Modern technologies such as Artificial Intelligence are the ultimate drivers behind current mobile healthcare initiatives. Its applications in healthcare apps are the catalyst of the mass adoption they've had these past years.
By now, it’s an irrefutable fact that the demand for mobile healthcare services is growing exponentially. For some years now, we have witnessed the birth of digital healthcare and medical-care delivery via remote interactions that are available anytime and anywhere. However, there is still an ever-increasing need for healthcare solutions that enable easier access and promote more efficient care delivery. This increase is becoming overbearing, especially now that the world is experiencing a shortage of healthcare professionals. Consequently, using tools such as AI in healthcare apps has become a need to propel mobile healthcare forward.
Mobile healthcare growth has to be leveraged by adequate technologies and proper IT infrastructure so that the essence of mobile healthcare isn’t lost in poor digital operations. As a result, most healthcare institutions and professionals struggle to keep up with the technological implementations and patients’ high expectations regarding remote, faster, and more successful outcomes. Luckily, modern advancements in mobile and wireless technology, and their melding with Artificial Intelligence (AI) tools, have laid the groundwork for the emergence of current on-demand mobile healthcare solutions.
AI-powered tools have become paramount for the healthcare ecosystem and have undeniably propelled the mobile initiatives currently in trend. Studies have shown that the AI-powered healthcare market will grow from USD 4.9 billion in 2020 to USD 45. 2 billion by 2026, which corresponds to a 44.9 % CAGR. Rightfully so, it’s safe to say that Artificial Intelligence is finding successful applications in the mobile healthcare environment. This hype will soon accelerate even more, and AI-powered tools and mobile devices will become interdependent as AI keeps on driving remote healthcare delivery forward.
AI as a Propeller of Mobile Healthcare
AI in healthcare apps means using large amounts of data through AI-powered tools such as machine learning algorithms to perform specific tasks automatically and produce more efficient remote healthcare operations and delivery outcomes. These outcomes result in successful patient recovery, monitoring, positive drug research outcomes, assistance in administrative tasks, or educational resources and simulators.
As a result, patients now have access to medical services in their homes and can play an active role in their treatments and conditions. Doctors can ease their workload and have a 360-degree view of each patient while also having access to learning tools, simulators, and calculators. Pharma companies also benefit from AI by using it to develop new drugs, test existing ones, manage personnel, or for educational purposes. Moreover, AI is merging with mobile devices to bring breakthroughs to the mobile healthcare sector. Hence, healthcare app developers are responsible for successfully creating the matrimony between AI and mobile technologies.
Additionally, AI’s cost savings benefits are an essential driver for its implementation in healthcare apps. According to Accenture, clinical health AI tools can create $150 billion in annual savings for the US healthcare economy by 2026. A large part of these cost reductions stems from AI’s ability to change the healthcare delivery model from a passive to a proactive approach; thus, helping medical professionals and pharma focus on health management and prevention rather than disease control. This approach, primarily brought on by AI applications, can result in fewer hospitalizations and less expensive treatments. Likewise, AI-based mobile technology will have a pivotal role in public health management via constant monitoring, ensuring earlier and more efficient diagnoses, personalized treatments, and more effortless follow-ups.
Let’s look at some of the ways AI can leverage remote health monitoring and other medical tools relevant to healthcare apps.
AI is synonymous with efficiency and speed in the digital healthcare sector. Artificial Intelligence has become essential in medical diagnosis because it provides valuable help with medical decision-making, disease management, treatment monitoring, and the overall workflow that leads to successful patient outcomes. These benefits translate into what is referred to as automated diagnosis. With automated diagnosis, AI tools such as machine learning can automatically diagnose diseases, triage findings in imaging such as x-rays, detect abnormalities in tests, and help with the overall management of chronic diseases, both in-hospital and remotely. Programmers train these AI-based tools to analyze medical data patterns to find the outliers and markers that define a diseased or healthy image. Furthermore, developers can synchronize these technologies with patients’ EHRs (electronic health records) to further enhance their benefits and provide more personalized diagnoses.
