Clinical Response to Procedural Stroke Following Carotid Endarterectomy:A Delphi Consensus Study

Objective: No dedicated studies have been performed on the optimal management of patients with an acute stroke related to carotid intervention nor is there a solid recommendation given in the European Society for Vascular Surgery guideline. By implementation of an international expert Delphi panel, this study aimed to obtain expert consensus on the optimal management of in hospital stroke occurring during or following CEA and to provide a practical treatment decision tree. Methods: A four round Delphi consensus study was performed including 31 experts. The aim of the first round was to investigate whether the conceptual model indicating the traditional division between intra- and post-procedural stroke in six phases was appropriate, and to identify relevant clinical responses during these six phases. In rounds 2, 3, and 4, the aim was to obtain consensus on the optimal response to stroke in each predefined setting. Consensus was reached in rounds 1, 3, and 4 when ≥ 70% of experts agreed on the preferred clinical response and in round 2 based on a Likert scale when a median of 7 – 9 (most adequate response) was given, IQR ≤ 2. Results: The experts agreed (> 80%) on the use of the conceptual model. Stroke laterality and type of anaesthesia were included in the treatment algorithm. Consensus was reached in 17 of 21 scenarios (> 80%). Perform diagnostics first for a contralateral stroke in any phase, and for an ipsilateral stroke during cross clamping, or apparent stroke after leaving the operation room. For an ipsilateral stroke during the wake up phase, no formal consensus was achieved, but 65% of the experts would perform diagnostics first. A CT brain combined with a CTA or duplex ultrasound of the carotid arteries should be performed. For an ipsilateral intra-operative stroke after flow restoration, the carotid artery should be re-explored immediately (75%). Conclusion: In patients having a stroke following carotid endarterectomy, expedited diagnostics should be performed initially in most phases. In patients who experience an ipsilateral intra-operative stroke following carotid clamp release, immediate re-exploration of the index carotid artery is recommended

Integrating telemedicine in routine heart failure management: Experiences of healthcare professionals – A qualitative study

Objective: To describe the experiences of healthcare professionals with integrating telemedicine in routine heart failure (HF) care. Methods: Semi-structured interviews were conducted with healthcare professionals (n = 19) in the Netherlands who were involved in decision-making, implementation or routine use of telemedicine in HF management. Using purposive sampling, nurses, cardiologists and managers were selected to be interviewed. Interviews were performed in-person, recorded and transcribed verbatim. Interview data were analysed using a reflexive thematic analysis. Results: This study identified four themes: (1) Responsibility – the lack of a clear delineation of roles and responsibilities among healthcare professionals, patients and suppliers in telemedicine. (2) Confidence and safety – telemedicine is seen by healthcare professionals as capable of enhancing safety, yet also introduces the risk of fostering a false sense of security among patients. (3) Collaboration – actively involving end-users in the development and implementation of telemedicine promotes the adoption. (4) Processes and mutual agreements – rather than replacing traditional care, telemedicine is perceived as an adjunct to it. Structured care pathways support telemedicine implementation, and personalised telemedicine can empower patients in self-care. Conclusions: Telemedicine is a promising intervention in the management of HF. However, existing systems and care pathways have resulted in limited adoption. Improvements in the collaboration and establishing clear agreements on responsibilities between professional, patient and supplier can lead to more confidence in adopting telemedicine. Structured care pathways can be supportive. A personalised telemedicine approach can ensure that telemedicine remains manageable for patient and professional

Which heart failure patients benefit most from non-invasive telemedicine? An overview of current evidence and future directions

Telemedicine in heart failure (HF) management may positively impact health outcomes, but varied effects in studies hinder guidance in HF guidelines. Evidence on the effectiveness of telemedicine in HF subpopulations is limited. We conducted a scoping review to evaluate and synthesise evidence on the effectiveness of telemedicine across HF subpopulations that could guide telemedicine strategies in routine practice. Meta-analyses concerning randomised controlled trials (RCTs) with subgroup analyses on telemedicine effectives were identified in PubMed. We identified 15 RCTs, encompassing 21 different subgroups based on characteristics of HF patients. Findings varied across studies and no definite evidence was found about which patients benefit most from telemedicine. Subgroup definitions were inconsistent, not always a priori defined and subgroups contained few patients. Some studies found heterogeneous effects of telemedicine on mortality and hospitalisation across subgroups defined by: New York Heart Association (NYHA) classification, previous HF decompensation, implantable device, concurrent depression, time since hospital discharge and duration of HF. Patients represented in the RCTs were mostly male, aged 65–75 years, with HF with reduced ejection fraction and NYHA class II/III. Traditional RCTs have not been able to provide clinicians with guidance; continuous real-world evidence generation could enhance monitoring and identify who benefits from telemedicine

