The impact of malnutrition and decreased food intake on length of stay, readmission, and mortality in acute care patients

Rationale: The Australasian Nutrition Care Day Survey (ANCDS) evaluated if malnutrition and decreased food intake are independent risk factors for negative outcomes in hospitalised patients. Methods: A multicentre (56 hospitals) cross-sectional survey was conducted in two phases. Phase 1 evaluated nutritional status (defined by Subjective Global Assessment) and 24-hour food intake recorded as 0, 25, 50, 75, and 100% intake. Phase 2 data, which included length of stay (LOS), readmissions and mortality, were collected 90 days post-Phase 1. Logistic regression was used to control for confounders: age, gender, disease type and severity (using Patient Clinical Complexity Level scores). Results: Of 3122 participants (53% males, mean age: 65±18 years) 32% were malnourished and 23% consumed�25% of the offered food. Median LOS for malnourished (MN) patients was higher than well-nourished (WN) patients (15 vs. 10 days, p<0.0001). Median LOS for patients consuming �25% of the food was higher than those consuming �50% (13 vs. 11 days, p<0.0001). MN patients had higher readmission rates (36% vs. 30%, p = 0.001). The odds ratios of 90-day in-hospital mortality were 1.8 times greater for MN patients (CI: 1.03 3.22, p = 0.04) and 2.7 times greater for those consuming �25% of the offered food (CI: 1.54 4.68, p = 0.001). Conclusion: The ANCDS demonstrates that malnutrition and/or decreased food intake are associated with longer LOS and readmissions. The survey also establishes that malnutrition and decreased food intake are independent risk factors for in-hospital mortality in acute care patients; and highlights the need for appropriate nutritional screening and support during hospitalisation. Disclosure of Interest: None Declared.

Language affects length of stay in emergency departments in Queensland public hospitals

BACKGROUND: A long length of stay (LOS) in the emergency department (ED) associated with overcrowding has been found to adversely affect the quality of ED care. The objective of this study is to determine whether patients who speak a language other than English at home have a longer LOS in EDs compared to those whose speak only English at home. METHODS: A secondary data analysis of a Queensland state-wide hospital EDs dataset (Emergency Department Information System) was conducted for the period, 1 January 2008 to 31 December 2010. RESULTS: The interpreter requirement was the highest among Vietnamese speakers (23.1%) followed by Chinese (19.8%) and Arabic speakers (18.7%). There were significant differences in the distributions of the departure statuses among the language groups (Chi-squared=3236.88, P<0.001). Compared with English speakers, the Beta coeffi cient for the LOS in the EDs measured in minutes was among Vietnamese, 26.3 (95%CI: 22.1–30.5); Arabic, 10.3 (95%CI: 7.3–13.2); Spanish, 9.4 (95%CI: 7.1–11.7); Chinese, 8.6 (95%CI: 2.6–14.6); Hindi, 4.0 (95%CI: 2.2–5.7); Italian, 3.5 (95%CI: 1.6–5.4); and German, 2.7 (95%CI: 1.0–4.4). The fi nal regression model explained 17% of the variability in LOS. CONCLUSION: There is a close relationship between the language spoken at home and the LOS at EDs, indicating that language could be an important predictor of prolonged LOS in EDs and improving language services might reduce LOS and ease overcrowding in EDs in Queensland's public hospitals.

Malnutrition and its impact on cost of hospitalization, length of stay, readmission and 3-year mortality

Background & aims The confounding effect of disease on the outcomes of malnutrition using diagnosis-related groups (DRG) has never been studied in a multidisciplinary setting. This study aims to determine the impact of malnutrition on hospitalisation outcomes, controlling for DRG. Methods Subjective Global Assessment was used to assess the nutritional status of 818 patients within 48 hours of admission. Prospective data were collected on cost of hospitalisation, length of stay (LOS), readmission and mortality up to 3 years post-discharged using National Death Register data. Mixed model analysis and conditional logistic regression matching by DRG were carried out to evaluate the association between nutritional status and outcomes, with the results adjusted for gender, age and race. Results Malnourished patients (29%) had longer hospital stays (6.9±7.3 days vs. 4.6±5.6 days, p<0.001) and were more likely to be readmitted within 15 days (adjusted relative risk = 1.9, 95%CI 1.1–3.2, p=0.025). Within a DRG, the mean difference between actual cost of hospitalisation and the average cost for malnourished patients was greater than well-nourished patients (p=0.014). Mortality was higher in malnourished patients at 1 year (34% vs. 4.1 %), 2 years (42.6% vs. 6.7%) and 3 years (48.5% vs. 9.9%); p<0.001 for all. Overall, malnutrition was a significant predictor of mortality (adjusted hazard ratio = 4.4, 95%CI 3.3-6.0, p<0.001). Conclusions Malnutrition was evident in up to one third of inpatients and led to poor hospitalisation outcomes, even after matching for DRG. Strategies to prevent and treat malnutrition in the hospital and post-discharge are needed.

