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Using biomarkers to predict healthcare costs: Evidence from a UK household panel

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  • Davillas, Apostolos
  • Pudney, Stephen

Abstract

We investigate the extent to which healthcare service utilisation and costs can be predicted from biomarkers, using the UK Understanding Society panel. We use a sample of 2314 adults who reported no history of diagnosed long-lasting health conditions at baseline (2010/11), when biomarkers were collected. Five years later, their GP, outpatient (OP) and inpatient (IP) utilisation was observed. We develop an econometric technique for count data observed within ranges and a method of combining administrative reference cost data with the survey data without exact individual-level matching. Our composite biomarker index (allostatic load) is a powerful predictor of costs: for those with a baseline allostatic load of at least one standard deviation (1-s.d.) above mean, a 1-s.d. reduction reduces GP, OP and IP costs by around 18%.

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  • Davillas, Apostolos & Pudney, Stephen, 2020. "Using biomarkers to predict healthcare costs: Evidence from a UK household panel," Journal of Health Economics, Elsevier, vol. 73(C).
  • Handle: RePEc:eee:jhecon:v:73:y:2020:i:c:s0167629619308495
    DOI: 10.1016/j.jhealeco.2020.102356
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Chris Sampson’s journal round-up for 5th October 2020
      by Chris Sampson in The Academic Health Economists' Blog on 2020-10-05 11:00:05

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    Cited by:

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    2. Barry, L.E. & O'Neill, S. & Heaney, L.G. & O'Neill, C., 2021. "Stress-related health depreciation: Using allostatic load to predict self-rated health," Social Science & Medicine, Elsevier, vol. 283(C).
    3. Fernando Antonio Slaibe Postali & Maria Dolores M Diaz, Adriano Dutra Teixeira, Natalia Nunes Ferreira Batista, Rodrigo Moreno Serra, 2021. "Impact of primary care coverage on individual health: evidence from biomarkers in Brazil," Working Papers, Department of Economics 2021_01, University of São Paulo (FEA-USP).

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    More about this item

    Keywords

    Healthcare costs; Socioeconomic gradient; Biomarkers; Allostatic load; Understanding society;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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