scholarly journals Extended Length of Hospital Stay for Surgical and Medical Patients – Insights from Hospital and Psychosocial Predictors

2022 ◽  
Author(s):  
Chinedu Ossai ◽  
Nilmini Wickramasinghe
Keyword(s):  
Hospital Stay ◽  
Length Of Hospital Stay ◽  
Psychosocial Predictors ◽  
Medical Patients ◽  
Extended Length

MRI in Acutely Ill Medical Patients in an Irish Hospital: Influence on Outcomes and Length of Hospital Stay

2014 ◽  
Vol 11 (7) ◽  
pp. 698-702 ◽  
Author(s):  
Seán Cournane ◽  
Donnacha Creagh ◽  
Neil O'Hare ◽  
Niall Sheehy ◽  
Bernard Silke
Keyword(s):  
Hospital Stay ◽  
Length Of Hospital Stay ◽  
Medical Patients ◽  
Irish Hospital

scholarly journals Efficacy of Quetiapine for Delirium Prevention in Hospitalized Older Medical Patients: a Randomized Double-blind Controlled Trial

2021 ◽  
Author(s):  
Saran Thanapluetiwong ◽  
Sirasa Ruangritchankul ◽  
Orapitchaya Sriwanno ◽  
Sirintorn Chansirikarnjana ◽  
Pichai Ittasakul ◽  
...  
Keyword(s):  
Hospital Stay ◽  
Controlled Trial ◽  
Length Of Hospital Stay ◽  
Population Group ◽  
Incidence Rates ◽  
Medical Patients ◽  
Double Blind ◽  
Icu Admission ◽  
Intention To Treat ◽  
Delirium Prevention

Abstract Background: Delirium is a common disorder among hospitalized older patients and results in increased morbidity and mortality. The prevention of delirium is still challenging in older patient care. The role of antipsychotics in delirium prevention has been limited. Therefore, we conducted a trial to investigate the efficacy of quetiapine use to prevent delirium in hospitalized older medical patients.Methods: This study was a randomized double-blind controlled trial conducted at Ramathibodi Hospital, Bangkok, Thailand. Patients aged ≥ 65 years hospitalized in the internal medicine service were randomized to quetiapine 12.5 mg or placebo once daily at bedtime for a maximum 7-day duration. The primary end point was delirium incidence. Secondary end points were delirium duration, length of hospital stay, ICU admission, rehospitalization and mortality within 30 and 90 days.Results: A total of 122 patients were enrolled in the study. Eight (6.6%) left the trial before receiving the first dose of the intervention, whereas 114 (93.4%) were included in an intention-to-treat analysis allocated to the quetiapine or placebo group (n=57 each). The delirium incidence rates in the quetiapine and placebo groups were 14.0% and 8.8% (OR=1.698, 95% CI 0.520-5.545, P=0.381), respectively. Other endpoints in the quetiapine and placebo groups were the median length of hospital stay, 6 (4-8) days versus 5 (4-8) days (P=0.133), respectively; delirium duration, 4 (2.3-6.5) versus 3 (1.5-4.0) days (P=0.557), respectively; ICU admission, 3 (5.3%) patients from both groups (P=1.000); and mortality in the quetiapine and placebo groups, 1 (1.8%) versus 2 (3.5%) at 30 days (P=0.566) and 7 (12.3%) versus 9 (15.8%) days at 90 days (P=0.591). There were no significant differences in other outcomes. None of the participants reported adverse events.Conclusions: Quetiapine prophylaxis did not reduce delirium incidence in hospitalized older medical patients. The use of quetiapine to prevent delirium in this population group should not be recommended.Trial registration: This trial was retrospectively registered with the Thai clinical trials registry (TCTR) at clinicaltrials.in.th (TCTR20190927001) on September 26, 2019.

scholarly journals Hospitals in Europe Link for Infection Control through Surveillance (HELICS)

2004 ◽  
Vol 8 (8) ◽  
Author(s):  
J Wilson
Keyword(s):  
Infection Control ◽  
Hospital Stay ◽  
Length Of Hospital Stay ◽  
Significant Morbidity ◽  
Permanent Disability ◽  
Extended Length

Infections acquired in hospitals are recognised to be associated with significant morbidity, resulting in extended length of hospital stay, pain, discomfort and sometimes prolonged or permanent disability

scholarly journals A multistage mixed methods study protocol to evaluate the implementation and impact of a reconfiguration of acute medicine in Ireland’s hospitals

