Preoperative Deficiency Anemia in Digital Replantation: A Marker of Disparities, Increased Length of Stay, and Hospital Cost

2020 ◽  
Author(s):  
Fouad Chouairi ◽  
Michael R. Mercier ◽  
Michael Alperovich ◽  
James Clune ◽  
Adnan Prsic
Keyword(s):  
Length Of Stay ◽  
Household Income ◽  
Hospital Cost ◽  
Deficiency Anemia ◽  
Median Household Income ◽  
Hospital Type ◽  
Total Cost ◽  
Poor Outcomes ◽  
Income Quartile ◽  
Digital Replantation

Abstract Introduction The effects of preoperative anemia have been shown to be an independent risk factor associated with poor outcomes in both cardiac and noncardiac surgery. Socioeconomic status and race have also been linked to poor outcomes in a variety of conditions. This study was designed to study iron deficiency anemia as a marker of health disparities, length of stay and hospital cost in digital replantation. Materials and Methods Digit replantations performed between 2008 and 2014 were reviewed from the National Inpatient Sample (NIS) database using the ICD-9-CM procedure codes 84.21 and 84.22. Patients with more than one code or with an upper arm (83.24) or hand replantation (84.23) code were excluded. Extracted variables included age, race, comorbidities, hospital type, hospital region, insurance payer type, and median household income quartile. Digit replantations were separated into patients with and without deficiency anemia. Demographics, comorbidities, and access to care were compared between cohorts by chi-squared and t-tests. Multivariate regressions were utilized to assess the effects of anemia on total cost and length of stay. The regression controlled for demographics, region, income, insurance, hospital type, and comorbidities. Beta coefficient was calculated for length of stay and hospital cost. The regression controlled for significant age, race, region, and comorbidities in addition to the above variables. Results In the studied patient population of those without anemia, 59.5% were Caucasian, and in patients with anemia, 46.7% were Caucasian (p < 0.001). Whereas in the in the studied patient population of those without anemia, 6.7% were Black, and in patients with anemia, 15.7% were Black (p < 0.001). Median household income, payer information, length of stay and total cost of hospitalization had statistically significant differences. Using regression and β-coefficient, the effect of anemia on length of stay and cost was also significant (p < 0.001). Regression controlled for age, race, region and comorbidities, with the β-coefficient for effect on cost 37327.18 and on length of stay 3.96. Conclusion These data show that deficiency anemias are associated with a significant increase in length and total cost of stay in patients undergoing digital replantation. Additionally, a larger percentage of patients undergoing digital replantations and who have deficiency anemia belong to the lowest income quartile. Our findings present an important finding for public health prevention and resource allocation. Future studies could focus on clinical intervention with iron supplementation at the time of digital replantation.

Abstract P220: Disparity In Hospital Admissions And Length Of Stay Based On Income Status For Emergency Department Hypertensive Crisis Visits: A Cross-sectional Study Using The Nationwide Emergency Department Sample

Hypertension ◽  
2021 ◽  
Vol 78 (Suppl_1) ◽  
Author(s):  
Shreya Srivastava ◽  
Bhargav Vemulapalli ◽  
Alexis K Okoh ◽  
John Kassotis
Keyword(s):  
Emergency Department ◽  
Length Of Stay ◽  
Regression Model ◽  
Household Income ◽  
Hypertensive Crisis ◽  
Cross Sectional ◽  
Delivery Of Care ◽  
Income Status ◽  
Ed Visits ◽  
Income Quartile

Introduction: Racial, gender and lower socioeconomic status have been shown to negatively impact the delivery of care. How this impacts the management of hypertensive crisis (HC) remains unclear. Objective: Identify disparities on admission frequency and length of stay (LOS) among those presenting with HC, as a function of household income. Methods: This is a cross-sectional analysis of 2016 ED visits and supplemental Inpatient data from the Nationwide Emergency Department Sample. Median household income quartiles were established. A multivariable logistic regression model was used to estimate odds of admission in each income quartile. A multivariable linear regression model was used to predict LOS. Results: After applying sample weighting, the total number of ED visits was 33,728 with 25442, 6906, and 1380 visits for hypertensive urgency (HU), emergency (HE) and unspecified crisis, respectively. There were 13191, 8889, 6401, 5247 visits in the (1 st ) lowest, 2 nd , 3 rd and 4 th (highest) income quartiles, respectively. The median age was 61 and 58 years for HU and HE, respectively. The most common comorbidity was chronic kidney disease. Individuals with the highest income, had a lower odds of admission compared to the lowest quartile [Adjusted Odds Ratio: 0.41, 95% CI: 0.22,0.74] ( Figure 1a ). There was a significant linear association between income quartile and LOS across all HC and HE [beta coefficient: 0.411, 0.407 p value = 0.015, 0.019] ( Figure 1b ). Conclusions: In this study, patients with lower income were more likely to be admitted, while those with higher income exhibited a longer LOS. Clinicians must be made aware these disparities to ensure the equitable delivery of care.

