Evidence map›Paper›PMID 35395792›Full record

ArticleBMC health services research2022

Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations.

Ronja Flemming, Wiebke Schüttig, Frank Ng, Verena Leve, Leonie Sundmacher

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.1field-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

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Motif discovery in hospital ward vital signs observation networks.Network modeling and analysis in health informatics and bioinformatics · 2024
    Article
  3. Article
  4. 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

5 authors at 3 institutions in 1 country.

Ronja FlemmingChair of Health Economics, Technical University of Munich, Georg-Brauchle-Ring 60/62, 80992, München, Germany. ronja.flemming@tum.de.
Wiebke SchüttigChair of Health Economics, Technical University of Munich, Georg-Brauchle-Ring 60/62, 80992, München, Germany.
Frank NgCentral Institute, for SHI Physician Care in Germany, Salzufer 8, 10587, Berlin, Germany.
Verena LeveInstitute of General Practice (Ifam), Centre for Health and Society (Chs), Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
Leonie SundmacherChair of Health Economics, Technical University of Munich, Georg-Brauchle-Ring 60/62, 80992, München, Germany.
Ludwig-Maximilians-Universität München · DEHeinrich Heine University Düsseldorf · DETechnical University of Munich · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoordinating health care within and among sectors is crucial to improving quality of care and avoiding undesirable negative health outcomes, such as avoidable hospitalizations. Quality circles are one approach to strengthening collaboration among health care providers and improving the continuity of care. However, identifying and including the right health professionals in such meetings is challenging, especially in settings with no predefined patient pathways. Based on the Accountable Care in Germany (ACD) project, our study presents a framework for and investigates the feasibility of applying social network analysis (SNA) to routine data in order to identify networks of ambulatory physicians who can be considered responsible for the care of specific patients.

methodsThe ACD study objectives predefined the characteristics of the networks. SNA provides a methodology to identify physicians who have patients in common and ensure that they are involved in health care provision. An expert panel consisting of physicians, health services researchers, and data specialists examined the concept of network construction through informed decisions. The procedure was structured by five steps and was applied to routine data from three German states.

resultsIn total, 510 networks of ambulatory physicians met our predefined inclusion criteria. The networks had between 20 and 120 physicians, and 72% included at least ten different medical specialties. Overall, general practitioners accounted for the largest proportion of physicians in the networks (45%), followed by gynecologists (10%), orthopedists, and ophthalmologists (5%). The specialties were distributed similarly across the majority of networks. The number of patients this study allocated to the networks varied between 95 and 45,268 depending on the number and specialization of physicians per network.

conclusionsThe networks were constructed according to the predefined characteristics following the ACD study objectives, e.g., size of and specialization composition in the networks. This study shows that it is feasible to apply SNA to routine data in order to identify groups of ambulatory physicians who are involved in the treatment of a specific patient population. Whether these doctors are also mainly responsible for care and if their active collaboration can improve the quality of care still needs to be examined.

Indexed as

General PractitionersMedicineAmbulatory Care FacilitiesHumansSocial Network AnalysisSpecializationAmbulatory careCare coordinationPhysician networksQuality of careSocial network analysis

Identifiers

PMID35395792
PMCPMC8991784
OpenAlexW4223533635

What OpenQuestion holds

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LicenceCC BY
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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.