{"id":98857,"date":"2024-12-30T13:02:16","date_gmt":"2024-12-30T10:02:16","guid":{"rendered":"https:\/\/www.instinctools.com\/?p=98857"},"modified":"2025-07-15T10:55:10","modified_gmt":"2025-07-15T07:55:10","slug":"conversational-ai-in-healthcare","status":"publish","type":"post","link":"https:\/\/www.instinctools.com\/blog\/conversational-ai-in-healthcare\/","title":{"rendered":"Conversational AI for Healthcare: 10 use cases and real-world examples"},"content":{"rendered":"\n<div class=\"wp-block-yoast-seo-table-of-contents yoast-table-of-contents\"><h2>Contents<\/h2><ul><li><a href=\"#h-what-is-conversational-ai-technology-in-healthcare\" data-level=\"2\">What is conversational AI technology in healthcare?<\/a><\/li><li><a href=\"#h-proven-benefits-of-healthcare-conversational-ai\" data-level=\"2\">Proven benefits of healthcare conversational AI<\/a><\/li><li><a href=\"#h-from-code-to-cure-10-applications-of-conversational-ai-in-healthcare\" data-level=\"2\">From code to cure: 10 applications of conversational AI in healthcare<\/a><\/li><li><a href=\"#h-activate-holistic-healthcare-conversational-ai-for-your-organization-in-5-steps\" data-level=\"2\">Activate holistic healthcare conversational AI for your organization in 5 steps<\/a><\/li><li><a href=\"#h-challenges-of-putting-conversational-ai-to-work-in-healthcare\" data-level=\"2\">Challenges of putting conversational AI to work in healthcare<\/a><\/li><li><a href=\"#h-conversational-ai-in-healthcare-a-new-pill-for-the-future\" data-level=\"2\">Conversational AI in healthcare, a new pill for the future<\/a><\/li><li><a href=\"#h-faq\" data-level=\"2\">FAQ<\/a><\/li><\/ul><\/div>\n\n\n\n<div class=\"wp-block-highlights-block-highlights block-highlights__wrap orange\"><h2 class=\"heading-2-bold\">Key highlights<\/h2><ul class=\"highlights__desc body\"><li>Conversational AI in healthcare provides a more natural, flexible user experience that can significantly expand areas of use for healthcare chatbots.<\/li><li>Conversational AI solutions can introduce gains in a raft of areas, both in the healthcare settings and outside hospitals.<\/li><li>To successfully implement the technology, healthcare organizations must tidy up the data, shore up tech foundations, and draw up a risk mitigation strategy.<\/li><\/ul><\/div>\n\n\n\n<p>If there\u2019s one thing to be said about healthcare today, it\u2019s that the healthcare system is buckling under the weight of increasing costs, staff shortages, and growing patient numbers. Against this challenging backdrop, the potential of <a href=\"https:\/\/www.instinctools.com\/ai-chatbot-development-services\/\" target=\"_blank\" rel=\"noreferrer noopener\">conversational AI<\/a> in healthcare is touted as a much-needed lifeline that offers a promising solution to healthcare\u2019s toughest burdens.<\/p>\n\n\n\n<p>However, as healthcare providers consider which conversational AI solution to bank on, it\u2019s important to avoid the shiny object syndrome and invest in resilient tools. So, let\u2019s see what conversational AI <a href=\"\/healthcare\/\" target=\"_blank\" rel=\"noreferrer noopener\">healthcare<\/a> solutions are here to stay.&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-what-is-conversational-ai-technology-in-healthcare\">What is conversational AI technology in healthcare?<\/h2>\n\n\n\n<p>Healthcare conversational AI relies on advanced natural language processing to interact with patients and other healthcare stakeholders in a natural way. The technology can manifest as text-based <a href=\"\/blog\/conversational-ai-chatbot-vs-assistants\/\" target=\"_blank\" rel=\"noreferrer noopener\">conversational chatbots<\/a>, virtual assistants, or voice-enabled interfaces that act as co-pilots, automating various tasks.<\/p>\n\n\n\n<p>Compared with traditional, rule-based chatbots, conversational AI interfaces offer a significant leap forward, providing a more natural, adaptable user experience.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>Feature<\/strong><\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>Rule-based chatbots<\/strong><\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>Conversational AI interfaces<\/strong><\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Task<\/td><td class=\"has-text-align-center\" data-align=\"center\">Navigation-focused<\/td><td class=\"has-text-align-center\" data-align=\"center\">Dialog-focused<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Type of input data<\/td><td class=\"has-text-align-center\" data-align=\"center\">Cannot directly process unstructured data<\/td><td class=\"has-text-align-center\" data-align=\"center\">Can leverage unstructured data (e.g. purchasing and accounts payable data) to shape outputs&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Language understanding<\/td><td class=\"has-text-align-center\" data-align=\"center\">Pre-determined and scripted with limited understanding of context<\/td><td class=\"has-text-align-center\" data-align=\"center\">Advanced natural language processing, understands nuances and context<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Response generation<\/td><td class=\"has-text-align-center\" data-align=\"center\">Predefined