Universität zu Köln

Stollenwerk, Bjorn ORCID: 0000-0002-3189-409X, Welchowski, Thomas ORCID: 0000-0003-2940-647X, Vogl, Matthias and Stock, Stephanie (2016). Cost-of-illness studies based on massive data: a prevalence-based, top-down regression approach. Eur. J. Health Econ., 17 (3). S. 235 - 245. NEW YORK: SPRINGER. ISSN 1618-7601

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Abstract

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.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Stollenwerk, Bjorn UNSPECIFIED orcid.org/0000-0002-3189-409X UNSPECIFIED Welchowski, Thomas UNSPECIFIED orcid.org/0000-0003-2940-647X UNSPECIFIED Vogl, Matthias UNSPECIFIED UNSPECIFIED UNSPECIFIED Stock, Stephanie UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-280073
DOI:	10.1007/s10198-015-0667-z
Journal or Publication Title:	Eur. J. Health Econ.
Volume:	17
Number:	3
Page Range:	S. 235 - 245
Date:	2016
Publisher:	SPRINGER
Place of Publication:	NEW YORK
ISSN:	1618-7601
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language LARGE DATA SETS; STATUTORY HEALTH-INSURANCE; ECONOMIC BURDEN; CARE-SYSTEM; DISEASE; MODELS; IMPACT; COPD; EXPENDITURES; DEMENTIA Multiple languages Economics; Health Policy & Services Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/28007