Telemonitoring after discharge from hospital with heart failure: cost-effectiveness modelling of alternative service designs.

Objectives To estimate the cost-effectiveness of remote monitoring strategies versus usual care for adults recently discharged after a heart failure (HF) exacerbation. Design Decision analysis modelling of cost-effectiveness using secondary data sources. Setting Acute hospitals in the UK. Patients Patients recently discharged (within 28 days) after a HF exacerbation. Interventions Structured telephone support (STS) via human to machine (STS HM) interface, (2) STS via human to human (STS HH) contact and (3) home telemonitoring (TM), compared with (4) usual care. Main outcome measures The incremental cost per quality-adjusted life year (QALY) gained by each strategy compared to the next most effective alternative and the probability of each strategy being cost-effective at varying willingness to pay per QALY gained. Results TM was the most cost-effective strategy in the scenario using these base case costs. Compared with usual care, TM had an estimated incremental cost effectiveness ratio (ICER) of £11 873/QALY, whereas STS HH had an ICER of £228 035/QALY against TM. STS HM was dominated by usual care. Threshold analysis suggested that the monthly cost of TM has to be higher than £390 to have an ICER greater than £20 000/QALY against STS HH. Scenario analyses performed using higher costs of usual care, higher costs of STS HH and lower costs of TM do not substantially change the conclusions. Conclusions Cost-effectiveness analyses suggest that TM was an optimal strategy in most scenarios, but there is considerable uncertainty in relation to clear descriptions of the interventions and robust estimation of costs

Prognostic value of psychosocial factors for first and recurrent hospitalizations and mortality in heart failure patients: insights from the OPERA-HF study

Aims: Psychosocial factors are rarely collected in studies investigating the prognosis of patients with heart failure (HF), and only time to first-event is commonly reported. We investigated the prognostic value of psychosocial factors for predicting first or recurrent events after discharge following hospitalization for HF. Methods and results: OPERA-HF is an observational study enrolling patients hospitalized for HF. In addition to clinical variables, psychosocial variables are recorded. Patients provide the information through questionnaires which include social information, depression and anxiety scores, and cognitive function. Kaplan-Meier, Cox regression and the Andersen-Gill model were used to identify predictors of first and recurrent events (re-admissions or death). Of 671 patients (age 76±15 years, 66% men) with one-year follow-up, 291 had no subsequent event, 34 died without being readmitted, 346 had one or more unplanned readmissions and 71 patients died after a first readmission. Increasing age, higher urea and creatinine, the presence of co-morbidities (diabetes, history of MI, COPD), were all associated with increasing risk of first or recurrent event. Psychosocial variables independently associated with both the first and recurrent events were: presence of frailty, moderate to severe depression and moderate to severe anxiety. Living alone and the presence of cognitive impairment were independently associated only with an increasing risk of recurrent events. Conclusion: Psychosocial factors are strongly associated with unplanned recurrent readmissions or mortality following an admission to hospital for HF. Further research is needed to show whether recognition of these factors and support tailored to individual patients’ needs will improve outcomes

Implantable cardioverter defibrillators for the treatment of arrhythmias and cardiac resynchronisation therapy for the treatment of heart failure: systematic review and economic evaluation

