Hepatitis C Virus Elimination Programs in Louisiana and Washington: Importance of Screening and Surveillance Systems.

The US government has established a national goal of hepatitis C virus (HCV) elimination by 2030. To date, most HCV elimination planning and activity have been at the state level. Fifteen states presently have publicly available HCV elimination plans. In 2019, Louisiana and Washington were the first states to initiate 5-year funded HCV elimination programs. These states differ on motivation for pursuing HCV elimination and ranking on several indicators. Simultaneously, however, they have emphasized several similar elimination components including HCV screening promotion through public awareness, screening expansion, surveillance enhancement (including electronic reporting and task force development), and harm reduction. The 13 other states with published elimination plans have proposed the majority of the elements identified by Louisiana and Washington, but several have notable gaps. Louisiana's and Washington's comprehensive plans, funding approaches, and programs provide a useful framework that can move states and the nation toward HCV elimination.

Towards diagnostic excellence on academic ward teams: building a conceptual model of team dynamics in the diagnostic process.

OBJECTIVES: Achieving diagnostic excellence on medical wards requires teamwork and effective team dynamics. However, the study of ward team dynamics in teaching hospitals is relatively underdeveloped. We aim to enhance understanding of how ward team members interact in the diagnostic process and of the underlying behavioral, psychological, and cognitive mechanisms driving team interactions. METHODS: We used mixed-methods to develop and refine a conceptual model of how ward team dynamics in an academic medical center influence the diagnostic process. First, we systematically searched existing literature for conceptual models and empirical studies of team dynamics. Then, we conducted field observations with thematic analysis to refine our model. RESULTS: We present a conceptual model of how medical ward team dynamics influence the diagnostic process, which serves as a roadmap for future research and interventions in this area. We identified three underexplored areas of team dynamics that are relevant to diagnostic excellence and that merit future investigation (1): ward team structures (e.g., team roles, responsibilities) (2); contextual factors (e.g., time constraints, location of team members, culture, diversity); and (3) emergent states (shared mental models, psychological safety, team trust, and team emotions). CONCLUSIONS: Optimizing the diagnostic process to achieve diagnostic excellence is likely to depend on addressing all of the potential barriers and facilitators to ward team dynamics presented in our model.

Hepatitis C Treatment Initiation Among US Medicaid Enrollees.

Importance: Direct-acting antiviral (DAA) treatment for hepatitis C virus (HCV) infection is highly effective but remains underused. Understanding disparities in the delivery of DAAs is important for HCV elimination planning and designing interventions to promote equitable treatment. Objective: To examine variations in the receipt of DAA in the 6 months following a new HCV diagnosis. Design, Setting, and Participants: This retrospective cohort study used national Medicaid claims from 2017 to 2019 from 50 states, Washington DC, and Puerto Rico. Individuals aged 18 to 64 years with a new diagnosis of HCV in 2018 were included. A new diagnosis was defined as a claim for an HCV RNA test followed by an International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) diagnosis code, after a 1-year lookback period. Main Outcomes and Measures: Outcome was receipt of a DAA prescription within 6 months of diagnosis. Logistic regression was used to examine demographic factors and ICD-10-identified comorbidities associated with treatment initiation. Results: Among 87 652 individuals, 43 078 (49%) were females, 12 355 (14%) were age 18 to 29 years, 35 181 (40%) age 30 to 49, 51 282 (46%) were non-Hispanic White, and 48 840 (49%) had an injection drug use diagnosis. Of these individuals, 17 927 (20%) received DAAs within 6 months of their first HCV diagnosis. In the regression analyses, male sex was associated with increased treatment initiation (OR, 1.24; 95% CI, 1.16-1.33). Being age 18 to 29 years (OR, 0.65; 95% CI, 0.50-0.85) and injection drug use (OR, 0.84; 95% CI, 0.75-0.94) were associated with decreased treatment initiation. After adjustment for state fixed effects, Asian race (OR, 0.50; 95% CI, 0.40-0.64), American Indian or Alaska Native race (OR, 0.68; 95% CI, 0.55-0.84), and Hispanic ethnicity (OR, 0.81; 95% CI, 0.71-0.93) were associated with decreased treatment initiation. Adjustment for state Medicaid policy did not attenuate the racial or ethnic disparities. Conclusions: In this retrospective cohort study, HCV treatment initiation was low among Medicaid beneficiaries and varied by demographic characteristics and comorbidities. Interventions are needed to increase HCV treatment uptake among Medicaid beneficiaries and to address disparities in treatment among key populations, including younger individuals, females, individuals from minoritized racial and ethnic groups, and people who inject drugs.