responses, limited flexibility<\/td><td class=\"has-text-align-center\" data-align=\"center\">Dynamic response generation, can adapt to various queries<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Adaptation<\/td><td class=\"has-text-align-center\" data-align=\"center\">Limited learning capabilities, requires explicit training<\/td><td class=\"has-text-align-center\" data-align=\"center\">Continuous learning, improves over time through <a href=\"\/machine-learning-app-development-services\/\" target=\"_blank\" rel=\"noreferrer noopener\">machine learning<\/a><\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Personalization<\/td><td class=\"has-text-align-center\" data-align=\"center\">Provides generic responses<\/td><td class=\"has-text-align-center\" data-align=\"center\">Personalized responses based on user history and preferences<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Complexity of interactions<\/td><td class=\"has-text-align-center\" data-align=\"center\">Handles linear, predictable queries<\/td><td class=\"has-text-align-center\" data-align=\"center\">Can handle complex, multi-turn conversations<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">Flexibility of deployment<\/td><td class=\"has-text-align-center\" data-align=\"center\">Trained for a specific task<\/td><td class=\"has-text-align-center\" data-align=\"center\">Generalizable nature, can be integrated into multiple healthcare settings<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-proven-benefits-of-healthcare-conversational-ai\">Proven benefits of healthcare conversational AI<\/h2>\n\n\n\n<p>Over <a href=\"https:\/\/www2.deloitte.com\/content\/dam\/Deloitte\/us\/Documents\/life-sciences-health-care\/us-from-code-to-cure-1.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">70%<\/a> of leading healthcare companies are experimenting with or planning to scale generative AI \u2014 a core conversational AI enabler \u2014 across the enterprise. Let\u2019s probe into the gains they can already reap by <a href=\"\/machine-learning-consulting-services\/\" target=\"_blank\" rel=\"noreferrer noopener\">implementing conversational AI solutions.<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-bringing-patient-self-service-into-the-practice\">Bringing patient self-service into the practice<\/h3>\n\n\n\n<p>Whether it&#8217;s due to high costs, inherent stigma, or shortage of healthcare professionals, <a href=\"https:\/\/pmc.ncbi.nlm.nih.gov\/articles\/PMC5309146\/#:~:text=As%20shown%20in%20Table%202,year%20varies%20by%20demographic%20characteristics.\" target=\"_blank\" rel=\"noreferrer noopener\">29% of the US population<\/a> choose not to seek needed medical care. Patient-facing conversational AI agents and chatbots can remove the obstacles in the path to healthcare services and give patients the autonomy to manage health on their own terms.<\/p>\n\n\n\n<p>Conversational AI systems interact directly with patients to perform tasks that span from mental health support to appointment scheduling and medication management. With conversational interfaces in tow, individuals can get the necessary support and direction, even when the care organization\u2019s resources are spread thin.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>Looking to automate Rx management, a US-based healthcare provider reached out to *instinctools. Our team developed a custom virtual medical assistant that handles repeat prescription refills from patients autonomously and proactively notifies patients when the refill is due. The result was an estimated 120% increase in patient satisfaction and slashed admin costs.<\/p>\n<cite>\u2014 Pavel Klapatsiuk, AI Lead Engineer, *instinctools<\/cite><\/blockquote>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-driving-administrative-cost-efficiency-nbsp\">Driving administrative cost-efficiency&nbsp;<\/h3>\n\n\n\n<p>While evaluating the high-value areas lined up for gen AI disruption, <a href=\"https:\/\/www.mckinsey.com\/industries\/healthcare\/our-insights\/generative-ai-in-healthcare-adoption-trends-and-whats-next\" target=\"_blank\" rel=\"noreferrer noopener\" class=\"broken_link\">60%<\/a> of healthcare leaders deem administrative efficiency to be one of them. From automated patient data extraction to medical record management, conversational agents can execute administrative tasks related to revenue cycle, reporting, and approval processes.<\/p>\n\n\n\n<p>By automating these operations, healthcare organizations can potentially save up to 15% to 25% of total healthcare spending.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-making-patients-feel-heard\">Making patients feel heard<\/h3>\n\n\n\n<p>Patients often waste hours on getting their issues resolved through IVRs and other systems. The lack of contextual understanding, long wait times, and inaccessible interfaces result in low first-call resolution percentages and leave patients feeling abandoned.&nbsp;<\/p>\n\n\n\n<p>Healthcare conversational AI can flip the script. By building on structured and unstructured patient data, past interactions, and real-time contextual cues, conversational AI interfaces can bring humanity back into the experience and share the workload with human agents.