Evidence map›Paper›PMID 31517600›Full record

ArticlePreventing chronic disease2019

A Public Health Framework to Improve Population Health Through Health Care and Community Clinical Linkages: The ASTHO/CDC Heart Disease and Stroke Prevention Learning Collaborative.

Rose Anne Felipe, Marcus Plescia, Emily Peterman, Holly Tomlin, Michael Sells, Camillia Easley, Kaha Ahmed, Letitia Presley-Cantrell

Abstract read
In one paragraph

Article in Preventing chronic disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
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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

8 authors.

Rose Anne FelipeAssociation of State and Territorial Health Officials, 2231 Crystal Dr, Suite 450, Arlington, VA 22202. Email: Rose.A.Felipe@gmail.com.
Marcus PlesciaAssociation of State and Territorial Health Officials, Arlington, Virginia.
Emily PetermanAssociation of State and Territorial Health Officials, Arlington, Virginia.
Holly TomlinTomlin Health Sciences Communications, Brooklyn, New York.
Michael SellsCenters for Disease Control and Prevention, Atlanta, Georgia.
Camillia EasleyCenters for Disease Control and Prevention, Atlanta, Georgia.
Kaha AhmedCenters for Disease Control and Prevention, Atlanta, Georgia.
Letitia Presley-CantrellCenters for Disease Control and Prevention, Atlanta, Georgia.

Funding

OSTLTS CDC HHS U38 OT000161
6 · The paper itself

Abstract

Thirty-one state and territorial public health agencies participated in a learning collaborative to improve diagnosis and management of hypertension in clinical and community settings. These health agencies implemented public health and clinical interventions in medical settings and health organizations using a logic model and rapid quality improvement process focused on a framework of 4 systems-change levers: 1) data-driven action, 2) clinical practice standardization, 3) clinical-community linkages, and 4) financing and policy. We provide examples of how public health agencies applied the systems-change framework in all 4 areas to assess and modify population-based interventions to improve control of hypertension. This learning collaborative approach illustrates the importance of public health in the prevention and control of chronic disease by supporting interventions that address community and clinical linkages to address medical risk factors associated with cardiovascular disease.

Indexed as

ArkansasCommunity Health ServicesHeart DiseasesHumansHypertensionNew YorkOklahomaPopulation HealthPublic Health AdministrationStroke

Identifiers

PMID31517600
PMCPMC6745896

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.