276 resultados para Hospital Departments


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Police reported crash data are the primary source of crash information in most jurisdictions. However, the definition of serious injury within police-reported data is not consistent across jurisdictions and may not be accurate. With the Australian National Road Safety Strategy targeting the reduction of serious injuries, there is a greater need to assess the accuracy of the methods used to identify these injuries. A possible source of more accurate information relating to injury severity is hospital data. While other studies have compared police and hospital data to highlight the under-reporting in police-reported data, little attention has been given to the accuracy of the methods used by police to identify serious injuries. The current study aimed to assess how accurate the identification of serious injuries is in police-reported crash data, by comparing the profiles of transport-related injuries in the Queensland Road Crash Database with an aligned sample of data from the Queensland Hospital Admitted Patients Data Collection. Results showed that, while a similar number of traffic injuries were recorded in both data sets, the profile of these injuries was different based on gender, age, location, and road user. The results suggest that the ‘hospitalisation’ severity category used by police may not reflect true hospitalisations in all cases. Further, it highlights the wide variety of severity levels within hospitalised cases that are not captured by the current police-reported definitions. While a data linkage study is required to confirm these results, they highlight that a reliance on police-reported serious traffic injury data alone could result in inaccurate estimates of the impact and cost of crashes and lead to a misallocation of valuable resources.

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Objectives Heatwaves can have significant health consequences resulting in increased mortality and morbidity. However, their impact on people living in tropical/subtropical regions remains largely unknown. This study assessed the impact of heatwaves on mortality and emergency hospital admissions (EHAs) from non-external causes (NEC) in Brisbane, a subtropical city in Australia. Methods We acquired daily data on weather, air pollution and EHAs for patients aged 15 years and over in Brisbane between January 1996 and December 2005, and on mortality between January 1996 and November 2004. A locally derived definition of heatwave (daily maximum ≥37°C for 2 or more consecutive days) was adopted. Case–crossover analyses were used to assess the impact of heatwaves on cause-specific mortality and EHAs. Results During heatwaves, there was a statistically significant increase in NEC mortality (OR 1.46; 95% CI 1.21 to 1.77), cardiovascular mortality (OR 1.89; 95% CI 1.44 to 2.48), diabetes mortality in those aged 75+ (OR 9.96; 95% CI 1.02 to 96.85), NEC EHAs (OR 1.15; 95% CI 1.07 to 1.23) and EHAs from renal diseases (OR 1.41; 95% CI 1.09 to 1.83). The elderly were found to be particularly vulnerable to heatwaves (eg, for NEC EHAs, OR 1.24 for 65–74-year-olds and 1.39 for those aged 75+). Conclusions Significant increases in NEC mortality and EHAs were observed during heatwaves in Brisbane where people are well accustomed to hot summer weather. The most vulnerable were the elderly and people with cardiovascular, renal or diabetic disease.

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Objective Despite ‘hospital resilience’ gaining prominence in recent years, it remains poorly defined. This article aims to define hospital resilience, build a preliminary conceptual framework and highlight possible approaches to measurement. Methods Searches were conducted of the commonly used health databases to identify relevant literature and reports. Search terms included ‘resilience and framework or model’ or ‘evaluation or assess or measure and hospital and disaster or emergency or mass casualty and resilience or capacity or preparedness or response or safety’. Articles were retrieved that focussed on disaster resilience frameworks and the evaluation of various hospital capacities. Result A total of 1480 potentially eligible publications were retrieved initially but the final analysis was conducted on 47 articles, which appeared to contribute to the study objectives. Four disaster resilience frameworks and 11 evaluation instruments of hospital disaster capacity were included. Discussion and conclusion Hospital resilience is a comprehensive concept derived from existing disaster resilience frameworks. It has four key domains: hospital safety; disaster preparedness and resources; continuity of essential medical services; recovery and adaptation. These domains were categorised according to four criteria, namely, robustness, redundancy, resourcefulness and rapidity. A conceptual understanding of hospital resilience is essential for an intellectual basis for an integrated approach to system development. This article (1) defines hospital resilience; (2) constructs conceptual framework (including key domains); (3) proposes comprehensive measures for possible inclusion in an evaluation instrument, and; (4) develops a matrix of critical issues to enhance hospital resilience to cope with future disasters.

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The introduction of Systematized Nomenclature of Medicine - Clinical Terms (Snomed CT) for diagnosis coding in emergency departments (EDs) in New South Wales (NSW) has implications for injury surveillance abilities. This study aimed to assess the consequences of its introduction, as implemented as part of the ED information system in NSW, for identifying road trauma-related injuries in EDs. It involved a retrospective analysis of road trauma-related injuries identified in linked police, ED and mortality records during March 2007 to December 2009. Between 53.7% to 78.4% of all Snomed CT classifications in the principal provisional diagnosis field referred to the type of injury or symptom experienced by the individual. Of the road users identified by police, 3.2% of vehicle occupants, 6% of motorcyclists, 10.0% of pedal cyclists and 5.2% of pedestrians were identified using Snomed CT classifications in the principal provisional diagnosis field. The introduction of Snomed CT may provide flexible terminologies for clinicians. However, unless carefully implemented in information systems, its flexibility can lead to mismatches between the intention and actual use of defined data fields. Choices available in Snomed CT to indicate either symptoms, diagnoses, or injury mechanisms need to be controlled and these three concepts need to be retained in separate data fields to ensure a clear distinction between their classification in the ED.

