Trends in hospital average lengths of stay, casemix, and discharge, 1980-85.

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Factors influencing hospital readmission and length of stay of Vietnamese patients with type 2 diabetes and cardiac disease

Background: Increased hospital readmission and longer stays in the hospital for patients with type 2 diabetes and cardiac disease can result in higher healthcare costs and heavier individual burden. Thus, knowledge of the characteristics and predictive factors for Vietnamese patients with type 2 diabetes and cardiac disease, at high risk of hospital readmission and longer stays in the hospital, could provide a better understanding on how to develop an effective care plan aimed at improving patient outcomes. However, information about factors influencing hospital readmission and length of stay of patients with type 2 diabetes and cardiac disease in Vietnam is limited. Aim: This study examined factors influencing hospital readmission and length of stay of Vietnamese patients with both type 2 diabetes and cardiac disease. Methods: An exploratory prospective study design was conducted on 209 patients with type 2 diabetes and cardiac disease in Vietnam. Data were collected from patient charts and patients' responses to self-administered questionnaires. Descriptive statistics, bivariate correlation, logistic and multiple regression were used to analyse the data. Results: The hospital readmission rate was 12.0% among patients with both type 2 diabetes and cardiac disease. The average length of stay in the hospital was 9.37 days. Older age (OR= 1.11, p< .05), increased duration of type 2 diabetes (OR= 1.22, p< .05), less engagement in stretching/strengthening exercise behaviours (OR= .93, p< .001) and in communication with physician (OR= .21, p< .001) were significant predictors of 30-dayhospital readmission. Increased number of additional co-morbidities (β= .33, p< .001) was a significant predictor of longer stays in the hospital. High levels of cognitive symptom management (β= .40, p< .001) significantly predicted longer stays in the hospital, indicating that the more patients practiced cognitive symptom management, the longer the stay in hospital. Conclusions: This study provides some evidence of factors influencing hospital readmission and length of stay and argues that this information may have significant implications for clinical practice in order to improve patients' health outcomes. However, the findings of this study related to the targeted hospital only. Additionally, the investigation of environmental factors is recommended for future research as these factors are important components contributing to the research model.

Length of Stay-Based Patient Flow Models: Recent Developments and Future Directions

Modelling patient flow in health care systems is vital in understanding the system activity and may therefore prove to be useful in improving their functionality. An extensively used measure is the average length of stay which, although easy to calculate and quantify, is not considered appropriate when the distribution is very long-tailed. In fact, simple deterministic models are generally considered inadequate because of the necessity for models to reflect the complex, variable, dynamic and multidimensional nature of the systems. This paper focuses on modelling length of stay and flow of patients. An overview of such modelling techniques is provided, with particular attention to their impact and suitability in managing a hospital service.

Length of stay comparisons for private and public hospitals.

This analysis uses average length of stay as a proxy for efficiency, to compare the Australian private and public hospital sectors. We conclude that private hospitals are more efficient than public hospitals in providing the range of care provided by private hospitals. However, public hospitals are more efficient in handling the casemix of the public hospital sector. The picture is more complicated when particular types of care (such as obstetric and psychiatric) are excluded.

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

Impact of a stroke unit on length of hospital stay and in-hospital case fatality

Background and Purpose Randomized trials have demonstrated reduced morbidity and mortality with stroke unit care; however, the effect on length of stay, and hence the economic benefit, is less well-defined. In 2001, a multidisciplinary stroke unit was opened at our institution. We observed whether a stroke unit reduces length of stay and in-hospital case fatality when compared to admission to a general neurology/medical ward. Methods A retrospective study of 2 cohorts in the Foothills Medical Center in Calgary was conducted using administrative databases. We compared a cohort of stroke patients managed on general neurology/medical wards before 2001, with a similar cohort of stroke patients managed on a stroke unit after 2003. The length of stay was dichotomized after being centered to 7 days and the Charlson Index was dichotomized for analysis. Multivariable logistic regression was used to compare the length of stay and case fatality in 2 cohorts, adjusted for age, gender, and patient comorbid conditions defined by the Charlson Index. Results Average length of stay for patients on a stroke unit (n=2461) was 15 days vs 19 days for patients managed on general neurology/medical wards (n=1567). The proportion of patients with length of stay >7 days on general neurology/medical wards was 53.8% vs 44.4% on the stroke unit (difference 9.4%; P<0.0001). The adjusted odds of a length of stay >7 days was reduced by 30% (P<0.0001) on a stroke unit compared to general neurology/medical wards. Overall in-hospital case fatality was reduced by 4.5% with stroke unit care. Conclusions We observed a reduced length of stay and reduced in-hospital case-fatality in a stroke unit compared to general neurology/medical wards.

