Social distancing, lockdowns, pandemic or COVID-19 outbreak, the words you and I are tired of hearing and reading, but in a true sense, these things have brought a huge change in the world and the way it operated.
Talking about the technology and the healthcare industry, the wake of social distancing has made people shift towards online healthcare to get them treated without stepping out of their safe zone.
The surge of remote healthcare combining the power of technology and healthcare knowledge has acted as adrenaline to increase the usage of Telemedicine apps in the world.
Looking at the revenue numbers of the existing Telemedicine apps like Maple, Babylon, PlushCare, and MDLIVE, the entrepreneur’s interest in developing such apps have seen a 3X rapid growth.
For such aspiring investors, here is the basic information on the Telemedicine app technological needs to understand before taking a plunge into the telemedicine app development process.
List of technologies used in Telehealth app development
● Artificial Intelligence
AI technology works on stimulating intelligence into machines (telehealth app development), here these programmed machines recognize and learn the patterns like the human mind does to process the machine actions accordingly.
Healthcare industry tools like Telemedicine use this power of AI to enhance the user experience.
Chatbot feature: As doctors are not available online 24/7 to answer the questions of the patients, an AI-based chatbot feature of the Telemedicine app helps the patients to get answers to their queries at any time of the day with the FAQ’s that are researched and embedded into the application. The app also uses natural language processing to improve the machine learning process to serve the patients with the most asked queries.
Implementing the AI learning process, the app can improve its diagnosis and treatment recommendation by monitoring cases of different patients to enhance its algorithm and deliver better treatment.
AI also helps in automating certain reparative tasks like entering data into EMR to reduce doctors’ workload.
● Big Data technology
There is a huge amount of patient data generated each day in the form of patient reports, data collected from wearable health tech gadgets, and the various smart devices that play a role in the healthcare industry.
Telemedicine apps with the help of Big Data technology utilize this information to analyze and process it to understand different patterns and derive some valuable solutions that can be used to improve healthcare service to take it to the next level. The insights from the big data analyses can be used to produce better outcomes by understanding flaws in the system to redefine the Telemedicine app working model.
Telemedicine apps are designed on the concept of remote healthcare. As the patient and the doctors are connected through a network, the data is transferred in the form of video and voice calls need to be secured.
Blockchain technology ensures that the sensitive patient’s data is well encrypted to protect it from any data breach activity. Basically, this technology is the answer to all the questions that arise on the data security of Telemedicine apps. The exchange of information through the telemedicine apps is thus secured by encrypted packets of blockchain.
● Cloud storage
The remote facility of Telemedicine is supported by cloud services. The need for access and the storage of data from any time anywhere is because of the way it is stored in a cloud.
The usage of cloud services in Telemedicine improves the security and privacy controls of the telemedicine app and also improves apps response time as the data can be fetched easily in no time from the cloud servers attached to the app.
The secured cloud infrastructure makes storage and transfer of electronic health records and patients images efficient through the distributed data services.
● AR & VR
Telemedicine apps use video app features and tools to diagnose patients. VR technology plays a great role in revolutionizing the communication medium to improve the interaction between the patients and doctors with its 3D video facilities.
Implementing Augmented reality in the Telemedicine app can help the doctors to operate more efficiently to have augmented reality conference calls to discuss a patient case and check the reports using the digital interface.
Considering remote healthcare as a modern way of treating patients, the implementation of IoT technology in wearable tech apps helps them to monitor patients’ healthcare data in real-time. These measures are stored and recorded in the wearable health tech devices and are connected to Telemedicine apps to provide this data to respective doctors.
Fitness trackers, pulse checkers, stress meters, all of these features of the app creates an automatic report to help the doctor keep a check on the patient and suggest them the right medication.
Moving further towards our second phase of the article that is “Tech stack use in Tememedicine app development”, below are the details to be explored.
Technology stack use to build Telemedicine app
Below are the tech requirements to develop a workable Telemedicine app.
Programming languages to be known:
- For Android => Learn Java and Kotlin
- For iOS => Learn Swift
Telemedicine back-end app development:
- Laravel: The PHP framework helps in developing automotive tasks like routing, sessions, and authentication.
- Node.js: Used for fetching data in nodes at runtime.
Telemedicine front-end app development:
Tools and Technologies used in developing various features;
- Video calls and Video Conferencing:
WebRTC: These are the open-source projects that provide mobile apps to have real-time communication via APIs. It is used to develop app features like screen sharing, voice chats, and video calls.
- Notification and voice messaging:
Twilio is a software that’s used for adding voice and video messaging capabilities along with the notification and reminder option in an app. It’s mostly used for chatting with customers.
- EHR integration:
Use Rails or GraphQL technologies to record and store the patient data in digital format.
- Search and filter feature:
Elastic search is a powerful analytical engine used to analyze a large amount of data with full-text search queries.
- Geolocation app feature:
Implementation of Google’s geolocation API helps the app fetch the real-time location data of the user.
- Secured Payment:
The changing market trends in the Telemedicine industry and the current situation of COVID-19 is opening gates for the development of such remote working healthcare apps. Telemedicine app development is indeed a tough process as it needs an in-depth knowledge of technology and most importantly app compliances. Solving your first step towards Telehealth app development above was the list of Technologies that can be used and the required tech stack for app development to help you navigate through your research process with ease.