooperation between analysts and domain experts	[45]
	Learning by practice	R5: Deal with learning curves (process change)	[44, 45]
	Building evidence from practice	R6: Foresee process mining with big data analysis	[25, 26]
Response to treatment	Timeframe short-term or long-term response	R8: Manage uncertainty	[46–48]
	Compliance – depending on patient’s engagement	R9: Manage indeterminacy	[46–48]
	Expected outcomes	R10: Define outcome variables	[49, 50]
	Patient feedback to reshape therapy – depending on patient’s empowerment and education	R11: Integrate patient-reported outcome measures	[49, 50]
		R8: Manage uncertainty	[46–48]
Personalization of care	Patient-centric approach – treatment definition considering patients preferences and history	R7: Manage exceptions	[42]
		R3: Manage flexibility	[34]
	Treatment adaptation considering occurring changes	R3: Manage flexibility	[34]