The Medicare prescription drug benefit (Part D) relies on private market mechanisms to deliver care: a typical beneficiary can choose from between 45 and 57 private stand-alone Part D plans (PDP) in 2009, depending on his/her region of residence. It is known that beneficiaries do not choose plans based on their medication needs; and that the ability to choose plans is poorer among beneficiaries with mental disorders. The purpose of this study is to simulate personalized plan choice based on patient medication needs in schizophrenia and quantify potential improvement in patient drug coverage and potential savings to the government. Part D provides substantial premium and cost-sharing assistance to beneficiaries qualifying for the low-income subsidy (LIS) program. About 93% of PDP enrollees with schizophrenia received the LIS in 2007, whereas 40% of all PDP enrollees did. The majority of LIS enrollees are randomly assigned to PDP plans with premiums at or below the regional average. Random assignment does not assign enrollees to plans based on their medication needs and has caused severe problems including disruptions in plan coverage for 5.9 million between 2007 and 2010; and high beneficiary and government spending for those assigned to plans requiring high copayments. Our study will develop intelligent assignment algorithms based on beneficiaries' medication needs and dynamics of plan features in the Part D market. The algorithms can be easily implemented each year after an initial setup of software without substantial costs. The intelligent assignment method can be used by the government to assign/reassign beneficiaries or provide personalized assistance to help beneficiaries with schizophrenia to choose plans. The intelligent assignment method has the potential to substantially reduce government spending while improving patient outcomes.

Public Health Relevance

The prevalence rate of schizophrenia is 2.6% among Medicare beneficiaries enrolled in stand-alone prescription drug plans (PDP), much higher than the 1.1% among the US general population. About 93% of Medicare PDP enrollees with schizophrenia received the low-income- subsidy (LIS) on the plan premium and cost-sharing for medications, whereas 40% of overall Medicare Part D enrollees did. The majority of LIS enrollees are randomly assigned to PDP plans with premiums at or below the regional average. Random assignment does not assign enrollees to plans based on their medication needs and this leaves room for substantial savings and improvement in drug coverage under alternative assignments. It is known that beneficiaries are unable to choose plans based on their medication needs. Compared with average beneficiaries, patients with schizophrenia are poorer, less educated, and less likely to make rational plan choices. If we find that enrollees wit schizophrenia are assigned in ill-fitting plans that require utilization reviews for many of their psychiatric and non-psychiatric drugs and are unable to switch to better plans, alternative assignments based on their medication use or personalized assistance in switching plans are necessary. The intelligent assignment method has the potential to substantially reduce government spending while improving patient outcomes.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21MH100721-02
Application #
8775263
Study Section
Special Emphasis Panel (SERV)
Program Officer
Rupp, Agnes
Project Start
2013-12-01
Project End
2015-11-30
Budget Start
2014-12-01
Budget End
2015-11-30
Support Year
2
Fiscal Year
2015
Total Cost
$227,298
Indirect Cost
$77,298
Name
University of Pittsburgh
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Hernandez, Inmaculada; Zhang, Yuting; Brooks, Maria M et al. (2017) Anticoagulation Use and Clinical Outcomes After Major Bleeding on Dabigatran or Warfarin in Atrial Fibrillation. Stroke 48:159-166
Driessen, Julia; Zhang, Yuting (2017) Trends in the Inclusion of Mental Health Providers in Medicare Shared Savings Program ACOs. Psychiatr Serv 68:303-305
Hernandez, Inmaculada; Zhang, Yuting (2017) Comparing Adoption of Breakthrough and ""Me-too"" Drugs among Medicare Beneficiaries: A Case Study of Dipeptidyl Peptidase-4 Inhibitors. J Pharm Innov 12:105-109
Jarlenski, Marian; Hyon Baik, Seo; Zhang, Yuting (2016) Trends in Use of Medications for Smoking Cessation in Medicare, 2007-2012. Am J Prev Med 51:301-8
Baik, Seo Hyon; Hernandez, Inmaculada; Zhang, Yuting (2016) Evaluating the Initiation of Novel Oral Anticoagulants in Medicare Beneficiaries. J Manag Care Spec Pharm 22:281-92
Driessen, Julia; Baik, Seo Hyon; Zhang, Yuting (2016) Trends in Off-Label Use of Second-Generation Antipsychotics in the Medicare Population From 2006 to 2012. Psychiatr Serv 67:898-903
Driessen, Julia; Baik, Seo Hyon; Zhang, Yuting (2016) Explaining Improved Use of High-Risk Medications in Medicare Between 2007 and 2011. J Am Geriatr Soc 64:674-6
Hernandez, Inmaculada; Zhang, Yuting (2015) Risk of Bleeding With Dabigatran in 2010-2011 Medicare Data. JAMA Intern Med 175:1245-7
Zhang, Yuting; Talisa, Victor; Baik, Seo Hyon (2015) Part D Plan Switching Among Medicare Beneficiaries With Schizophrenia. Psychiatr Serv 66:1105-8
Zhang, Yuting; Baik, Seo Hyon; Newhouse, Joseph P (2015) Use of intelligent assignment to Medicare Part D plans for people with schizophrenia could produce substantial savings. Health Aff (Millwood) 34:455-60

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