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>One of our clients, a health insurance provider, implemented conversational AI to handle a growing volume of claims processing calls. By automating the initial intake, claim status updates, and document verification, our AI-powered solution helped the client decrease resolution time by 40%, increase deflection rate by 25%, and lower costs by 20%.<\/p>\n<cite>\u2014 Pavel Klapatsiuk, AI Lead Engineer, *instinctools<\/cite><\/blockquote>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-enhancing-health-outcomes\">Enhancing health outcomes<\/h3>\n\n\n\n<p>Conversational AI in healthcare wears many hats \u2014 with each of them contributing to enhanced patient outcomes. Whether it\u2019s through personalized medication reminders, symptom checking, or billing assistance, human-like AI interfaces can positively transform the way patients interact with existing healthcare systems.<\/p>\n\n\n\n<p>More importantly, conversational AI healthcare solutions help clinicians fill the gaps in patient data \u2014 both directly and indirectly \u2014 by enabling proactive patient engagement and facilitating comprehensive data collection. Having more validated patient data on hand allows healthcare providers to make more informed decisions about diagnosis, treatment, and preventative measures.<\/p>\n\n\n\n<div class=\"wp-block-cta-blog-block-cta cta-blog\"><span class=\"draw draw_color-right draw_undefined\"><\/span><span class=\"draw draw_color-left draw_gray\"><\/span><div class=\"cta-blog__wrap\"><div class=\"cta-blog__left\" style=\"max-width:367px\"><p class=\"cta-blog__title\">More efficient assistance for patients and doctors, when it matters most<\/p><p class=\"cta-blog__desc\"><\/p><\/div><div class=\"button button_undefined button_bg-gray cta-blog__btn\"><a class=\"link-anchor\" target=\"_self\" rel=\"noopener\">Get started\u00a0<\/a><\/div><\/div><div class=\"cta-blog__form form_light\"><\/div><\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-from-code-to-cure-10-applications-of-conversational-ai-in-healthcare\">From code to cure: 10 applications of conversational AI in healthcare<\/h2>\n\n\n\n<p>While the storm is gathering in the healthcare sector, opportunities abound for private payers, hospitals, and labs to drive conversational AI innovation and usher in a brighter future. Let\u2019s have a look at how conversational artificial intelligence can shake the healthcare status quo for the better.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-1-appointment-scheduling\">1. Appointment scheduling<\/h3>\n\n\n\n<p>Conversational AI can not only make care easier to find but also easier to schedule. Available 24\/7, AI appointment setters and schedulers align patients\u2019 needs with provider-specific data to bring forth a speedier search and scheduling experience.<\/p>\n\n\n\n<p>Along with scheduling appointments, conversational AI interfaces can:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Offer a self-reschedule path to patients and alternative time slots.<\/li>\n\n\n\n<li>Update patients on the time and location of the upcoming appointment.<\/li>\n\n\n\n<li>Automatically serve canceled appointments to other patients on the waitlist.<\/li>\n\n\n\n<li>Sync online appointments, digital forms, insurance verification, payments, and patient interactions.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1176\" height=\"876\" src=\"https:\/\/www.instinctools.com\/wp-content\/uploads\/2024\/12\/conversational-ai-in-healthcare-image1.png\" alt=\"Appointment booking and confirmation with a scheduling AI assistant.\" class=\"wp-image-103656\"\/><\/figure>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>We made the strategic decision to invest in a conversational AI interface to reduce no-shows and keep calendars full without headaches. The solution allowed us to reduce missed appointments by 34 percent and streamline the process of pointing patients to the right care, at the right place and time.<\/p>\n<cite>\u2014 Head of Patient Services, plastic surgery &amp; dermatology clinic, Los Angeles<\/cite><\/blockquote>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-2-medical-triaging-nbsp\">2. Medical triaging&nbsp;<\/h3>\n\n\n\n<p>In the US, primary care doctors deal with an average of 53 patient calls per day \u2014 and not all of those calls require immediate medical attention. Alleviating this burden is conversational AI that can streamline patient triage by assessing patient symptoms and determining the level of care they need. An AI chatbot can even <a href=\"https:\/\/www.nytimes.com\/2024\/11\/17\/health\/chatgpt-ai-doctors-diagnosis.html?unlocked_article_code=1.ek4.u5hK.ial4BmkCO0Ym&amp;smid=url-share\" target=\"_blank\" rel=\"noreferrer noopener\">defeat doctors at diagnosing illnesses<\/a> \u2014 provided it\u2019s properly prompted.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"930\" height=\"716\" src=\"https:\/\/www.instinctools.com\/wp-content\/uploads\/2024\/12\/conversational-ai-in-healthcare-image2.png\" alt=\"Discussing symptoms of a headache and fever with a healthcare conversational chatbot.