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المحتوى المقدم من Listening In (with Permission...) and Catalyst for Payment Reform. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرةً بواسطة Listening In (with Permission...) and Catalyst for Payment Reform أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
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Episode 103: Dr. Irene Dankwa-Mullan on why every employer needs a health equity strategy

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Manage episode 302274767 series 1602067
المحتوى المقدم من Listening In (with Permission...) and Catalyst for Payment Reform. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرةً بواسطة Listening In (with Permission...) and Catalyst for Payment Reform أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
Suzanne Delbanco speaks with Dr. Irene Dankwa-Mullan, Chief Health Equity Officer at IBM Watson Health and Deputy Chief Health Officer within the Center for AI, Research & Evaluation. As an industry physician and scientist working at the intersection of AI, health equity, and health care, Dr. Dankwa-Mullan speaks to best practices for employers interested in measuring and addressing health inequities being experienced by those in their health benefits program, building on a Health Affairs article that she co-authored in December of 2020. Dr. Dankwa-Mullan cites definitions pioneered by Dr. Paula Bravemen for understanding what health equity and health disparities signify in the context of health care benefits. Health equity calls on stakeholders to focus on the unfair differences in health experienced by social groups based on the varying degrees of social advantages and disadvantages conferred to these groups, often across socially constructed racial and ethnic groupings. Diving deeper, Dr. Dankwa-Mullan highlights the lack of a uniform approach to collecting race and ethnicity data for use in addressing disparities. Amidst the lack of standardization and other challenges, the most important best practice is to have patients and/or plan members self-identify their race, ethnicity, primary language, and other cultural attributes that are important to their identity. Self-identification avoids inaccurate and incomplete categorizations. As employers and other stakeholders know all too well, health care benefits are a costly line item in any organization’s budget. But inequitable health care adds even more costs. Dr. Dankwa-Mullan offers the following rationales for why employers should collect and measure health statistics by race and ethnicity. 1. To ensure that the employer’s investment is reaching the full covered population in an equitable manner 2. To discover opportunities to improve population health 3. To demonstrate an organizational commitment to health equity Altogether, Dr. Irene Dankwa-Mullan highlights the need for employers and their business associates – including TPAs, consultants, and other partners - to acknowledge that health inequities exist and use their role as plan sponsors and benefits administrators to address them through comprehensive, data-driven, health equity strategies.
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iconمشاركة
 
Manage episode 302274767 series 1602067
المحتوى المقدم من Listening In (with Permission...) and Catalyst for Payment Reform. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرةً بواسطة Listening In (with Permission...) and Catalyst for Payment Reform أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
Suzanne Delbanco speaks with Dr. Irene Dankwa-Mullan, Chief Health Equity Officer at IBM Watson Health and Deputy Chief Health Officer within the Center for AI, Research & Evaluation. As an industry physician and scientist working at the intersection of AI, health equity, and health care, Dr. Dankwa-Mullan speaks to best practices for employers interested in measuring and addressing health inequities being experienced by those in their health benefits program, building on a Health Affairs article that she co-authored in December of 2020. Dr. Dankwa-Mullan cites definitions pioneered by Dr. Paula Bravemen for understanding what health equity and health disparities signify in the context of health care benefits. Health equity calls on stakeholders to focus on the unfair differences in health experienced by social groups based on the varying degrees of social advantages and disadvantages conferred to these groups, often across socially constructed racial and ethnic groupings. Diving deeper, Dr. Dankwa-Mullan highlights the lack of a uniform approach to collecting race and ethnicity data for use in addressing disparities. Amidst the lack of standardization and other challenges, the most important best practice is to have patients and/or plan members self-identify their race, ethnicity, primary language, and other cultural attributes that are important to their identity. Self-identification avoids inaccurate and incomplete categorizations. As employers and other stakeholders know all too well, health care benefits are a costly line item in any organization’s budget. But inequitable health care adds even more costs. Dr. Dankwa-Mullan offers the following rationales for why employers should collect and measure health statistics by race and ethnicity. 1. To ensure that the employer’s investment is reaching the full covered population in an equitable manner 2. To discover opportunities to improve population health 3. To demonstrate an organizational commitment to health equity Altogether, Dr. Irene Dankwa-Mullan highlights the need for employers and their business associates – including TPAs, consultants, and other partners - to acknowledge that health inequities exist and use their role as plan sponsors and benefits administrators to address them through comprehensive, data-driven, health equity strategies.
  continue reading

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