Cost-effectiveness of advanced life support and prehospital critical care for out-of-hospital cardiac arrest in England: a decision analysis model

Abstract

Objectives: This research aimed to answer the following questions: What are the costs of prehospital advanced life support (ALS) and prehospital critical care for out-of-hospital cardiac arrest (OHCA)? What is the cost-effectiveness of prehospital ALS? What improvement in survival rates from OHCA would prehospital critical care need to achieve in order to be cost-effective?

Setting: A single National Health Service ambulance service and a charity-funded prehospital critical care service in England.

Participants: The patient population is adult, non-traumatic OHCA.

Methods: We combined data from previously published research with data provided by a regional ambulance service and air ambulance charity to create a decision tree model, coupled with a Markov model, of costs and outcomes following OHCA. We compared no treatment for OHCA to the current standard of care of prehospital ALS, and prehospital ALS to prehospital critical care. To reflect the uncertainty in the underlying data, we used probabilistic and two-way sensitivity analyses.

Results: Costs of prehospital ALS and prehospital critical care were £347 and £1711 per patient, respectively. When costs and outcomes of prehospital, in-hospital and postdischarge phase of OHCA care were combined, prehospital ALS was estimated to be cost-effective at £11 407/quality-adjusted life year. In order to be cost-effective in addition to ALS, prehospital critical care for OHCA would need to achieve a minimally economically important difference (MEID) in survival to hospital discharge of 3%-5%.

Conclusion: This is the first economic analysis to address the question of cost-effectiveness of prehospital critical care following OHCA. While costs of either prehospital ALS and/or critical care per patient with OHCA are relatively low, significant costs are incurred during hospital treatment and after discharge in patients who survive. Knowledge of the MEID for prehospital critical care can guide future research in this field.

Trial registration number: ISRCTN18375201.

Keywords: accident & emergency medicine; adult intensive & critical care; cardiology.

Figure 1

Final analytic model of prehospital critical care following out-of-hospital cardiac arrest, combining decision tree and Markov model. Due to limited space, the full pathway is shown for the ALS option only. ALS, advanced life support; CPC, Cerebral Performance Category; ICU, intensive care unit.

Figure 2

Scatter plot of the cost-effectiveness of advanced life support for out-of-hospital cardiac arrest, compared with no treatment. QALY, quality-adjusted life year.

Figure 3

Cost-effectiveness acceptability curves of different plausible treatment effects of prehospital critical care for out-of-hospital cardiac arrest, when compared with ALS. The underlying baseline survival to hospital discharge for the ALS cohort in this model is 9.0%. ALS, advanced life support; QALY, quality-adjusted life year.