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

BACKGROUND: Coordinating 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 c...

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Autores principales: Flemming, Ronja, Schüttig, Wiebke, Ng, Frank, Leve, Verena, Sundmacher, Leonie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8991784/
https://www.ncbi.nlm.nih.gov/pubmed/35395792
http://dx.doi.org/10.1186/s12913-022-07807-8
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author Flemming, Ronja
Schüttig, Wiebke
Ng, Frank
Leve, Verena
Sundmacher, Leonie
author_facet Flemming, Ronja
Schüttig, Wiebke
Ng, Frank
Leve, Verena
Sundmacher, Leonie
author_sort Flemming, Ronja
collection PubMed
description BACKGROUND: Coordinating 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. METHODS: The 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. RESULTS: In 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. CONCLUSIONS: The 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.
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spelling pubmed-89917842022-04-09 Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations Flemming, Ronja Schüttig, Wiebke Ng, Frank Leve, Verena Sundmacher, Leonie BMC Health Serv Res Research BACKGROUND: Coordinating 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. METHODS: The 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. RESULTS: In 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. CONCLUSIONS: The 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. BioMed Central 2022-04-08 /pmc/articles/PMC8991784/ /pubmed/35395792 http://dx.doi.org/10.1186/s12913-022-07807-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Flemming, Ronja
Schüttig, Wiebke
Ng, Frank
Leve, Verena
Sundmacher, Leonie
Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations
title Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations
title_full Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations
title_fullStr Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations
title_full_unstemmed Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations
title_short Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations
title_sort using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8991784/
https://www.ncbi.nlm.nih.gov/pubmed/35395792
http://dx.doi.org/10.1186/s12913-022-07807-8
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