Skip to main content
Download PDF

Impact of a digital web-based asthma platform, a real-life study

BMC Pulmonary Medicine volume 23, Article number: 165 (2023) Cite this article

Abstract

Background

Digital health technology (DHT) is a growing area in the treatment of chronic diseases. Study results on DHT’s effect on asthma control have been mixed, but benefits have been seen for adherence, self-management, symptoms, and quality of life. The aim was to evaluate the impact of an interactive web-based asthma treatment platform on asthma exacerbations and health care visits.

Methods

In this real-life study, we retrospectively collected data on adult patients registered on a web-based interactive asthma treatment platform between December 2018 and May 2021. Patients who activated their accounts were active users, and patients who did not were inactive users and considered as controls. We compared the number of exacerbations, total number of exacerbation events defined as the sum of oral corticosteroid (OCS) and antimicrobial courses, emergency room visits, hospitalizations, and asthma-related health care visits before and one year after the registration on the platform. Statistical tests used included the t-test, Pearson’s chi-square test and Poisson regression models.

Results

Of 147 patients registered on the platform, 106 activated their accounts and 41 did not. The active users had significantly fewer total number of exacerbation events (2.56 per person years, relative decline 0.78, 95% CI 0.6 to 1.0) and asthma-related health care visits (2.38 per person years, relative decline 0.84, 95% CI 0.74 to 0.96) than before registration to the platform, whereas the reductions in health care visits and the total number of exacerbation events were not significant in the inactive users.

Conclusions

An interactive web-based asthma platform can reduce asthma-related health care visits and exacerbations when used actively.

Peer Review reports

Introduction

Bronchial asthma is an airway disease affecting over 300 million people worldwide [1, 2]. Self-management and adherence are important in the prevention of exacerbations, and both remain a challenge in asthma treatment [3]. Financial issues, inadequate knowledge about medication, fear of adverse events, motivation, attitudes, and communication problems may represent barriers for effective asthma self-management [4]. The growth of telehealth and digital health technology (DHT) has provided technological solutions for the treatment of chronic diseases [5, 6]. Examples of telehealth solutions in asthma treatment include mobile health via smartphone apps, electronic reminders to improve inhaler adherence, telemedicine with personal asthma treatment instructions, inhaler trackers, and clinical decision support systems [6, 7].

The results of using DHT to improve asthma treatment adherence have been mixed, and some studies have reported nonsignificant effects [8]. A systematic review showed improvements in asthma self-care, quality of life, and medication use with digital interventions but no benefit for lung function or health service use. Poorly described interventions have made it difficult to identify effective types of interventions [9]. A recent study showed a reduction in emergency room visits and hospital stays with the use of asthma inhalator monitors, [10] while an audiovisual reminder improved adherence with inhaled corticosteroids in adult asthma in another study [11].

A study published in 2016 showed that use of an asthma smartphone app improved asthma control test (ACT) scores and lung function measured by forced expiratory volume in one second (FEV1) [12]. In contrast, a review published in 2013 stated concerns about the evidence on the use of mobile apps in asthma self-management due to conflicting results in randomized controlled trials and a high risk of bias [13]. Interventions that combine several types of DHT have been associated with better asthma control and fewer symptoms [5, 14, 15].

The aim of this study was to evaluate in a real-life setting the benefits of a digital web-based asthma treatment platform in asthma control, measured according to exacerbations, the total number of exacerbation events, and the number of visits to the asthma clinic.

Methods

The digital asthma platform

In 2018, the asthma clinic at Helsinki University Hospital, Skin and Allergy Hospital, started using a digital asthma platform alongside the traditional treatment of adult asthma patients receiving specialist care. The platform is a web-based tool used by health care professionals and asthma patients. It is an electronic interactive website consisting of information about asthma, self-care instructions, symptom diaries, an exacerbation questionnaire, and a facility to message health care professionals (Table 1).

