AI-driven solution to manage care gaps caused by incidental findings
The Problem
Imaging diagnostics are a critical component of modern healthcare, aiding in the detection and management of various medical conditions. However, incidental findings—unexpected results discovered unintentionally—can pose significant challenges for healthcare providers. These findings often require further evaluation and follow-up, but the manual processes in place for managing them are time-consuming and prone to human error.
Our client, a prominent imaging diagnostics provider, struggled with the inefficiencies of their existing system, which left many incidental findings unaddressed and widened care gaps. The lack of a streamlined process led to delays in patient follow-up, risking potential deterioration in patient health and increasing the workload on already overburdened healthcare professionals.
The Solution
To address care gap management, we developed Proactive Follow-up, an AI-driven Population Health Management solution. This system automates the identification of clinically significant findings from imaging diagnostics, ensuring rapid detection and response. It flags potential care gaps, guides providers through follow-up steps, and streamlines documentation for better communication among healthcare teams.
By integrating this solution into existing workflows, our client achieved reduced workloads, improved care delivery, and better patient outcomes.
Using our Rapid Idea Validation framework with Design Thinking and lean methodologies, we were able to quickly ideate and find the right solution to bring to market.
Results
Proactive Follow-up, a Population Health Management Artificial Intelligence solution to manage care gaps, proactively. Enabling healthcare organizations to automate the processes for closing the loop in care gaps, transform care delivery, and improve the patient outcomes.
This innovative solution has produced exceptional results, revolutionizing the client’s digital capabilities in the care delivery space. Key outcomes include:
- Proactive Follow-up: The solution enabled healthcare professionals to address care gaps proactively, ensuring timely intervention and reducing the risk of adverse patient outcomes. This proactive approach fostered a culture of accountability and collaboration among the healthcare team.
- Improved Patient Outcomes: By automating the detection and follow-up processes, our solution ensured that no incidental findings were overlooked, leading to more accurate diagnoses and better patient outcomes. Patients received the care they needed precisely when they needed it, resulting in improved overall health and satisfaction.
- Enhanced Efficiency: The automated processes significantly reduced the workload on healthcare staff, allowing them to focus on providing personalized patient care. This efficiency also translated into cost savings for the organization, as resources were allocated more effectively.
- Scalable and Sustainable: Our solution’s scalability ensured that our client could easily expand its use across different departments and facilities, making it a sustainable option for long-term care gap management.
Conclusion
In conclusion, our collaboration with our client successfully addressed the pressing challenge of care gaps arising from incidental findings in imaging diagnostics. By implementing Proactive Follow-Up automated solution, care providers were able to revolutionize their care delivery system, resulting in improved patient outcomes, enhanced efficiency, and a sustainable solution for the future.
Learn how our customized framework helped bring innovative AI-driven solution quickly to market.
Visit Siemens Healthineers for additional information on Proactive Follow-up