Delirium occurrence and association with outcomes in hospitalized COVID-19 patients

2021 ◽  
pp. 1-5
Author(s):  
Sandeep Pagali ◽  
Sunyang Fu ◽  
Heidi Lindroth ◽  
Sunghwan Sohn ◽  
M. Caroline Burton ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Mayo Clinic ◽  
Skilled Nursing Facility ◽  
Age Groups ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Chi Square ◽  
Skilled Nursing ◽  
Mortality And Morbidity ◽  
Chi Square Test

ABSTRACT Delirium is reported to be one of the manifestations of coronavirus infectious disease 2019 (COVID-19) infection. COVID-19 hospitalized patients are at a higher risk of delirium. Pathophysiology behind the association of delirium and COVID-19 is uncertain. We analyzed the association of delirium occurrence with outcomes in hospitalized COVID-19 patients, across all age groups, at Mayo Clinic hospitals. A retrospective study of all hospitalized COVID-19 patients at Mayo Clinic between March 1, 2020 and December 31, 2020 was performed. Occurrence of delirium and outcomes of mortality, length of stay, readmission, and 30-day mortality after hospital discharge were measured. Chi-square test, student t-test, survival analysis, and logistic regression analysis were performed to measure and compare outcomes of delirium group adjusted for age, sex, Charlson comorbidity score, and COVID-19 severity with no-delirium group. A total of 4351 COVID-19 patients were included in the study. Delirium occurrence in the overall study population was noted to be 22.4%. The highest occurrence of delirium was also noted in patients with critical COVID-19 illness severity. A statistically significant OR 4.35 (3.27–5.83) for in-hospital mortality and an OR 4.54 (3.25–6.38) for 30-day mortality after discharge in the delirium group were noted. Increased hospital length of stay, 30-day readmission, and need for skilled nursing facility on discharge were noted in the delirium group. Delirium in hospitalized COVID-19 patients is a marker for increased mortality and morbidity. In this group, outcomes appear to be much worse when patients are older and have a critical severity of COVID-19 illness.

Surgical Scheduling Impacts Hospital Length of Stay and Associated Healthcare Costs for Patients Undergoing Total Hip and Knee Arthroplasty

2021 ◽  
pp. 155633162110400
Author(s):  
Sofia Ahsanuddin ◽  
Daniel J. Snyder ◽  
Hsin-Hui Huang ◽  
Aakash Keswani ◽  
Jashvant Poeran ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Skilled Nursing Facility ◽  
Hospital Length ◽  
Postoperative Outcomes ◽  
Hospital Length Of Stay ◽  
Skilled Nursing ◽  
Total Hip ◽  
Surgical Scheduling ◽  
Modifiable Factor ◽  
Day Of The Week

Background: Surgical scheduling, specifically the day of the week on which surgery is performed, has been associated with various postoperative outcomes in patients undergoing lower extremity joint arthroplasty. Purpose: We sought to investigate surgical scheduling as a potential modifiable factor for patient quality metrics and related costs. Methods: In a retrospective prognostic study, all total knee and total hip arthroplasty (TKA/THA) cases that took place in 2017 to 2018 at a multihospital academic health system were queried. Patients were separated by the day of the week the surgery was performed, with Monday/Tuesday compared to Thursday/Friday. Outcomes included length of stay (LOS) (extended LOS defined as 3 days or longer), cost, and complications. Multivariable regression models measured associations between scheduling of surgery and outcomes; odds ratios (OR) and 95% confidence intervals (CIs) are reported. Results: Overall, 1,571 TKA and 992 THA patients were included (65% and 35%, respectively, performed on Monday/Tuesday and 70% and 30%, respectively, performed on Thursday/Friday). Patients undergoing TKA on Monday/Tuesday versus Thursday/Friday had higher American Society of Anesthesiologists scores (42% vs 33% with score of 3 or higher) but less often an extended LOS (31% vs 54%; adjusted OR: 2.76, 95% CI: 2.22-3.46), lower skilled nursing facility costs (unadjusted mean, $12,515 vs $14,154) and lower home health aide costs (unadjusted mean, $3,793 vs $4,192). Similar patterns were observed in THA patients. Conclusion: These results from institutional data suggest that surgical scheduling is a modifiable factor possibly associated with postoperative outcomes. Furthermore, more rigorous study is warranted.

