ITEMAS ontology for healthcare technology innovation Articles uri icon

authors

  • MORENO CODE, A.
  • MARTI RAS, N.
  • ALBERTI IBARZ, M.
  • DESCO MENENDEZ, MANUEL
  • PARRA CALDERON, CARLOS LUIS
  • SANCHEZ SEDA, S.
  • ESCOBAR RODRIGUEZ, G. A.
  • LOPEZ OTERO, M.
  • CUSSO MULA, LORENA
  • DEL CERRO GARCIA, R.
  • SEGURA SANCHEZ, M.
  • HERRERO URIGUEN, L.

publication date

  • May 2019

volume

  • 17

international standard serial number (ISSN)

  • 1478-4505

abstract

  • BackgroundThe Platform for Innovation in Medical and Health Technologies (ITEMAS) is a network of 66 healthcare centres focused on fostering innovation in medical and health technologies as an essential tool for increasing the sustainability of the Spanish healthcare system. The present research is focused on defining a formal representation that details the most relevant concepts associated with the creation and adoption of innovative medical technology in the Spanish healthcare system.MethodsThe methodology applied is based on the methontology process, including peer-review identification and selection of concepts from the ITEMAS innovation indicators and innovation management system standards. This stage was followed by an iterative validation process. Concepts were then conceptualised, formalised and implemented in an ontology.ResultsThe ontology defined describes how relationships between employees, organisations, projects and ideas can be applied to generate results that are transferrable to the market, general public and scientific forums. Overall, we identified 136 concepts, 138 object properties and 30 properties in a five-level hierarchy. The ontology was tested and validated as an appropriate framework for calculating the ITEMAS innovation indicators.ConclusionsThe consensus concepts were expressed in the form of an ontology to be used as a single communication format between the members of the ITEMAS network. Healthcare centres can compare their innovation results and obtain a better understanding of their innovation context based on the reasoning techniques of artificial intelligence. As a result, they can benefit from advanced analytical capabilities to define the most appropriate innovation policies for each centre based on the common experience of the large number of healthcare centres involved. The results can be used to create a map of agents and knowledge to show capabilities, projects and services provided by each of the participating centres. Th

keywords

  • ontology; innovation management; medical technology; healthcare; indicators