86 research outputs found

    Code Status Discussions Between Attending Hospitalist Physicians and Medical Patients at Hospital Admission

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    BackgroundBioethicists and professional associations give specific recommendations for discussing cardiopulmonary resuscitation (CPR).ObjectiveTo determine whether attending hospitalist physicians' discussions meet these recommendations.DesignCross-sectional observational study on the medical services at two hospitals within a university system between August 2008 and March 2009.ParticipantsAttending hospitalist physicians and patients who were able to communicate verbally about their medical care.Main measuresWe identified code status discussions in audio-recorded admission encounters via physician survey and review of encounter transcripts. A quantitative content analysis was performed to determine whether discussions included elements recommended by bioethicists and professional associations. Two coders independently coded all discussions; Cohen's kappa was 0.64-1 for all reported elements.Key resultsAudio-recordings of 80 patients' admission encounters with 27 physicians were obtained. Eleven physicians discussed code status in 19 encounters. Discussions were more frequent in seriously ill patients (OR 4, 95% CI 1.2-14.6), yet 66% of seriously ill patients had no discussion. The median length of the code status discussions was 1 min (range 0.2-8.2). Prognosis was discussed with code status in only one of the encounters. Discussions of patients' preferences focused on the use of life-sustaining interventions as opposed to larger life goals. Descriptions of CPR as an intervention used medical jargon, and the indication for CPR was framed in general, as opposed to patient-specific scenarios. No physician quantitatively estimated the outcome of or provided a recommendation about the use of CPR.ConclusionsCode status was not discussed with many seriously ill patients. Discussions were brief, and did not include elements that bioethicists and professional associations recommend to promote patient autonomy. Local and national guidelines, research, and clinical practice changes are needed to clarify and systematize with whom and how CPR is discussed at hospital admission

    Natriuretic peptide vs. clinical information for diagnosis of left ventricular systolic dysfunction in primary care

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    <p>Abstract</p> <p>Background</p> <p>Screening of primary care patients at risk for left ventricular systolic dysfunction by a simple blood-test might reduce referral rates for echocardiography. Whether or not natriuretic peptide testing is a useful and cost-effective diagnostic instrument in primary care settings, however, is still a matter of debate.</p> <p>Methods</p> <p>N-terminal pro-brain natriuretic peptide (NT-proBNP) levels, clinical information, and echocardiographic data of left ventricular systolic function were collected in 542 family practice patients with at least one cardiovascular risk factor. We determined the diagnostic power of the NT-proBNP assessment in ruling out left ventricular systolic dysfunction and compared it to a risk score derived from a logistic regression model of easily acquired clinical information.</p> <p>Results</p> <p>23 of 542 patients showed left ventricular systolic dysfunction. Both NT-proBNP and the clinical risk score consisting of dyspnea at exertion and ankle swelling, coronary artery disease and diuretic treatment showed excellent diagnostic power for ruling out left ventricular systolic dysfunction. AUC of NT-proBNP was 0.83 (95% CI, 0.75 to 0.92) with a sensitivity of 0.91 (95% CI, 0.71 to 0.98) and a specificity of 0.46 (95% CI, 0.41 to 0.50). AUC of the clinical risk score was 0.85 (95% CI, 0.79 to 0.91) with a sensitivity of 0.91 (95% CI, 0.71 to 0.98) and a specificity of 0.64 (95% CI, 0.59 to 0.67). 148 misclassifications using NT-proBNP and 55 using the clinical risk score revealed a significant difference (McNemar test; p < 0.001) that was based on the higher specificity of the clinical risk score.</p> <p>Conclusion</p> <p>The evaluation of clinical information is at least as effective as NT-proBNP testing in ruling out left ventricular systolic dysfunction in family practice patients at risk. If these results are confirmed in larger cohorts and in different samples, family physicians should be encouraged to rely on the diagnostic power of the clinical information from their patients.</p

    An ontology-based nurse call management system (oNCS) with probabilistic priority assessment

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    <p>Abstract</p> <p>Background</p> <p>The current, place-oriented nurse call systems are very static. A patient can only make calls with a button which is fixed to a wall of a room. Moreover, the system does not take into account various factors specific to a situation. In the future, there will be an evolution to a mobile button for each patient so that they can walk around freely and still make calls. The system would become person-oriented and the available context information should be taken into account to assign the correct nurse to a call.</p> <p>The aim of this research is (1) the design of a software platform that supports the transition to mobile and wireless nurse call buttons in hospitals and residential care and (2) the design of a sophisticated nurse call algorithm. This algorithm dynamically adapts to the situation at hand by taking the profile information of staff members and patients into account. Additionally, the priority of a call probabilistically depends on the risk factors, assigned to a patient.</p> <p>Methods</p> <p>The <it>ontology-based Nurse Call System (oNCS) </it>was developed as an extension of a <it>Context-Aware Service Platform</it>. An ontology is used to manage the profile information. Rules implement the novel nurse call algorithm that takes all this information into account. Probabilistic reasoning algorithms are designed to determine the priority of a call based on the risk factors of the patient.</p> <p>Results</p> <p>The <it>oNCS </it>system is evaluated through a prototype implementation and simulations, based on a detailed dataset obtained from Ghent University Hospital. The arrival times of nurses at the location of a call, the workload distribution of calls amongst nurses and the assignment of priorities to calls are compared for the <it>oNCS </it><it>system </it>and the current, place-oriented nurse call system. Additionally, the performance of the system is discussed.</p> <p>Conclusions</p> <p>The execution time of the nurse call algorithm is on average 50.333 ms. Moreover, the <it>oNCS system </it>significantly improves the assignment of nurses to calls. Calls generally have a nurse present faster and the workload-distribution amongst the nurses improves.</p
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