1. Electronic Prescribing & Clinical Decision Support Sarah Pontefract
University of Birmingham

2. Background From this… To this!
ePrescribing is the “utilisation of electronic systems to facilitate and enhance the communication of a prescription or medicine order, aiding the choice, administration and supply of a medicine through knowledge and decision support and providing a robust audit trail for the entire medicines use process” [NHS Connecting for Health, 2009].
Clinical decision support software is designed to facilitate clinical decision-making at the point of care through the connection of patient information, a pre-configured knowledge base, and occasionally the demographics of the user.
ePrescribing and decision support can:
Reduce the rate of prescribing errors in our hospitals
Facilitate the optimisation of treatment to improve patient outcomes
Hence, there is a drive for all hospitals to be paperless by 2023 [NHS England, 2014].
BUT, the technology can also have some unintended consequences on our healthcare processes, with the potential to impact on the safety of our patients.

3. Clinical Pharmacologists and ePrescribing
Investigate the impact of systems on patient safety.
Work locally with ePrescribing teams to optimise systems to minimise patient harm and improve outcomes.
Work with NHS organisations to investigate the impact of new systems on the rate and severity of medication errors.
Work with NHS England and NHS Digital to drive evidence-based implementation of systems across healthcare settings.

4. Medication errors
Medication errors are common and a major source of preventable harm.
Processing a prescription drug order through eP decreases the likelihood of error by 48% (95% CI 41–55%).[1]
ePrescribing is associated with half as many medication errors (RR 0.46) compared to paper. [2]
Clinical Decision Support can reduce the likelihood of high-risk errors, highly dependent on the format and level of alerts / warnings presented.

5. Workflow and communication
ePrescribing systems can:
Facilitate a non-interruptive workflow, with fewer distractions for clinical staff reducing the risk of procedural errors.
Improve access to information to facilitate clinical decision-making (e.g. clinical guidelines, patient-specific information).
Improve accountability through complete, accurate documentation.
Improve communication at transitions of care.

6. Big data
Big data refers to the Volume, Velocity, Variety, and Veracity of data.
Just over 1.1 billion prescription items were dispensed in the community setting in 2016.
An estimated 500,000 prescriptions are generated in English NHS Hospitals on a daily basis.
Data from ePrescribing systems can be captured and used for:
Quality improvement
Audit and research
Monitoring (and feedback)
Education, training and knowledge dissemination

7. Big data Investigating omitted doses
We captured data from the audit database of the ePrescribing system.
6.28 million doses charted in 2010
275,632 diet products removed
6.01 million medication doses due
Randomly selected
weeks 9, 22, 27, 42
491,894 medication doses due over 4 weeks
60,763 doses not administered
42,277 omissions with coded reasons (~70%)

8. Big data Investigating omitted doses[4]
We performed a regression analysis to identify the impact of interventions on the percentage of doses omitted over time.

9. Unintended consequences of the technology

10. Unintended consequences
Some noted unintended consequences associated with implementation of eP and decision support [8]
Workflow Changes
New Safety Hazards
New work demands for healthcare staff
System design problems
Overdependence on technology
Alert fatigue
Changes in communication patterns between staff
Workarounds to avoid perceived or actual problems with systems
Shift of data entry from administration staff to clinicians
Continued warnings mean clinicians override high-severity alerts
Workstation availability can impair clinician efficiency
Development of alternate computer or paper-based workflows
Limitation to obtain medications in an emergency
Problems relating to transitioning between different systems

11. New error types[5] Errors of selection
When a wrong selection is made in a pre-populated lists
Default (auto-populated) errors:
When the wrong prescription is generated owing to the acceptance of a pre-populated (suggested)order.
Default settings
Such as the times of day available for prescribing a dose to be administered.
Repeat prescriptions
Out of date prescriptions are dispensed, not accounting for updates to the patients medication regimen
Clinical decision support
Over-alerting staff, or alerting staff at the wrong time in their workflow can lead to “alert fatigue”, where the information is ignored or overlooked.

12. Interprofessional Communication
Poor or ineffective communication remains one of the leading contributing factors of adverse events in healthcare.
Over dependence on the computer to communicate with healthcare staff can increase the “noise” in the process, which can impact on the effectiveness of the communication.
via the computer
Fig: Process of communication

13. Conclusions
ePrescribing can reduce the likelihood of medication errors occurring.
The use of electronic systems can promote accurate and complete documentation of patient information, which can facilitate workflow and communication.
The data generated from systems can be used to monitor safety and inform quality improvement processes.
The implementation of new technology can have some unintended consequences, which must be monitored and adjusted for to reduce impact on patient safety and quality of care.
The ePrescribing toolkit is available to all NHS practitioners to support hospitals in the planning, implementation and use of systems. It can be accessed at

14. References
NHS England. Personalised Health and Care 2020: Using Data and Technology to Transform Outcomes for Patients and Citizens. A framework for action. London; 2014.
Radley DC, Wasserman MR, Olsho LEW, Shoemaker SJ, Spranca MD, Bradshaw B. Reduction in medication errors in hospitals due to adoption of computerized provider order entry systems. Journal of the American Medical Informatics Association. 2013;2013:470-6.
Nuckols TK, Smith-Spangler C, Morton SC, Asch SM, Patel VM, Anderson LJ, et al. The effectiveness of computerized order entry at reducing preventable adverse drug events and medication errors in hospital settings: a systematic review and meta-analysis. Systematic Reviews. 2014;3:56-.
Coleman JJ et al. Missed medication doses in hospitalised patients: a descriptive account of quality improvement measures and time series analysis. Int J Qual Health Care Oct;25(5):
Brown CL, et al. A systematic review of the types and causes of prescribing errors generated from using computerized provider order entry systems in primary and secondary care. Journal of the American Medical Informatics Association. 2017;24(2):

15. I am a clinical pharmacologist
Clinical Pharmacology and Therapeutics (CPT) is one of 30 physician specialties in the medical career pathway.
Consultants trained in this specialty lead on all aspects of medicines management.
It is the only medical specialty in the NHS focusing on the safe, effective, and cost- effective use of medicines.
Clinical pharmacologists play a crucial role in refining the use of currently available medicines, and in developing the pioneering medicines of tomorrow.
Clinical pharmacologists have diverse career paths working, for example, in the NHS, regulatory bodies, clinical trials units, universities or the pharmaceutical industry.