How team clinical reasoning occurs on ward rounds: Implications for learning.

BACKGROUND: Ward rounds offer a rich environment for learning about team clinical reasoning. We aimed to assess how team clinical reasoning occurs on ward rounds to inform efforts to enhance the teaching of clinical reasoning. METHODS: We performed focused ethnography of ward rounds over a 6-week period, during which we observed five different teams. Each day team comprised one senior physician, one senior resident, one junior resident, two interns and one medical student. Twelve 'night-float' residents who discussed new patients with the day team were also included. Field notes were analysed using content analysis. FINDINGS: We analysed 41 new patient presentations and discussions on 23 different ward rounds. The median duration of case presentations and discussions was 13.0 minutes (IQR, 10.0-18.0 minutes). More time was devoted to information sharing (median 5.5 minutes; IQR, 4.0-7.0 minutes) than any other activity, followed by discussion of management plans (median 4.0 minutes; IQR, 3.0-7.8 minutes). Nineteen (46%) cases did not include discussion of a differential diagnosis for the chief concern. We identified two themes relevant to learning: (1) linear versus iterative approaches to team-based diagnosis and (2) the influence of hierarchy on participation in clinical reasoning discussions. CONCLUSION: The ward teams we observed spent far less time discussing differential diagnoses compared with information sharing. Junior learners such as medical students and interns contributed less frequently to team clinical reasoning discussions. In order to maximise student learning, strategies to engage junior learners in team clinical reasoning discussions on ward rounds may be needed.

Digital Health at Enterprise Scale: Evaluation Framework for Selecting Patient-Facing Software in a Digital-First Health System.

The digital transformation of our health care system will require not only digitization of existing tools but also a redesign of our care delivery system and collaboration with digital partners. Traditional patient journeys are reactive to symptom presentation and delayed by health care system-centric scheduling, leading to poor experience and avoidable adverse outcomes. Patient journeys will be reimagined to a digital health pathway that seamlessly integrates various care experiences from telemedicine, remote monitoring, to in-person clinic visits. Through centering the care delivery around the patients, they can have more delightful experiences and enjoy the quality of standardized condition pathways and outcomes. To design and implement digital health pathways at scale, enterprise health care systems need to develop capabilities and partnerships in human-centered design, operational workflow, clinical content management, communication channels and mechanisms, reporting and analytics, standards-based integration, security and data management, and scalability. Using a human-centered design methodology, care pathways will be built upon an understanding of the unmet needs of the patients to have a more enjoyable experience of care with improved clinical outcomes. To power this digital care pathway, enterprises will choose to build or partner for clinical content management to operationalize up-to-date, best-in-class pathways. With this clinical engine, this digital solution will engage with patients through multimodal communication modalities, including written, audio, photo, or video, throughout the patient journey. Leadership teams will review reporting and analytics functions to track that the digital care pathways will be iterated to improve patient experience, clinical metrics, and operational efficiency. On the backend, standards-based integration will allow this system to be built in conjunction with the electronic medical record and other data systems to provide safe and efficient use of the digital care solution. For protecting patient information and compliance, a security and data management strategy is critical to derisking breeches and preserving privacy. Finally, a framework of technical scalability will allow digital care pathways to proliferate throughout the enterprise and support the entire patient population. This framework empowers enterprise health care systems to avoid collecting a fragmented series of one-off solutions but develop a sustainable concerted roadmap to the future of proactive intelligent patient care.