Table 1 Digital asthma platform contents
Full size table

The asthma platform was developed by asthma nurses and specialists in the asthma clinic (MD, specialists in respiratory medicine and allergology), utilizing the Finnish Current Care Guidelines and Global Initiative for Asthma (GINA) guideline [16, 17]. The platform is one of several disease specific platforms used in specialist care in the hospital district and part of a large network of public information about different diseases (Health Village, [18]). Any patient can visit the network, but to get access to the functions of the digital asthma platform described above, patients need to be registered to the platform by health care professionals. Adult asthma patients that receive and stay in specialist care are registered on the digital asthma platform (My Path, [19]) if they meet one of the following criteria: (1) Asthma diagnosed according to international guidelines at the asthma clinic at Helsinki University Hospital, Skin and Allergy Hospital [20], (2) need of comprehensive guidance and support in asthma self-care, or (3) use of biological therapy for asthma. The patients also must agree to registration, be motivated to and capable of using a web-based intervention and have visited a pulmonary specialist in the asthma clinic. To start using the platform, patients need to activate their accounts on the platform. The activation is documented, as are questionnaires, asthma diary notes, and messages sent by the patients on the platform.

Patients and study design

This was a retrospective real-life study that included all adult patients registered on the digital asthma platform in the asthma clinic of Helsinki University Hospital, Skin and Allergy Hospital, between December 2018 and May 2021. Patients that did not continue in specialist care were either initially not registered to the asthma platform, or if registered but the specialist care discontinued between December 2018 and May 2021, not included in this study. The patients were separated into a treatment group comprising the registered patients who activated their account on the digital asthma platform (active users) and a control group consisting of registered patients who never activated their account (inactive users).

We retrospectively collected the data from electronic patient records and the digital asthma platform and compared need of OCS and antimicrobial agents, exacerbations, total number of exacerbation events and asthma related health care visits one year before and after registration on the asthma platform. The baseline data included age (when added to the digital asthma platform), sex, body mass index, comorbidities, lung function measured by FEV1 and forced vital capacity (FVC), smoking and allergy status, serum immunoglobulin E (IgE) concentration, and asthma medication. Asthma medication was documented as the inhaled corticosteroid dose and the need for additional therapy, including long-acting beta-agonists, long-acting anticholinergics, montelukast, theophylline, and continuous oral corticosteroids (OCS). We also documented the use of biological therapies for asthma. Asthma medication was classified according to the GINA, from step 1 to step 5 treatment [16].

The data on asthma control were collected from electronic patient records for the period of one year before and one year after a patient’s registration on the digital asthma platform. The follow-up time was defined as the number of days between an asthma related health care visit closest to one year before registration and registration to the platform, and as the number of days between registration and an asthma related health care visit closest to one year after registration. The data collected included OCS courses, antimicrobial courses for respiratory tract infections, hospitalizations and emergency room visits due to asthma, exacerbations, and visits to the asthma polyclinic. A course of OCS was defined as at least a doubling of a possible continuous OCS dose for at least three days or, in patients without continuous OCS, as a course of OCS lasting three days at minimum. We accepted both the OCS and antimicrobial courses prescribed by asthma clinic physicians and other doctors outside the asthma clinic such as general practitioners and we did not separate these. If no baseline spirometry tests or serum IgE measurements were conducted within one year before the patient’s registration on the digital asthma platform, we accepted older spirometry values and serum IgE concentrations and chose the closest to when the patients were registered on the platform.

We documented exacerbations. An individual exacerbation was defined as an entity, where asthma symptoms increase and together with use of SABA and at least one of the following (1) a course of OCS or (2) antimicrobics for respiratory tract infections or (3) an emergency room visit or (4) hospitalization. We documented for each patient the total number of exacerbation events, which was defined as the sum of OCS courses, antimicrobial courses for respiratory tract infections and emergency room visits and hospitalizations associated with asthma before and after registration on the digital asthma platform.

Visits to the asthma polyclinic or health care visits associated with asthma were defined as patient-health professional appointments for asthma, where the health professional was a pulmonology specialist or a pulmonology specialist in training in the hospital district, a nurse specialized in asthma treatment, or an emergency room physician when the emergency room visit was associated with asthma. Because of the coronavirus pandemic, some scheduled asthma clinic appointments were replaced with video or phone appointments. These appointments were included and considered equal to physical visits.

The spirometry reference values were changed in Finland during the study period from liters and percentages of predicted values to liters and z-scores [21]. Due to this change, we report spirometry values in liters.

