Designing a continuous data-driven feedback and learning initiative to improve electronic prescribing: an interdisciplinary quality improvement study

Abstract

Abstract Introduction The WHO Global Patient Safety Challenge aims to reduce severe avoidable medication-related harm by 50% by 2023[1]. Research suggests that providing timely, trusted feedback that incorporates relevant action can improve practice. However, a key barrier is lack of prescribing error data. Hospital electronic prescribing (EP) data may help address this gap. Aims To explore approaches for continuously monitoring medication safety signals using existing or new EP data, and to deliver personalised prescribing feedback and learning to improve patient safety. Methods We conducted a feasibility study (November 2019 - February 2020) on a 28-bed adult gastroenterology. This ward was chosen because of a high prescribing error rate. All foundation year 1 and 2 doctors, and pharmacists on the ward, participated in the study. The study team comprised pharmacists, doctors, quality improvement experts and clinical analysts, and used a quality improvement approach to design and test (i) methods for extracting electronic data to calculate prescribing accuracy rates, (ii) ways to refine a paper-prototype of an electronic pharmacists’ interventions form, (iii) potential digital medication safety indicators, and (iv) approaches for feedback for doctors to augment existing verbal feedback from pharmacists. Data were documented in accordance with local information governance and analysed using Excel. Acceptability and usability was assessed through verbal feedback from participants during weekly huddles. Outcome measures: feasibility of using EP to determine prescribing accuracy, user acceptability and usability of data collection, feedback and learning by pharmacists and doctors. We also measured changes in prescribing accuracy rate, pharmacists’ interventions, and quality of prescribing for targeted problematic medications. Results Extracting EP data required multiple data linkages to be configured and validated, and not all required data were available. Potential digital medication safety indicators: utility of the reason code ‘prescribed in error’ and actions by pharmacists to modify medications were limited by underuse and lack of data granularity. After testing different ways to extract relevant EP data, we eventually used a combination of EP and manual retrospective review of electronic patient records to determine prescribing accuracy rates. An intervention form was redesigned to tally interventions and capture details for contextual learning for email feedback to doctors and weekly prescribing improvement huddles. Doctors reported emails as timely and helpful for gaining new prescribing- and system-related knowledge. Pharmacists reported intervention data as providing invaluable evidence to drive improvement. Statistical process control charts showed no special cause variation around a mean prescription accuracy rate of 98% for inpatient orders, and 87% for discharge orders. By contrast, pharmacists recorded a mean of 10 interventions/day with 7 special cause variation (above upper control limit of 19) in the first two months. Omission of venous thromboembolism prophylaxis was identified as a priority medication issue. Specific prescriber- and system-based improvements were suggested (Jan 2020), some implemented (Feb 2020) and others fed back to the thrombosis committee (Feb 2020). Conclusion Harnessing the potential of EP data to improve medication safety requires the workforce to have a deeper understanding of the EP data structure and processes. Using a quality improvement approach, we developed a feedback and learning model that is acceptable and useful to pharmacists and doctors. Further research should explore adapting the approach to other clinical areas. Reference 1. Sheikh, A., Dhingra-Kumar, N., Kelley, E., Kieny, M. and Donaldson, L. The Third Global Patient Safety Challenge: Tackling Medication-Related Harm. Bulletin of the World Health Organization. World Health Organisation. 2017;95:546-546A.