In the ever-evolving landscape of healthcare, artificial intelligence (AI) is poised to revolutionize the way we approach patient care. From predictive analytics to preventive interventions, AI holds immense promise in improving outcomes, reducing costs, and ultimately saving lives. As a thought leader in this space, Intrahealth, a HEALWELL AI Company is committed to exploring the possibilities and driving meaningful change.
The Problem: Missed Opportunities in Patient Care
The issue of patients not receiving approved medications or medical interventions is a prevalent one in the healthcare industry. There are a variety of reasons why this may happen – sometimes, it’s simply a matter of oversight or lack of awareness on the part of healthcare providers, while in other cases, there may be resource constraints or other logistical barriers preventing patients from accessing the care they need.
Regardless of the specific reason, it’s clear that these gaps in patient care represent a significant missed opportunity. By not providing patients with the treatments and interventions proven to improve health outcomes, we are invariably increasing the cost to the healthcare system and reducing patient quality of life.
It is in everyone’s best interest to ensure that patients receive the care they need. By addressing the root causes of these gaps in care and working to improve access to approved medications and interventions, we can help to improve patient outcomes and create a more efficient and effective healthcare system overall.
The Unstructured Data Challenge
Why do patients fall through the cracks? The answer lies in the overwhelming amount of unstructured patient data across multiple systems making it almost impossible for care providers to have a concise view of patient information. Approximately 90% of patient information exists in Electronic Medical Record (EMR) format. Digitizing patient records has enabled improved accessibility, accuracy, and efficiency. However, the data is often fragmented, inconsistent and unstructured making it difficult for care providers to manage patients holistically across different care systems and it’s challenging for traditional database management tools to extract meaningful insights.
As a result, valuable insights into patient health and treatment outcomes can be missed, leading to gaps in care and potentially adverse health outcomes for patients. By leveraging advanced machine learning and natural language processing technologies, healthcare organizations can unlock the full potential of this data, enabling clinicians to make more informed decisions and deliver more personalized, effective care.
AI’s Transformative Role
Extracting Insights from Unstructured Data:
At the heart of AI’s transformative power is its proficiency in processing unstructured data, particularly through techniques like Natural Language Processing (NLP).
- By leveraging NLP algorithms, AI can swiftly analyze vast swathes of unstructured text, ranging from electronic health records (EHRs) to clinical notes and research papers.
- This capability enables healthcare providers to unlock valuable insights embedded within these textual repositories.
In a scenario where AI meticulously sifts through mountains of patient records, distilling key information about diagnoses, treatments, and outcomes. This ability to extract meaningful insights from EHRs empowers healthcare professionals to identify trends, detect anomalies, and address gaps in patient care more effectively than ever before.
Predictive Analytics and Preventive Care:
Beyond retrospective analysis, AI holds immense promise in the realm of predictive analytics and preventive care. We envision a future where AI algorithms anticipate patient behaviors and health trajectories, allowing for proactive interventions long before the onset of illness.
- By integrating AI into analytics and reporting frameworks, healthcare organizations can combine historical data with real-time monitoring, offering a holistic view of patient health.
- This fusion of retrospective insights with predictive modeling enables clinicians to identify individuals at heightened risk, tailor personalized interventions, and optimize healthcare delivery.
AI is transforming healthcare by improving patient outcomes, reducing costs, and developing preventive strategies. The future of healthcare is proactive, anticipatory, and focused on the patient.
Intrahealth’s Differentiation: Trust and Validation
Trust is vital in healthcare, and it is the foundation of our Central Healthcare System. Our HEALWELL AI solution, is designed to fully embody this principle. DARWEN™ has undergone extensive validation through controlled trials at renowned medical institutions, which have been documented in high-impact peer-reviewed journals. At our healthcare system, accuracy, transparency, and trust are our top priorities.
Use Case: Pentavere’s Success with Lung Cancer Patients
Pentavere is an AI-powered medical technology company that uses advanced algorithms to identify patients to receive more effective cancer treatments.
The company’s AI system analyzes patient data and identifies those who may benefit from guideline-recommended medical therapy.
According to this study, through the innovative use of AI and large language models, Pentavere has successfully extracted one of the largest population cohorts of advanced rare EGFRexon20 lung cancer patients for use as Real World Evidence. This dataset has provided valuable insights into unmet patient needs to support more effective cancer treatments.
The ability to analyze the large amounts of unstructured clinical documentation within the electronic health record at scale using generative AI has opened new avenues for improving patient outcomes and advancing precision medicine initiatives.
Overall, Pentavere’s AI system has demonstrated significant benefits in improving the care and outcomes of lung cancer. By identifying patients who may not be receiving optimal treatment and optimizing the use of recommended medications, Pentavere is helping to improve the quality of life for those living with cancer.
A New Era of Healthcare
As we embrace the possibilities AI brings, we must remember that every eligible patient who does not receive approved medications or medical interventions represents an opportunity for growth and transformation. By harnessing the power of AI, we can bridge gaps, create value, and ensure that no patient falls through the cracks.
Learn more about Intrahealth.
Learn more about HEALWELL AI Company.
Learn more about Pentavere.
Publications
- Moulson, R., Law, J., Sacher, A., Liu, G., Shepherd, F. A., Bradbury, P., Eng, L., Iczkovitz, S., Abbie, E., & Elia-Pacitti, J., et al. (2024). Real-world outcomes of patients with advanced epidermal growth factor receptor-mutated non-small cell lung cancer in Canada using data extracted by large language model-based artificial intelligence. Current Oncology, 31(4), 1947-1960. https://doi.org/10.3390/curroncol31040146
- Shepherd, F. A., Laskin, J., & Chu, Q. S. (2022). Automating access to real world evidence. Journal of Thoracic Oncology. Manuscript. https://www.jtocrr.org/article/S2666-3643(22)00064-9/fulltext
- Moulson, R., Law, J., Sacher, A., Liu, G., Shepherd, F. A., Bradbury, P., Eng, L., Iczkovitz, S., Abbie, E., & Elia-Pacitti, J., et al. (2022). Upfront next generation sequencing in non-small cell lung cancer. Current Oncology. Manuscript. https://www.mdpi.com/1718-7729/29/7/352
- Abed, S. N., & Hasan, H. S. (2021). Exploring treatment patterns and outcomes of patients with advanced lung cancer (aLC) using artificial intelligence (AI)-extracted data. Annals of Oncology. https://www.annalsofoncology.org/article/S0923-7534(21)04636-6/fulltext
- Shepherd, F. A., Bradbury, P., & Melosky, B. (2022). Real-world data curation to transform medical investigation: Technology to reimagine the economics of evidence gathering and support regulatory decision-making. Journal of Pharmacy and Pharmaceutical Sciences. https://www.mdpi.com/1718-7729/29/7/352
