Systematic review, meta-analysis and economic modelling of ...

DOI: 10.3310/hta17010 Health Technology Assessment 2013 Vol. 17 No. 1Chapter 4 Assessment of cost-effectivenessevidenceThis section details the methods and results of our health economic model, constructed to compareinvestigation strategies for patients with suspected ACS. We developed a decision-analysis model toevaluate the cost-effectiveness of using (1) early biomarker strategies to diagnose MI before a 10- to12-hour troponin assay and (2) biomarkers, CTCA or ETT to risk-stratify patients with a negative troponin.The model applied diagnostic strategies to a hypothetical cohort of patients with suspected ACS todetermine the costs and outcomes associated with each strategy. The model involved two phases:1. The diagnostic phase tested biomarker strategies for MI. Early biomarker strategies (involving troponinalone or in combination with sensitive early biomarkers) were compared with the most effective andexpensive strategy of 10- to 12-hour troponin assays (specified in our model as being 10 hours) andthe least effective and cheapest strategy of no testing or treatment. Early biomarkers were assumed toincur costs and miss cases due to suboptimal sensitivity compared with a 10-hour troponin test (thusworsening outcomes) but could save costs by reducing length of hospital stay.2. The prognostic phase tested biomarkers and other investigations (CTCA and exercise ECG) thatcould stratify patients with a negative troponin for subsequent risk of MACEs. The potentialbenefit of additional biomarkers, CTCA or exercise ECG was assumed to relate to identifying whichtroponin-negative patients have a higher risk of MACEs, which could be reduced by investigationand intervention.The diagnostic phase modelThis section details the methods and results of our health economic model constructed to comparediagnostic strategies for identifying MI in patients with suspected ACS. We developed a decisionanalysismodel to estimate the costs and QALYs accrued by each potential management strategy fordiagnosing patients with MI. A theoretical ‘zero option’ strategy of discharging all patients home withoutinvestigation was also included. The key aim was to determine the optimal diagnostic strategy in terms ofcost-effectiveness. We also aimed to use the model to estimate the effect of different diagnostic strategiesupon subsequent event rates.ObjectivesThe objectives of the cost-effectiveness analysis were to:1. estimate the cost-effectiveness of diagnostic strategies for ACS, in terms of the cost per QALY gainedby each strategy compared with the next most effective2. identify the optimal strategy for diagnosing ACS in the NHS, defined as the most cost-effectivestrategy at a willingness-to-pay threshold of £20,000–30,000 per QALY gained3. estimate subsequent rates of death and non-fatal MI among the whole study population and amongthose with negative diagnostic tests according to the various diagnostic strategies4. identify the critical areas of uncertainty in the diagnosis of ACS, where future research would producethe most benefit.The costs and benefits of diagnostic management of suspected acutecoronary syndromeThe main benefits of diagnostic management relate to rapid identification and treatment of patientswith risk of MI and death. The direct costs of diagnostic management include the costs of investigation,hospital stay for diagnosis, and the subsequent costs of providing treatment, intensive care and© Queen’s Printer and Controller of HMSO 2013. This work was produced by Goodacre et al. under the terms of a commissioning contract issued by the Secretary of Statefor Health. This issue may be freely reproduced for the purposes of private research and study and extracts (or indeed, the full report) may be included in professional journalsprovided that suitable acknowledgement is made and the reproduction is not associated with any form of advertising. Applications for commercial reproduction should beaddressed to: NIHR Journals Library, National Institute for Health Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton SciencePark, Southampton SO16 7NS, UK.81