1. Patient care in complex Sociotechnological ecosystems and learning health systems
- Author
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Tu, Shin‐Ping, Garcia, Brittany, Zhu, Xi, Sewell, Daniel, Mishra, Vimal, Matin, Khalid, and Dow, Alan
- Subjects
Information and Computing Sciences ,Health Services and Systems ,Information Systems ,Health Sciences ,Health Services ,Networking and Information Technology R&D (NITRD) ,Machine Learning and Artificial Intelligence ,Patient Safety ,Clinical Research ,8.1 Organisation and delivery of services ,Generic health relevance ,Good Health and Well Being ,learning health system ,multiteam systems ,team communication - 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.
- Published
- 2024