778 resultados para Emergency service, hospital


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Gemstone Team HOPE (Hospital Optimal Productivity Enterprise)

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Current policy and practice emphasises much more than ever before a need for purchasers and providers to reduce appropriately the length of hospital stay. Consequently, a number of early discharge “schemes” have been developed. This paper presents the findings from an evaluation of a “home from hospital” (HFH) scheme. The HFH service provides a maximum of six weeks intensive domiciliary care for older people on their discharge from hospital. The aim of the service is to facilitate early discharge from hospital and to assist patients to regain independence. The study reported here elicited the views and perceptions of clients and professionals involved in the HFH scheme about the quality, efficiency and effectiveness of the service. Seventy-five clients were discharged from hospital to the HFH scheme during a two month period and those who consented to participate in the study were interviewed after discharge from the HFH service (n = 40). Participants had attended hospital for various conditions but the largest group were fracture patients. Hospital staff and community based professionals completed a questionnaire about the service. Overall, clients and professionals perceived the HFH scheme as a beneficial service, though some minor problems existed at an individual level. Clients’ dependency levels generally decreased during their time on the scheme. Research using a controlled design is necessary in order to draw firm conclusions about the cost-effectiveness of a HFH service. Overall, home-from-hospital appears to be an effective model of an early discharge scheme worthy of further attention.

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This paper reports the results of an investigation, by postal questionnaire, of the views of 30 General Practitioners about a model of out of hospital care – the home from hospital (HFH) service, which mainly provides social care and rehabilitation for patients in their own home. The GPs, who all worked within one of the Health and Social Services Board areas in Northern Ireland during the time of the study (March-April 1998), indicated that the introduction of the HFH service, unlike other models of out of hospital care, did not increase their workload. Therefore, it is suggested that the HFH model of care should be given more attention in terms of research evaluation and service development.

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There is compelling evidence for the effectiveness of home-based occupational therapy and physiotherapy rehabilitation for community dwelling elderly who may struggle with basic activities and the functions of daily living and mobility. Nonetheless, an estimated 2% of home care’s elderly clients receive these therapies. Ontario’s home care data indicates that 78% of clients that could benefit from these specific therapies are not receiving them. The study examined a subset of elderly clients receiving home care following a hospital discharge during 2009-2010. The aim of this study was to: understand the difference between those home care clients who received occupational therapy or physiotherapy and those who did not; and determine if receiving these therapies impacted the utilization of hospital emergency departments and inpatient admissions. A retrospective cohort design and multivariate and survival analysis of hospital and home care administrative data structured the study. Results suggest that home-based rehabilitation is offered to a minority of the home care population. Distinct client characteristics and process variables significantly associated with the increased likelihood of receiving home-based occupational and physical therapies included: clients who were older, females, admitted to home care from hospital inpatient units, assessed as non-acute for clinical and service needs and required more home making support and assistance with activities of daily living. Almost one quarter of the total sample returned to hospital. Visits to emergency departments accounted for the greater part of hospital utilization and primarily for sub-acute general symptoms and signs, post-procedural complications, infections or acute episodes from chronic obstructive pulmonary disease and renal failure. Slightly over half of the clients returning to hospital did not receive home-based rehabilitation. Clients who received occupational therapy returned to the hospital sooner following their home care admission whereas clients receiving physiotherapy spent the longest time before rehospitalizing. The majority of the clients receiving occupational therapy were admitted to home care having just resolved sub-acute conditions or symptoms, many of which are known to influence functional and physical decline. Moreover, analysis of process variables indicated that the wait time for a referral to occupational therapy was two times longer compared to physiotherapy. These same clients also waited, on average, over one month before an occupational therapist’s first visit. The need to discriminate who receives home-based rehabilitation is essential to understanding how specific therapies contribute to improving systems outcomes. This study is the first examination that focuses specifically on home-based occupational therapy and physiotherapy rehabilitation and the client characteristics and process variables associated with receiving/not receiving these therapies and the impact these factors have on the time-to-rehospitalization.

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The paper introduces a new modeling approach that represents the waiting times in an Accident and Emergency (A&E) Department in a UK based National Health Service (NHS) hospital. The technique uses Bayesian networks to capture the heterogeneity of arriving patients by representing how patient covariates interact to influence their waiting times in the department. Such waiting times have been reviewed by the NHS as a means of investigating the efficiency of A&E departments (Emergency Rooms) and how they operate. As a result activity targets are now established based on the patient total waiting times with much emphasis on trolley waits.

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Objective: To evaluate the impact of a hospital based community liaison pharmacy service on a range of outcomes in patients aged more than 55 years and taking more than 3 prescribed drugs, who had been admitted to the medical unit of a district general hospital in Northern Ireland.

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The paper introduces a new modeling approach that represents the waiting times in an accident and emergency (A&E) department in a UK based national health service (NHS) hospital. The technique uses Bayesian networks to capture the heterogeneity of arriving patients by representing how patient covariates interact to influence their waiting times in the department. Such waiting times have been reviewed by the NHS as a means of investigating the efficiency of A&E departments (emergency rooms) and how they operate. As a result activity targets are now established based on the patient total waiting times with much emphasis on trolley waits.

