The Impact of Housing Insecurity on Hospitalized Patients with Diagnosis of Cirrhosis: A Comparative Analysis Using Data from the National Inpatient Sample (2016-2021)

The Impact of Housing Insecurity on Hospitalized Patients with Diagnosis of Cirrhosis: A Comparative Analysis Using Data from the National Inpatient Sample (2016-2021) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Impact of Housing Insecurity on Hospitalized Patients with Diagnosis of Cirrhosis: A Comparative Analysis Using Data from the National Inpatient Sample (2016-2021) Joseph A Akambase, Yasmin Ali, Spencer R Goble This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5758007/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Patients experiencing homelessness are disproportionately affected by cirrhosis due to socioeconomic barriers, housing insecurity, and healthcare access challenges. However, the impact of homelessness on clinical outcomes and healthcare utilization among hospitalized cirrhosis patients has not been well-characterized. Methods We conducted a cross-sectional study using the National Inpatient Sample (2016–2021) to analyze hospitalizations of adults with cirrhosis, comparing outcomes between those with and without homelessness. Demographic, clinical, and hospital-level characteristics were assessed, along with outcomes such as mortality and AMA discharges. Healthcare utilization metrics, including length of stay (LOS) and cost, were also evaluated, with multivariable regression used to adjust for confounders Results Among 4,579,858 hospitalizations for cirrhosis, 109,640 (2.4%) involved homeless patients, who were younger (mean 53.5 vs. 60.6 years, p < 0.001) and predominantly male (80.4% vs. 58.9%, p < 0.001). Homeless patients had higher rates of alcohol use (73.5% vs. 30.9%, p < 0.001), opioid use disorder (11.8% vs. 3.6%, p < 0.001), and psychiatric comorbidities (62% vs. 37.4%, p < 0.001). Hispanic and Native American patients were overrepresented, while white patients were underrepresented. Mortality was lower in homeless patients ([aOR] 0.46, 95% CI: 0.42–0.50, p < 0.001). However, AMA discharges were significantly higher (9.6% vs. 2.7%, p < 0.001). Homeless patients had longer hospital stays (mean 7.3 vs. 6.2 days, p < 0.001) but lower per-day hospitalization costs ( $ 2,278 vs. $ 2,859, p < 0.001). Conclusion Homelessness is associated with distinct clinical and healthcare utilization patterns among hospitalized patients with cirrhosis. Despite lower mortality and procedural intervention rates, high AMA discharge rates and prolonged hospital stays underscore the challenges to safe discharge among patient with cirrhosis. Homelessness Cirrhosis Length of stay mortality Introduction The prevalence of liver cirrhosis in the United States has significantly increased, rising from an estimated 0.27% in 2010 to 0.71% in 2018, now affecting over 600,000 adults [ 1 , 2 ]. Globally, liver cirrhosis is responsible for more than 1 million deaths annually and significantly contributes to disability-adjusted life years (DALYs) [ 3 , 4 ]. In the U.S., the economic burden of cirrhosis is substantial, with annual costs estimated at $ 32.5 billion in 2016 [ 5 ]. Moreover, the cost of care for cirrhosis patients is notably higher than for many other chronic conditions, with average annual expenses reaching $ 35,029 in the first year of treatment and ranging from $ 14,216 to $ 17,629 in subsequent years [ 6 ]. The impact of cirrhosis disproportionately affects racial and ethnic minorities, as well as individuals with lower socioeconomic status, who experience poorer health outcomes, including higher rates of hospital readmissions. A study by Chirapongsathorn et al. found that the estimated annual cost of readmissions for cirrhosis patients within 30 days is $ 73,252 per patient [ 7 ]. Additionally, patients from low-income households are 32% more likely to be readmitted [ 8 ]. Housing insecurity further exacerbates these challenges, limiting access to appropriate healthcare due to financial constraints, lack of insurance, transportation difficulties, and stigma [ 9 , 10 ]. This often leads to delayed care-seeking, with patients typically presenting only during acute crises, resulting in increased reliance on emergency department services [ 11 ]. Moreover, housing instability contributes to medication non-adherence and delayed treatment, ultimately leading to worse health outcomes [ 12 , 13 ]. Notably, studies have shown that veterans with liver cirrhosis who face housing insecurity have a 24% higher risk of all-cause mortality [ 14 ]. Housing insecurity is a significant yet often understudied social determinant of health that can affect hospital outcomes. Patients with cirrhosis are particularly vulnerable to its challenges. Despite the known risks, there is limited data on its impact on hospitalized patients with liver cirrhosis. Therefore, this study aims to investigate the outcomes of homelessness among hospitalized patients with liver cirrhosis at a national level. Methods Study Design and Database Description This is an exploratory, cross-sectional study that uses that National Inpatient Sample (NIS). The NIS is the largest all-payer inpatient database within the United States. It incorporates a systematic, stratified sampling design to select approximately 7 million hospitalizations annually within the United States and after weighting, it provides estimations for the entire United States inpatient population. The standardized weighting procedures, as supplied by the Healthcare Cost and Utilization Project, were used for this study and all results are weighted. The NIS provides demographic, clinical and outcome data for individual hospitalizations. Available clinical data includes a primary admission diagnosis (the diagnosis chiefly responsible for the admission) and secondary diagnoses which can encompass chronic medical conditions and complication of the hospitalization. Diagnoses are defined by ICD-10 diagnostic codes. Available outcome data includes inpatient procedures (defined by ICD-10 procedure codes), inpatient mortality, where a patient discharges to, length of hospital stay (LOS) and total hospital charges. Cost can be determined by using the charges to cost conversion files provided by the Healthcare Cost and Utilization Project. The NIS is publicly available and deidentified and therefore Institutional Board Review approval was waived. Study Sample and Variables All hospitalizations between the years 2016–2021 for any adult patient with a primary or secondary diagnosis of cirrhosis were assessed. Patients with a primary or secondary diagnosis of homelessness were compared to those with no documented diagnosis of homelessness. The presence of homelessness was established by the relevant ICD-10 diagnostic code (Table S1). Demographic, clinical, and hospital-level characteristics were compared between those experiencing and not experiencing homelessness with the relevant comparisons found in Table 1 . Cirrhosis-specific clinical comparisons were