The impact of digital health tools on the study of asthma

By March 13, 2019 March 31st, 2019 Mobile Health

Asthma is a chronic respiratory disease affecting millions of people worldwide and has a global economic burden of more than 50 billion dollars. Asthma patients suffer from shortness of breath, chest tightness, coughing and wheezing, all of which needs to be managed life-long. Although asthma cannot be treated, it can be kept under control by a combination of drugs including Beta-blockers, corticosteroids, leukotriene modifiers etc.

Research Techniques for Studying Asthma

Asthma is a globally prevalent condition that has been a hot topic for research for decades. Traditionally, data collection on asthma has been a complicated process requiring investigations from multiple resources. Some of the sources for data collection include:

  1. Population Census: National Health Interview Survey
  2. Asthma patient directed surveys and questionnaires
  3. Clinical trials for asthma management
  4. Hospital discharge and admission surveys
  5. Emergency Department Asthma Assessment and Management Form
  6. Health care used by asthma patients

These processes require long duration, diligence and large manpower. Such data may still be inaccurate or lost due to the long complicated process. However, in the era of digitization, data collection can be done by much simpler and convenient methods.

Installation of free applications on the mobile phone of patients can be done to collect data [1] on asthma prevalence, activity limitation, days of work or school lost, rescue and control medication use, asthma self-management education, physician visits, emergency department visits and hospitalizations due to asthma. Data collected using digital tools are not only convenient but also significantly improves accuracy.

Incorporating the use of sensors and data recording while examining patients in outpatient department during regular general physicians visit can be another useful data collection method for asthma study. Along with this, adding sensors with automatic data collection digital tools to home-based self-management applications could also be used for asthma study purposes.

The Adaptation of Software in the Field of Asthma for Research

The available digital tools can have two major applications. It can be used to collect data for asthma research and can also be used as a guide for physicians on any required changes in treatment modalities. These tools can assess information on episodes of acute exacerbations, the number of hospital visits, patient knowledge of inhaler techniques and overall epidemiology of asthma prevalence. These tools are not only beneficial for the patients, but they also are excellent for researching patient demographics and patient’s medical compliance at home. They can also help physicians better educate their patients by understanding the mistakes asthma patients make when it comes to using their medications at home without a doctor’s assistance. The main purpose of this article is to educate researchers on the various digital health tools that are used to study asthma and how it can be useful to them.

A new innovative technology, electronic inhalers equipped with sensors has been recently gaining popularity for its ability to accurately record data. This technology also has great potential as a tool in studying asthma for research.

Use of Sensors

Electronic sensors combined with inhalers can be highly useful to document a patient’s progress before and after treatment. This can be done by monitoring the spirometry values, detecting the frequency of inhaler use, and the time period of peak use.

Electronic inhaler sensors were used in a study[4] to track medication usage as well as gather information by acting as an effective digital tool to conduct studies on asthma treatment and efficacy. The study analyzed asthma control, device usability, user-friendly nature and value of the technology. It concluded that electronic sensors combined with a digital health platform had reports of high customer satisfaction. Most patients perceive high value in such devices and sought long-term continued use of digital health platforms for asthma control. Ease of use and convenience was found to be a major influencing factor amongst patients’ preference for continued usage of the digital tools.

Similarly, in another study,[5] residents of a specific area with asthma received electronic inhaler sensors which assessed medication dosage, time and frequency of medication required for a period of 30 days. After completion of the 30-day mark, patients took part in a self-management digital health intervention to enhance at home treatment and prevention of asthma episodes. The study analyzed the progress achieved in outcomes by taking into account the number of daily Short Acting Beta Agonists (SABA), days with and without symptoms, and the degree of control over asthma through a period starting from the initial 30-day baseline to the following months. A significant improvement was observed with a 39% reduction in the mean number of SABA event, and 12% increment in the number of days without symptoms. This improvement was observed to increase over time in the subsequent months with an overall improvement in asthma control.

Recently, Sema4, a patient-centered predictive health company, and the Mount Sinai Health System have collaborated with Sanofi on a five-year study of almost 1,200 asthma patients. The study was developed to analyze the potential in incorporating digital tools to collect research data on Asthma. It will employ connected apps with sensors to analyze the difference in the effects of asthma on different individuals while also collecting clinical, genomic and environmental data.

Apps for Asthma Management

Currently, there are many apps with varying functions to assess data from patients regarding asthma symptoms, exacerbations and their management. Vigorous study and evaluation are required to assess the feasibility of using mobile applications as a tool to obtain data for clinical studies.

