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Beydon N, Taillé C, Corvol H, Valcke J, Portal JJ, Plantier L, Mangiapan G, Perisson C, Aubertin G, Hadchouel A, Briend G, Guilleminault L, Neukirch C, Cros P, Appere de Vecchi C, Mahut B, Vicaut E, Delclaux C. Digital Action Plan (Web App) for Managing Asthma Exacerbations: Randomized Controlled Trial. J Med Internet Res 2023; 25:e41490. [PMID: 37255277 PMCID: PMC10365576 DOI: 10.2196/41490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 11/30/2022] [Accepted: 02/28/2023] [Indexed: 03/06/2023] Open
Abstract
BACKGROUND A written action plan (WAP) for managing asthma exacerbations is recommended. OBJECTIVE We aimed to compare the effect on unscheduled medical contacts (UMCs) of a digital action plan (DAP) accessed via a smartphone web app combined with a WAP on paper versus that of the same WAP alone. METHODS This randomized, unblinded, multicenter (offline recruitment in private offices and public hospitals), and parallel-group trial included children (aged 6-12 years) or adults (aged 18-60 years) with asthma who had experienced at least 1 severe exacerbation in the previous year. They were randomized to a WAP or DAP+WAP group in a 1:1 ratio. The DAP (fully automated) provided treatment advice according to the severity and previous pharmacotherapy of the exacerbation. The DAP was an algorithm that recorded 3 to 9 clinical descriptors. In the app, the participant first assessed the severity of their current symptoms on a 10-point scale and then entered the symptom descriptors. Before the trial, the wordings and ordering of these descriptors were validated by 50 parents of children with asthma and 50 adults with asthma; the app was not modified during the trial. Participants were interviewed at 3, 6, 9, and 12 months to record exacerbations, UMCs, and WAP and DAP use, including the subjective evaluation (availability and usefulness) of the action plans, by a research nurse. RESULTS Overall, 280 participants were randomized, of whom 33 (11.8%) were excluded because of the absence of follow-up data after randomization, leaving 247 (88.2%) participants (children: n=93, 37.7%; adults: n=154, 62.3%). The WAP group had 49.8% (123/247) of participants (children: n=45, 36.6%; mean age 8.3, SD 2.0 years; adults: n=78, 63.4%; mean age 36.3, SD 12.7 years), and the DAP+WAP group had 50.2% (124/247) of participants (children: n=48, 38.7%; mean age 9.0, SD 1.9 years; adults: n=76, 61.3%; mean age 34.5, SD 11.3 years). Overall, the annual severe exacerbation rate was 0.53 and not different between the 2 groups of participants. The mean number of UMCs per year was 0.31 (SD 0.62) in the WAP group and 0.37 (SD 0.82) in the DAP+WAP group (mean difference 0.06, 95% CI -0.12 to 0.24; P=.82). Use per patient with at least 1 moderate or severe exacerbation was higher for the WAP (33/65, 51% vs 15/63, 24% for the DAP; P=.002). Thus, participants were more likely to use the WAP than the DAP despite the nonsignificant difference between the action plans in the subjective evaluation. Median symptom severity of the self-evaluated exacerbation was 4 out of 10 and not significantly different from the symptom severity assessed by the app. CONCLUSIONS The DAP was used less often than the WAP and did not decrease the number of UMCs compared with the WAP alone. TRIAL REGISTRATION ClinicalTrials.gov NCT02869958; https://clinicaltrials.gov/ct2/show/NCT02869958.