Research approval was granted for this study by the Institutional review board of Helsinki University Hospital, Skin and Allergy Hospital (approval number HUS/3371/2019). Because this study was retrospective, ethical approval was not necessary.

Statistical analysis

The data are expressed as mean and standard deviation (SD), median and interquartile range (IQR), or count and percentage (%), as appropriate. Missing data was handled by using available-case analysis. We did not perform imputation for missing data, and we included only patients with information on the assessed variable. Statistical comparisons between the inactive and active groups were performed with the t-test and Pearson’s chi-square test. The incidence rate, incidence rate ratio (IRR), and relative change were calculated using Poisson regression models. Poisson regression is a generalized linear model used to model count data with Poisson distribution and a log link function. The Poisson regression models were tested using the goodness-of-fit test, and the assumptions of overdispersion in models were tested using the Lagrange multiplier test. In cases of violation of the assumptions (e.g., non-normality), a bootstrap-type method was used for the continuous variables, and Monte Carlo p-values (small number of observations) were used for the categorical variables. The Stata 17.0 (StataCorp LP; College Station, Texas, USA) statistical package was used for the analysis.

Results

Baseline characteristics

Altogether, 166 adult patients with asthma were registered on the digital asthma platform of the Helsinki and Uusimaa Hospital District, Skin and Allergy Hospital between December 2018 and May 2021 and included in this study. Of these, 119 patients activated their account on the platform (active users), and 47 did not (inactive users). Thirteen patients were excluded from the active users and six patients from the inactive users due to insufficient data or discontinued treatment in specialist care. Finally, 106 active users (mean age 47 years) and 41 inactive users (mean age 45 years) remained in the study (Fig. 1).

Fig. 1
figure 1

Flow chart of included patients

Full size image

A total of 113 of the patients registered on the digital asthma platform were female (77%); 80 (75%) women and 26 of 34 (76%) men activated their account on the platform. Sex did not significantly affect the patients’ activity on the platform (Table 2). Of the registered patients who activated their accounts, 49 (46%) sent messages, 39 (37%) used the asthma diary, and 42 (40%) replied to exacerbation questionnaires. Thirty (28%) active users used none of these functions (Table 3). The mean age of active users with interaction (messages, asthma diary or exacerbation questionnaires) was 47 (SD 12) years. Similarly, the mean age of active users but without interaction was 46 (SD 15) years (the difference between the groups was not significant, p = 0.71). The patients’ messages on the platform included questions about medication and self-care, the coronavirus pandemic, vaccinations, appointments, adverse events of biological and other asthma medications, prescription requests, and queries on whether to seek help at the emergency room.

Table 2 Baseline characteristics of asthma patients before registration on the digital asthma platform
Full size table
Table 3 Interaction on the digital asthma platform among the patients who activated their account after being registered on the platform
Full size table

A total of 77% of the registered patients had never smoked, and smoking status did not significantly differ between the active and the inactive platform users. Reflux was the only comorbidity where active and inactive platform users differed; a greater proportion of active users suffered from reflux compared to inactive users (p = 0.03) (Table 2). The patients who activated their platform account seemed to suffer from more severe asthma at baseline than the inactive platform users. The active users needed 1.84 times as many OCS courses (95% confidence interval [CI] 1.14 to 2.96, p = 0.012), had 3.4 times as many emergency room visits (95% CI 1.04 to 11.12, p = 0.043), experienced 1.76 times as many exacerbations (95% CI 1.11 to 2.79, p = 0.016), and had 1.9 times as many total number of exacerbation events (95% CI 1.21 to 3.00, p = 0.006) at baseline as the inactive users (Table 4). Conversely, the mean ACT scores before platform registration did not differ significantly between the active (17.1/25) and inactive (17.2/25) platform users (Table 2).

Table 4 OCS and antimicrobial courses, emergency room visits, hospitalizations, exacerbations, total number of exacerbation events, and health care visits due to asthma per person years in active and inactive platform users before and during registration on the asthma platform
Full size table

More than half (56%) of the patients were taking GINA step 5 medication before being registered on the digital asthma platform, and the proportion of patients taking GINA step 5 medication was higher among the patients who activated their platform account (41% vs. 62%, p = 0.024). Twenty-seven patients (18%) used continuous OCS at registration to the platform, but there was no significant difference between the proportion of OCS users among the active and the inactive platform users. The proportion of patients receiving biological asthma therapy before registration on the platform was similar among the active and the inactive users (26% active users vs. 22% inactive users, p = 0.58) (Table 2).