The prolongation of length of stay because of Clostridium difficile infection

Background Clostridium difficile infection (CDI) possibly extends hospital length of stay (LOS); however, the current evidence does not account for the time-dependent bias, ie, when infection is incorrectly analyzed as a baseline covariate. The aim of this study was to determine whether CDI increases LOS after managing this bias. Methods We examined the estimated extra LOS because of CDI using a multistate model. Data from all persons hospitalized >48 hours over 4 years in a tertiary hospital in Australia were analyzed. Persons with health care-associated CDIs were identified. Cox proportional hazards models were applied together with multistate modeling. Results One hundred fifty-eight of 58,942 admissions examined had CDI. The mean extra LOS because of infection was 0.9 days (95% confidence interval: −1.8 to 3.6 days, P = .51) when a multistate model was applied. The hazard of discharge was lower in persons who had CDI (adjusted hazard ratio, 0.42; P < .001) when a Cox proportional hazard model was applied. Conclusion This study is the first to use multistate models to determine the extra LOS because of CDI. Results suggest CDI does not significantly contribute to hospital LOS, contradicting findings published elsewhere. Conversely, when methods prone to result in time-dependent bias were applied to the data, the hazard of discharge significantly increased. These findings contribute to discussion on methods used to evaluate LOS and health care-associated infections.

Number of prior episodes and the presence of depressive symptoms are associated with longer length of stay for patients with acute manic episodes

Background: Few studies have analyzed predictors of length of stay (LOS) in patients admitted due to acute bipolar manic episodes. The purpose of the present study was to estimate LOS and to determine the potential sociodemographic and clinical risk factors associated with a longer hospitalization. Such information could be useful to identify those patients at high risk for long LOS and to allocate them to special treatments, with the aim of optimizing their hospital management. Methods: This was a cross-sectional study recruiting adult patients with a diagnosis of bipolar disorder (Diagnostic and Statistical Manual of Mental Disorders, 4th edition, text revision (DSM-IV-TR) criteria) who had been hospitalized due to an acute manic episode with a Young Mania Rating Scale total score greater than 20. Bivariate correlational and multiple linear regression analyses were performed to identify independent predictors of LOS. Results: A total of 235 patients from 44 centers were included in the study. The only factors that were significantly associated to LOS in the regression model were the number of previous episodes and the Montgomery-Åsberg Depression Rating Scale (MADRS) total score at admission (P < 0.05). Conclusions: Patients with a high number of previous episodes and those with depressive symptoms during mania are more likely to stay longer in hospital. Patients with severe depressive symptoms may have a more severe or treatment-resistant course of the acute bipolar manic episode.

Modelling HIV/AIDS length of stay in Portugal

Tese apresentada como requisito parcial para obtenção do grau de Doutor em Estatística e Gestão de Informação pelo Instituto Superior de Estatística e Gestão de Informação da Universidade Nova de Lisboa

Blood transfusion in cardiac surgery is a risk factor for increased hospital length of stay in adult patients