Associations of peer generational status on adolescent weight across Hispanic immigrant generations: A social network analysis.

BACKGROUND: Childhood obesity disproportionately impacts Hispanics in the United States (US), the nation's largest ethnic minority population. However, even among Hispanic children, those born in the US are at increased risk of developing obesity than those not born in the US (i.e. first-generation Hispanics). The objective of this study is to assess whether ethnic and generational differences in the friend networks of Hispanic adolescents moderate the association between immigrant generation and weight. METHODS: We analyzed data from first-generation, second-generation, and third-generation Hispanic 12 to 19 year-old participants in Wave 1 of the Longitudinal Study of Adolescent to Adult Health (Add Health). Using multivariable linear regression, we examined the association between generational status and body mass index (BMI), and whether the ethnic and generational composition of friends moderated that association. RESULTS: Higher generational status was associated with higher BMI. The ethnic and generational composition of friends was not independently associated with BMI among Hispanic adolescents. However, a social network with a greater proportion of second-generation Hispanics was positively associated with BMI among first-generation Hispanics, and negatively associated with BMI among second-generation Hispanics. CONCLUSIONS: The generational status of peers in Hispanic adolescents' social networks, particularly the proportion that are second-generation Hispanic, moderates the positive association between immigrant generation and BMI. Moreover, this moderation effect is different across immigrant generations so that the proportion of second-generation adolescents within a social network is associated with higher BMI in first-generation Hispanic adolescents, but with lower BMI among those who are second-generation. These results were confirmed in sensitivity analyses. Our findings suggest that the generational composition of social networks alters the association between the generational status and weight of Hispanic adolescents, and thus that social factors within those networks may contribute to those associations.

Cultural and neighborhood characteristics associated with activity-specific parenting practices in Hispanic/Latino youth: a secondary analysis of the Hispanic Community Children's health study/study of Latino youth.

Hispanic/Latino youth are less physically active than non-Hispanic/Latino youth. We assessed whether activity-specific parenting practices relate to moderate-to-vigorous physical activity (MVPA) and sedentary behavior among Hispanic/Latino youth, and whether cultural (acculturation) and neighborhood characteristics (perceived barriers to activity) relate to the use of parenting practice patterns. Using the Hispanic Community Children's Health Study/Study of Latino Youth (SOL Youth, n = 976 8-16-year-olds), we modeled linear regression associations between parenting practices and mean daily MVPA and sedentary behavior. Parenting practice patterns were then developed using k-means cluster analysis, and regressed on parental acculturation and neighborhood characteristics. Discipline predicted higher MVPA in females (ß 1.89 [95% CI 0.11-3.67]), while Monitoring/Reinforcement predicted higher MVPA in males (ß 4.71 [95% CI 0.68-8.74]). Three patterns were then identified: Negative Reinforcement (high Limit Setting and Discipline use), Positive Reinforcement (high Limit Setting and Monitoring/Reinforcement use), and Permissive Parenting (low parenting practice use). Higher acculturation predicted use of Positive Reinforcement. Activity-specific parenting practices are associated with activity in sex-specific ways among Hispanic/Latino youth, and cultural factors predict the use of parenting practices.

Comparing Hospital Length of Stay Risk-Adjustment Models in US Value-Based Physician Payments.