\" class=\"wp-image-103655\"\/><\/figure>\n\n\n\n<p>By integrating conversational AI into the triaging process, care providers can create autonomous patient entry points that:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Gather symptoms and identify potential diagnoses.<\/li>\n\n\n\n<li>Provide patients with the most clinically appropriate care based on the symptoms.<\/li>\n\n\n\n<li>Automate the referral process, including scheduling appointments and coordinating with other healthcare providers.<\/li>\n\n\n\n<li>Integrate with internal systems, providing triaging nurses with access to relevant patient data.<\/li>\n\n\n\n<li>Shift to an accelerated lane for assistance if the patient needs urgent help and\/or requests it.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-3-clinical-decision-support\">3. Clinical decision support<\/h3>\n\n\n\n<p>To give the right clinical recommendation, doctors have to factor in and analyze patient context, clinical guidelines, and research literature. This time-consuming process can take hours upon hours, holding back timely interventions and leading to inappropriate treatments, if any piece of the puzzle is missed.&nbsp;<\/p>\n\n\n\n<p>No wonder, <a href=\"https:\/\/www.fiercehealthcare.com\/special-reports\/some-doctors-are-using-public-generative-ai-tools-chatgpt-clinical-decisions-it\" target=\"_blank\" rel=\"noreferrer noopener\">76% of doctors<\/a> reported using general-purpose LLMs in clinical decision-making. While the safety of this very method is dubious, custom healthcare-specific conversational AI solutions can amplify the doctor\u2019s expertise and intuition by delivering real-time, evidence-based insights at the point of care.<\/p>\n\n\n\n<p>For example, AI-powered interfaces can aid doctors in making dosing decisions based on individual patients\u2019 profiles, identify high-risk patients, and determine personalized treatment plans, based on factors such as age, comorbidities, and drug allergies.<\/p>\n\n\n\n<p>Aiming to address the clinical evidence challenge, Atropos Health <a href=\"https:\/\/www.businesswire.com\/news\/home\/20241022926591\/en\/ChatRWD%E2%84%A2-from-Atropos-Health-Exceeds-Expectations-in-Beta-and-now-Available-to-Clinicians-and-Researchers-seeking-Personalized-Evidence\" target=\"_blank\" rel=\"noreferrer noopener\" class=\"broken_link\">released<\/a> ChatRWD, a specialized medical language model that combines chat-to-database capability and AI agents. The model reduces the time needed for high-quality publication-grade real-world evidence from months to 5.23 minutes.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-4-remote-patient-monitoring\">4. Remote patient monitoring<\/h3>\n\n\n\n<p>Traditionally, remote patient monitoring is considered a challenging care delivery mode due to logistical hurdles and the amount of data generated. <a href=\"\/ai-agent-development-services\/\" target=\"_blank\" rel=\"noreferrer noopener\">Multimodal conversational agents<\/a> can minimize the complexity of RPM and aid in monitoring a patient&#8217;s health status beyond healthcare settings.&nbsp;<\/p>\n\n\n\n<p>With the human-in-the-loop, such agents can conduct on-demand automated screening interviews over the phone or web browser and deliver explicit insights into the patient\u2019s progress, risk factors, and treatment adherence \u2014 invaluable data for effective chronic disease management.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"804\" height=\"832\" src=\"https:\/\/www.instinctools.com\/wp-content\/uploads\/2024\/12\/conversational-ai-in-healthcare-image3.png\" alt=\"A medical conversational assistant guides a patient through consents, form submission, and medical history intake.\" class=\"wp-image-103653\"\/><\/figure>\n\n\n\n<p>Along with assisted interviews, conversational AI can pitch in to support the following RPM activities:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Automated check-ins <\/strong>\u2014 conversational agents can check up on a patient&#8217;s medication adherence, symptoms, and well-being.<\/li>\n\n\n\n<li><strong>Wearable device data collection<\/strong> \u2014 AI-powered systems can team up with RPM devices to vacuum and analyze data on vital signs, activity levels, and sleep patterns.<\/li>\n\n\n\n<li><strong>Personalized health coaching <\/strong>\u2014 conversational AI interfaces can deliver clear, actionable advice tailored to the patient\u2019s specific health conditions, reducing the need for emergency room visits.<\/li>\n\n\n\n<li><strong>Early intervention <\/strong>\u2014 by analyzing wearable devices, sensors, and patient-reported health data, agents can spot early signs of potential issues and notify care teams of such.<\/li>\n\n\n\n<li><strong>Telehealth stunts<\/strong> \u2014 smart agents can support patients in between remote consultations and assist doctors during telehealth sessions by jotting down patient interactions, summarizing key points, and updating EHRs.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1312\" height=\"850\" src=\"https:\/\/www.instinctools.com\/wp-content\/uploads\/2024\/12\/conversational-ai-in-healthcare-image4.jpg\" alt=\"\" class=\"wp-image-103651\"\/><\/figure>\n\n\n\n<p>A healthcare conversational chatbot discusses a patient\u2019s blood sugar levels, diet, exercise, and fatigue concerns.