scholarly journals Tranexamic acid is associated with decreased transfusion, hospital length of stay, and hospital cost in simultaneous bilateral total knee arthroplasty

2020 ◽  
Author(s):  
Ryan D'Souza ◽  
Christopher Duncan ◽  
Daniel Whiting ◽  
Michael Brown ◽  
Matthew Warner ◽  
...  
Keyword(s):  
Total Knee Arthroplasty ◽  
Length Of Stay ◽  
Hospital Cost ◽  
Skilled Nursing Facility ◽  
Hospital Length ◽  
Cost Of Care ◽  
Hospital Length Of Stay ◽  
Nursing Facility ◽  
Skilled Nursing ◽  
Total Knee

Tranexamic acid (TXA) reduces blood loss and transfusion rates in unilateral total knee arthroplasty (TKA), but there is limited data regarding its efficacy in bilateral TKA. This study reports the impact TXA has on clinical outcomes and hospital cost of care in simultaneous, primary bilateral TKA. The 449 patients were retrospectively reviewed. Primary outcomes included the rates of allogeneic and autologous blood transfusion. Secondary outcomes included hospital length of stay (HLOS), post-hospital discharge disposition, 30-day thromboembolic events (TEE), and mean hospital cost of care. Total direct medical costs were obtained from an institutional research database and adjusted to nationally representative unit costs in 2013 inflation-adjusted dollars. Our study revealed that in patients undergoing simultaneous bilateral TKA, TXA use was associated with reduced allogeneic (OR 0.181, 95% CI 0.090-0.366, p<0.001) and combined allogeneic and autologous transfusion rates (OR 0.451, 95% CI 0.235-0.865, p=0.017). TXA was associated with a HLOS reduction of 0.9 days (β-coefficient -0.582, 95% CI -1.008– -0.156, p=0.008), an increased likelihood of hospital discharge over skilled nursing facility (SNF) (OR 2.25, 95% CI 1.117-4.531, p=0.023) and reduced total hospital cost of care by 6.45% (p<0.001), room and board costs by 11.76% (p<0.001), and transfusion costs by 81.65% (p<0.001). In conclusion, TXA use in bilateral TKA is associated with lower blood transfusion rates, reduced hospital length of stay, reduced cost of hospital care and skilled nursing facility avoidance.

Disagreement between emergency department admission diagnosis and hospital discharge diagnosis: mortality and morbidity

Diagnosis ◽  
2016 ◽  
Vol 3 (1) ◽  
pp. 23-30 ◽  
Author(s):  
James Eames ◽  
Arie Eisenman ◽  
Richard J. Schuster
Keyword(s):  
Emergency Department ◽  
Length Of Stay ◽  
Medical Center ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Admission Diagnosis ◽  
Mortality And Morbidity ◽  
Emergency Department Admission ◽  
Icu Length Of Stay ◽  
Discordant Group

AbstractPrevious studies have shown that changes in diagnoses from admission to discharge are associated with poorer outcomes. The aim of this study was to investigate how diagnostic discordance affects patient outcomes.: The first three digits of ICD-9-CM codes at admission and discharge were compared for concordance. The study involved 6281 patients admitted to the Western Galilee Medical Center, Naharyia, Israel from the emergency department (ED) between 01 November 2012 and 21 January 2013. Concordant and discordant diagnoses were compared in terms of, length of stay, number of transfers, intensive care unit (ICU) admission, readmission, and mortality.: Discordant diagnoses was associated with increases in patient mortality rate (5.1% vs. 1.5%; RR 3.35, 95% CI 2.43, 4.62; p<0.001), the number of ICU admissions (6.7% vs. 2.7%; RR 2.58, 95% CI 2.07, 3.32; p<0.001), hospital length of stay (3.8 vs. 2.5 days; difference 1.3 days, 95% CI 1.2, 1.4; p<0.001), ICU length of stay (5.2 vs. 3.8 days; difference 1.4 days, 95% CI 1.0, 1.9; p<0.001), and 30 days readmission (14.11% vs. 12.38%; RR 1.14, 95% CI 1.00, 1.30; p=0.0418). ED length of stay was also greater for the discordant group (3.0 vs. 2.9 h; difference 8.8 min; 95% CI 0.1, 0.2; p<0.001): These findings indicate discordant admission and discharge diagnoses are associated with increases in morbidity and mortality. Further research should identify modifiable causes of discordance.

