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Using electronic health records to predict costs and outcomes in stable coronary artery disease

Author

Listed:
  • Asaria, Miqdad
  • Walker, Simon
  • Palmer, Stephen
  • Gale, Chris P
  • Shah, Anoop D
  • Abrams, Keith R
  • Crowther, Michael
  • Manca, Andrea
  • Timmis, Adam
  • Hemingway, Harry
  • Sculpher, Mark

Abstract

Objectives 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. Methods 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. Results 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. Conclusions 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.

Suggested Citation

  • Asaria, Miqdad & Walker, Simon & Palmer, Stephen & Gale, Chris P & Shah, Anoop D & Abrams, Keith R & Crowther, Michael & Manca, Andrea & Timmis, Adam & Hemingway, Harry & Sculpher, Mark, 2016. "Using electronic health records to predict costs and outcomes in stable coronary artery disease," LSE Research Online Documents on Economics 101257, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:101257
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    File URL: http://eprints.lse.ac.uk/101257/
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    References listed on IDEAS

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    1. Briggs, Andrew & Sculpher, Mark & Claxton, Karl, 2006. "Decision Modelling for Health Economic Evaluation," OUP Catalogue, Oxford University Press, number 9780198526629.
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    Cited by:

    1. Miqdad Asaria & Katja Grasic & Simon Walker, 2016. "Using Linked Electronic Health Records to Estimate Healthcare Costs: Key Challenges and Opportunities," PharmacoEconomics, Springer, vol. 34(2), pages 155-160, February.
    2. Michael Crowther & Paul Lambert, 2016. "Multistate survival analysis in Stata," United Kingdom Stata Users' Group Meetings 2016 02, Stata Users Group.
    3. Rudolf T. Hoogenveen & Hendriek C. Boshuizen & Peter M. Engelfriet & Pieter H. M. van Baal, 2017. "You Only Die Once: Accounting for Multi-Attributable Mortality Risks in Multi-Disease Models for Health-Economic Analyses," Medical Decision Making, , vol. 37(4), pages 403-414, May.
    4. Lauren Scott & Chris Rogers, 2016. "Creating summary tables using the sumtable command," United Kingdom Stata Users' Group Meetings 2016 05, Stata Users Group.
    5. James Lomas & Miqdad Asaria & Laura Bojke & Chris P. Gale & Gerry Richardson & Simon Walker, 2018. "Which Costs Matter? Costs Included in Economic Evaluation and their Impact on Decision Uncertainty for Stable Coronary Artery Disease," PharmacoEconomics - Open, Springer, vol. 2(4), pages 403-413, December.

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    JEL classification:

    • E6 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook

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