also made with the proportion of patients with decompensated cirrhosis calculated for each cohort. Decompensated cirrhosis was defined as the presence of a primary or secondary diagnosis of any of the following: hepatorenal syndrome, spontaneous bacteria peritonitis, ascites, hepatic encephalopathy and esophageal variceal hemorrhage. Clinical and Healthcare Utilization Outcomes The following clinical outcomes were compared between patients experiencing homelessness and those not experiencing homelessness: mortality, cardiopulmonary resuscitation (CPR) rates, mechanical ventilation, renal replacement therapy (RRT), and against medical advice (AMA) discharge. CPR, mechanical ventilation and RRT rates were all determined by the presence of relevant ICD-10 procedure codes while mortality and AMA discharge or each specific variables included within the NIS. LOS and cost were the assessed healthcare utilization outcomes with the mean for each compared between those experiencing homelessness and those not experiencing homelessness. Statistical analysis In the comparison of basic clinical and demographic data, the student’s t-test was used to assess continuous variables while chi-square was used to assess categorical variables. Clinical outcomes are displayed both as percentages and as rates per 1,000 admissions. The differences between clinical outcomes in the two cohorts are displayed both as odds ratios (OR) and absolute risk differences (ARD) per 1,000 admissions. LOS and cost are displayed as means with rate ratios (RR) utilized to describe differences between the two cohorts. Additionally, the proportion of hospital days and cost for all hospitalizations for patients with cirrhosis attributable to each cohort was calculated by dividing the total hospital days and total cost for each cohort by the total hospital days and total cost respectively for all hospitalizations for patients with cirrhosis. Multivariable logistic regression was used to assess associations between homelessness and all of the assessed clinical outcomes. LOS associations were evaluated with multivariable negative binomial regression while a log-gamma model was used to assess for association between homelessness and cost. Both LOS and cost associations and presented as rate ratios that are the products of exponentiated coefficients. For each multivariable assessment, a univariable screen was used to determine which variables would be included in the multivariable model with a p- value of less than 0.20 on univariable screen needed for inclusion in the multivariable model (Tables S2-S8). The following were the candidate variables for each multivariable analysis: age, sex, race, hospital region, primary payer, Charlson Comorbidity Index, and hospital bed size. All statistical computations were performed with STATA, version 17.0. Results Demographic and clinical characteristics Of the assessed 4,579,858 hospitalizations, 109,640 (2.4%) were for patients experiencing homelessness. Mean age of the combined cohort (housed and homeless) was 60.4 years while 59.5% of all patients were males and the majority (66.5%) were white. Those experiencing homelessness were younger (mean 53.5 vs 60.6 years, p < 0.001) and more likely to be male (80.4% vs 58.9%, p < 0.001) (Table 1 ). Rates of homelessness ranged from 1.5% in Asian or Pacific Islander patients to 4.8% in Native American patients. When assessed by United States region, homelessness rates were highest in the West (43.3%) and lowest in the Midwest (10.9%). Alcohol use related diagnoses and opioid use disorder were both significantly higher in the homeless cohort in comparison to the housed cohort ( P -values both < 0.001). In patients with a substance-use-related diagnosis (alcohol or opioid), the homelessness rate was 4.3% which was significantly higher than the 0.9% in patients without a substance-use-related diagnosis (OR = 4.88, 95% CI: 4.71–5.06, p < 0.001). The presence of a mental health diagnosis was higher in those experiencing homelessness with 62.0% of patients having at least one of the mental health diagnoses listed in Table 1 compared to only 37.4% of patients not experiencing homelessness (p < 0.001). In contrast, diabetes, obesity, hyperlipidemia, hypertension and chronic kidney disease rates were all lower in those experiencing homelessness compared to those not experiencing homelessness ( P -values all < 0.001) (Table 1 ). Table 1 Comparison of characteristics of hospitalizations for patients with cirrhosis 2016–2021 experiencing and not experiencing homelessness Variable Experiencing homelessness Not experiencing homelessness P -Value Sample size 109,640 4,470,218 Mean age, years 53.5 60.6 < 0.001** Female, % 19.6 41.1 < 0.001** Race, % White 60.1 66.7 < 0.001** Black 10.4 10.3 0.646 Hispanic 21.5 16.5 < 0.001** Asian or Pacific Islander 1.3 2.1 < 0.001** Native American 3.4 1.7 < 0.001** Other 3.3 2.8 < 0.001** Hospital region, % Northeast 14.6 16.7 < 0.001** Midwest 10.9 20.3 < 0.001** South 31.3 40.3 < 0.001** West 43.3 22.7 < 0.001** Decompensated cirrhosis, % 44.6 55.5 < 0.001** Alcohol use, % 73.5 40.9 < 0.001** Hepatitis C virus, % 39.9 18.6 < 0.001** Hepatitis B virus, % 3.2 2.1 < 0.001** Autoimmune hepatitis, % 0.3 1.2 < 0.001** Primary biliary cholangitis, % 0.1 1.8 < 0.001** Primary sclerosing cholangitis, % 0.1 0.3 < 0.001** Diabetes, % 9.6 14.3 < 0.001** Obesity, % 8.8 16.8 < 0.001** Hyperlipidemia, % 10.1 25.8 < 0.001** Hypertension, % 48.5 62.0 < 0.001** Tobacco use, % 53.3 24.5 < 0.001** Chronic kidney disease, % 8.8 23.8 < 0.001** Human immunodeficiency virus, % 2.5 1.2 < 0.001** Opioid use disorder, % 11.8 3.6 < 0.001** Generalized anxiety disorder, % 17.3 14.7 < 0.001** Major depressive disorder, % 21.5 15.9 < 0.001** Bipolar disorder, % 9.5 3.3 < 0.001** Post-traumatic stress disorder, % 5.0 1.5 < 0.001** Schizophrenia, % 8.6 2.0 < 0.001** * p < 0.05, ** p < 0.001 Clinical outcomes Mortality for all assessed hospitalizations of patients with cirrhosis was 6.2%. Mortality in hospitalizations for those experiencing homelessness was significantly lower than mortality in hospitalizations for those not experiencing homelessness (ARD = 34.7:1,000, aOR = 0.46, 95% CI: 0.42–0.50, p < 0.001). CPR was used in 0.8% of all assessed hospitalizations while mechanical ventilation was used in 7.4% and RRT was used in 5.2%. Those experiencing homelessness had lower rates of CPR (ARD = 2.0:1,000), mechanical ventilation (ARD = 24.2:1,000) and RRT (ARD = 37.2:1,000) with each of those differences being statistically significant ( P -values all < 0.001) (Table 2 ). By contrast, rates of AMA discharge were higher in those experiencing homelessness (ARD = 71.4:1,000) with nearly 10% of all admissions for patients experiencing homelessness ending in an AMA discharge compared to only 2.7% in patients not experiencing homelessness (Table 2 ). Healthcare utilization outcomes Mean LOS for all assessed hospitalizations was 6.2 days. Those experiencing homelessness had a greater than 1 day increase in LOS compared to those not experiencing