Influence of Insurance Status on Hospital Length of Stay and Discharge Location in Burn Patients

2018 ◽  
Vol 84 (6) ◽  
pp. 924-929 ◽  
Author(s):  
Rachel M. Nygaard ◽  
Jon R. Gayken ◽  
Frederick W. Endorf
Keyword(s):  
Skilled Nursing Facility ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Insurance Status ◽  
Burn Patients ◽  
Nursing Facility ◽  
Skilled Nursing ◽  
Rehabilitation Facility ◽  
Lengths Of Stay ◽  
Discharge Location

Insurance status affects many aspects of healthcare in America, from access to delivery to outcomes. Our goal in this study was to determine whether different subtypes of insurance status affected hospital lengths of stay (LOS) and/or the location to which patients were discharged. The National Burn Repository was used to examine a total of 119,509 burn patients. Patients with noncommercial insurance (NONCOM) have increased LOS and are more likely to be discharged to a nonhome location, compared with no insurance or other insurance subtypes. Patients with no insurance have similar injury characteristics and comorbidities as patients with NONCOM, but have a shorter LOS and are more likely to be discharged home rather than to a skilled nursing facility or rehabilitation facility.

Survival trends in palliative care patients with cancer: A Mayo Clinic 5-year review

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 9592-9592
Author(s):  
A. H. Kamal ◽  
K. M. Swetz ◽  
H. Liu ◽  
S. R. Ruegg ◽  
E. C. Carey ◽  
...  
Keyword(s):  
Palliative Care ◽  
Length Of Stay ◽  
Median Time ◽  
Mayo Clinic ◽  
Hospital Admissions ◽  
Cox Model ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Care Plan ◽  
Palliative Care Consultation

9592 Background: Palliative care (PC) is an essential part of the continuum of care for cancer (CA) patients (pts). Little is known about the aggregate characteristics and survival of pts receiving inpatient palliative care consultation (PCC). Methods: We reviewed data prospectively collected on patients seen by the Palliative Care Inpatient Consult Service at Mayo Clinic - Rochester from 2003–2008. Demographics, consult characteristics, and survival were analyzed. Kaplan-Meier survival curves and a Cox model of survival were produced. Results: 1794 total patients were seen over the five year period. Cancer is the most common primary diagnosis (47%). Growth in annual PCC has risen dramatically (113 in 2003 vs. 414 in 2007) despite stable total hospital admissions. Patient are predominantly men (52% vs. 48%, p=0.02); median age is 76. General medicine, medical cardiology, and medical intensive care unit services refer most often. Most frequent issues addressed are goals of care, dismissal planning, and pain control (29%, 19%, 17%). PCC in actively dying pts have increased with 27% of all non-operating room, non-trauma in-hospital deaths being seen. Although CA pts have the highest median survival after PCC vs. other diagnoses (17 days, p = 0.018), we observed a five-year trend of decreasing survival from admission to death and PCC to death. Median time from admission to death in CA pts is 36 days in 2003 and 19 days in 2008 (p<0.01). Median time from PCC to death is 33 versus 11.5 days (p<0.01). Despite this, median hospital length of stay and time from PCC to discharge have remained fixed at 8 and 2.5 days, respectively. A Cox model of survival to discharge and <6 months survival (hospice eligibility) shows hospital length of stay, time from consult to discharge, and dismissal location from hospital are all prognostic factors. Conclusions: Survival window for PC intervention for CA pts is lessening. With the trend of shorter survival after PCC, PC professionals have little over two days to implement a comprehensive, ongoing care plan. This highlights the importance of earlier outpatient palliative care involvement with advanced cancer patients and families. No significant financial relationships to disclose.

scholarly journals Time between Symptom Onset, Hospitalisation and Recovery or Death: a Statistical Analysis of Different Time-Delay Distributions in Belgian COVID-19 Patients

2020 ◽  
Author(s):  
Christel Faes ◽  
Steven Abrams ◽  
Dominique Van Beckhoven ◽  
Geert Meyfroidt ◽  
Erika Vlieghe ◽  
...  
Keyword(s):  
Nursing Home ◽  
Length Of Stay ◽  
Symptom Onset ◽  
Age Groups ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Age Group ◽  
Median Length ◽  
Nursing Home Patients ◽  
Interval Censored

