26 research outputs found

    Recognizing and Tackling Inhaler Technique Decay in Asthma and Chronic Obstructive Pulmonary Disesase (COPD) Clinical Practice

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    A poor inhaler technique continues to represent a substantial barrier to effective asthma and chronic obstructive pulmonary disease management. It can result in perceived lack of treatment effectiveness even with apparent adherence to a prescribed regimen of inhaled maintenance therapies, potentially resulting in an unnecessary change or escalation of treatment. Many patients are not trained to inhaler mastery in real-world practice; furthermore, even where mastery is initially achieved, an ongoing assessment and education are seldom maintained. In this review, we present an overview of the evidence for deterioration of the inhaler technique over time after training, investigate the factors that contribute to this deterioration, and explore innovative approaches to addressing the problem. We also propose steps forward drawn from the literature and our clinical insights.</p

    The Use of eHealth for Pharmacotherapy Management With Patients With Respiratory Disease, Cardiovascular Disease, or Diabetes:Scoping Review

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    Background: eHealth is increasingly considered an important tool for supporting pharmacotherapy management.Objective: We aimed to assess the (1) use of eHealth in pharmacotherapy management with patients with asthma or chronic obstructive pulmonary disease (COPD), diabetes, or cardiovascular disease (CVD); (2) effectiveness of these interventions on pharmacotherapy management and clinical outcomes; and (3) key factors contributing to the success of eHealth interventions for pharmacotherapy management.Methods: We conducted a scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping review) statement. Databases searched included Embase, MEDLINE (PubMed), and Cochrane Library. Screening was conducted by 2 independent researchers. Eligible articles were randomized controlled trials and cohort studies assessing the effect of an eHealth intervention for pharmacotherapy management compared with usual care on pharmacotherapy management or clinical outcomes in patients with asthma or COPD, CVD, or diabetes. The interventions were categorized by the type of device, pharmacotherapy management, mode of delivery, features, and domains described in the conceptual model for eHealth by Shaw at al (Health in our Hands, Interacting for Health, Data Enabling Health). The effectiveness on pharmacotherapy management outcomes and patient- and clinician-reported clinical outcomes was analyzed per type of intervention categorized by number of domains and features to identify trends.Results: Of 63 studies, 16 (25%), 31 (49%), 13 (21%), and 3 (5%) included patients with asthma or COPD, CVD, diabetes, or CVD and diabetes, respectively. Most (38/63, 60%) interventions targeted improving medication adherence, often combined for treatment plan optimization. Of the 16 asthma or COPD interventions, 6 aimed to improve inhaled medication use. The majority (48/63, 76%) of the studies provided an option for patient feedback. Most (20/63, 32%) eHealth interventions combined all 3 domains by Shaw et al, while 25% (16/63) combined Interacting for Health with Data Enabling Health. Two-thirds (42/63, 67%) of the studies showed a positive overall effect. Respectively, 48% (23/48), 57% (28/49), and 39% (12/31) reported a positive effect on pharmacotherapy management and clinician- and patient-reported clinical outcomes. Pharmacotherapy management and patient-reported clinical outcomes, but not clinician-reported clinical outcomes, were more often positive in interventions with ≥3 features. There was a trend toward more studies reporting a positive effect on all 3 outcomes with more domains by Shaw et al. Of the studies with interventions providing patient feedback, more showed a positive clinical outcome, compared with studies with interventions without feedback. This effect was not seen for pharmacotherapy management outcomes.Conclusions: There is a wide variety of eHealth interventions combining various domains and features to target pharmacotherapy management in asthma or COPD, CVD, and diabetes. Results suggest feedback is key for a positive effect on clinician-reported clinical outcomes. eHealth interventions become more impactful when combining domains.</p

    The Use of eHealth for Pharmacotherapy Management With Patients With Respiratory Disease, Cardiovascular Disease, or Diabetes:Scoping Review