homelessness (mean 7.3 vs 6.2 days, p < 0.001). When restricting analysis to just those experiencing homelessness, LOS was shorter in those who discharged AMA compared to those who did not (mean 4.7 vs 6.2 days, aRR = 0.62, 95% CI: 0.58–0.66, p < 0.001). Mean cost of all assessed hospitalizations was $ 17,654. Cost was significantly lower in hospitalizations for those experiencing homelessness in comparison to those not experiencing homelessness (mean $ 16,547 vs $ 17,681, p < 0.001). In addition, mean cost per each hospitalization day was lower in those experiencing homelessness ( $ 2,278 vs $ 2,859, p < 0.001) (Table 2 ). Table 2 Comparison of clinical and healthcare utilization outcomes for patients with cirrhosis 2016–2021 experiencing and not experiencing homelessness Experiencing homelessness Not experiencing homelessness Clinical outcomes Total Rate per 1,000 hospitalizations Total Rate per 1,000 hospitalizations Adjusted odds ratio (95% CI) P -value Death a 3,030 27.6 278,500 62.3 0.46 (0.42–0.50) < 0.001** Cardiopulmonary resuscitation a 630 5.7 34,265 7.7 0.70 (0.59–0.84) < 0.001** Mechanical ventilation a 5,475 50.0 331,475 74.2 0.57 (0.54–0.61) < 0.001** Renal replacement therapy b 1,745 15.9 237,190 53.1 0.41 (0.36–0.46) < 0.001** Against medical advicedischarge a 10,824 98.7 122,420 27.3 2.23 (2.11–2.35) < 0.001** Utilization outcomes Mean Proportion of all admissions c Mean Proportion of all admissions c Adjusted rate ratio (95% CI) P -value Length of stay (days) a 7.3 2.9% 6.2 97.1% 1.19 (1.17–1.22) < 0.001** Cost (U.S dollars) a $ 16,547 2.3% $ 17,681 97.7% 0.92 (0.90–0.94) < 0.001** a Odds ratio adjusted for age, sex, race, hospital region, primary payer, Charlson Comorbidity Index, and hospital bed size b Odds ratio adjusted for sex, race, hospital region, primary payer, Charlson Comorbidity Index, and hospital bed size c Proportional assessments calculated as the proportion of all hospital days and all hospital costs in patients with cirrhosis attributed to those with and without a secondary diagnosis of homelessness * p < 0.05, ** p < 0.001 Discussion The findings of this study highlight significant disparities in healthcare outcomes and utilization between patients experiencing homelessness and those with stable housing, particularly among individuals with cirrhosis. While previous research has documented the vulnerability of homeless populations, by leveraging a large, nationally representative inpatient database, our findings provide critical insights into the unique vulnerabilities and challenges faced by this population. Patients experiencing homelessness were younger, predominantly male, and had higher rates of substance use, chronic viral infections, and mental health conditions, highlighting their multifaceted vulnerabilities as previously noted by others [ 15 ]. AMA discharges were significantly more common in this group, occurring in nearly 10% of hospitalizations compared to 2.7% among housed patients (aOR 2.23, p < 0.001). This trend likely reflects the combined effects of housing insecurity, financial barriers, and stigma, which hinder care engagement and adherence. AMA discharges are linked to increased hospital readmissions, poorer outcomes, and higher long-term costs, underscoring the need for targeted interventions [ 16 ]. Despite these challenges, patients experiencing homelessness had a lower adjusted mortality rate compared to housed patients (aOR 0.46, p < 0.001), a finding likely influenced by several factors. Homeless patients may present with acute, treatable conditions rather than advanced comorbidities, while their younger age and lower prevalence of chronic diseases like diabetes and kidney disease could further reduce mortality risk. Higher rates of AMA discharges might also skew mortality data by leading to earlier hospital departures. Additionally, lower use of advanced interventions, such as mechanical ventilation and RRT, may reflect disparities in care access, clinical decision-making, or patient preferences, warranting further investigation. Healthcare utilization outcomes revealed mixed patterns. Similar to reports of longer length of stay among people experiencing homelessness after an injury by Silver et al., patients experiencing homelessness with cirrhosis had longer hospital stays on average (7.3 vs. 6.2 days, p < 0.001) [ 17 ]. This longer LOS may reflect the complexity of social and health needs among homeless individuals, including the challenge of finding appropriate post-discharge care and housing. Interestingly, despite the longer LOS, the costs associated with hospitalizations per day for patients experiencing homelessness were lower than for housed patients ( $ 2,278 vs. $ 2,859, p < 0.001). These differences may reflect varying patterns of care delivery, resource use, and reimbursement rates across facilities serving homeless populations. However, the total cost of care for homeless patients remained substantial, underscoring the economic burden associated with this vulnerable group. These findings may highlight a disconnect between resource utilization and patient needs, where homeless individuals, though staying longer in the hospital, are not receiving more resource-intensive care, evidenced by the observed had lower rates of CPR, mechanical ventilation, and RRT among patients experiencing homelessness. Key strategies to address the challenges faced by homeless patients with cirrhosis include implementing multidisciplinary teams that integrate care for medical and social determinants of health, such as housing insecurity and mental health. Strengthening transitions of care is also critical, as it can reduce the high rates of AMA discharges and improve engagement with outpatient services. Additionally, expanding access to treatment programs for alcohol use disorder and opioid use disorder is particularly important for this vulnerable population. This study has limitations, including the use of administrative databases, which rely on ICD-10 codes and may lead to potential misclassification of diagnoses and procedures. The cross-sectional design also restricts causal inferences, and unmeasured confounders could influence the observed associations. Future research should investigate the longitudinal outcomes of homeless patients with cirrhosis, focusing on the impact of targeted interventions on both clinical and healthcare utilization outcomes. Qualitative studies would also provide valuable insights into the barriers homeless individuals face in accessing and adhering to care. In summary, this study underscores critical disparities in healthcare utilization and clinical outcomes among homeless individuals with cirrhosis. The observed lower mortality and reduced use of life-saving interventions in homeless patients, alongside longer hospital stays and lower overall costs, suggest differential treatment from their housed counterparts. These disparities appear to stem from a combination of social, clinical, and systemic healthcare factors. Addressing these issues requires tailored interventions that recognize and accommodate the complex social and medical needs of homeless individuals. Such efforts must aim to improve access to comprehensive and equitable care. Further research is essential to uncover the root causes of these disparities and to develop effective strategies for better supporting homeless patients, particularly those with chronic conditions like cirrhosis. Declarations Author Contribution "J.A., Y.A. and S.G. wrote the main manuscript text. All authors reviewed the manuscript." Potential competing interests: None Financial support: None References Scaglione S, Kliethermes S, Cao G, Shoham D, Durazo R, Luke A, et al. The Epidemiology of Cirrhosis in the United States: A Population-based Study. Journal of Clinical Gastroenterology. 