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Potential of GenAI in Healthcare

Potential of GenAI in Healthcare

Clinicians spend about 28 hours per week on administrative tasks, mainly clinical documentation and communication. Medical and claims staff reported even higher administrative loads, with 34 and 36 hours spent weekly on tasks like documentation, communication, and prior authorization. Many respondents linked these demands directly to burnout, with 77% of claims staff, 81% of medical staff, and 82% of clinicians citing administrative burdens as significant contributors. Additionally, 78% of payer executives and 85% of provider executives noted that administrative work is a key driver of staffing shortages.

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Value-Based Care Technologies

Value-Based Care Technologies

Essential Technologies for Value-Based Care Success As healthcare providers increasingly adopt value-based care, they must invest in the right technologies and resources to succeed in this model, which incentivizes high-quality, cost-effective care. Value-Based Care Technologies tie reimbursement to care quality, making providers accountable for patient outcomes while providing resources to enhance care. As of 2021, nearly 60% of healthcare payments were already tied to value-based models, according to the Health Care Payment Learning and Action Network (HCP LAN). While partnerships can initiate value-based care, providers must invest in the right technology to fully achieve the intended outcomes. Health Information Exchange (HIE) A robust health information exchange (HIE) is fundamental to value-based care, as it enables providers and payers to access high-quality data seamlessly. HIE allows healthcare professionals to share patients’ medical information electronically across organizations, promoting care coordination by giving providers a comprehensive view of patient needs. For patients, HIE enables more informed involvement in their care by making their health data accessible across specialists, labs, and pharmacies. While joining an HIE may involve new technology investments and workflow adjustments, it ultimately enhances provider access to critical health data. Population Health Management Tools Population health management tools help providers assess health outcomes within groups rather than focusing on individuals alone. These tools aggregate and analyze data, allowing practices to identify high-risk patients and create targeted interventions. This not only enhances health outcomes but can also reduce costs by avoiding expensive treatments. Patient engagement tools, such as telehealth and remote patient monitoring, are essential in population health management, especially for monitoring high-risk patients when in-person care is not feasible. Digital surveys integrated within patient portals can provide insights into social determinants of health, adding a broader context to patient needs. Data Analytics Data analytics transform healthcare data into actionable insights across four types: descriptive, diagnostic, predictive, and prescriptive. Providers can use these analytics to reduce hospital readmissions, predict diseases, and identify chronic illnesses. Data integration and risk stratification capabilities are especially valuable in value-based care, enabling providers to track patient health outcomes effectively and prioritize high-risk cases. Artificial Intelligence & Machine Learning AI and machine learning support many data analytics functions, helping identify patient needs and easing administrative burdens. Given staffing shortages and burnout—reported by 63% of physicians in 2021, according to the American Medical Association (AMA)—AI can automate tasks like documentation, charting, and scheduling, allowing providers to focus more on patient care. Additionally, AI-driven automation in revenue cycle management tasks, such as billing and coding, can reduce the administrative workload associated with value-based care. Price Transparency Technology Price transparency empowers patients to seek cost-effective care, a core principle of value-based models. When providers comply with transparency regulations, patients can better understand their costs and make informed decisions. For providers, leveraging price transparency tools ensures compliance and facilitates partnerships with payers by enabling more effective negotiation, which supports the overall goals of value-based care. As healthcare continues shifting to value-based models, investing in these technologies is critical for providers aiming for long-term success. While these tools rdo equire substantial investment, they are essential for improving patient outcomes, optimizing care quality, and ensuring sustainability in value-based care. When evaluating and choosing healthcare technology tools, contact Tectonic for help. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Digital Transformation for Life Sciences

