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Ranking the 'Balance' of State Long-Term Care Systems: A Comparative Exposition of the SMARTER and CaRBS Techniques

Beynon, Malcolm James ORCID: https://orcid.org/0000-0002-5757-270X and Kitchener, Martin James ORCID: https://orcid.org/0000-0001-6249-557X 2005. Ranking the 'Balance' of State Long-Term Care Systems: A Comparative Exposition of the SMARTER and CaRBS Techniques. Health Care Management Science 8 (2) , pp. 157-166. 10.1007/s10729-005-0398-2

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Abstract

The use of attribute sets to rank units of health provision (e.g., states, organizations) against policy goals is an essential task within decision-making and analysis. This paper elucidates and compares two techniques, SMARTER (Simple Multiattribute Rating Technique Exploiting Ranks) and CaRBS (Classification and Ranking Belief Simplex), within an expositional ranking of US states long-term care (LTC) systems against the policy goal of providing a balance between (traditionally dominant) institutional care, and alternative home and community-based services (HCBS). While the (more established) SMARTER technique is used primarily for comparative purposes, greater emphasis is placed on elucidating CaRBS which is based on the Dempster-Shafer theory of evidence. It is shown that CaRBS offers four appealing features for health policy analysis: (1) the capacity to rank using either of two confidence measures (DST-related belief and plausibility values), (2) a systematic approach to managing missing data, (3) the production of stable rankings, and (4) the simplex plot method of data representation. In addition to discussing the LTC policy implications of the study findings, the issues of rank order stability and the management of missing data are discussed with respect to the two techniques employed.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > H Social Sciences (General)
Uncontrolled Keywords: ranking - CaRBS - SMARTER - state long-term care systems - rebalancing
Publisher: Springer Verlag
ISSN: 1386-9620
Last Modified: 21 Oct 2022 09:51
URI: https://orca.cardiff.ac.uk/id/eprint/38005

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