Abstract Background Allogeneic red blood cell (RBC) transfusion has been proposed as a negative indicator of quality in cardiac surgery. Hospital length of stay (LOS) may be a surrogate of poor outcome in transfused patients. Methods Data from 502 patients included in Transfusion Requirements After Cardiac Surgery (TRACS) study were analyzed to assess the relationship between RBC transfusion and hospital LOS in patients undergoing cardiac surgery and enrolled in the TRACS study. Results According to the status of RBC transfusion, patients were categorized into the following three groups: 1) 199 patients (40%) who did not receive RBC, 2) 241 patients (48%) who received 3 RBC units or fewer (low transfusion requirement group), and 3) 62 patients (12%) who received more than 3 RBC units (high transfusion requirement group). In a multivariable Cox proportional hazards model, the following factors were predictive of a prolonged hospital length of stay: age higher than 65 years, EuroSCORE, valvular surgery, combined procedure, LVEF lower than 40% and RBC transfusion of > 3 units. Conclusion RBC transfusion is an independent risk factor for increased LOS in patients undergoing cardiac surgery. This finding highlights the adequacy of a restrictive transfusion therapy in patients undergoing cardiac surgery. Trial registration Clinicaltrials.gov identifier: http://NCT01021631.

Influencing factors on the length of stay in lumbar spine surgery: analysis of the German spine registry

INTRODUCTION Spinal disc herniation, lumbar spinal stenosis and spondylolisthesis are known to be leading causes of lumbar back pain. The cost of low back pain management and related operations are continuously increasing in the healthcare sector. There are many studies regarding complications after spine surgery but little is known about the factors predicting the length of stay in hospital. The purpose of this study was to identify these factors in lumbar spine surgery in order to adapt the postoperative treatment. MATERIAL AND METHODS The current study was carried out as a post hoc analysis on the basis of the German spine registry. Patients who underwent lumbar spine surgery by posterior surgical access and with posterior fusion and/or rigid stabilization, whereby procedures with dynamic stabilization were excluded. Patient characteristics were tested for association with length of stay (LOS) using bivariate and multivariate analyses. RESULTS A total of 356 patients met the inclusion criteria. The average age of all patients was 64.6 years and the mean LOS was 11.9 ± 6.0 days with a range of 2-44 days. Independent factors that were influencing LOS were increased age at the time of surgery, higher body mass index, male gender, blood transfusion of 1-2 erythrocyte concentrates and the presence of surgical complications. CONCLUSION Identification of predictive factors for prolonged LOS may allow for estimation of patient hospitalization time and for optimization of postoperative care. In individual cases this may result of a reduction in the LOS.

Study of length of stay in the cardiovascular intensive care unit

Coronary artery bypass graft (CABG) surgery is among the most common operations performed in the United States and accounts for more resources expended in cardiovascular medicine than any other single procedure. CABG surgery patients initially recover in the Cardiovascular Intensive Care Unit (CVICU). The post-procedure CVICU length of stay (LOS) goal is two days or less. A longer ICU LOS is associated with a prolonged hospital LOS, poor health outcomes, greater use of limited resources, and increased medical costs. ^ Research has shown that experienced clinicians can predict LOS no better than chance. Current CABG surgery LOS risk models differ greatly in generalizability and ease of use in the clinical setting. A predictive model that identified modifiable pre- and intra-operative risk factors for CVICU LOS greater than two days could have major public health implications as modification of these identified factors could decrease CVICU LOS and potentially minimize morbidity and mortality, optimize use of limited health care resources, and decrease medical costs. ^ The primary aim of this study was to identify modifiable pre-and intra-operative predictors of CVICU LOS greater than two days for CABG surgery patients with cardiopulmonary bypass (CPB). A secondary aim was to build a probability equation for CVICU LOS greater than two days. Data were extracted from 416 medical records of CABG surgery patients with CPB, 50 to 80 years of age, recovered in the CVICU of a large teaching, referral hospital in southeastern Texas, during the calendar year 2004 and the first quarter of 2005. Exclusion criteria included Diagnosis Related Group (DRG) 106, CABG surgery without CPB, CABG surgery with other procedures, and operative deaths. The data were analyzed using multivariate logistic regression for an alpha=0.05, power=0.80, and correlation=0.26. ^ This study found age, history of peripheral arterial disease, and total operative time equal to and greater than four hours to be independent predictors of CVICU LOS greater than two days. The probability of CVICU LOS greater than two days can be calculated by the following equation: -2.872941 +.0323081 (age in years) + .8177223 (history of peripheral arterial disease) + .70379 (operative time). ^

Adherence to a Bronchiolitis Clinical Pathway is Associated with Decreased Length of Stay and Costs

Thesis (Master's)--University of Washington, 2016-06

Finite mixture regression model with random effects: application to neonatal hospital length of stay