Salesforce Winter 25 Release for Life Sciences

The Salesforce Winter ’25 release introduces groundbreaking updates tailored to the life sciences industry. Whether you’re in pharmaceuticals, biotech, or medical devices, these innovations aim to streamline operations, enhance patient care, and strengthen stakeholder relationships. Let’s explore the key enhancements: Quote and Agreement Automation Salesforce’s advancements in Quote and Agreement Automation simplify pricing and contractual negotiations for life sciences organizations. Key benefits include: These updates not only improve operational efficiency but also reduce errors and compliance risks, helping organizations stay ahead in a highly regulated industry. Financial Assistance Programs Navigating financial support for patients can be challenging, but Salesforce is making it easier. The Winter ’25 release enhances tools for managing financial assistance programs, ensuring eligible patients get the support they need. Key features include: By easing the financial burden on patients, these updates strengthen trust and foster better patient-provider relationships. Participant Recruitment and Enrollment Recruiting and enrolling participants for clinical trials is now more efficient with Salesforce’s new AI-driven tools. Notable improvements include: These updates not only shorten recruitment timelines but also enhance the overall trial experience for participants. Patient Program Outcome Management Tracking patient outcomes is vital for life sciences companies, and Salesforce’s Patient Program Outcome Management tools deliver powerful capabilities. Features include: These tools empower organizations to make data-driven decisions, improving program effectiveness and elevating patient care. Pharmacy Benefits Verification Verifying patient benefits is often a time-consuming task. The Winter ’25 release introduces automation to streamline this process. Key highlights: By simplifying benefits verification, this update enhances efficiency for providers and ensures a smoother experience for patients. Why It Matters for Life Sciences The Winter ’25 release is a leap forward for the life sciences industry, offering tools that: From automating quotes and agreements to improving patient support and trial management, these updates empower organizations to focus on delivering exceptional care and innovation. Ready to Transform Your Salesforce Experience?Tectonic is here to help you unlock the full potential of these enhancements. Whether you’re looking to optimize patient care, streamline operations, or improve outcomes, we’ll guide you every step of the way. Contact Tectonic today to get started! Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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healthcare Can prioritize ai governance

Healthcare Can Prioritize AI Governance

As artificial intelligence gains momentum in healthcare, it’s critical for health systems and related stakeholders to develop robust AI governance programs. AI’s potential to address challenges in administration, operations, and clinical care is drawing interest across the sector. As this technology evolves, the range of applications in healthcare will only broaden.

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Data Analytics for Disease Management

Data Analytics for Disease Management

Healthcare IT advancements, especially electronic health records (EHRs), have made it easier to gather and store data, which, in turn, fuels population health initiatives and improves patient outcomes. The Agency for Healthcare Research and Quality highlights that using health IT tools can significantly enhance chronic disease management by promoting efficient care delivery, information-sharing, and patient education. However, selecting and adopting the right analytics tools remains challenging. Here are five essential data analytics tools that healthcare providers can leverage for effective chronic disease management.