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-5-post-visit-patient-support-and-engagement\">5. Post-visit patient support and engagement<\/h3>\n\n\n\n<p>Lots of patients leave doctor\u2019s offices without understanding how to care for themselves once they get home and what comes next. Disjointed care pathways add to the information divide, making it challenging for patients to navigate further care.<\/p>\n\n\n\n<p>Advanced conversational AI systems can bridge this informational divide and enhance patient engagement post-visit and after discharge by:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Integrating visit notes and discharge summaries with insurance coverage information to generate clear action plans for patients.<\/li>\n\n\n\n<li>Outlining care summaries for referrals and consolidating healthcare data such as medical records, lab results, and clinical notes.<\/li>\n\n\n\n<li>Extracting key information from specialist notes for primary-care physician teams.<\/li>\n\n\n\n<li>Estimating out-of-the-pocket costs for patients, including deductibles, copayments, and coinsurance.<\/li>\n\n\n\n<li>Walking the patient through insurance coverage and billing process.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1328\" height=\"814\" src=\"https:\/\/www.instinctools.com\/wp-content\/uploads\/2024\/12\/conversational-ai-in-healthcare-image5.png\" alt=\"\" class=\"wp-image-103649\" style=\"object-fit:cover\"\/><\/figure>\n\n\n\n<p>Kaiser Permanente reported that its AI-powered patient messaging system resolved <a href=\"https:\/\/www.beckershospitalreview.com\/healthcare-information-technology\/kaiser-permanente-ai-system-clears-32-of-patient-messages-study.html\" target=\"_blank\" rel=\"noreferrer noopener\">32%<\/a> of patient messages with no manual intervention, freeing up physicians\u2019 time and timely attending to patient queries.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-6-medication-management\">6. Medication management<\/h3>\n\n\n\n<p>Only about 50% of patients stick to their prescribed medication regimen, while the other 25% are unsure about their post-prescription next steps. Polypharmacy patients have it the hardest: they have to keep a mental note of multiple medications, dosages, and timing.&nbsp;<\/p>\n\n\n\n<p>Virtual assistants equipped with conversational AI capabilities can ease the medication management burden for all sides of care:&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>They can serve as a personalized medication encyclopedia that breaks down information about prescriptions, including dosages, frequency, and potential side effects.&nbsp;<\/li>\n\n\n\n<li>Conversational AI solutions can also send refill reminders, cross-reference medications, and pull patient medical data right from EHRs.<\/li>\n\n\n\n<li>They can help pharmacists reconcile medication lists to avoid medication errors.<\/li>\n\n\n\n<li>For doctors, such interfaces can provide evidence-based recommendations for medication prescribing, dosage adjustments, and treatment plans.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1040\" height=\"838\" src=\"https:\/\/www.instinctools.com\/wp-content\/uploads\/2024\/12\/conversational-ai-in-healthcare-image6.png\" alt=\"MediMate chatbot helps a user set a daily reminder to take medication, confirming the schedule details.\" class=\"wp-image-103654\"\/><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-7-reimbursement\">7. Reimbursement<\/h3>\n\n\n\n<p>In healthcare, reimbursement is a field full of speed bumps, with denied claims, complex coding, and inefficient billing processes being chief among them. No wonder this activity lends itself well to conversational AI and its unrivaled automation superpowers.<\/p>\n\n\n\n<p>The technology can take over the following reimbursement tasks:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Prioritizing claims for payer follow-up and generating automated responses, using physician\u2019s notes.<\/li>\n\n\n\n<li>Automating the process of submitting claims to insurance providers and tracking their status.<\/li>\n\n\n\n<li>Verifying codes to improve coding accuracy.<\/li>\n\n\n\n<li>Identifying potential appeal opportunities by validating payer contracts.<\/li>\n\n\n\n<li>Monitoring payments from insurance providers and updating on any delays.<\/li>\n\n\n\n<li>Providing guidance on bills, insurance coverage, and payment options to patients.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-8-clinical-operations\">8. Clinical operations<\/h3>\n\n\n\n<p>Today, doctors have to spend twice as much time on computers as they do with patients. Post-visit notes, patient forms, and other paperwork drain healthcare professionals and leave them with little time on their hands. Much of this paperwork is identical, and therefore redundant.<\/p>\n\n\n\n<p>Clerical tasks are another strong suit for conversational AI in healthcare that can:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Churn out post-visit summaries, care summaries for referrals, standardized consent forms, utilization reports, and rate comparisons.