Using ‘nudge’ principles for order set design: a before and after evaluation of an electronic prescribing template in critical care
- Correspondence to Dr Christopher P Bourdeaux, Intensive Care Unit, Queens Building, University Hospitals Bristol, Bristol Royal Infirmary, Upper Maudlin Street, Bristol BS2 8HW, UK;
- Received 8 August 2013
- Revised 21 October 2013
- Accepted 27 October 2013
- Published Online First 26 November 2013
Objective Computerised order sets have the potential to reduce clinical variation and improve patient safety but the effect is variable. We sought to evaluate the impact of changes to the design of an order set on the delivery of chlorhexidine mouthwash and hydroxyethyl starch (HES) to patients in the intensive care unit.
Methods The study was conducted at University Hospitals Bristol NHS Foundation Trust, UK. Our intensive care unit uses a clinical information system (CIS). All drugs and fluids are prescribed with the CIS and drug and fluid charts are stored within a database. Chlorhexidine mouthwash was added as a default prescription to the prescribing template in January 2010. HES was removed from the prescribing template in April 2009. Both interventions were available to prescribe manually throughout the study period. We conducted a database review of all patients eligible for each intervention before and after changes to the configuration of choices within the prescribing system.
Results 2231 ventilated patients were identified as appropriate for treatment with chlorhexidine, 591 before the intervention and 1640 after. 55.3% were prescribed chlorhexidine before the change and 90.4% after (p<0.001). 6199 patients were considered in the HES intervention, 2177 before the intervention and 4022 after. The mean volume of HES infused per patient fell from 630 mL to 20 mL after the change (p<0.001) and the percentage of patients receiving HES fell from 54.1% to 3.1% (p<0.001). These results were well sustained with time.
Conclusions The presentation of choices within an electronic prescribing system influenced the delivery of evidence-based interventions in a predictable way and the effect was well sustained. This approach has the potential to enhance the effectiveness of computerised order sets.