Unravelling effectiveness of a nurse-led behaviour change intervention to enhance physical activity in patients at risk for cardiovascular disease in primary care: study protocol for a cluster randomised controlled trial

BACKGROUND: Self-management interventions are considered effective in patients with chronic disease, but trials have shown inconsistent results, and it is unknown which patients benefit most. Adequate self-management requires behaviour change in both patients and health care providers. Therefore, the Activate intervention was developed with a focus on behaviour change in both patients and nurses. The intervention aims for change in a single self-management behaviour, namely physical activity, in primary care patients at risk for cardiovascular disease. The aim of this study is to evaluate the effectiveness of the Activate intervention. METHODS/DESIGN: A two-arm cluster randomised controlled trial will be conducted to compare the Activate intervention with care as usual at 31 general practices in the Netherlands. Approximately 279 patients at risk for cardiovascular disease will participate. The Activate intervention is developed using the Behaviour Change Wheel and consists of 4 nurse-led consultations in a 3-month period, integrating 17 behaviour change techniques. The Behaviour Change Wheel was also applied to analyse what behaviour change is needed in nurses to deliver the intervention adequately. This resulted in 1-day training and coaching sessions (including 21 behaviour change techniques). The primary outcome is physical activity, measured as the number of minutes of moderate to vigorous physical activity using an accelerometer. Potential effect modifiers are age, body mass index, level of education, social support, depression, patient-provider relationship and baseline number of minutes of physical activity. Data will be collected at baseline and at 3 months and 6 months of follow-up. A process evaluation will be conducted to evaluate the training of nurses, treatment fidelity, and to identify barriers to and facilitators of implementation as well as to assess participants' satisfaction. DISCUSSION: To increase physical activity in patients and to support nurses in delivering the intervention, behaviour change techniques are applied to change behaviours of the patients and nurses. Evaluation of the effectiveness of the intervention, exploration of which patients benefit most, and evaluation of our theory-based training for primary care nurses will enhance understanding of what works and for whom, which is essential for further implementation of self-management in clinical practice. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02725203 . Registered on 25 March 2016

Factors That Influence the Use of eHealth in Home Care: Scoping Review and Cross-sectional Survey

BACKGROUND: In home care, eHealth implementation requires health care professionals and home care clients to change their behavior because they have to incorporate the use of eHealth into their daily routines. Knowledge of factors that influence the use of eHealth in home care is needed to optimize implementation strategies. However, a comprehensive overview of such factors is lacking. OBJECTIVE: The aims of this study were to (1) provide insight into the types of eHealth that are used and preferred in home care and (2) identify factors that influence the use of eHealth in home care according to health care professionals and home care clients. METHODS: A scoping review and online, cross-sectional survey were conducted sequentially. The survey was conducted among Dutch health care professionals with a nursing background who were working for a home care organization at the time. The capability, opportunity, motivation, behavior (COM-B) model, which posits that for any behavior (B) to occur, a person must have the capability (C), opportunity (O), and motivation (M) to perform the behavior, was used to identify influencing factors. The use of a theoretical model may contribute to a better understanding of how to achieve and sustain behavior change in clinical practice. RESULTS: We included 30 studies in the scoping review. The most frequently studied type of eHealth was a telecommunication/telemonitoring system. The survey was completed by 102 participants. The most frequently used types of eHealth were electronic health records, social alarms, and online client portals. A health app was the most frequently preferred type of eHealth. We identified 22 factors that influence the use of eHealth in home care according to health care professionals and home care clients. Influencing factors were organized into the components of the COM-B model, namely capability (n=6), opportunity (n=10), and motivation (n=6). We found that there is no single influencing factor that is key to the complexity of eHealth implementation. CONCLUSIONS: Different types of eHealth are used, and many types of eHealth are preferred by health care professionals. The identified factors that influence the use of eHealth in home care relate to all components of the COM-B model. These factors need to be addressed and embedded in implementation strategies of eHealth to optimize the use of eHealth in home care

