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dc.contributor.authorLieberman, Daniel A.en_US
dc.contributor.authorPolinski, Jennifer M.en_US
dc.contributor.authorChoudhry, Niteesh K.en_US
dc.contributor.authorAvorn, Jerryen_US
dc.contributor.authorFischer, Michael A.en_US
dc.date.accessioned2016-02-01T15:47:41Z
dc.date.issued2016en_US
dc.identifier.citationLieberman, Daniel A., Jennifer M. Polinski, Niteesh K. Choudhry, Jerry Avorn, and Michael A. Fischer. 2016. “Medicaid prescription limits: policy trends and comparative impact on utilization.” BMC Health Services Research 16 (1): 15. doi:10.1186/s12913-016-1258-0. http://dx.doi.org/10.1186/s12913-016-1258-0.en
dc.identifier.issn1472-6963en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:24984062
dc.description.abstractBackground: Medicaid programs face growing pressure to control spending. Despite evidence of clinical harms, states continue to impose policies limiting the number of reimbursable prescriptions (caps). We examined the recent use of prescription caps by Medicaid programs and the impact of policy implementation on prescription utilization. Methods: We identified Medicaid cap policies from 2001–2010. We classified caps as applying to all prescriptions (overall caps) or only branded prescriptions (brand caps). Using state-level, aggregate prescription data, we developed interrupted time-series analyses to evaluate the impact of implementing overall caps and brand caps in a subset of states with data available before and after cap initiation. For overall caps, we examined the use of essential medications, which were classified as preventive or as providing symptomatic benefit. For brand caps, we examined the use of all branded drugs as well as branded and generic medications among classes with available generic replacements. Results: The number of states with caps increased from 12 in 2001 to 20 in 2010. Overall cap implementation (n = 3) led to a 0.52 % (p < 0.001) annual decrease in the proportion of essential prescriptions but no change in cost. For preventive essential medications, overall caps led to a 1.12 % (p = 0.001) annual decrease in prescriptions (246,000 prescriptions annually) and a 1.20 % (p < 0.001) decrease in spending (−$12.2 million annually), but no decrease in symptomatic essential medication use. Brand cap implementation (n = 6) led to an immediate 2.29 % (p = 0.16) decrease in branded prescriptions and 1.26 % (p = 0.025) decrease in spending. For medication classes with generic replacements, the decrease in branded prescriptions (0.74 %, p = 0.003) approximately equaled the increase in generics (0.79 %, p = 0.009), with estimated savings of $17.4 million. Conclusions: An increasing number of states are using prescription caps, with mixed results. Overall caps decreased the use of preventive but not symptomatic essential medications, suggesting that patients assign higher priority to agents providing symptomatic benefit when faced with reimbursement limits. Among medications with generic replacements, brand caps shifted usage from branded drugs to generics, with considerable savings. Future research should analyze the patient-level impact of these policies to measure clinical outcomes associated with these changes. Electronic supplementary material The online version of this article (doi:10.1186/s12913-016-1258-0) contains supplementary material, which is available to authorized users.en
dc.language.isoen_USen
dc.publisherBioMed Centralen
dc.relation.isversionofdoi:10.1186/s12913-016-1258-0en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC4714442/pdf/en
dash.licenseLAAen_US
dc.subjectHealth policyen
dc.subjectMedicaiden
dc.subjectPrescription drugsen
dc.subjectPharmacy benefitsen
dc.subjectPharmacoepimiologyen
dc.subjectHealth services researchen
dc.titleMedicaid prescription limits: policy trends and comparative impact on utilizationen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalBMC Health Services Researchen
dash.depositing.authorChoudhry, Niteesh K.en_US
dc.date.available2016-02-01T15:47:41Z
dc.identifier.doi10.1186/s12913-016-1258-0*
dash.contributor.affiliatedAvorn, Jerome
dash.contributor.affiliatedChoudhry, Niteesh
dash.contributor.affiliatedFischer, Michael


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