These AI applications in mobile healthcare solutions show immense promise in shifting the paradigm of manual diagnosis and can alleviate the workload of medical professionals across the globe. Moreover, these AI systems are highly scalable, and they can constantly grow and adapt to the needs of patients and stakeholders.
Healthcare apps that incorporate AI-powered tools can deliver diagnosis straight to the patient by analyzing images and test results, thus annulling the need for in-person visits or doctor interpretation. This way, AI in healthcare apps has evolved to become the second pair of eyes that is always available and doesn’t need to rest. It provides overworked doctors and congested facilities invaluable support by minimizing physician workload and promoting remote care delivery. Patients can play an active role in monitoring their conditions through apps. Doctors can manage chronic care patients remotely while dedicating more time to providing crucial care to critically ill individuals.
Patients are open to managing their health conditions, and outcomes may improve when they are aware of their illnesses and engaged in their care. However, it’s time-consuming and sometimes impossible for doctors to constantly communicate with each patient, especially when physicians are already overwhelmed. Luckily, AI-powered healthcare apps can help doctors deliver high-quality automated care to their patients. One of these AI-powered tools is chatbots. We engage with chatbots every day without even realizing it, from catching up on the news to navigating banking or retail applications. For healthcare apps, though, the impact and benefits are far more profound.
Chatbots, or AI-powered health assistants, are software-based agents that developers program with Natural Language Processing (NLP), sentiment analysis, and machine learning algorithms to engage in conversation and provide real-time assistance. Patients chat with chatbots the same way they would with a doctor or pharma agent. They can list their symptoms, personal information, medicines, and even previous diagnoses or illnesses. And as just a doctor would answer, chatbots can ask follow-up questions and give patients personalized assistance and a complete assessment of their health condition and recommendations. They can answer questions regarding billing, scheduling appointments, and medication refills. As a result, patients can obtain automated assistance anywhere, anytime, while doctors can relieve workload and have more time to focus on crucial tasks.
Chatbots are one of the main drivers of healthcare’s digital transformation. They have helped developers transform healthcare apps from simple information sources into interactive platforms for active healthcare delivery. Furthermore, they can promote patient engagement by replacing rigid medical interfaces and static content with more dynamic, flexible, and friendly interactions. Therefore, they help programmers deliver a more engaging, authentic, and innovative healthcare app that allows stakeholders to achieve better outcomes via automated treatment and engage patients in their treatments.
Intelligent Electronic Health Records (EHR)
Historically, health records have always been physician-oriented and usually lack patient-based functionalities, blocking them from engaging in their treatment. However, one of the primary goals of medical apps is to promote patient engagement via self-management and improve their health outcomes. EHR target this need; they are a digital version of a patient’s medical history. EHRs store medical data and can also include demographic data, administrative data, or socioeconomic data.
The knowledge extracted from EHRs can leverage medical decisions, help create epidemiological and predictive models, manage public health, and even aid in disease pattern recognition. However, physicians were spending large amounts of time entering data manually into EHRs. A 2017 study found that doctors spent 6 hours of an 11.4-hour workday in patients’ EHRs per weekday. Thankfully, AI tools have melded with EHRs to produce intelligent EHRs. Intelligent EHRs are a way of employing AI tools to interpret, predict, calculate, and help patients understand their conditions and doctors to manage them remotely.
AI-powered technologies, such as Natural Language Processing, can be programmed to extract knowledge from EHRs and interpret it to provide insights and conclusions regarding patients’ health conditions. Using NLP in healthcare apps that handle EHRs can help doctors swiftly perform document searches, enter data, analyze EHR data, produce predictive models, and even use voice-enabled technology to enter information. Intelligent EHRs also enable patients to track their health conditions without visiting a medical facility, which gives providers a means to share information remotely and free their time for more pressing situations.
In the digital healthcare realm, intelligent electronic health records are the most efficient way to improve data filing and enable healthcare providers to rapidly enter, access, and share patient information. AI-powered EHRs also help doctors provide faster and more accurate diagnoses, access educational resources, and get appointment reminders. For patients, they can enable prescription refill, lab results, imaging, immunizations, and schedule appointments, all from the comfort of their homes.