Self-management behaviors to reduce exacerbation impact in COPD patients: a Delphi study

This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).Background: Little is known about which self-management behaviors have the highest potential to influence exacerbation impact in COPD patients. We aimed to reach expert consensus on the most relevant set of self-management behaviors that can be targeted and influenced to maximize reduction of exacerbation impact. Materials and methods: A 2-round Delphi study was performed using online surveys to rate the relevance and feasibility of predetermined self-management behaviors identified by literature and expert opinion. Descriptive statistics and qualitative analyses were used. Results: An international expert panel reached consensus on 17 self-management behaviors focusing on: stable phase (n=5): pharmacotherapy, vaccination, physical activity, avoiding stimuli and smoking cessation; periods of symptom deterioration (n=1): early detection; during an exacerbation (n=5): early detection, health care contact, self-treatment, managing stress/anxiety and physical activity; during recovery (n=4): completing treatment, managing stress/anxiety, physical activity and exercise training; and after recovery (n=2): awareness for recurrent exacerbations and restart of pulmonary rehabilitation. Conclusion: This study has provided insight into expert opinion on the most relevant and feasible self-management behaviors that can be targeted and influenced before, during and after an exacerbation to exert the highest magnitude of influence on the impact of exacerbations. Future research should focus at developing more comprehensive patient-tailored interventions supporting patients in these exacerbation-related self-management behaviors

SAFE@HOME: Digital health platform facilitating a new care path for women at increased risk of preeclampsia – A case-control study

Objective: In women at risk of developing preeclampsia, we evaluated the use of a digital health platform for telemonitoring blood pressure and symptoms combined with a minimal antenatal visit schedule. Study design: A case-control study for women with chronic hypertension, history of preeclampsia, or maternal cardiac or kidney disease. A care path was designed with reduced visits enhanced with a digital platform (SAFE@HOME) for daily blood pressure and symptom monitoring starting from 16 weeks of gestation. Home-measurements were monitored in-hospital by obstetric professionals, taking actions upon alarming results. This prospective SAFE@HOME group was compared to a retrospective control group managed without self-monitoring. Main outcome measures: Primary: healthcare consumption (number of antenatal visits, ultrasounds, admissions and diagnostics), user experiences of the platform. Secondary: maternal and perinatal outcomes. Results: Baseline characteristics of the SAFE@HOME (n = 103) and control group (n = 133) were comparable. In the SAFE@HOME group, antenatal visits (mean 13.7 vs 16.0, p < 0.001) and ultrasounds (6.3 vs 7.4, p = 0.005) were lower compared to the control group. Admissions for hypertension or suspected preeclampsia were significantly fewer in the SAFE@HOME group (2.9% versus 13.5%, p = 0.004). Telemonitoring participants were highly satisfied using the platform. No differences were observed for maternal and perinatal outcomes. Conclusions: Our care path including blood pressure telemonitoring for women at risk of preeclampsia allows fewer antenatal visits, ultrasounds and hypertension-related admissions. We observed no differences in perinatal outcomes. These results suggest that telemonitoring of blood pressure is feasible in a high-risk pregnant population and has the potential to profoundly change antenatal care

Towards tailoring of self-management for patients with chronic heart failure or chronic obstructive pulmonary disease: a protocol for an individual patient data meta-analysis