Background This assessment updates and expands on two previous technology assessments that evaluated implantable cardioverter defibrillators (ICDs) for arrhythmias and cardiac resynchronisation therapy (CRT) for heart failure (HF). Objectives To assess the clinical effectiveness and cost-effectiveness of ICDs in addition to optimal pharmacological therapy (OPT) for people at increased risk of sudden cardiac death (SCD) as a result of ventricular arrhythmias despite receiving OPT; to assess CRT with or without a defibrillator (CRT-D or CRT-P) in addition to OPT for people with HF as a result of left ventricular systolic dysfunction (LVSD) and cardiac dyssynchrony despite receiving OPT; and to assess CRT-D in addition to OPT for people with both conditions. Data sources Electronic resources including MEDLINE, EMBASE and The Cochrane Library were searched from inception to November 2012. Additional studies were sought from reference lists, clinical experts and manufacturers’ submissions to the National Institute for Health and Care Excellence. Review methods Inclusion criteria were applied by two reviewers independently. Data extraction and quality assessment were undertaken by one reviewer and checked by a second. Data were synthesised through narrative review and meta-analyses. For the three populations above, randomised controlled trials (RCTs) comparing (1) ICD with standard therapy, (2) CRT-P or CRT-D with each other or with OPT and (3) CRT-D with OPT, CRT-P or ICD were eligible. Outcomes included mortality, adverse events and quality of life. A previously developed Markov model was adapted to estimate the cost-effectiveness of OPT, ICDs, CRT-P and CRT-D in the three populations by simulating disease progression calculated at 4-weekly cycles over a lifetime horizon. Results A total of 4556 references were identified, of which 26 RCTs were included in the review: 13 compared ICD with medical therapy, four compared CRT-P/CRT-D with OPT and nine compared CRT-D with ICD. ICDs reduced all-cause mortality in people at increased risk of SCD, defined in trials as those with previous ventricular arrhythmias/cardiac arrest, myocardial infarction (MI) > 3 weeks previously, non-ischaemic cardiomyopathy (depending on data included) or ischaemic/non-ischaemic HF and left ventricular ejection fraction ≤ 35%. There was no benefit in people scheduled for coronary artery bypass graft. A reduction in SCD but not all-cause mortality was found in people with recent MI. Incremental cost-effectiveness ratios (ICERs) ranged from £14,231 per quality-adjusted life-year (QALY) to £29,756 per QALY for the scenarios modelled. CRT-P and CRT-D reduced mortality and HF hospitalisations, and improved other outcomes, in people with HF as a result of LVSD and cardiac dyssynchrony when compared with OPT. The rate of SCD was lower with CRT-D than with CRT-P but other outcomes were similar. CRT-P and CRT-D compared with OPT produced ICERs of £27,584 per QALY and £27,899 per QALY respectively. The ICER for CRT-D compared with CRT-P was £28,420 per QALY. In people with both conditions, CRT-D reduced the risk of all-cause mortality and HF hospitalisation, and improved other outcomes, compared with ICDs. Complications were more common with CRT-D. Initial management with OPT alone was most cost-effective (ICER £2824 per QALY compared with ICD) when health-related quality of life was kept constant over time. Costs and QALYs for CRT-D and CRT-P were similar. The ICER for CRT-D compared with ICD was £27,195 per QALY and that for CRT-D compared with OPT was £35,193 per QALY. Limitations Limitations of the model include the structural assumptions made about disease progression and treatment provision, the extrapolation of trial survival estimates over time and the assumptions made around parameter values when evidence was not available for specific patient groups. Conclusions In people at risk of SCD as a result of ventricular arrhythmias and in those with HF as a result of LVSD and cardiac dyssynchrony, the interventions modelled produced ICERs of < £30,000 per QALY gained. In people with both conditions, the ICER for CRT-D compared with ICD, but not CRT-D compared with OPT, was < £30,000 per QALY, and the costs and QALYs for CRT-D and CRT-P were similar. A RCT comparing CRT-D and CRT-P in people with HF as a result of LVSD and cardiac dyssynchrony is required, for both those with and those without an ICD indication. A RCT is also needed into the benefits of ICD in non-ischaemic cardiomyopathy in the absence of dyssynchrony. Study registration This study is registered as PROSPERO number CRD42012002062. Funding The National Institute for Health Research Health Technology Assessment programme

Successful pleurodesis with OK-432 in preterm infants with persistent pleural effusion

OK-432 (picibanil) is an inactivated preparation of Streptococcus pyogenes that causes pleurodesis by inducing a strong inflammatory response. Intrapleural instillation of OK-432 has recently been used to successfully treat neonatal and fetal chylothorax. Here we report a trial of intrapleural instillation of OK-432 in two preterm infants who were born with hydrops fetalis and massive bilateral pleural effusion. Both cases showed persistent pleural effusion, refractory to conservative treatment, up to postnatal days 26 and 46, respectively. An average of 80 to 140 mL of pleural fluid was drained daily. In case 1, the infant was treated with OK-432 during the fetal period at gestation 28 weeks and 4 days of gestation, but showed recurrence of pleural effusion and progressed into hydrops. Within two to three days after OK-432 injection, the amount of pleural fluid drainage was dramatically decreased and there was no reaccumulation. We did not observe any side effects related to OK-432 injection. We suggest that OK-432 should be considered as a therapeutic option in infants who have persistent pleural effusion for more than four weeks, with the expectation of the early removal of the chest tube and a good outcome

Empowering people to help speak up about safety in primary care: Using codesign to involve patients and professionals in developing new interventions for patients with multimorbidity.

