Automated audit of hospital oxygen use devised during the COVID-19 pandemic - Ronan O'Driscoll (BMJ Open Respiratory Research, 2023)
Background The British Thoracic Society (BTS) has organised intermittent audits of hospital oxygen use in UK hospitals since 2008. Manual audits are time-consuming and subject to human errors. Oxygen prescribing and bedside observations including National Early Warning Scores (NEWS2 scores) are undertaken within an integrated electronic medical record (EMR) at this hospital.Methods The hospital’s Business Information team were commissioned in late 2019 to devise a bespoke automated audit of oxygen prescribing and use. A summary report displays the oxygen saturation alongside the oxygen prescription status of every patient in the hospital except for critical care units which do not use NEWS2. The display has a ‘traffic-light’ colour scheme (green within target range, amber or red if below range or if above range on supplemental oxygen), with a graph showing oxygen use and saturation levels for patients with each prescribed target range. Clinicians can access raw data including oxygen saturation, oxygen device and flow rate for each individual patient.Results Over 51 audits involving 34 352 sets of observations, an average of 6.0% involved use of oxygen and 88.6% of these had a valid oxygen prescription. During the first wave of the COVID-19 pandemic in spring 2020, the monthly percentage of observations involving oxygen use increased to a peak of 10.4% followed by a rise to 10.6% during the second wave and 7.4% during the third (Omicron) wave. Oxygen use returned to baseline after each wave.Conclusions In hospitals with integrated EMRs, it is possible to automate all fundamental aspects of the BTS oxygen audits and to monitor oxygen use at individual patient level and a hospital-wide level. This could be particularly valuable during major events such as the COVID-19 pandemic. This methodology could be extended to other clinical audits where the audit questions relate to routinely collected EMR data.