Summary:
Addressing inequities in healthcare delivery and service is crucial to achieving equitable healthcare for all populations. Underserved areas such as rural communities (when compared to urban areas) are characterized by a higher percentage of older adults, higher rates of all-cause mortality, and lower density of healthcare infrastructure. Available evidence suggests that these poor health outcomes and inequities – further exacerbated by the COVID-19 pandemic – are driven in part by social risk factors (e.g., the social determinants of health) and biological risk factors (e.g. older age and chronic disease).
While COVID-19 has had a profound impact in exacerbating healthcare inequities, it has provided opportunity to identify, develop, deploy, and evaluate innovative technological advances such as AI, 5G, biosensors, apps, and beyond that can improve health access and outcomes in older adults, especially those from underserved populations (e.g. low-income, Medicaid-eligible, and rural communities).
Against this backdrop of widening healthcare disparities and inequities, and in an effort to build upon previous federal efforts to leverage data and technology to improve patient outcomes, access, safety, quality, cost, and value for aging populations in underserved areas, OASH, in partnership with other federal agencies issued a request for information (RFI) to gain a comprehensive understanding of innovative efforts around chronic disease management for aging populations in underserved settings by leveraging technology-driven solutions. The responses – from a diverse set of external stakeholders including academia, hospital systems, insurers, and digital health firms among others – revealed opportunities to develop, operationalize, and scale innovation in healthcare delivery at the individual and population levels with several broad themes emerging:
- Increase awareness, trust, and understanding around the products and social services available to patients is critical towards improving health outcomes.
- Person-centered design remains critical to ensure increased adoption of solutions by older adults, given this group often experiences age-related physical, cognitive, and sensory deficits atypical of other population segments.
- Solutions must be culturally and linguistically competent, accessible to individuals with varying levels of education attainment, digital literacy, healthcare fluency, and embedded with privacy and security safeguards tailored to an individual’s needs.
- Insufficient knowledge and understanding of solutions can lead to disuse, distrust, and skepticism around the accuracy, effectiveness, and reliability of a solution.
- Integration of novel solutions to existing clinical settings, platforms, and systems, along with complementary education and training of healthcare professionals (including caregivers) to ensure effective implementation.
- Desirable infrastructure needs (e.g., broadband, mobile connectivity, hardware, etc.), associated costs, and lack of provision for end-user access pose significant barriers to the adoption of solutions.
- Balkanized data standardization practices, proprietary electronic health record systems, and data sources that are not “linked” together via interoperability make it difficult to ensure high quality, accurate, and verifiable data is collected for analysis and evaluation.
- Embedded within solutions should be principles of transparency, iterative improvements based on user-generated feedback, and validation by internal stakeholders and independent third parties.
- Essential to minimizing bias and variance in AI-driven interventions and tools and boosting their subsequent fidelity, is the use of training datasets representative of the communities of interest.
Emerging technologies have a role to combat health disparities. Insights gathered from this RFI provide context to the policy and programmatic landscape in support of the design, development, deployment, and evaluation of these technologies in communities nationwide. While we share a few of the broad insights above, we continue to analyze the input from external stakeholders to help shape future federal efforts towards leveraging data and technology in service of our nation’s older Americans.
