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Is a selective triage strategy more cost-effective than current practices for determining which injured patients should be transported by helicopter vs ground ambulance to a trauma center?
In a nationally representative cohort using cost-effectiveness modeling, current helicopter triage practices have an incremental cost-effectiveness ratio of $255 333 per quality-adjusted life-year compared with using the Air Medical Prehospital Triage score, which is significantly more than the generally accepted threshold of $100 000 per quality-adjusted life-year for cost-effective medical interventions.
Current helicopter triage practices are not cost-effective compared with the Air Medical Prehospital Triage score for determining helicopter vs ground transport for trauma patients.
Little evidence exists to guide helicopter emergency medical services (HEMS) triage, and current practice is inefficient. The Air Medical Prehospital Triage (AMPT) score was developed to identify patients most likely to benefit from HEMS compared with ground EMS. To our knowledge, no studies have evaluated the potential effect on costs and outcomes of a more targeted HEMS triage strategy, such as the AMPT score.
To evaluate the cost-effectiveness of current practice compared with the AMPT score for HEMS scene triage of trauma patients.
Design, Setting, and Participants
A cost-effectiveness Markov model was developed for the US health care system to compare current practice with the AMPT score as HEMS scene triage strategies from the health care system perspective over a patient lifetime horizon. A base case was estimated using national data of patient characteristics from the National Trauma Databank from 2007 to 2012. Model inputs, including demographic information, health care costs, survival, and utility estimates, were derived from literature and national registries. Triage strategies were modeled as probability of HEMS transport. Multilevel logistic regression was used to evaluate survival probability between HEMS and ground EMS under the triage strategies. Costs considered included transport reimbursements, hospitalization, cost of health care in the first year postinjury, and annual cost of health care after the first year postinjury. Several sensitivity analyses were performed to evaluate robustness of model assumptions.
Main Outcomes and Measures
Incremental cost-effectiveness ratio, with a threshold of $100 000 or less per quality-adjusted life-year defining cost-effectiveness.
The base case had an incremental cost-effectiveness ratio of $255 333 per quality-adjusted life-year for current practice compared with the AMPT score. Assuming 20% of patients have severe injuries and assuming HEMS only benefits these patients, current practice had an incremental cost-effectiveness ratio of $176 686 per quality-adjusted life-year. Probabilistic sensitivity analysis demonstrated that current practice is inferior in 85% of iterations, only becoming favored when the cost-effectiveness threshold is greater than $310 000 per quality-adjusted life-year.
Conclusions and Relevance
Current practice is not cost-effective compared with the AMPT score for HEMS scene triage. The AMPT score was the preferred strategy across a range of model input values in sensitivity analyses. The AMPT score identifies patients most likely to benefit from HEMS while potentially reducing costs to the health care system and should be considered in air medical transport protocols for trauma patients.
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Corresponding Author: Joshua B. Brown, MD, MSc, Division of General Surgery and Trauma, Department of Surgery, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213 (firstname.lastname@example.org).
Accepted for Publication: July 23, 2017.
Published Online: November 1, 2017. doi:10.1001/jamasurg.2017.4485
Author Contributions: Dr Brown had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Brown, Smith, Gestring, Rosengart, Sperry, Weissman.
Acquisition, analysis, or interpretation of data: Brown, Smith, Billiar, Peitzman.
Drafting of the manuscript: Brown, Rosengart.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Brown, Smith, Rosengart.
Administrative, technical, or material support: Brown, Peitzman, Sperry, Weissman.
Study supervision: Smith, Rosengart, Billiar, Sperry, Weissman.
Conflict of Interest Disclosures: None reported.
Funding/Support: Dr Brown receives support from an institutional T-32 Ruth L. Kischstein National Research Service Award training grant (5-T32-GM-008516-20) from the National Institutes of Health.
Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
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