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The Analytic Foundation of a Robust Population Health Management Program

Health Dialog

Most risk-bearing organizations, including health plans, accountable care organizations (ACOs), and self-funded employers deploy some form of analytical strategy to inform their approach to population health management. But what that means could be as wide-ranging as: Using registries to track compliance with quality measures.

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Best Practices in Applying Analytics to Population Health Management Programs

Health Dialog

The primary goal of any population health management program is to improve health outcomes. These improvements in health outcomes should be measurable and analytics are front and center in the process to achieve this measurability. Five Best Practices in Applying Analytics to Population Health Management Programs.

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AI-Powered Pop Health and SDOH – The Good, The Bad and The Best Practices

HIT Consultant

Artificial intelligence (AI) has emerged as a powerful tool for making population health analytics more accurate and interventions more effective. They can also benefit from building on the best practices and hard-won wisdom developed from effective pop health interventions for SDOH communities in recent years.

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How to Use Analytics to Guide the Day-to-Day Operations of Your Population Health Intervention

Health Dialog

In a previous blog post, we emphasized the three pronged analytic strategy that risk-bearing organizations should employ when implementing chronic care management and other population health programs. In this post, I will review the final component of the strategy we have outlined: Quality Assurance – the best practice.

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Inovalon Launches Race & Ethnicity Data Enrichment Offering for Health Plans

HIT Consultant

– What You Should Know: Inovalon , a provider of cloud-based software solutions empowering data-driven healthcare unveils a new data enrichment offering that allows health plans to improve the completeness and accuracy of race and ethnicity data for their members. Challenges Capturing Race & Ethnicity Data.

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Racial Bias in Algorithms: How One State is Leading the Charge

NASHP

In June, the World Health Organization (WHO) released a report on Artificial Intelligence (AI) in health and six guiding principles for its design and use, noting that “AI holds great promise for improving the delivery of healthcare and medicine worldwide, but only if ethics and human rights are put at the heart of its design, deployment, and use.”

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Why Health Plans Are Vital to Health Equity

HIT Consultant

Evidence of implicit biases among healthcare professionals fuel distrust of the healthcare system as a whole. However, COVID-19 illuminated the disproportionate impact of many diseases on specific populations, including Native American, Black and Latino communities. These are solid first steps toward change.