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Stollenwerk, B. ; Welchowski, T. ; Vogl, M. ; Stock, S.*

Cost-of-illness studies based on massive data: A prevalence-based, top-down regression approach.

Eur. J. Health Econ. 17, 235-244 (2016)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Despite the increasing availability of routine data, no analysis method has yet been presented for cost-of-illness (COI) studies based on massive data. We aim, first, to present such a method and, second, to assess the relevance of the associated gain in numerical efficiency. We propose a prevalence-based, top-down regression approach consisting of five steps: aggregating the data; fitting a generalized additive model (GAM); predicting costs via the fitted GAM; comparing predicted costs between prevalent and non-prevalent subjects; and quantifying the stochastic uncertainty via error propagation. To demonstrate the method, it was applied to aggregated data in the context of chronic lung disease to German sickness funds data (from 1999), covering over 7.3 million insured. To assess the gain in numerical efficiency, the computational time of the innovative approach has been compared with corresponding GAMs applied to simulated individual-level data. Furthermore, the probability of model failure was modeled via logistic regression. Applying the innovative method was reasonably fast (19 min). In contrast, regarding patient-level data, computational time increased disproportionately by sample size. Furthermore, using patient-level data was accompanied by a substantial risk of model failure (about 80 % for 6 million subjects). The gain in computational efficiency of the innovative COI method seems to be of practical relevance. Furthermore, it may yield more precise cost estimates.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Cost-of-illness ; Error Propagation ; Generalized Additive Models ; Massive Data
ISSN (print) / ISBN 1618-7598
e-ISSN 1618-7601
Zeitschrift The European journal of health economics
Quellenangaben Band: 17, Heft: , Seiten: 235-244 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Berlin ; Heidelberg
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Health Economics and Health Care Management (IGM)