2015 Sep;49(8):690–6. Ladner DP, Gmeiner M, Hasjim BJ, Mazumder N, Kang R, Parker E, et al. Increasing prevalence of cirrhosis among insured adults in the United States, 2012–2018. PLoS ONE. 2024 Feb;19(2):e0298887. Asrani SK, Devarbhavi H, Eaton J, Kamath PS. Burden of liver diseases in the world. Journal of Hepatology. 2019 Jan;70(1):151–71. Rehm J, Samokhvalov AV, Shield KD. Global burden of alcoholic liver diseases. Journal of Hepatology. 2013 Jul;59(1):160–8. Ma C, Qian AS, Nguyen NH, Stukalin I, Congly SE, Shaheen AA, et al. Trends in the Economic Burden of Chronic Liver Diseases and Cirrhosis in the United States: 1996–2016. Am J Gastroenterol. 2021 Oct;116(10):2060–7. Kanwal F, Nelson R, Liu Y, Kramer JR, Hernaez R, Cholankeril G, et al. Cost of Care for Patients With Cirrhosis. Am J Gastroenterol. 2024 Mar;119(3):497–504. Chirapongsathorn S, Krittanawong C, Enders FT, Pendegraft R, Mara KC, Borah BJ, et al. Incidence and cost analysis of hospital admission and 30‐day readmission among patients with cirrhosis. Hepatology Communications. 2018 Feb;2(2):188–98. Brahmania M, Wiskar K, Walley KR, Celi LA, Rush B. Lower household income is associated with an increased risk of hospital readmission in patients with decompensated cirrhosis. J of Gastro and Hepatol. 2021 Apr;36(4):1088–94. Culhane DP, Metraux S, Byrne T, Stino M, Bainbridge J. The Age Structure of Contemporary Homelessness: Evidence and Implications For Public Policy. Anal Soc Iss & Public Policy. 2013 Dec;13(1):228–44. Ufere NN, Lago-Hernandez C, Alejandro-Soto A, Walker T, Li L, Schoener K, et al. Health care–related transportation insecurity is associated with adverse health outcomes among adults with chronic liver disease. Hepatology Communications. 2024 Jan;8(1). DOI: 10.1097/HC9.0000000000000358 Clemenzi-Allen A, Neuhaus J, Geng E, Sachdev D, Buchbinder S, Havlir D, et al. Housing Instability Results in Increased Acute Care Utilization in an Urban HIV Clinic Cohort. Open Forum Infectious Diseases. 2019 May;6(5):ofz148. Harris RA, Xue X, Selwyn PA. Housing Stability and Medication Adherence among HIV-Positive Individuals in Antiretroviral Therapy: A Meta-Analysis of Observational Studies in the United States. JAIDS Journal of Acquired Immune Deficiency Syndromes. 2017 Mar;74(3):309–17. Surratt HL, O’Grady CL, Levi-Minzi MA, Kurtz SP. Medication adherence challenges among HIV positive substance abusers: the role of food and housing insecurity. AIDS Care. 2015 Mar;27(3):307–14. Rogal SS, Yakovchenko V, Gonzalez R, Park A, Lamorte C, Gibson SP, et al. Characterizing patient-reported outcomes in veterans with cirrhosis. PLoS ONE. 2020 Sep;15(9):e0238712. Taylor SN, Munson D. Health Care of People Experiencing Homelessness: Part II. NEJM Evidence. 2023 Aug;2(9). DOI: 10.1056/EVIDra2300175 Southern WN, Nahvi S, Arnsten JH. Increased Risk of Mortality and Readmission among Patients Discharged Against Medical Advice. The American Journal of Medicine. 2012 Jun;125(6):594–602. Silver CM, Thomas AC, Reddy S, Kirkendoll S, Nathens AB, Issa N, et al. Morbidity and Length of Stay After Injury Among People Experiencing Homelessness in North America. JAMA Netw Open. 2024 Feb;7(2):e240795. Tables S1-S8 Tables S1-S8 are not available with this version Additional Declarations No competing interests reported. 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Globally, liver cirrhosis is responsible for more than 1\u0026nbsp;million deaths annually and significantly contributes to disability-adjusted life years (DALYs) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In the U.S., the economic burden of cirrhosis is substantial, with annual costs estimated at \u003cspan\u003e$\u003c/span\u003e32.5\u0026nbsp;billion in 2016 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover, the cost of care for cirrhosis patients is notably higher than for many other chronic conditions, with average annual expenses reaching \u003cspan\u003e$\u003c/span\u003e35,029 in the first year of treatment and ranging from \u003cspan\u003e$\u003c/span\u003e14,216 to \u003cspan\u003e$\u003c/span\u003e17,629 in subsequent years [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe impact of cirrhosis disproportionately affects racial and ethnic minorities, as well as individuals with lower socioeconomic status, who experience poorer health outcomes, including higher rates of hospital readmissions. A study by Chirapongsathorn et al. found that the estimated annual cost of readmissions for cirrhosis patients within 30 days is \u003cspan\u003e$\u003c/span\u003e73,252 per patient [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Additionally, patients from low-income households are 32% more likely to be readmitted [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Housing insecurity further exacerbates these challenges, limiting access to appropriate healthcare due to financial constraints, lack of insurance, transportation difficulties, and stigma [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This often leads to delayed care-seeking, with patients typically presenting only during acute crises, resulting in increased reliance on emergency department services [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Moreover, housing instability contributes to medication non-adherence and delayed treatment, ultimately leading to worse health outcomes [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Notably, studies have shown that veterans with liver cirrhosis who face housing insecurity have a 24% higher risk of all-cause mortality [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHousing insecurity is a significant yet often understudied social determinant of health that can affect hospital outcomes. Patients with cirrhosis are particularly vulnerable to its challenges. Despite the known risks, there is limited data on its impact on hospitalized patients with liver cirrhosis. Therefore, this study aims to investigate the outcomes of homelessness among hospitalized patients with liver cirrhosis at a national level.