Impact on exacerbations and health care visits

The median follow-up time (IQR) before registration on the asthma platform was 0.9 (0.7, 1.0) years for the inactive users and 1.0 (0.7, 1.0) years for the active users. At the time of the analysis, after having registered on the platform, the median follow-up time was 0.9 (0.7, 1.0) years for the inactive users and 0.9 (0.7, 1.1) years for the active users.

The patients who activated their platform account had statistically significantly fewer health care visits due to asthma than before registration on the platform after adjustment for the follow up time (relative decline 0.84, 95% CI 0.74 to 0.96), whereas the reduction in health care visits was not significant in the patients who did not activate their account (relative decline 0.96, 95% CI 0.76 to 1.2). The number of active users (n = 106) was 2.5 times higher than inactive users (n = 41) and the confidence interval was narrower for the group of active users. The confidence intervals were partly but not totally overlapping and the difference between the active and inactive users was small. Among the active platform users, the number of total exacerbation events reduced significantly (relative decline 0.78, 95% CI 0.6 to 1.0) compared to before registration, and the reduction of exacerbations (relative decline 0.80, 95% CI 0.64 to 1.01) approached statistical significance. There was a significant reduction in the inactive users’ exacerbations (relative decline 0.41, 95% CI 0.25 to 0.96), but the reduction in the total number of exacerbation events in this group was not significant (relative decline 0.52, 95% CI 0.21 to 1.29). (Fig. 2). Although a significant reduction in total number of exacerbation events and health care visits was seen among the active asthma platform users, the reduction did not significantly differ from the reduction in the group of inactive platform users (Fig. 2). Lung function, measured as FEV1 did not change during use of the DHT (change of FEV1 was + 0.1 L (95% CI -0.0 to 0.1) in the active users’ group and + 0.1 L (95% CI -0.0 to 0.2) in the inactive users’ group. In addition, the difference between the groups was non-significant.

Fig. 2
figure 2

Relative changes and confidence intervals for health care visits, exacerbations, and total number of exacerbation events (defined as OCS and antimicrobial courses, emergency room visits, and hospitalizations) in the active and inactive platform users before and during registration on the digital asthma platform

Full size image

Discussion

In this study, the digital asthma platform significantly reduced total number of exacerbation events and asthma-related health care visits among the patients who activated their accounts on the platform, compared to before registration.

Results on DHT use in chronic diseases have been somewhat mixed. A meta-review showed conflicting results from telemonitoring in asthma and chronic obstructive pulmonary disease (COPD). Some studies showed a positive effect of DHT interventions on self-management and disease control, while others did not [22]. A systematic review suggested that digital platforms could benefit self-management in noncommunicable diseases such as cardiovascular diseases, diabetes, and COPD, [23] while another review showed no benefits of digital interventions for the diabetes disease course [24]. Lander et al. suggest that evaluations of web-based interventions should consider the evidence base for the content, the structure including data safety and qualifications of trainers and authors, and impact of the intervention [25]. The digital asthma platform evaluated in this study is developed by asthma nurses and specialists in respiratory medicine and allergology, and in concordance with Finnish and international asthma treatment guidelines and thus, has evidence-based content. The platform was constructed as part of the web- based Health Village My Paths which is widely used at Helsinki University Hospital. A cellphone-based application was not available when digital health-pathway to asthma was designed.

The impact of the platform on asthma exacerbations and asthma related health care visits was beneficial in this study.

In this study, the patients who were registered to the asthma platform and activated their accounts seemed to suffer from more severe asthma at baseline than the patients who did not activate their accounts. More severe asthma might motivate patients to use telehealth interventions to facilitate control of their disease. However, more studies on what kind of patients are likeliest to use and be suitable for telehealth are still needed. In the literature, patients seem to find digital health solutions useful in the treatment of chronic diseases. In a randomized controlled trial from 2018, asthma patients reported being satisfied with the use of electronic inhaler sensors and a digital health platform and found these digital health interventions useful [26]. A study evaluating adolescents with asthma or diabetes found that over 50% of the participants had previously searched for health information online, and 79% intended to use at least one health-related website [27]. In a cross-sectional study, parents of children with asthma reported satisfaction with an interactive website on pediatric asthma [28]. These findings indicate a desire for DHT in chronic disease management. In a study involving patients with chronic respiratory diseases, patients showed the highest acceptance for DHT solutions that facilitated booking appointments with physicians, viewing laboratory test results and educational material, and renewing prescriptions [29]. In our study, we did not evaluate patient reported satisfaction with DHT.

