Evidence map›Paper›PMID 30865835›Full record

ReviewAnnals of the American Thoracic Society2019

Identifying Patients with Pulmonary Arterial Hypertension Using Administrative Claims Algorithms.

Stephen C Mathai, Anna Ryan Hemnes, Scott Manaker, Rebekah H Anguiano, Bonnie B Dean, Vishal Saundankar, Peter Classi, Andrew C Nelsen, Kathryn Gordon, Corey E Ventetuolo

Abstract readReview
In one paragraph

Review in Annals of the American Thoracic Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

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

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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

10 authors.

Stephen C Mathai1 Johns Hopkins University School of Medicine, Baltimore, Maryland.
Anna Ryan Hemnes2 Department of Medicine, Vanderbilt University, Nashville, Tennessee.
Scott Manaker3 University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.
Rebekah H Anguiano4 University of Illinois at Chicago College of Pharmacy, Chicago, Illinois.
Bonnie B Dean5 Xcenda, LLC, Palm Harbor, Florida.
Vishal Saundankar5 Xcenda, LLC, Palm Harbor, Florida.
Peter Classi6 United Therapeutics Corporation, Research Triangle Park, North Carolina; and.
Andrew C Nelsen6 United Therapeutics Corporation, Research Triangle Park, North Carolina; and.ORCID 0000-0001-5956-7026
Kathryn Gordon6 United Therapeutics Corporation, Research Triangle Park, North Carolina; and.
Corey E Ventetuolo7 Alpert Medical School of Brown University; Brown University School of Public Health, Providence, Rhode Island.ORCID 0000-0002-4223-4775

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Retrospective administrative claims database studies provide real-world evidence about treatment patterns, healthcare resource use, and costs for patients and are increasingly used to inform policy-making, drug formulary, and regulatory decisions. However, there is no standard methodology to identify patients with pulmonary arterial hypertension (PAH) from administrative claims data. Given the number of approved drugs now available for patients with PAH, the cost of PAH treatments, and the significant healthcare resource use associated with the care of patients with PAH, there is a considerable need to develop an evidence-based and systematic approach to accurately identify these patients in claims databases. A panel of pulmonary hypertension clinical experts and researchers experienced in retrospective claims database studies convened to review relevant literature and recommend best practices for developing algorithms to identify patients with PAH in administrative claims databases specific to a particular research hypothesis.

Indexed as

AlgorithmsAntihypertensive AgentsDatabases, FactualHumansInsurance Claim ReviewPatient Acceptance of Health CarePulmonary Arterial HypertensionRetrospective StudiesAntihypertensive Agentsadministrative claimspulmonary arterial hypertensionpulmonary hypertension

Identifiers

PMID30865835
PMCPMC6600840

What OpenQuestion holds

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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.