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        Prediction of mortality 1 year after hospital admission.

        Kellett, J; Rasool, S; McLoughlin, B; Department of Medicine, Nenagh Hospital, Nenagh, County Tipperary, Ireland. jgkellett@eircom.net (2012-09)
        Hospital admission, especially for the elderly, can be a seminal event as many patients die within a year. This study reports the prediction of death within a year of admission to hospital of the Simple Clinical Score (SCS) and ECG dispersion mapping (ECG-DM). ECG-DM is a novel technique that analyzes low-amplitude ECG oscillations and reports them as the myocardial micro-alternation index (MMI).
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        The prediction of the in-hospital mortality of acutely ill medical patients by electrocardiogram (ECG) dispersion mapping compared with established risk factors and predictive scores--a pilot study.

        Kellett, John; Rasool, Shahzeb; Department of Medicine, Nenagh Hospital, Nenagh, County Tipperary, Ireland. jgkellett@eircom.net (2011-08)
        ECG dispersion mapping (ECG-DM) is a novel technique that analyzes low amplitude ECG oscillations and reports them as the myocardial micro-alternation index (MMI). This study compared the ability of ECG-DM to predict in-hospital mortality with traditional risk factors such as age, vital signs and co-morbid diagnoses, as well as three predictive scores: the Simple Clinical Score (SCS)--based on clinical and ECG findings, and two Medical Admission Risk System scores--one based on vital signs and laboratory data (MARS), and one only on laboratory data (LD).
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        Quality improvement plans based on the recommendation by HIQA Report following unannounced focused monitoring assessment at the UL Hospital, Nenagh Hospital on 5th September 2013.

        Dunne, Suzanne; Ryan, Cathrina; Ryan, Louise; Slevin, Barbara; Smith, Siobhain; Brennan, Philip; Casey, Liam; Murphy, Paula Cussen (Health Service Executive (HSE), 2013-11)
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        READS: the rapid electronic assessment documentation system.

        Hickey, Ann; Gleeson, Margaret; Kellett, John; Nenagh Hospital, Nenagh, Ireland. (2012-12-13)
        Patient documentation is time consuming and can detract from care. The authors report a novel computer programme that manipulates routinely collected information to quantify nursing workload, along with the reason for admission, functional status, estimates of in-hospital mortality and life expectancy. The programme stores information in a database, and produces a print-out in a situation/background/assessment/recommendation (SBAR) format. The average time taken to enter 629 patient encounters was 6.6 minutes. Pain was the most common presentation for low workload patients, while high workload patients often presented with altered mental status and reduced mobility. There was only a modest correlation between the risk of death and nursing workload. The programme measures nursing workload without further paperwork, and improves routine documentation with a legible brief report that is automatically generated. This report can be shared and provides data that is immediately available for day-to-day care, audit, quality control and service planning.
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        Should systematic risk assessment and immediate intervention of the acutely ill patient replace the traditional management paradigm?

        Kellett, John; Department of Medicine, Nenagh Hospital, Nenagh, County Tipperary, Ireland. jgkellett@eircom.net (2012)
        The outcome of the traditional diagnostic history and physical depends entirely on the availability, ability and diligence of an individual doctor. An alternative is a team-based approach that performs the following tasks: a focused assessment, monitoring of the response to initial treatment, and then determining what further management is appropriate (calling for urgent help if it is required). This concept is based on risk prediction rather than diagnosis, and is captured by the mnemonic FAITH3 (Focused Assessment, Initial Treatment, hAssessing response, calling for Help and Handing over care).
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        Validation of an abbreviated Vitalpac™ Early Warning Score (ViEWS) in 75,419 consecutive admissions to a Canadian regional hospital.

        Kellett, John; Kim, Arnold; Department of Medicine, Nenagh Hospital, Nenagh, County Tipperary, Ireland. jgkellett@eircom.net (2012-03)
        The early warning score derived from 198,755 vital sign sets in the Vitalpac™ database (ViEWS) has an area under the receiver operator characteristic curve (AUROC) for death of acute unselected medical patients within 24h of 88%.
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        What diagnoses may make patients more seriously ill than they first appear? Mortality according to the Simple Clinical Score Risk Class at the time of admission compared to the observed mortality of different ICD9 codes identified on death or discharge.

        Kellett, John; Deane, Breda; Department of Medicine, Nenagh Hospital, Nenagh, County Tipperary, Ireland. jgkellett@eircom.net (2009-01)
        The Simple Clinical Score (SCS) determined at the time of admission places acutely ill general medical patients into one of five risk classes associated with an increasing risk of death within 30 days. The cohort of acute medical patient that the SCS was derived from had, on average, four combinations of 74 groupings of ICD9 codes. This paper reports the ICD9 codes associated with the different SCS risk classes and identifies those ICD9 codes with a greater observed mortality than that of other patients in the same SCS risk class.
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        Who will be sicker in the morning? Changes in the Simple Clinical Score the day after admission and the subsequent outcomes of acutely ill unselected medical patients.

        Kellett, John; Emmanuel, Andrew; Deane, Breda; Department of Medicine, Nenagh Hospital, Nenagh, County Tipperary, Ireland. jgkellett@eircom.net (2011-08)
        All doctors are haunted by the possibility that a patient they reassured yesterday will return seriously ill tomorrow. We examined changes in the Simple Clinical Score (SCS) the day after admission, factors that might influence these changes and the relationship of these changes to subsequent clinical outcome.
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        Why should clinicians design robots? Expediating stroke recovery with a wearable robot [Poster]

        Thangaramanujam, Muthukumaran; Nenagh Primary Care Team, HSE West, Nenagh General Hospital, Nenagh, Co. Tipperary (Health Service Executive (HSE), 2012)
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