In our current society we find it important that every individual has a fair opportunity to receive the best possible care and outcomes, regardless of differences in income, ethnical background, age, or gender. To me, this is the definition of health equity. Still today, a lot of people do not have this fair opportunity as they are involved in a healthcare system that has perpetuated health inequities, also called health disparities. Ever since the ancient Greeks, health disparities have existed in society, but this topic has never been in the spotlight so clearly as today. The differences in health outcomes between people of different race and age during the COVID-19 pandemic increased our awareness about existing health disparities. It is now urgent to act to create more fair opportunities for everyone to be as healthy as they can be. This starts with the right collection and use of patient-level data.
Health disparities often remain unnoticed due to the way we aggregate and analyze data
Research has shown that health care outcomes are closely associated with what we call the social determinants of health, amongst which are one’s neighborhood crime level, access to places to exercise and basic health care, ability to get healthy foods and a good education. To discover health disparities in society, it is essential to make the differences in the social determinants of health measurable and traceable. Only then, we can analyze the influence of social determinants on a population’s health and take effective measurements. Currently, health data is mostly collected in a way where differences in social determinants of health can’t be stratified or interpreted. In the past, I have led a health equity affinity group for the Centers for Medicare & Medicaid Services (CMS) in which we created the Health Equity Organizational Assessment (HEOA). In this assessment, we looked at seven health equity-related categories to see how prepared the institutions were to identify and address health disparities. Over 2,300 hospitals participated in the HEOA, and we discovered that although they collect a lot of data, they don’t validate or stratify it. And when they do disaggregate their data, they don’t know what parameters to compare and what measurements to take to achieve health equity. If we keep working with aggregated data and don’t become aware of the measurements that can be disaggregated to identify patients with disproportionately worse outcomes (health disparities), we won’t be able to improve outcomes enough to substantially reduce the cost of care to sustain the current health care system.
Using REAL data as a fundamental base for achieving health equity
A proper analysis of disaggregated data starts with accuracy and completeness of the data. To create complete and inclusive data, it is first and foremost pivotal to categorize and collect the raw data consistently. The use of the “REAL” data framework can aid in patient-level data collection, -reporting, and -analysis. REAL in this regard stands for Race, Ethnicity and Language, which are the most important factors to stratify. The process of disaggregation and stratification helps us to find our most vulnerable patients. By looking at predefined process and outcomes quality measurements and how they differ between patient populations, we can get insights into where our care processes need adjustments to make sure they’re working for all patients. Being able to collect accurate and complete patient demographic data is the key to an effective health equity strategy for any health organization. In fact, REAL data collection, reporting and analysis is and has been a top priority area under the CMS Equity Plan for Improving Quality in Medicare.
An illustrative example of quality improvement due to REAL data-driven decision making is that of the Seattle-based Harborview Medical Center that noticed patients were often showing up for their colonoscopies unprepared. When the hospital started disaggregating the data by language, they uncovered that mainly Spanish- and Vietnamese-speaking patients were showing up unprepared. Based on these insights, they started offering preparatory classes and materials in Spanish and Vietnamese, after which their rates of success and improvement significantly increased. Consequently, their appointment cancellation rate went down, and patient care could take place faster and more efficient. Another hospital system called Novant Health, based in North Carolina, wanted to improve their readmission rates for pneumonia, a condition that is commonly associated with high readmission rates. When they disaggregated their readmissions data, they found that African Americans in their hospital had by far the highest rates of pneumonia admissions. They got a workgroup together, used traditional performance- and quality improvement tools (e.g., did chart reviews, interviewed patients and staff), and found some very specific things that they could do that would decrease the African American readmission rates.
Making healthcare more equitable starts with awareness and courage
Besides the fact that health equity interventions make a huge impact, they don’t have to be complex nor expensive. Most healthcare administrators seem to think that they need to build a farmers’ market or rent housing for patients to achieve health equity. In fact, they simply need to ensure that they are delivering equitable care through examination of disaggregated process and outcomes quality measurements. Yet, health equity strategies that utilize this type of examination are uncommon and I think that a lack of awareness and the fear of bad publicity play an important role as to why it is not utilized.
The good news is that more and more health care institutions are committing to provide more equitable health care and there are excellent cultural humility and personal leadership trainings that tackle unconscious bias in health care, including the effect of social determinants of health on the ability of people to be healthy and have good health outcomes. Working toward health equity is a journey and it takes some courage from healthcare administrators to face the facts. Fortunately, more and more research is being done on the topic of health disparities, increasing awareness and the sense of urgency among healthcare administrators. Take for example the recent report by the Agency for Healthcare Research & Quality, in which 250 quality measurements were studied and 40% of these measurements were reported to have worse outcomes for Black and Indigenous People of Color than for White people. For example, delayed medication administration for Black patients experiencing heart failure as compared to Whites. It is now time to act upon these statistics with the right quality measurements disaggregated by patient demographics and learn from organizations that are already doing this.
Governments should take their responsibility in achieving health equity
Inspired by the Rush University Medical Center in Chicago, what I would love to see as the gold standard for any healthcare institution in the future is an annual Health Equity Report. This type of report looks at patient care and outcomes through an equity lens, laying out all health disparities that the institution found. This takes courage from healthcare administrators, but it also requires governmental support, for example by having it become a mandatory part of the Community Health Needs Assessment (CHNA), which hospitals must already do every three years in the U.S. Additionally, governments must protect the privacy and ownership of health data, especially with the emergence of Big Tech companies like Apple and Amazon continuing to move into the healthcare industry. However, I believe that these companies can also play a crucial role in disrupting healthcare access and analytics, improving relationships between patients and healthcare professionals, and bringing personalized care closer to the patient. In this way, potentially, Big Tech could be an important accelerator of health equity in the future. Together, we can all work toward a fairer and more equitable health system.
