mHealth is becoming an important part of the new healthcare landscape
as smartphones and mobile technology become ubiquitous and mHealth
services are promoted for people’s health and well-being. Healthcare
systems are strained worldwide across the aging population. The
development, proliferation, and utilization of mobile and digital
technologies could be transformative, helping to provide
patient-centered and cost-effective solutions to the challenges. From
chronic diseases to remote consultations with health professionals,
mHealth apps can potentially transform health as we know it.
Fast
forward five years, and there have been more changes to mobile
technology that will transform the healthcare industry, including
faster connectivity, improved data security and despatch of private
and confidential information, and more sophisticated AI that will
enable improved functions to mHealth. Well-utilized mHealth will
become a critical factor in transforming healthcare from reactive to
more efficient preventive and personalized care. The next five years
will see the mHealth sector continue accelerating, bringing major
innovation and growth to the healthcare industry.
This blog
intends to deliver insight and information on the forefront of
developments in the area of mHealth app growth, which systematically
overhauls conventional approaches to healthcare. It will also discuss
how the exciting emergence of AI as an operational part of mHealth
exposes the onset of a new phase of utilization within the industry.
The growth of mHealth (mobile health) over the last decade or so is
unprecedented. Today, millions of people worldwide utilize mHealth
apps to track and manage several health-related functions, from
monitoring fitness goals to managing chronic diseases such as
depression. These apps allow users to access healthcare services from
the luxury of their homes, cars, schools, or offices. There have been
significant advancements in the design of these apps, based on the
data captured over the years, to provide users with care better
tailored to their personal health needs. Many factors, including the
invisible hands of the market and the wider demand for digital health
solutions, have combined to drive the wide acceptance of mHealth
apps.
The market for mHealth apps has been growing strongly and
is expected to grow further through at least the next decade.
According to recent studies, the global mHealth market is estimated to
reach more than $300 billion by 2025, thanks in part to the increasing
shift towards remote healthcare services and the growing demand for
health and wellness solutions. The COVID-19 pandemic undeniably
fuelled this growth, as patients and healthcare providers increasingly
relied on digital tools to provide and enable continuity of care
during lockdowns and social distancing orders. Overall, it seems clear
that the healthcare industry is rapidly digitalizing, with the mHealth
sector poised for continuous growth as more innovative apps are
launched to serve the needs of patients and providers alike.
Among
the most widely used mHealth apps are those in three broad categories:
telemedicine, fitness tracking, and chronic disease management.
Telemedicine apps that allow patients to consult with healthcare
providers online, reducing the need for in-person visits, have seen a
surge in use, making healthcare convenient at the tap of a finger.
Fitness-tracking apps that record patients’ physical activity,
nutrition, and general well-being are widely used by those wanting to
maintain a healthy lifestyle. These apps are especially beneficial for
those with chronic diseases such as diabetes, hypertension, and asthma
as apps for chronic disease management track physical data, provide
reminders, and alert the patient of any deterioration in condition,
enabling timely intervention and improving treatment adherence. These
three major underlying technologies show the expanding role of mHealth
in today’s healthcare system.
AI and machine learning are enabling more personalized and predictive mHealth apps. Algorithms can aggregate large amounts of data about people’s health to provide personalized information and predict diseases or injuries. For example, AI-supported apps can use the information users provide about their activities and wearable data to offer a personalized fitness plan or adjust their dietary regime. Machine learning models are also used for interpreting medical images, for example, in recognizing a tumor, detecting cardiovascular diseases, or analyzing infections. Prominent examples include various diabetes management apps that use AI for predictive analytics of blood sugar levels based on past data and activity schedules for managing chronic conditions.
Wearable technology and the IoT allow mHealth apps to perform real-time data collection and monitoring. Some wearables, such as smartwatches, can collect continuous health data to be synced to a mobile app, which provides health providers and users with actionable insights. IoT medical instruments allow remote monitoring, whereby IoT devices can track vital signs and other health metrics from a distance and alert us of any significant changes. Future applications of the IoT in healthcare will likely see more sophisticated remote monitoring solutions that can provide real-time feedback and intervention, potentially revolutionizing the management of chronic diseases and post-surgery care.