A two-component mixture regression model that allows simultaneously for heterogeneity and dependency among observations is proposed. By specifying random effects explicitly in the linear predictor of the mixture probability and the mixture components, parameter estimation is achieved by maximising the corresponding best linear unbiased prediction type log-likelihood. Approximate residual maximum likelihood estimates are obtained via an EM algorithm in the manner of generalised linear mixed model (GLMM). The method can be extended to a g-component mixture regression model with the component density from the exponential family, leading to the development of the class of finite mixture GLMM. For illustration, the method is applied to analyse neonatal length of stay (LOS). It is shown that identification of pertinent factors that influence hospital LOS can provide important information for health care planning and resource allocation. (C) 2002 Elsevier Science B.V. All rights reserved.

Modelling inpatient length of stay by a hierarchical mixture regression via the EM algorithm

The modelling of inpatient length of stay (LOS) has important implications in health care studies. Finite mixture distributions are usually used to model the heterogeneous LOS distribution, due to a certain proportion of patients sustaining-a longer stay. However, the morbidity data are collected from hospitals, observations clustered within the same hospital are often correlated. The generalized linear mixed model approach is adopted to accommodate the inherent correlation via unobservable random effects. An EM algorithm is developed to obtain residual maximum quasi-likelihood estimation. The proposed hierarchical mixture regression approach enables the identification and assessment of factors influencing the long-stay proportion and the LOS for the long-stay patient subgroup. A neonatal LOS data set is used for illustration, (C) 2003 Elsevier Science Ltd. All rights reserved.

Length of Stay, Discharge Destination, and Functional Improvement: Utility of the Australian National Subacute and Nonacute Patient Casemix Classification

Background and Purpose - Although implemented in 1998, no research has examined how well the Australian National Subacute and Nonacute Patient (AN-SNAP) Casemix Classification predicts length of stay (LOS), discharge destination, and functional improvement in public hospital stroke rehabilitation units in Australia. Methods - 406 consecutive admissions to 3 stroke rehabilitation units in Queensland, Australia were studied. Sociode-mographic, clinical, and functional data were collected. General linear modeling and logistic regression were used to assess the ability of AN-SNAP to predict outcomes. Results - AN-SNAP significantly predicted each outcome. There were clear relationships between the outcomes of longer LOS, poorer functional improvement and discharge into care, and the AN-SNAP classes that reflected poorer functional ability and older age. Other predictors included living situation, acute LOS, comorbidity, and stroke type. Conclusions - AN-SNAP is a consistent predictor of LOS, functional change and discharge destination, and has utility in assisting clinicians to set rehabilitation goals and plan discharge.

Factors affecting emergency department length of stay of patients admitted to telemetry and critical care units

The purpose of this study was to determine the emergency department (ED) length of stay (LOS) of patients admitted to inpatient telemetry and critical care units and to identify the factors that contribute to a prolonged ED LOS. It also examined whether there was a difference in ED LOS between clients evaluated by an ED physician, an Advanced Registered Nurse Practitioner (ARNP) or a Physician's Assistant (PA).^ A data collection tool was devised and used to record data obtained by retrospectively reviewing 110 charts of patients from this sample. The mean ED LOS was 286.75 minutes. Multiple factors were recorded as affecting the ED LOS of this sample, including: age, diagnosis, consultations, multiple radiographs, pending admission orders, nurse unable to call report/busy, relatives at bedside, observation or stabilization necessary, bed not ready and infusion in progress. No significant difference in ED LOS was noted between subjects initially evaluated by a physician, an ARNP or a PA. ^

Length of Stay in Intensive Care Units - A Case Base Evaluation

As a matter of fact, an Intensive Care Unit (ICU) stands for a hospital facility where patients require close observation and monitoring. Indeed, predicting Length-of-Stay (LoS) at ICUs is essential not only to provide them with improved Quality-of-Care, but also to help the hospital management to cope with hospital resources. Therefore, in this work one`s aim is to present an Artificial Intelligence based Decision Support System to assist on the prediction of LoS at ICUs, which will be centered on a formal framework based on a Logic Programming acquaintance for knowledge representation and reasoning, complemented with a Case Based approach to computing, and able to handle unknown, incomplete, or even contradictory data, information or knowledge.