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OBJECTIVE The study investigates the knowledge, intentions, and driving behavior of persons prescribed medications that display a warning about driving. It also examines their confidence that they can self-assess possible impairment, as is required by the Australian labeling system. METHOD We surveyed 358 outpatients in an Australian public hospital pharmacy, representing a well-advised group taking a range of medications including those displaying a warning label about driving. A brief telephone follow-up survey was conducted with a subgroup of the participants. RESULTS The sample had a median age of 53.2 years and was 53 percent male. Nearly three quarters (73.2%) had taken a potentially impairing class of medication and more than half (56.1%) had taken more than one such medication in the past 12 months. Knowledge of the potentially impairing effects of medication was relatively high for most items; however, participants underestimated the possibility of increased impairment from exceeding the prescribed dose and at commencing treatment. Participants' responses to the safety implications of taking drugs with the highest level of warning varied. Around two thirds (62.8%) indicated that they would consult a health practitioner for advice and around half would modify their driving in some way. However, one fifth (20.9%) would drive when the traffic was thought to be less heavy and over a third (37.7%) would modify their medication regime so that they could drive. The findings from the follow-up survey of a subsample taking target drugs at the time of the first interview were also of concern. Only just over half (51%) recalled seeing the warning label on their medications and, of this group, three quarters (78%) reported following the warning label advice. These findings indicated that there remains a large proportion of people who either did not notice or did not consider the warning when deciding whether to drive. There was a very high level of confidence in this group that they could determine whether they were personally affected by the medication, which may be a problem from a safety perspective. CONCLUSION This study involved persons who should have had a very high level of knowledge and awareness of medication warning labeling. Even in this group there was a lack of informed response to potential impairment. A review of the Australian warning system and wider dissemination of information on medication treatment effects would be useful. Clarifying the importance of potential risk in the general community context is recommended for consideration and further research.

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Hospital liability for alleged sexual assault upon a medicated patient by an orderly - non-delegable duty owed by a hospital to its patients - vicarious liability - liability for criminal conduct by employer - recruitment processes - assessment of damages.

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In 2008, Weeks et al. published the results of a postal survey, which explored the views of the Society of Hospital Pharmacists of Australia’s (SHPA) members on collaborative prescribing, and the extent of de facto prescribing in their institution. Since then, significant work has been undertaken on non-medical prescribing, such as pilots of pharmacist prescribing across Australia and a National Health Workforce report on developing a nationally consistent approach to prescribing by nonmedical health professionals. The first stage of the Health Workforce Australia Health Practitioner Prescribing Pathway project is complete and the recommendations for implementation have been approved by the Standing Council in November 2013. New Zealand pharmacists obtained prescribing rights in 2013, and the first cohort of 14 prescribers have completed the postgraduate pharmacist prescribing course (jointly run by the Otago and Auckland Universities).

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The aim of the current study was to examine the dimensions and reliability of a hospital safety climate questionnaire in Chinese health-care practice. To achieve this, a cross-sectional survey of health-care professionals was undertaken at a university teaching hospital in Shandong province, China. Our survey instrument demonstrated very high internal consistency, comparing well with previous research in this field conducted in other countries. Factor analysis highlighted four key dimensions of safety climate, which centred on employee personal protection, employee interactions, safetyrelated housekeeping and time pressures. Overall, this study suggests that hospital safety climate represents an important aspect of health-care practice in contemporary China.

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The aim of this research is to report initial experimental results and evaluation of a clinician-driven automated method that can address the issue of misdiagnosis from unstructured radiology reports. Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to disperse information resources and vast amounts of manual processing of unstructured information, a point-of-care accurate diagnosis is often difficult. A rule-based method that considers the occurrence of clinician specified keywords related to radiological findings was developed to identify limb abnormalities, such as fractures. A dataset containing 99 narrative reports of radiological findings was sourced from a tertiary hospital. The rule-based method achieved an F-measure of 0.80 and an accuracy of 0.80. While our method achieves promising performance, a number of avenues for improvement were identified using advanced natural language processing (NLP) techniques.

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This report describes the evaluation of the Refugee Antenatal Clinic (Mater Mothers' Hospital, Brisbane) which was established in November 2008

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Background Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. Aims The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. Method A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. Results The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. Conclusion While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.

