33,028 research outputs found

    Design and usage of the HeartCycle education and coaching program for patients with heart failure

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    Background: Heart failure (HF) is common, and it is associated with high rates of hospital readmission and mortality. It is generally assumed that appropriate self-care can improve outcomes in patients with HF, but patient adherence to many self-care behaviors is poor. Objective: The objective of our study was to develop and test an intervention to increase self-care in patients with HF using a novel, online, automated education and coaching program. Methods: The online automated program was developed using a well-established, face-to-face, home-based cardiac rehabilitation approach. Education is tailored to the behaviors and knowledge of the individual patient, and the system supports patients in adopting self-care behaviors. Patients are guided through a goal-setting process that they conduct at their own pace through the support of the system, and they record their progress in an electronic diary such that the system can provide appropriate feedback. Only in challenging situations do HF nurses intervene to offer help. The program was evaluated in the HeartCycle study, a multicenter, observational trial with randomized components in which researchers investigated the ability of a third-generation telehealth system to enhance the management of patients with HF who had a recent (<60 days) admission to the hospital for symptoms or signs of HF (either new onset or recurrent) or were outpatients with persistent New York Heart Association (NYHA) functional class III/IV symptoms despite treatment with diuretic agents. The patients were enrolled from January 2012 through February 2013 at 3 hospital sites within the United Kingdom, Germany, and Spain. Results: Of 123 patients enrolled (mean age 66 years (SD 12), 66% NYHA III, 79% men), 50 patients (41%) reported that they were not physically active, 56 patients (46%) did not follow a low-salt diet, 6 patients (5%) did not restrict their fluid intake, and 6 patients (5%) did not take their medication as prescribed. About 80% of the patients who started the coaching program for physical activity and low-salt diet became adherent by achieving their personal goals for 2 consecutive weeks. After becoming adherent, 61% continued physical activity coaching, but only 36% continued low-salt diet coaching. Conclusions: The HeartCycle education and coaching program helped most nonadherent patients with HF to adopt recommended self-care behaviors. Automated coaching worked well for most patients who started the coaching program, and many patients who achieved their goals continued to use the program. For many patients who did not engage in the automated coaching program, their choice was appropriate rather than a failure of the program

    Deep Neural Networks for ECG-Based Pulse Detection during Out-of-Hospital Cardiac Arrest

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    The automatic detection of pulse during out-of-hospital cardiac arrest (OHCA) is necessary for the early recognition of the arrest and the detection of return of spontaneous circulation (end of the arrest). The only signal available in every single defibrillator and valid for the detection of pulse is the electrocardiogram (ECG). In this study we propose two deep neural network (DNN) architectures to detect pulse using short ECG segments (5 s), i.e., to classify the rhythm into pulseless electrical activity (PEA) or pulse-generating rhythm (PR). A total of 3914 5-s ECG segments, 2372 PR and 1542 PEA, were extracted from 279 OHCA episodes. Data were partitioned patient-wise into training (80%) and test (20%) sets. The first DNN architecture was a fully convolutional neural network, and the second architecture added a recurrent layer to learn temporal dependencies. Both DNN architectures were tuned using Bayesian optimization, and the results for the test set were compared to state-of-the art PR/PEA discrimination algorithms based on machine learning and hand crafted features. The PR/PEA classifiers were evaluated in terms of sensitivity (Se) for PR, specificity (Sp) for PEA, and the balanced accuracy (BAC), the average of Se and Sp. The Se/Sp/BAC of the DNN architectures were 94.1%/92.9%/93.5% for the first one, and 95.5%/91.6%/93.5% for the second one. Both architectures improved the performance of state of the art methods by more than 1.5 points in BAC.This work was supported by: The Spanish Ministerio de Economía y Competitividad, TEC2015-64678-R, jointly with the Fondo Europeo de Desarrollo Regional (FEDER), UPV/EHU via GIU17/031 and the Basque Government through the grant PRE_2018_2_0260

