As we work to engage underserved communities in proactive, value-based medical treatment, we need to find ways to provide more granular data that accurately and precisely reflects the communities we serve. There is no more pressing issue than the advancement of care equity in a country so rife with disparities.
As we work to engage underserved communities in proactive, value-based medical treatment, we need to find ways to provide more granular data that accurately and precisely reflects the communities we serve. There is no more pressing issue than the advancement of care equity in a country so rife with disparities.
So following the aptly themed “Black Health and Wellness” Black History Month this year, I think it’s appropriate to reflect on the population health management challenges that continue to undermine the health of African Americans and other underserved populations.
We don’t need more data, we need better data
As our industry’s understanding of health inequity progresses beyond yesterday’s theoretical arguments grounded in access to care and various downstream effects of poverty, we look to data and analytics to inform new approaches. The work ahead includes further exploration of the ways poverty impacts health behavior, and the role patient data (or lack thereof) plays in influencing outcomes.
Answers live inside this overlap, which is why volume and accuracy of patient data should be our primary focus. That includes, for example, supporting an informed approach to reimbursement and treatment decisions, mitigating the effects of self-selection by digging into patient history.
Marginalized groups interact less with the medical establishment than their more economically advantaged peers; our models need to take this into account. With better data, risk models produce better insights—a critical condition if payers are to successfully sync reimbursement structure with symptom-specific diagnosis and treatment.
Guided by Black History Month’s focus on the “many ways of knowing”—from Western medicine to birth workers, doulas, midwives and naturopaths—I am reminded that our pursuit of greater information access is grounded in the human instinct to always know more. And all knowledge-based pursuits produce great value.
What you don’t know will hurt you
As the healthcare field continues to focus on eliminating health disparities, we see all sorts of diverse activity, ranging from research to product implementation. There is a problem, however, with the basic structures of our healthcare system. Our costs far exceed other countries, and our outcomes lag far behind.
This failure is a product of dysfunctional feedback loops and little to no standardization. A system conceived of by separate private sector actors and influenced more by market forces than a desire for cooperation left us with a legacy of inconsistency across state legislation, payer dictates and privacy regulations. It’s a system that would make only Rube Goldberg proud.
Vulnerable populations bear the worst effects of this fragmented, inefficient and expensive system. Just look at the bill from your last visit to the hospital or clinic. Deciphering what was paid, by whom, and what you owe requires a level of sophistication that even those of us in the healthcare industry lack. One can only imagine the frustration and feelings of disenfranchisement for people less fortunate than us.
The mission of healthcare leaders needs to be centered around creating a platform that accelerates the remaking of this system so that product and solutions address our fractured landscape. For instance, by integrating AI and machine learning into products, we can tear down the barriers to cooperation. With the healthy exchange of information, we start rebuilding healthcare’s foundation block by block.
We know that certain patients have trouble keeping appointments due to a lack of reliable transportation. We know that some patients have less trust in medical professionals because of historical maltreatment. We know that access to technology and medical information varies broadly across population cohorts. With this knowledge comes responsibility, a responsibility to use the data we collect and the technological tools at our disposal to address these issues and make healthcare more accessible.
The provider paradox
Without a doubt, healthcare providers practice in an environment full of factors that complicate the delivery of value-based care. Value-based care is by nature demanding in its time sensitivity, location specificity and patient-determined response.
Good outcomes rest on the ability of providers to adjust seamlessly to a dynamic set of variables. Work like this relies on access to data that builds consistency, continuity and scalability across their practices.
How can providers successfully engage marginalized communities without good information? And once engaged, how does this same provider decide what treatment will work best at what time? The difficulties born of inadequate data handicap the healers.
Through the provision of better, more granular data, providers, patients and payers enjoy a streamlined, cost-effective healthcare experience. It’s a triple crown victory.
Fresh models, fresh data
Risk models play a huge role in how compensation and health vulnerability are determined. So it’s important to work toward improving analytics and the algorithms that inform these risk models.
The models used by payers today do not perform at a high enough level to produce well-functioning billing and treatment protocols. Faulty conclusions based on insufficient data have disastrous consequences for the entire healthcare apparatus. Doctors cannot provide the appropriate treatment for the presenting symptomatology because reimbursement problems arise when patient records don’t exactly match highly prescribed symptom clusters.
As a practicing physician, I know illness is both uniform and individual. No two patients make the exact same presentation; so, when payer regulations call for identical accounting, value-based care becomes far less achievable.
Inspiring change
There are so many sources to take inspiration from on the journey toward health equity. People of all backgrounds suffer from lack of coverage, geographical isolation and busy signals that make active engagement with providers almost impossible.
As better data ushers in an era of collaboration, we can expect more productive and open relationships with the communities who need it most. But wherever disproportionate needs exist, we must take steps to provide equitable access and care for all.