Educational and behavioural interventions for anticoagulant therapy in patients with atrial fibrillation

Background Current guidelines recommend oral anticoagulation therapy for patients with atrial fibrillation who are at moderate-to-high risk of stroke, however anticoagulation control (time in therapeutic range (TTR)) is dependent on many factors. Educational and behavioural interventions may impact on patients’ ability to maintain their International Normalised Ratio (INR) control. Objectives To evaluate the effects on TTR of educational and behavioural interventions for oral anticoagulation therapy (OAT) in patients with atrial fibrillation (AF). Search methods We searched the Cochrane Central Register of Controlled Trials (CENTRAL) and the Database of Abstracts of Reviews of Effects (DARE) in The Cochrane Library (2012, Issue 7 of 12), MEDLINE Ovid (1950 to week 4 July 2012), EMBASE Classic + EMBASE Ovid (1947 to Week 31 2012), PsycINFO Ovid (1806 to 2012 week 5 July) on 8 August 2012 and CINAHL Plus with Full Text EBSCO (to August 2012) on 9 August 2012. We applied no language restrictions. Selection criteria The primary outcome analysed was TTR. Secondary outcomes included decision conflict (patient's uncertainty in making health-related decisions), percentage of INRs in the therapeutic range, major bleeding, stroke and thromboembolic events, patient knowledge, patient satisfaction, quality of life (QoL), and anxiety. Data collection and analysis The two review authors independently extracted data. Where insufficient data were present to conduct a meta-analysis, effect sizes and confidence intervals (CIs) of the included studies were reported. Data were pooled for two outcomes, TTR and decision conflict. Main results Eight trials with a total of 1215 AF patients (number of AF participants included in the individual trials ranging from 14 to 434) were included within the review. Studies included education, decision aids, and self-monitoring plus education. For the primary outcome of TTR, data for the AF participants in two self-monitoring plus education trials were pooled and did not favour self-monitoring plus education or usual care in improving TTR, with a mean difference of 6.31 (95% CI -5.63 to 18.25). For the secondary outcome of decision conflict, data from two decision aid trials favoured usual care over the decision aid in terms of reducing decision conflict, with a mean difference of -0.1 (95% CI -0.2 to -0.02). Authors' conclusions This review demonstrated that there is insufficient evidence to draw definitive conclusions regarding the impact of educational or behavioural interventions on TTR in AF patients receiving OAT. Thus, more trials are needed to examine the impact of interventions on anticoagulation control in AF patients and the mechanisms by which they are successful. It is also important to explore the psychological implications for patients suffering from this long-term chronic condition.

Development and trialling of a behavioural intervention for patients with atrial fibrillation initiating oral anticoagulation:the 'treat' study

Purpose: Atrial fibrillation (AF) is the most common heart arrhythmia and is associated with an increased risk of stroke. Stroke risk is commonly treated with oral anticoagulation (OAC) with a narrow therapeutic range (INR 2.0 to 3.0); which is poorly controlled in practice. Barriers to adherence include poor knowledge, and inaccurate perceptions surrounding illness and medications. Trial registration: ISRCTN93952605. Systematic review: Seven trials of educational, self-monitoring and decision aid interventions were included in a systematic review. Pooled analysis suggested education OR, 95% CI 7.89 (5.54-10.24) and self monitoring OR (95% CI) 5.47(2.55-8.39) significantly improve TTR; whereas decision aids are no more effective in reducing decision conflict than usual care, OR (95% CI) -0.10 (-0.17 to -0.02). Intervention development: The intervention was theoretically-driven (utilising the common sense and beliefs about medication models) and developed with expert patient feedback. Described using behavioural change techniques, the one-off group session included an educational booklet, ‘expert-patient’ focussed DVD, and worksheet. Methods: Ninety seven warfarin-naïve AF patients were randomised to receive the intervention (n=43), or usual care (n=54). The primary endpoint was time within therapeutic range (TTR), secondary endpoints included knowledge, quality of life (AF-QoL-18), beliefs about medication (BMQ), illness perceptions (IPQ-B), and anxiety and depression (HADS). Results: Intervention group had significantly higher TTR than usual care (78.5% vs. 66.7%; p=0.01). Knowledge changed significantly across time (F (3, 47) = 6.4; p<0.01), but not between groups (F (1, 47) = 3.3; p = 0.07). At six months knowledge predicted TTR (r=0.245; p=0.04). Illness concern negatively correlated with TTR (r= - 0.199; p=0.05). General Harm scores at one month predicted TTR (F (1, 72) = 4.08; p=0.048). There were significant differences in emotional representations (F (3, 49) = 3.3 (3, 49); p= 0.03), anxiety (F (3, 46) = 25.2; p<0.01) and depression (F (3, 46) = 37.7; p<0.01) across time. Conclusion: A theory-driven educational intervention can improve TTR in AF patients and potentially reduce the risk of adverse clinical outcomes. Improving education provision for AF patients is essential to ensure efficacious treatment.

