Identifying and Managing High-Risk Patients During COVID-19

71

By Dr. Seleem R. Choudhury, DNP

More people are infected with and have died from the coronavirus in the U.S. than anywhere else in the world, according to the available data at the time of this article’s publication (Andrew, 2020).  Even with these astounding numbers, researchers are almost certain that the number of COVID-19 cases in the U.S. have been significantly undercounted, since individuals with few to no symptoms are rarely tested.  

The extent and impact of the COVID pandemic is still emerging. Often when we talk about the virus, it is compared to the Spanish flu or other public health outbreaks.  Many in the healthcare industry point to the higher number of deaths in the second wave of the Spanish flu as a reason for grave concern. Though epidemiologists say the same, they also remind us that in the U.S., we are still experiencing the first wave. The second wave is yet to come. 

While the healthcare system is encouraging the entire population to practice the basic precautions for avoiding infectious disease transmission, studies show that a focus on those with complex chronic conditions should remain a priority, and is essential to minimize the number of COVID-related deaths (Vishnevetsky & Levy, 2020).

Estimating the number of people at increased risk of severe COVID-19 can help countries “design more effective interventions to protect vulnerable individuals and reduce pressure on health systems. This information can also inform a broader assessment of the health, social, and economic implications of shielding various groups” (Clark, Jit, Warren-Gash, Guthrie, Wang, & Mercer, 2020).  The outcome of this virus depends on employing a united approach to protecting the most vulnerable populations among us.

In strengthening population health intervention in the world of a COVID pandemic we must absorb, understand, and implement a strategy based upon the acquisition of knowledge. A simple model is Knowledge Translation (KT). KT strategies are designed to help develop a hypothesis based upon the understanding of the current research and applying it appropriately as an intervention or strategy (Wensing, & Grol, 2019).   At a community level this involves us identifying who is at high risk. 

Identifying high risk patients

According to a recent study published in The Lancet Global Health, 22% of the world’s population is at risk for severe COVID symptoms—that is 1.7 billion people worldwide (Clark, Jit, Warren-Gash, Guthrie, Wang, & Mercer, 2020). It is estimated that 4% of those people would require hospitalization if they were to contract the disease.  Out of the 20 most affected countries, the U.S. has the highest number of coronavirus deaths per 100,000 people, at the time of this article’s publication (Wilson, Hamzelou, Vaughan, Quilty-Harper, & Liverpool, 2020).  It is crucial that we identify high-risk patients in order to decrease the mortality rate of COVID.

The data has shown that the pandemic has been disproportionately affecting Black, Indigenous, and other people of colour, who have higher levels of chronic health conditions. The populations are seeing higher rates of hospitalization or death from COVID-19 than among non-Hispanic white persons, with a high proportion of minorities working low paid frontline jobs, often with insufficient sick time (Krishnan, Ogunwole, & Cooper, 2020).

Advanced older age as a risk factor for COVID-19 infection and death has been well substantiated. Over one out of five patients in Italy over the age of 80 succumbed to the disease (Livingston & Bucher, 2020).  The COVID-19 outbreak at the cruise ship Diamond Princess showed that the virus infected 621 out of 3711 persons within four weeks and six died. All of the deceased were at least 70 years old, and at least two of them had comorbidities (Standl, Jockel, & Stang, 2020).  

As a result, many third-party analytics and online models only have age as a consideration, but the data indicates that age is only one among many risk factors for severe COVID (Vishnevetsky & Levy, 2020). While the very elderly are most severely affected by the disease, the median age of hospitalized patients with severe COVID-19 in a large retrospective study in China was only 52 years (Standl, Jockel, & Stang, 2020).  Early analyses of large Chinese cohorts have identified risk factors such as older age, hypertension, chronic respiratory diseases, and cardiovascular diseases (Vishnevetsky & Levy, 2020).  

The association between obesity and poor outcomes from the virus is particularly concerning. Researchers said that in the U.S. and Mexico, more than one-third of people 15 years and older are obese (Standl, Jockel, & Stang, 2020). This is, in part, why we are seeing higher numbers in the U.S., Mexico, Brazil, the United Kingdom, all of which have larger obese populations than other affected countries.

A unified strategy: Implementing “inverse quarantine”

By assessing patients’ exposure risk, current health status, and social determinants of health, and tracking these patients through every phase of COVID-19, healthcare providers can determine the risk levels of their patients, and implement a care strategy for those patients who are considered high-risk.  In an effort to protect the highest-risk members of our communities, many healthcare providers are moving toward an “inverse quarantine” care model. 

In the inverse quarantine model, “provider groups and hospital systems proactively identify their patients at the highest risk of serious morbidity or mortality from COVID-19” (Schnake-Mahl, Carty, Sierra, & Ajayi, 2020).  As a means to prevent fatal outcomes during infectious epidemics or pandemics, people with high-risk factors who are not yet infected choose to isolate themselves, unlike usual quarantine measures where infected people are isolated. High-risk people could isolate themselves at home until the pandemic subsides to the point that isolation is not necessary anymore. With this targeted approach, the vast majority of COVID-19 deaths can be prevented (Schnake-Mahl, Carty, Sierra, & Ajayi, 2020).

The inverse quarantine model can help providers take a proactive approach to their outreach and monitoring to keep patients safe and at home, and creates a clear pathway for rapid care escalation, including in-home care if needed.  A unified, rules-based strategy saves lives, and allows providers to use sacred resources wisely while controlling the cost of care.

