title: Using electronic health records to predict costs and outcomes in stable coronary artery disease.
abstract: To use electronic health records (EHR) to predict lifetime costs and health outcomes of patients with stable coronary artery disease (stable-CAD) stratified by their risk of future cardiovascular events, and to evaluate the cost-effectiveness of treatments targeted at these populations.
  
  
  
  The analysis was based on 94 966 patients with stable-CAD in England between 2001 and 2010, identified in four prospectively collected, linked EHR sources. Markov modelling was used to estimate lifetime costs and quality-adjusted life years (QALYs) stratified by baseline cardiovascular risk.
  
  
  
  For the lowest risk tenth of patients with stable-CAD, predicted discounted remaining lifetime healthcare costs and QALYs were £62 210 (95% CI £33 724 to £90 043) and 12.0 (95% CI 11.5 to 12.5) years, respectively. For the highest risk tenth of the population, the equivalent costs and QALYs were £35 549 (95% CI £31 679 to £39 615) and 2.9 (95% CI 2.6 to 3.1) years, respectively. A new treatment with a hazard reduction of 20% for myocardial infarction, stroke and cardiovascular disease death and no side-effects would be cost-effective if priced below £72 per year for the lowest risk patients and £646 per year for the highest risk patients.
  
  
  
  Existing EHRs may be used to estimate lifetime healthcare costs and outcomes of patients with stable-CAD. The stable-CAD model developed in this study lends itself to informing decisions about commissioning, pricing and reimbursement. At current prices, to be cost-effective some established as well as future stable-CAD treatments may require stratification by patient risk.
authors: Centre for Health Economics, University of York, York, UK.
authors: Miqdad
authors: M
authors: Asaria
authors: Centre for Health Economics, University of York, York, UK.
authors: Simon
authors: S
authors: Walker
authors: Centre for Health Economics, University of York, York, UK.
authors: Stephen
authors: S
authors: Palmer
authors: Faculty of Medicine and Health, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
authors: Chris P
authors: CP
authors: Gale
authors: Farr Institute of Health Informatics Research, UCL Institute of Health Informatics, University College, London, UK.
authors: Anoop D
authors: AD
authors: Shah
authors: Department of Health Sciences, University of Leicester, Leicester, UK.
authors: Keith R
authors: KR
authors: Abrams
authors: Department of Health Sciences, University of Leicester, Leicester, UK.
authors: Michael
authors: M
authors: Crowther
authors: Centre for Health Economics, University of York, York, UK.
authors: Andrea
authors: A
authors: Manca
authors: NIHR Biomedical Research Unit, Barts and the London NHS Trust, London, UK.
authors: Adam
authors: A
authors: Timmis
authors: Farr Institute of Health Informatics Research, UCL Institute of Health Informatics, University College, London, UK.
authors: Harry
authors: H
authors: Hemingway
authors: Centre for Health Economics, University of York, York, UK.
authors: Mark
authors: M
authors: Sculpher
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003324:Coronary Artery Disease / Q000175:diagnosis / Q000191:economics* / Q000401:mortality / Q000628:therapy*; D003362:Cost-Benefit Analysis; D057225:Data Mining; D016208:Databases, Factual; D003661:Decision Support Techniques; D018450:Disease Progression; D057286:Electronic Health Records / Q000191:economics*; D004739:England; D005260:Female; D017048:Health Care Costs; D006801:Humans; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D018803:Models, Economic; D017064:Process Assessment, Health Care / Q000191:economics*; D019057:Quality-Adjusted Life Years; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome