The 80% Problem: Leveraging Data to Achieve Health Equity

More than 80% of your health status is dependent on social determinants of health, such as where you live and work, the air you breathe, your transportation, the water you drink, and whether you use tobacco or other drugs. These factors also can – and do – impact your access to healthcare, critical resources, and opportunities for wellbeing. 

Underprivileged and underserved populations do not have the same access or opportunities as others in our society, and they feel these inequities acutely with poorer health and higher mortality rates. Yet, everyone feels the effects of unhealthy communities and rising healthcare costs. 

Health inequity is entrenched and systemic in global healthcare. The life expectancy gap between low- and high-income countries can be as high as 18 years.2 Inequities account for more than $320B in annual healthcare spend in the U.S. alone and is anticipated to grow to $1T by 2040.1 This path is repeated in many countries worldwide, which overwhelms the system and is not sustainable. 

Just as technology has improved so many other parts of our lives, it could also advance health equity by eliminating barriers to the tools, resources, knowledge, and opportunities we all need to be as healthy as possible. 

Data is at the heart of advancing health equity. People, whether as patients, caregivers, community leaders, or public health officials, need clean, usable, trustworthy data to take meaningful action. To advance health equity, we need to understand social determinants of health along with information from claims data, research, operations, and community risks. A patient’s physical environment, health-related behaviors, and economic factors make a profound difference.

Bringing all this data together in a meaningful way will be transformative. While clinical data is flowing through information exchanges, most data that impacts a person’s health is siloed and disconnected, existing outside the hospital’s electronic health record system. That is why we are building an open, intelligent, cloud-based healthcare platform – to connect clinical and enterprise systems for organizations and to bring in data like social determinants of health or community risk factors. We’re removing the siloes and connecting disparate systems. 

At an individual level, technology can give caregivers a holistic view of a patient’s health through a single, longitudinal health record. This enables them to address all aspects of a person’s condition including non-clinical factors. At a community level, technology supports leaders with a full picture of their community’s health and risk. With better information, they can more effectively reach and treat different segments of the population, direct resources, programming, and interventions equitably, and create policies that lead to health justice. 

With a cloud-based health platform, we can also extend data across the healthcare ecosystem, making it available for researchers and scientists. Advancing health equity includes ensuring everyone has access to the newest and most innovative therapies available. Technology enables life sciences companies to connect with healthcare providers, their clinicians, patients, and communities to expand access to clinical trials. This results in more diverse study participants, which means researchers have more representative, complete, and comprehensive patient information to validate the safety and efficacy of treatments. 

Oracle Health’s Learning Health Network includes over 100 healthcare delivery organizations dedicated to sharing de-identified data to advance clinical research. With more than 100 million patients represented, diversity has become the network’s superpower. Clinical trials run through the Learning Health Network have three times the U.S. average of Black and Hispanic participants. Individuals, clinicians, and communities who have never had the chance to participate in clinical discovery can now do so, gaining access to leading therapeutics, diagnostics, and medications sooner. 

Technology comes with its own challenges in equity, so we have an obligation to be responsible stewards of patient data. Artificial intelligence (AI) and machine learning could be game changers as we look to solve healthcare’s biggest challenges like burnout and cost. Since healthcare data represents real people and real situations, we need to be careful that any technology relying on this data does not further exacerbate the biases and inequities that exist today. 

For example, healthcare providers have been using clinical calculators for decades to estimate risk and predict outcomes. Yet, many of these calculators include race as a data element, which is not evidence-based and can cause harm to segments of the population. Ethical AI begins with incorporating equitable and just principles into the design, development, delivery, and analysis of products, solutions, and services. Plus, in partnership across the healthcare ecosystem — especially with researchers — we need to evaluate new technologies for potential bias, eliminate it, and evaluate the results.

In short, with more data and better information, we have an incredible opportunity to create a better healthcare system that improves lives and experiences for patients, caregivers, and communities around the world regardless of economic status or geography. It will take all of us working together to achieve this. Now is our time for action.