Evidence map›Paper›PMID 21397779›Full record

ArticleClinical therapeutics2011

Impact of prior authorization on the use and costs of lipid-lowering medications among Michigan and Indiana dual enrollees in Medicaid and Medicare: results of a longitudinal, population-based study.

Christine Y Lu, Michael R Law, Stephen B Soumerai, Amy Johnson Graves, Robert F LeCates, Fang Zhang, Dennis Ross-Degnan, Alyce S Adams

Abstract read
In one paragraph

Article in Clinical therapeutics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  12. Trends in high-dose opioid prescribing in Canada.Canadian family physician Medecin de famille canadien · 2014
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Christine Y LuDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA. christine_lu@harvardpilgrim.org
Michael R Law
Stephen B Soumerai
Amy Johnson Graves
Robert F LeCates
Fang Zhang
Dennis Ross-Degnan
Alyce S Adams

Funding

Impact of Prior Approval for Antidepressants in MedicaidR01MH069776 · NIMH · HARVARD PILGRIM HEALTH CARE, INC. · PI SOUMERAI, STEPHEN B · 2005 to 2007
$1.4M
THE HMO RESEARCH NETWORK CERTU18HS010391 · AHRQ · HARVARD PILGRIM HEALTH CARE, INC. · PI PLATT, RICHARD · 2000 to 2006
$799k
AHRQ HHS U18 HS010391AHRQ HHS U18HS010391CIHRNIMH NIH HHS 5R01MH069776-03NIMH NIH HHS R01 MH069776
6 · The paper itself

Abstract

backgroundSome Medicaid programs have adopted prior-authorization (PA) policies that require prescribers to request approval from Medicaid before prescribing drugs not included on a preferred drug list.

objectiveThis study examined the association between PA policies for lipid-lowering agents in Michigan and Indiana and the use and cost of this drug class among dual enrollees in Medicare and Medicaid.

methodsMichigan and Indiana claims data from the Centers for Medicare and Medicaid Services were assessed. Michigan Medicaid instituted a PA requirement for several lipid-lowering medications in March 2002; Indiana implemented a PA policy for drugs in this class in September 2002. Although the PA policies affected some statins, they predominantly targeted second-line treatments, including bile acid sequestrants, fibrates, and niacins. Individuals aged ≥18 years who were continuously dually enrolled in both Medicare and Medicaid from July 2000 through September 2003 were included in this longitudinal, population-based study, which included a 20-month observation period before the implementation of PA in Michigan and a 12-month follow-up period after the Indiana PA policy was initiated. Interrupted time series analysis was used to examine changes in prescription rates and pharmacy costs for lipid-lowering drugs before and after policy implementation.

resultsA total of 38,684 dual enrollees in Michigan and 29,463 in Indiana were included. Slightly more than half of the cohort were female (Michigan, 53.3% [20,614/38,684]; Indiana, 56.3% [16,595/29,463]); nearly half were aged 45 to 64 years (Michigan, 43.7% [16,921/38,684]; Indiana, 45.2% [13,321/29,463]). Most subjects were white (Michigan, 77.4% [29,957/38,684]; Indiana: 84.9% [25,022/29,463]). The PA policy was associated with an immediate 58% reduction in prescriptions for nonpreferred medications in Michigan and a corresponding increase in prescriptions for preferred agents. However, the PA policy had no apparent effect in Indiana, where there had been little use of nonpreferred medications before the policy was implemented (3.3%). The policies were associated with an immediate reduction of $24,548 in prescription expenditures in Michigan and an immediate reduction of $16,070 in Indiana.

conclusionsThe PA policy was associated with substantially lower use of nonpreferred lipid-lowering drugs in Michigan, offset by increases in the use of preferred medications, but there was less change in Indiana. Data limitations did not permit the evaluation of the impact of policy-induced switching on clinical outcomes such as cholesterol levels. The monetary benefit of PA policies for lipid-lowering agents should be weighed against administrative costs and the burden on patients and health care providers.

Indexed as

Organizational PolicyCohort StudiesDrug CostsFemaleFollow-Up StudiesHumansHypolipidemic AgentsIndianaLongitudinal StudiesMaleMedicaidMedicareMichiganMiddle AgedReimbursement MechanismsRetrospective StudiesHypolipidemic Agents

Identifiers

PMID21397779
PMCPMC3980661

What OpenQuestion holds

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LicenceTDM
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.