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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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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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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. Code is written by humans who have unconscious biases, and those biases can creep into the algorithms of AI when Quality Assurance functions are not properly sensitized to detect them.

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NCQA Launches Race and Ethnicity Stratification Learning Network

HIT Consultant

What You Should Know: – The National Committee for Quality Assurance (NCQA) today launched the Race and Ethnicity Stratification Learning Network, a free, interactive, online tool that offers data and best practices to help health plans improve how they collect race and ethnicity data on their enrollees.

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Inovalon Launches Race & Ethnicity Data Enrichment Offering for Health Plans

HIT Consultant

These challenges can affect the completeness of population data and hinder efforts to incorporate race and ethnicity data into holistic member-centric care and intervention planning, which can also significantly impact a health plan’s overall quality ratings. While promising, some indirect methods pose challenges as well.

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

NASHP

NCQA recently updated their Health Plan Accreditation Population Health Management (PHM) standard category to require organizations to assess its segmentation or stratification methodology for racial bias.