Brenna Kelly’s research while affiliated with University of Utah and other places

Background: Little is known about nursing home (NH) residents' family characteristics despite the important role families play at end-of-life (EOL). Objective: To describe the size and composition of first-degree families (FDFs) of Utah NH residents who died 1998–2016 (n = 43,405). Methods: Using the Utah Population Caregiving Database, we linked NH decedents to their FDF (n = 124,419; spouses = 10.8%; children = 55.3%; siblings = 32.3%) and compared sociodemographic and death characteristics of those with and without FDF members (n = 9424). Results: Compared to NH decedents with FDF (78.3%), those without (21.7%) were more likely to be female (64.7% vs. 57.1%), non-White/Hispanic (11.2% vs. 4.2%), less educated (<9th grade; 41.1% vs. 32.4%), and die in a rural/frontier NH (25.3% vs. 24.0%, all p < 0.001). Despite similar levels of disease burden (Charlson Comorbidity score 3 + 37.7% vs. 38.0%), those without FDF were more likely to die from cancer (14.2% vs. 12.4%), Chronic Obstructive Pulmonary Disease (COPD) (6.0% vs. 4.0%), and dementia (17.1% vs. 16.6%, all p < 0.001), and were less likely to have 2+ hospitalizations at EOL (20.5% vs. 22.4%, p < 0.001). Conclusions: Among NH decedents, those with and without FDF have different sociodemographic and death characteristics—factors that may impact care at EOL. Understanding the nature of FDF relationship type on NH resident EOL care trajectories and outcomes is an important next step in clarifying the role of families of persons living and dying in NHs.

To better understand determinants and potential disparities in end of life, we model decedents' place of death with explanatory variables describing familial, social, and economic resources. A retrospective cohort of 204,041 decedents and their family members are drawn from the Utah Population Database family caregiving dataset. Using multinomial regression, we model place of death, categorized as at home, in a hospital, in another location, or unknown. The model includes family relationship variables, sex, race and ethnicity, and a socioeconomic status score, with control variables for age at death and death year. We identified the effect of a family network of multiple caregivers, with 3+ daughters decreasing odds of a hospital death by 17 percent (OR: 0.83 [0.79, 0.87], p < 0.001). Place of death also varies significantly by race and ethnicity, with most nonwhite groups more likely to die in a hospital. These determinants may contribute to disparities in end of life.

Consistent with preferences, home deaths in the US increasing — yet most Americans still die in hospitals or other healthcare facilities. Although declining health has been considered the primary factor influencing place of death, few studies have examined how family support and sociodemographic factors influence place of death. This study examined a population-based cohort of 205,932 decedents aged 50+ who died in Utah between 1998 and 2016. Using multivariate logistic regression models, we found that having a living spouse or child was associated with decreased odds of a healthcare facility death (spouse: AOR= 0.62, CI 0.65-0.59; child: AOR = 0.80, CI 0.79-0.82). Additionally, educational attainment (graduate degree: AOR = 0.95, CI 0.91-0.99) and non-Hispanic/Latinx ethnicity (AOR = 0.81, CI 0.79-0.85) were associated with decreased odds of a home death. Our findings highlight the importance of families in place of death and suggest that sociodemographic and economic disparities persist even in death.

Over 2/3 of nursing home (NH) residents are eligible for palliative care (PC), but do not receive it. Utilizing the Utah Population Database, we examined EOL characteristics for 39,672 NH residents who died in Utah between 1998-2016. Dementia was the leading cause of death (36.6%), followed by cardiovascular disease (23.9%) and COPD (16.7%). Women were more likely than men to die in a NH (21.0 vs 15%) and more likely to die in a NH with heart disease (20.0% vs. 11.7%) or cerebrovascular disease (25.9% vs. 21.0%), compared to men. Use of PC, hospice, and life-sustaining treatments was low within this NH sample, particularly among persons with dementia. First-degree family characteristics varied at EOL with presence of a spouse exerting the greatest influence on EOL care utilization. Understanding population-based NH resident EOL life characteristics can help inform the development of resident- and caregiver-centered PC interventions and health policies.

Background To increase bed capacity and resources, hospitals have postponed elective surgeries, although the financial impact of this decision is unknown. We sought to report elective surgical case distribution, associated gross hospital revenue and regional hospital and intensive care unit (ICU) bed capacity as elective surgical cases are cancelled and then resumed under simulated trends of COVID-19 incidence. Methods A retrospective, cohort analysis was performed using insurance claims from 161 million enrollees from the MarketScan database from January 1, 2008 to December 31, 2017. COVID-19 cases were calculated using Institute for Health Metrics and Evaluation models. Centers for Disease Control (CDC) reports on the number of hospitalized and intensive care patients by age estimated the number of cases seen in the ICU, the reduction in elective surgeries and the financial impact of this from historic claims data, using a denominator of all inpatient revenue and outpatient surgeries. Results Assuming 5% infection prevalence, cancelling all elective procedures decreases ICU overcapacity from 160 to 130%, but these elective surgical cases contribute 78% (IQR 74, 80) (1.1 trillion (T) US dollars) to inpatient hospital plus outpatient surgical gross revenue per year. Musculoskeletal, circulatory and digestive category elective surgical cases compose 33% ($447B) of total revenue. Conclusions Procedures involving the musculoskeletal, cardiovascular and digestive system account for the largest loss of hospital gross revenue when elective surgery is postponed. As hospital bed capacity increases following the COVID-19 pandemic, restoring volume of these elective cases will help maintain revenue. In these estimates, adopting universal masking would help to avoid overcapacity in all states.

Background: To increase bed capacity and resources, hospitals have postponed elective surgeries, although the financial impact of this decision is unknown. We sought to report elective surgical case distribution, associated gross hospital earnings and regional hospital and intensive care unit (ICU) bed capacity as elective surgical cases are cancelled and then resumed under simulated trends of COVID-19 incidence. Methods: A retrospective, cohort analysis was performed using insurance claims from 161 million enrollees from the MarketScan database from January 1, 2008 to December 31, 2017. COVID-19 cases were calculated using a generalized Richards model. Centers for Disease Control (CDC) reports on the number of hospitalized and intensive care patients by age were used to estimate the number of cases seen in the ICU, the reduction in elective surgeries and the financial impact of this from historic claims data, using a denominator of all inpatient revenue and outpatient surgeries. Results: Assuming 5% infection prevalence, cancelling all elective procedures decreases ICU overcapacity from 340% to 270%, but these elective surgical cases contribute 78% (IQR 74, 80) (1.1 trillion (T) US dollars) to inpatient hospital plus outpatient surgical gross earnings per year. Musculoskeletal, circulatory and digestive category elective surgical cases compose 33% ($447B) of total revenue. Conclusions: Procedures involving the musculoskeletal, cardiovascular and digestive system account for the largest loss of hospital gross earnings when elective surgery is postponed. As hospital bed capacity increases following the COVID-19 pandemic, restoring volume of these elective cases will help maintain revenue.