Davillas A, Pudney S. Using biomarkers to predict healthcare costs: Evidence from a UK household panel.
JOURNAL OF HEALTH ECONOMICS 2020;
73:102356. [PMID:
32663637 DOI:
10.1016/j.jhealeco.2020.102356]
[Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 06/27/2020] [Accepted: 07/01/2020] [Indexed: 06/11/2023]
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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