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Bringing the real world into the exam room


Why whole-person health begins with non-clinical needs.

cartoon exam room | © Zentangle - stock.adobe.com

© Zentangle - stock.adobe.com

What you see is what you get. While this adage holds true for many aspects of life, those of us in healthcare know that things are a bit more complicated. Within clinical settings, what you see represents only a small fraction of the full story. Instead, we know that up to 80% of a person’s health is determined by invisible, non-medical factors: social drivers of health (SDOH).

I was recently reminded of this through an anecdote that was shared with me by one of our provider clients. Their care team was puzzled over an eight-year-old patient who had been previously healthy, but since his mother had become pregnant, had been coming into their local health center regularly with lethargy and stomach pains; he was rapidly losing weight. Once bubbly and gregarious, he had recently become withdrawn and spoke only in whispers. The team had tried everything – medicines, allergy tests, and depression screenings.

That is, until at one appointment, a baffled doctor paused and asked perhaps the most simple question of all: “Have you been eating, son?” The boy paused, then thoughtfully replied: “Well, mom is growing my little brother. I give her my food so that the baby can grow strong too.”

Within thirty seconds, the mystery was solved. For the clinical team, this reinforced one of the most valuable lessons of healthcare today: these unseen, non-superficial risk factors are driving outsized impacts on our population’s health and well-being.

That’s why it has become more important than ever to stop and ask: What risk factors exist right under our noses? It is up to us to look beyond what we can see on the surface to deliver truly comprehensive, equitable care. Essential to this approach is striking a healthy balance between data and patient stories. By harnessing data to tell stories, we can identify health risks, unmet needs, and populations who need clinical attention.

In the sections that follow, I’ll outline three necessary steps that can help guide healthcare stakeholders as they work to advance equitable, high-quality care for everyone.

1.High-quality care begins with high-quality data

Some organizations are new entrants to population health; others have advanced health equity strategies proactively addressing gaps in care. Regardless of their relative SDOH strategy, maturity, size, or budget, every organization must begin with the very same ingredient: high-quality data.

Inaccurate, incomplete, or unreliable data can be misleading. And, the dangers of this bad information are endless – for patients this can mean critical lost time to diagnosis, and for providers, loss of credibility. For an organization, this can mean misinformed strategic approaches, lost revenue, and most of all, inaccurate information that impacts patient care.

Clean, well-populated data sets are essential. They are the building blocks of patient stories at scale – within the data are trends, insights, and predictive models just waiting to be extrapolated. At its most simplistic, it’s giving care teams the information they need to improve the care of their patients – providing actionable insights that can drive meaningful change.

2.Think big, but act small (in stages)

While it is tempting to begin a population health journey by dreaming about its ending – such as cost savings and higher quality outcomes – the truth is that the pathway is winding, long, and ever-evolving. Rather than looking to increase a well visit rate from 15% to 60% in a year, look to reach smaller, more attainable goals. It may sound simple, but the road to 100% becomes closer as you pass each benchmark, and these paradigm-shifting strategic goals begin to feel less out of reach.

At this interval, thinking big (but acting in small leaps) is all about asking the data the right questions. Rather than looking to broadly improve quality scores off the bat, dive deep into the information you have at hand. For instance, you could ask: which cohorts are missing cancer screenings regularly? Why is that? To understand, look at the patterns that emerge. Which quality measures are lagging the most? Are there similarities between the groups regularly scoring the lowest? Perhaps it's a transportation issue. Now, consider how your organization can adjust to better engage these individuals and help them secure rides to improve their access to care.

When organizations ask the right questions, and begin to make incremental, informed, and standardized process changes, outsized impacts are sure to follow. The best benchmark is another question: will we be doing better tomorrow than we did today?

3.Know your population(s)

Lastly, take the time to get to know those you are responsible for. Make sure you understand the services they need – and the non-clinical factors impacting their access to care. The best care is contextual and comprehensive. For instance, if an individual walks into a clinic with strep throat, a provider might offer a prescription drug that requires refrigeration. Based on all available presenting clinical symptoms, this is commonly considered comprehensive care.

If, instead, the provider is presented with a profile that correctly identifies this patient’s food risk and lack of access to stable housing, the course of treatment will likely be very different. For starters, the doctor would recommend a non-perishable drug, and also connect that individual to social services and a food bank. This is truly comprehensive care that can make a difference. And it’s only possible when you know what your patients need, how to engage them, and how best to support them.

By leveraging available data to better know your population and their unique needs, you’ll learn how to deliver the right care at the right time to make an impact across the board - on quality outcomes, resources, and spend alike - but most importantly the health and well-being of the patient.

Adopting a data-driven approach to care

Remember the eight-year-old who was not eating to give his pregnant mother extra food? In this case, advanced data models might have predicted the food insecurity risk for him and his family before he was ever impacted, but a few extra questions could also inform the same conclusion. His care team could have recommended local resources that offer fresh food stipends, healthy school lunches, or community fridges. Perhaps his illness could have been prevented by simply uncovering underlying non-medical needs much earlier in the process.

As healthcare stakeholders, this is our goal. Keeping that eight-year-old, and millions like him, as healthy as possible – before medical intervention is needed. To get to that point, though,begin with small, realistic steps. Steps like implementing standardized screening questionnaires – universal, equitable documents that ask the right questions to unearth risks that may exist just beneath the surface.

This is what it looks like to adopt a data-driven approach to whole-person care. The steps are simple, interconnected, and iterative: collecting high-quality data and learning to ask the right questions to guide the most appropriate care helps organizations understand their populations and begin to change lives. Only once we begin to activate accurate data within clinical settings to contextualize patients’ lives, can we begin to make an impact at scale.

Jeff Brandes is President & CEO, Azara Healthcare, the 2023 Best in KLAS provider of population health management solutions, and leading provider of quality measurement, analytics and reporting for the Community Health and physician practice market.

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