BACKGROUNG AND OBJECTIVES: Under the Affordable Care Act, the US Centers for Medicare & Medicaid Services created the Physician Value-Based Payment Modifier Program and its successor, the Merit-Based Incentive Payment System, to tie physician payments to quality and cost. The addition of hospital length of stay (LOS) to these value-based physician payment models reflects its increasing importance as a metric of health care cost and efficiency and its association with adverse health outcomes. This study compared the Centers for Medicare & Medicaid Services-endorsed LOS risk-adjustment methodology with a novel methodology that accounts for pre-hospitalization clinical, socioeconomic status (SES), and admission-related factors as influential factors of hospital LOS. METHODS: Using the 2014 New York, Florida, and New Jersey State Inpatient Database, we compared the observed-to-expected LOS of 2373102 adult admissions for 742 medical and surgical diagnosis-related groups (DRGs) by 3 models: ( a ) current risk-adjustment model (CRM), which adjusted for age, sex, number of chronic conditions, Elixhauser comorbidity score, and DRG severity weight, ( b ) CRM but modeling LOS using a generalized linear model (C-GLM), and (c) novel risk-adjustment model (NRM), which added to the C-GLM covariates for race/ethnicity, SES, discharge destination, weekend admission, and individual intercepts for DRGs instead of severity weights. RESULTS: The NRM disadvantaged physicians for fewer medical and surgical DRGs, compared with both the C-GLM and CRM models (medical DRGs: 0.49% vs 13.17% and 10.89%, respectively; surgical DRGs: 0.30% vs 13.17% and 10.98%, respectively). In subgroup analysis, the NRM reduced the proportion of physician-penalizing DRGs across all racial/ethnic and socioeconomic groups, with the highest reduction among Whites, followed by low SES patients, and the lowest reduction among Hispanic patients. CONCLUSIONS: After accounting for pre-hospitalization socioeconomic and clinical factors, the adjusted LOS using the NRM was lower than estimates from the current Centers for Medicare & Medicaid Services-endorsed model. The current model may disadvantage physicians serving communities with higher socioeconomic risks.

Impact of Hurricanes and Associated Extreme Weather Events on Cardiovascular Health: A Scoping Review.

BACKGROUND: The frequency and destructiveness of hurricanes and related extreme weather events (e.g., cyclones, severe storms) have been increasing due to climate change. A growing body of evidence suggests that victims of hurricanes have increased incidence of cardiovascular disease (CVD), likely due to increased stressors around time of the hurricane and in their aftermath. OBJECTIVES: The objective was to systematically examine the evidence of the association between hurricanes (and related extreme weather events) and adverse CVD outcomes with the goal of understanding the gaps in the literature. METHODS: A comprehensive literature search of population-level and cohort studies focused on CVD outcomes (i.e., myocardial infarction, stroke, and heart failure) related to hurricanes, cyclones, and severe storms was performed in the following databases from inception to December 2021: Ovid MEDLINE, Ovid EMBASE, Web of Science, and The Cochrane Library. Studies retrieved were then screened for eligibility against predefined inclusion/exclusion criteria. Studies were then qualitatively synthesized based on the time frame of the CVD outcomes studied and special populations that were studied. Gaps in the literature were identified based on this synthesis. RESULTS: Of the 1,103 citations identified, 48 met our overall inclusion criteria. We identified articles describing the relationship between CVD and extreme weather, primarily hurricanes, based on data from the United States (42), Taiwan (3), Japan (2), and France (1). Outcomes included CVD and myocardial infarction-related hospitalizations (30 studies) and CVVD-related mortality (7 studies). Most studies used a retrospective study design, including one case-control study, 39 cohort studies, and 4 time-series studies. DISCUSSION: Although we identified a number of papers that reported evaluations of extreme weather events and short-term adverse CVD outcomes, there were important gaps in the literature. These gaps included a) a lack of rigorous long-term evaluation of hurricane exposure, b) lack of investigation of hurricane exposure on vulnerable populations regarding issues related to environmental justice, c) absence of research on the exposure of multiple hurricanes on populations, and d) absence of an exploration of mechanisms leading to worsened CVD outcomes. Future research should attempt to fill these gaps, thus providing an important evidence base for future disaster-related policy. https://doi.org/10.1289/EHP11252.

Closing the Knowledge Gap in the Long-Term Health Effects of Natural Disasters: A Research Agenda for Improving Environmental Justice in the Age of Climate Change.

