Mental Health During the Pandemic and How Predictive Analytics Can Help

by | Dec 14, 2020 | Healthcare

With the COVID-19 pandemic still at large, and a vaccine is still months away from having an impact on slowing it down, most people are still doing their part to slow the spread by staying at home as much as possible. The pandemic is something that none of us could have predicted or prepared for in this day and age, and it has resulted in countless changes such as the way individuals go about living their daily lives, the way businesses operate, and the way hospitals and healthcare organizations conduct procedures and protocols – just to name a few. All of that being said, it’s not a surprise to hear that mental health issues among individuals of all backgrounds are one of the greatest effects of this global pandemic. In Episode 10 of the Smarter Healthcare Podcast, Krithika Srivats, vice president of the health/clinical center of excellence at HGS Healthcare, discusses how the pandemic has affected mental health, which populations are more impacted, and how predictive analytics can play a role in improving the situation.

Increasing psychological distress

In early June, a survey posted by JAMA found that among 1,468 adults, 14 percent of people had high levels of psychological distress compared with an average of 4 percent during the pre-COVID era. Six months later with the pandemic increasingly getting worse, the numbers are thought to be much higher. Srivats discusses a more recent survey that was conducted by Kaiser Family Foundation which found, “People who already have a risk factor for their mental health issues, including anxiety, eating disorders, et cetera, have a higher potential to be led all the way into depression. In addition to that, I think there’s also a significant rise in some of the downstream impact on it, Srivats continues. “This being, like, a rise in substance abuse all of a sudden. The same survey finds I think about 12% of folks are now newly addicted to substance abuse since the pandemic.”

While individuals of all backgrounds are experiencing 2020’s newest mental health crisis around the world, BIPOC (Black, Indigenous, People of Color) communities are facing the mental health crisis head-on, some with even more severe effects. MedicalNewsToday states that past research has shown that African American, Native Hawaiian, Hispanic, and Asian individuals have higher rates of post-traumatic stress disorder (PTSD) than white individuals. For example, this could mean Black individuals reliving traumatic events of police brutality and oppression towards their people while simultaneously living through the hardships of the COVID-19 pandemic or those of Asian descent experiencing racist and xenophobic violence and discrimination towards their community due to the racist statement that anyone of Asian descent is at fault for the COVID-19 outbreak.

High-risk vulnerability

In addition to BIPOC communities being affected by the pandemic, individuals of high risk are also more vulnerable to mental health issues. “Specific to COVID if you look at the vulnerabilities it’s either because people have a high exposure to getting COVID, or upon being exposed to COVID, they have a higher risk of having a debilitating outcome,” says Srivats. “Research has it all the way from 50 to 70% of elderly, of the deaths, have been in people with higher vulnerability as a result of COVID… Most people pre-COVID, and who are above the age of 70, actually were found to have complained of social isolation and loneliness, about at least, I think 33% of folks were found to have complained of social isolation pre-COVID, and that significantly exacerbated since the COVID lockdown for them. Socialization has been a major issue and that’s been one of the biggest vulnerabilities.”

The impact of predictive analytics

How can predictive analytics and other technology help support these vulnerable populations? “Historically when you wanted to identify what are the risk factors [of an individual], you went to the physician or nowadays their health insurance company, who maintain a fairly large profile of an individual across all the diagnoses and conditions that they’ve been treated for,” says Srivats. “But if you look at that, that’s just the medical data. Whole person is a lot more than that, right?”

Children’s Hospital of Philadelphia is one example of how healthcare workers and those in the industry are using predictive analytics to help highlight high-risk areas and populations in regard to COVID-19. PolicyLab developed a model which uses weather to predict how coronavirus may affect certain areas in relation to factors like outdoor temperatures and humidity levels, but it also takes into account data such as a county’s demographics or population density – which all affect how high the risk for contracting the virus may be [due to factors such as poverty level].

Chicago-based CommonSpirit Health created a system which uses predictive analytics to “examine the COVID-19 infection rates for communities across the U.S., taking into consideration fixed data including population and availability of healthcare providers” as well as other variables.

The development of these types of predictive analytics tools as well as medical professionals utilizing them is extremely important and is relevant to the world’s mental health crisis. Factors such as how vulnerable an individual really is or how much access they have to socially distanced areas may seem mundane, but they should not be ignored. Using these analytics can ultimately help slow the spread of the virus by pinpointing the most vulnerable populations and therefore helping reduce the rising cases of mental health crises or at the very least helping find more outlets and accessible resources and treatment for vulnerable populations as well as the general public.

“There is a shortage in trained formal caregivers, specifically in the mental health areas. You leverage upon volunteers, you leverage upon community resources, health coaches that are available in the community to get to those people and then hand off and triage it to those trained clinicians for the specific interventions but at least now you have a mechanism for people to identify, acknowledge, take information about them and then triage it to the clinicians, so in that process you don’t make the person just wait around on getting them the right trained help and you have a process, a mechanism, for them to be connected along the way,” says Srivats. “Cogitative behavior therapy and motivational therapy are also well-evidenced to be highly effective in people who are at the earliest stages of or lowest risk of really having a full-blown mental health episode. And a lot of these coping strategies really look at the whole person again, and not just at the current moment of what they’re going through, but also connects with them at the physiological as well as spiritual context to be able to help them cope with some of their issues.”

To listen to the full episode of the Smarter Healthcare Podcast and to learn more about Krithika Srivats, click here.

Lindsey Berke

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