title: Past speculations of the future: a review of the methods used for forecasting emerging health technologies.
abstract: OBJECTIVE
  Forecasting can support rational decision-making around the introduction and use of emerging health technologies and prevent investment in technologies that have limited long-term potential. However, forecasting methods need to be credible. We performed a systematic search to identify the methods used in forecasting studies to predict future health technologies within a 3-20-year timeframe. Identification and retrospective assessment of such methods potentially offer a route to more reliable prediction.
  
  
  METHODS
  Systematic search of the literature to identify studies reported on methods of forecasting in healthcare.
  
  
  METHODS
  People are not needed in this study.
  
  
  METHODS
  The authors searched MEDLINE, EMBASE, PsychINFO and grey literature sources, and included articles published in English that reported their methods and a list of identified technologies.
  
  
  METHODS
  Studies reporting methods used to predict future health technologies within a 3-20-year timeframe with an identified list of individual healthcare technologies. Commercially sponsored reviews, long-term futurology studies (with over 20-year timeframes) and speculative editorials were excluded.
  
  
  RESULTS
  15 studies met our inclusion criteria. Our results showed that the majority of studies (13/15) consulted experts either alone or in combination with other methods such as literature searching. Only 2 studies used more complex forecasting tools such as scenario building.
  
  
  CONCLUSIONS
  The methodological fundamentals of formal 3-20-year prediction are consistent but vary in details. Further research needs to be conducted to ascertain if the predictions made were accurate and whether accuracy varies by the methods used or by the types of technologies identified.
authors.affiliation: NIHR Horizon Scanning Research and Intelligence Centre, Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
authors.forename: Lucy
authors.initials: L
authors.lastname: Doos
authors.affiliation: NIHR Horizon Scanning Research and Intelligence Centre, Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
authors.forename: Claire
authors.initials: C
authors.lastname: Packer
authors.affiliation: NIHR Horizon Scanning Research and Intelligence Centre, Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
authors.forename: Derek
authors.initials: D
authors.lastname: Ward
authors.affiliation: NIHR Horizon Scanning Research and Intelligence Centre, Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
authors.forename: Sue
authors.initials: S
authors.lastname: Simpson
authors.affiliation: Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
authors.forename: Andrew
authors.initials: A
authors.lastname: Stevens
mesh_terms: D003657:Decision Making; D003695:Delivery of Health Care / Q000639:trends*; D005544:Forecasting / Q000379:methods*; D006801:Humans; D013673:Technology Assessment, Biomedical / Q000639:trends*
keywords: Forecasting; Systematic review; health technology; innovations; methods