18 research outputs found

    Case of carbon monoxide poisoning after smoking shisha

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    Carbon monoxide poisoning has been reported as a result of exposure to various sources of smoke, such as car exhaust fumes, home water heaters and tobacco smoke. We describe a case of symptomatic, moderately severe carbon monoxide (CO) poisoning in a young Mediterranean man after smoking a waterpipe, or shisha. This case highlights the importance of considering carbon monoxide exposure in patients presenting with non-specific neurological symptoms to the emergency department (ED)

    Pandemic (H1N1) 2009 Surveillance and Prevalence of Seasonal Influenza, Singapore

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    On April 25, 2009, Singapore implemented strict containment measures for pandemic (H1N1) 2009 with enhanced surveillance and hospital isolation. In the first month, seasonal influenza, predominantly virus subtype H3N2, was diagnosed for 32% of patients with acute febrile respiratory illness. Our findings underscore the high prevalence of seasonal influenza in Singapore

    Forecasting daily attendances at an emergency department to aid resource planning

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    <p>Abstract</p> <p>Background</p> <p>Accurate forecasting of emergency department (ED) attendances can be a valuable tool for micro and macro level planning.</p> <p>Methods</p> <p>Data for analysis was the counts of daily patient attendances at the ED of an acute care regional general hospital from July 2005 to Mar 2008. Patients were stratified into three acuity categories; i.e. P1, P2 and P3, with P1 being the most acute and P3 being the least acute. The autoregressive integrated moving average (ARIMA) method was separately applied to each of the three acuity categories and total patient attendances. Independent variables included in the model were public holiday (yes or no), ambient air quality measured by pollution standard index (PSI), daily ambient average temperature and daily relative humidity. The seasonal components of weekly and yearly periodicities in the time series of daily attendances were also studied. Univariate analysis by t-tests and multivariate time series analysis were carried out in SPSS version 15.</p> <p>Results</p> <p>By time series analyses, P1 attendances did not show any weekly or yearly periodicity and was only predicted by ambient air quality of PSI > 50. P2 and total attendances showed weekly periodicities, and were also significantly predicted by public holiday. P3 attendances were significantly correlated with day of the week, month of the year, public holiday, and ambient air quality of PSI > 50.</p> <p>After applying the developed models to validate the forecast, the MAPE of prediction by the models were 16.8%, 6.7%, 8.6% and 4.8% for P1, P2, P3 and total attendances, respectively. The models were able to account for most of the significant autocorrelations present in the data.</p> <p>Conclusion</p> <p>Time series analysis has been shown to provide a useful, readily available tool for predicting emergency department workload that can be used to plan staff roster and resource planning.</p

    Female trauma patients in the emergency department: should their injury prevention programme be different?

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    Background: (1) To compare the characteristics of female and male trauma patients seen in the Emergency Department (ED) and (2) to determine if injury prevention programmes for women should be different. Methods: A prospective survey was conducted for 11544 trauma patients, aged 15 years and above, who presented to the ED of an urban public hospital in Singapore over 6 months. The following data were collected: demography, place, type and mechanism of injury and subsequent disposition from the ED. Results: Almost half (49.5%) the injuries sustained by females occurred at home, with low falls of less than 2 metres being the most common mechanism of injury (52.7%). Victims of domestic violence were predominantly female at p&lt;0.0001

    Applying Andersen's healthcare utilization model to assess factors influencing patients' expectations for diagnostic tests at emergency department visits during the COVID-19 pandemic