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Database Description\u003c/h2\u003e \u003cp\u003eThis is an exploratory, cross-sectional study that uses that National Inpatient Sample (NIS). The NIS is the largest all-payer inpatient database within the United States. It incorporates a systematic, stratified sampling design to select approximately 7\u0026nbsp;million hospitalizations annually within the United States and after weighting, it provides estimations for the entire United States inpatient population. The standardized weighting procedures, as supplied by the Healthcare Cost and Utilization Project, were used for this study and all results are weighted. The NIS provides demographic, clinical and outcome data for individual hospitalizations. Available clinical data includes a primary admission diagnosis (the diagnosis chiefly responsible for the admission) and secondary diagnoses which can encompass chronic medical conditions and complication of the hospitalization. Diagnoses are defined by ICD-10 diagnostic codes. Available outcome data includes inpatient procedures (defined by ICD-10 procedure codes), inpatient mortality, where a patient discharges to, length of hospital stay (LOS) and total hospital charges. Cost can be determined by using the charges to cost conversion files provided by the Healthcare Cost and Utilization Project. The NIS is publicly available and deidentified and therefore Institutional Board Review approval was waived.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Sample and Variables\u003c/h3\u003e\n\u003cp\u003eAll hospitalizations between the years 2016\u0026ndash;2021 for any adult patient with a primary or secondary diagnosis of cirrhosis were assessed. Patients with a primary or secondary diagnosis of homelessness were compared to those with no documented diagnosis of homelessness. The presence of homelessness was established by the relevant ICD-10 diagnostic code (Table S1). Demographic, clinical, and hospital-level characteristics were compared between those experiencing and not experiencing homelessness with the relevant comparisons found in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Cirrhosis-specific clinical comparisons were also made with the proportion of patients with decompensated cirrhosis calculated for each cohort. Decompensated cirrhosis was defined as the presence of a primary or secondary diagnosis of any of the following: hepatorenal syndrome, spontaneous bacteria peritonitis, ascites, hepatic encephalopathy and esophageal variceal hemorrhage.\u003c/p\u003e\n\u003ch3\u003eClinical and Healthcare Utilization Outcomes\u003c/h3\u003e\n\u003cp\u003eThe following clinical outcomes were compared between patients experiencing homelessness and those not experiencing homelessness: mortality, cardiopulmonary resuscitation (CPR) rates, mechanical ventilation, renal replacement therapy (RRT), and against medical advice (AMA) discharge. CPR, mechanical ventilation and RRT rates were all determined by the presence of relevant ICD-10 procedure codes while mortality and AMA discharge or each specific variables included within the NIS. LOS and cost were the assessed healthcare utilization outcomes with the mean for each compared between those experiencing homelessness and those not experiencing homelessness.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eIn the comparison of basic clinical and demographic data, the student\u0026rsquo;s t-test was used to assess continuous variables while chi-square was used to assess categorical variables. Clinical outcomes are displayed both as percentages and as rates per 1,000 admissions. The differences between clinical outcomes in the two cohorts are displayed both as odds ratios (OR) and absolute risk differences (ARD) per 1,000 admissions. LOS and cost are displayed as means with rate ratios (RR) utilized to describe differences between the two cohorts. Additionally, the proportion of hospital days and cost for all hospitalizations for patients with cirrhosis attributable to each cohort was calculated by dividing the total hospital days and total cost for each cohort by the total hospital days and total cost respectively for all hospitalizations for patients with cirrhosis.\u003c/p\u003e \u003cp\u003eMultivariable logistic regression was used to assess associations between homelessness and all of the assessed clinical outcomes. LOS associations were evaluated with multivariable negative binomial regression while a log-gamma model was used to assess for association between homelessness and cost. Both LOS and cost associations and presented as rate ratios that are the products of exponentiated coefficients. For each multivariable assessment, a univariable screen was used to determine which variables would be included in the multivariable model with a \u003cem\u003ep-\u003c/em\u003evalue of less than 0.20 on univariable screen needed for inclusion in the multivariable model (Tables S2-S8). The following were the candidate variables for each multivariable analysis: age, sex, race, hospital region, primary payer, Charlson Comorbidity Index, and hospital bed size. All statistical computations were performed with STATA, version 17.0.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDemographic and clinical characteristics\u003c/h2\u003e \u003cp\u003eOf the assessed 4,579,858 hospitalizations, 109,640 (2.4%) were for patients experiencing homelessness. Mean age of the combined cohort (housed and homeless) was 60.4 years while 59.5% of all patients were males and the majority (66.5%) were white. Those experiencing homelessness were younger (mean 53.5 vs 60.6 years, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and more likely to be male (80.4% vs 58.9%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Rates of homelessness ranged from 1.5% in Asian or Pacific Islander patients to 4.8% in Native American patients. When assessed by United States region, homelessness rates were highest in the West (43.3%) and lowest in the Midwest (10.9%).\u003c/p\u003e \u003cp\u003eAlcohol use related diagnoses and opioid use disorder were both significantly higher in the homeless cohort in comparison to the housed cohort (\u003cem\u003eP\u003c/em\u003e-values both \u0026lt;\u0026thinsp;0.001). In patients with a substance-use-related diagnosis (alcohol or opioid), the homelessness rate was 4.3% which was significantly higher than the 0.9% in patients without a substance-use-related diagnosis (OR\u0026thinsp;=\u0026thinsp;4.88, 95% CI: 4.71\u0026ndash;5.06, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The presence of a mental health diagnosis was higher in those experiencing homelessness with 62.0% of patients having at least one of the mental health diagnoses listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e compared to only 37.4% of patients not experiencing homelessness (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In contrast, diabetes, obesity, hyperlipidemia, hypertension and chronic kidney disease rates were all lower in those experiencing homelessness compared to those not experiencing homelessness (\u003cem\u003eP\u003c/em\u003e-values all \u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of characteristics of hospitalizations for patients with cirrhosis 