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Objectives: To report the quarterly incidence of hospital-identified Clostridium difficile infection (HI-CDI) in Australia, and to estimate the burden ascribed to hospital-associated (HA) and community-associated (CA) infections. Design, setting and patients: Prospective surveillance of all cases of CDI diagnosed in hospital patients from 1 January 2011 to 31 December 2012 in 450 public hospitals in all Australian states and the Australian Capital Territory. All patients admitted to inpatient wards or units in acute public hospitals, including psychiatry, rehabilitation and aged care, were included, as well as those attending emergency departments and outpatient clinics. Main outcome measures: Incidence of HI-CDI (primary outcome); proportion and incidence of HA-CDI and CA-CDI (secondary outcomes). Results: The annual incidence of HI-CDI increased from 3.25/10 000 patient-days (PD) in 2011 to 4.03/10 000 PD in 2012. Poisson regression modelling demonstrated a 29% increase (95% CI, 25% to 34%) per quarter between April and December 2011, with a peak of 4.49/10 000 PD in the October–December quarter. The incidence plateaued in January–March 2012 and then declined by 8% (95% CI, − 11% to − 5%) per quarter to 3.76/10 000 PD in July–September 2012, after which the rate rose again by 11% (95% CI, 4% to 19%) per quarter to 4.09/10 000 PD in October–December 2012. Trends were similar for HA-CDI and CA-CDI. A subgroup analysis determined that 26% of cases were CA-CDI. Conclusions: A significant increase in both HA-CDI and CA-CDI identified through hospital surveillance occurred in Australia during 2011–2012. Studies are required to further characterise the epidemiology of CDI in Australia.

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There are limited studies that describe patient meal preferences in hospital; however this data is critical to develop menus that address satisfaction and nutrition whilst balancing resources. This quality study aimed to determine preferences for meals and snacks to inform a comprehensive menu revision in a large (929 bed) tertiary public hospital. The method was based on Vivanti et al. (2008) with data collected by two final year dietetic students. The first survey comprised 72 questions, achieved a response rate of 68% (n = 192), with the second more focused at 47 questions achieving a higher response rate of 93% (n = 212). Findings showed over half the patients reporting poor or less than normal appetite, 20% describing taste issues, over a third with a LOS >7 days, a third with a MST _ 2 and less than half eating only from the general menu. Soup then toast was most frequently reported as eaten at home when unwell, and whilst most reported not missing any foods when in hospital (25%), steak was most commonly missed. Hot breakfasts were desired by the majority (63%), with over half preferring toast (even if cold). In relation to snacks, nearly half (48%) wanted something more substantial than tea/coffee/biscuits, with sandwiches (54%) and soup (33%) being suggested. Sandwiches at the evening meal were not popular (6%). Difficulties with using cutlery and meal size selection were identified as issues. Findings from this study had high utility and supported a collaborative and evidenced based approach to a successful major menu change for the hospital.

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Information on foods patients like and dislike is the essential basis for planning menus which are acceptable to patients and promote adequate consumption. The aim of this study was to obtain quantitative data on the food preferences of inpatients at a large metropolitan public hospital for use in menu planning. Methodology was based on a study by Williams et al (1988), and included additional questions about appetite and taste changes. The survey used a 9 point hedonic scale to rate foods listed in random order and was modified to incorporate more contemporary foods than those used in the originalWilliams study. Surveys were conducted by final year University of Queensland dietetics students on Food Service Practicum at the Royal Brisbane and Women’s Hospital (929 beds) in 2012. The first survey (220 questions, n = 157) had a response rate of 61%. The second included more sandwich fillings and salads (231 questions, n = 219, response rate 67%). Total number surveyed was 376. Results showed the most preferred foods were roast potato, grilled steak, ice cream, fresh strawberries, roast lamb, roast beef, grapes and banana. The least preferred foods were grapefruit, soybeans, lentils, sardines, prune juice and grapefruit juice. Patients who reported taste changes (10%) had similar food preferences to those who didn’t report taste changes. Patients who reported poor/very poor appetite (10%) generally scored foods lower than those who reported OK (22%), good/very good appetite (65%). The results of this study informed planning for a new patient menu at the RBWH in December 2012.

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Objectives: To i) identify predictors of admission, and ii) describe outcomes for patients who arrived via ambulance to three Australian public Emergency Departments (EDs), before and after the opening of 41 additional ED beds within the area. Methods: A retrospective, comparative, cohort study using deterministically linked health data collected between 3 September 2006 and 2 September 2008. Data included ambulance offload delay, time to see doctor, ED length of stay (ED LOS), admission requirement, access block, hospital length of stay and in-hospital mortality. Logistic regression analysis was undertaken to identify predictors of hospital admission. Results: One third of all 286,037 ED presentations were via ambulance (n= 79,196) and 40.3% required admission. After increasing emergency capacity, the only outcome measure to improve was in-hospital mortality. Ambulance offload delay, time to see doctor, ED length of stay (ED LOS), admission requirement, access block, hospital length of stay did not improve. Strong predictors of admission before and after increased capacity included: age over 65 years, Australian Triage Scale (ATS) category 1-3, diagnoses of circulatory or respiratory conditions and ED LOS > 4 hours. With additional capacity the odds ratios for these predictors increased for age >65 and ED LOS > 4 hours and decreased for triage category and ED diagnoses. Conclusions: Expanding ED capacity from 81 to 122 beds within a health service area impacted favourably on mortality outcomes but not on time-related service outcomes such as ambulance offload time, time to see doctor and ED LOS. To improve all service outcomes, when altering (increasing/decreasing) ED bed numbers, the whole healthcare system needs to be considered.