The growing number of mobile apps provides potential for asthma treatment. Mobile apps have increased asthma control in adults, in some studies to a greater extent than web-based interventions [5, 30]. Interventions that combine several types of DHT have been associated with increased asthma control [5]. We consider that the possibility to interact with health care personnel to receive personal guidance might have influenced mostly to decrease the number of asthma-related health care visits in our study. Probably better knowledge of asthma and asthma treatment together with personal messages might influence and decrease the total number of exacerbation events.

This study’s results showed that men and women activated their accounts in equal numbers on the digital asthma platform, even though more women were registered to the platform by health care professionals. Income, education, and social status are factors that might influence the use of DHT and access to equipment necessary for use of DHT. The lack of this data is a limitation of this study, as information about income, education and socioeconomic status might help to select patients most suitable for DHT [31]. The heterogenicity of questions sent via the platform shows the wide variety of problems asthma patients face in their daily lives and the potential of digital tools to quickly solve these problems.

The strengths of this study were its real-life setting, inclusion of a control group, and detailed description of the functions of the digital asthma platform intervention in this study (see Table 1). A limitation of this study is its retrospective design. We hypothesized that the effectiveness of DHT might be noticed in more severe asthma control measurements such as exacerbations and did not use FEV1 as a predefined outcome measure. ACT score or similar is not included in the asthma DHP and thus we were not able to use this measurement although it would have been an interesting information and should be measured in the future studies. Further, medication compliance in detail was not included in the study and cannot be reported although it is one of the factors that may affect asthma control. Even if pharmacy purchases would be traced it does not confirm that patients use the medication and thus there would still be uncertainties in the medication compliance. The coronavirus pandemic also led to the replacement of some appointments with virtual appointments (mostly phone calls).

Patients were categorized into active and inactive users according to whether they activated their account on the platform or not. However, 28% of patients who activated their account had no interaction on the platform and therefore might not have used it at all. On the other hand, these patients may have benefit from getting disease specific information about asthma and advice on treatment on the platform without answering questionnaires or sending messages on the platform.

The fact that all the patients who were registered on the digital asthma platform were receiving specialist care at the asthma clinic of Helsinki University Hospital might have influenced this study’s results for asthma control. Treatment in specialist care alone could have improved asthma control without the impact of the digital asthma platform [32,33,34,35]. However, both groups (active and inactive users) were treated in the same asthma clinic and can be assumed to have received similar asthma care. We assume that the results of this study can be applicable for patients treated for asthma in specialist care. Treatment in specialist care might explain why the inactive platform users also showed a reduction in exacerbations. Biological therapy has been shown to improve asthma control [36,37,38], and may partly explain the improved asthma control after follow-up in both groups. On the other hand, there was no statistically significant difference in the use of biological therapy between the active and the inactive platform users.

Although there is evidence for the positive effects of eHealth on asthma control and other chronic diseases, there is still limited information about what specific digital intervention is effective. Studies are often heterogeneous, and interventions poorly described, making implementation in real life challenging. Also, very little information is available on the possible adverse effects of digital interventions [6, 9, 39]. Studies about which patients are most suitable for digital interventions are lacking. All these topics need further research. However, digital interventions have a major advantage: possibility to remote consultation which may be time saving for both the patient and the doctor or the nurse. Because of a real-life study setting, we did not have a possibility to include any preplanned economic analysis in our study.

Conclusions

The patients who activated their digital asthma platform accounts had more OCS courses, exacerbations and emergency room visits before registration on the platform than the patients who did not activate their accounts. During follow-up, the reduction in health care visits and the total number of exacerbation events was significant only among the active platform users.

Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request with an additional study permission application.

