Evidence map›Paper›PMID 29262798›Full record

ArticleBMC family practice2017

Which strategies might improve local primary healthcare in Germany? An explorative study from a local government point of view.

Bertolt Kuhn, Kim-Sarah Kleij, Sebastian Liersch, Jost Steinhäuser, Volker Amelung

Open access · goldAbstract read
In one paragraph

Article in BMC family practice, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.5field-weighted citation impact, top 9% of its field
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

22 citing papers in PubMed, 42 citations in OpenAlex.

  1. Article
  2. Addressing Medical Deserts in Europe: Lessons From a Comparative Analysis.Health expectations : an international journal of public participation in health care and health policy · 2026
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  8. [How to Motivate Medical Students to Practice in Rural Areas].Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)) · 2024
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  10. Observational
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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

5 authors at 1 institution in 1 country.

Bertolt KuhnMedical School Hannover, Institute for Epidemiology, Social Medicine and Health Systems Research, OE 5410, Carl-Neuberg-Str. 1, D-30625, Hannover, Germany. Kuhn.Bertolt@mh-hannover.de.ORCID http://orcid.org/0000-0002-8677-7122
Kim-Sarah KleijMedical School Hannover, Institute for Epidemiology, Social Medicine and Health Systems Research, OE 5410, Carl-Neuberg-Str. 1, D-30625, Hannover, Germany.
Sebastian LierschMedical School Hannover, Institute for Epidemiology, Social Medicine and Health Systems Research, OE 5410, Carl-Neuberg-Str. 1, D-30625, Hannover, Germany.
Jost SteinhäuserUniversity Hospital of Schleswig-Holstein, Campus Lübeck, Institute of Family Medicine, Lübeck, Germany.
Volker AmelungMedical School Hannover, Institute for Epidemiology, Social Medicine and Health Systems Research, OE 5410, Carl-Neuberg-Str. 1, D-30625, Hannover, Germany.
Medizinische Hochschule Hannover · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFacing rising inequities and poorer accessibility of physicians in rural areas, new healthcare delivery structures are being considered to support local healthcare in German communities. To better understand perspectives on and attitudes towards different supplementary models, we examined attitudes among local politicians in the German federal state of Lower Saxony towards the suitability of supplementary care models.

methodsAs part of a cross-sectional study, we surveyed local politicians in Lower Saxony at the local authority and district levels (n = 449) by mail questionnaire. We asked for an assessment of four potential supplementary healthcare models at the local level: the use of trained medical assistants, patients' buses, mobile physicians' offices, and telemedicine.

resultsThe response rate was 71.0% for mayors (n = 292) and 81.6% (n = 31) for county administrators. In summary, 72.4% of respondents supported the use of trained medical assistants, 48.9% voted for patients' buses, 22.0% for mobile physicians' offices, and 13.9% for telemedicine. Except for telemedicine, the politicians' approval of the supplementary models in rural areas was higher than in urban areas. The assessment regarding the suitability of each model was not significantly connected with indicators of a positively or negatively assessed local healthcare situation. The analyses showed that the use of trained medical assistants was associated with the positive effects of division of labor and potential to relieve physicians. In contrast, there was skepticism about technical support via telemedicine, mostly due to concerns about its unsuitability for elderly people and the potential lower quality of healthcare delivery.

conclusionLocal politicians widely accept the use of trained medical assistants, whereas the applicability of technical solutions such as telemedicine is perceived with skepticism. Therefore, the knowledge gap between evidence for and prejudices against telemedicine needs to be addressed more effectively. Reasons for the assessments of the presented models are more likely traceable to personal views than to assessments of the actual estimated local primary care situation.

Indexed as

AttitudeLocal GovernmentAge FactorsCross-Sectional StudiesDelivery of Health CareGermanyHumansMobile Health UnitsNursesPhysician AssistantsPoliticsPrimary Health CareRural Health ServicesSurveys and QuestionnairesTelemedicineTransportationCommunitiesDelegationMobilityPhysician shortagePrimary healthcareSupplementary care modelsTelemedicine

Identifiers

PMID29262798
PMCPMC5738820
OpenAlexW2778104643

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.