Population health management (PHM) aims to improve the health outcomes of a group by monitoring and identifying individual patients within that group. A robust data infrastructure is fundamental to the success of PHM programs. It enables the collection, analysis, and sharing of health data across various platforms and stakeholders, facilitating informed decision-making and effective management of patient populations.
A comprehensive data infrastructure supports:
Information-Powered Clinical Decision-Making: By integrating and analyzing datafrom diverse sources, healthcare providers can make evidence-based decisions tailored to individual patient needs.
Identification of High-Risk Patients: Advanced data analytics can stratify patient populations to identify individuals at higher risk, allowing for targeted interventions.
Performance Monitoring: Continuous data collection and analysis enable healthcare organizations to monitor outcomes, assess the effectiveness of interventions, and make necessary adjustments to improve care quality.
While partnerships with accountable care organizations (Option A), business plans demonstrating cost savings (Option B), and patient satisfaction metrics (Option D) are important elements in healthcare management, they are not as foundational as a robust data infrastructure in establishing a comprehensive PHM program.
[References:, American Hospital Association – "Three Key Elements for Successful Population Health Management", aha.org, Southern New Hampshire University – "What is Population Health Management?", snhu.edu, , , , ]