Abbreviations

ACT:

Asthma control test

CI:

Confidence interval

COPD:

Chronic obstructive pulmonary disease

DHT:

Digital health technology

FEV1:

Forced expiratory volume in one second

FVC:

Forced vital capacity

GINA:

Global Initiative for Asthma

IgE:

Immunoglobulin E

OCS:

Oral corticosteroids

References

  1. Chung F, Wenzel SE, Brozek JL, Bush A, Castro M, Sterk PJ, et al, Erratum, Wenzel SE, Brozek JL, Bush A, Castro M, Sterk PJ, Adcock IM, Bateman ED, Bel EH, et al. Eugene R Bl Eur Respir J. 2018;52(1):13993003.

    Google Scholar 

  2. To T, Stanojevic S, Moores G, Gershon AS, Bateman ED, Cruz AA et al. Global asthma prevalence in adults: Findings from the cross-sectional world health survey. Vol. 12, BMC Public Health. 2012.

  3. Williams LK, Peterson EL, Wells K, Ahmedani BK, Kumar R, Burchard EG et al. Quantifying the proportion of severe asthma exacerbations attributable to inhaled corticosteroid nonadherence. J Allergy Clin Immunol. 2011;128(6).

  4. Peláez S, Lamontagne AJ, Collin J, Gauthier A, Grad RM, Blais L et al. Patients’ perspective of barriers and facilitators to taking long-term controller medication for asthma: A novel taxonomy. BMC Pulm Med. 2015 Apr 25;15(1).

  5. Unni E, Gabriel S, Ariely R. A review of the use and effectiveness of digital health technologies in patients with asthma. Vol. 121, Annals of Allergy, Asthma and Immunology.American College of Allergy, Asthma and Immunology; 2018. 680–691e1.

  6. Alvarez-Perea A, Dimov V, Popescu F, Zubeldia JM. The applications of eHealth technologies in the management of asthma and allergic diseases. Clin Transl Allergy [Internet]. 2021 Sep 6;11(7). Available from: https://onlinelibrary.wiley.com/doi/https://doi.org/10.1002/clt2.12061.

  7. Bonini M, Usmani O. Novel methods for device and adherence monitoring in asthma. Curr Opin Pulm Med. 2018 Jan;24(1):63–9. https://doi.org/10.1097/MCP.0000000000000439.

  8. Schulte MHJ, Aardoom JJ, Loheide-Niesmann L, Verstraete LLL, Ossebaard HC, Riper H. Effectiveness of eHealth Interventions in Improving Medication Adherence for Patients With Chronic Obstructive Pulmonary Disease or Asthma: Systematic Review. J Med Internet Res [Internet]. 2021 Jul 27;23(7):e29475–e29475. Available from: https://pubmed.ncbi.nlm.nih.gov/34313593.

  9. Morrison D, Wyke S, Agur K, Cameron EJ, Docking RI, MacKenzie AM, et al. Digital asthma self-management interventions: a systematic review. Journal of Medical Internet Research. Volume 16. JMIR Publications Inc.; 2014.

  10. Merchant R, Szefler SJ, Bender BG, Tuffli M, Barrett MA, Gondalia R, et al. Impact of a digital health intervention on asthma resource utilization. Volume 11. World Allergy Organization Journal. BioMed Central Ltd; 2018.

  11. Charles T, Quinn D, Weatherall M, Aldington S, Beasley R, Holt S. An audiovisual reminder function improves adherence with inhaled corticosteroid therapy in asthma. J Allergy Clin Immunol. 2007 Apr;119(4):811–6.

  12. Cook KA, Modena BD, Simon RA. Improvement in Asthma Control Using a Minimally Burdensome and Proactive Smartphone Application. J Allergy Clin Immunol Pract 2016 Dec 11;4(4):730–737e1.

  13. Marcano Belisario JS, Huckvale K, Greenfield G, Car J, Gunn LH. Smartphone and tablet self management apps for asthma. Vol. 2017, Cochrane Database of Systematic Reviews. John Wiley and Sons Ltd; 2013.

  14. van Sickle D, Magzamen S, Truelove S, Morrison T. Remote Monitoring of Inhaled Bronchodilator Use and Weekly Feedback about Asthma Management: An Open-Group, Short-Term Pilot Study of the Impact on Asthma Control. PLoS ONE. 2013 Feb 27;8(2).