Background There are different patterns in the COVID-19 outbreak in the general population and amongst nursing home patients. Different age-groups are also impacted differently. However, it remains unclear whether the time from symptom onset to diagnosis and hospitalization or the length of stay in the hospital is different for different age groups, gender, residence place or whether it is time dependent. Methods Sciensano, the Belgian Scientific Institute of Public Health, collected information on hospitalized patients with COVID-19 hospital admissions from 114 participating hospitals in Belgium. Between March 14, 2020 and June 12, 2020, a total of 14,618 COVID-19 patients were registered. The time of symptom onset, time of COVID-19 diagnosis, time of hospitalization, time of recovery or death, and length of stay in intensive care are recorded. The distributions of these different event times for different age groups are estimated accounting for interval censoring and right truncation in the observed data. Results The truncated and interval-censored Weibull regression model is the best model for the time between symptom onset and diagnosis/hospitalization best, whereas the length of stay in hospital is best described by a truncated and interval-censored lognormal regression model. Conclusions The time between symptom onset and hospitalization and between symptom onset and diagnosis are very similar, with median length between symptom onset and hospitalization ranging between 3 and 10.4 days, depending on the age of the patient and whether or not the patient lives in a nursing home. Patients coming from a nursing home facility have a slightly prolonged time between symptom onset and hospitalization (i.e., 2 days). The longest delay time is observed in the age group 20-60 years old. The time from symptom onset to diagnosis follows the same trend, but on average is one day longer as compared to the time to hospitalization. The median length of stay in hospital varies between 3 and 10.4 days, with the length of stay increasing with age. However, a difference is observed between patients that recover and patients that die. While the hospital length of stay for patients that recover increases with age, we observe the longest time between hospitalization and death in the age group 20-60. And, while the hospital length of stay for patients that recover is shorter for patients living in a nursing home, the time from hospitalization to death is longer for these patients. But, over the course of the first wave, the length of stay has decreased, with a decrease in median length of stay of around 2 days.

Could payer mix affect length of stay or readmissions among an outpatient palliative care cohort?

2017 ◽  
Vol 35 (31_suppl) ◽  
pp. 165-165
Author(s):  
Ali John Zarrabi ◽  
Karen Armstrong ◽  
Kimberly A. Curseen ◽  
Tammie E. Quest
Keyword(s):  
Palliative Care ◽  
Length Of Stay ◽  
Hospital Readmissions ◽  
Retrospective Chart Review ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Nursing Facilities ◽  
Skilled Nursing ◽  
Commercial Insurance ◽  
Discharge Disposition

165 Background: Outpatient palliative care clinics (PCC) are a developing frontier of palliative medicine. Characterizing and promoting financially viable models for payment of services are imperative to the sustainability of PCC. There is a paucity of research addressing payer mix – meaning the breakdown of individuals and organizations that pay for a provider's services – in PCC or its impact on metrics important to quality in PC such as hospital length of stay (LOS) and hospital readmissions. We seek to describe the payer mix for our academic outpatient PC practice. Furthermore, we sought to identify if payer mix (commercial, government—Medicare, Medicaid – or self-pay) influenced hospital LOS, discharge to hospice, or readmissions. Methods: After obtaining IRB approval, we conducted a retrospective chart review of supportive oncology patients from 2014-2017 (n = 3137) using data restricted to ICD10 codes for solid tumors. We performed bivariate tests and multivariable logistic regressions to examine the main effects of length of stay (LOS), readmissions, insurance status, and discharge disposition using SAS version 9.4 (Cary, NC). Results: Payer mix included 711 (24%) commercial insurance enrollees, 2357 (75%) Medicare or Medicaid recipients, and 38 (1%) self-pay. Mean LOS was 12.7 days (SD 16.38). The majority (94%) of patients had more than 5 readmissions. Commercial insurance was associated with prolonged LOS ( > = 30 days), discharge disposition to hospice, and hospital readmissions ( > 5) compared to government insurance (p < 0.05). Of the 3137 patients, 325 (10%) expired, 1328 (42%) were discharged to hospice, while 1463 (47%) were discharged to rehab, skilled nursing facilities or home care. Conclusions: The majority of patients in our academic PCC had governmental insurance and were less likely than those with commercial insurance to have prolonged LOS, discharge to hospice, or hospital readmission. These findings provide evidence that further investigation is needed to examine the effect of payer mix on PCC and patient outcomes.

