title: Developing the FARSEEING Taxonomy of Technologies: Classification and description of technology use (including ICT) in falls prevention studies.
abstract: Recent Cochrane reviews on falls and fall prevention have shown that it is possible to prevent falls in older adults living in the community and in care facilities. Technologies aimed at fall detection, assessment, prediction and prevention are emerging, yet there has been no consistency in describing or reporting on interventions using technologies. With the growth of eHealth and data driven interventions, a common language and classification is required.
  
  
  
  The FARSEEING Taxonomy of Technologies was developed as a tool for those in the field of biomedical informatics to classify and characterise components of studies and interventions.
  
  
  
  The Taxonomy Development Group (TDG) comprised experts from across Europe. Through face-to-face meetings and contributions via email, five domains were developed, modified and agreed: Approach; Base; Components of outcome measures; Descriptors of technologies; and Evaluation. Each domain included sub-domains and categories with accompanying definitions. The classification system was tested against published papers and further amendments undertaken, including development of an online tool. Six papers were classified by the TDG with levels of consensus recorded.
  
  
  
  Testing the taxonomy with papers highlighted difficulties in definitions across international healthcare systems, together with differences of TDG members' backgrounds. Definitions were clarified and amended accordingly, but some difficulties remained. The taxonomy and manual were large documents leading to a lengthy classification process. The development of the online application enabled a much simpler classification process, as categories and definitions appeared only when relevant. Overall consensus for the classified papers was 70.66%. Consensus scores increased as modifications were made to the taxonomy.
  
  
  
  The FARSEEING Taxonomy of Technologies presents a common language, which should now be adopted in the field of biomedical informatics. In developing the taxonomy as an online tool, it has become possible to continue to develop and modify the classification system to incorporate new technologies and interventions.
authors.affiliation: School of Nursing, Midwifery and Social Work, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK; Manchester Academic Health Sciences Centre, Manchester, UK. Electronic address: elisabeth.boulton@manchester.ac.uk.
authors.forename: Elisabeth
authors.initials: E
authors.lastname: Boulton
authors.affiliation: School of Nursing, Midwifery and Social Work, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK; Manchester Academic Health Sciences Centre, Manchester, UK. Electronic address: helen.hawley-hague@manchester.ac.uk.
authors.forename: Helen
authors.initials: H
authors.lastname: Hawley-Hague
authors.affiliation: Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway. Electronic address: beatrix.vereijken@ntnu.no.
authors.forename: Beatrix
authors.initials: B
authors.lastname: Vereijken
authors.affiliation: Department of Clinical Therapies, University of Limerick, Limerick, Ireland. Electronic address: amanda.clifford@ul.ie.
authors.forename: Amanda
authors.initials: A
authors.lastname: Clifford
authors.affiliation: University Medical Centre Utrecht, Utrecht, The Netherlands. Electronic address: n.a.guldemond@umcutrecht.nl.
authors.forename: Nick
authors.initials: N
authors.lastname: Guldemond
authors.affiliation: Klinik für Geriatrische Rehabilitation, Robert-Bosch-Krankenhaus, Stuttgart, Germany. Electronic address: klaus.pfeiffer@rbk.de.
authors.forename: Klaus
authors.initials: K
authors.lastname: Pfeiffer
authors.affiliation: School of Nursing, Midwifery and Social Work, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK; Manchester Academic Health Sciences Centre, Manchester, UK. Electronic address: alex.hall@manchester.ac.uk.
authors.forename: Alex
authors.initials: A
authors.lastname: Hall
authors.affiliation: Department of Computer Science and Engineering - DISI, University of Bologna, Bologna, Italy. Electronic address: federico.chesani@unibo.it.
authors.forename: Federico
authors.initials: F
authors.lastname: Chesani
authors.affiliation: Biomedical Engineering Unit, Department of Electrical, Electronic, and Information Engineering, University of Bologna, Bologna, Italy. Electronic address: sabato.mellone@unibo.it.
authors.forename: Sabato
authors.initials: S
authors.lastname: Mellone
authors.affiliation: Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway. Electronic address: alan.bourke@ntnu.no.
authors.forename: Alan
authors.initials: A
authors.lastname: Bourke
authors.affiliation: School of Nursing, Midwifery and Social Work, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK; Manchester Academic Health Sciences Centre, Manchester, UK. Electronic address: chris.todd@manchester.ac.uk.
authors.forename: Chris
authors.initials: C
authors.lastname: Todd
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control*; D003695:Delivery of Health Care; D005060:Europe; D006801:Humans; D020407:Internet; D008490:Medical Informatics / Q000592:standards*; D017216:Telemedicine; D009626:Terminology as Topic
keywords: Detection; Falls; ICT; Prediction; Prevention; Technology