Length of Stay

Brasel, Karen J.; Lim, Hyun J.; Nirula, Ram; Weigelt, John A.

doi:10.1001/archsurg.142.5.461

Cited by 152 publications

(57 citation statements)

References 27 publications

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“…Similar to this result, another study in one of Tehran’s hospitals showed that LOS in patients who had no insurance was less than those who paid by insurance (28). Other studies also have confirmed the relationship between method of payment and LOS (29, 30). The results of this study showed that the mean LOS was higher among patients with medical treatment compared with those with surgical intervention because general surgeries usually require less hospitalization compared with medical treatments in intensive care departments such as ICU and CCU.…”

Section: Discussionmentioning

confidence: 69%

Factors affecting length of stay in teaching hospitals of a middle-income country

Khosravizadeh¹,

Vatankhah²,

Bastani³

et al. 2016

Electron physician

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IntroductionThe length of stay (LOS) in hospitals is a widely used and important criteria for evaluating hospital performance. The aim of this study was to determine factors affecting LOS in teaching hospitals of Qazvin Providence.MethodsIn this cross-sectional study, patients’ health records were randomly selected from archives in teaching hospitals of Qazvin in 2013. Data were collected through a data entry form and were analyzed using Kolmogorov–Smirnov, Kruskal–Wallis, and Mann–Whitney U tests at the significant level of 0.05.ResultsThe mean of hospital LOS was 5.45 ± 6.14 days. Age, employment, marital status, history of previous admission, patient condition at discharge, method of payment, and type of treatment had an impact on LOS (p<0.05). Other factors, including gender, place of residence, and type of admission, did not affect LOS.ConclusionBecause hospitals consume a perceptible part of resources in a health system, controlled and optimized use of its resources help to save a lot. Therefore, this study showed many clinical and nonclinical factors affect LOS in evaluating these factors, which may reduce inappropriate hospital stays and decrease costs.

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Section: Discussionmentioning

confidence: 69%

Factors affecting length of stay in teaching hospitals of a middle-income country

Khosravizadeh¹,

Vatankhah²,

Bastani³

et al. 2016

Electron physician

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“…In other patient populations, care coordination and extended care facility availability influence LOS to a large degree. 8,18 For surgical patients, emerging evidence suggests that process interventions like enhanced recovery pathways are effective at reducing LOS without increasing overall complication rates, but the efficacy of such interventions on a large scale remains unclear. 9,19–22 With different uptake and implementation of enhanced recovery for colectomy patients, it would be reasonable to assume practice style differences underlie at least a portion of the unexplained variation in hospital extended LOS rates.…”

Section: Discussionmentioning

confidence: 99%

Extended Length of Stay After Surgery

2014

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Importance With recent health policy focus on shifting risk to providers, hospital leaders are increasing efforts to reduce excessive resource use, such as patients with extended length of stay (LOS) after surgery. However, it is unclear the degree to which extended LOS represents complications, patient illness, or inefficient practice style. Objective We sought to examine the influence of complications on hospital extended LOS rate variation after colorectal resections. Design Retrospective cohort study. Setting Hospitals participating in the 2009 American College of Surgeons National Surgical Quality Improvement Project (199 hospitals) Participants Adults undergoing inpatient colorectal resections (N=22,664 patients) Exposures Inpatient complications recorded in the ACS-NSQIP dataset. Inpatient complications were identified by their postoperative date of occurrence’s relationship to the patient’s surgical discharge date. Main outcome measures Risk-adjusted hospital extended LOS rates, defined as the proportion of patients with hospital stay greater than 75th percentile for the entire cohort. Results Forty-three percent of patients with extended LOS did not have a documented inpatient complication. While there was wide variation in both risk-adjusted extended LOS (15%–35%) and risk-adjusted inpatient complication (12%–29%) rates, there was only weak correlation (Spearman’s rho 0.56) between the two. Only half (52%) of the variation in hospital extended LOS rates was attributable to hospital inpatient complication rates. Conclusions and Relevance Much of the variation in hospital risk-adjusted extended LOS rates is not attributable to patient illness or complications and therefore most likely represents differences in practice style. Efforts to reduce excess resource utilization should focus on the efficiency of care, such as increased adoption of enhanced recovery pathways.

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“…Within the field of trauma, several studies have shown that race and insurance are related to measures such as the likelihood of inhospital mortality, the amount of care received, and length of stay. 1–6 Yet despite these findings, little is known about how these factors influence the interactions of trauma patients with the health care system immediately after discharge from the hospital.…”

Section: Introductionmentioning

confidence: 99%

Factors Affecting the Likelihood of Presentation to the Emergency Department of Trauma Patients After Discharge

Ladha

Young

et al. 2011

Annals of Emergency Medicine

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Study objective We determine the rate at which trauma patients re-present to the emergency department (ED) after discharge from the hospital and determine whether re-presentation is related to race, insurance, and socioeconomic factors such as neighborhood income level. Methods Trauma patients admitted to a Level I trauma center between January 1, 1997, and December 31, 2007, were identified with the hospital’s trauma registry. These patients were linked to administrative data to obtain information about re-presentation to the hospital. Neighborhood income was obtained with census block data; multiple imputation was implemented to account for missing income data. Logistic regression analysis was used to determine the predictors of re-presentation. Results There were 6,675 patients who were included in the study. A total of 886 patients (13.3%) returned to the ED within 30 days of discharge from the hospital. Uninsured patients (odds ratio [OR]=1.64; 95% confidence interval [CI] 1.30 to 2.06) and publicly insured patients (OR=1.60; 95% CI 1.20 to 2.14) were more likely to re-present to the ED than those with commercial insurance. Residing in a neighborhood with a median household income less than $20,000 was associated with a higher odds of re-presentation (OR=1.77; 95% CI 1.37 to 2.29). Only 13.2% of patients who came to the ED were readmitted to the hospital. Conclusion A substantial number of trauma patients return to the ED within 30 days of being discharged, but only a small proportion of these patients required readmission. Re-presentation is associated with being uninsured or underinsured and with lower neighborhood income level.

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Length of Stay

Cited by 152 publications

References 27 publications

Factors affecting length of stay in teaching hospitals of a middle-income country

Factors affecting length of stay in teaching hospitals of a middle-income country

Extended Length of Stay After Surgery

Factors Affecting the Likelihood of Presentation to the Emergency Department of Trauma Patients After Discharge

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