scholarly journals “Association between Median Household Income, State Medicaid Expansion Status, and COVID-19 Outcomes Across US Counties”

2021 ◽  
Author(s):  
Tsikata Apenyo ◽  
Antonio Vera-Urbina ◽  
Khansa Ahmad ◽  
Tracey H. Taveira ◽  
Wen-Chih Wu
Keyword(s):  
Mortality Risk ◽  
Low Income ◽  
Household Income ◽  
Medicaid Expansion ◽  
Median Household Income ◽  
Incidence And Mortality ◽  
Significant Difference ◽  
Us Counties ◽  
The Relationship ◽  
Income Quartile

AbstractObjectiveThe relationship between socioeconomic status and its interaction with State’s Medicaid-expansion policies on COVID-19 outcomes across United States (US) counties are uncertain. To determine the association between median-household-income and its interaction with State Medicaid-expansion status on COVID-19 incidence and mortality in US countiesMethodsLongitudinal, retrospective analysis of 3142 US counties (including District of Columbia) to study the relationship between County-level median-household-income (defined by US Census Bureau’s Small-Area-Income-and-Poverty-Estimates) and COVID-19 incidence and mortality per 100000 of the population in US counties from January 20, 2020 through December 6, 2020. County median-household-income was log-transformed and stratified by quartiles. Medicaid-expansion status was defined by US State’s Medicaid-expansion adoption as of first reported US COVID-19 infection, January 20, 2020. Multilevel mixed-effects generalized-linear-model with negative binomial distribution and log link function compared quartiles of median-household-income and COVID-19 incidence and mortality, reported as incidence-risk-ratio (IRR) and mortality-risk-ratio (MRR), respectively. Models adjusted for county socio-demographic and comorbidity conditions, population density, and hospitals, with a random intercept for states. Multiplicative interaction tested for Medicaid-expansion*income quartiles on COVID-19 incidence and mortality.ResultsThere was no significant difference in COVID-19 incidence across counties by income quartiles or by Medicaid expansion status. Conversely, significant differences exist between COVID-19 mortality by income quartiles and by Medicaid expansion status. The association between income quartiles and COVID-19 mortality was significant only in counties from non-Medicaid-expansion states but not significant in counties from Medicaid-expansion states (P<0.01 for interaction). For non-Medicaid-expansion states, counties in the lowest income quartile had a 41% increase in COVID-19 mortality compared to counties in the highest income quartile (MRR 1.41, 95% CI: 1.25-1.59).Conclusions and RelevanceMedian-household-income was not related to COVID-19 incidence but negatively related to COVID-19 mortality in US counties of states without Medicaid-expansion. It was unrelated to COVID-19 mortality in counties of states that adopted Medicaid-expansion. These findings suggest that expanded healthcare coverage should be investigated further to attenuate the excessive COVID-19 mortality risk associated with low-income communities.Key FindingsQuestionIs there a relationship between COVID-19 outcomes (incidence and mortality) and household income and status of Medicaid expansion of US counties?FindingsIn this longitudinal, retrospective analysis of 3142 US counties, we found no significant difference in COVID-19 incidence across US counties by quartiles of household income. However, counties with lower median household income had a higher risk of COVID-19 mortality, but only in non-Medicaid expansion states. This relationship was not significant in Medicaid expansion states.MeaningExpanded healthcare coverage through Medicaid expansion should be investigated as an avenue to attenuate the excessive COVID-19 mortality risk associated with low-income communities.