    Measuring patient-perceived quality of care in US hospitals using Twitter

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    BACKGROUND: Patients routinely use Twitter to share feedback about their experience receiving healthcare. Identifying and analysing the content of posts sent to hospitals may provide a novel real-time measure of quality, supplementing traditional, survey-based approaches. OBJECTIVE: To assess the use of Twitter as a supplemental data stream for measuring patient-perceived quality of care in US hospitals and compare patient sentiments about hospitals with established quality measures. DESIGN: 404 065 tweets directed to 2349 US hospitals over a 1-year period were classified as having to do with patient experience using a machine learning approach. Sentiment was calculated for these tweets using natural language processing. 11 602 tweets were manually categorised into patient experience topics. Finally, hospitals with ≥50 patient experience tweets were surveyed to understand how they use Twitter to interact with patients. KEY RESULTS: Roughly half of the hospitals in the US have a presence on Twitter. Of the tweets directed toward these hospitals, 34 725 (9.4%) were related to patient experience and covered diverse topics. Analyses limited to hospitals with ≥50 patient experience tweets revealed that they were more active on Twitter, more likely to be below the national median of Medicare patients (p<0.001) and above the national median for nurse/patient ratio (p=0.006), and to be a non-profit hospital (p<0.001). After adjusting for hospital characteristics, we found that Twitter sentiment was not associated with Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) ratings (but having a Twitter account was), although there was a weak association with 30-day hospital readmission rates (p=0.003). CONCLUSIONS: Tweets describing patient experiences in hospitals cover a wide range of patient care aspects and can be identified using automated approaches. These tweets represent a potentially untapped indicator of quality and may be valuable to patients, researchers, policy makers and hospital administrators

    A pilot randomised controlled trial of an internet-based cognitive behavioural therapy self-management programme (MS Invigor8) for multiple sclerosis fatigue

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    The majority of people affected by Multiple Sclerosis (PaMS) experience severe and disabling fatigue. MS Fatigue is poorly understood and most existing treatments have limited effectiveness. However, a recent randomised controlled trial (RCT) showed that cognitive-behaviour therapy with a clinical psychologist was effective in reducing MS fatigue severity and impact. The current study developed an Internet-based version of this intervention to make it available to a wider group of PaMS and conducted preliminary investigations of its efficacy, feasibility and cost-effectiveness in a pilot RCT. The ‘MS Invigor8’ website was developed using agile design and substantial input from PaMS. The programme includes eight online tailored and interactive sessions along with homework tasks, intended to be accessed weekly. In the pilot trial, 40 patients were randomised to MS Invigor8 (n=23) or standard care (n=17). The MS Invigor8 group accessed sessions over 8-10 weeks and received up to three 30-50 minute telephone support sessions. Participants completed online questionnaires assessing fatigue, mood and quality of life at baseline and 10 weeks follow-up. Large between group treatment effects were found for the primary outcomes of fatigue severity (d=1.19) and impact (d =1.22). The MS Invigor8 group also reported significantly greater improvements in anxiety and depression. Analysis suggested that the intervention may be cost-effective. Qualitative feedback suggested that participants considered this treatment approach acceptable and helpful. Technical website problems negatively affected some users’ experiences and need to be resolved. Given the promising results a larger RCT with longer term follow-up is warranted. <br/

    A novel tool for organisational learning and its impact on safety culture in a hospital dispensary

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    Incident reporting as a key mechanism for organisational learning and the establishment of a stronger safety culture are pillars of the current patient safety movement. Studies have suggested that incident reporting in healthcare does not achieve its full potential due to serious barriers to reporting and that sometimes staff may feel alienated by the process. The aim of the work reported in this paper was to prototype a novel approach to organisational learning that allows an organisation to assess and to monitor the status of processes that often give rise to latent failure conditions in the work environment, and to assess whether and through which mechanisms participation in this approach affects local safety culture. The approach was prototyped in a hospital dispensary using Plan-Do-Study-Act (PDSA) cycles, and the effect on safety culture was described qualitatively through semi-structured interviews. The results suggest that the approach has had a positive effect on the safety culture within the dispensary, and that staff perceive the approach to be useful and usable
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