BACKGROUND: Multimorbidity, defined as the presence of two or more long-term conditions, is increasingly common in primary care, and patients with multimorbidity may face particular barriers to quality of care and increased safety risks due to the complexity of managing multiple conditions. Consistent with calls to directly involve service users in improving care, we aimed to use design materials to codesign new interventions to improve safety in primary care. DESIGN: We drew on two established methods-accelerated experience-based codesign and the future workshop approach. We synthesized design materials based on research into the patient experience of safety and multimorbidity in primary care to enable both patients, service users and carers, and primary health-care professionals to propose interventions to improve care. RESULTS: Both patients and professionals prioritized polypharmacy as a threat to safety. Their recommendations for supportive interventions were consistent with Burden of Treatment theory, emphasizing the limited capacity of patients with multimorbidity and the need for services to proactively offer support to reduce the burden of managing complex treatment regimes. DISCUSSION & CONCLUSIONS: The process was feasible and acceptable to participants, who valued the opportunity to jointly propose new interventions. The iterative workshop approach enabled the research team to better explore and refine the suggestions of attendees. Final recommendations included the need for accessible reminders to support medication adherence and medication reviews for particularly vulnerable patients conducted with pharmacists within GP practices

Conventional and molecular epidemiology of Tuberculosis in Manitoba

BACKGROUND: To describe the demographic and geographic distribution of tuberculosis (TB) in Manitoba, thus determining risk factors associated with clustering and higher incidence rates in distinct subpopulations. METHODS: Data from the Manitoba TB Registry was compiled to generate a database on 855 patients with tuberculosis and their contacts from 1992–1999. Recovered isolates of M. tuberculosis were typed by IS6110 restriction fragment length polymorphisms. Bivariate and multivariate logistic regression models were used to identify risk factors involved in clustering. RESULTS: A trend to clustering was observed among the Canadian-born treaty Aboriginal subgroup in contrast to the foreign-born. The dominant type, designated fingerprint type 1, accounts for 25.8% of total cases and 75.3% of treaty Aboriginal cases. Among type 1 patients residing in urban areas, 98.9% lived in Winnipeg. In rural areas, 92.8% lived on Aboriginal reserves. Statistical models revealed that significant risk factors for acquiring clustered tuberculosis are gender, age, ethnic origin and residence. Those at increased risk are: males (p < 0.05); those under age 65 (p < 0.01 for each age subgroup); treaty Aboriginals (p < 0.001), and those living on reserve land (p < 0.001). CONCLUSION: Molecular typing of isolates in conjunction with contact tracing data supports the notion of the largest ongoing transmission of a single strain of TB within the treaty-status population of Canada recorded to date. This data demonstrates the necessity of continued surveillance of countries with low prevalence of the disease in order to determine and target high-risk populations for concentrated prevention and control measures

Estimating the Cost-Effectiveness of Implementation : Is Sufficient Evidence Available?

BACKGROUND: Timely implementation of recommended interventions can provide health benefits to patients and cost savings to the health service provider. Effective approaches to increase the implementation of guidance are needed. Since investment in activities that improve implementation competes for funding against other health generating interventions, it should be assessed in term of its costs and benefits. OBJECTIVE: In 2010, the National Institute for Health and Care Excellence released a clinical guideline recommending natriuretic peptide (NP) testing in patients with suspected heart failure. However, its implementation in practice was variable across the National Health Service in England. This study demonstrates the use of multi-period analysis together with diffusion curves to estimate the value of investing in implementation activities to increase uptake of NP testing. METHODS: Diffusion curves were estimated based on historic data to produce predictions of future utilization. The value of an implementation activity (given its expected costs and effectiveness) was estimated. Both a static population and a multi-period analysis were undertaken. RESULTS: The value of implementation interventions encouraging the utilization of NP testing is shown to decrease over time as natural diffusion occurs. Sensitivity analyses indicated that the value of the implementation activity depends on its efficacy and on the population size. CONCLUSIONS: Value of implementation can help inform policy decisions of how to invest in implementation activities even in situations in which data are sparse. Multi-period analysis is essential to accurately quantify the time profile of the value of implementation given the natural diffusion of the intervention and the incidence of the disease