Walking in hospital is associated with a shorter length of stay in older medical inpatients

Evidence suggests that inactivity during a hospital stay is associated with poor health outcomes in older medical inpatients. We aimed to estimate the associations of average daily step-count (walking) in hospital with physical performance and length of stay in this population. Medical in-patients aged ⩾65 years, premorbidly mobile, with an anticipated length of stay ⩾3 d, were recruited. Measurements included average daily step-count, continuously recorded until discharge, or for a maximum of 7 d (Stepwatch Activity Monitor); co-morbidity (CIRS-G); frailty (SHARE F-I); and baseline and end-of-study physical performance (short physical performance battery). Linear regression models were used to estimate associations between step-count and end-of-study physical performance or length of stay. Length of stay was log transformed in the first model, and step-count was log transformed in both models. Similar models were used to adjust for potential confounders. Data from 154 patients (mean 77 years, SD 7.4) were analysed. The unadjusted models estimated for each unit increase in the natural log of stepcount, the natural log of length of stay decreased by 0.18 (95% CI −0.27 to −0.09). After adjustment of potential confounders, while the strength of the inverse association was attenuated, it remained significant (βlog(steps) = −0.15, 95%CI −0.26 to −0.03). The back-transformed result suggested that a 50% increase in step-count was associated with a 6% shorter length of stay. There was no apparent association between step-count and end-of-study physical performance once baseline physical performance was adjusted for. The results indicate that step-count is independently associated with hospital length of stay, and merits further investigation.

Excess length of stay due to central line–associated bloodstream infection in intensive care units in Argentina, Brazil, and Mexico

Objective.To estimate the excess length of stay in an intensive care unit (ICU) due to a central line–associated bloodstream infection (CLABSI), using a multistate model that accounts for the timing of infection. Design.A cohort of 3,560 patients followed up for 36,806 days in ICUs. Setting.Eleven ICUs in 3 Latin American countries: Argentina, Brazil, and Mexico. Patients.All patients admitted to the ICU during a defined time period with a central line in place for more than 24 hours. Results.The average excess length of stay due to a CLABSI increased in 10 of 11 ICUs and varied from −1.23 days to 4.69 days. A reduction in length of stay in Mexico was probably caused by an increased risk of death due to CLABSI, leading to shorter times to death. Adjusting for patient age and Average Severity of Illness Score tended to increase the estimated excess length of stays due to CLABSI. Conclusions.CLABSIs are associated with an excess length of ICU stay. The average excess length of stay varies between ICUs, most likely because of the case‐mix of admissions and differences in the ways that hospitals deal with infections.

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 prevalence of malnutrition in a tertiary hospital in Singapore and its impact on hospitalization outcomes and costs, controlling for DRG. Methods: This prospective cohort study included a matched case control study. Subjective Global Assessment was used to assess the nutritional status on admission of 818 adults. Hospitalization outcomes over 3 years were adjusted for gender, age, ethnicity, and matched for DRG. 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 hospitalization 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 the inpatients and led to poor hospitalization outcomes and survival as well as increased costs of care, even after matching for DRG. Strategies to prevent and treat malnutrition in the hospital and post-discharge are needed.

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.

Does improved access to diagnostic imaging results reduce hospital length of stay? A retrospective study.

BACKGROUND: One year after the introduction of Information and Communication Technology (ICT) to support diagnostic imaging at our hospital, clinicians had faster and better access to radiology reports and images; direct access to Computed Tomography (CT) reports in the Electronic Medical Record (EMR) was particularly popular. The objective of this study was to determine whether improvements in radiology reporting and clinical access to diagnostic imaging information one year after the ICT introduction were associated with a reduction in the length of patients' hospital stays (LOS). METHODS: Data describing hospital stays and diagnostic imaging were collected retrospectively from the EMR during periods of equal duration before and one year after the introduction of ICT. The post-ICT period was chosen because of the documented improvement in clinical access to radiology results during that period. The data set was randomly split into an exploratory part used to establish the hypotheses, and a confirmatory part. The data was used to compare the pre-ICT and post-ICT status, but also to compare differences between groups. RESULTS: There was no general reduction in LOS one year after ICT introduction. However, there was a 25% reduction for one group - patients with CT scans. This group was heterogeneous, covering 445 different primary discharge diagnoses. Analyses of subgroups were performed to reduce the impact of this divergence. CONCLUSION: Our results did not indicate that improved access to radiology results reduced the patients' LOS. There was, however, a significant reduction in LOS for patients undergoing CT scans. Given the clinicians' interest in CT reports and the results of the subgroup analyses, it is likely that improved access to CT reports contributed to this reduction.

Preoperative pain level and patient expectation predict hospital length of stay after total hip arthroplasty.

The purpose of this study was to identify preoperative predictors of length of stay after primary total hip arthroplasty in a patient population reflecting current trends toward shorter hospitalization and using readily obtainable factors that do not require scoring systems. A retrospective review of 112 consecutive patients was performed. High preoperative pain level and patient expectation of discharge to extended care facilities (ECFs) were the only significant multivariable predictors of hospitalization extending beyond 2 days (P=0.001 and P<0.001 respectively). Patient expectation remained significant after adjusting for Medicare's 3-day requirement for discharge to ECFs (P<0.001). The study was adequately powered to analyze the variables in the multivariable logistic regression model, which had a concordance index of 0.857.

Preoperative predictors of extended hospital length of stay following total knee arthroplasty.

The purpose of this study was to identify the preoperative predictors of hospital length of stay after primary total knee arthroplasty in a patient population reflecting current trends toward shorter hospitalization and using readily obtainable factors that do not require scoring systems. A single-center, multi-surgeon retrospective chart review of two hundred and sixty consecutive patients who underwent primary total knee arthroplasty was performed. The mean length of stay was 3.0 days. Among the different variables studied, increasing comorbidities, lack of adequate assistance at home, and bilateral surgery were the only multivariable significant predictors of longer length of stay. The study was adequately powered for statistical analyses and the concordance index of the multivariable logistic regression model was 0.815.