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MedCity News October 30, 2025
MedCity News Editor-in-Chief Arundhati Parmar and Reporter Marissa Plescia interviewed health tech executives at HLTH 2025.
At the HLTH 2025 conference, healthcare executives shared how their companies perceive the shifting healthcare landscape and how their health tech companies fit into it.
Wolters Kluwer Health Director of Clinical Content Strategy Sheila Bond talked about how it is unlocking data and using AI to make its content more easily accessible for clinicians. She also highlighted the role of ambient AI in healthcare innovation.
Berry Street Chief…
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2025-10-30T12:05:58-04:00
How is your institution addressing data governance to ensure the accuracy and reliability of data used for AI-driven clinical decision-making?
AI in Healthcare: Insights from Executives on Clinical,OR Efficiency,and Payment Streamlining Innovations
Transforming Clinical Decision-Making with Artificial Intelligence
Healthcare executives are increasingly turning to artificial intelligence (AI) and machine learning (ML) to enhance clinical decision-making. This isn’t about replacing clinicians, but augmenting their abilities with data-driven insights. Several key applications are gaining traction:
* Diagnostic Accuracy: AI algorithms, especially in medical imaging analysis (radiology, pathology), are demonstrating accuracy comparable to, and sometimes exceeding, human experts. This leads to earlier and more precise diagnoses for conditions like cancer, heart disease, and neurological disorders.
* Personalized Medicine: AI-powered precision medicine analyzes patient data – genomics, lifestyle, medical history – to predict individual responses to treatments.This allows for tailored therapies, maximizing effectiveness and minimizing adverse effects. Predictive analytics plays a crucial role here.
* Remote Patient Monitoring: Wearable sensors and IoT devices, coupled with AI, enable continuous monitoring of patients outside traditional clinical settings.This is particularly valuable for managing chronic conditions like diabetes and hypertension, reducing hospital readmissions.
* drug Revelation & Development: AI is accelerating the traditionally lengthy and expensive drug development process. AI in pharmaceutical research helps identify potential drug candidates,predict their efficacy,and optimize clinical trial design.
Optimizing Operating Room (OR) efficiency Through AI
The OR represents a significant cost center for hospitals. Executives are exploring AI solutions to streamline operations and improve efficiency:
* Predictive Scheduling: AI algorithms can analyze ancient data to predict OR utilization, optimize scheduling, and minimize downtime between surgeries. This leads to increased throughput and reduced costs.
* Surgical Workflow Optimization: Computer vision and robotic surgery are enhancing surgical precision and efficiency. AI-powered systems can provide real-time guidance to surgeons, reducing errors and improving patient outcomes.
* Inventory Management: AI can optimize inventory levels of surgical supplies, ensuring that necessary materials are available when needed while minimizing waste and storage costs. Supply chain optimization is a key benefit.
* Real-time Data Analytics: during surgery, AI can analyze real-time data from monitoring devices to identify potential complications and alert the surgical team, improving patient safety.
Streamlining Healthcare Payment with AI
The complexities of healthcare billing and coding create significant administrative burdens. AI offers solutions to automate and streamline these processes:
* Automated coding: AI-powered medical coding automatically assigns appropriate codes to medical procedures and diagnoses, reducing errors and improving billing accuracy. This minimizes claim denials and accelerates reimbursement.
* Claims Adjudication: AI can automate the claims adjudication process, identifying fraudulent claims and ensuring compliance with payer regulations. This reduces administrative costs and improves payment integrity.
* Prior authorization: AI can automate the prior authorization process, reducing the administrative burden on providers and ensuring that patients receive timely access to necessary care.
* Revenue Cycle Management (RCM): AI in RCM analyzes data to identify areas for improvement in the revenue cycle, optimizing billing processes and maximizing revenue capture.
Benefits of AI Implementation in Healthcare
The advantages of integrating AI into healthcare are substantial:
* Improved Patient Outcomes: Earlier diagnoses, personalized treatments, and enhanced surgical precision all contribute to better patient outcomes.
* Reduced Healthcare Costs: Increased efficiency, automated processes, and reduced errors lead to significant cost savings.
* Enhanced Clinician Experience: AI tools can alleviate administrative burdens, allowing clinicians to focus on patient care.
* Increased Access to Care: Remote patient monitoring and telehealth solutions powered by AI can expand access to care,particularly for patients in underserved areas.
Practical Tips for Successful AI Implementation
Executives considering AI implementation should focus on these key areas:
- Data Quality: AI algorithms are only as good as the data they are trained on. Ensure data is accurate, complete, and standardized. Data governance is paramount.
- Interoperability: Ensure that AI systems can seamlessly integrate with existing electronic health record (EHR) systems and other healthcare IT infrastructure. HL7 FHIR standards are crucial.
- **Ethical Considerations
