The New Era of Personalized Digital Healthcare.
The digital health landscape is constantly changing, and artificial intelligence is definitely contributing to these changes.
In today’s digital health landscape, patients expect from a healthcare app not only usability but also personalization.
With AI-based personalization, healthcare applications can analyze user behavior, health data, and engagement to offer recommendations, reminders, and insights to users. Such personalization can greatly improve patient engagement in healthcare applications.
However, there is a major responsibility associated with personalization in healthcare applications. Data collected in healthcare applications is among the most sensitive types of user information. Misusing such data can lead to a severe decrease in user engagement.
For digital health founders and healthcare startups, the question is how to leverage AI-based personalization while maintaining high standards of data privacy.
This guide is designed to help healthcare startups achieve this balance.
What AI Personalization Means in Healthcare Apps
What does AI personalization in healthcare apps mean?
The use of artificial intelligence in providing a personalized experience based on individual patient data and health behaviors.
Unlike traditional healthcare apps, which offer a one-size-fits-all experience, AI apps offer a personalized experience based on individual patients.
The various types of AI personalization:
Behavioral Personalization
The use of healthcare apps in tracking user behaviors, such as activity levels and app use.
Predictive Health Insights
Using artificial intelligence technology, patients’ data sets can be scanned to find any pattern that may be an indication of health risks and alert the patient accordingly to take necessary preventative measures.
Personalized Treatment Reminders
Using AI technology, patients can be reminded of their medical schedules and appointments through the AI system.
Intelligent Symptom Monitoring
Advanced healthcare apps have the ability to monitor patients’ symptoms and alert them if any unusual pattern is noticed.
In this manner, the healthcare experience becomes less reactive and more proactive.
Why AI Personalization Improves Patient Outcomes
Personalization is not only about making things convenient for people; it can actually lead to better patient outcomes.
Better Adherence to Treatments
There is a higher chance of patients following their treatment plans when reminders are tailored to their lifestyle.
Early Identification of Health Issues
AI can identify changes in people’s health patterns that may be an early sign of a disease.
Keeping Patients Engaged Throughout the Healthcare Journey
Personalization helps keep patients engaged with their healthcare journey.
Support for Preventive Healthcare Measures
With the help of AI-driven insights, patients are encouraged to adopt better lifestyle habits to prevent serious health conditions.
For healthcare startups, all these mean better patient retention rates and higher patient engagement.
The Privacy Challenge in AI-Powered Healthcare Apps
Though there are various benefits of AI-powered personalization in healthcare apps, some of the challenges that need to be addressed are discussed in this section.
The data that is collected by these healthcare apps is of a very sensitive nature,
Including:
Medical history
Biometric data
Mental health data
Lifestyle patterns
The abuse of this data can have major consequences for the company as well as the users of these apps.
The risk of data privacy in these healthcare apps includes:
Data Breaches
Healthcare data is of high value for hackers, and startups in this industry are in a very tough spot when it comes to gaining users’ trust.
A ‘Privacy First’ approach is something that needs to be integrated into the product development process itself.
The overcollection of data is a major threat when it comes to data privacy in healthcare apps.
Privacy Regulations That Healthcare Applications Are Required to Follow
Healthcare applications must adhere to very strict data protection regulations to ensure patient privacy at all times.
HIPAA Compliance for the United States
In the United States, HIPAA (Health Insurance Portability and Accountability Act) protects patient health information that is considered sensitive.
GDPR Guidelines for Apps in Europe
In addition to complying with HIPAA, apps providing services to users located in Europe will also need to follow the GDPR (General Data Protection Regulation), which requires clear and transparent collection of information, consent from users before collecting any personal information, and has guidelines governing the protection, use, and storage of personal information.
User’s Control of Personal Data and Information
Users must have clear control over how and why their data is collected, stored, and used by the app developer.
Healthcare startups need to develop their compliance strategies early in product development to limit their liabilities down the road.
How Healthcare Startups Can Implement AI Personalization Safely
Implementing AI personalization does not necessarily mean that the privacy of the users will be compromised. Therefore, it is possible for healthcare startups to achieve the best results without risking the security of the users.
- Collect Only Essential Data
Only collect the data that is essential to the users.
- Privacy-First AI
Implement an AI architecture that does not require direct access to the sensitive data of the users.
- Implement Strong Data Encryption
Implement data encryption to ensure that the data is secure.
- Implement Federated Learning or Edge AI
Implement federated learning or edge AI to enable the AI to learn without the sensitive data of the users needing to be sent to a central server.
Transparency to Users
Explain to the users how the AI works and the benefits that the users will derive from it.
Applications of AI Personalization in Real Life happen all across the Globe.
These include:
Fitness & Wellness Apps -Created with the help of Artificial Intelligence, these Apps deliver customized fitness and wellness programs based upon the users’ activity level, their health goals & the data collected from wearables (Google Fit, Fitbit, etc.).
Mental Health Platforms – Therapy Platforms that utilize Artificial Intelligence technology offer depression & anxiety self-help tools (exercises) as well as online support groups.
Chronic Disease Management – An example of a Chronic Disease Management App is a Diabetes App that tracks blood glucose levels, offers personalized assistance with dietary decisions based upon what the individual is eating, and provides information about foods that lower blood glucose levels when eaten.
Remote Patient Monitoring – Numerous healthcare services utilize remote patient monitoring (RPM) & many of these services will be incorporating Artificial Intelligence into RPM processes, such as identifying potential risk factors for patients.
All of these examples of how AI Personalization is already being used in Healthcare make healthcare a more proactive & patient-oriented system of care delivery versus a reactive & provider-centered system of care delivery.
The Future of AI Personalization in the Field of Digital Health
What does the future hold for the digital health space? The future is all about more intelligence and personalization.
Some of the trends that are to be expected in the future are:
AI Health Assistants
Virtual AI assistants that can help people with their day-to-day life.
Predictive Healthcare Models
AI that can help predict any health problems that may arise without the presence of any symptoms.
Personalized Digital Therapeutics
AI that can help people with treatment programs that are tailored to their needs.
For digital health startups, the opportunity is huge.
The ones who will be able to capitalize on the opportunity are the ones who will be able to successfully marry personalization with privacy.
Final Perspective
AI personalization has the power to completely transform the digital health app space.
However, innovation should never be done at the expense of privacy.
Digital health startups should always maintain a mindset that focuses on the importance of privacy while trying to innovate AI personalization for the digital health space.
The future of the digital health space is for those who will be able to successfully marry personalization with privacy.
As a healthcare startup founder, if you wish to create a health app that offers secure AI personalization, the right technology partner can be the key to your success.
The team at AveryBit can help healthcare startup founders design and develop healthcare apps that offer secure AI personalization.
We can help healthcare startups with healthcare app development and secure AI integration. We can help healthcare startups create a healthcare app that offers scalability.
Are you ready to create the future of intelligent healthcare apps?
Reach out to the experts at AveryBit and start creating smarter healthcare apps.
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