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Objective: To determine the pooled effect of exposure to one of 11 specialist palliative care teams providing services in patients’ homes.Design: Pooled analysis of a retrospective cohort study.Setting: Ontario, Canada.Participants: 3109 patients who received care from specialist palliative care teams in 2009-11 (exposed) matched by propensity score to 3109 patients who received usual care (unexposed).Intervention: The palliative care teams studied served different geographies and varied in team composition and size but had the same core team members and role: a core group of palliative care physicians, nurses, and family physicians who provide integrated palliative care to patients in their homes. The teams’ role was to manage symptoms, provide education and care, coordinate services, and be available without interruption regardless of time or day.Main outcome measures: Patients (a) being in hospital in the last two weeks of life; (b) having an emergency department visit in the last two weeks of life; or (c) dying in hospital.Results: In both exposed and unexposed groups, about 80% had cancer and 78% received end of life homecare services for the same average duration. Across all palliative care teams, 970 (31.2%) of the exposed group were in hospital and 896 (28.9%) had an emergency department visit in the last two weeks of life respectively, compared with 1219 (39.3%) and 1070 (34.5%) of the unexposed group (P<0.001). The pooled relative risks of being in hospital and having an emergency department visit in late life comparing exposed versus unexposed were 0.68 (95% confidence interval 0.61 to 0.76) and 0.77 (0.69 to 0.86) respectively. Fewer exposed than unexposed patients died in hospital (503 (16.2%) v 887 (28.6%), P<0.001), and the pooled relative risk of dying in hospital was 0.46 (0.40 to 0.52).Conclusions: Community based specialist palliative care teams, despite variation in team composition and geographies, were effective at reducing acute care use and hospital deaths at the end of life.

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Rationale, aims and objectives: This study aimed to determine the value of using a mix of clinical pharmacy data and routine hospital admission spell data in the development of predictive algorithms. Exploration of risk factors in hospitalized patients, together with the targeting strategies devised, will enable the prioritization of clinical pharmacy services to optimize patient outcomes. 

Methods: Predictive algorithms were developed using a number of detailed steps using a 75% sample of integrated medicines management (IMM) patients, and validated using the remaining 25%. IMM patients receive targeted clinical pharmacy input throughout their hospital stay. The algorithms were applied to the validation sample, and predicted risk probability was generated for each patient from the coefficients. Risk threshold for the algorithms were determined by identifying the cut-off points of risk scores at which the algorithm would have the highest discriminative performance. Clinical pharmacy staffing levels were obtained from the pharmacy department staffing database. 

Results: Numbers of previous emergency admissions and admission medicines together with age-adjusted co-morbidity and diuretic receipt formed a 12-month post-discharge and/or readmission risk algorithm. Age-adjusted co-morbidity proved to be the best index to predict mortality. Increased numbers of clinical pharmacy staff at ward level was correlated with a reduction in risk-adjusted mortality index (RAMI). 

Conclusions: Algorithms created were valid in predicting risk of in-hospital and post-discharge mortality and risk of hospital readmission 3, 6 and 12 months post-discharge. The provision of ward-based clinical pharmacy services is a key component to reducing RAMI and enabling the full benefits of pharmacy input to patient care to be realized.

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Introduction
Standard treatment for neovascular age-related macular degeneration (nAMD) is intravitreal injections of anti-VEGF drugs. Following multiple injections, nAMD lesions often become quiescent but there is a high risk of reactivation, and regular review by hospital ophthalmologists is the norm. The present trial examines the feasibility of community optometrists making lesion reactivation decisions.

Methods
The Effectiveness of Community vs Hospital Eye Service (ECHoES) trial is a virtual trial; lesion reactivation decisions were made about vignettes that comprised clinical data, colour fundus photographs, and optical coherence tomograms displayed on a web-based platform. Participants were either hospital ophthalmologists or community optometrists. All participants were provided with webinar training on the disease, its management, and assessment of the retinal imaging outputs. In a balanced design, 96 participants each assessed 42 vignettes; a total of 288 vignettes were assessed seven times by each professional group.The primary outcome is a participant's judgement of lesion reactivation compared with a reference standard. Secondary outcomes are the frequency of sight threatening errors; judgements about specific lesion components; participant-rated confidence in their decisions about the primary outcome; cost effectiveness of follow-up by optometrists rather than ophthalmologists.

Discussion
This trial addresses an important question for the NHS, namely whether, with appropriate training, community optometrists can make retreatment decisions for patients with nAMD to the same standard as hospital ophthalmologists. The trial employed a novel approach as participation was entirely through a web-based application; the trial required very few resources compared with those that would have been needed for a conventional randomised controlled clinical trial.

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The objective of this study was to develop, test and benchmark a framework and a predictive risk model for hospital emergency readmission within 12 months. We performed the development using routinely collected Hospital Episode Statistics data covering inpatient hospital admissions in England. Three different timeframes were used for training, testing and benchmarking: 1999 to 2004, 2000 to 2005 and 2004 to 2009 financial years. Each timeframe includes 20% of all inpatients admitted within the trigger year. The comparisons were made using positive predictive value, sensitivity and specificity for different risk cut-offs, risk bands and top risk segments, together with the receiver operating characteristic curve. The constructed Bayes Point Machine using this feature selection framework produces a risk probability for each admitted patient, and it was validated for different timeframes, sub-populations and cut-off points. At risk cut-off of 50%, the positive predictive value was 69.3% to 73.7%, the specificity was 88.0% to 88.9% and sensitivity was 44.5% to 46.3% across different timeframes. Also, the area under the receiver operating characteristic curve was 73.0% to 74.3%. The developed framework and model performed considerably better than existing modelling approaches with high precision and moderate sensitivity.

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The prolonged wait times may arguably put into question the Canadian Health Act of 1984. Statistics show throughput wait times are 5.5 hours and output wait times for admitted patients are 32.4 hours. After probing and analyzing best practices through a qualitative/quantitative Value Stream Mapping and a qualitative SWOT Analysis; Team Triage and an Overcapacity Protocol is suggested to improve non-admitted patients wait times by 1.89 hours and admitted patients wait times by 16 hours by eliminating wasteful steps in the patient process and upon overcapacity, effectively sharing already stabilized and admitted patients with all wards in the hospital.