Quantitative metrics for evaluating the phased roll-out of clinical information systems

Int J Med Inform. 2017 Sep:105:130-135. doi: 10.1016/j.ijmedinf.2017.06.007. Epub 2017 Jun 28.


Objectives: We introduce a novel quantitative approach for evaluating the order of roll-out during phased introduction of clinical information systems. Such roll-outs are associated with unavoidable risk due to patients transferring between clinical areas using both the old and new systems.

Methods: We proposed a simple graphical model of patient flow through a hospital. Using a simple instance of the model, we showed how a roll-out order can be generated by minimising the flow of patients from the new system to the old system.

Results: The model was applied to admission and discharge data acquired from 37,080 patient journeys at the Churchill Hospital, Oxford between April 2013 and April 2014. The resulting order was evaluated empirically and produced acceptable orders.

Discussion: The development of data-driven approaches to clinical Information system roll-out provides insights that may not necessarily be ascertained through clinical judgment alone. Such methods could make a significant contribution to the smooth running of an organisation during the roll-out of a potentially disruptive technology.

Conclusion: Unlike previous approaches, which are based on clinical opinion, the approach described here quantitatively assesses the appropriateness of competing roll-out strategies. The data-driven approach was shown to produce strategies that matched clinical intuition and provides a flexible framework that may be used to plan and monitor Clinical Information System roll-out.

Keywords: Algorithms; Clinical information systems; Implementation; Information systems.

Publication types

  • Evaluation Study

MeSH terms

  • Algorithms*
  • Continuity of Patient Care / standards*
  • Delivery of Health Care, Integrated*
  • Humans
  • Information Dissemination*
  • Management Information Systems / standards*
  • Monitoring, Physiologic
  • Patient Discharge*