Empowering Our Communities with Data
Clinical trial diversity and inclusivity are the keys to discovery in evidence-based medicine and health care.
The power of clinical data to drive equitable insights cannot be overstated. It is through the power of clinical data that systemic, environmental, and intergenerational processes of disease and illness can be understood and ameliorated.
The demographic composition of the United States is changing. There is a lack of representation of communities of color in clinical trials. Increasing diversity and supporting equitable participation in clinical trials is vital. Engaging community clinicians in research is one way we can empower communities with clinical data.
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Significant health inequities plague the U.S. healthcare system, impacting historically marginalized and minoritized communities. Individuals often experience higher rates of diabetes, adverse mental health outcomes, hypertension, obesity, asthma, heart disease, cancer and preterm birth.
The lack of comprehensive data and archaic standards for collecting data contribute to the growing health equity gap. The Office of Management and Budget’s (OMB) data collection standards remain static. The 30-year delay in updates challenges the ability to accurately identify and appropriately address health disparities.
Data standards are the gatekeepers of insights. Decisions derived from data are only as useful as the quality of data itself. It is imperative that the conversation around the expanding world of data and data analytics is underpinned by high-quality data. Ensuring data standards are upheld means that data are collected, stored, accessed, extracted, transformed, analyzed, and interpreted in predictable and consistent ways.
By adopting robust and comprehensive race, ethnicity, language (REL), sexual orientation and gender identity (SOGI) data, health entities can better monitor data access utilization and design sustainable community interventions that support health outcomes.
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Analytical methodologies are always transforming and expanding. The rapid insights driven by the analysis of high-dimensional, multifactorial datasets are unparalleled in their utility and application. More data is generated, recorded, analyzed, and interpreted every instant. Increasingly, our society is relying on complex and massive datasets for which traditional methods of analysis are limited and inappropriate.
Artificial intelligence is expanding frontiers in medicine and health care. AI can play a crucial role in analyzing vast amounts of healthcare data collected by NMQF, especially related to minority health disparities. AI-powered predictive analytics can help forecast health outcomes and disease prevalence among minority populations.
By employing AI algorithms, patterns, trends, and disparities within minority communities can be identified more efficiently, providing valuable insights for policymakers, healthcare providers, and community organizations. AI is enabling key stakeholders and clinicians to predict and improve outcomes, increase speed and precision of cancer screening without increasing cost. This capability allows NMQF to anticipate health challenges and allocate resources effectively to address them during National Minority Health Month and beyond.
Email dmshake [at] nmqf.org now to join our cohort of experts, academics, research scientists, stakeholders interested in the future of artificial intelligence in health equity.
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