Predicting Emergency Department “Bouncebacks”: A Retrospective Cohort Analysis

Introduction: The short-term return visit rate among patients discharged from emergency departments (ED) is a quality metric and target for interventions. The ability to accurately identify which patients are more likely to revisit the ED could allow EDs and health systems to develop more focused interventions, but efforts to reduce revisits have not yet found success. Whether patients with a high number of ED visits are at increased risk of a return visit remains underexplored.Methods: This was a population-based, retrospective, cohort study using administrative data from a large physician partnership. We included patients discharged from EDs from 80 hospitals in seven states from July 2014 – June 2016. We performed multivariable logistic regression of short-term return visits on patient, visit, hospital, and community characteristics. The primary outcome was the proportion of patients who had a return visit within 14 days of an index ED visit.Results: Among 6,699,717 index visits, the overall risk of 14-day revisit was 12.6%. Frequent visitors accounted for 18.7% of all visits and 40.2% of all 14-day revisits. Frequent visitor status was associated with the highest odds of a revisit (odds ratio [OR] 3.06; 95% confidence interval [CI], 3.041 – 3.073). Other predictors of revisits were cellulitis (OR 2.131; 95% CI, 2.106 – 2.156), alcohol-related disorders (OR 1.579; 95%CI, 1.548 – 1.610), congestive heart failure (OR 1.175; 95% CI, 1.126 – 1.226), and public insurance (Medicaid OR 1.514; 95% CI, 1.501 – 1.528; Medicare OR 1.601; 95% CI, 1.583 – 1.620).Conclusion: Previous ED use – even a single previous visit – was a stronger predictor of a return visit than any other patient, hospital, or community characteristic. Clinicians should consider previous ED use when considering treatment decisions and risk of return visit, as should stakeholders targeting patients at risk of a return visit

Long COVID Clinical Phenotypes up to 6 Months After Infection Identified by Latent Class Analysis of Self-Reported Symptoms

BACKGROUND: The prevalence, incidence, and interrelationships of persistent symptoms after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection vary. There are limited data on specific phenotypes of persistent symptoms. Using latent class analysis (LCA) modeling, we sought to identify whether specific phenotypes of COVID-19 were present 3 months and 6 months post-infection. METHODS: This was a multicenter study of symptomatic adults tested for SARS-CoV-2 with prospectively collected data on general symptoms and fatigue-related symptoms up to 6 months postdiagnosis. Using LCA, we identified symptomatically homogenous groups among COVID-positive and COVID-negative participants at each time period for both general and fatigue-related symptoms. RESULTS: Among 5963 baseline participants (4504 COVID-positive and 1459 COVID-negative), 4056 had 3-month and 2856 had 6-month data at the time of analysis. We identified 4 distinct phenotypes of post-COVID conditions (PCCs) at 3 and 6 months for both general and fatigue-related symptoms; minimal-symptom groups represented 70% of participants at 3 and 6 months. When compared with the COVID-negative cohort, COVID-positive participants had higher occurrence of loss of taste/smell and cognition problems. There was substantial class-switching over time; those in 1 symptom class at 3 months were equally likely to remain or enter a new phenotype at 6 months. CONCLUSIONS: We identified distinct classes of PCC phenotypes for general and fatigue-related symptoms. Most participants had minimal or no symptoms at 3 and 6 months of follow-up. Significant proportions of participants changed symptom groups over time, suggesting that symptoms present during the acute illness may differ from prolonged symptoms and that PCCs may have a more dynamic nature than previously recognized

Association Between SARS-CoV-2 Variants and Frequency of Acute Symptoms: Analysis of a Multi-institutional Prospective Cohort Study-December 20, 2020-June 20, 2022.

Background: While prior work examining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern focused on hospitalization and death, less is known about differences in clinical presentation. We compared the prevalence of acute symptoms across pre-Delta, Delta, and Omicron. Methods: We conducted an analysis of the Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE), a cohort study enrolling symptomatic SARS-CoV-2-positive participants. We determined the association between the pre-Delta, Delta, and Omicron time periods and the prevalence of 21 coronavirus disease 2019 (COVID-19) acute symptoms. Results: We enrolled 4113 participants from December 2020 to June 2022. Pre-Delta vs Delta vs Omicron participants had increasing sore throat (40.9%, 54.6%, 70.6%; Conclusions: Participants infected during Omicron were more likely to report symptoms of common respiratory viruses, such as sore throat, and less likely to report loss of smell and taste. Trial Registration: NCT04610515

Association of Initial SARS-CoV-2 Test Positivity With Patient-Reported Well-being 3 Months After a Symptomatic Illness.

