Title : Implementing team-based strategies for diabetes control in skilled nursing settings
Abstract:
This presentation, titled "Implementing Team-Based Strategies for Diabetes Control in Skilled Nursing Settings," addresses the critical need for enhanced diabetes care within skilled nursing facilities through the integration of Complex Adaptive Systems (CAS) theory. Diabetes management for older adults presents unique challenges due to the complexities of physiological changes, comorbidities, cognitive impairments, and psychosocial factors. Effective management requires a responsive, multidisciplinary approach grounded in interprofessional collaboration.
The presentation begins by establishing the foundational importance of collaborative care models, highlighting the need for integrated efforts among nurses, physicians, pharmacists, dietitians, and information technology specialists. The application of CAS theory is explored as a means of fostering decentralized communication and promoting adaptive teamwork structures capable of responding swiftly to evolving patient needs.
An overview of the Integrated Diabetes Care Program (IDCP) is presented, emphasizing the synchronization of discipline-specific expertise and the use of evidence-based practices. Digital innovations such as continuous glucose monitoring (CGM) and teleconsultation platforms will be discussed, with data demonstrating their effectiveness in improving glycemic outcomes and patient satisfaction, as evidenced by recent studies including Tourkmani et al. (2024).
The presentation further delves into the specific mechanisms of CAS theory application within diabetes management, emphasizing dynamic partnerships, shared goals, and feedback loops that support real-time adaptive care. The CAS model is outlined with practical examples of how it enables healthcare teams to collaboratively address the complex and fluctuating care needs of diabetic residents in skilled nursing environments.
A significant segment is dedicated to data terminologies and management practices, highlighting the critical role of standardized clinical vocabularies such as SNOMED CT and LOINC for precise documentation and communication. The role of big data analytics and data mining techniques in predicting care patterns, facilitating proactive interventions, and enhancing decision-making accuracy is also discussed.
The importance of efficient data management through Electronic Health Record (EHR) systems is highlighted, emphasizing their capabilities for medication management, dietary tracking, and integration with continuous glucose monitoring systems. Secure, cloud-based platforms for remote interdisciplinary team collaboration and real-time data exchange will be explored as integral components of modern diabetes management strategies.
Lastly, compelling evidence from recent clinical trials is presented, demonstrating the superiority of integrated care approaches guided by CAS principles. Data indicates substantial improvements in detecting hypoglycemia and hyperglycemia episodes, significantly reducing adverse events compared to traditional point-of-care testing. These results underscore the value of adopting a coordinated, dynamic care model that prioritizes patient-centered outcomes and safety.
In conclusion, the presentation synthesizes the discussed elements, reinforcing the significance of interdisciplinary collaboration, innovative technology utilization, and strategic data management in achieving optimal diabetes outcomes within skilled nursing facilities. Attendees will be equipped with actionable insights into implementing and sustaining effective diabetes management strategies grounded in the robust principles of Complex Adaptive Systems theory.