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    Background: eHealth is increasingly considered an important tool for supporting pharmacotherapy management.Objective: We aimed to assess the (1) use of eHealth in pharmacotherapy management with patients with asthma or chronic obstructive pulmonary disease (COPD), diabetes, or cardiovascular disease (CVD); (2) effectiveness of these interventions on pharmacotherapy management and clinical outcomes; and (3) key factors contributing to the success of eHealth interventions for pharmacotherapy management.Methods: We conducted a scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping review) statement. Databases searched included Embase, MEDLINE (PubMed), and Cochrane Library. Screening was conducted by 2 independent researchers. Eligible articles were randomized controlled trials and cohort studies assessing the effect of an eHealth intervention for pharmacotherapy management compared with usual care on pharmacotherapy management or clinical outcomes in patients with asthma or COPD, CVD, or diabetes. The interventions were categorized by the type of device, pharmacotherapy management, mode of delivery, features, and domains described in the conceptual model for eHealth by Shaw at al (Health in our Hands, Interacting for Health, Data Enabling Health). The effectiveness on pharmacotherapy management outcomes and patient- and clinician-reported clinical outcomes was analyzed per type of intervention categorized by number of domains and features to identify trends.Results: Of 63 studies, 16 (25%), 31 (49%), 13 (21%), and 3 (5%) included patients with asthma or COPD, CVD, diabetes, or CVD and diabetes, respectively. Most (38/63, 60%) interventions targeted improving medication adherence, often combined for treatment plan optimization. Of the 16 asthma or COPD interventions, 6 aimed to improve inhaled medication use. The majority (48/63, 76%) of the studies provided an option for patient feedback. Most (20/63, 32%) eHealth interventions combined all 3 domains by Shaw et al, while 25% (16/63) combined Interacting for Health with Data Enabling Health. Two-thirds (42/63, 67%) of the studies showed a positive overall effect. Respectively, 48% (23/48), 57% (28/49), and 39% (12/31) reported a positive effect on pharmacotherapy management and clinician- and patient-reported clinical outcomes. Pharmacotherapy management and patient-reported clinical outcomes, but not clinician-reported clinical outcomes, were more often positive in interventions with ≥3 features. There was a trend toward more studies reporting a positive effect on all 3 outcomes with more domains by Shaw et al. Of the studies with interventions providing patient feedback, more showed a positive clinical outcome, compared with studies with interventions without feedback. This effect was not seen for pharmacotherapy management outcomes.Conclusions: There is a wide variety of eHealth interventions combining various domains and features to target pharmacotherapy management in asthma or COPD, CVD, and diabetes. Results suggest feedback is key for a positive effect on clinician-reported clinical outcomes. eHealth interventions become more impactful when combining domains.</p

    The Use of eHealth for Pharmacotherapy Management With Patients With Respiratory Disease, Cardiovascular Disease, or Diabetes:Scoping Review

    Get PDF
    Background: eHealth is increasingly considered an important tool for supporting pharmacotherapy management.Objective: We aimed to assess the (1) use of eHealth in pharmacotherapy management with patients with asthma or chronic obstructive pulmonary disease (COPD), diabetes, or cardiovascular disease (CVD); (2) effectiveness of these interventions on pharmacotherapy management and clinical outcomes; and (3) key factors contributing to the success of eHealth interventions for pharmacotherapy management.Methods: We conducted a scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping review) statement. Databases searched included Embase, MEDLINE (PubMed), and Cochrane Library. Screening was conducted by 2 independent researchers. Eligible articles were randomized controlled trials and cohort studies assessing the effect of an eHealth intervention for pharmacotherapy management compared with usual care on pharmacotherapy management or clinical outcomes in patients with asthma or COPD, CVD, or diabetes. The interventions were categorized by the type of device, pharmacotherapy management, mode of delivery, features, and domains described in the conceptual model for eHealth by Shaw at al (Health in our Hands, Interacting for Health, Data Enabling Health). The effectiveness on pharmacotherapy management outcomes and patient- and clinician-reported clinical outcomes was analyzed per type of intervention categorized by number of domains and features to identify trends.Results: Of 63 studies, 16 (25%), 31 (49%), 13 (21%), and 3 (5%) included patients with asthma or COPD, CVD, diabetes, or CVD and diabetes, respectively. Most (38/63, 60%) interventions targeted improving medication adherence, often combined for treatment plan optimization. Of the 16 asthma or COPD interventions, 6 aimed to improve inhaled medication use. The majority (48/63, 76%) of the studies provided an option for patient feedback. Most (20/63, 32%) eHealth interventions combined all 3 domains by Shaw et al, while 25% (16/63) combined Interacting for Health with Data Enabling Health. Two-thirds (42/63, 67%) of the studies showed a positive overall effect. Respectively, 48% (23/48), 57% (28/49), and 39% (12/31) reported a positive effect on pharmacotherapy management and clinician- and patient-reported clinical outcomes. Pharmacotherapy management and patient-reported clinical outcomes, but not clinician-reported clinical outcomes, were more often positive in interventions with ≥3 features. There was a trend toward more studies reporting a positive effect on all 3 outcomes with more domains by Shaw et al. Of the studies with interventions providing patient feedback, more showed a positive clinical outcome, compared with studies with interventions without feedback. This effect was not seen for pharmacotherapy management outcomes.Conclusions: There is a wide variety of eHealth interventions combining various domains and features to target pharmacotherapy management in asthma or COPD, CVD, and diabetes. Results suggest feedback is key for a positive effect on clinician-reported clinical outcomes. eHealth interventions become more impactful when combining domains.</p