Educational and behavioural interventions for anticoagulant therapy in patients with atrial fibrillation

background Current guidelines recommend oral anticoagulation therapy for patients with atrial fibrillation who are at moderate-to-high risk of stroke, however anticoagulation control (time in therapeutic range (TTR)) is dependent on many factors. Educational and behavioural interventions may impact on patients’ ability to maintain their International Normalised Ratio (INR) control. Objectives To evaluate the effects on TTR of educational and behavioural interventions for oral anticoagulation therapy (OAT) in patients with atrial fibrillation (AF). Search methods We searched the Cochrane Central Register of Controlled Trials (CENTRAL) and the Database of Abstracts of Reviews of Effects (DARE) in The Cochrane Library (2012, Issue 7 of 12), MEDLINE Ovid (1950 to week 4 July 2012), EMBASE Classic + EMBASE Ovid (1947 to Week 31 2012), PsycINFO Ovid (1806 to 2012 week 5 July) on 8 August 2012 and CINAHL Plus with Full Text EBSCO (to August 2012) on 9 August 2012. We applied no language restrictions. Selection criteria The primary outcome analysed was TTR. Secondary outcomes included decision conflict (patient's uncertainty in making health-related decisions), percentage of INRs in the therapeutic range, major bleeding, stroke and thromboembolic events, patient knowledge, patient satisfaction, quality of life (QoL), and anxiety. Data collection and analysis The two review authors independently extracted data. Where insufficient data were present to conduct a meta-analysis, effect sizes and confidence intervals (CIs) of the included studies were reported. Data were pooled for two outcomes, TTR and decision conflict. Main results Eight trials with a total of 1215 AF patients (number of AF participants included in the individual trials ranging from 14 to 434) were included within the review. Studies included education, decision aids, and self-monitoring plus education. For the primary outcome of TTR, data for the AF participants in two self-monitoring plus education trials were pooled and did not favour self-monitoring plus education or usual care in improving TTR, with a mean difference of 6.31 (95% CI -5.63 to 18.25). For the secondary outcome of decision conflict, data from two decision aid trials favoured usual care over the decision aid in terms of reducing decision conflict, with a mean difference of -0.1 (95% CI -0.2 to -0.02). Authors' conclusions This review demonstrated that there is insufficient evidence to draw definitive conclusions regarding the impact of educational or behavioural interventions on TTR in AF patients receiving OAT. Thus, more trials are needed to examine the impact of interventions on anticoagulation control in AF patients and the mechanisms by which they are successful. It is also important to explore the psychological implications for patients suffering from this long-term chronic condition.

The influence of patient's age on clinical decision-making about coronary heart disease in the USA and the UK

This paper examines UK and US primary care doctors' decision-making about older (aged 75 years) and midlife (aged 55 years) patients presenting with coronary heart disease (CHD). Using an analytic approach based on conceptualising clinical decision-making as a classification process, it explores the ways in which doctors' cognitive processes contribute to ageism in health-care at three key decision points during consultations. In each country, 56 randomly selected doctors were shown videotaped vignettes of actors portraying patients with CHD. The patients' ages (55 or 75 years), gender, ethnicity and social class were varied systematically. During the interviews, doctors gave free-recall accounts of their decision-making. The results do not establish that there was substantial ageism in the doctors' decisions, but rather suggest that diagnostic processes pay insufficient attention to the significance of older patients' age and its association with the likelihood of co-morbidity and atypical disease presentations. The doctors also demonstrated more limited use of 'knowledge structures' when diagnosing older than midlife patients. With respect to interventions, differences in the national health-care systems rather than patients' age accounted for the differences in doctors' decisions. US doctors were significantly more concerned about the potential for adverse outcomes if important diagnoses were untreated, while UK general practitioners cited greater difficulty in accessing diagnostic tests.

