Top 5 AI Use Cases for Driving Patient Engagement in Healthcare

The healthcare industry is undergoing a phenomenal technological transformation and the role of Artificial Intelligence (AI) in augmenting patient engagement is particularly something that has been catching the eyes of experts and researchers. According to an analysis by Vantage Market Research, the total global Artificial Intelligence in healthcare is estimated to reach USD 95.65 Billion by 2028.

Traditional ways of creating patient engagement in healthcare via voice, SMS, emails, and in-person patient conversations were quite helpful in the past, but with today’s technological revolution, the healthcare industry needs something more – which is AI. The present and the future of patient engagement is Artificial Intelligence.

Overcoming Data Challenges with AI

Today’s patient population comprises GenX, GenY, and GenZ who want faster solutions. The healthcare industry needs to up its game to cater to this new generation of patients who look for improved patient care experiences. And for this, the healthcare industry needs to rely on technology-driven digital patient engagement platforms. These platforms are digitally advanced and backed by powerful data systems.
In this article, we will throw light on the power of AI in driving patient engagement through some AI use cases in healthcare.
Adopting a powerful data platform helps healthcare providers overcome the following challenges while increasing patient engagement –
  1. Disparate data repositories – Patient data is scattered everywhere making it challenging for providers to get a “Single View of the Patient Data“.
  2. Huge volumes of data from disparate data sources need to be integrated, cleansed, transformed and stored quickly to help with actionable insights.
  3. The lack of data-driven culture impedes healthcare providers from intelligence about their patients, preventing them from providing relevant and timely services.

Data Analytics & AI in Patient Engagement

The healthcare industry is one of the most data-intensive industries. Data in healthcare gets generated via various channels like patient registration, EHR, EMR, Doctor consultation notes, Patient feedback, Patient claims, etc. It is this data that is invaluable and useful in increasing patient engagement.
The data in healthcare ideally suits the requirements of “Big Data” as it comes in different volumes, high velocity, and variety. Healthcare technology platforms must be constantly upgraded or re-architected to manage and consume such large volumes of data.
The consolidation of diverse types and formats of data becomes quintessential for healthcare providers to acquire more patient intelligence. This further enables them to deliver superior patient experience, increase patient engagement, and achieve operational excellence. To this extent, healthcare providers need the following –
  1. A robust and modernized data platform that allows data ingestion, consolidation, transformation, analytics, and usage. Out of these, usage is vital to attain value from the Big Data that is generated.
  2. Artificial intelligence that helps achieve the results below-
    1. AI can help in screening large volumes of consolidated data and help automate workflows like patient appointment booking, payment collection, predicting no-shows, recommending patient services, etc.
    2. Conversational AIcan help triage patient emergency calls and advise them with the right set of actions and steps.
    3. AI can help providers in pre-empting the probability of patient no-shows, saving millions of dollars
    4. AI can back up a live patient counselor by providing relevant intelligence during a call with a patient
    5. AI can help support a patient during times when patient counselors are not available.

The global patient engagement solutions market size was estimated at USD 15.1 billion in 2020 and is expected to expand at a compound annual growth rate (CAGR) of 21.4% from 2021 to 2028.

– Grand View Research

Patient Engagement Solutions can be largely divided into –
  • Patient Conversations
  • Patient Recommendations
  • Patient Sentiments
  • Patient Payments
  • Patient Engagement Solutions market is driven by:
  • Increased use of EHR reports
  • Growing chronic diseases and increasing awareness regarding mobile health among people
  • Mining patient sentiments
  • Segmenting patients based on factors like disease profile, age, income, occupation, location, genetics, etc.
  • Top 5 AI Use Cases for Driving Patient Engagement

    Patient engagement is at the heart of patient experience. Today, patients have multiple options available to them. If they are not happy with one healthcare provider, they will go to the other. More so, they are willing to rely on AI for utilizing healthcare services. Realizing this fact, healthcare organizations are embarking on taking a personalized and data-driven approach to patient engagement. They are shifting from fee-for-service care to patient-centered value-based care driven by AI-enabled tools that enable healthcare providers and staff to deliver exceptional patient care. Here are the top five ways to use AI for patient engagement:

    1. Healthcare Virtual Assistants (Chatbots)

    Patients interact with healthcare organizations by making calls to the customer care center to get assistance on how to proceed with their medical conditions, find the right provider/doctor, schedule appointments, etc. The healthcare providers may not have the required staff to assist or guide the customers with their queries.
    To ensure continuous and consistent patient engagement, Intelligent Virtual Assistants (Chatbots) can be set up to automate responses to patients’ simple inquiries and requests. Patients can interact with these Chatbots on their preferred digital channel to get answers to their queries. Chatbots can easily handle and resolve patient inquiries without manual intervention and effort. They collect patient information and suggest appropriate resolutions. And for instances where a virtual conversation requires escalation, the patient can be directed to the most appropriate channel and form of care. This solution allows healthcare providers to scale during times of high-volume patient consultations. The VAs can also help patients book an appointment with a doctor if required.