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
E. Hurley ◽  
S. McHugh ◽  
J. Browne ◽  
L. Vaughan ◽  
C. Normand
Keyword(s):  
Mixed Methods ◽  
Hospital Stay ◽  
Patient Care ◽  
Hospital Admissions ◽  
Hospital Setting ◽  
Length Of Hospital Stay ◽  
Comparative Case Study ◽  
Medical Patients ◽  
Acute Medicine ◽  
The Impact

Abstract Background To address deficits in the delivery of acute services in Ireland, the National Acute Medicine Programme (NAMP) was established in 2010 to optimise the management of acutely ill medical patients in the hospital setting, and to ensure their supported discharge to primary and community-based care. NAMP aims to reduce inappropriate hospital admissions, reduce length of hospital stay and ensure patients receive timely treatment in the most appropriate setting. It does so primarily via the development of Acute Medical Assessment Units (AMAUs) for the rapid assessment and management of medical patients presenting to hospitals, as well as streamlining the care of those admitted for further care. This study will examine the impact of this programme on patient care and identify the factors influencing its implementation and operation. Methods We will use a multistage mixed methods evaluation with an explanatory sequential design. Firstly, we will develop a logic model to describe the programme’s outcomes, its components and the mechanisms of change by which it expects to achieve these outcomes. Then we will assess implementation by measuring utilisation of the Units and comparing the organisational functions implemented to that recommended by the NAMP model of care. Using comparative case study research, we will identify the factors which have influenced the programme’s implementation and its operation using the Consolidated Framework for Implementation Research to guide data collection and analysis. This will be followed by an estimation of the impact of the programme on reducing overnight emergency admissions for potentially avoidable medical conditions, and reducing length of hospital stay of acute medical patients. Lastly, data from each stage will be integrated to examine how the programme’s outcomes can be explained by the level of implementation. Discussion This formative evaluation will enable us to examine whether the NAMP is improving patient care and importantly draw conclusions on how it is doing so. It will identify the factors that contribute to how well the programme is being implemented in the real-world. Lessons learnt will be instrumental in sustaining this programme as well as planning, implementing, and assessing other transformative programmes, especially in the acute care setting.

Female Sex Is Associated With Extended Length of Hospital Stay Following CABG Surgery in Patients With Severe Obesity

2016 ◽  
Vol 32 (4) ◽  
pp. S5
Author(s):  
M. Forhan ◽  
W. Qiu ◽  
T. Terada ◽  
R. Padwal ◽  
J. Johnson ◽  
...  
Keyword(s):  
Hospital Stay ◽  
Severe Obesity ◽  
Length Of Hospital Stay ◽  
Cabg Surgery ◽  
Female Sex ◽  
Extended Length

scholarly journals Different models for prediction of radical cystectomy postoperative complications and care pathways

2019 ◽  
Vol 11 ◽  
pp. 175628721987558 ◽  
Author(s):  
Jacob Taylor ◽  
Xiaosong Meng ◽  
Audrey Renson ◽  
Angela B. Smith ◽  
James S. Wysock ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Random Forest ◽  
Postoperative Complications ◽  
Adverse Events ◽  
Hospital Stay ◽  
Radical Cystectomy ◽  
Length Of Hospital Stay ◽  
Level Of Care ◽  
Improvement Program ◽  
Extended Length

Background: Radical cystectomy for bladder cancer has one of the highest rates of morbidity among urologic surgery, but the ability to predict postoperative complications remains poor. Our study objective was to create machine learning models to predict complications and factors leading to extended length of hospital stay and discharge to a higher level of care after radical cystectomy. Methods: Using the American College of Surgeons National Surgical Quality Improvement Program, peri-operative adverse outcome variables for patients undergoing elective radical cystectomy for bladder cancer from 2005 to 2016 were extracted. Variables assessed include occurrence of minor, infectious, serious, or any adverse events, extended length of hospital stay, and discharge to higher-level care. To develop predictive models of radical cystectomy complications, we fit generalized additive model (GAM), least absolute shrinkage and selection operator (LASSO) logistic, neural network, and random forest models to training data using various candidate predictor variables. Each model was evaluated on the test data using receiver operating characteristic curves. Results: A total of 7557 patients were identified who met the inclusion criteria, and 2221 complications occurred. LASSO logistic models demonstrated the highest area under curve for predicting any complications (0.63), discharge to a higher level of care (0.75), extended length of stay (0.68), and infectious (0.62) adverse events. This was comparable with random forest in predicting minor (0.60) and serious (0.63) adverse events. Conclusions: Our models perform modestly in predicting radical cystectomy complications, highlighting both the complex cystectomy process and the limitations of large healthcare datasets. Identifying the most important variable leading to each type of adverse event may allow for further strategies to model cystectomy complications and target optimization of modifiable variables pre-operative to reduce postoperative adverse events.

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