How is Artificial Intelligence (AI) Transforming Patient Engagement?


The Healthcare industry has always laid heavy stress on patient experience as one of the key factors to providing valuable patient care. Traditional patient experience methods such as provider-patient communication via voice, SMS, emails, and in-person patient conversations proved very vital.

That said, today’s patient population comprises GenX, GenY, and GenZ who want faster solutions to reach them on their hand-held device. The healthcare industry needs to up its game to cater to this new generation of patients who look for improved patient care experiences.

To cater to this, the healthcare industry needs to take the support of technology platforms that are digitally advanced and supported by powerful data platforms. Adopting a powerful data platform can also help healthcare providers overcome the following challenges:

  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 insights
  3. The lack of data-driven culture impedes health care 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 1. Patient registration 2. EHR 3. EMR 4. Doctor consultation notes 5. Patient feedback 6. Patient claims, etc. The data in healthcare ideally suits the requirements of “Big Data” as data comes in different volumes, high velocity, variety. The healthcare technology platforms must be constantly upgraded or re-architected to manage and consume such large volumes of data.

The consolidation of different types and formats of data becomes quintessential for healthcare to acquire more patient intelligence. This will further drive them in delivering superior patient experience and operational excellence. To this extent, healthcare providers need:

  1. A robust and modernized data platform that allows ingestion, consolidation, transformation, analytics, and usage. Out of these, usage is vital to attain value from the Big Data that is generated.
  2. To adopt artificial intelligence that helps achieve the below results:
    1. AI can help in screening large volumes of consolidated data and help automate workflows like patient appointment booking, payment collection, predict no-shows, recommend patient services, etc.
    2. Conversational AI can help triage patient emergency calls and advise them with the right set of actions and steps.
    3. AI can help providers 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 the 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 care powered with AI-enabled tools that enable healthcare providers and staff to deliver exceptional patient care. Here are the top 5 ways to use AI for patient engagement:

    1. Healthcare Virtual Assistants (Chatbots)

    Patients interact with the 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.

    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.

    2. AI-powered Patient Self-Service Portal

    Providing a self-service portal is very 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 patients’ health information online. Patients can obtain their historical health records, lab reports, discharge summaries, immunizations, and healthcare provider’s notes from any connected device, any time. These portals also enable patients to book, change or cancel appointments anytime, anywhere.

    However, true patient self-service can be achieved when the portals are powered by AI. Such AI-enabled patient portals can guide patients throughout the portal by an intelligent bot that can help them with relevant suggestions. A few examples are:

  • Alerting the patient on the next arriving appointment
  • Recommending patients with the best and suitable doctor for the consultation, also the nearest, 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 the critical success factor for their business growth. They need a single view of the patient to properly diagnose, treat, or deliver the best medical care.

    A Single (360-degree) View of a Patient Enables providers with the following:

  • 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 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 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 had 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.

    5. Healthcare Workforce Optimization

    Patient experience is often suffered by long delays and wait times that negatively impact patient engagement. Leveraging advanced analytics and AI, the provider’s staff can identify where the delays happen and the areas of 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. It automates 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 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.


    Anand Subramaniam

    Anand Subramaniam leads Data Analytics & AI practice at Kanini and is passionate about the data science domain and has championed data analytics practices across startups to Enterprises in various verticals. He is a thought leader, start-up mentor, and data architect. He brings forth over 2 decades of techno-functional leadership in envisaging, planning, and building high-performance state-of-the-art technology teams.