Worldwide, the World Health Organization estimates the cost associated with medication errors to be $42 billion USD and in Australia the cost to the health system is estimated at $1.4 billion AUD annually. Electronic medication management systems (eMM, also known as e-prescribing or Computerised Provider Order Entry [CPOE]) have been increasingly deployed into adult hospitals around the world with a demonstrated decrease in medication errors.1 While deployment into paediatric hospitals has been less widespread, Australia’s largest children’s hospital network introduced a new eMM in 2016. We worked with the project steering committee to answer the question, does the introduction of eMM reduce medication errors and harm for children in hospital?
During this research, 35,260 medication orders for 4,821 paediatric inpatients were reviewed. We engaged pharmacists, data analysts, biostatisticians, health services researchers, clinicians and hospital managers in the process, recognising the complex nature of prescribing for children. Just as adult eMM should not be used in a paediatric setting without specific modifications, adult eMM performance cannot be extrapolated to a paediatric population. Weight, age, dosing ranges and off-label use of medicines complicate data collection and analysis and need to be taken into consideration.
An added challenge was the eMM was introduced across the hospital, not just in specific wards - thereby bringing into play the enormous variation between wards due to the nature of the conditions and patients being treated and making it more complicated to compare performance. We therefore conducted a stepped-wedge cluster randomised controlled trial, with a one-year post-eMM follow-up to assess the short- and long-term effectiveness of the eMM to reduce prescribing errors. We also conducted interviews with clinicians to understand and record their experience of using the new system.2
Crucially, this project was never going to be about waiting until the end of a five-year timeframe to report results. Close collaboration and dynamic feedback loops were critical from the start. Working closely with healthcare professionals within the hospital and observing many going about their regular routines, we were not only collecting data to evaluate the impact of the new eMM but were also able to identify practical areas where the eMM and traditional clinical practices could be immediately improved.
We fed back results and observations to the project steering committee and saw improvements and modifications made in real time to systems and practices that directly impacted patient safety.
We found that despite high levels of training and real-time support during implementation, prescribing errors did not change in the short term and some error rates increased during the first 70 days of use. The introductory phases of a new eMM were disruptive to many work processes. Use of the system in real-time on busy hospital wards is hard to replicate in training scenarios, meaning that many clinicians struggled with the system in the early stages. Our findings highlight the need for vigilance during the first months of eMM use.
However, benefits accrued in the long-term. We found that a year after the eMM was introduced, there was a significant reduction in overall prescribing error rates of 36%. For high-risk drugs, there was a 33% decrease in prescribing error rates.
Regardless of whether paper or eMM was used, the most common type of error were dose errors where the child either gets too much of a medication or not enough. These types of errors were also most likely to be associated with harm to children. The eMM saw a reduction in dose errors but they remained frequent. Improving the design of eMM to specifically target dose errors is important.
While observing 300 nurses administering over 5000 medications to children, we also discovered that the traditional safety practice of nurses double-checking the administration of medication was not as effective in reducing errors as previously thought.3 Double-checking requires two nurses to independently check the patient and dose details. We found this process as performed accounts for an estimated 107 hours (for the second nurse) per 1000 administrations or on average 6 minutes per dose with no reduction in error rates. Further investigation of double-checking has the potential to understand why and when double-checking may be most effective.
While it was positive news ultimately, that the introduction of an eMM into a paediatric setting significantly reduced prescribing errors, the research also highlights prescribing errors as a continuing area of concern, particularly dose errors. New technology-related errors can also be introduced.
We have produced a plain-language bulletin, the Health Innovation Series, that provides practical steps to optimise eMM systems, as well as tips for users, to make eMM systems safer. 4-10
A national Medication Safety Symposium in 2022 brought together clinicians, researchers, policy-makers and consumers to discuss these research findings and the implications. Recordings are available online.11
Coming soon, and the first of its kind, will be a four-year post analysis of this eMM in the paediatric hospital network. Stay tuned.
1 Gates, P. J., Hardie, R.-A., Raban, M. Z., Li, L. & Westbrook, J. I. How effective are electronic medication systems in reducing medication error rates and associated harm among hospital inpatients? A systematic review and meta-analysis. J Am Med Inform Assoc 28, 167-176, doi:10.1093/jamia/ocaa230 %J Journal of the American Medical Informatics Association (2020).
2 Baysari, M. T. et al. Longitudinal study of user experiences of a CPOE system in a pediatric hospital. Int J Med Inform 109, 5-14, doi:https://doi.org/10.1016/j.ijmedinf.2017.10.018 (2018).
3 Westbrook, J. I. et al. Associations between double-checking and medication administration errors: a direct observational study of paediatric inpatients. BMJ Qual Saf, bmjqs-2020-011473, doi:http://dx.doi.org/10.1136/bmjqs-2020-011473 (2020).
4 Merchant A, Fitzpatrick E, Westbrook JI & Raban MZ. Accidental prescribing of extended-release opioids. Health Innovation Series (2022). doi:https://doi.org/10.25949/5ka7-ab42.
5 Merchant A, Raban MZ & Westbrook JI. Caution: editing within a dose calculator can result in large dose errors. Health Innovation Series (2022). doi:https://doi.org/10.25949/MWNH-P929.
6 Merchant A, Raban MZ, Fitzpatrick E & Westbrook JI. Dose calculator: Missing in action! . Health Innovation Series (2022). doi:https://doi.org/10.25949/w6vs-dd62.
7 Merchant A, Fitzpatrick E, Westbrook JI & Raban MZ. Double dose trouble: systemic intranasal medication: Can you spot the problem? . Health Innovation Series (2022). doi: https://doi.org/10.25949/PRND-F975.
8 Raban MZ, Merchant A & Westbrook JI. Pre-operative medication frequencies matter. Health Innovation Series (2022). doi:https://doi.org/10.25949/7yc3-a257.
9 Raban MZ, Merchant A & Westbrook JI. Prescribing an IV in an electronic medication system: What could possibly go wrong? Health Innovation Series (2022). doi:https://doi.org/10.25949/N04Z-4Y85.
10 Raban MZ, Merchant A, Fitzpatrick E & Westbrook JI. Preventing dangerous intraspinal injections. Health Innovation Series (2022). doi:https://doi.org/10.25949/dy3f-pa76.
11 Australian Institute of Health Innovation.https://www.youtube.com/playlist?list=PLsxNm03dgU1pel88izCNo1h6JhJcR_oLN
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