Evidence map›Paper›PMID 17003157›Full record

ReviewAnnals of family medicine

Shaping the future of academic health centers: the potential contributions of departments of family medicine.

Warren P Newton, C Annette DuBard

Abstract readReview
In one paragraph

Review in Annals of family medicine. 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
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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

2 authors.

Warren P NewtonDepartment of Family Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599-7595, USA. Warren_Newton@med.unc.edu
C Annette DuBard

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Academic health centers (AHCs) must change dramatically to meet the changing needs of patients and society, but how to do this remains unclear. The purpose of this supplement is to describe ways in which departments of family medicine can play leadership roles in helping AHCs evolve. This overview provides background for case studies and commentaries about the contribution of departments of family medicine in 5 areas: (1) ambulatory and primary care, (2) indigent care, (3) education in community and international settings, (4) workforce policy and practice, and (5) translational research. The common theme is a revitalization of the relationship between AHCs and the communities they serve across all missions. Family medicine leadership can provide dramatic organizational improvement in primary and ambulatory care networks and foster opportunities for leadership by AHCs in improving the health of the population. Departments of family medicine can also play a leading role in developing new partnerships with community-based organizations, managing the care of the indigent, and developing new curricula in community and international settings. Finally, family medicine departments and their faculty have a central role in helping AHCs respond to workforce needs and in developing translational research that emphasizes the health of the population and effectiveness of care. AHCs are a public good that must now evolve substantially to meet the needs of patients and society. By pushing for substantial change, by helping to reinvigorate the relationship between AHCs and the communities they serve, and by emphasizing fundamental innovation in clinical care, teaching, and research, family medicine can help lead the renewal of the AHC.

Indexed as

Academic Medical CentersEducation, MedicalFamily PracticeForecastingHumans

Identifiers

PMID17003157
PMCPMC1578669

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.