Impact of team configuration and team stability on primary care quality

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dc.citation.articleNumber22en_US
dc.citation.journalTitleImplementation Scienceen_US
dc.citation.volumeNumber14en_US
dc.contributor.authorHysong, Sylvia J.en_US
dc.contributor.authorAmspoker, Amber B.en_US
dc.contributor.authorHughes, Ashley M.en_US
dc.contributor.authorWoodard, Lechauncyen_US
dc.contributor.authorOswald, Frederick L.en_US
dc.contributor.authorPetersen, Laura A.en_US
dc.contributor.authorLester, Houston F.en_US
dc.date.accessioned2019-12-12T17:25:39Zen_US
dc.date.available2019-12-12T17:25:39Zen_US
dc.date.issued2019en_US
dc.description.abstractBackground: The science of effective teams is well documented; far less is known, however, about how specific team configurations may impact primary care team effectiveness. Further, teams experiencing frequent personnel changes (perhaps as a consequence of poor implementation) may have difficulty delivering effective, continuous, well-coordinated care. This study aims to examine the extent to which primary care clinics in the Veterans Health Administration have implemented team configurations consistent with recommendations based on the Patient-Centered Medical Home model and the extent to which adherence to said recommendations, team stability, and role stability impact healthcare quality. Specifically, we expect to find better clinical outcomes in teams that adhere to recommended team configurations, teams whose membership and configuration are more stable over time, and teams whose clinical manager role is more stable over time. Methods/design: We will employ a combination of social network analysis and multilevel modeling to conduct a database review of variables extracted from the Veterans Health Administration’s Team Assignments Report (TAR) (one of the largest, most diverse existing national samples of primary care teams (nteams > 7000)), as well as other employee and clinical data sources. To ensure the examination of appropriate clinical outcomes, we will enlist a team of subject matter experts to select a concise set of clear, prioritized primary care performance metrics. We will accomplish this using the Productivity Measurement and Enhancement System, an evidence-based methodology for developing and implementing performance measurement. Discussion: We are unaware of other studies of healthcare teams that consider team size, composition, and configuration longitudinally or with sample sizes of this magnitude. Results from this study can inform primary care team implementation policy and practice in both private- and public-sector clinics, such that teams are configured optimally, with adequate staffing, and the right mix of roles within the team.en_US
dc.identifier.citationHysong, Sylvia J., Amspoker, Amber B., Hughes, Ashley M., et al.. "Impact of team configuration and team stability on primary care quality." <i>Implementation Science,</i> 14, (2019) BioMed Central: https://doi.org/10.1186/s13012-019-0864-8.en_US
dc.identifier.digitals13012-019-0864-8en_US
dc.identifier.doihttps://doi.org/10.1186/s13012-019-0864-8en_US
dc.identifier.urihttps://hdl.handle.net/1911/107891en_US
dc.language.isoengen_US
dc.publisherBioMed Centralen_US
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/),en_US
dc.titleImpact of team configuration and team stability on primary care qualityen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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