Several innovative and convenient mHealth apps have contributed to a huge leap in the field of telehealth services, allowing patients to bypass the inconvenience of in-person visits to a clinical setting simply by using their smartphones. Mobile apps now allow patients to set up video consultations, send text messages to their doctors, and even get a diagnosis done directly from their homes. In the field of chronic disease management, mHealth apps have also played a pivotal role in improving ongoing care and follow-ups. Specially developed mHealth apps now offer real-time monitoring of key parameters to remotely manage the care of patients with chronic diseases who can’t visit a hospital frequently. Besides remote diagnosis and monitoring services, innovative mHealth apps also include diagnostic tools and treatment-monitoring features for remote patient care.
Since mHealth apps treat and share sensitive health information, data privacy and security have become important areas of concern. An increasing amount of personal health data is being shared and stored on mobile platforms, increasing the risk of unauthorized data breaches. With distributed health data, a need exists to secure access throughout the entire lifecycle of handling, exchanging, and storing. New mHealth apps must incorporate high-level encryption, secure user authentication, and regular security audits. Recent solutions in security include distributed ledger technology (blockchain), a transparent and tamper-proof data management technology. Strict compliance with the Health Insurance Portability and Accountability Act (HIPAA) and General Data Protection Regulation (GDPR) can be beneficial in improving the credibility of mHealth apps that treat sensitive patient data. In the future, mHealth will need consistent innovation in data security to protect health information and to gain increased trust among users.
Another promising use for blockchain technology, given its inherent characteristics for security, transparency, and immutability, is in the way it can transform mHealth by providing more secure, transparent, and immutable management of health data. The very nature of the blockchain, as a decentralized platform with backup algorithms for maintaining the ‘gold standard’ where authorship is not affected, means that records kept on it are securely stored, accessed, and modified only by those who have complete permission to do so. This makes it much more difficult for ‘hackers,’ who attempt to access and exploit valuable health-related information, and much harder for their fraudulent activities to be concealed, greatly reducing the risk of data breaches. Blockchain has already been applied to several mHealth apps to manage consent for data sharing – recording usage, tracking the provenance of data, and enforcing compliance with data protection laws. For example, blockchain-based systems are being set up to store patient records, such as drug stores, and facilitate transparent tracking of accessing and modifications to this data.
AR and VR technologies in medicine and in healthcare are changing the way we live and interact. Clinical medical training is one of the primary applications of this interactive technology, where AR and VR can offer realistic simulations for surgery practice, anatomy education, and procedural training. AR and VR can also provide patients with an engaging and interactive way of understanding their conditions and treatment options. AR and VR have also been shown to be useful in rehabilitation applications thanks to creating an adapted realistic virtual environment for physical therapy and rehabilitation purposes. The utilization of AR/VR in mHealth has many fascinating applications, such as VR-based pain management tools and AR apps to simulate, visualize, and explain medical conditions before and during their treatment.
As more and more mHealth apps come with voice-activated assistants and conversational interfaces, the methods in which patients interact with technology are becoming more and more natural. Voice-activated assistants and conversational interfaces are currently used to enable users to access features of healthcare apps via natural language, such as the ability to schedule appointments, access health information, and receive medication reminders. Voice-activated assistants (such as those supported by virtual health assistants or built into smart devices) might also replace or complement more traditional buttons or keyboards that we use to interact with medical devices. Having a voice-powered assistant that allows for hands-free usage is especially beneficial for people with a disability or for other users who might prefer interactions via natural language. Conversational interfaces might also improve accessibility as they allow natural interactions that could yield system feedback different from traditional interfaces. This added functional level of human interaction could also support healthy patient dialogues and amplify emotional inferences and hidden feelings. In short, both future interfaces could better support patient engagement by making it seem more like a real human interaction.
Undoubtedly, one of the greatest developments in 5G technology is its improved speed and network reliability, both of which will affect the development of mHealth. This connectivity can make mobile health applications even lighter, faster, and more refined. As a result, mHealth apps will be better able to handle massive volumes of data with little latency. Such capabilities will enable real-time data applications and more advanced telemedicine services. With faster speed and lower latency, 5G can support the transmission of high-definition video consultations, the immediate sharing of medical imaging between different doctors or platforms, and the real-time remote monitoring of patients. Additionally, as a new-generation telecommunications technology, 5G will have increased bandwidth and decreased latency that will empower mobile-health devices like AR/VR, Internet of Things (IoT) devices, and more, as well as trigger a wave of innovation of mobile-health applications. This will allow more efficient and effective healthcare provision.