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    BackgroundThe uncertainties surrounding the COVID-19 pandemic led to a surge in non-urgent emergency department (ED) attendance among people presenting with upper respiratory tract infection (URTI) symptoms. These non-urgent visits, often manageable in primary care, exacerbated ED overcrowding, which could compromise the quality of ED services. Understanding patients' expectations and the reasons for these ED visits is imperative to mitigate the problem of ED overcrowding. Hence, we assessed the factors influencing patients' expectations for diagnostic tests during their ED visits for uncomplicated URTI during different phases of the pandemic.MethodsWe conducted a cross-sectional study on adults with URTI symptoms seeking care at four public EDs in Singapore between March 2021 and March 2022. We segmented the study period into three COVID-19 pandemic phases—containment, transition, and mitigation. The outcome variables are whether patients expected (1) a COVID-19-specific diagnostic test, (2) a non-COVID-19-specific diagnostic test, (3) both COVID-19-specific and non-COVID-19-specific diagnostic tests, or (4) no diagnostic test. We built a multinomial regression model with backward stepwise selection and classified the findings according to Andersen's healthcare utilization model.ResultsThe mean age of participants was 34.5 (12.7) years. Factors (adjusted odds ratio [95% confidence interval]) influencing expectations for a COVID-19-specific diagnostic test in the ED include younger age {21–40 years: (2.98 [1.04–8.55])}, no prior clinical consultation (2.10 [1.13–3.89]), adherence to employer's health policy (3.70 [1.79–7.67]), perceived non-severity of illness (2.50 [1.39–4.55]), being worried about contracting COVID-19 (2.29 [1.11–4.69]), and during the transition phase of the pandemic (2.29 [1.15–4.56]). Being non-employed influenced the expectation for non-COVID-19-specific diagnostic tests (3.83 [1.26–11.66]). Factors influencing expectations for both COVID-19-specific and non-COVID-19-specific tests include younger age {21–40 years: (3.61 [1.26–10.38]); 41–60 years: (4.49 [1.43–14.13])}, adherence to employer's health policy (2.94 [1.41–6.14]), being worried about contracting COVID-19 (2.95 [1.45– 5.99]), and during the transition (2.03 [1.02–4.06]) and mitigation (2.02 [1.03–3.97]) phases of the pandemic.ConclusionPatients' expectations for diagnostic tests during ED visits for uncomplicated URTI were dynamic across the COVID-19 pandemic phases. Expectations for COVID-19-specific diagnostic tests for ED visits for uncomplicated URTI were higher among younger individuals and those worried about contracting COVID-19 during the COVID-19 pandemic. Future studies are required to enhance public communications on the availability of diagnostic services in primary care and public education on self-management of emerging infectious diseases such as COVID-19

    Exploring if day and time of admission is associated with average length of stay among inpatients from a tertiary hospital in Singapore: an analytic study based on routine admission data.

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    BACKGROUND: It has been postulated that patients admitted on weekends or after office hours may experience delays in clinical management and consequently have longer length of stay (LOS). We investigated if day and time of admission is associated with LOS in Tan Tock Seng Hospital (TTSH), a 1,400 bed acute care tertiary hospital serving the central and northern regions of Singapore. METHODS: This was a historical cohort study based on all admissions from TTSH from 1st September 2003 to 31st August 2004. Data was extracted from routinely available computerized hospital information systems for analysis by episode of care. LOS for each episode of care was log-transformed before analysis, and a multivariate linear regression model was used to study if sex, age group, type of admission, admission source, day of week admitted, admission on a public holiday or eve of public holiday, admission on a weekend and admission time were associated with an increased LOS. RESULTS: In the multivariate analysis, sex, age group, type of admission, source of admission, admission on the eve of public holiday and weekends and time of day admitted were independently and significantly associated with LOS. Patients admitted on Friday, Saturday or Sunday stayed on average 0.3 days longer than those admitted on weekdays, after adjusting for potential confounders; those admitted on the eve of public holidays, and those admitted in the afternoons and after office hours also had a longer LOS (differences of 0.71, 1.14 and 0.65 days respectively). CONCLUSION: Cases admitted over a weekend, eve of holiday, in the afternoons, and after office hours, do have an increased LOS. Further research is needed to identify processes contributing to the above phenomenon
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