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dc.contributor.authorWrobel, Marian V.
dc.contributor.authorDoshi, Jalpa A.
dc.contributor.authorStuart, Bruce
dc.contributor.authorBriesacher, Becky A.
dc.date2022-08-11T08:09:22.000
dc.date.accessioned2022-08-23T16:28:04Z
dc.date.available2022-08-23T16:28:04Z
dc.date.issued2004-05-06
dc.date.submitted2011-12-09
dc.identifier.citationHealth Care Financ Rev. 2003 Winter;25(2):37-46. <a href="https://www.cms.gov/HealthCareFinancingReview/Downloads/03winterpg37.pdf">Link to article on publisher's website</a>
dc.identifier.issn0195-8631 (Linking)
dc.identifier.pmid15124376
dc.identifier.urihttp://hdl.handle.net/20.500.14038/36935
dc.description<p>At the time of publication, Becky Briesacher was not yet affiliated with the University of Massachusetts Medical School.</p>
dc.description.abstractMCBS data are used to analyze the predictability of drug expenditures by Medicare beneficiaries. Predictors include demographic characteristics and measures of health status, the majority derived using CMS' diagnosis cost group/hierarchical condition category (DCG/HCC) risk-adjustment methodology. In prospective models, demographic variables explained 5 percent of the variation in drug expenditures. Adding health status measures raised this figure between 10 and 24 percent of the variation depending on the model configuration. Adding lagged drug expenditures more than doubled predictive power to 55 percent. These results are discussed in the context of forecasting, and risk adjustment for the proposed new Medicare drug benefit.
dc.language.isoen_US
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=15124376&dopt=Abstract">Link to Article in PubMed</a>
dc.subjectAged
dc.subjectAged, 80 and over
dc.subjectData Collection
dc.subjectDrug Prescriptions
dc.subjectDrug Utilization
dc.subjectFee-for-Service Plans
dc.subjectFemale
dc.subjectForecasting
dc.subjectHealth Expenditures
dc.subjectHumans
dc.subjectInsurance, Pharmaceutical Services
dc.subjectMale
dc.subjectMedicare
dc.subjectModels, Statistical
dc.subjectUnited States
dc.subjectHealth Services Research
dc.subjectPrimary Care
dc.titlePredictability of prescription drug expenditures for Medicare beneficiaries
dc.typeJournal Article
dc.source.journaltitleHealth care financing review
dc.source.volume25
dc.source.issue2
dc.identifier.legacyfulltexthttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=1620&amp;context=meyers_pp&amp;unstamped=1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/meyers_pp/322
dc.identifier.contextkey2396683
refterms.dateFOA2022-08-23T16:28:05Z
html.description.abstract<p>MCBS data are used to analyze the predictability of drug expenditures by Medicare beneficiaries. Predictors include demographic characteristics and measures of health status, the majority derived using CMS' diagnosis cost group/hierarchical condition category (DCG/HCC) risk-adjustment methodology. In prospective models, demographic variables explained 5 percent of the variation in drug expenditures. Adding health status measures raised this figure between 10 and 24 percent of the variation depending on the model configuration. Adding lagged drug expenditures more than doubled predictive power to 55 percent. These results are discussed in the context of forecasting, and risk adjustment for the proposed new Medicare drug benefit.</p>
dc.identifier.submissionpathmeyers_pp/322
dc.contributor.departmentMeyers Primary Care Institute
dc.contributor.departmentDepartment of Medicine, Division of Geriatric Medicine
dc.source.pages37-46


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