    By 2023, 20% of all patient interactions will involve some form of AI enablement within clinical or nonclinical processes, up from less than 4% today.

    – Gartner

    2. AI-powered Patient Self-Service Portal

    Providing a self-service portal is important to engage today’s digitally fluent patients and empower them to access the required information. Patient portals are self-service platforms that provide instant access to patient’s health information online. Patients can obtain their historical health records, lab reports, discharge summaries, immunizations, and healthcare provider’s notes from any connected device, at any time from such digital patient engagement platforms. These portals also enable patients to book, change, or cancel appointments anytime, anywhere.
    However, true patient self-service can be achieved when AI powers patient self-service portals. Such AI-enabled digital patient engagement platforms can guide patients throughout the portal using an intelligent bot that can help them with relevant suggestions. A few examples are:
    • Alerting the patient on the next arriving appointment.
    • Recommending the best and most suitable, also the nearest, doctors to patients for consultation, and automatically presenting them with the choice of time slots.
    • Giving patients an estimate of the cost involved for the consultation.
    • Helping patients to be ready with payer information to submit any claims to the payer.
    • Suggesting personalized patient care plan.

    3. 360-degree View of the Patient

    Healthcare providers understand that delivering exceptional patient experience is a critical success factor for their business growth. They need a single view of the patient to accurately diagnose, treat, or deliver the best medical care.
    A single (360-degree) view of a patient helps the provider in the following ways –
    • Enables the provider to track the patient history across all the services they have solicited and serve their needs better.
    • Allows the provider to get additional patient intelligence in terms of improving future patient engagements.
    • Helps the provider to use patient feedback to proactively address issues for other patients.
    • Improves operational efficiency within the provider organization.

    A Patient 360 view can be achieved by implementing a data platform that is capable of –

    1. Integrating data from various data sources
    2. Providing data integrity to remove redundancies
    3. Building a data pipeline that can handle large volume, high velocity, and high variety of data
    4. Allowing faster analytics

    4. Risk Assessments for Preventive Care

    AI applications can help providers with useful insights about the onset of diseases like cancer, diabetes, heart attack, etc. AI applications can ingest large volumes of data from x-rays and medical imagery and understand the pattern of disease onset.
    AI applications can also be integrated with smart devices like smart bands and can help monitor the heart rate of a patient and warn the onset of an attack or stroke. For example, a woman named Diane Feenstra, a native of Norton Shores in Michigan, owes her life to a smartwatch that she was wearing. The smartwatch identified irregular heart rate patterns through its heart-monitoring system and cautioned her of an impending heart attack. When rushed to the hospital, she learned that she suffered a heart attack but was not aware of it. By knowing her condition from the intelligence provided by the AI-powered Smartwatch; the doctor could give her appropriate care. This is a very apt use case of AI in healthcare.

    5. Healthcare Workforce Optimization

    Patient experience is often suffered by prolonged delays and wait times that negatively impact patient engagement. Leveraging advanced analytics and AI for patient engagement, the provider’s staff can identify where the delays are happening and the bottlenecks that can hamper patient satisfaction and implement data-driven intelligent solutions to manage the same. With an AI-powered workflow management platform, healthcare coordinators can be empowered with automated workflows that keep informing them of the daily patient flow, minimizing their input into the systems and screen time. AI-driven digital patient engagement platforms automate end-to-end follow-ups, consultation schedules, advice related to medicine dosages, etc. for patients.

    Looking Ahead

    AI is transforming patient engagement. It promises to enhance the overall care experience by predicting patient needs, streamlining operations, accelerating the overall workflow of healthcare delivery, and offering personalized patient care. However, since patient healthcare data is inherently sensitive, and must comply with regulatory norms such as HIPAA, stringent security measures should be put in place when training the algorithms.
    To incorporate AI into your patient engagement strategy, you would need an expert IT partner to get you started. With deep healthcare expertise and rich experience in developing AI/ML applications, we at KANINI can help you deliver delightful patient engagement and experience. Contact us for more information.
    Author

    Anand Subramaniam

    Anand Subramaniam is the Chief Solutions Officer, leading Data Analytics & AI service line at KANINI. He is passionate about data science and has championed data analytics practice across start-ups to enterprises in various verticals. As a thought leader, start-up mentor, and data architect, Anand brings over two decades of techno-functional leadership in envisaging, planning, and building high-performance, state-of-the-art technology teams.

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