AI Integration in Practice Management and the Impact on Value-Based Care
7 min
As the healthcare industry continues its shift from fee-for-service to value-based care (VBC), artificial intelligence (AI) has emerged as a transformative force — reshaping how practice groups and practitioners deliver care, manage risk, and engage patients.
Integrating AI into electronic health record (EHR) technology is driving a paradigm shift, setting higher benchmarks for what practitioners and their practice groups can achieve in terms of enhancing healthcare delivery and improving patient outcomes. As AI continues to evolve, EHRs are becoming more intuitive and responsive, transforming from mere data repositories into dynamic tools that actively support clinical decision-making and patient management.
To better understand the impact of AI integration within the EHR and how it enhances VBC delivery for practice groups, this article will explore AI’s evolving role in streamlining workflows and improving patient outcomes. It will also examine the risks associated with AI and potential challenges, including data governance and regulatory alignment.
The Current State of AI in Value-Based Care
AI has quickly become a pivotal component in the healthcare industry, particularly in VBC models. It is being utilized to complete administrative tasks, enhance clinical decision-making, and improve patient engagement. A 2024 survey of healthcare leaders indicated that more than 70% of healthcare organizations have either implemented AI technology or plan to do so in the near future. Of the organizations who have already integrated AI into their workflows, 59% have chosen to partner with third-party vendors to develop customized solutions.
This rapid shift in AI use is fostering a new standard where healthcare providers expect EHR systems to not only store and organize patient information but also to help clinicians more quickly analyze data, predict outcomes, and access actionable insights in real time, all crucial to successful VBC delivery. The results are already evident: enhanced ability to predict patient risk, improved patient outcomes, and a time savings over manual administrative tasks.
The Evolution of AI in Value-Based Care
From 2015-2020, AI in healthcare saw a five-fold increase in venture capital investment. As its capabilities have evolved, so has the recognition of its potential: the AI in healthcare market CAGR is expected to increase 37% by 2033. Organizations eager to remain on the leading edge of care delivery and navigate new VBC models are fueling demand.
The journey of AI in VBC has been marked by significant advancements with sophisticated algorithms and machine learning models. AI is now capable of providing predictive analytics, personalized treatment plans, and real-time monitoring of patient health. This evolution has enabled healthcare providers to shift from reactive to proactive care, thereby improving the overall quality of care—an outcome core to successful VBC delivery.
Risks vs. Benefits of AI in Value-Based Care
Responsible AI should benefit practice groups and improve compliance, not detract from it. While practice groups are rightfully excited about benefits of AI such as improved accuracy in diagnoses and more efficient workflows, ethical, safety, and regulatory challenges do exist. Some considerations in effectively implementing AI include:
- Ensuring patient data is private and secure from data breaches and unauthorized access
- Eliminating biases that can be ingrained in AI algorithms
- Providing transparency in decision-making and building trust, crucial in supporting physician buy-in
Responsible AI and the TEFCA Framework for AI Implementation
The American Medical Association notes that supporting VBC makes it critical to integrate AI into existing EHR workflows, allowing practical application of the tool rather than creating a frustrating barrier for physicians who are completing tasks.
Additionally, AI should be developed within the Trusted Exchange Framework and Common Agreement (TEFCA), which helps ensure responsible AI. Best practices of responsible AI include:
- Data Governance: Ensuring high-quality, representative data is crucial for effective AI implementation.
- AI Governance: Establishing clear guidelines and frameworks for responsible AI use.
- Regulatory Compliance: Staying up-to-date with evolving regulations and guidelines around AI in healthcare.
- Partnerships: Collaborating with technology partners to develop customized AI solutions.
By prioritizing transparency, accountability, and safety, healthcare leaders can harness the potential of AI to transform the industry. To stay ahead, healthcare professionals should educate themselves on emerging AI trends and technologies, and consider partnering with experienced technology providers to navigate the complexities of AI implementation. Look for voluntary certifications like the ONC Health IT Certification that indicate a technology partner’s commitment to ensuring products meet robust technical and interoperability requirements.
Practical Application of AI in Value-Based Care
AI tools are being applied in various practical ways to support VBC models. There are many areas in which AI tools can help support a practice group’s engagement with the interdisciplinary teams across senior care facilities, as well as with risk-bearing entities they interact with. A few key areas to consider include seeking tools that offer:
- Predictive analytics and monitoring
- Personalized treatment plans
- Workflow efficiency
- Quality performance measuring
- Administrative automation
- Coding and billing
- Scheduling
Staying Ahead of Future Trends
By partnering with PointClickCare, practice groups can position themselves at the forefront of value-based healthcare innovation. Gain tools that support streamlined patient care and administrative tasks, automated workflows, and insights that enhance care coordination and decision-making.
Request a demo today to discover how PointClickCare can help your practice group thrive in the evolving healthcare landscape.
