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The impact of using different costing methods on the results of an economic evaluation of cardiac care: microcosting vs gross-costing approaches
Health economics, 2009-04, Vol.18 (4), p.377-388
Clement (Nee Shrive), Fiona M.
Ghali, William A.
Donaldson, Cam
Manns, Braden J.
2009
Details
Autor(en) / Beteiligte
Clement (Nee Shrive), Fiona M.
Ghali, William A.
Donaldson, Cam
Manns, Braden J.
Titel
The impact of using different costing methods on the results of an economic evaluation of cardiac care: microcosting vs gross-costing approaches
Ist Teil von
Health economics, 2009-04, Vol.18 (4), p.377-388
Ort / Verlag
Chichester, UK: John Wiley & Sons, Ltd
Erscheinungsjahr
2009
Link zum Volltext
Quelle
Applied Social Sciences Index & Abstracts (ASSIA)
Beschreibungen/Notizen
Background: Published guidelines on the conduct of economic evaluations provide little guidance regarding the use and potential bias of the different costing methods. Objectives: Using microcosting and two gross‐costing methods, we (1) compared the cost estimates within and across subjects, and (2) determined the impact on the results of an economic evaluation. Methods: Microcosting estimates were obtained from the local health region and gross‐costing estimates were obtained from two government bodies (one provincial and one national). Total inpatient costs were described for each method. Using an economic evaluation of sirolimus‐eluting stents, we compared the incremental cost–utility ratios that resulted from applying each method. Results: Microcosting, Case‐Mix‐Grouper (CMG) gross‐costing, and Refined‐Diagnosis‐Related grouper (rDRG) gross‐costing resulted in 4‐year mean cost estimates of $16 684, $16 232, and $10 474, respectively. Using Monte Carlo simulation, the cost per QALY gained was $41 764 (95% CI: $41 182–$42 346), $42 538 (95% CI: $42 167–$42 907), and $36 566 (95% CI: $36 172–$36 960) for microcosting, rDRG‐derived and CMG‐derived estimates, respectively (P<0.001). Conclusions: Within subject, the three costing methods produced markedly different cost estimates. The difference in cost–utility values produced by each method is modest but of a magnitude that could influence a decision to fund a new intervention. Copyright © 2008 John Wiley & Sons, Ltd.
Sprache
Englisch
Identifikatoren
ISSN: 1057-9230
eISSN: 1099-1050
DOI: 10.1002/hec.1363
Titel-ID: cdi_proquest_miscellaneous_67019637
Format
–
Schlagworte
Aged
,
Alberta
,
Bias
,
Cardiovascular Diseases - drug therapy
,
Cardiovascular Diseases - economics
,
Cardiovascular Diseases - surgery
,
case-mix groupers
,
Cost estimates
,
costing
,
Costs and Cost Analysis - methods
,
Diagnosis-Related Groups - economics
,
economic evaluation
,
Estimation bias
,
gross costing
,
Health care
,
Health economics
,
Hospitalization
,
Humans
,
microcosting
,
Middle Aged
,
Monte Carlo simulation
,
Quality-Adjusted Life Years
,
Studies
,
Utility functions
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