Natural disasters continue to worsen in both number and intensity globally, but our understanding of their long-term consequences on individual and community health remains limited. As climate-focused researchers, we argue that a publicly funded research agenda that supports the comprehensive exploration of these risks, particularly among vulnerable groups, is urgently needed. This exploration must focus on the following three critical components of the research agenda to promote environmental justice in the age of climate change: (1) a commitment to long term surveillance and care to examine the health impacts of climate change over their life course; (2) an emphasis on interventions using implementation science frameworks; (3) the employment of a transdisciplinary approach to study, address, and intervene on structural disadvantage among vulnerable populations. Without doing so, we risk addressing these consequences in a reactive way at greater expense, limiting the opportunity to safeguard communities and vulnerable populations in the era of climate change.

Predictors of life-threatening complications in relatively lower-risk patients hospitalized with COVID-19.

Older individuals with chronic health conditions are at highest risk of adverse clinical outcomes from COVID-19, but there is widespread belief that risk to younger, relatively lower-risk individuals is negligible. We assessed the rate and predictors of life-threatening complications among relatively lower-risk adults hospitalized with COVID-19. Of 3766 adults hospitalized with COVID-19 to three hospitals in New York City from March to May 2020, 963 were relatively lower-risk based on absence of preexisting health conditions. Multivariable logistic regression models examined in-hospital development of life-threatening complications (major medical events, intubation, or death). Covariates included age, sex, race/ethnicity, hypertension, weight, insurance type, and area-level sociodemographic factors (poverty, crowdedness, and limited English proficiency). In individuals ≥55 years old (n = 522), 33.3% experienced a life-threatening complication, 17.4% were intubated, and 22.6% died. Among those <55 years (n = 441), 15.0% experienced a life-threatening complication, 11.1% were intubated, and 5.9% died. In multivariable analyses among those ≥55 years, age (OR 1.03 [95%CI 1.01-1.06]), male sex (OR 1.72 [95%CI 1.14-2.64]), being publicly insured (versus commercial insurance: Medicare, OR 2.02 [95%CI 1.22-3.38], Medicaid, OR 1.87 [95%CI 1.10-3.20]) and living in areas with relatively high limited English proficiency (highest versus lowest quartile: OR 3.50 [95%CI 1.74-7.13]) predicted life-threatening complications. In those <55 years, no sociodemographic factors significantly predicted life-threatening complications. A substantial proportion of relatively lower-risk patients hospitalized with COVID-19 experienced life-threatening complications and more than 1 in 20 died. Public messaging needs to effectively convey that relatively lower-risk individuals are still at risk of serious complications.

Association Between Patient Diversity in Hospitals and Racial/Ethnic Differences in Patient Length of Stay.

BACKGROUND: Hospitals serving a disproportionate share of racial/ethnic minorities have been shown to have poorer quality outcomes. It is unknown whether efficiencies in inpatient care, measured by length of stay (LOS), differ based on the proportion patients served by a hospital who are minorities. OBJECTIVE: To examine the association between the racial/ethnic diversity of a hospital's patients and disparities in LOS. DESIGN: Retrospective cross-sectional study. PARTICIPANTS: One million five hundred forty-six thousand nine hundred fifty-five admissions using the 2017 New York State Inpatient Database from the Healthcare Cost and Utilization Project. MAIN MEASURE: Differences in mean adjusted LOS (ALOS) between White and Black, Hispanic, and Other (Asian, Pacific Islander, Native American, and Other) admissions by Racial/Ethnic Diversity Index (proportion of non-White patients admitted to total patients admitted to that same hospital) in quintiles (Q1 to Q5), stratified by discharge destination. Mean LOS was adjusted for patient demographic, clinical, and admission characteristics and for individual intercepts for each hospital. KEY RESULTS: In both unadjusted and adjusted analysis, Black-White and Other-White mean LOS differences were smallest in the most diverse hospitals (Black-White: unadjusted, -0.07 days [-0.1 to -0.04], and adjusted, 0.16 days [95% CI: 0.16 to 0.16]; Other-White: unadjusted, -0.74 days [95% CI: -0.77 to -0.71], and adjusted, 0.01 days [95% CI: 0.01 to 0.02]). For Hispanic patients, in unadjusted analysis, the mean LOS difference was greatest in the most diverse hospitals (-0.92 days, 95% CI: -0.95 to -0.89) but after adjustment, this was no longer the case. Similar patterns across all racial/ethnic groups were observed after analyses were stratified by discharge destination. CONCLUSION: Mean adjusted LOS differences between White and Black patients, and White and patients of Other race was smallest in most diverse hospitals, but not differences between Hispanic and White patients. These findings may reflect specific structural factors which affect racial/ethnic differences in patient LOS.