Carbon myopia: the urgent need for integrated social, economic and environmental action in the livestock sector

Livestock have long been integral to food production systems, often not by choice but by need. While our knowledge of livestock greenhouse gas emissions (GHG) mitigation has evolved, the prevailing focus has been - somewhat myopically on technology applications associated with mitigation.Here, we (1) examine the global distribution of livestock GHG emissions, (2) explore social, economic and environmental co-benefits and trade-offs associated with mitigation interventions, and (3) critique approaches for quantifying GHG emissions.This review uncovered many insights. First, while GHG emissions from ruminant livestock are greatest in low and middle-income countries (LMIC; globally, 66% of emissions are produced by Latin America and the Caribbean, East and southeast Asia, and south Asia), the majority of mitigation strategies are designed for developed countries. This serious concern is heightened by the fact that 80% of growth in global meat production over the next decade will occur in LMIC. Second, few studies concurrently assess social, economic and environmental aspects of mitigation. Of the 54 interventions reviewed, only 16 had triple-bottom line benefit with medium-high mitigation potential. Third, while efforts designed to stimulate adoption of strategies allowing both emissions reduction (ER) and carbon sequestration (CS) would achieve the greatest net emissions mitigation, CS measures have greater potential mitigation and co-benefits.The scientific community must shift attention away from the prevailing myopic lens on carbon, towards more holistic, systems-based, multi-metric approaches that carefully consider the raison d'être for livestock systems. Consequential life-cycle assessments and systems-aligned socio-economic planetary boundaries offer useful starting points that may uncover leverage points and cross-scale emergent properties. Derivation of harmonised, globally-reconciled sustainability metrics requires iterative dialogue between stakeholders at all levels. Greater emphasis on the simultaneous characterisation of multiple sustainability dimensions would help avoid situations where progress made in one area causes maladaptive outcomes in other areas

Deep learning analysis of mobile physiological, environmental and location sensor data for emotion detection

The detection and monitoring of emotions are important in various applications, e.g. to enable naturalistic and personalised human-robot interaction. Emotion detection often require modelling of various data inputs from multiple modalities, including physiological signals (e.g.EEG and GSR), environmental data (e.g. audio and weather), videos (e.g. for capturing facial expressions and gestures) and more recently motion and location data. Many traditional machine learning algorithms have been utilised to capture the diversity of multimodal data at the sensors and features levels for human emotion classification. While the feature engineering processes often embedded in these algorithms are beneficial for emotion modelling, they inherit some critical limitations which may hinder the development of reliable and accurate models. In this work, we adopt a deep learning approach for emotion classification through an iterative process by adding and removing large number of sensor signals from different modalities. Our dataset was collected in a real-world study from smart-phones and wearable devices. It merges local interaction of three sensor modalities: on-body, environmental and location into global model that represents signal dynamics along with the temporal relationships of each modality. Our approach employs a series of learning algorithms including a hybrid approach using Convolutional Neural Network and Long Short-term Memory Recurrent Neural Network (CNN-LSTM) on the raw sensor data, eliminating the needs for manual feature extraction and engineering. The results show that the adoption of deep-learning approaches is effective in human emotion classification when large number of sensors input is utilised (average accuracy 95% and F-Measure=%95) and the hybrid models outperform traditional fully connected deep neural network (average accuracy 73% and F-Measure=73%). Furthermore, the hybrid models outperform previously developed Ensemble algorithms that utilise feature engineering to train the model average accuracy 83% and F-Measure=82%