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Provider Hybrid Care Model

Provider Hybrid Care Model

Primary care in the United States urgently needs a redesign, as rural hospital closures and a shortage of providers are severely limiting access for nearly one-third of the population. While advanced technologies like virtual care have helped expand primary care access, there is still a strong preference for in-person visits. To address this, healthcare providers must create a hybrid care model that integrates both virtual and in-person services to better meet patient needs. Hackensack Meridian Health, a New Jersey-based health system, has embraced an AI-based solution to establish this hybrid care model. Through a partnership with K Health, the system aims to create a seamless patient journey that fluidly transitions between virtual and in-person care as needed. According to Dr. Daniel Varga, chief physician executive at Hackensack Meridian Health, the need for this partnership became apparent during the COVID-19 pandemic, which disrupted in-person care across New Jersey. “Before the pandemic, we did zero virtual visits in our offices,” Varga said. “By early 2020, we were doing thousands per day, and we realized there was real demand for it, but we didn’t have the skill set to execute it properly.” With the support of K Health, Varga believes the health system now has the technology and expertise to integrate AI-driven virtual care into its network of 18 hospitals. However, successful implementation requires overcoming technology integration challenges. The AI-Powered Virtual Care Solution The partnership between Hackensack Meridian Health and K Health has two key components, Varga explained. The first is a 24/7 AI-driven virtual care service, and the second is a professional services agreement between K Health’s doctors and the Hackensack medical group. The AI system used in the virtual care platform is built to learn from clinical data, distinguishing it from traditional symptom-checking tools. According to K Health co-founder Ran Shaul, the AI analyzes data from patients’ EHRs and symptom inputs to provide detailed insights into the patient’s health history, giving primary care providers a comprehensive view of the patient‘s current health concerns. “We know about your chronic conditions, your recent visits, and whether you’ve followed up on key health checks like mammograms,” Shaul explained. “It creates a targeted medical chart rather than a generic symptom analysis.” In addition, K Health’s virtual physicians and Hackensack Meridian’s medical group are integrated, sharing the same tax ID and EHR system, which ensures continuity of care between virtual and in-person visits. Varga highlighted that this integration allows for seamless transitions between care settings, where virtual doctors’ notes are readily available to in-person providers the following day. “If a patient sees a virtual doctor at 2 a.m., I have the 24/7 notes right in front of me the next morning in the office,” Varga said. The service is accessible to all patients, including new patients and those recently discharged from Hackensack Meridian Health’s inpatient services who require follow-up care. Overcoming Challenges in Implementation Deploying an AI-driven virtual care system across 18 hospitals presents significant challenges, but Hackensack Meridian Health has developed several strategies to ensure smooth implementation. First, the health system provided training to all 36,000 team members to familiarize them with the platform. Additionally, a dedicated team was created to enhance collaboration between the traditional medical group and the virtual care team. One major focus was connecting hospitals and 24/7 virtual care services to ensure continuity of care for patients leaving emergency departments or being discharged from inpatient care. “Many patients don’t have a primary care doctor when they leave the hospital,” Varga explained. “With this virtual service, we can immediately book a virtual appointment for them before they leave the ED.” Provider Hybrid Care Models provide better patient care, follow-up, and outcomes. The system also offers language accessibility, with patients able to interact with the platform in Spanish and request Spanish-speaking clinicians. This feature is part of the health system’s broader strategy to break down barriers to care access and improve health equity. Improving Access and Health Equity-Provider Hybrid Care Model Shaul noted that the convenience of scheduling virtual appointments at any time helps patients who would otherwise struggle to see a doctor due to work schedules or long travel distances. The virtual care service also addresses the needs of patients with limited English proficiency, allowing them to access care in their native language. By connecting patients who lack a usual source of care with primary care providers through the virtual platform, Hackensack Meridian Health aims to close care gaps. Access to primary care is critical for improving health outcomes, yet the number of Americans with a regular source of care has dropped by 10% in the past 18 years. This decline disproportionately affects Hispanic individuals, those with lower education levels, and the uninsured. Varga emphasized that the virtual care service aligns with Hackensack’s goal of meeting patients where they are—whether virtually, in their hospitals, or at brick-and-mortar medical offices. “The reason we have such a geographically diverse spread of sites is that we believe in meeting patients where they are,” Varga said. “If that means a virtual visit, we’ll meet them there. If it means the No. 1 ranked hospital in New Jersey, we’ll meet them there. And if it’s a medical office, that’s where we’ll meet them.” Salesforce and Tectonic can help your provider solution offer the same diversity. Contact us today! Heath and Life Sciences are winning a competitive edge with Salesforce for better patient outcomes. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. 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Einstein Copilot for Healthcare