scholarly journals Safety and Costs of Stroke Unit Admission for Select Acute Intracerebral Hemorrhage Patients

2017 ◽  
Vol 8 (1) ◽  
pp. 12-17 ◽  
Author(s):  
Corey R. Fehnel ◽  
Kimberly M. Glerum ◽  
Linda C. Wendell ◽  
N. Stevenson Potter ◽  
Brian Silver ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Intracerebral Hemorrhage ◽  
Functional Outcome ◽  
Stroke Unit ◽  
Skilled Nursing Facility ◽  
Patient Characteristics ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Discharge Disposition ◽  
Group 5

Background and Purpose: There are limited data to guide intensive care unit (ICU) versus dedicated stroke unit (SU) admission for intracerebral hemorrhage (ICH) patients. We hypothesized select patients can be safely cared for in SU versus ICU at lower costs. Methods: We conducted a retrospective cohort study of consecutive patients with predefined minor ICH (≤20 cm3, supratentorial, no coagulopathy) receiving care in either an ICU or an SU. Multiple linear regression and inverse probability weighting were used to adjust for differences in patient characteristics and nonrandom ICU versus SU assignment. The primary outcome was poor functional status at discharge (modified Rankin score [mRS] ≥3). Secondary outcomes included complications, discharge disposition, hospital length of stay, and direct inpatient costs. Results: The study population included 104 patients (41 admitted to the ICU and 63 admitted to the SU). After controlling for differences in baseline characteristics, there were no differences in poor functional outcome at discharge (93% vs 85%, P = .26) or in mean mRS (2.9 vs 3.0, P = .73). Similarly, there were no differences in the rates of complications (6% vs 10%, P = .44), discharged dead or to a skilled nursing facility (8% vs 13%, P = .59), or direct patient costs (US$7100 vs US$6200, P = .33). Median length of stay was significantly longer in the ICU group (5 vs 4 days, P = .01). Conclusions: This study revealed a shorter length of stay but no large differences in functional outcome, safety, or cost among patients with minor ICH admitted to a dedicated SU compared to an ICU.

A Longer Route to the PICU Can Lead to a Longer Stay in the PICU: A Single-Center Retrospective Cohort Study

2020 ◽  
pp. 088506662096910
Author(s):  
Sandeep Tripathi ◽  
Logan J. Meixsell ◽  
Michele Astle ◽  
Minchul Kim ◽  
Yamini Kapileshwar ◽  
...  
Keyword(s):  
Emergency Department ◽  
Cohort Study ◽  
Length Of Stay ◽  
Retrospective Cohort ◽  
Age Groups ◽  
Hospital Length ◽  
Cost Of Care ◽  
Hospital Length Of Stay ◽  
Icu Length Of Stay ◽  
Pediatric Icu

Introduction: Admission to the pediatric ICU versus general pediatric floor for patients is a significant triage decision for emergency department physicians. Escalation of care within 24 hours of hospital admission is considered as a quality metric for pediatric E.R. There exists, however, a lack of data to show that such escalation leads to a poor outcome. Methods: A retrospective cohort study was conducted to compare outcomes of patients who required escalation of care within 24 hours of hospital admission to the pediatric ICU (cases) from 01/01 2015 to 02/28 2019 with those who were directly admitted from emergency department to the PICU (controls). A total of 327 cases were compared to 931 controls. Univariate and multivariable regression analysis was done to compare the length of stay and mortality data. Results: Patients who required escalation of care were significantly younger (median age 1.9 years compared to 4.6 years for controls) and had lower severity of illness score (PIM 3). Cases had a much higher proportion of respiratory diagnosis. ICU length of stay, hospital length of stay and the direct cost was significantly higher for cases compared to controls. This difference persisted for all age groups and respiratory diagnosis. The cost of care, however, was only different for 1-5 years and >5 years age groups. The difference in ICU length of stay (Δ11.1%) and hospital length of stay (Δ7.8%) persisted on multivariate regression analysis after controlling for age, sex, PIM3 score, and diagnostic variables. There was no difference in mortality on the univariate or multivariate analysis between the 2 groups. Conclusions: Patients who required escalation of care within 24 hours of hospital admissions have more prolonged ICU and hospital stay and potentially increased cost of care. This measure should be considered while making patient disposition decisions in the emergency department.

Sign in / Sign up

Export Citation Format

Share Document