Minimally important difference in cost savings: Is it possible to identify an MID for cost savings?
Cost savings
MID
Minimally important differences
Journal
Health services & outcomes research methodology
ISSN: 1387-3741
Titre abrégé: Health Serv Outcomes Res Methodol
Pays: Netherlands
ID NLM: 9815809
Informations de publication
Date de publication:
2021
2021
Historique:
received:
30
04
2020
revised:
18
11
2020
accepted:
25
11
2020
pubmed:
14
1
2021
medline:
14
1
2021
entrez:
13
1
2021
Statut:
ppublish
Résumé
As healthcare costs continue to increase, studies assessing costs are becoming increasingly common, but researchers planning for studies that measure costs differences (savings) encounter a lack of literature or consensus among researchers on what constitutes "small" or "large" cost savings for common measures of resource use. Other fields of research have developed approaches to solve this type of problem. Researchers measuring improvement in quality of life or clinical assessments have defined minimally important differences (MID) which are then used to define magnitudes when planning studies. Also, studies that measure cost effectiveness use benchmarks, such as cost/QALY, but do not provide benchmarks for cost differences. In a review of the literature, we found no publications identifying indicators of magnitude for costs. However, the literature describes three approaches used to identify minimally important outcome differences: (1) anchor-based, (2) distribution-based, and (3) a consensus-based Delphi methods. In this exploratory study, we used these three approaches to derive MID for two types of resource measures common in costing studies for: (1) hospital admissions (high cost); and (2) clinic visits (low cost). We used data from two (unpublished) studies to implement the MID estimation. Because the distributional characteristics of cost measures may require substantial samples, we performed power analyses on all our estimates to illustrate the effect that the definitions of "small" and "large" costs may be expected to have on power and sample size requirements for studies. The anchor-based method, while logical and simple to implement, may be of limited value in cases where it is difficult to identify appropriate anchors. We observed some commonalities and differences for the distribution and consensus-based approaches, which require further examination. We recommend that in cases where acceptable anchors are not available, both the Delphi and the distribution-method of MID for costs be explored for convergence.
Identifiants
pubmed: 33437174
doi: 10.1007/s10742-020-00233-5
pii: 233
pmc: PMC7790477
doi:
Types de publication
Journal Article
Langues
eng
Pagination
131-144Subventions
Organisme : NIDDK NIH HHS
ID : P30 DK123704
Pays : United States
Organisme : NIGMS NIH HHS
ID : U54 GM104941
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001450
Pays : United States
Informations de copyright
© The Author(s) 2021.
Déclaration de conflit d'intérêts
Conflict of interestThe authors declare that they have no conflict of interest.