Einstein Copilot for Healthcare

Einstein Copilot for Healthcare – Salesforce has introduced a new AI-powered healthcare assistant within its CRM system, marking its latest move to expand into the healthcare industry. As AI development accelerates, tech giants like Microsoft, Google, Amazon Web Services, and Salesforce are capitalizing on the opportunity to integrate AI and cloud technologies into healthcare to streamline administrative and operational tasks. Salesforce’s healthcare-specific AI tool, Einstein Copilot, is a conversational assistant that leverages an organization’s private data to provide relevant responses. Einstein Copilot enables healthcare providers and care teams to digitally capture and summarize information from both clinical and nonclinical sources, update patient records, and automate manual workflows. Key Features of Einstein Copilot Providers can use Einstein Copilot to generate patient summaries that include medications, diagnoses, social determinants, assessments, clinical service requests, and care gaps. A care manager can also ask the assistant to find an in-network provider based on location, specialty, and insurance coverage, and auto-fill referral forms using natural language prompts. The AI assistant can also trigger workflows for tasks such as sending referrals, scheduling appointments, and updating care plans. Salesforce expects Einstein Copilot to be HIPAA-compliant by summer 2024, with Copilot: Health Actions slated for general availability in winter 2024. Digitizing Health Assessments Salesforce is adding a feature called Assessment Generation that allows healthcare organizations to digitize standardized health assessments. These can be automatically populated into Salesforce Health Cloud, filled out electronically, and tracked for progress over time. Reducing Administrative Waste Salesforce cites research from McKinsey & Co. showing that administrative costs account for nearly a quarter of U.S. healthcare spending, with a potential savings of up to $320 billion. By integrating AI and CRM tools, Salesforce aims to reduce the operational burden on healthcare providers and improve patient outcomes. Amit Khanna, Senior Vice President and General Manager for Health at Salesforce, highlighted the value of these innovations: “These new data, AI, and CRM features reduce the administrative and operational burden for healthcare providers, leading to better outcomes for patients. With Salesforce’s trusted AI, healthcare organizations excited about generative AI—but wary of clinical and security concerns—can confidently integrate these innovations into their workflows.” Early Adopters and Impact Healthcare providers including Baptist Health South Florida and HarmonyCares are already leveraging Salesforce to personalize patient interactions and create unified patient views. HarmonyCares, which operates across 14 states with over 150 primary care providers, has used Salesforce’s AI-driven field service platform to streamline patient scheduling. The company reported a 50% increase in self-scheduling efficiency since adopting the platform and plans to expand its use of Salesforce Health Cloud for care management and engagement. Kristin Darby, Chief Information Officer at HarmonyCares, emphasized the benefits of AI in healthcare: “AI will dramatically improve our ability to quickly synthesize patient needs and preferences, enabling us to offer a more personalized experience with greater accuracy.” However, the integration of AI in healthcare is not without skepticism. A recent survey revealed that 69% of individuals are uncomfortable with AI being used to diagnose them, though more than half are open to its use in nonclinical tasks like scheduling and billing. Salesforce’s Healthcare Journey Salesforce first launched Health Cloud in 2015 to help providers manage patients by aggregating data from electronic medical records, devices, and wearables. In 2022, the company expanded this offering with Customer 360 for Health, a unified platform that combines real-time data from Data Cloud, Einstein AI, and automation tools like Flow to streamline processes such as prior authorizations, intake, and patient scheduling. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Gen AI to Predict and Automate Discharge