Mobile case-based decision support for intelligent patient knowledge management

Hospitals everywhere are integrating health data using electronic health record (EHR) systems, and disparate and multimedia patient data can be input by different caregivers at different locations as encapsulated patient profiles. Healthcare institutions are also using the flexibility and speed of wireless computing to improve quality and reduce costs. We are developing a mobile application that allows doctors to efficiently record and access complete and accurate real-time patient information. The system integrates medical imagery with textual patient profiles as well as expert interactions by healthcare personnel using knowledge management and case-based reasoning techniques. The application can assist other caregivers in searching large repositories of previous patient cases. Patients' symptoms can be input to a portable device and the application can quickly retrieve similar profiles which can be used to support effective diagnoses and prognoses by comparing symptoms, treatments, diagnosis, test results and other patient information. © 2007 Sage Publications.

Decision support system for risk management:a case study

This study demonstrates a quantitative approach to construction risk management through analytic hierarchy process and decision tree analysis. All the risk factors are identified, their effects are quantified by determining probability and severity, and various alternative responses are generated with cost implication for mitigating the quantified risks. The expected monetary values are then derived for each alternative in a decision tree framework and subsequent probability analysis aids the decision process in managing risks. The entire methodology is explained through a case application of a cross-country petroleum pipeline project in India and its effectiveness in project management is demonstrated.

Multi-criteria decision making approaches for supplier evaluation and selection:a literature review

Supplier evaluation and selection problem has been studied extensively. Various decision making approaches have been proposed to tackle the problem. In contemporary supply chain management, the performance of potential suppliers is evaluated against multiple criteria rather than considering a single factor-cost. This paper reviews the literature of the multi-criteria decision making approaches for supplier evaluation and selection. Related articles appearing in the international journals from 2000 to 2008 are gathered and analyzed so that the following three questions can be answered: (i) Which approaches were prevalently applied? (ii) Which evaluating criteria were paid more attention to? (iii) Is there any inadequacy of the approaches? Based on the inadequacy, if any, some improvements and possible future work are recommended. This research not only provides evidence that the multi-criteria decision making approaches are better than the traditional cost-based approach, but also aids the researchers and decision makers in applying the approaches effectively.

A concept-based framework for retrieving evidence to support emergency physician decision making at the point of care

The goal of evidence-based medicine is to uniformly apply evidence gained from scientific research to aspects of clinical practice. In order to achieve this goal, new applications that integrate increasingly disparate health care information resources are required. Access to and provision of evidence must be seamlessly integrated with existing clinical workflow and evidence should be made available where it is most often required - at the point of care. In this paper we address these requirements and outline a concept-based framework that captures the context of a current patient-physician encounter by combining disease and patient-specific information into a logical query mechanism for retrieving relevant evidence from the Cochrane Library. Returned documents are organized by automatically extracting concepts from the evidence-based query to create meaningful clusters of documents which are presented in a manner appropriate for point of care support. The framework is currently being implemented as a prototype software agent that operates within the larger context of a multi-agent application for supporting workflow management of emergency pediatric asthma exacerbations. © 2008 Springer-Verlag Berlin Heidelberg.

Using secondary knowledge to support decision tree classification of retrospective clinical data

Retrospective clinical data presents many challenges for data mining and machine learning. The transcription of patient records from paper charts and subsequent manipulation of data often results in high volumes of noise as well as a loss of other important information. In addition, such datasets often fail to represent expert medical knowledge and reasoning in any explicit manner. In this research we describe applying data mining methods to retrospective clinical data to build a prediction model for asthma exacerbation severity for pediatric patients in the emergency department. Difficulties in building such a model forced us to investigate alternative strategies for analyzing and processing retrospective data. This paper describes this process together with an approach to mining retrospective clinical data by incorporating formalized external expert knowledge (secondary knowledge sources) into the classification task. This knowledge is used to partition the data into a number of coherent sets, where each set is explicitly described in terms of the secondary knowledge source. Instances from each set are then classified in a manner appropriate for the characteristics of the particular set. We present our methodology and outline a set of experiential results that demonstrate some advantages and some limitations of our approach. © 2008 Springer-Verlag Berlin Heidelberg.

The influence of patient and doctor gender on diagnosing coronary heart disease

Using novel methods, this paper explores sources of uncertainty and gender bias in primary care doctors' diagnostic decision-making about coronary heart disease (CHD). Claims about gendered consultation styles and quality of care are re-examined, along with the adequacy of CHD models for women. Randomly selected doctors in the UK and the US (n=112, 56 per country, stratified by gender) were shown standardised videotaped vignettes of actors portraying patients with CHD. Patients' age, gender, ethnicity and social class were varied systematically. During interviews, doctors gave free-recall accounts of their decision-making, which were analysed to determine patient and doctor gender effects. We found differences in male and female doctors' responses to different types of patient information. Female doctors recall more patient cues overall, particularly about history presentation, and particularly amongst women. Male doctors appear less affected by patient gender but both male and especially female doctors take more account of male patients' age, and consider more age-related disease possibilities for men than women. Findings highlight the need for better integration of knowledge about female presentations within accepted CHD risk models, and do not support the contention that women receive better-quality care from female doctors.