AI-Powered Precision Medicine
Precision medicine is an emerging approach for personalized disease treatment and prevention. It considers a patient’s genomic variations, environment vulnerability, age, environment, gender, race, lifestyle, family history, and immune profile. Applying AI-powered analytics to these datasets allows researchers and healthcare providers to identify patterns, determine treatment effectiveness, and identify the genetic markers related to treatment success or failure. Moreover, precision medicine can tailor medical interventions based on disease profile, previous or current diagnostic or prognostic information, and their treatment response rates. In other words, it allows doctors and researchers to accurately predict which treatment strategy will work best for a particular patient.
The objective of using precision medicine in healthcare apps and medical software is to merge it with AI-powered technologies to potentialize its benefits for stakeholders. Also, precision medicine uses individual profiles rather than population biology, which means that the mobile scenario is the perfect environment for precision medicine to be milked. Collecting and storing medical data from individuals is inherent to healthcare apps, which sets the ground for AI to analyze and interpret said data. This interpretation depends on AI-powered tools, such as machine learning, deep learning, and artificial neural networks (ANN). These computer systems are fed data and programmed to observe and analyze the source’s data (app, software, website, IoT devices). They can efficiently identify patterns, establish treatment programs, and predict disease risk, all based on the analysis and interpretation of an individual’s medical data.
AI-powered precision medicine offers a realistic path to faster illness recovery and longevity. It can also reduce healthcare costs, improve physician burnout, counteract adverse drug reactions, and even make genetics-based diet recommendations. This way, using AI tools to drive precision medicine in healthcare apps is a great way to potentialize tailored treatments that are more effective and save more lives.
This point may be an obvious one, but here it is one more time: data security in healthcare apps is paramount. In 2020, hacking incidents exposed sensitive healthcare information from 24.1 million breached records. Another study tested 100 healthcare apps and found that 71% of them have at least one high-level security vulnerability. These figures are grim, but luckily, AI has become a savior for developers to enforce the proper security measures and enhance the ones already in place.
AI can help automate security processes at a much faster rate than is humanly possible. Additionally, the number of daily malware threats worldwide increased by 5.2% to reach 360,000 in 2020. These malware threats grow exponentially, and IT experts can no longer manually keep up with them. Most of the time, IT security experts work by detecting the signatures of specific malware threats. However, their growth is outpacing what developers can realistically do to stop them. Here’s where AI and machine learning come into play in the healthcare security scenario.
Developers can program machine learning algorithms and AI tools to help proactively search and identify hacking threats. Using historical data, these AI tools can learn to recognize hacking and malware patterns even when the destructive program is unknown. Once the threat is detected, AI-powered systems can alert security experts or be designed to take autonomous action against the threat. Furthermore, leaving these security tasks to AI-based programs reduces the financial strain from breaches, and it helps development teams use their human resources more efficiently.
These applications of AI in healthcare apps and their security are becoming increasingly necessary for data protection and regulatory compliance. AI promotes the faster evaluation of data coming and going between patients, doctors, pharma, and hospitals via connected devices. It can also help manage access to these devices and monitor user behavior within the app to grant or deny permissions. Moreover, AI programs deliver a more proactive approach to security as it helps developers detect abnormal behaviors as they happen instead of waiting for them to access the data. This way, developers can identify and stop the attacks before they become a problem.
Healthcare apps that leverage AI could empower patients to take part in their health conditions, which will inevitably lead to better outcomes. AI can also help doctors accomplish better patient outcomes by assisting them in making more accurate diagnoses, identifying high-risk patients, managing their time and dedication to crucial endeavors, and ultimately saving more lives. Hospitals and pharma companies can also benefit from AI by using it to help manage administrative resources, forecast drug research outcomes, model potential research projects, and better understand how medications will impact patients. The ultimate goal of using AI is to give patients the freedom to manage their health conditions while freeing up time for the doctors to perform their more crucial and urgent tasks without burning out.