Abstract 16279: Impact of Race and Socioeconomic Status on Rates of Congestive Heart Failure Admissions, Readmissions, and Length of Stay

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Muhammad A Shakir ◽  
Meghan E Buckley ◽  
William D Surkis ◽  
John M Clark
Keyword(s):  
Heart Failure ◽  
Socioeconomic Status ◽  
Length Of Stay ◽  
Low Income ◽  
Household Income ◽  
High Income ◽  
Median Household Income ◽  
Admission Rates ◽  
Black Patients ◽  
White Patients

Introduction: Health disparities due to race and socioeconomic status persist among congestive heart failure (CHF) patients. Our hospital in the Philadelphia area is uniquely situated to study disparities as it sits on the border of a diverse inner city and suburban population. The area west of our hospital is known to have a drastically higher median income than the area to the east. We aimed to evaluate differences in rates of CHF admissions, readmissions, and length of stay (LOS) for patients based on race and socioeconomic status. Methods: From 3/1/2018 to 3/31/2020, 6,785 total patients were admitted to our hospital due to acute decompensated CHF. To compare rates of admission, readmission and a LOS > 5 days based on race and socioeconomic status, we used the SlicerDicer function of the EPIC electronic record platform. For race, we compared data for white and black patients. For socioeconomic status, we included a 10-mile radius around our hospital and used public records to collect median household income for 11 zip codes to the east and 11 to the west. The average yearly median household income for the east and west zip codes were USD $27,171 and $134,390, respectively. Outcomes are expressed as percentages and compared using a Chi-square test of independence and 95% confidence interval (CI) for differences. Significance was assessed at the 0.05 level. Results: Admission rates were significantly higher among Black patients at 67% compared to White patients at 58% (95% CI 7-11%, p<0.05). There was no significant difference between rates of readmission (60% for Black vs. 58% for White patients, 95% CI 0-4%, p=0.11) or LOS > 5 days (56% for Black vs. 55% for White patients, 95% CI 0-3%, p=0.42). Admission rates were significantly higher among patients from low income areas at 70% compared to high income areas at 56% (95% CI 11-17%, p<0.05). Readmission rates were not significantly different, 57% for low income and 56% for high income areas (95% CI 0-4%, p=0.82). Patients from low income areas were significantly more likely to have a LOS > 5 days at 57% compared to patients from high income areas at 53% (95% CI 0.8-8%, p<0.05). Conclusions: Race and socioeconomic status continue to impact CHF patients’ health outcomes including rates of admissions, readmissions, and length of stay.

Social determinants of health and their impact on postcolectomy surgery readmissions: a multistate analysis, 2009–2014

2019 ◽  
Vol 8 (16) ◽  
pp. 1365-1379 ◽  
Author(s):  
Hyun S Park ◽  
Robert S White ◽  
Xiaoyue Ma ◽  
Briana Lui ◽  
Kane O Pryor
Keyword(s):  
New York ◽  
Household Income ◽  
Odds Ratio ◽  
Insurance Status ◽  
Median Income ◽  
Median Household Income ◽  
Discharge Data ◽  
Black Patients ◽  
Race Ethnicity ◽  
Income Quartile

Aim: To examine the effect of race/ethnicity, insurance status and median household income on postoperative readmissions following colectomy. Patients & methods: Multivariate analysis of hospital discharge data from California, Florida, Maryland and New York from 2009 to 2014. Primary outcomes included adjusted odds of 30- and 90-day readmissions following colectomy by race, insurance status and median income quartile. Results: Total 330,840 discharges included. All 30-day readmissions were higher for black patients (adjusted odds ratio [aOR]: 1.07). Both 30- and 90-day readmissions were higher for Medicaid (aOR: 1.30 and 1.26) and Medicare (aOR: 1.30 and 1.29). The 30- and 90-day readmissions were lower in the highest income quartiles. Conclusion: Race, insurance status and median household income are all independent predictors of disparity in readmissions following colectomy.

scholarly journals The Relationship Between Estimated Median Household Income and Critical Care Length of Stay in Children With Diabetic Ketoacidosis

2020 ◽  
Vol 7 ◽  
pp. 2333794X2095677
Author(s):  
Meredith C. G. Broberg ◽  
Jerri A. Rose ◽  
Katherine N. Slain
Keyword(s):  
Length Of Stay ◽  
Diabetic Ketoacidosis ◽  
Low Income ◽  
Household Income ◽  
Severity Of Illness ◽  
Pediatric Intensive Care ◽  
Median Household Income ◽  
Poverty Threshold ◽  
The Relationship ◽  
Zip Code

