Evidence map›Paper›PMID 35994196›Full record

ReviewCurrent cardiology reports2022

Leveraging Healthcare System Data to Identify High-Risk Dyslipidemia Patients.

Nayrana Griffith, Grace Bigham, Aparna Sajja, Ty J Gluckman

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current cardiology reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

4 authors.

Nayrana GriffithDepartment of Internal Medicine, Medstar Georgetown University Hospital, Washington, DC, USA. Nayrana.c.griffith@gunet.georgetown.edu.
Grace BighamDepartment of Internal Medicine, Medstar Georgetown University Hospital, Washington, DC, USA.
Aparna SajjaDivision of Cardiology, Medstar Georgetown University Hospital-Washington Hospital Center, Washington, DC, USA.
Ty J GluckmanCenter for Cardiovascular Analytics, Research and Data Science (CARDS), Providence Heart Institute, Providence Research Network, Portland, OR, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewWhile randomized controlled trials have historically served as the gold standard for shaping guideline recommendations, real-world data are increasingly being used to inform clinical decision-making. We describe ways in which healthcare systems are generating real-world data related to dyslipidemia and how these data are being leveraged to improve patient care. RECENT

findingsThe electronic medical record has emerged as a major source of clinical data, which alongside claims and pharmacy dispending data is enabling healthcare systems the ability to identify care gaps (underdiagnosis and undertreatment) in patients with dyslipidemia. Availability of this data also allows healthcare systems the ability to test and deliver interventions at the point-of-care. Real-world data possess great potential as a complement to randomized controlled trials. Healthcare systems are uniquely positioned to not only define care gaps and areas of opportunity, but to also to leverage tools (e.g., clinical decision support, case identification) aimed at closing them.

Indexed as

Delivery of Health CareDyslipidemiasElectronic Health RecordsHumansArtificial intelligenceCare gapsDyslipidemiaElectronic medical recordHealthcare systemsReal-world data

Identifiers

PMID35994196

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.