An essential component in this inverse quarantine model is ensuring that patients and their loved ones are comprehensively educated and understand the factors that could identify them as high-risk (Schnake-Mahl, Carty, Sierra, & Ajayi, 2020).  Unlike immunocompromised individuals who are familiar with the risks associated with their condition, average adults in their 50s or 60s may never have thought of themselves as vulnerable; thus, messaging about their elevated risk should be targeted and unambiguous (Jayadevan, 2020).  We cannot control what the entire population does; but those who are educated on their risk factors can control what they do, with the guidance of their doctor.

Additionally, health systems should be in proactive communication with patients with existing chronic diseases, such as COPD or diabetes, in order to improve COVID-19 outcomes (Jayadevan, 2020). Complications of such conditions can be difficult and expensive to treat. As an alternative to regularly scheduled in-person doctor visits, telemedicine could be used to minimize unnecessary trips while still ensuring that patients with chronic conditions are receiving essential care and resources (Schnake-Mahl, Carty, Sierra, & Ajayi, 2020).  Physicians should ensure that patients understand that actions such as controlling their blood sugar can boost immunity, or quitting smoking is essential for their respiratory health, which in turn can decrease their risk of experiencing serious COVID symptoms (Delaronde, 2020).

While the pandemic persists, healthcare organizations need to avoid recommending visits to urgent care or the emergency department, when possible.  You cannot replace the experience of an in-person visit, but there are alternatives that can still allow patients to receive the care they need. Telehealth has taken off during COVID, and in addition to increasing safety for patients, it has increased capacity for healthcare providers, allowing them to “visit” more patients. Telehealth is a much more efficient approach.

There are, of course, exceptions to the effectiveness of telehealth as an alternative to in-person appointments. For many years clinics and emergency departments have ben screening patients for depression and suicidality. Typically, a patient will respond by saying yes or no to these questions; however, many clinicians often rely on subtle on cues from patients who are hesitant in their response. Asking these same questions via telehealth (especially with patients who previously have not discussed depression and suicide) may make it harder to discover or less likely for people to admit that they are depressed or feeling suicidal over a virtual appointment. Additionally, some patients do not have the necessary devices, a suitable wireless internet connection, or a private space to conduct a confidential appointment. In these situations, the definition of “telehealth” should be expanded to include alternatives such as a phone call or home visit.

The communication from the Centers for Disease Control is clear—anyone who is exposed to COVID-19 is at risk for contracting the virus.  However, some people are more likely than others to become severely ill, which means that they may require hospitalization, intensive care, or a ventilator to help them breathe.  These individuals may even die from the disease.

To prevent deaths from COVID, health systems and care providers can employ a unified inverse quarantine model to protect patients with risk factors that increase the possibility of having serious, life-threatening COVID symptoms if infected.  By identifying these patients, educating them on their risk factors in relation to the virus, and implementing a care strategy that allows these patients to isolate themselves while still receiving the care they need, healthcare providers can prevent COVID deaths among the most vulnerable in our population.

About Seleem R. Choudhury

Seleem Choudhury is an international clinician and operational executive with over 15 years of experience leading Academic Hospitals and Health Systems & Community Settings.  He writes about clinical excellence and entrepreneurism in healthcare at seleemchoudhury.com.

Resources:

Covid-19 news: England to offer more flu vaccines to ease NHS burden, By Clare Wilson , Jessica Hamzelou , Adam Vaughan , Conrad Quilty-Harper and Layal Liverpool

Krishnan, L., Ogunwole, S. M., & Cooper, L. A. (2020). Historical Insights on Coronavirus Disease 2019 (COVID-19), the 1918 Influenza Pandemic, and Racial Disparities: Illuminating a Path Forward. Annals of Internal Medicine.

Livingston E., Bucher K. Coronavirus disease 2019 (COVID-19) in Italy. JAMA. 2020;323(14) doi: 10.1001/jama.2020.4344.

Rethinking high-risk groups in COVID-19, by Anastasia Vishnevetsky and Michael Levy

COVID-19 and the need of targeted inverse quarantine, by Fabian Standl, Karl-Heinz Jöckel, and Andreas Stang

Identifying Patients with Increased Risk of Severe Covid-19 Complications: Building an Actionable Rules-Based Model for Care Teams, by Alina S. Schnake-Mahl, ScD, MPH, Marcy G. Carty, MD, MPH, Gerardo Sierra, MA & Toyin Ajayi, MD, MPhil

Reverse Quarantine: 10 steps to protect the elderly and the vulnerable from COVID19, by Dr Rajeev Jayadevan

COVID-19 and chronic conditions: A look at population health, by Steve Delaronde

Globally, 1 in 5 at risk for serious COVID-19, study finds, by Mary Van Beusekom

The US has 4% of the world’s population but 25% of its coronavirus cases, by Scottie Andrew

How many are at increased risk of severe COVID-19 disease? Rapid global, regional and national estimates for 2020, by Andrew Clark,  View ORCID ProfileMark Jit, Charlotte Warren-Gash, Bruce Guthrie, Harry HX Wang, Stewart W Mercer, Colin Sanderson, Martin McKee, Christopher Troeger, Kanyin I Ong, Francesco Checchi, Pablo Perel, Sarah Joseph, Hamish P Gibbs, Amitava Banerjee, Rosalind M Eggo

Wensing, M., & Grol, R. (2019). Knowledge translation in health: how implementation science could contribute more. BMC medicine, 17(1), 88.

LEAVE A REPLY

Please enter your comment!
Please enter your name here

10 + fifteen =

This site uses Akismet to reduce spam. Learn how your comment data is processed.