<\/li>\n\n\n\n<li>Create and organize clinical notes, EMR updates, dictations, and messages.<\/li>\n\n\n\n<li>Outline workflow materials and schedules for processes.<\/li>\n\n\n\n<li>Develop training materials and personalized learning plans for clinicians.<\/li>\n\n\n\n<li>Create educational content on disease diagnosis and treatment.<\/li>\n<\/ul>\n\n\n\n<p>Conversational solutions can also work alongside a clinician during a patient visit to transcribe the clinician&#8217;s dictation into a structured note and auto-populate notes with EHR data.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-9-clinical-trials\">9. Clinical trials<\/h3>\n\n\n\n<p>With decentralized clinical trials sloping upwards and traditional clinical research grappling with patient maintenance, there\u2019s much on the plate for AI-driven conversational agents.&nbsp;<\/p>\n\n\n\n<p>Conversational AI can address many shortcomings of both conventional clinical trial execution and decentralized clinical trials:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Screening candidates based on eligibility criteria.<\/li>\n\n\n\n<li>Handling incoming clinical trial data, marrying it with images and lab results, and adding missing data points.<\/li>\n\n\n\n<li>Interacting with patients throughout the trial period to offer guidance on medication and prevent drop-outs.<\/li>\n\n\n\n<li>Identifying the right combination of drugs for an indication or the right patients.<\/li>\n\n\n\n<li>Fetching relevant data from clinical trial reports to prepare documentation for the FDA.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-10-back-office-work-and-administrative-functions\">10. Back-office work and administrative functions<\/h3>\n\n\n\n<p>Finance, staffing, legal activities, and other picks and shovels of healthcare keep a hospital system running. However, the majority of healthcare operations in the industry are siloed and rely on manual inputs that lead to errors, gaps, and discrepancies.<\/p>\n\n\n\n<p>Stepping up to the plate, conversational AI can shoulder the burden of repetitive tasks and introduce the following improvements across the board:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Automating the onboarding process, enabling self-serve HR functions, and streamlining feedback collection.<\/li>\n\n\n\n<li>Optimizing staff schedules based on availability, skills, and workload.<\/li>\n\n\n\n<li>Automating invoice processing, payment tracking, and account reconciliation.<\/li>\n\n\n\n<li>Validating contracts for compliance with legal and regulatory requirements.<\/li>\n\n\n\n<li>Updating on evolving compliance regulations and regulatory changes.<\/li>\n<\/ul>\n\n\n\n<div class=\"wp-block-cta-blog-block-cta cta-blog\"><span class=\"draw draw_color-right draw_undefined\"><\/span><span class=\"draw draw_color-left draw_gray\"><\/span><div class=\"cta-blog__wrap\"><div class=\"cta-blog__left\" style=\"max-width:367px\"><p class=\"cta-blog__title\">Create a healthier tomorrow, powered by conversational AI<\/p><p class=\"cta-blog__desc\"><\/p><\/div><div class=\"button button_undefined button_bg-gray cta-blog__btn\"><a href=\"#contact-form\" class=\"link-anchor\" target=\"_self\" rel=\"noopener\">Let\u2019s talk<\/a><\/div><\/div><div class=\"cta-blog__form form_light\"><\/div><\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-activate-holistic-healthcare-conversational-ai-for-your-organization-in-5-steps\">Activate holistic healthcare conversational AI for your organization in 5 steps<\/h2>\n\n\n\n<p>Bringing conversational AI to healthcare can alleviate a slew of pressure points, provided HCPs deploy the right tech, operational, and talent resources to develop a robust conversational AI strategy.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-identify-the-right-use-case\">Identify the right use case<\/h3>\n\n\n\n<p>A successful conversational AI project starts with <a href=\"https:\/\/www.instinctools.com\/blog\/ai-adoption-workshop\/\" target=\"_blank\" rel=\"noreferrer noopener\">prioritizing potential use cases<\/a> based on six key areas, including its impact, function, measurability, permission space, time to market, and extensibility. After identifying promising automation areas, organizations should design AI solutions to implement high-value use cases and determine any functional and technical gaps.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-tackle-the-70-percent-problem-of-data-readiness\">Tackle the 70 percent problem of data readiness<\/h3>\n\n\n\n<p>Data wrangling makes up <a href=\"https:\/\/www.mckinsey.com\/capabilities\/mckinsey-digital\/our-insights\/rewired-to-outcompete\" target=\"_blank\" rel=\"noreferrer noopener\" class=\"broken_link\">70%<\/a> of all <a href=\"https:\/\/www.instinctools.com\/blog\/ai-development\/\" target=\"_blank\" rel=\"noreferrer noopener\">AI development efforts<\/a>. Although healthcare has an edge over other industries in terms of data volume, most of this data is buried across fragmented systems in varying formats. Along with consolidating clinical and patient data, organizations might also need other data points to develop conversational AI solutions, such as PGHD, retail purchases, and wearable data.