Distribution of Patients at Risk for Complications Related to COVID-19 in the United States: Model Development Study

Abstract

Background Coronavirus disease (COVID-19) has spread exponentially across the United States. Older adults with underlying health conditions are at an especially high risk of developing life-threatening complications if infected. Most intensive care unit (ICU) admissions and non-ICU hospitalizations have been among patients with at least one underlying health condition. Objective The aim of this study was to develop a model to estimate the risk status of the patients of a nationwide pharmacy chain in the United States, and to identify the geographic distribution of patients who have the highest risk of severe COVID-19 complications. Methods A risk model was developed using a training test split approach to identify patients who are at high risk of developing serious complications from COVID-19. Adult patients (aged ≥18 years) were identified from the Walgreens pharmacy electronic data warehouse. Patients were considered eligible to contribute data to the model if they had at least one prescription filled at a Walgreens location between October 27, 2019, and March 25, 2020. Risk parameters included age, whether the patient is being treated for a serious or chronic condition, and urban density classification. Parameters were differentially weighted based on their association with severe complications, as reported in earlier cases. An at-risk rate per 1000 people was calculated at the county level, and ArcMap was used to depict the rate of patients at high risk for severe complications from COVID-19. Real-time COVID-19 cases captured by the Johns Hopkins University Center for Systems Science and Engineering (CSSE) were layered in the risk map to show where cases exist relative to the high-risk populations. Results Of the 30,100,826 adults included in this study, the average age is 50 years, 15% have at least one specialty medication, and the average patient has 2 to 3 comorbidities. Nearly 28% of patients have the greatest risk score, and an additional 34.64% of patients are considered high-risk, with scores ranging from 8 to 10. Age accounts for 53% of a patient’s total risk, followed by the number of comorbidities (29%); inferred chronic obstructive pulmonary disease, hypertension, or diabetes (15%); and urban density classification (5%). Conclusions This risk model utilizes data from approximately 10% of the US population. Currently, this is the most comprehensive US model to estimate and depict the county-level prognosis of COVID-19 infection. This study shows that there are counties across the United States whose residents are at high risk of developing severe complications from COVID-19. Our county-level risk estimates may be used alongside other data sets to improve the accuracy of anticipated health care resource needs. The interactive map can also aid in proactive planning and preparations among employers that are deemed critical, such as pharmacies and grocery stores, to prevent the spread of COVID-19 within their facilities.

Predictive Models of Mortality for Hospitalized Patients With COVID-19: Retrospective Cohort Study

“…In many ways, our patient cohort represented a typical cohort of hospitalized patients with COVID-19. In particular, individuals who die of the infection tend to be older and male [ 22 - 25 ]. However, the rate of mortality in our study cohort was higher; close to 50% of the patients admitted to hospital died (174/375, 46.4%).…”

Telemedicine and urban diabetes during COVID-19 pandemic in Milano, Italy during lock-down: epidemiological and sociodemographic picture

“…Up-to-date, no study has specifically assessed the difference in prevalence of diabetes between the Milano Metropolitan Area and Italian rural areas. Nonetheless, the South of Italy, less urbanized and industrialized than the North of Italy, has an higher prevalence of diabetes mellitus [ 20 ]. Interestingly, a similar pattern of high prevalence of diabetes mellitus in rural areas was reported in China [ 18 ].…”

Processes for Trauma Care at Six Level I Trauma Centers During the COVID-19 Pandemic

“…Data available shows that the burden of COVID-19 varied by the states included in this study. 11 , 12 The Centers for Disease Control and Prevention (CDC) released a report of the number of cases per state on April 7 and reported 5,429 in Colorado, 900 in Kansas, 3,037 in Missouri, and 8,262 in Texas. 11 Smith-Rey et al created a model to report the number of people at risk for complications per 1,000 persons by the US county with eight levels for each risk category.…”

“… 11 Smith-Rey et al created a model to report the number of people at risk for complications per 1,000 persons by the US county with eight levels for each risk category. 12 The centers involved in this study resided in counties that were designated as risk categories 3–5, ranging from 125 to 200 persons at risk for developing complications from COVID-19 per 1,000 persons; these data could be indicative of the burden of hospitalizations for patients with complications from COVID-19. 12 …”

“… 12 The centers involved in this study resided in counties that were designated as risk categories 3–5, ranging from 125 to 200 persons at risk for developing complications from COVID-19 per 1,000 persons; these data could be indicative of the burden of hospitalizations for patients with complications from COVID-19. 12 …”