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Patient care in complex Sociotechnological ecosystems and learning health systems.
Tu, Shin-Ping; Garcia, Brittany; Zhu, Xi; Sewell, Daniel; Mishra, Vimal; Matin, Khalid; Dow, Alan.
Afiliação
  • Tu SP; Department of Internal Medicine University of California, Davis Sacramento California USA.
  • Garcia B; Department of Internal Medicine University of California, Davis Sacramento California USA.
  • Zhu X; Department of Health Policy and Management University of California, Los Angeles Los Angeles California USA.
  • Sewell D; Department of Biostatistics University of Iowa Iowa City Iowa USA.
  • Mishra V; Department of Internal Medicine University of California, Davis Sacramento California USA.
  • Matin K; Department of Internal Medicine Virginia Commonwealth University Richmond Virginia USA.
  • Dow A; Department of Internal Medicine Virginia Commonwealth University Richmond Virginia USA.
Learn Health Syst ; 8(Suppl 1): e10427, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38883874
ABSTRACT
The learning health system (LHS) model was proposed to provide real-time, bi-directional flow of learning using data captured in health information technology systems to deliver rapid learning in healthcare delivery. As highlighted by the landmark National Academy of Medicine report "Crossing the Quality Chasm," the U.S. healthcare delivery industry represents complex adaptive systems, and there is an urgent need to develop innovative methods to identify efficient team structures by harnessing real-world care delivery data found in the electronic health record (EHR). We offer a discussion surrounding the complexities of team communication and how solutions may be guided by theories such as the Multiteam System (MTS) framework and the Multitheoretical Multilevel Framework of Communication Networks. To advance healthcare delivery science and promote LHSs, our team has been building a new line of research using EHR data to study MTS in the complex real world of cancer care delivery. We are developing new network metrics to study MTSs and will be analyzing the impact of EHR communication network structures on patient outcomes. As this research leads to patient care delivery interventions/tools, healthcare leaders and healthcare professionals can effectively use health IT data to implement the most evidence-based collaboration approaches in order to achieve the optimal LHS and patient outcomes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Learn Health Syst Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Learn Health Syst Ano de publicação: 2024 Tipo de documento: Article