  15. Barrett MA, Humblet O, Marcus JE, Henderson K, Smith T, Eid N, et al. Effect of a mobile health, sensor-driven asthma management platform on asthma control. Ann Allergy Asthma Immunol. 2017 Nov;119(1):415–421e1.

  16. 2019 GINA. Main Report - Global Initiative for Asthma - GINA [Internet]. Available from: https://ginasthma.org/gina-reports/.

  17. Keuhkol S, Lastenl S, Lastenl S, Kliinisen S, Yhdistys F. Astma. 2022;1–28.

  18. Health Village. Available from: www.terveyskyla.fi/en.

  19. My Path. Available from: www.terveyskyla.fi/en/mypath.

  20. Louis R, Satia I, Ojanguren I, Schleich F, Bonini M, Tonia T, et al. European respiratory society guidelines for the diagnosis of asthma in adults. European Respiratory Journal. Volume 60. European Respiratory Society; 2022.

  21. Kainu A, Timonen KL, Vanninen E, Sovijärvi AR. Reference values of inspiratory spirometry for Finnish adults. Scand J Clin Lab Invest [Internet]. 2018;78(4):245–52. Available from: https://doi.org/10.1080/00365513.2018.1439185.

  22. Hanlon P, Daines L, Campbell C, Mckinstry B, Weller D, Pinnock H. Telehealth interventions to support self-management of long-term conditions: A systematic metareview of diabetes, heart failure, asthma, chronic obstructive pulmonary disease, and cancer. J Med Internet Res. 2017;19(5).

  23. Tighe SA, Ball K, Kensing F, Kayser L, Rawstorn JC, Maddison R. Toward a Digital Platform for the Self-Management of Noncommunicable Disease: Systematic Review of Platform-Like Interventions. J Med Internet Res [Internet]. 2020 Oct 28;22(10):e16774. Available from: http://www.jmir.org/2020/10/e16774/.

  24. Pal K, Eastwood SV, Michie S, Farmer A, Barnard ML, Peacock R, et al. Computer-based interventions to improve self-management in adults with type 2 diabetes: a systematic review and meta-analysis. Diabetes Care. Volume 37. American Diabetes Association Inc.; 2014. pp. 1759–66.

  25. Lander J, Drixler K, Dierks M-L, Bitzer EM. How do publicly available allergy-specific web-based Training Programs conform to the established criteria for the reporting, methods, and content of evidence-based (Digital) Health Information and Education: thematic content evaluation. Interact J Med Res. 2019;8(4):e12225.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Merchant R, Inamdar R, Henderson K, Barrett M, Su JG, Riley J et al. Digital health intervention for asthma: Patient-reported value and usability. JMIR mHealth uHealth. 2018 Jun 1;6(6).

  27. Chisolm DJ, Hardin DS, McCoy KS, Johnson LD, McAlearney AS, Gardner W. Health literacy and willingness to use online health information by teens with asthma and diabetes. Telemed J E Health. 2011;17(9):676–82.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Ansari R, Ahmadian L, Harandi NB, Developing. andEvaluating Parents’ Satisfaction with a Website to Manage Pediatric Asthma.

  29. Duplaga M. The acceptance of e-health solutions among patients with chronic respiratory conditions. Telemed e-Health 2013 Sep 1;19(9):683–91.

  30. Licskai CJ, Sands TW, Ferrone M. Development and pilot testing of a mobile health solution for asthma self-management: Asthma action plan smartphone application pilot study. Can Respir J. 2013;20(4):301–6.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Dobransky K, Hargittai E. Inquiring minds acquiring wellness: uses of online and offline sources for health information. Health Commun. 2012;27(4):331–43. https://doi.org/10.1080/10410236.2011.585451. Epub 2011 Sep 20. PMID: 21932982.

    Article  PubMed  Google Scholar 

  32. Wu TD, Brigham EP, McCormack MC. Asthma in the primary care setting. Medical Clinics of North America. Volume 103. W.B. Saunders; 2019. pp. 435–52.

  33. Schatz M, Zeiger RS, Mosen D, Apter AJ, Vollmer WM, Stibolt TB, et al. Improved asthma outcomes from allergy specialist care: a population-based cross-sectional analysis. J Allergy Clin Immunol. 2005 Dec;116(6):1307–13.