    The Long-term Burden of COPD Exacerbations during Maintenance Therapy and Lung Function Decline

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    Data Sharing Statement The dataset supporting the conclusions of this article was derived from the Clinical Practice Research Datalink (www.cprd.com) and the Optimum Patient Care Research Database (www.opcrd.co.uk). The CPRD has broad National Research Ethics Service Committee (NRES) ethics approval for purely observational research using the primary care data and established data linkages. The OPCRD has ethical approval from the National Health Service (NHS) Research Authority to hold and process anonymized research data (Research Ethics Committee reference: 15/EM/0150). This study was approved by the Anonymized Data Ethics Protocols and Transparency (ADEPT) committee – the independent scientific advisory committee for the OPCRD, and the Independent Scientific Advisory Committee (ISAC) for the CPRD. The authors do not have permission to give public access to the study dataset; researchers may request access to CPRD or OPCRD data for their own purposes. Access to CPRD can be made via the CPRD website (https://www.cprd.com/researcher/) or via the inquiries email [email protected]. Access to OCPRD can be made via the OCPRD website (https://opcrd.co.uk/our-database/data-requests/) or via the inquiries email [email protected]. Funding This study is funded by AstraZeneca. AstraZeneca participated in the study design and reporting.Peer reviewedPublisher PD

    Comparison of adverse events associated with different spacers used with non-extrafine beclometasone dipropionate for asthma

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    The authors would like to extend their acknowledgement to Dr. Antony Hardjojo for proof-reading this manuscript. This study is funded by Chiesi Limited. All relevant data are within the paper and the supporting information files. The dataset supporting the conclusions of this article was derived from the UK Optimum Patient Care Research Database (www.opcrd.co.uk). We do not have permission to give public access to these databases; however, researchers may request access for their own purposes. Request for access to OCPRD can be made via the OCPRD website (https://opcrd.co.uk/our-database/data-requests/) or via the enquiries email [email protected] reviewedPublisher PD

    Diagnostic Performance of a Machine Learning Algorithm (Asthma/Chronic Obstructive Pulmonary Disease [COPD] Differentiation Classification) Tool Versus Primary Care Physicians and Pulmonologists in Asthma, COPD, and Asthma/COPD Overlap

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    Funding The study was funded by Novartis Pharmaceuticals Corporation, East Hanover, NJ, United States. Acknowledgement The studies were funded by Novartis Pharmaceuticals Corporation, East Hanover, NJ, United States. Under the direction of authors, Rabi Panigrahy, Preethi B and Ian Wright (professional medical writers; Novartis) assisted in the preparation of this article in accordance with the third edition of Good Publication Practice (GPP3) guidelines (http://www.ismpp.org/gpp3)Peer reviewedPublisher PD

    Effectiveness, usability and acceptability of a smart inhaler programme in patients with asthma:protocol of the multicentre, pragmatic, open-label, cluster randomised controlled ACCEPTANCE trial

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    Introduction Suboptimal asthma control is associated with incorrect inhaler use and poor medication adherence, which could lead to unfavourable clinical and economic outcomes. Smart inhaler programmes using electronic monitoring devices (EMDs) could support self-management and increase medication adherence and asthma control. However, evidence on long-term benefits and acceptability is scarce. This study aims to investigate the effectiveness of a smart inhaler asthma self-management programme on medication adherence and clinical outcomes in adults with uncontrolled asthma, to evaluate its acceptability and to identify subgroups who would benefit most based on patient characteristics.Methods and analysis This open-label cluster randomised controlled trial of 12 months will be conducted in primary care in the Netherlands. General practices will be randomly assigned to either intervention or control group. We aim to include 242 patients. The intervention consists of (1) an EMD attached to the patient’s inhaler that measures medication use; (2) a smartphone application to set medication reminders, receive motivational messages and track asthma symptoms; and (3) a portal for healthcare professionals to view data on medication use. The control group is passively monitored by the EMD but cannot view their inhaler data or receive feedback. Eligible patients are adults with suboptimal controlled asthma (Asthma Control Questionnaire score ≥0.75) with evidence of non-adherence established by the EMD during a 6-week run-in period. Primary outcome is the difference in mean medication adherence between intervention and control group. Secondary outcomes include asthma control, asthma-related quality of life, exacerbations, acceptance, cost-effectiveness and whether the effect of the intervention on medication adherence and asthma control is modified by patient characteristics (eg, self-efficacy, medication beliefs and eHealth literacy).Trial registration numberNL7854
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