<\/p>\n\n\n\n<p>Specific use cases such as medication management and clinical decision support also require healthcare organizations to tap into literature and knowledge bases, pharmacy data, and clinical trial data.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-address-risks-and-biases\">Address risks and biases<\/h3>\n\n\n\n<p>If mishandled, conversational AI can exacerbate existing data risks in healthcare \u2014 as well as usher in new ones, such as its inclination to hallucinate. For example, if the training data skews towards certain patient populations, then the output of the conversational AI solution is likely to be biased, providing patients with inaccurate and potentially harmful insights.&nbsp;<\/p>\n\n\n\n<p>So, before making headway with the technology, make sure to outline risk and legal frameworks that will govern the use of conversational AI and account for its risks in organizations.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-plan-integrations\">Plan integrations<\/h3>\n\n\n\n<p>If your conversational AI solution needs to interface with other healthcare systems (and it probably does), you need to account for additional layers around it to integrate the solution with EHRs, CDSS, telehealth, and other platforms. Here, you need to identify the integration points, design integration architecture, and determine what types of connectors your solution needs.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-test-and-iterate\">Test and iterate<\/h3>\n\n\n\n<p>Instead of going all in and scaling your conversational AI solutions to adjacent use cases \u2014 test, evaluate, and refine the performance of your initial AI model. Make sure the output of the model is accurate, aligned with the healthcare domains, and performs well across multiple dimensions. If necessary, you can iterate to fine-tune the model performance and revisit your data management strategy.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-challenges-of-putting-conversational-ai-to-work-in-healthcare\">Challenges of putting conversational AI to work in healthcare<\/h2>\n\n\n\n<p>Conversational AI might be one of the most potent technologies to address the gaps in healthcare, but it\u2019s not the easiest to adopt. For example, a mere <a href=\"https:\/\/www.mckinsey.com\/industries\/healthcare\/our-insights\/reimagining-healthcare-industry-service-operations-in-the-age-of-ai\" target=\"_blank\" rel=\"noreferrer noopener\" class=\"broken_link\">10%<\/a> of patient interactions with healthcare conversational AI turn out to be successful and self-served. The following barriers might be to blame.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-data-management\">Data management<\/h3>\n\n\n\n<p>Healthcare notably has a data problem: its data is unstructured, sprinkled across siloed systems, and stored in varying formats. Moreover, many healthcare organizations lack the data maturity muscle, falling behind in data completeness, availability, and governance frameworks. For conversational AI, this data slump is not an option as it demands sufficient data for effective learning and prediction.<\/p>\n\n\n\n<p>To maximize the use of internal data, healthcare organizations must invest in a <a href=\"\/blog\/when-data-goes-bad-how-to-improve-data-quality\/\" target=\"_blank\" rel=\"noreferrer noopener\">comprehensive data management strategy<\/a>, including data standardization, data security, governance, and integration.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-regulatory-compliance\">Regulatory compliance<\/h3>\n\n\n\n<p>The healthcare sector is a regulation-heavy industry with strict AI compliance standards. To demonstrate commitment to PHI and PII security, your conversational AI solution must comply with HIPAA, GDPR, CCPA, and other applicable regulations. The majority of these regulations require your solutions to integrate specific data security measures, such as data minimization, data encryption at rest and in transit, and other mechanisms.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-technical-limitations\">Technical limitations<\/h3>\n\n\n\n<p>Over 73% of healthcare providers still rely on legacy information systems and architectures, making AI scale-ups a tough nut to crack. Complex integrations, data migration challenges, and even staff adoption reluctance \u2014 all stem from the tech stone age in healthcare. To break out of the tech rut and effectively leverage any type of artificial intelligence, healthcare leaders require an AI-ready tech infrastructure that includes centralized data repositories, cloud computing set-ups, and data controls and guardrails.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-ethical-considerations\">Ethical considerations<\/h3>\n\n\n\n<p>When it comes to something as high-stakes as conversational AI in healthcare, consumer trust hangs in the balance. Not all patients are enthusiastic about trading clinician advice for AI wisdom \u2014 and you need to address that if you plan to dabble in the technology. To address the skepticism, you can engage clinicians as change agents to demonstrate the credibility and clinical utility of AI.