IMPORTANCE: Long-term sequelae after symptomatic SARS-CoV-2 infection may impact well-being, yet existing data primarily focus on discrete symptoms and/or health care use. OBJECTIVE: To compare patient-reported outcomes of physical, mental, and social well-being among adults with symptomatic illness who received a positive vs negative test result for SARS-CoV-2 infection. DESIGN, SETTING, AND PARTICIPANTS: This cohort study was a planned interim analysis of an ongoing multicenter prospective longitudinal registry study (the Innovative Support for Patients With SARS-CoV-2 Infections Registry [INSPIRE]). Participants were enrolled from December 11, 2020, to September 10, 2021, and comprised adults (aged ≥18 years) with acute symptoms suggestive of SARS-CoV-2 infection at the time of receipt of a SARS-CoV-2 test approved by the US Food and Drug Administration. The analysis included the first 1000 participants who completed baseline and 3-month follow-up surveys consisting of questions from the 29-item Patient-Reported Outcomes Measurement Information System (PROMIS-29; 7 subscales, including physical function, anxiety, depression, fatigue, social participation, sleep disturbance, and pain interference) and the PROMIS Short Form-Cognitive Function 8a scale, for which population-normed T scores were reported. EXPOSURES: SARS-CoV-2 status (positive or negative test result) at enrollment. MAIN OUTCOMES AND MEASURES: Mean PROMIS scores for participants with positive COVID-19 tests vs negative COVID-19 tests were compared descriptively and using multivariable regression analysis. RESULTS: Among 1000 participants, 722 (72.2%) received a positive COVID-19 result and 278 (27.8%) received a negative result; 406 of 998 participants (40.7%) were aged 18 to 34 years, 644 of 972 (66.3%) were female, 833 of 984 (84.7%) were non-Hispanic, and 685 of 974 (70.3%) were White. A total of 282 of 712 participants (39.6%) in the COVID-19-positive group and 147 of 275 participants (53.5%) in the COVID-19-negative group reported persistently poor physical, mental, or social well-being at 3-month follow-up. After adjustment, improvements in well-being were statistically and clinically greater for participants in the COVID-19-positive group vs the COVID-19-negative group only for social participation (β = 3.32; 95% CI, 1.84-4.80; P \u3c .001); changes in other well-being domains were not clinically different between groups. Improvements in well-being in the COVID-19-positive group were concentrated among participants aged 18 to 34 years (eg, social participation: β = 3.90; 95% CI, 1.75-6.05; P \u3c .001) and those who presented for COVID-19 testing in an ambulatory setting (eg, social participation: β = 4.16; 95% CI, 2.12-6.20; P \u3c .001). CONCLUSIONS AND RELEVANCE: In this study, participants in both the COVID-19-positive and COVID-19-negative groups reported persistently poor physical, mental, or social well-being at 3-month follow-up. Although some individuals had clinically meaningful improvements over time, many reported moderate to severe impairments in well-being 3 months later. These results highlight the importance of including a control group of participants with negative COVID-19 results for comparison when examining the sequelae of COVID-19

Association of SARS-CoV-2 nucleocapsid viral antigen and the receptor for advanced glycation end products with development of severe disease in patients presenting to the emergency department with COVID-19

IntroductionThere remains a need to better identify patients at highest risk for developing severe Coronavirus Disease 2019 (COVID-19) as additional waves of the pandemic continue to impact hospital systems. We sought to characterize the association of receptor for advanced glycation end products (RAGE), SARS-CoV-2 nucleocapsid viral antigen, and a panel of thromboinflammatory biomarkers with development of severe disease in patients presenting to the emergency department with symptomatic COVID-19.MethodsBlood samples were collected on arrival from 77 patients with symptomatic COVID-19, and plasma levels of thromboinflammatory biomarkers were measured.ResultsDifferences in biomarkers between those who did and did not develop severe disease or death 7 days after presentation were analyzed. After adjustment for multiple comparisons, RAGE, SARS-CoV-2 nucleocapsid viral antigen, interleukin (IL)-6, IL-10 and tumor necrosis factor receptor (TNFR)-1 were significantly elevated in the group who developed severe disease (all p<0.05). In a multivariable regression model, RAGE and SARS-CoV-2 nucleocapsid viral antigen remained significant risk factors for development of severe disease (both p<0.05), and each had sensitivity and specificity >80% on cut-point analysis.DiscussionElevated RAGE and SARS-CoV-2 nucleocapsid viral antigen on emergency department presentation are strongly associated with development of severe disease at 7 days. These findings are of clinical relevance for patient prognostication and triage as hospital systems continue to be overwhelmed. Further studies are warranted to determine the feasibility and utility of point-of care measurements of these biomarkers in the emergency department setting to improve patient prognostication and triage