Gen AI to Predict and Automate Discharge

While electronic health records (EHRs) have improved data exchange for care coordination, they have also increased the clinical documentation burden on healthcare providers. Research from 2023 suggests that clinicians may now spend more time on EHRs than on direct patient care. On average, providers spend over 36 minutes on EHR tasks for every 30-minute patient visit. Generative AI, however, holds the potential to transform this. As defined by the Government Accountability Office, generative AI (GenAI) is a technology that can create content—such as text, images, audio, or video—based on user prompts. With the rise of chatbot interfaces like Chat-GPT, health IT vendors and healthcare systems are piloting GenAI tools to streamline clinical documentation. While the technology shows promise in reducing the documentation burden and mitigating clinician burnout, several challenges still hinder widespread adoption. Ambient Clinical Intelligence Ambient clinical intelligence leverages smartphone microphones and GenAI to transcribe patient encounters in real time, producing draft clinical documentation for providers to review within seconds. A 2024 study examined the use of ambient AI scribes by 10,000 physicians and staff at The Permanente Medical Group. The results were promising—providers reported better patient conversations and less after-hours EHR documentation. However, accuracy is critical for patient safety. A 2023 study found that ambient AI tools struggle with non-lexical conversational sounds (NLCSes)—like “mm-hm” and “uh-uh”—which patients and providers use to convey information. For instance, a patient might say “Mm-hm” to confirm they have no allergies to antibiotics. The study found that while the AI tools had a word error rate of 12% for all words, the error rate for NLCSes conveying clinically relevant information was as high as 98.7%. These inaccuracies could lead to patient safety risks, highlighting the importance of provider review. Patient Communication Patient portal messaging has surged since the COVID-19 pandemic, with a 2023 report showing a 157% increase in messages compared to pre-pandemic levels. To manage inbox overload, healthcare systems are exploring generative AI for drafting responses to patient messages. Clinicians review and edit these drafts before sending them to patients. A 2024 study found that primary care physicians rated AI-generated responses higher in communication style and empathy than those written by providers. However, the AI-generated responses were often longer and more complex, posing challenges for patients with lower health or English literacy. There are also potential risks to clinical decision-making. A 2024 simulation study revealed that the content of replies to patient messages changed when physicians used AI assistance, introducing an automation bias that could impact patient outcomes. Although most AI-generated drafts posed minimal safety risks, a small portion, if left unedited, could result in severe harm or death. Although GenAI may reduce the cognitive load of writing replies, it might not significantly decrease the overall time spent on patient communications. A recent study showed that while providers felt less emotional exhaustion when using AI to draft messages, the time spent on replying, reading, and writing messages remained unchanged from pre-pilot levels. Discharge Summaries Generative AI has also been shown to improve the readability of patient discharge summaries. A study published in JAMA Network Open demonstrated that GenAI could lower the reading level of discharge notes from an eleventh-grade to a sixth-grade level, which is more appropriate for diverse health literacy levels. However, accuracy is still a concern. Physician reviews of these AI-generated summaries found that while some were complete, others contained omissions and inaccuracies that raised safety concerns. Balancing AI’s Benefits with Oversight While generative AI shows promise in alleviating the documentation burden and improving patient communication, challenges remain. Issues such as accurately capturing non-verbal cues and ensuring document accuracy underscore the need for careful provider oversight. As AI technologies continue to evolve, ensuring that the benefits are balanced with provider review will be crucial for safe and effective healthcare implementation. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. 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collaboration between humans and AI