<\/p>\n\n\n\n<p>To warm up customers to the solution, your organization should also be explicit about how it uses conversational AI to assist doctors and what patient data it feeds on. The human-in-the-loop approach is essential in such critical areas as healthcare to mitigate the risks associated with AI and build trust with patients.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-conversational-ai-in-healthcare-a-new-pill-for-the-future\">Conversational AI in healthcare, a new pill for the future<\/h2>\n\n\n\n<p>With the repetitive task burden and the imperative for value-based care, the healthcare industry could benefit from conversational AI implementation. The latter, thanks to its unmatched automation potential and human-like interactions, can revolutionize healthcare delivery, boost operational efficiency, and put patients where they belong \u2014 at the center of care.<\/p>\n\n\n\n<p>Around <a href=\"https:\/\/www2.deloitte.com\/us\/en\/insights\/industry\/health-care\/consumer-trust-in-health-care-generative-ai.html\" target=\"_blank\" rel=\"noreferrer noopener\">59% of healthcare leaders<\/a> are already partnering with third-party vendors providing <a href=\"https:\/\/www.instinctools.com\/ai-development-company-in-usa\/\" target=\"_blank\" rel=\"noreferrer noopener\">AI development services in USA<\/a> to develop customized solutions. Those who succeed with scaling their conversational AI solutions past proof of concepts and to other use cases stand to gain early benefits that turn into long-term, flexible value.<\/p>\n\n\n\n<div class=\"wp-block-cta-blog-block-cta cta-blog\"><span class=\"draw draw_color-right draw_undefined\"><\/span><span class=\"draw draw_color-left draw_gray\"><\/span><div class=\"cta-blog__wrap\"><div class=\"cta-blog__left\" style=\"max-width:367px\"><p class=\"cta-blog__title\">Prescribe a dose of AI innovation to your healthcare organization<\/p><p class=\"cta-blog__desc\"><\/p><\/div><div class=\"button button_undefined button_bg-gray cta-blog__btn\"><a href=\"#contact-form\" class=\"link-anchor\" target=\"_self\" rel=\"noopener\">Contact our team<\/a><\/div><\/div><div class=\"cta-blog__form form_light\"><\/div><\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-faq\">FAQ<\/h2>\n\n\n\n<div class=\"schema-faq wp-block-yoast-faq-block\"><div class=\"schema-faq-section\" id=\"faq-question-1735552846732\"><strong class=\"schema-faq-question\">How is conversational AI used in healthcare?<\/strong> <p class=\"schema-faq-answer\">Conversational AI tools take many forms in healthcare. They can be used to enhance patient care, support clinical decision-making, improve patient experience, streamline insurance claims, analyze patient data, and supplement remote healthcare delivery.<\/p> <\/div> <div class=\"schema-faq-section\" id=\"faq-question-1735552895706\"><strong class=\"schema-faq-question\">Which is the best conversational AI?<\/strong> <p class=\"schema-faq-answer\">The choice of the model for a conversational AI solution depends on your unique needs. The quantity of training data, computational resources, model complexity, and other variables impact the selection.<\/p> <\/div> <div class=\"schema-faq-section\" id=\"faq-question-1735552911842\"><strong class=\"schema-faq-question\">Which type of AI is currently being used in medical care?<\/strong> <p class=\"schema-faq-answer\">Machine learning, natural language processing, generative AI, and conversational AI are some of the modalities currently in use in the healthcare industry.<\/p> <\/div> <\/div>\n","protected":false},"excerpt":{"rendered":"<p>Learn about the real-world implementations of conversational AI in healthcare. Top 10 high-value use cases with fast gains.<\/p>\n","protected":false},"author":29,"featured_media":98865,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"cta":"","footnotes":""},"categories":[715],"products_posts":[],"consulting_posts":[714],"industry_posts":[588],"engagement_model_posts":[],"class_list":["post-98857","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-development","consulting_posts-machine-learning-consulting","industry_posts-healthcare"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v24.5 (Yoast SEO v24.5) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Conversational AI in Healthcare 2024: Top 10 Use Cases and Examples | *instinctools<\/title>\n<meta name=\"description\" content=\"Learn about the real-world implementations of conversational AI in healthcare. 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They can be used to enhance patient care, support clinical decision-making, improve patient experience, streamline insurance claims, analyze patient data, and supplement remote healthcare delivery.","inLanguage":"en-US"},"inLanguage":"en-US"},{"@type":"Question","@id":"https:\/\/www.instinctools.com\/blog\/conversational-ai-in-healthcare\/#faq-question-1735552895706","position":2,"url":"https:\/\/www.instinctools.com\/blog\/conversational-ai-in-healthcare\/#faq-question-1735552895706","name":"Which is the best conversational AI?","answerCount":1,"acceptedAnswer":{"@type":"Answer","text":"The choice of the model for a conversational AI solution depends on your unique needs. 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