The Asthma Mobile Health Study

A wide scale study was initiated in 2015 using an application that was uploaded on the apple store. Since the beginning of the research, this application has been downloaded by more than 50,000 iPhone users. The app collected information via surveys on the varying ways asthma patients dealt with their disease, as well as the various treatments methods employed by each patient. The results of the study were compared to a control group of asthma patients to analyze the accuracy of patient-reported data. Further details into the research such as research objectives, data collected, potential, methodology, have been described below.[2]

Target Population

Individuals over 18 with asthma confirmed by a doctor, taking medications for asthma, not pregnant and living in the United States.

Total Participants

7,593

Methodology

The study collected data remotely via smartphones from 7,593 participants that included many patients with severe asthma via

  1. Surveys
  2. Structured tasks, including a personal journal of symptoms and triggers logged in manually
  3. Passive monitoring of activity and local air quality via personal input of this information by the patients

Research Objectives

  1. To assess the association between app use and asthma control, quality of life and health care utilization scores.
  2. To develop and validate the medical accuracy of an algorithm for personalized trigger avoidance.

Data collected

The data collection was multidimensional using mediums such as surveys and devices over a period of 6 months. Data were collected on patients regarding their asthma triggers, geolocation, and air quality of their location. These data were collected by obtaining information inputted manually by the patients, acquiring patient’s geolocation information via their mobile GPS, and through surveys.

Study Findings

Initial study results reported heat, pollen and wildfires to be significant triggers for asthma exacerbation episodes. The study’s multidimensional data collection method enabled high quality collection of data by correlating interrelated variables.

Dr. Sam Pejham’s AsthmaMD App for Research

Dr. Sam Pejham is a pediatric specialist who developed a free application- AsthmaMD that allows users to manually log their asthma activity, their medications and triggers of their asthma in the form of a diary. The app was designed with the intention of researching the risk factors that trigger asthma and the potential ways to avoid them. In addition to this, the study assesses the effectiveness of different medication dosage during each asthma episode and the frequency of asthma exacerbation. Let us look further into the study with a short description of each aspect of the research.[3]

Target Population

Asthma patients of all ages across the world

Methodology

The application keeps a record of asthma patients by allowing patients to manually record their asthma activity, their medications and causes of their asthma as a medical journal.

Data collected

  1. Asthma journal of symptoms, spirometry results ( FEV1, PEF, Spo2) and medications used
  2. Record of asthma triggers: Allergies, Pollens, Pollutants etc.

Potential

AsthmaMD is designed to help asthma patients while also gathering anonymous data to aid researchers with information about the causes and external correlation of asthma. It also solves the issue of privacy by allowing AsthmaMD users to optionally opt-in and to allow the application to securely send encrypted and anonymous data.

Pediatric Respiratory Assessment Measure (PRAM)

The PRAM was designed by the Ontario Lung Association with dual purposes. The app assists patients in self-managing their asthma and collects data for research purposes. It uses a scoring system to analyze the severity of symptoms and provide a plan for acute care. Here are the available details regarding the app’s potential for research purposes.

Target Population

Pediatric Asthma patients (1-17 years old)

Methodology

It rapidly calculates a score based on clinical findings recorded by the patient into the platform. The collected data then provides the score which gives an idea about the level of asthma severity.

Data collected

PRAM employs a scoring system of 12 points to objectively assess the degree of asthma severity. It collects information on 5 major clinical findings in episodes of acute exacerbation including oxygen saturation, suprasternal retractions, scalene muscle use, air entry and wheezing.

Potential

Offered by Ontario lung association,Since 2015, within the first 3 years of release, this app had over 1000 downloads and is still available for download. It can aid researchers to obtain information on patient’s condition and treatment methodology during acute exacerbation. Although no study has yet been conducted regarding the effectiveness of the app, it shows potential in being utilized as a tool for collecting data for research purposes.

SaniQ Asthma App

SaniQ asthma allows patients to record their medical data in the form of a daily medical journal. The individualized data collection allows the collection of data in a more accurate manner by removing subjective data collector bias. Although no study has yet been conducted on the usage of this app for research, it shows some promising potential as a digital tool for study. The following information can further aid in understanding the app’s effectiveness as a research tool.

Target Population

Asthma patients of all ages across the world

Methodology

SaniQ asthma app allows patients to record their medical data in the form of a daily medical journal.

