Cost prediction models for the comparison of two groups
For trial‐based economic evaluation where patient‐specific cost data are not routinely available, cost prediction models are commonly used to estimate total cost for each patient. Typically, multiple regression techniques are used on data from diagnosis‐matched, non‐trial patients (where patient‐lev...
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| Published in | Health economics Vol. 10; no. 4; pp. 363 - 366 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Chichester, UK
John Wiley & Sons, Ltd
01.06.2001
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| Series | Health Economics |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1057-9230 1099-1050 |
| DOI | 10.1002/hec.615 |
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| Summary: | For trial‐based economic evaluation where patient‐specific cost data are not routinely available, cost prediction models are commonly used to estimate total cost for each patient. Typically, multiple regression techniques are used on data from diagnosis‐matched, non‐trial patients (where patient‐level cost data are available) to model cost as a function of covariates that are observed on the trial subjects (e.g. length of hospital stay, procedures, etc.). The estimated beta coefficients provide a means of estimating the total cost for each patient in the trial. However, the variability of the beta coefficients due the measurement and sampling error is seldom included in the overall variance expression for mean costs by treatment group. In this paper we provide a method for estimating this variance and provide an example application Copyright © 2001 John Wiley & Sons, Ltd. |
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| Bibliography: | ArticleID:HEC615 istex:CD29947848D518B4676D58199FC7903C52F523A1 ark:/67375/WNG-HCB899LZ-4 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
| ISSN: | 1057-9230 1099-1050 |
| DOI: | 10.1002/hec.615 |