One set of regulatory issues that developers of mHealth apps have to contend with relates to the principles of legal and ethical operation and includes – among others – HIPAA (Health Insurance Portability and Accountability Act) in the United States, which specifies that personally identifiable health data have to be protected; GDPR (General Data Protection Regulation) in Europe, which requires even stricter data protection for every user in the EU; and the regulation of apps which can be considered a medical device by the FDA (Food and Drug Administration), which controls the safety and efficacy of digital health applications. In order to avoid legal issues and serve their users to their expectations, developers have to make sure that the rolling out complies with the regulations listed above – on data security, security of data handling, and testing – from the development stage.
There are multiple challenges in designing intuitive, accessible, and useful mHealth apps that appeal to a wide range of users with various technological backgrounds, ages, health statuses, and disabilities. How to translate complex medical information and medical procedures into user-friendly graphic and audio interactions and how to make apps accessible to users with visual, auditory, and motor impairments are two important challenges. Best practices for achieving these goals include user-centered design, usability testing with real users, following accessibility standards (e.g., WCAG), and providing features such as voice command, large-text options, and screen reader compatibility embedded into apps.
Integrating mHealth apps with ‘legacy’ healthcare systems (e.g., using EHRs) is also a major challenge. Passing data between different, disparate systems will require adherence to standards, using APIs (Application Programming Interfaces) that can communicate with interoperable systems but may use different data models with unique data formats that need translation. Issues such as formatting, real-time synchronization, combining, and making fundamentally diverse information systems work together must all be successful. This can be less of an issue if the data is structured and adheres to ‘the gold standard’ in interoperability (e.g., using industry standards such as HL7 – Health Level Seven – and FHIR – Fast Healthcare Interoperability Resources). From the outset of creating an app, developers must focus on interoperability so their solutions find a place within the broader healthcare landscape.
For mHealth apps to be successful and functional in the long run,
there must be a clear synergy between the mHealth application
developer, the healthcare professional, and the patient. Ideally, the
development of mHealth solutions will be fuelled by the developer’s
technical know-how, healthcare providers’ expertise in medicine and
clinical rationale, and patients’ ability to provide user-centric
invaluable feedback on the usability and effectiveness of the
applications.
For example, the MySugr app was designed with the
help of software developers and experts in diabetes care. This app,
intended to make diabetes management easier, tracks blood sugar
levels, medication, and diet. Because it was built with input from
doctors and patients, MySugr is a widely used, effective,
patient-friendly tool for managing diabetes care.
Another example
of the promises and the pitfalls of this model are organizations such
as the Teladoc Health platform, which combines telehealth services
with various mHealth solutions, including telemedicine systems,
digital pharmacy tools, and remote monitoring of chronic
disease—creating this platform involves working with healthcare
providers to refine the functions to meet clinical requirements and
patient needs while allowing for an effective telemedicine experience.
Partnerships like this are key to building mHealth apps that are
clinically effective and user-friendly.
One of the biggest challenges associated with mHealth is the pace of
innovation because this influences what patients expect from their
apps. Technology and the needs of patients differ between the ‘old’
and ‘new’ worlds, and developers are constantly trying to keep up with
new trends. To remain competitive, mHealth developers are continuously
updating their apps to ensure that they trend, such as artificial
intelligence, immersive wearable technology, and new forms of
connectivity, such as 5G.
Investments in RD, timely updates of
the app based on user feedback, a flexible open technology that allows
easy integration of newer developments and suppliers, and
relationships with Healthcare Providers that begin to afford insights
into the evolving clinical practices and patient needs will be
important for staying ahead in the competitive mHealth market.
Innovation must become part of the DNA in mHealth development,
production, and distribution to suit a rapidly evolving clinical
landscape where value in mHealth can be bought only when the pace of
innovation in the apps meets the pace of population healthcare
innovations.
The future of mHealth is ripe for a transformation if the trends shaping mobile health app development in the next decade are anything to go by: AI, wearables, AR/VR, and 5G hold a lot of promise to take this field to a different level altogether. The apps they power seem poised to become faster, more responsive, more personalized, and better integrated into an individual’s health care. The time-worn issues of compliance, patient experience, data-sharing efficacy, and user experience remain, and navigating them will continue to push health app developers to innovate relentlessly.