Evidence map›Paper›PMID 36441366›Full record

ReviewJournal of general internal medicine2023

Where Do Real-Time Prescription Benefit Tools Fit in the Landscape of High US Prescription Medication Costs? A Narrative Review.

Rachel Wong, Tanvi Mehta, Bradley Very, Jing Luo, Kristian Feterik, Bradley H Crotty, Jeremy A Epstein, Michael J Fliotsos, Nitu Kashyap, Erika Smith and 2 more

Open access · bronzeAbstract readReview
In one paragraph

Review in Journal of general internal medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Emergency Medicine Pharmacist Prescriptive Authority for Resolution of Outpatient Prescription Issues.Journal of the American College of Emergency Physicians open · 2025
    Article
  4. Article
  5. Article
  6. Price transparency at the point of prescribing with real-time prescription benefits.American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists · 2024
    Article
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

12 authors at 7 institutions in 1 country.

Rachel WongDepartment of Biomedical Informatics, Renaissance School of Medicine at Stony Brook, Stony Brook, USA. rachel.wong@stonybrookmedicine.edu.ORCID 0000-0003-3108-7324
Tanvi MehtaDuke University School of Medicine, Durham, USA.
Bradley VeryDepartment of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, USA.
Jing LuoDepartment of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, USA.
Kristian FeterikDepartment of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, USA.
Bradley H CrottyFroedtert & the Medical College of Wisconsin Health Network, Milwaukee, WI, USA.
Jeremy A EpsteinDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Michael J FliotsosDepartment of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, USA.
Nitu KashyapJoint Data Analytics Team, Yale New Haven Hospital, New Haven, CT, USA.
Erika SmithFroedtert & the Medical College of Wisconsin Health Network, Milwaukee, WI, USA.
Fasika A WoretaWilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Jeremy I SchwartzSection of General Internal Medicine, Yale University School of Medicine, New Haven, CT, USA.
University of Pittsburgh · USFroedtert Hospital · USJohns Hopkins University · USYale University · USDuke University · USStony Brook School · USYale New Haven Hospital · US

Funding

Developing a provider-facing intervention to address cost-related medication restrictions and improve medication use in patients with type 2 diabetesK23DK120956 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LUO, JING · 2021 to 2024
$829k
6 · The paper itself

Abstract

The problem of unaffordable prescription medications in the United States is complex and can result in poor patient adherence to therapy, worse clinical outcomes, and high costs to the healthcare system. While providers are aware of the financial burden of healthcare for patients, there is a lack of actionable price transparency at the point of prescribing. Real-time prescription benefit (RTPB) tools are new electronic clinical decision support tools that retrieve patient- and medication-specific out-of-pocket cost information and display it to clinicians at the point of prescribing. The rise in US healthcare costs has been a major driver for efforts to increase medication price transparency, and mandates from the Centers for Medicare & Medicaid Services for Medicare Part D sponsors to adopt RTPB tools may spur integration of such tools into electronic health records. Although multiple factors affect the implementation of RTPB tools, there is limited evidence on outcomes. Further research will be needed to understand the impact of RTPB tools on end results such as prescribing behavior, out-of-pocket medication costs for patients, and adherence to pharmacologic treatment. We review the terminology and concepts essential in understanding the landscape of RTPB tools, implementation considerations, barriers to adoption, and directions for future research that will be important to patients, prescribers, health systems, and insurers.

Indexed as

Medicare Part DPrescription DrugsAgedHealth ExpendituresHumansPrescriptionsUnited StatesPrescription DrugsCost of careFormulary decision supportMedication price transparencyPrescription medication costsReal-time prescription benefit tools

Identifiers

PMID36441366
PMCPMC10039141
OpenAlexW4310130622

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.