P67 Electronic prescribing alerts significantly increase oxygen prescribing

Abstract

Introduction In 2011, the number of patients using oxygen without a prescription within a teaching hospital in the West Midlands was higher than the national average (local 11.3% vs national 7.1%). Following this, an electronic alert was incorporated into a bespoke prescribing system to remind doctors to prescribe oxygen. This alert was triggered whenever the oxygen saturations of a patient were recorded on supplemental oxygen without an oxygen prescription. Method Data was collected using the standard BTS oxygen prescribing audit proforma in October 2011 and October 2012. In 2012, 215 patients from six medical and respiratory wards were included; 40 were on supplemental oxygen. We used Fisher exact test to analyse our data. Results The number of patients using oxygen with a valid prescription increased significantly from 42.9% in 2011 to 72.5% in 2012 (p = 0.023). The national average for oxygen prescriptions in 2012 was 52.3%. Oxygen is being signed for on drug round s more often, 64.1% of the time compared with 13.5% the previous year. Despite the number of oxygen prescriptions increasing significantly, the proportion of patients with saturations in their target range actually decreased. Conclusions The number of oxygen prescriptions have increased significantly with the introduction of an electronic alert system. Potential development s for the future would include an automatic prescription with ‘opt out’ facility and an alert for nursing staff when oxygen saturations are out of range to allow better titration of oxygen. This study shows that use of information technology and prescribing alerts and reminders can have a significant effect on number of prescriptions. What remains to be seen is if this will have an effect on patient outcomes. References O9Driscoll BR et al . BTS guideline for emergency oxygen use in adult patients., Thorax . 2008 Oct;63 Suppl 6:vi1–68 O9Driscoll BR Emergency oxygen use. 2012 BMJ ;345:e6856. Brent Mollon et al. Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials. BMC Medical Informatics and Decision Making 2009, 9 :11