2016\u0026ndash;2021 experiencing and not experiencing homelessness\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExperiencing homelessness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot experiencing homelessness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109,640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,470,218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean age, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.646\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNative American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital region, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMidwest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecompensated cirrhosis, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol use, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis C virus, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis B virus, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAutoimmune hepatitis, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary biliary cholangitis, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary sclerosing cholangitis, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipidemia, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTobacco use, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman immunodeficiency virus, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOpioid use disorder, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneralized anxiety disorder, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor depressive disorder, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBipolar disorder, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-traumatic stress disorder, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSchizophrenia, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClinical outcomes\u003c/h3\u003e\n\u003cp\u003eMortality for all assessed hospitalizations of patients with cirrhosis was 6.2%. Mortality in hospitalizations for those experiencing homelessness was significantly lower than mortality in hospitalizations for those not experiencing homelessness (ARD\u0026thinsp;=\u0026thinsp;34.7:1,000, aOR\u0026thinsp;=\u0026thinsp;0.46, 95% CI: 0.42\u0026ndash;0.50, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). CPR was used in 0.8% of all assessed hospitalizations while mechanical ventilation was used in 7.4% and RRT was used in 5.2%. Those experiencing homelessness had lower rates of CPR (ARD\u0026thinsp;=\u0026thinsp;2.0:1,000), mechanical ventilation (ARD\u0026thinsp;=\u0026thinsp;24.2:1,000) and RRT (ARD\u0026thinsp;=\u0026thinsp;37.2:1,000) with each of those differences being statistically significant (\u003cem\u003eP\u003c/em\u003e-values all \u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). By contrast, rates of AMA discharge were higher in those experiencing homelessness (ARD\u0026thinsp;=\u0026thinsp;71.4:1,000) with nearly 10% of all admissions for patients experiencing homelessness ending in an AMA discharge compared to only 2.7% in patients not experiencing homelessness (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eHealthcare utilization outcomes\u003c/h3\u003e\n\u003cp\u003eMean LOS for all assessed hospitalizations was 6.2 days. Those experiencing homelessness had a greater than 1 day increase in LOS compared to those not experiencing homelessness (mean 7.3 vs 6.2 days, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). When restricting analysis to just those experiencing homelessness, LOS was shorter in those who discharged AMA compared to those who did not (mean 4.7 vs 6.2 days, aRR\u0026thinsp;=\u0026thinsp;0.62, 95% CI: 0.58\u0026ndash;0.66, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Mean cost of all assessed hospitalizations was \u003cspan\u003e$\u003c/span\u003e17,654. Cost was significantly lower in hospitalizations for those experiencing homelessness in comparison to those not experiencing homelessness (mean \u003cspan\u003e$\u003c/span\u003e16,547 vs \u003cspan\u003e$\u003c/span\u003e17,681, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In addition, mean cost per each hospitalization day was lower in those experiencing homelessness (\u003cspan\u003e$\u003c/span\u003e2,278 vs \u003cspan\u003e$\u003c/span\u003e2,859, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of clinical and healthcare utilization outcomes for patients with cirrhosis 2016\u0026ndash;2021 experiencing and not experiencing homelessness\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eExperiencing homelessness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eNot experiencing homelessness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical outcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRate per 1,000 hospitalizations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRate per 1,000 hospitalizations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdjusted odds ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e278,500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.46 (0.42\u0026ndash;0.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiopulmonary resuscitation \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34,265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.70 (0.59\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical\u003c/p\u003e \u003cp\u003eventilation \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e331,475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57 (0.54\u0026ndash;0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal replacement therapy \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e237,190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.41 (0.36\u0026ndash;0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgainst medical advicedischarge \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122,420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.23 (2.11\u0026ndash;2.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUtilization outcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProportion of all admissions \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProportion of all admissions \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdjusted rate ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of stay (days) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.19 (1.17\u0026ndash;1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCost (U.S dollars) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e16,547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e17,681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92 (0.90\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003e Odds ratio adjusted for age, sex, race, hospital region, primary payer, Charlson Comorbidity Index, and hospital bed size\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003eb\u003c/sup\u003e Odds ratio adjusted for sex, race, hospital region, primary payer, Charlson Comorbidity Index, and hospital bed size\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ec\u003c/sup\u003e Proportional assessments calculated as the proportion of all hospital days and all hospital costs in patients with cirrhosis attributed to those with and without a secondary diagnosis of homelessness\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings of this study highlight significant disparities in healthcare outcomes and utilization between patients experiencing homelessness and those with stable housing, particularly among individuals with cirrhosis. While previous research has documented the vulnerability of homeless populations, by leveraging a large, nationally representative inpatient database, our findings provide critical insights into the unique vulnerabilities and challenges faced by this population.