Evidence map›Paper›PMID 26772962›Full record

ArticleBMC health services research2016

Medicaid prescription limits: policy trends and comparative impact on utilization.

Daniel A Lieberman, Jennifer M Polinski, Niteesh K Choudhry, Jerry Avorn, Michael A Fischer

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 24% of its field
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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
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  7. Healthcare Rationing in Public Insurance Programs: Evidence from Medicaid.American economic journal. Economic policy · 2022
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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

5 authors at 3 institutions in 1 country.

Daniel A LiebermanDivision of Emergency Medicine, University of Washington, Seattle, WA, USA. danlieb@uw.edu.
Jennifer M PolinskiCVS Health, Woonsocket, RI, USA.
Niteesh K ChoudhryDivision of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Jerry AvornDivision of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Michael A FischerDivision of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Brigham and Women's Hospital · USCVS Health (United States) · USSeattle University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMedicaid 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.

methodsWe 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.

resultsThe 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.

conclusionsAn 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.

Indexed as

Drug CostsDrug PrescriptionsDrugs, GenericDrug Utilization ReviewHealth PolicyHumansInterrupted Time Series AnalysisMedicaidPrescription DrugsUnited StatesDrugs, GenericPrescription Drugs

Identifiers

PMID26772962
PMCPMC4714442
OpenAlexW2239612222

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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.