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          4 ways to scale ‘always on’ care with AI-driven patient engagement

          by Marcus Garcia
          March 8, 2024
          Share

          Patient engagement really goes beyond the traditional doctor-patient relationship—it encompasses all interactions between patients, their healthcare providers, and the overall healthcare system. Care communication occurs during clinical visits, but also takes place across a variety of voice and digital touchpoints.

          Every interaction with the provider contributes to the patient’s experience, and data from every interaction can be used strategically to understand and improve patient experiences. Advancements in artificial intelligence (AI) are making it possible for organizations to collect and make sense of patient interaction data at scale. As a provider striving to deliver “always on” care, you need look no further than your contact center as the ideal point to centralize the data and intelligence that comes from voice and digital patient interactions.

          Let’s explore four key areas of how healthcare contact centers enable “always on” care with the support of customer experience technology and AI.

          1. Keeping up with evolving communication channels

          Modern contact centers are evolving beyond phone calls and offering interactions through voice assistants, chatbots, SMS/texts, video consultations, and secure messaging apps.

          Accommodating an omnichannel patient experience caters to the diverse patient preferences and accessibility needs of your patient population. Providers are expected to not only support voice and digital interactions, but self-service channels, as well. Research firm Metrigy compared adoption of interaction channels in healthcare versus all other industries, and found that healthcare organizations are using voice and email the most, in line with other industries, followed by self-service and a slightly higher adoption of SMS.

          The bottom line is, limiting interaction types will limit patient engagement, and this is where patient experience solutions can help.

          2. Personalizing support and guidance

          For healthcare contact centers, personalized support and guidance is a balance between automation and rep training. The right balance can support scalable patient-centric engagement and care—and dynamic patient interactions that range from full self-service to conversations that elevate to a human rep.

          • Virtual assistants and chatbots provide 24/7 availability for scheduling appointments, answering basic questions, and managing refills improves accessibility and reduces wait times. AI-powered symptom checkers and chatbots may offer educational resources relevant to individual needs. Virtual assistants and chatbots can handle basic inquiries, triage concerns, and schedule appointments, freeing up human agents for complex issues.

            With access to patient data and AI insights, agents can provide personalized guidance, address emotional concerns, and connect patients with appropriate resources, offering a human touch in the digital age. Metrigy analyzed the impact of virtual assistants and the benefits are clear in the form of patient benefits: a 9% revenue boost, 18% patient satisfaction improvement, and an 18% efficiency boost.
          • Agent assist uses machine learning technology to provide suggestions to human agents when they are in conversation with a customer. These suggestions are typically based on the organization’s own data. Metrigy found that agent assist reduces handle time by 32% for healthcare organizations.
          • Workflow automation, which may or may not be paired with AI, improves employee efficiency by automating mundane tasks. Examples include sending text or email reminders of upcoming appointments, providing patients summaries of their visits, or updating charts. Metrigy reports that about one-third of healthcare companies use automated workflows, and when it comes to resolving an issue or problem, they are twice as likely to use the technology. For example, if a patient posts a negative review of a physician, hospital, or treatment center, an automated workflow initiates a call, email, or text to the patient to try resolving the issue.
          • Autosummary uses AI to summarize a call on behalf of the agent, minimizing the amount of time the agent spends notetaking and summarizing the call. This results in significant savings in cost and time. For example, for an organization with 1,000 contact center agents, if after-call work takes 30 seconds per agent per call, it can cost the organization upwards of $7 million per year. Automating that task with AI decreases handle time, manual note taking, and drives consistency and context for the next rep who interacts with that patient.
          • Proactive engagement leverages predictive analytics and AI to anticipate a patient’s next steps and use that information to proactively remind, notify, or prompt for next best action. For providers, using AI for proactive engagement means more efficient use of scarce resources. Providers can automate outreach through the patient’s preferred communication channels. Utilizing patient data, contact centers can reach out with appointment reminders, medication adherence support, and targeted health education, fostering a preventative approach. Proactive patient engagement also entails offering the right self-service options to address patient needs.
          doctors mentor student

          3. Maximizing data collection and insights

          Healthcare contact centers are a key center for accessing data and insights. Every consumer or patient interaction generates valuable data on patient needs, concerns, and experiences. Data can be analyzed to improve patient education materials, healthcare services, and overall patient engagement strategies—not to mention outcomes. With an understanding of which patient pathways lead to successful outcomes, providers can replicate that for other patients with similar situations and drive faster resolution.

          AI enables health systems to analyze vast amounts of data quickly and accurately. AI tools can identify call trends, detect patient sentiment, and suggest next best action, enabling proactive interventions and improving health outcomes.

          Process mining can give a provider an understanding of which historic patient pathways led to successful outcomes, and then can automate those interactions for patients with similar situations and drive faster resolution.

          4. Building patient trust and empowerment

          The contact center is an extension of your care team. AI enables personalization and proactive interactions that build trust in the provider and help the patient feel seen and understood.

          By demonstrating an understanding of each patient and their circumstances, you’ll build trust and better outcomes. Scaling this for your entire patient population is possible with AI-powered patient engagement from the contact center and improves patient experience:

          • Respond to patients 24/7
          • Empower patients with the ability to self-serve when possible
          • Empower patient reps with information, history, and context to deliver a personalized conversation with every patient.
          • Reach patients proactively to educate and demonstrate concern and care

          By readily providing accurate, understandable information and aiding patients in navigating complex healthcare systems, contact centers can build trust and empower patients to make informed decisions about their health.

          The future of patient engagement and ‘always on’ care

          According to a study from the College of Healthcare Information Management Executives and KLAS Research, more than 80% of healthcare organizations use advanced analytics in some form. But there remains tremendous potential for AI to enable stronger patient engagement. Generally, healthcare organizations are behind other industries when it comes to using AI to resolve patient interactions. Research firm Metrigy found that just 38% of healthcare orgs use AI to resolve patient interactions, compared to all other industries (44% average).

          As we navigate the evolving landscape of both consumer and healthcare technology, one thing remains clear: The future of patient engagement is intricately linked to AI and technological advancements. Achieving “always on” care is possible with the intelligent use of data, AI, and automation, even if to connect the right patient with the right rep at the right time, and to make human interactions more satisfactory and productive.

          By embracing innovation, prioritizing ethical considerations, and fostering meaningful patient-provider interactions, we pave the way for a healthcare ecosystem that is truly transformative and patient-centric.

          Get Metrigy’s research report here.

          About the Author

          Marcus Garcia

          Marcus Garcia has more than 20 years of experience in communication technology and runs the healthcare vertical at NiCE.

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