Essays in Behavioral Health Economics

This dissertation is comprised of three chapters, each of which contributes to the fields of health economics and psychology & economics. Two of the chapters investigate how choice architecture affects patients health care decisions. The third investigates the role of beliefs in the demand for health information. The underlying motivation for these studies stems from the observations that the proportion of HIV-infected persons in the United States who are undiagnosed has remained constant for over a decade, and those who are diagnosed are often diagnosed late in the course of their disease. Deeper understanding of how HIV test acceptance by patients depends on how the test is offered has the potential to decrease the frequency of missed opportunities for identifying infected persons.Choice architecture has the potential to influence patients' health and health care deci- sions. In particular, decisions with significant but delayed consequences can be very sensitive to small, immediate costs and benefits. I investigate how small monetary incentives and de- fault test policies affect patient decision making with regard to HIV testing. I conduct and analyze the results of a field experiment that takes place in an urban emergency depart- ment (ED). In parallel with routine care, patients are approached by research assistants and offered HIV tests and questionnaires according to treatment assignments. In a factorial design, patients are randomly assigned to be offered HIV tests according to default scripts; they are also offered small monetary incentives and a questionnaire eliciting HIV-related risk behaviors. Patients are offered the questionnaire either before or after the test offer. Among those assigned to an early questionnaire, half are assigned to an additional question asking whether they would hypothetically accept an HIV test, a `foot-in-the-door' question (FITD).In Chapter 1, "HIV Screening: To Test or Not to Test? It Depends on the Question," I examine three test defaults: traditional opt-in (test only those patients who request test- ing), opt-out (routine testing unless patients decline), and active-choice testing (patients are required to state whether they want to be tested). I find a test acceptance rate of 51.2% in the opt-in treatment. Active-choice and opt-out test schemes increased the proportion of patients who accepted HIV testing by clinically significant levels. Patients assigned to an active-choice test offer are 9.5 percentage points more likely to accept an HIV test; those assigned to an opt-out offer are 18.2 percentage points more likely than opt-in patients.I take up the issue of monetary incentives in "Conditional Cash Incentives for HIV Test- ing." Patients are offered monetary incentives ($0,$1, $5,$10), which vary by ED zone (four zones) by day. I find that cash incentives of $5 and$10 increase test acceptance rates by 11.7 and 12.8 percentage points, respectively, from a baseline of 57.9% with no incentive. The $1 treatment assignment has no significant effect on overall test rates. It does, however, have a differential effect on high- and low-risk patients: patients reporting HIV risk factors are 4.3 percentage points more likely to test when offered$1 than when offered no incentive, and patients denying any risk factors are 9.6 percentage points less likely to accept testing when offered $1 than when offered no incentive. I find no difference in test rates between patients assigned to the FITD treatment and those in the early questionnaire treatment who were not asked the hypothetical question. Across defaults and monetary incentives, I observe an effect of being offered a questionnaire: patients assigned to either of Early or FITD questionnaires are 10.8 percentage points less likely to accept testing than those who are offered the test prior to being offered the questionnaire.In "Perceptions and Misperceptions of HIV Transmission, Testing, and Treatment" I examine the relationship between beliefs regarding HIV transmission, testing, and treatment on subjects' testing behavior. I find that subjects grossly overestimate the probability of transmission for both real (e.g., injection drug use) and false (e.g., sharing a beverage) risk behaviors. Subjects also overestimate the prevalence of HIV. Despite these overestimates and self-reported risk behaviors, most consider themselves to be at no or very low risk of HIV infection, and few have ever tested for HIV. While these findings support both classical and behavioral interpretations (including psychological expected utility), these findings suggest that people's beliefs regarding HIV risk are biased and suggest that educating the public might be counterproductive, leading to more risky behaviors and lower testing rates

Patient choice in opt-in, active choice, and opt-out HIV screening: randomized clinical trial.

STUDY QUESTION:What is the effect of default test offers--opt-in, opt-out, and active choice--on the likelihood of acceptance of an HIV test among patients receiving care in an emergency department? METHODS:This was a randomized clinical trial conducted in the emergency department of an urban teaching hospital and regional trauma center. Patients aged 13-64 years were randomized to opt-in, opt-out, and active choice HIV test offers. The primary outcome was HIV test acceptance percentage. The Denver Risk Score was used to categorize patients as being at low, intermediate, or high risk of HIV infection. STUDY ANSWER AND LIMITATIONS:38.0% (611/1607) of patients in the opt-in testing group accepted an HIV test, compared with 51.3% (815/1628) in the active choice arm (difference 13.3%, 95% confidence interval 9.8% to 16.7%) and 65.9% (1031/1565) in the opt-out arm (difference 27.9%, 24.4% to 31.3%). Compared with active choice testing, opt-out testing led to a 14.6 (11.1 to 18.1) percentage point increase in test acceptance. Patients identified as being at intermediate and high risk were more likely to accept testing than were those at low risk in all arms (difference 6.4% (3.4% to 9.3%) for intermediate and 8.3% (3.3% to 13.4%) for high risk). The opt-out effect was significantly smaller among those reporting high risk behaviors, but the active choice effect did not significantly vary by level of reported risk behavior. Patients consented to inclusion in the study after being offered an HIV test, and inclusion varied slightly by treatment assignment. The study took place at a single county hospital in a city that is somewhat unique with respect to HIV testing; although the test acceptance percentages themselves might vary, a different pattern for opt-in versus active choice versus opt-out test schemes would not be expected. WHAT THIS PAPER ADDS:Active choice is a distinct test regimen, with test acceptance patterns that may best approximate patients' true preferences. Opt-out regimens can substantially increase HIV testing, and opt-in schemes may reduce testing, compared with active choice testing. FUNDING, COMPETING INTERESTS, DATA SHARING:This study was supported by grant NIA 1RC4AG039078 from the National Institute on Aging. The full dataset is available from the corresponding author. Consent for data sharing was not obtained, but the data are anonymized and risk of identification is low.Trial registration Clinical trials NCT01377857