SMART on FHIR in spine: integrating clinical prediction models into electronic health records for precision medicine at the point of care

Spine J. 2021 Oct;21(10):1649-1651. doi: 10.1016/j.spinee.2020.06.014. Epub 2020 Jun 26.


Recent applications of artificial intelligence have shown great promise for improving the quality and efficiency of clinical care. Numerous clinical decision support tools exist in today's electronic health records (EHRs) such as medication dosing support, order facilitators (eg, procedure specific order sets), and point of care alerts. However, less has been done to integrate artificial intelligence (AI)-enabled risk predictors into EHRs despite wide availability of validated risk prediction tools. An interoperability standard known as SMART on FHIR (substitutable medical applications and reusable technologies on fast health interoperability resources) offers a promising path forward, enabling digital innovations to be seamlessly integrated with the EHR with regard to the user interface and patient data. For the next step in progress towards the goal of learning healthcare and informatics-enabled spine surgery, we propose the application of SMART on FHIR to integrate existing and new risk predictions tools in spine surgery through an EHR add-on-application.

Keywords: Artificial intelligence; Clinical decision support; Diagnosis; Electronic medical records; Integration; Machine learning; Natural language processing; Prediction; SMART on FHIR; Spine.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Artificial Intelligence
  • Electronic Health Records*
  • Humans
  • Models, Statistical
  • Point-of-Care Systems
  • Precision Medicine*
  • Prognosis
  • Software