\u003c/p\u003e \u003cp\u003ePatients experiencing homelessness were younger, predominantly male, and had higher rates of substance use, chronic viral infections, and mental health conditions, highlighting their multifaceted vulnerabilities as previously noted by others [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. AMA discharges were significantly more common in this group, occurring in nearly 10% of hospitalizations compared to 2.7% among housed patients (aOR 2.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This trend likely reflects the combined effects of housing insecurity, financial barriers, and stigma, which hinder care engagement and adherence. AMA discharges are linked to increased hospital readmissions, poorer outcomes, and higher long-term costs, underscoring the need for targeted interventions [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite these challenges, patients experiencing homelessness had a lower adjusted mortality rate compared to housed patients (aOR 0.46, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), a finding likely influenced by several factors. Homeless patients may present with acute, treatable conditions rather than advanced comorbidities, while their younger age and lower prevalence of chronic diseases like diabetes and kidney disease could further reduce mortality risk. Higher rates of AMA discharges might also skew mortality data by leading to earlier hospital departures. Additionally, lower use of advanced interventions, such as mechanical ventilation and RRT, may reflect disparities in care access, clinical decision-making, or patient preferences, warranting further investigation.\u003c/p\u003e \u003cp\u003eHealthcare utilization outcomes revealed mixed patterns. Similar to reports of longer length of stay among people experiencing homelessness after an injury by Silver et al., patients experiencing homelessness with cirrhosis had longer hospital stays on average (7.3 vs. 6.2 days, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This longer LOS may reflect the complexity of social and health needs among homeless individuals, including the challenge of finding appropriate post-discharge care and housing. Interestingly, despite the longer LOS, the costs associated with hospitalizations per day for patients experiencing homelessness were lower than for housed patients (\u003cspan\u003e$\u003c/span\u003e2,278 vs. \u003cspan\u003e$\u003c/span\u003e2,859, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These differences may reflect varying patterns of care delivery, resource use, and reimbursement rates across facilities serving homeless populations. However, the total cost of care for homeless patients remained substantial, underscoring the economic burden associated with this vulnerable group. These findings may highlight a disconnect between resource utilization and patient needs, where homeless individuals, though staying longer in the hospital, are not receiving more resource-intensive care, evidenced by the observed had lower rates of CPR, mechanical ventilation, and RRT among patients experiencing homelessness.\u003c/p\u003e \u003cp\u003eKey strategies to address the challenges faced by homeless patients with cirrhosis include implementing multidisciplinary teams that integrate care for medical and social determinants of health, such as housing insecurity and mental health. Strengthening transitions of care is also critical, as it can reduce the high rates of AMA discharges and improve engagement with outpatient services. Additionally, expanding access to treatment programs for alcohol use disorder and opioid use disorder is particularly important for this vulnerable population.\u003c/p\u003e \u003cp\u003eThis study has limitations, including the use of administrative databases, which rely on ICD-10 codes and may lead to potential misclassification of diagnoses and procedures. The cross-sectional design also restricts causal inferences, and unmeasured confounders could influence the observed associations. Future research should investigate the longitudinal outcomes of homeless patients with cirrhosis, focusing on the impact of targeted interventions on both clinical and healthcare utilization outcomes. Qualitative studies would also provide valuable insights into the barriers homeless individuals face in accessing and adhering to care.\u003c/p\u003e \u003cp\u003eIn summary, this study underscores critical disparities in healthcare utilization and clinical outcomes among homeless individuals with cirrhosis. The observed lower mortality and reduced use of life-saving interventions in homeless patients, alongside longer hospital stays and lower overall costs, suggest differential treatment from their housed counterparts. These disparities appear to stem from a combination of social, clinical, and systemic healthcare factors. Addressing these issues requires tailored interventions that recognize and accommodate the complex social and medical needs of homeless individuals. Such efforts must aim to improve access to comprehensive and equitable care. Further research is essential to uncover the root causes of these disparities and to develop effective strategies for better supporting homeless patients, particularly those with chronic conditions like cirrhosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003e\"J.A., Y.A. and S.G. wrote the main manuscript text. All authors reviewed the manuscript.\"\u003c/p\u003e\u003cp\u003e\u003cstrong\u003ePotential competing interests:\u003c/strong\u003e None\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial support:\u003c/strong\u003e None\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eScaglione S, Kliethermes S, Cao G, Shoham D, Durazo R, Luke A, et al. The Epidemiology of Cirrhosis in the United States: A Population-based Study. Journal of Clinical Gastroenterology. 2015 Sep;49(8):690\u0026ndash;6. \u003c/li\u003e\n\u003cli\u003eLadner DP, Gmeiner M, Hasjim BJ, Mazumder N, Kang R, Parker E, et al. Increasing prevalence of cirrhosis among insured adults in the United States, 2012\u0026ndash;2018. PLoS ONE. 2024 Feb;19(2):e0298887. \u003c/li\u003e\n\u003cli\u003eAsrani SK, Devarbhavi H, Eaton J, Kamath PS. Burden of liver diseases in the world. Journal of Hepatology. 