Evidence map›Paper›PMID 38585437›Full record

ArticleNeurology. Clinical practice2024

Transforming Neurology Care Delivery Through a Population Health Data Strategy.

Ines M Vigil, Martha Sylvia

Abstract read
In one paragraph

Article in Neurology. Clinical practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Ines M VigilClarify Health Solutions (IMV); and Medical University of South Carolina College of Nursing (MS).
Martha SylviaClarify Health Solutions (IMV); and Medical University of South Carolina College of Nursing (MS).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With more than 30% of global data originating from health care, deriving usable insights that improve health requires population health analytics. In neurology, data-driven approaches have grown in significance because of digital health records and advanced analytics. A vital aspect of this evolution is adopting a population health data strategy (PHDS). Recent Findings: Crafting a tailored PHDS for neurology involves cataloging data points and measures spanning demographics, clinical history, genetics, and social determinants. Neurologic outcomes include mortality rates, functional and cognitive abilities, and imaging results. A robust strategy relies on interoperability, advanced analytics, and transparent AI algorithms. Summary: Neurology is embracing data-driven health care. The PHDS synthesizes diverse patient data to provide personalized care. It includes a wide range of outcome measures to address neurologic complexities. Advanced analytics and collaboration among neurologists, data scientists, and business leaders uncover hidden patterns and promote outcome-driven medicine in the 21st century.

Identifiers

PMID38585437
PMCPMC10996910

What Socratic 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 Socratic graph.