A tree-based decision model to support prediction of the severity of asthma exacerbations in children

This paper describes the development of a tree-based decision model to predict the severity of pediatric asthma exacerbations in the emergency department (ED) at 2 h following triage. The model was constructed from retrospective patient data abstracted from the ED charts. The original data was preprocessed to eliminate questionable patient records and to normalize values of age-dependent clinical attributes. The model uses attributes routinely collected in the ED and provides predictions even for incomplete observations. Its performance was verified on independent validating data (split-sample validation) where it demonstrated AUC (area under ROC curve) of 0.83, sensitivity of 84%, specificity of 71% and the Brier score of 0.18. The model is intended to supplement an asthma clinical practice guideline, however, it can be also used as a stand-alone decision tool.

Knowledge engineering for mental-health risk assessment and decision support

Mental-health risk assessment practice in the UK is mainly paper-based, with little standardisation in the tools that are used across the Services. The tools that are available tend to rely on minimal sets of items and unsophisticated scoring methods to identify at-risk individuals. This means the reasoning by which an outcome has been determined remains uncertain. Consequently, there is little provision for: including the patient as an active party in the assessment process, identifying underlying causes of risk, and eecting shared decision-making. This thesis develops a tool-chain for the formulation and deployment of a computerised clinical decision support system for mental-health risk assessment. The resultant tool, GRiST, will be based on consensual domain expert knowledge that will be validated as part of the research, and will incorporate a proven psychological model of classication for risk computation. GRiST will have an ambitious remit of being a platform that can be used over the Internet, by both the clinician and the layperson, in multiple settings, and in the assessment of patients with varying demographics. Flexibility will therefore be a guiding principle in the development of the platform, to the extent that GRiST will present an assessment environment that is tailored to the circumstances in which it nds itself. XML and XSLT will be the key technologies that help deliver this exibility.

Increased salience of gains versus decreased associative learning differentiate bipolar disorder from schizophrenia during incentive decision making

Background Abnormalities in incentive decision making, typically assessed using the Iowa Gambling Task (IGT), have been reported in both schizophrenia (SZ) and bipolar disorder (BD). We applied the Expectancy-Valence (E-V) model to determine whether motivational, cognitive and response selection component processes of IGT performance are differentially affected in SZ and BD. Method Performance on the IGT was assessed in 280 individuals comprising 70 remitted patients with SZ, 70 remitted patients with BD and 140 age-, sex-and IQ-matched healthy individuals. Based on the E-V model, we extracted three parameters, 'attention to gains or loses', 'expectancy learning' and 'response consistency', that respectively reflect motivational, cognitive and response selection influences on IGT performance. Results Both patient groups underperformed in the IGT compared to healthy individuals. However, the source of these deficits was diagnosis specific. Associative learning underlying the representation of expectancies was disrupted in SZ whereas BD was associated with increased incentive salience of gains. These findings were not attributable to non-specific effects of sex, IQ, psychopathology or medication. Conclusions Our results point to dissociable processes underlying abnormal incentive decision making in BD and SZ that could potentially be mapped to different neural circuits. © 2012 Cambridge University Press.

Designing multiple user perspectives and functionality for clinical decision support systems

Clinical Decision Support Systems (CDSSs) need to disseminate expertise in formats that suit different end users and with functionality tuned to the context of assessment. This paper reports research into a method for designing and implementing knowledge structures that facilitate the required flexibility. A psychological model of expertise is represented using a series of formally specified and linked XML trees that capture increasing elements of the model, starting with hierarchical structuring, incorporating reasoning with uncertainty, and ending with delivering the final CDSS. The method was applied to the Galatean Risk and Safety Tool, GRiST, which is a web-based clinical decision support system (www.egrist.org) for assessing mental-health risks. Results of its clinical implementation demonstrate that the method can produce a system that is able to deliver expertise targetted and formatted for specific patient groups, different clinical disciplines, and alternative assessment settings. The approach may be useful for developing other real-world systems using human expertise and is currently being applied to a logistics domain. © 2013 Polish Information Processing Society.

Green supply chain performance measurement using fuzzy ANP-based balanced scorecard:a collaborative decision-making approach

The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firms decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers performances meet the industry and environment standards with effective human resource. © 2013 Taylor & Francis.