Challenges with social distancing during the COVID-19 pandemic among Hispanics in New York City: a qualitative study.

BACKGROUND: Hispanics in the United States are disproportionately affected by the novel coronavirus (COVID-19). While social distancing and quarantining are effective methods to reduce its spread, Hispanics, who are more likely to be essential workers and live in multigenerational homes than non-Hispanics, may face challenges that limit their ability to carry out these preventative efforts. We elicited the experiences of Hispanic adults with social distancing and self-quarantining during the COVID-19 pandemic in New York. METHODS: In this qualitative study, Hispanic adults receiving care at a federally qualified community health center in East Harlem, New York, were recruited for remote one-on-one semi-structured interviews from 5/15/2020 to 11/17/2020. Interviews were conducted by a bilingual interviewer in Spanish or English, using a semi-structured topic guide informed by the Health Belief Model. Audio-recordings were professionally transcribed. We used thematic analysis to iteratively code the data. Each transcript was independently coded by two research team members, then reconciled by a third. Major themes and subthemes were identified. RESULTS: Among 20 participants, four major themes emerged; Hispanics were: (1) fearful of contracting and transmitting COVID-19, (2) engaging in practices to reduce transmission of COVID-19, (3) experiencing barriers to social distancing and quarantining, and (4) facing an enduring psychological and physical toll from COVID-19. CONCLUSIONS: Despite understanding the risks for contracting COVID-19 and taking appropriate precautions, Hispanics faced numerous challenges to social distancing and quarantining, such as living in crowded, multi-generational households, working as essential workers, and providing unpaid care to family members. Such challenges took a toll on their physical, emotional, and financial well-being. Our findings suggest that a tailored approach to public health messaging and interventions for pandemic planning are warranted among members of this community. Further research is needed to understand and mitigate the long term physical and psychological consequences of the pandemic among Hispanics.

Association Between Racial Disparities in Hospital Length of Stay and the Hospital Readmission Reduction Program.

BACKGROUND: On average Black patients have longer LOS than comparable White patients. Longer hospital length of stay (LOS) may be associated with higher readmission risk. However, evidence suggests that the Hospital Readmission Reduction Program (HRRP) reduced overall racial differences in 30-day adjusted readmission risk. Yet, it is unclear whether the HRRP narrowed these LOS racial differences. OBJECTIVE: We examined the relationship between Medicare-insured Black-White differences in average, adjusted LOS (ALOS) and the HRRP's implementation and evaluation periods. METHODS: Using 2009-2017 data from State Inpatient Dataset from New York, New Jersey, and Florida, we employed an interrupted time series analysis with multivariate generalized regression models controlling for patient, disease, and hospital characteristics. Results are reported per 100 admissions. RESULTS: We found that for those discharged home, Black-White ALOS differences significantly widened by 4.15 days per 100 admissions (95% CI: 1.19 to 7.11, P < 0.001) for targeted conditions from before to after the HRRP implementation period, but narrowed in the HRRP evaluation period by 1.84 days per 100 admissions for every year-quarter (95% CI: -2.86 to -0.82, P < 0.001); for those discharged to non-home destinations, there was no significant change between HRRP periods, but ALOS differences widened over the study period. Black-White ALOS differences for non-targeted conditions remained unchanged regardless of HRRP phase and discharge destination. CONCLUSION: Increased LOS for Black patients may have played a role in reducing Black-White disparities in 30-day readmission risks for targeted conditions among patients discharged to home.