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Affiliation(s)
- Nicole Beydon
- Unité Fonctionnelle de Physiologie-Explorations Fonctionnelles Respiratoires, Institut National de la Santé et de la Recherche Médicale 938, Centre de Recherche Saint Antoine, Hôpital Armand Trousseau, Assistance Publique Hôpitaux de Paris, F-75012, Paris, France
| | - Camille Taillé
- Service de Pneumologie et Centre de Référence Constitutif des Maladies Pulmonaires Rares, Hôpital Bichat, Assistance Publique Hôpitaux de Paris, Institut National de la Santé et de la Recherche Médicale 1152, Université Paris Cité, F-75018, Paris, France
| | - Harriet Corvol
- Service de Pneumologie Pédiatrique, Hôpital Armand Trousseau, Assistance Publique Hôpitaux de Paris, Institut National de la Santé et de la Recherche Médicale Centre de Recherche Saint-Antoine, Sorbonne Université, F-75012, Paris, France
| | - Judith Valcke
- Service de Pneumologie, Hôpital Européen Georges Pompidou, Assistance Publique Hôpitaux de Paris, F-75015 Paris, Hôpital Privé Armand Brillard, F-94130, Paris, France
| | - Jean-Jacques Portal
- Clinical Research Unit Saint-Louis Lariboisière, Assistance Publique Hôpitaux de Paris, Université de Paris Cité, F-75010, Paris, France
| | - Laurent Plantier
- Département de Pneumologie et Explorations Fonctionnelles Respiratoires, Centre Hospitalier Universitaire de Tours, Institut National de la Santé et de la Recherche Médicale unité 1100, Université de Tours, F-37000, Tours, France
| | - Gilles Mangiapan
- Service de Pneumologie, Centre Hospitalier Interrégional de Créteil, F-94010, Créteil, France
| | - Caroline Perisson
- Service de Pneumologie Pédiatrique, Hôpital Armand Trousseau, Assistance Publique Hôpitaux de Paris, Institut National de la Santé et de la Recherche Médicale Centre de Recherche Saint-Antoine, Sorbonne Université, F-75012, Paris, France
| | - Guillaume Aubertin
- Centre de pneumologie et d'allergologie de l'enfant, F-92100, Boulogne Billancourt, France
| | - Alice Hadchouel
- Service de Pneumologie Pédiatrique, Centre de Référence pour les Maladies Respiratoires Rares de l'Enfant, Hôpital Universitaire Necker-Enfants Malades, Assistance Publique Hôpitaux de Paris, Université de Paris Cité, F-75015, Paris, France
| | - Guillaume Briend
- Service de Pneumologie, Centre hospitalier de Pontoise, F-95303, Cergy Pontoise, France
| | - Laurent Guilleminault
- Département de Pneumologie et Allergologie, Centre Hospitalo-Universitaire Purpan, Centre National de la Recherche Scientifique U5282, Institut National de la Santé et de la Recherche Médicale U1291, Toulouse Institute for Infectious, Inflammatory Disease, Toulouse, France
| | - Catherine Neukirch
- Service de Pneumologie et Centre de Référence Constitutif des Maladies Pulmonaires Rares, Hôpital Bichat, Assistance Publique des Hôpitaux de Paris, Institut National de la Santé et de la Recherche Médicale 1152, F-75018, Paris, France
| | - Pierrick Cros
- Département de Pédiatrie, Hôpital Universitaire Morvan, F-29200, Brest, France
| | | | | | - Eric Vicaut
- Clinical Research Unit Saint-Louis Lariboisière, Assistance Publique Hôpitaux de Paris, Université de Paris Cité, F-75010, Paris, France
| | - Christophe Delclaux
- Service de Physiologie Pédiatrique-Centre du Sommeil, Hôpital Robert Debré, Assistance Publique Hôpitaux de Paris, Institut National de la Santé et de la Recherche Médicale NeuroDiderot, Université de Paris Cité, F-75019, Paris, France
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Chan A, De Simoni A, Wileman V, Holliday L, Newby CJ, Chisari C, Ali S, Zhu N, Padakanti P, Pinprachanan V, Ting V, Griffiths CJ. Digital interventions to improve adherence to maintenance medication in asthma. Cochrane Database Syst Rev 2022; 6:CD013030. [PMID: 35691614 PMCID: PMC9188849 DOI: 10.1002/14651858.cd013030.pub2] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND Asthma is the most common chronic lung condition worldwide, affecting 334 million adults and children globally. Despite the availability of effective treatment, such as inhaled corticosteroids (ICS), adherence to maintenance medication remains suboptimal. Poor ICS adherence leads to increased asthma symptoms, exacerbations, hospitalisations, and healthcare utilisation. Importantly, suboptimal use of asthma medication is a key contributor to asthma deaths. The impact of digital interventions on adherence and asthma outcomes is unknown. OBJECTIVES To determine the effectiveness of digital interventions for improving adherence to maintenance treatments in asthma. SEARCH METHODS We identified trials from the Cochrane Airways Trials Register, which contains studies identified through multiple electronic searches and handsearches of other sources. We also searched trial registries and reference lists of primary studies. We conducted the most recent searches on 1 June 2020, with no restrictions on language of publication. A further search was run in October 2021, but studies were not fully incorporated. SELECTION CRITERIA We included randomised controlled trials (RCTs) including cluster- and quasi-randomised trials of any duration in any setting, comparing a digital adherence intervention with a non-digital adherence intervention or usual care. We included adults and children with a clinical diagnosis of asthma, receiving maintenance treatment. DATA COLLECTION AND ANALYSIS We used standard methodological procedures for data collection. We used GRADE to assess quantitative outcomes where data were available. MAIN RESULTS We included 40 parallel randomised controlled trials (RCTs) involving adults and children