Diabetic ketoacidosis (DKA) is an important diagnosis in the pediatric intensive care unit (PICU) and is associated with significant morbidity. We hypothesized children with DKA living in poorer communities would have unfavorable outcomes while critically ill. This single-center retrospective study included children with DKA admitted to a PICU over a 27-month period. Patients were classified as low-income if they lived in a ZIP code where the median household income was estimated to be less than 200% of the federal poverty threshold, or $48 016 for a family of 4. In this study, living in a low-income ZIP code was not associated with increased severity of illness, longer PICU length of stay (LOS), or readmission.

scholarly journals Socioeconomic Inequities in Adherence to Positive Airway Pressure Therapy in Population-Level Analysis

2020 ◽  
Vol 9 (2) ◽  
pp. 442 ◽  
Author(s):  
Abhishek Pandey ◽  
Suresh Mereddy ◽  
Daniel Combs ◽  
Safal Shetty ◽  
Salma I. Patel ◽  
...  
Keyword(s):  
Sleep Apnea ◽  
Household Income ◽  
Airway Pressure ◽  
Positive Airway Pressure ◽  
Population Level ◽  
Median Household Income ◽  
Pressure Therapy ◽  
Level Data ◽  
Nationally Representative ◽  
Income Quartile

(a) Background: In patients with sleep apnea, poor adherence to positive airway pressure (PAP) therapy has been associated with mortality. Regional studies have suggested that lower socioeconomic status is associated with worse PAP adherence but population-level data is lacking. (b) Methods: De-identified data from a nationally representative database of PAP devices was geo-linked to sociodemographic information. (c) Results: In 170,641 patients, those in the lowest quartile of median household income had lower PAP adherence (4.1 + 2.6 hrs/night; 39.6% adherent by Medicare criteria) than those in neighborhoods with highest quartile median household income (4.5 + 2.5 hrs/night; 47% adherent by Medicare criteria; p < 0.0001). In multivariate regression, individuals in neighborhoods with the highest income quartile were more adherent to PAP therapy than those in the lowest income quartile after adjusting for various confounders (adjusted Odds Ratio (adjOR) 1.18; 95% confidence interval (CI) 1.14, 1.21; p < 0.0001). Over the past decade, PAP adherence improved over time (adjOR 1.96; 95%CI 1.94, 2.01), but health inequities in PAP adherence remained even after the Affordable Care Act was passed. (d) Conclusion: In a nationally representative population, disparities in PAP adherence persist despite Medicaid expansion. Interventions aimed at promoting health equity in sleep apnea need to be undertaken.

scholarly journals National U.S. Patient and Transplant Data for Krabbe Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Gabrielle Ghabash ◽  
Jacob Wilkes ◽  
Joshua L. Bonkowsky
Keyword(s):  
Household Income ◽  
Health Information System ◽  
Krabbe Disease ◽  
Median Household Income ◽  
Hematopoietic Stem ◽  
Improved Outcomes ◽  
Hispanic Patients ◽  
Patient Groups ◽  
Race Ethnicity ◽  
Income Quartile

Krabbe disease (KD) is a leukodystrophy caused by mutations in the galactosylceramidase gene. Presymptomatic hematopoietic stem cell transplantation (HSCT) is associated with improved outcomes, but most data are from single-center studies. Our objective was to characterize national patterns of HSCT for KD including whether there were disparities in HSCT utilization and outcomes. We conducted a retrospective study of KD patients ≤ age 18 years from November 1, 2015, through December 31, 2019, using the U.S. Children's Hospital Association's Pediatric Health Information System database. We evaluated outcomes for HSCT, intensive care unit days, and mortality, comparing age, sex, race/ethnicity, rural/urban location, and median household income. We identified 91 KD patients. HSCT, performed in 32% of patients, was associated with reduced mortality, 31 vs. 68% without HSCT (p &lt; 0.003). Trends included the fact that more males than females had HSCT (39 vs. 23%); more Asian and White patients had HSCT compared to Black or Hispanic patients (75, 33, 25, and 17%, respectively); and patients from households with the lowest-income quartile (&lt; $25,000) had more HSCT compared to higher-income quartiles (44 vs. 33, 30, and 0%). Overall, receiving HSCT was associated with reduced mortality. We noted trends in patient groups who received HSCT. Our findings suggest that disparities in receiving HSCT could affect outcomes for KD patients.

