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EP.002
Successful utilisation of a computer-based prompt to reduce the incidence of hyperoxaemia within a university hospital general critical care unit

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Successful utilisation of a computer-based prompt to reduce the incidence of hyperoxaemia within a university hospital general critical care unit

 

Introduction

The deleterious effects of oxygen toxicity have been well known for over a century1. However, it is only in recent years that there has been a shift toward using oxygen conservatively in healthcare due to emerging evidence associating its excess with harm.

 

We previously described a high incidence of excess oxygen therapy within our general critical care unit (GCCU) 2. We aimed to reduce this.

 

Method

Arterial blood gas (ABG) data is routinely collated using bedside software on GCCU. At the end of 2016 we implemented an alert highlighting PaO2 ≥13.3 kPa as abnormal and educated staff about potential harms from excess oxygen. Twelve months following intervention, we retrospectively reviewed 18,530 ABG samples from 679 admissions from the 6-month period prior (July-December 2017).

 

Mean PaO2 has been shown to be a useful metric for predicting poor outcomes associated with hyperoxaemia3. Mean PaO2 from the duration of each admission was calculated, and this was used to categorise admissions into three groups: hyperoxaemia, normoxaemia, and hypoxaemia. Hyperoxaemia was defined as PaO2 ≥13.3 kPa. Normoxaemia was defined as neither hyperoxaemia nor hypoxaemia (PaO2 <8 kPa).

 

Comparisons between rounds were made by Chi-squared testing.

 

Results

In our first audit we retrospectively reviewed data from two years of admissions (2012-2013) (n=2,916), almost half were in the hyperoxaemia group (48.35%, n=1,411)1. A target PaO2 was added to bedside documentation but this intervention had no significant effect when re-audited (50.46% in hyperoxaemia group, March-June 2016; 1,183 admissions; χ2=0.038, df=1, p= 0.8461).

 

After introduction of the computer-based alert there was a significant reduction of admissions in the hyperoxaemia group (32.84%; n=151; χ2=152.971, df=1, p< 0.0001) and almost two-thirds of admissions were in the normoxaemia group (65.98%; n=519).

 

Conclusion

A simple computer-based alert highlighting abnormally high PaO2 values to nursing staff during routine practice has enabled us to significantly reduce the incidence of sustained exposure to excess oxygen to patients within our general critical care unit.

 

 

  1. Smith JL. (1899) The pathological effects due to increase of oxygen tension in the air breathed. The Journal of Physiology. 24:19–35
  2. Shuker BA, Bassford CR (2015) “An audit of clinical practice: oxygenation of critically ill patients in a university hospital general critical care unit” in Clinical free paper presentations. Journal of the Intensive Care Society. 1 Suppl. Page 23.
  3. Helmerhorst HJ et al. (2017) Metrics of Arterial Hyperoxia and Associated Outcomes in Critical Care. Crit Care Med. 45(2):187-195.
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