Trends in Medical and Surgical Admission Length of Stay by Race/Ethnicity and Socioeconomic Status: A Time Series Analysis.

BACKGROUND: Length of stay (LOS), a metric of hospital efficiency, differs by race/ethnicity and socioeconomic status (SES) and longer LOS is associated with adverse health outcomes. Historically, projects to improve LOS efficiency have yielded LOS reductions by 0.3 to 0.7 days per admission. OBJECTIVE: To assess differences in average adjusted length of stay (aALOS) over time by race/ethnicity, and SES stratified by discharge destination (home or non-home). METHOD: Data were obtained from 2009-2014 Healthcare Cost and Utilization Project State Inpatient Datasets for New York, New Jersey, and Florida. Multivariate generalized linear models were used to examine trends in aALOS differences by race/ethnicity, and by high vs low SES patients (defined first vs fourth quartile of median income by zip code) controlling for patient, disease and hospital characteristics. RESULTS: For those discharged home, racial/ethnic and SES aALOS differences remained stable from 2009 to 2014. However, among those discharged to non-home destinations, Black vs White aALOS differences increased from 0.21 days in Q1 2009, (95% confidence interval (CI): 0.13 to 0.30) to 0.32 days in Q3 2013, (95% CI: 0.23 to 0.40), and for low vs high SES patients from 0.03 days in Q1 2009 (95% CI: -0.04 to 0.1) to 0.26 days, (95% CI: 0.19 to 0.34). Notably, for patients not discharged home, racial/ethnic and SES aALOS differences increased and persisted after Q3 2011, coinciding with the introduction of the Affordable Care Act (ACA). CONCLUSION: Further research to understand the ACA's policy impact on hospital efficiencies, and relationship to racial/ethnic and SES differences in LOS is warranted.

Thirty-Day Post-Discharge Outcomes Following COVID-19 Infection.

BACKGROUND: The clinical course of COVID-19 includes multiple disease phases. Data describing post-hospital discharge outcomes may provide insight into disease course. Studies describing post-hospitalization outcomes of adults following COVID-19 infection are limited to electronic medical record review, which may underestimate the incidence of outcomes. OBJECTIVE: To determine 30-day post-hospitalization outcomes following COVID-19 infection. DESIGN: Retrospective cohort study SETTING: Quaternary referral hospital and community hospital in New York City. PARTICIPANTS: COVID-19 infected patients discharged alive from the emergency department (ED) or hospital between March 3 and May 15, 2020. MEASUREMENT: Outcomes included return to an ED, re-hospitalization, and mortality within 30 days of hospital discharge. RESULTS: Thirty-day follow-up data were successfully collected on 94.6% of eligible patients. Among 1344 patients, 16.5% returned to an ED, 9.8% were re-hospitalized, and 2.4% died. Among patients who returned to the ED, 50.0% (108/216) went to a different hospital from the hospital of the index presentation, and 61.1% (132/216) of those who returned were re-hospitalized. In Cox models adjusted for variables selected using the lasso method, age (HR 1.01 per year [95% CI 1.00-1.02]), diabetes (1.54 [1.06-2.23]), and the need for inpatient dialysis (3.78 [2.23-6.43]) during the index presentation were independently associated with a higher re-hospitalization rate. Older age (HR 1.08 [1.05-1.11]) and Asian race (2.89 [1.27-6.61]) were significantly associated with mortality. CONCLUSIONS: Among patients discharged alive following their index presentation for COVID-19, risk for returning to a hospital within 30 days of discharge was substantial. These patients merit close post-discharge follow-up to optimize outcomes.