565 POST-OPERATIVE WEIGHT LOSS AND OUTCOMES FOLLOWING ESOPHAGECTOMY

2020 ◽  
Vol 33 (Supplement_1) ◽  
Author(s):  
R Khaw ◽  
S Munro ◽  
J Sturrock ◽  
H Jaretzke ◽  
S Kamarajah ◽  
...  
Keyword(s):  
Weight Loss ◽  
Length Of Stay ◽  
Hospital Stay ◽  
Enhanced Recovery ◽  
Length Of Hospital Stay ◽  
Failure To Thrive ◽  
Post Discharge ◽  
Postoperative Weight Loss ◽  
Poor Outcomes ◽  
The Impact

Abstract   Oesophageal cancer is the 11th most common cancer worldwide, with oesophagectomy remaining the mainstay curative treatment, despite significant associated morbidity and mortality. Postoperative weight loss remains a significant problem and is directly correlated to poor prognosis. Measures such as the Enhanced Recovery After Surgery (ERAS) programme and intraoperative jejunostomy feed have looked to tackle this. This study investigates the impact of these on mortality, length of hospital stay and postoperative weight loss. Methods Patients undergoing oesophagectomy between January 1st 2012—December 2014 and 28th October 2015–December 31st 2019 in a national tertiary oesophagogastric unit were included retrospectively. Variables measured included comorbidities, operation, histopathology, weights (pre- and post-operatively), length of hospital stay, postoperative complications and mortality. Pre-operative body weight was measured at elective admission, and further weights were identified from a prospectively maintained database, during further clinic appointments. Other data was collected through patient notes. Results 594 patients were included. Mean age at diagnosis was 65.9 years (13–65). Majority of cases were adenocarcinoma (63.3%), with varying stages of disease (TX-4, NX-3). Benign pathology accounted for 8.75% of cases. Mean weight loss post-oesophagectomy exceeded 10% at 6 months (SD 14.49). Majority (60.1%) of patients were discharged with feeding jejunostomy, and 5.22% of these required this feed to be restarted post-discharge. Length of stay was mean 16.5 days (SD 22.3). Complications occurred in 68.9% of patients, of which 13.8% were infection driven. Mortality occurred in 26.6% of patients, with 1.83% during hospital admission. 30-day mortality rate was 1.39%. Conclusion Failure to thrive and prolonged weight-loss following oesophagectomy can contribute to poor recovery, with associated complications and poor outcomes, including increased length of stay and mortality. Further analysis of data to investigate association between weight loss and poor outcomes for oesophagectomy patients will allow for personalised treatment of high-risk patients, in conjunction with members of the multidisciplinary team, including dieticians.

Hospital Volume is Not a Predictor of Outcomes after Gastrectomy for Neoplasm

2009 ◽  
Vol 75 (10) ◽  
pp. 932-936 ◽  
Author(s):  
Kevin M. Reavis ◽  
Marcelo W. Hinojosa ◽  
Brian R. Smith ◽  
James B. Wooldridge ◽  
Sindhu Krishnan ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Hospital Mortality ◽  
Gastric Surgery ◽  
National Database ◽  
Medical Centers ◽  
Outcome Relationship ◽  
Academic Medical ◽  
Low Volume ◽  
Poor Outcomes ◽  
The University

Studies have shown conflicting data with regard to the volume and outcome relationship for gastrectomy. Using the University HealthSystem Consortium national database, we examined the influence of the hospital's volume of gastrectomy on outcomes at academic centers between 2004 and 2008. Outcome measures, including length of stay, 30-day readmission, morbidity, and in-hospital mortality, were compared among high- (13 or greater), medium- (6 to 12), and low-volume (five or less) hospitals. There were 10 high- (n = 593 cases), 36 medium- (n = 1076 cases), and 75 low-volume (n = 500 cases) hospitals. There were no significant differences between high- and low-volume hospitals with regard to length of stay, overall complications, 30-day readmission rate, and in-hospital mortality (2.4 vs 4.4%, respectively, P = 0.06). Despite the small number of gastrectomies performed at the low-volume hospitals, these same hospitals performed a large number of other types of gastric surgery such as gastric bypass for the treatment of morbid obesity (102 cases/year). Within the context of academic medical centers, lower annual volume of gastrectomy for neoplasm is not a predictor of poor outcomes which may be explained by the gastric operative experience derived from other types of gastric surgery.

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