Name
#36 Revolutionizing Military Healthcare: A Comparative Effectiveness Research Review on Leveraging Technology, Machine Learning, and Interoperability for Value-Based Care and Superior Outcomes
Speakers
Content Presented on Behalf of
DHA
Services/Agencies represented
Defense Health Agency (DHA)
Session Type
Posters
Room#/Location
Prince Georges Exhibit Hall A/B
Focus Areas/Topics
Clinical Care, Medical Technology
Learning Outcomes
Learning Outcomes
1. Understand the Role of Advanced Technologies: Learners will be able to explain how machine learning, natural language processing (NLP), and interoperability can enhance access to care and improve health outcomes in the Military Health System (MHS).
2. Identify Budget Trends and Strategies: Learners will gain insights into the historical budget trends of the MHS and identify strategies to manage and potentially decrease the budget while maintaining high-quality care.
3. Recognize Barriers to Accessing Care: Learners will be able to identify and discuss the various barriers that impede effective access to care for military personnel, including mental health stigma, geographical challenges, and administrative issues.
4. Evaluate Preventive Care and Telehealth: Learners will understand the importance of enhanced preventive care and the expansion of telehealth services in reducing long-term healthcare costs and improving access to care for remote or underserved populations.
5. Assess the Impact of Technology Integration: Learners will be able to assess how the integration of advanced technologies, such as the Johns Hopkins Risk Scoring Model, can prioritize care for high-risk patients and support military readiness through improved health outcomes
1. Understand the Role of Advanced Technologies: Learners will be able to explain how machine learning, natural language processing (NLP), and interoperability can enhance access to care and improve health outcomes in the Military Health System (MHS).
2. Identify Budget Trends and Strategies: Learners will gain insights into the historical budget trends of the MHS and identify strategies to manage and potentially decrease the budget while maintaining high-quality care.
3. Recognize Barriers to Accessing Care: Learners will be able to identify and discuss the various barriers that impede effective access to care for military personnel, including mental health stigma, geographical challenges, and administrative issues.
4. Evaluate Preventive Care and Telehealth: Learners will understand the importance of enhanced preventive care and the expansion of telehealth services in reducing long-term healthcare costs and improving access to care for remote or underserved populations.
5. Assess the Impact of Technology Integration: Learners will be able to assess how the integration of advanced technologies, such as the Johns Hopkins Risk Scoring Model, can prioritize care for high-risk patients and support military readiness through improved health outcomes
Session Currently Live
Description
Abstract
This research review explores the transformative potential of advanced technologies in enhancing access to care and improving health outcomes for military service members and their families. By leveraging machine learning, interoperability, and innovative appointing systems, this study aims to align with the mission and vision of the Military Health System (MHS), ultimately supporting military readiness and optimal health outcomes.
Introduction
The Military Health System (MHS) is tasked with providing comprehensive healthcare to military personnel, retirees, and their families. Despite significant investments, challenges such as rising healthcare costs, mental health stigma, and geographical barriers persist. This study investigates how advanced technologies, including machine learning, natural language processing (NLP), and interoperability, can enhance access to care and improve health outcomes, aligning with the goals of value-based care.
Methods
This research review synthesizes findings from various studies and reports on the use of advanced technologies in healthcare. Key areas of focus include the Johns Hopkins Risk Scoring ACG Model, telehealth services, and innovative appointing systems. Data on budget trends, healthcare outcomes, and barriers to care were analyzed to identify strategies for optimizing the MHS.
Results
The budget for the MHS has seen consistent increases, with the FY2024 budget request at $58.7 billion and the FY2025 request at $61.4 billion. Enhanced preventive care, telehealth expansion, and efficient resource utilization were identified as key strategies to manage and potentially decrease the budget. Barriers to effective access to care include mental health stigma, geographical challenges, capacity constraints, cultural and attitudinal barriers, and administrative and logistical constraints.
Discussion
Utilizing robust technology such as Machine Learning, Natural Language Processing, and automation of the Johns Hopkins Risk Scoring Model is critical for the MHS. These technologies enable early identification and intervention for high-risk patients, enhancing preventive care. The Johns Hopkins Risk Scoring ACG Model, for instance, uses machine learning and fast computing processes to assign risk scores based on patient coding, helping prioritize face-to-face appointments for the most vulnerable patients. Telehealth services and innovative appointing systems improve access to care, particularly for those in remote or underserved areas. By addressing barriers to care and implementing these strategies, the MHS can improve health outcomes and support military readiness.
Conclusion
This research review demonstrates that leveraging advanced technologies can revolutionize military healthcare. By optimizing access to care, these strategies align with the goals of value-based care, enhance patient experience, and lead to superior health outcomes. Continued investment in technological advancements and strategic partnerships with civilian and military healthcare providers and industry partners are essential for sustaining military readiness and improving the health of service members and their families.
Keywords
Military Health System, Machine Learning, Natural Language Processing, Interoperability, Value-Based Care, Preventive Care, Telehealth, Johns Hopkins Risk Scoring Model, Healthcare Access, Military Readiness.