Introduction Self-management interventions in patients with chronic conditions have received increasing attention over the past few years, yet the meta-analyses encountered considerable heterogeneity in results. This suggests that the effectiveness of self-management interventions must be assessed in the context of which components are responsible for eliciting the effect and in which subgroups of patients the intervention works best. The aim of the present study is to identify condition-transcending determinants of success of self-management interventions in two parallel individual patient data meta-analyses of self-management trials in patients with congestive heart failure (CHF) and in patients with chronic obstructive pulmonary disease (COPD). Methods and analysis Investigators of 53 randomised trials (32 in CHF and 21 in COPD) will be requested to share their de-identified individual patient data. Data will be analysed using random effects models, taking clustering within studies into account. Effect modification by age, sex, disease severity, symptom status, comorbid conditions and level of education will be assessed. Sensitivity analyses will be conducted to assess the robustness of the findings. Ethics and dissemination The de-identified individual patient data are used only for the purpose for which they were originally collected and for which ethical approval has been obtained by the original investigators. Knowledge on the effective ingredients of self-management programmes and identification of subgroups of patients in which those interventions are most effective will guide the development of evidence-based personalised self-management interventions for patients with CHF and COPD as well as with other chronic diseases

Detecting exacerbations using the Clinical COPD Questionnaire

BACKGROUND: Early treatment of COPD exacerbations has shown to be important. Despite a non-negligible negative impact on health related quality of life, a large proportion of these episodes is not reported (no change in treatment). Little is known whether (low burden) strategies are able to capture these unreported exacerbations. METHODS: The Clinical COPD Questionnaire (CCQ) is a short questionnaire with great evaluative properties in measuring health status. The current explorative study evaluates the discriminative properties of weekly CCQ assessment in detecting exacerbations. RESULTS: In a multicentre prospective cohort study, 121 patients, age 67.4 ± 10.5 years, FEV(1 )47.7 ± 18.5% pred were followed for 6 weeks by daily diary card recording and weekly CCQ assessment. Weeks were retrospectively labeled as stable or exacerbation (onset) weeks using the Anthonisen symptom diary-card algorithm. Change in CCQ total scores are significantly higher in exacerbation-onset weeks, 0.35 ± 0.69 compared to -0.04 ± 0.37 in stable weeks (p < 0.001). Performance of the Δ CCQ total score discriminating between stable and exacerbation onset weeks was sufficient (area under the ROC curve 0.75). At a cut off point of 0.2, sensitivity was 62.5 (50.3-73.4), specificity 82.0 (79.3-84.4), and a positive and negative predictive value of 43.5 (35.0-51.0) and 90.8 (87.8-93.5), respectively. Using this cut off point, 22 (out of 38) unreported exacerbations were detected while 39 stable patients would have been false positively 'contacted'. CONCLUSIONS: Weekly CCQ assessment is a promising, low burden method to detect unreported exacerbations. Further research is needed to validate discriminative performance and practical implications of the CCQ in detecting exacerbations in daily care

Effectiveness of the nurse-led Activate intervention in patients at risk of cardiovascular disease in primary care: a cluster-randomised controlled trial

BACKGROUND: To understand better the success of self-management interventions and to enable tailoring of such interventions at specific subgroups of patients, the nurse-led Activate intervention is developed targeting one component of self-management (physical activity) in a heterogeneous subgroup (patients at risk of cardiovascular disease) in Dutch primary care. AIM: The aim of this study was to evaluate the effectiveness of the Activate intervention and identifying which patient-related characteristics modify the effect. METHODS: A two-armed cluster-randomised controlled trial was conducted comparing the intervention with care as usual. The intervention consisted of four nurse-led behaviour change consultations within a 3-month period. Data were collected at baseline, 3 months and 6 months. Primary outcome was the daily amount of moderate to vigorous physical activity at 6 months. Secondary outcomes included sedentary behaviour, self-efficacy for physical activity, patient activation for self-management and health status. Prespecified effect modifiers were age, body mass index, level of education, social support, depression, patient provider relationship and baseline physical activity. RESULTS: Thirty-one general practices (n = 195 patients) were included (intervention group n = 93; control group n = 102). No significant between-group difference was found for physical activity (mean difference 2.49 minutes; 95% confidence interval -2.1; 7.1; P = 0.28) and secondary outcomes. Patients with low perceived social support (P = 0.01) and patients with a low baseline activity level (P = 0.02) benefitted more from the intervention. CONCLUSION: The Activate intervention did not improve patients' physical activity and secondary outcomes in primary care patients at risk of cardiovascular disease. To understand the results, the intervention fidelity and active components for effective self-management require further investigation. Trial registration: ClinicalTrials.gov NCT02725203