Most Population Health programs utilize retrospective healthcare data to identify patients and the health system’s compliance with targeted performance measures. HCIS, partnering with innovative healthcare systems, is paving the way forward to deliver Prospective and Predictive Population Health Management through the use of Artificial Intelligence (AI) and Machine Learning (ML). The integration of AI/ML models within forward-looking population health platforms, such as HCIS’s Measures Manager, not only provide an opportunity for increased financial reimbursement through higher quality metric scoring but most importantly gives providers and their population health teams a chance to deliver greater quality and achieve better patient outcomes, faster.
Traditional population health programs are based on retrospective healthcare data. This creates an inherent disadvantage because they utilize data which over time becomes less relevant; resulting in the inability to proactively manage attributed patients. The current state of retrospective healthcare data can significantly benefit from a prospective approach allowing program managers to gain advanced insights into their patients.
HCIS and its partner health systems are leading the way to optimize population health performance by bringing together an innovative AI-enabled platform, Measures Manager, and subject matter experts to address high-value use cases such as QIP-NJ.
In summary, using AI and ML models to proactively manage patients within population health programs, we are able to gain tangible benefits such as:
- Leveraging existing data sources to prospectively manage patients and identify potential performance issues.
- Make predictions about patients and cohorts.
- See trends in target populations.
- Determine if there are systemic issues, such as bias, affecting specific populations.
- Pre-determine patient attribution with a high degree of accuracy.
Ready to learn more?
QIP-NJ participants – contact our population health experts and sign up for updates to hear from HCIS, including an invitation to our February webinar.