  34. Erickson S, Tolstykh I, Selby JV, Mendoza G, Iribarren C, Eisner MD. The impact of allergy and pulmonary specialist care on emergency asthma utilization in a large managed care organization. Health Serv Res. 2005 Oct;40(5 I):1443–65.

  35. Van Der Meer AN, Pasma H, Kempenaar-Okkema W, Pelinck JA, Schutten M, Storm H et al. A 1-day visit in a severe asthma centre: Effect on asthma control, quality of life and healthcare use. Eur Respir J [Internet]. 2016;48(3):726–33. Available from: https://doi.org/10.1183/13993003.00220-2016.

  36. Normansell R, Walker S, Sj M, Eh W, Nair P. Omalizumab for asthma in adults and children (Review). Cochrane Libr. 2014;(1).

  37. Darveaux J, Busse WW. Biologics in Asthma-The Next Step Toward Personalized Treatment. J Allergy Clin Immunol Pract [Internet]. 2015;3(2):152–60. Available from: https://doi.org/10.1016/j.jaip.2014.09.014.

  38. Rabe KF, Nair P, Brusselle G, Maspero JF, Castro M, Sher L, et al. Efficacy and safety of Dupilumab in glucocorticoid-dependent severe asthma. N Engl J Med. 2018 Jun;28(26):2475–85.

  39. Jeminiwa R, Hohmann L, Qian J, Garza K, Hansen R, Fox BI. Impact of eHealth on medication adherence among patients with asthma: a systematic review and meta-analysis. Respiratory Medicine. Volume 149. W.B. Saunders Ltd; 2019. pp. 59–68.

Download references

Acknowledgements

Special thanks to Kaisa Ojala and Minna Järvenpää for being responsible for the use of the digital asthma platform in the asthma clinic and helping this paper’s authors with practical matters regarding the platform.

Funding

Open Access funding provided by University of Helsinki including Helsinki University Central Hospital. This work was supported by the Medical Society of Finland, the Finnish Anti-Tuberculosis Foundation, the Mjolbolsta Foundation, Helsinki University Hospital Research Funds, and the Ida Montin Foundation.

Author information

Authors and Affiliations

  1. Allergic Diseases, Skin and Allergy Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland

    Emma M. Genberg, Hilkka T. Viitanen, Mika J. Mäkelä & Paula M. Kauppi

  2. Pulmonary Department, University of Helsinki and Helsinki University Hospital, Helsinki, Finland

    Emma M. Genberg & Paula M. Kauppi

  3. Primary Health Care Unit, Kuopio University Hospital, Kuopio, Finland

    Hannu J. Kautiainen

  4. Folkhälsan Research Center, Helsinki, Finland

    Hannu J. Kautiainen

Authors
  1. Emma M. Genberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hilkka T. Viitanen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mika J. Mäkelä
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hannu J. Kautiainen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Paula M. Kauppi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

EG and PK were responsible for the study design. EG and HV contributed to the data collection, EG, PK, and HK contributed to the data analysis and interpretation, and EG, HV, PK, HK, and MM contributed to writing the manuscript. All authors reviewed the manuscript.

Corresponding author

Correspondence to Emma M. Genberg.

Ethics declarations

Ethics approval and consent to participate

Research approval was granted for this study by the Institutional review board of Helsinki University Hospital, Skin and Allergy Hospital (approval number HUS/3371/2019). This study was conducted as a retrospective register study and thus the above-mentioned approval was needed but an ethical committee approval was not necessary. All use of human data was performed in accordance with relevant guidelines and regulations (Helsinki declaration). This was a retrospective registry study and thus consent to participate was not needed.

Consent to publish

Not applicable (this study does not include identifiable data).

Competing interests

The authors report no conflicts of interest concerning this work.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Genberg, E.M., Viitanen, H.T., Mäkelä, M.J. et al. Impact of a digital web-based asthma platform, a real-life study. BMC Pulm Med 23, 165 (2023). https://doi.org/10.1186/s12890-023-02467-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12890-023-02467-8

Keywords

BMC Pulmonary Medicine

ISSN: 1471-2466

Contact us