Across the healthcare industry, association and clinical leaders continue to feel excitement over the potential of artificial intelligence (AI) to improve care and outcomes. AI undoubtedly holds promise to deliver a positive impact across a wide variety of healthcare use cases, including identifying patients with gaps in clinical care, surfacing critical social determinants of health data hidden in patients’ medical records, prioritizing patients by risk of negative outcomes, and providing insights into the behavior of clinicians and patients.
Our four-part blog series explores the role medical specialty societies and patient organizations can play in overcoming barriers in the adoption and use of AI to improve patient outcomes.
This blog delves into AI-based clinical decision support tools (CDSTs) developed and designed in collaboration with IQVIA to intelligently address gaps in clinical care, supporting providers in disease management.
AI-based CDSTs offer transformative opportunities in patient diagnosis and management. Their value lies not in replacing clinicians, but in enhancing their decision-making processes by providing timely, patient-specific insights, ultimately improving patient outcomes.
Medical specialty societies and patient organizations play an essential role in the development and deployment of CDSTs: assuring alignment with the most acute clinical needs, bringing the input of providers, patients, and caregivers, and helping pave the path to adoption at scale. The insights, collaborations, and participation in CDST development by these organizations are crucial in ensuring AI reaches its full potential in healthcare.
AI in healthcare holds immense value in changing the patient care paradigm, specifically in predicting future medical events and informing interventions to alter clinical trajectories. By consuming and analyzing vast amounts of patient data within the medical record, AI can identify patterns and risk factors not surfaced by clinicians or overlooked in the context of a busy clinical practice. Embedding these insights intuitively into the clinical workflow helps ensure the adoption of CDSTs without adding to the existing challenge of provider burnout. This positions clinicians for proactive interventions that reduce or avoid the physical, emotional, and financial toll on the patient and caregiver.
Additionally, CDSTs can help codify existing clinical guidelines and surface new insights via a custom-built AI algorithm. While many diseases have established clinical guidelines, their consistent adoption into routine clinical care is often a challenge due to the emerging nature of the guidelines, the complexity of extracting required data from clinical notes, and limited provider capacity. An AI algorithm can be included in the CDST in cases where guidelines do not exist or do not achieve a desired level of precision. An AI algorithm can help proactively identify patients who are undiagnosed with a given disease, are at risk of progression, severe adverse events, or other medical events.
IQVIA develops disease-specific algorithms that identify clinical gaps and integrate that information into clinical workflows to minimize disruption to providers. Rather than a user experience that relies on intrusive alerts, such as pop-up messages, the CDST is intuitively embedded into the clinical workflow with clear actions aligned to care team members operating at the top of their license. Armed with this information, care team members can optimize the trajectory of their patient journeys and prevent the progression of disease.
While the deployment of AI-powered CDSTs at scale is an emerging field, there are many promising examples across diseases and geographies. For example, one healthcare organization partnered with IQVIA to identify atrial fibrillation patients at risk for stroke. By aligning the current treatment of at-risk patients to recommended clinical guidelines, the organization reduced atrial fibrillation-related strokes by 22% and saved $7 million.
Designing CDSTs is no easy task and requires cross-functional expertise to produce meaningful solutions.
IQVIA has been curating healthcare datasets from around the globe for over 20 years, hosting a secure environment and an established process for identifiable data storage and processing. Analytics experts develop scientifically rigorous algorithms with AI and natural language processing using methodologies validated across diseases on over 200 studies. IQVIA’s clinical leaders rely on deep knowledge within the medical field to understand exactly how CDSTs can be used and implemented. Technology experts map out how new tools should be integrated into electronic medical records to facilitate adoption. Finally, regulatory leaders bring a robust understanding of regulatory, privacy, and compliance frameworks across geographies.
When discussing nonprofits’ role in developing CDSTs, the question of the source of funding often arises. CDST development is frequently funded through the nonprofits’ established research grant mechanisms or through joint applications to government or life sciences funding opportunities.
Conclusion Leading the development of next-generation clinical decision support tools positions nonprofit groups to better advocate for their specific patient populations. IQVIA AI can help healthcare nonprofits accomplish several key objectives, including improving patient healthcare outcomes, aligning with clinical guidelines, and reducing burdens on clinicians.
To learn more about what IQVIA AI can do for healthcare, click here.
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