Healthcare leaders are increasingly aware of the power of technology and augmented intelligence (AI) to impact health equity. However, due to inconsistent collection of personal characteristic data (i.e. race, ethnicity, and language), multiple source systems that categorize and store characteristics differently, and no specific analytics for health equity, this task is overwhelming and often seems unattainable. By building a systematic approach to evaluating health equity as a core part of its commitment to quality, your organization can apply AI to perform an equity analysis that evaluates a range of measures over multiple dimensions to identify success and opportunities for improvement.
