By Emily Li
One of the major contributors to the federally declared disaster in New Orleans after Hurricane Katrina was the massive flooding that occurred once the levees surrounding the city could no longer hold back the water.
When they broke, they unleashed raging rivers that washed over the streets and quickly placed large sections of the city several feet under water.
Now, some 15 years later, another type of flood is ready to occur. Only this time it isn’t limited to one city, or even one region, but instead is preparing to overwhelm the entire country: The flood of patients/members with chronic conditions who will be seeking care once the latest COVID-19 surge has passed.
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Health plans and providers recognize that within this river of patients some have urgent needs to address significant care gaps while others are managing their conditions well. How to prioritize given limited resources during pandemic? That’s a problem, because focusing on the wrong patients/members first, (i.e., those who don’t have emergent needs and risks right now) can have a huge impact on healthcare outcomes and costs in the future.
Healthcare organizations also acknowledge that simply committing to closing care gaps isn’t enough. They need to understand the impact closing those gaps will have so they can set priorities and protect their most vulnerable populations not only from COVID-19 but from the long-term health issues their conditions can create.
This is where advanced analytics that goes beyond clinical information to incorporate social determinants of health (SDOH) factors adds tremendous value. It can help healthcare organizations sort through the pent-up demand to ensure all patients are receiving the most appropriate levels of care. They can also ensure that the organizations’ internal resources are being used to deliver the maximum benefit to all their patients/members.
Step one in this process is using analytics to predict the regions, and patients/members, who will have the greatest need. By matching publicly available information on COVID-19 hot spots, which indicates where self-care on chronic conditions was likely paused, against existing data on patients/members, including underlying conditions, clinical gaps, and SDOH barriers, they can quickly prioritize their populations and generate a risk score for each. The higher the risk score, the higher that an individual should rise on care managers’ outreach lists.
Once they reconnect with patients/members, providers can use analytics to determine which interventions will have the greatest impact on reducing risk, as well as how they should be delivered. If hands-on healing isn’t required, providers might opt for a telehealth visit, supplemented by patient-generated data from consumer devices. Conversely, if laboratory tests, imaging, diabetic eye exams, or other tests are required, they will need to set up an office visit.