with asthma (n = 15,207), of which eight are ongoing studies. Of the included studies, 30 contributed data to at least one meta-analysis. The total number of participants ranged from 18 to 8517 (median 339). Intervention length ranged from two to 104 weeks. Most studies (n = 29) reported adherence to maintenance medication as their primary outcome; other outcomes such as asthma control and quality of life were also commonly reported. Studies had low or unclear risk of selection bias but high risk of performance and detection biases due to inability to blind the participants, personnel, or outcome assessors. A quarter of the studies had high risk of attrition bias and selective outcome reporting. We examined the effect of digital interventions using meta-analysis for the following outcomes: adherence (16 studies); asthma control (16 studies); asthma exacerbations (six studies); unscheduled healthcare utilisation (four studies); lung function (seven studies); and quality of life (10 studies). Pooled results showed that patients receiving digital interventions may have increased adherence (mean difference of 14.66 percentage points, 95% confidence interval (CI) 7.74 to 21.57; low-certainty evidence); this is likely to be clinically significant in those with poor baseline medication adherence. Subgroup analysis by type of intervention was significant (P = 0.001), with better adherence shown with electronic monitoring devices (EMDs) (23 percentage points over control, 95% CI 10.84 to 34.16; seven studies), and with short message services (SMS) (12 percentage points over control, 95% CI 6.22 to 18.03; four studies). No significant subgroup differences were seen for interventions having an in-person component versus fully digital interventions, adherence feedback, one or multiple digital components to the intervention, or participant age. Digital interventions were likely to improve asthma control (standardised mean difference (SMD) 0.31 higher, 95% CI 0.17 to 0.44; moderate-certainty evidence) - a small but likely clinically significant effect. They may reduce asthma exacerbations (risk ratio 0.53, 95% CI 0.32 to 0.91; low-certainty evidence). Digital interventions may result in a slight change in unscheduled healthcare utilisation, although some studies reported no or a worsened effect. School or work absence data could not be included for meta-analysis due to the heterogeneity in reporting and the low number of studies. They may result in little or no difference in lung function (forced expiratory volume in one second (FEV1)): there was an improvement of 3.58% predicted FEV1, 95% CI 1.00% to 6.17%; moderate-certainty evidence); however, this is unlikely to be clinically significant as the FEV1 change is below 12%. Digital interventions likely increase quality of life (SMD 0.26 higher, 95% CI 0.07 to 0.45; moderate-certainty evidence); however, this is a small effect that may not be clinically significant. Acceptability data showed positive attitudes towards digital interventions. There were no data on cost-effectiveness or adverse events. Our confidence in the evidence was reduced by risk of bias and inconsistency. AUTHORS' CONCLUSIONS Overall, digital interventions may result in a large increase in adherence (low-certainty evidence). There is moderate-certainty evidence that digital adherence interventions likely improve asthma control to a degree that is clinically significant, and likely increase quality of life, but there is little or no improvement in lung function. The review found low-certainty evidence that digital interventions may reduce asthma exacerbations. Subgroup analyses show that EMDs may improve adherence by 23% and SMS interventions by 12%, and interventions with an in-person element and adherence feedback may have greater benefits for asthma control and adherence, respectively. Future studies should include percentage adherence as a routine outcome measure to enable comparison between studies and meta-analysis, and use validated questionnaires to assess adherence and outcomes.
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Affiliation(s)
- Amy Chan
- Centre for Behavioural Medicine, Department of Practice and Policy, UCL School of Pharmacy, University College London, London, UK
- School of Pharmacy, The University of Auckland, Auckland, New Zealand
- Asthma UK Centre for Applied Research, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Anna De Simoni
- Wolfson Institute of Population Health, Centre for Primary Care Asthma UK Centre for Applied Research, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Vari Wileman
- Centre for Behavioural Medicine, Department of Practice and Policy, UCL School of Pharmacy, University College London, London, UK
| | - Lois Holliday
- Wolfson Institute of Population Health, Centre for Primary Care Asthma UK Centre for Applied Research, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Chris J Newby
- Research Design Service, University of Nottingham, Queen's Medical Centre, Nottingham, UK
| | - Claudia Chisari
- Centre for Behavioural Medicine, Department of Practice and Policy, UCL School of Pharmacy, University College London, London, UK
| | - Sana Ali
- School of Pharmacy, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - Natalee Zhu
- School of Pharmacy, The University of Auckland, Auckland, New Zealand
| | | | | | - Victoria Ting
- School of Pharmacy, The University of Auckland, Auckland, New Zealand
| | - Chris J Griffiths
- Asthma UK Centre for Applied Research, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
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