Use of electronic medical records and biomarkers to manage risk and resource efficiencies

Dermot Ryan (Corresponding Author), John Blakey, Alison Chisholm, David Price, Mike Thomas, Björn Ställberg, Karin Lisspers, Janwillem W H Kocks, The Respiratory Effectiveness Group

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
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The migration from paper to electronic medical records (EMRs) was motivated by the administrative need to record, retrieve and process increasing amounts of clinical data in the 1980s. In the intervening period, there has been growing recognition of the potential of such records for achieving care efficiencies, informing clinical decision making and real-life research. EMRs can be used to characterise patient groups, management approaches and differential outcomes. Characterisation can also help with identification of potential biomarkers for future risk determination and likely treatment response. The future heralds even greater opportunities through integration of clinical records and a range of technology-based solutions within a more complete electronic health record (EHR). Through application of algorithms based on identified risk predictors and disease determinants, clinical records could also be used to enable risk stratification of patients to optimise targeted interventions, conserving resources to achieve individual patient and system-wide benefit. In this review, we reflect on the evolution of the EMR and EHR and discuss current and emerging opportunities, particularly with respect to biomarkers and targeting of innovative biologic interventions. We also consider some of the critical issues associated with realising the potential of the EHR as a clinical aid and research tool in an age of emerging technologies.​​​​
Original languageEnglish
Article number1293386
JournalEuropean Clinical Respiratory Journal
Issue number1
Early online date14 Mar 2017
Publication statusPublished - 2017


  • electronic medical record (EMR)
  • electronic health record (EHR)
  • database
  • asthma
  • biomarker
  • primary care
  • CDSS
  • big data


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