2019 Jan;70(1):151\u0026ndash;71. \u003c/li\u003e\n\u003cli\u003eRehm J, Samokhvalov AV, Shield KD. Global burden of alcoholic liver diseases. Journal of Hepatology. 2013 Jul;59(1):160\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eMa C, Qian AS, Nguyen NH, Stukalin I, Congly SE, Shaheen AA, et al. Trends in the Economic Burden of Chronic Liver Diseases and Cirrhosis in the United States: 1996\u0026ndash;2016. Am J Gastroenterol. 2021 Oct;116(10):2060\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eKanwal F, Nelson R, Liu Y, Kramer JR, Hernaez R, Cholankeril G, et al. Cost of Care for Patients With Cirrhosis. Am J Gastroenterol. 2024 Mar;119(3):497\u0026ndash;504. \u003c/li\u003e\n\u003cli\u003eChirapongsathorn S, Krittanawong C, Enders FT, Pendegraft R, Mara KC, Borah BJ, et al. Incidence and cost analysis of hospital admission and 30‐day readmission among patients with cirrhosis. Hepatology Communications. 2018 Feb;2(2):188\u0026ndash;98. \u003c/li\u003e\n\u003cli\u003eBrahmania M, Wiskar K, Walley KR, Celi LA, Rush B. Lower household income is associated with an increased risk of hospital readmission in patients with decompensated cirrhosis. J of Gastro and Hepatol. 2021 Apr;36(4):1088\u0026ndash;94. \u003c/li\u003e\n\u003cli\u003eCulhane DP, Metraux S, Byrne T, Stino M, Bainbridge J. The Age Structure of Contemporary Homelessness: Evidence and Implications For Public Policy. Anal Soc Iss \u0026amp; Public Policy. 2013 Dec;13(1):228\u0026ndash;44. \u003c/li\u003e\n\u003cli\u003eUfere NN, Lago-Hernandez C, Alejandro-Soto A, Walker T, Li L, Schoener K, et al. Health care\u0026ndash;related transportation insecurity is associated with adverse health outcomes among adults with chronic liver disease. Hepatology Communications. 2024 Jan;8(1). DOI: 10.1097/HC9.0000000000000358\u003c/li\u003e\n\u003cli\u003eClemenzi-Allen A, Neuhaus J, Geng E, Sachdev D, Buchbinder S, Havlir D, et al. Housing Instability Results in Increased Acute Care Utilization in an Urban HIV Clinic Cohort. Open Forum Infectious Diseases. 2019 May;6(5):ofz148. \u003c/li\u003e\n\u003cli\u003eHarris RA, Xue X, Selwyn PA. Housing Stability and Medication Adherence among HIV-Positive Individuals in Antiretroviral Therapy: A Meta-Analysis of Observational Studies in the United States. JAIDS Journal of Acquired Immune Deficiency Syndromes. 2017 Mar;74(3):309\u0026ndash;17. \u003c/li\u003e\n\u003cli\u003eSurratt HL, O\u0026rsquo;Grady CL, Levi-Minzi MA, Kurtz SP. Medication adherence challenges among HIV positive substance abusers: the role of food and housing insecurity. AIDS Care. 2015 Mar;27(3):307\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eRogal SS, Yakovchenko V, Gonzalez R, Park A, Lamorte C, Gibson SP, et al. Characterizing patient-reported outcomes in veterans with cirrhosis. PLoS ONE. 2020 Sep;15(9):e0238712. \u003c/li\u003e\n\u003cli\u003eTaylor SN, Munson D. Health Care of People Experiencing Homelessness: Part II. NEJM Evidence. 2023 Aug;2(9). DOI: 10.1056/EVIDra2300175\u003c/li\u003e\n\u003cli\u003eSouthern WN, Nahvi S, Arnsten JH. Increased Risk of Mortality and Readmission among Patients Discharged Against Medical Advice. The American Journal of Medicine. 2012 Jun;125(6):594\u0026ndash;602. \u003c/li\u003e\n\u003cli\u003eSilver CM, Thomas AC, Reddy S, Kirkendoll S, Nathens AB, Issa N, et al. Morbidity and Length of Stay After Injury Among People Experiencing Homelessness in North America. JAMA Netw Open. 2024 Feb;7(2):e240795. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables S1-S8","content":"\u003cp\u003eTables S1-S8 are not available with this version\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Homelessness, Cirrhosis, Length of stay, mortality","lastPublishedDoi":"10.21203/rs.3.rs-5758007/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5758007/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003ePatients experiencing homelessness are disproportionately affected by cirrhosis due to socioeconomic barriers, housing insecurity, and healthcare access challenges. However, the impact of homelessness on clinical outcomes and healthcare utilization among hospitalized cirrhosis patients has not been well-characterized.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a cross-sectional study using the National Inpatient Sample (2016\u0026ndash;2021) to analyze hospitalizations of adults with cirrhosis, comparing outcomes between those with and without homelessness. Demographic, clinical, and hospital-level characteristics were assessed, along with outcomes such as mortality and AMA discharges. Healthcare utilization metrics, including length of stay (LOS) and cost, were also evaluated, with multivariable regression used to adjust for confounders\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 4,579,858 hospitalizations for cirrhosis, 109,640 (2.4%) involved homeless patients, who were younger (mean 53.5 vs. 60.6 years, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and predominantly male (80.4% vs. 58.9%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Homeless patients had higher rates of alcohol use (73.5% vs. 30.9%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), opioid use disorder (11.8% vs. 3.6%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and psychiatric comorbidities (62% vs. 37.4%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Hispanic and Native American patients were overrepresented, while white patients were underrepresented. Mortality was lower in homeless patients ([aOR] 0.46, 95% CI: 0.42\u0026ndash;0.50, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, AMA discharges were significantly higher (9.6% vs. 2.7%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Homeless patients had longer hospital stays (mean 7.3 vs. 6.2 days, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but lower per-day hospitalization costs (\u003cspan\u003e$\u003c/span\u003e2,278 vs. \u003cspan\u003e$\u003c/span\u003e2,859, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHomelessness is associated with distinct clinical and healthcare utilization patterns among hospitalized patients with cirrhosis. Despite lower mortality and procedural intervention rates, high AMA discharge rates and prolonged hospital stays underscore the challenges to safe discharge among patient with cirrhosis.\u003c/p\u003e","manuscriptTitle":"The Impact of Housing Insecurity on Hospitalized Patients with Diagnosis of Cirrhosis: A Comparative Analysis Using Data from the National Inpatient Sample (2016-2021)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-06 20:31:58","doi":"10.21203/rs.3.rs-5758007/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e3eb5bd7-85f7-4902-9d3e-5f4c660e7817","owner":[],"postedDate":"January 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-11T15:53:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-06 20:31:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5758007","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5758007","identity":"rs-5758007","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}