Data collected

  1. Documentation of maximum exhalation rate (peak flow), one-second capacity (FEV1), weight & oxygen saturation
  2. Recording of medical measurements via Bluetooth using compatible measuring devices or by manual input

Potential

The individualized data collection allows the collection of data in a more accurate manner by removing subjective data collector bias. Data collected by such methods greatly reduce research costs, labor and time.

Challenges Faced With the Use of Digital Tools for Studying and Monitoring Asthma

The major limitations in using digital tools to study asthma include

  1. Selection bias and identity uncertainty: Studies conducted via apps rely heavily on participants for data and may result in biased data collection. Data provided by manual input from the patients can be false or exaggerated. There is no way of differentiating true data from false ones.
  2. Design limitations: The apps have a major downside as they do not implement any techniques for managing stress or offer any form of motivational intervention. Due to this impersonalized nature of the apps, long-term data collection is inhibited as patients tend to stop application usage after a short period.
  3. Long term retention: Digital tools are currently not widely used in clinical practice of Asthma due to the additional expense as well as limited awareness among the physicians and patients. Very few apps for Asthma have been designed with an intent to aid researchers to collect information and are mostly directed towards helping patients in self-management.
  4. Patient privacy: When apps are used to collect data from patients, the issue of privacy and confidentiality is the same as in a doctor-patient relationship. There is a high likelihood of patient privacy being breached while using their personal data for research. Misuse of patient information obtained from apps may lead to possible privacy lawsuits.

Recommendations for Developing Digital Tools for Asthma

  1. Users logging in the app can be requested to provide some form of identification and remove selection bias and identity uncertainty. Along with valid identification, medical proof of their existing asthma condition could further assist in validating the authenticity of each patient and the information provided by them.
  2. As stated before, asthma needs to be managed lifelong and becomes a part of the patient’s lifestyle. However, long-term continued usage of the apps has been found to be relatively limited. Perhaps the distant nature and automated response of the apps limit the development of a long-term attachment and result in early detachment from engaging in the app. A virtual online coach to guide the patients personally could vastly prolong patient’s engagement duration of the apps. Long-term app usage can be very helpful to collect information on long-term asthma control.
  3. Physicians should be encouraged to use digital tools such as electronic sensors while performing spirometry tests on patients. Only when digital tools are widely used, can they be reliable sources of accurate data collection for asthma study.
  4. The monitoring of patient symptoms by apps relies on information provided by the patients which can often be incorrect and unreliable. Utilizing the latest technology by integrating electronic inhaler sensors into apps has good potential to accurately record data for study.

Conclusion

Digital tools enhance widespread involvement of participants by eliminating limitations of geographical barriers, facilitate multi-dimensional assessments, and collect objective data.  As smartphone usage and technology advancement is increasing globally, the use of digital tools in Asthma study has huge potential.

References

  1. Asthma Surveillance Data. Retrieved from https://www.cdc.gov/asthma/asthmadata.htm
  2. Yu-Feng Yvonne Chan, Pei Wang, Linda Rogers, Nicole Tignor, Micol Zweig, Steven G Hershman, Nicholas Genes, Erick R Scott, Erick Krock, Marcus Badgeley, Ron Edgar, Samantha Violante, Rosalind Wright, Charles A Powell, Joel T Dudley. The Asthma Mobile Health Study, a large-scale clinical observational study using ResearchKit (2017, March 13) Retrieved from https://journals.lww.com/academicmedicine/fulltext/2017/02000/The_Use_of_Smartphones_for_Health_Research.15.aspx
  3. Sam Pejham, UCSF Medical School Clinical Faculty and Director of Tri-Valley Pediatrics. Asthma Management App(AsthmaMD) Retrieved from https://www.asthmamd.org/about/
  4. Meredith A.Barrett., Kelly Henderson.,Olivier Humblet.,Justine E.Marcus., Ted Smith., NemrEi., J. Wesley Sublett., AndrewRenda., Laquandra Nesbitt., David Van Sickle.,David Stempel., James L.Sublett. Effect of a mobile health, sensor-driven asthma management platform on asthma control (2017, November 5) Retrieved from https://www.sciencedirect.com/science/article/pii/S1081120617306415#
  5. Merchant R., Inamdar R, Henderson K, Barrett M, Su JG, Riley J, Van Sickle D, Stempel D. Digital Health Intervention for Asthma: Patient-Reported Value and Usability. (2018, June 4) Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/29866644
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