Collaboration Between Humans and AI

The Future of AI: What to Expect in the Next 5 Years In the next five years, AI will accelerate human life, reshape behaviors, and transform industries—these changes are inevitable. Collaboration Between Humans and AI. For much of the early 20th century, AI existed mainly in science fiction, where androids, sentient machines, and futuristic societies intrigued fans of the genre. From films like Metropolis to books like I, Robot, AI was the subject of speculative imagination. AI in fiction often over-dramatized reality and caused us to suspend belief in what was and was not possible. But by the mid-20th century, scientists began working to bring AI into reality. A Brief History of AI’s Impact on Society The 1956 Dartmouth Summer Research Project on Artificial Intelligence marked a key turning point, where John McCarthy coined the term “artificial intelligence” and helped establish a community of AI researchers. Although the initial excitement about AI often outpaced its actual capabilities, significant breakthroughs began emerging by the late 20th century. One such moment was IBM’s Deep Blue defeating chess champion Garry Kasparov in 1997, signaling that machines could perform complex cognitive tasks. The rise of big data and Moore’s Law, which fueled the exponential growth of computational power, enabled AI to process vast amounts of information and tackle tasks previously handled only by humans. By 2022, generative AI models like ChatGPT proved that machine learning could yield highly sophisticated and captivating technologies. AI’s influence is now everywhere. No longer is it only discussed in IT circles. AI is being featured in nearly all new products hitting the market. It is part of if not the creation tool of most commercials. Voice assistants like Alexa, recommendation systems used by Netflix, and autonomous vehicles represent just a glimpse of AI’s current role in society. Yet, over the next five years, AI’s development is poised to introduce far more profound societal changes. How AI Will Shape the Future Industries Most Affected by AI Long-term Risks of Collaboration Between Humans and AI AI’s potential to pose existential risks has long been a topic of concern. However, the more realistic danger lies in human societies voluntarily ceding control to AI systems. Algorithmic trading in finance, for example, demonstrates how human decisions are already being replaced by AI’s ability to operate at unimaginable speeds. Still, fear of AI should not overshadow the opportunities it presents. If organizations shy away from AI out of anxiety, they risk missing out on innovations and efficiency gains. The future of AI depends on a balanced approach that embraces its potential while mitigating its risks. In the coming years, the collaboration between humans and AI will drive profound changes across industries, legal frameworks, and societal norms, creating both challenges and opportunities for the future. Tectonic can help you map your AI journey for the best Collaboration Between Humans and AI. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Generative AI and Patient Engagement

Generative AI and Patient Engagement

The healthcare industry is undergoing a significant digital transformation, with generative AI and chatbots playing a prominent role in various patient engagement applications. Technologies such as online symptom checkers, appointment scheduling, patient navigation tools, medical search engines, and patient portal messaging are prime examples of how AI is enhancing patient-facing interactions. These advancements aim to alleviate staff workload while improving the overall patient experience, according to industry experts. However, even these patient-centric applications face challenges, such as the risk of generating medical misinformation or biased outcomes. As healthcare professionals explore the potential of generative AI and chatbots, they must also implement safeguards to prevent the spread of false information and mitigate disparities in care. Online Symptom Checkers Online symptom checkers allow patients to input their symptoms and receive a list of potential diagnoses, helping them decide the appropriate level of care, whether it’s urgent care or self-care at home. These tools hold promise for improving patient experiences and operational efficiency, reducing unnecessary healthcare visits. For healthcare providers, they help triage patients, ensuring those who need critical care receive it. However, the effectiveness of online symptom checkers is mixed. A 2022 literature review revealed that diagnostic accuracy ranged between 19% and 37.9%, while triage accuracy was higher, between 48.9% and 90%. Patient reception to these tools has been lukewarm as well, with some expressing dissatisfaction with the COVID-19 symptom checkers during the pandemic, mainly when the tools did not emulate human interaction. Moreover, studies have indicated that these tools might exacerbate health inequities, as users tend to be younger, female, and more digitally literate. To mitigate this, developers must ensure that chatbots can communicate in multiple languages, replicate human interactions, and escalate to human providers when needed. Self-Scheduling and Patient Navigation Generative AI and conversational AI have shown promise in addressing lower-level patient inquiries, such as appointment scheduling and navigation, reducing the strain on healthcare staff. AI-driven scheduling systems help fill gaps in navigation by assisting patients with appointment bookings and answering logistical questions, like parking or directions. A December 2023 review noted that AI-optimized patient scheduling reduces provider time burdens and improves patient satisfaction. However, barriers such as health equity, access to broadband, and patient trust must be addressed to ensure effective implementation. While organizations need to ensure these systems are accessible to all, AI is a valuable tool for managing routine patient requests, freeing staff to focus on more complex issues. Online Medical Research AI tools like ChatGPT are expanding on the “Dr. Google” phenomenon, offering patients a way to search for medical information. Despite initial concerns from clinicians about online medical searches, recent studies show that generative AI tools can provide accurate and understandable information. For instance, ChatGPT accurately answered breast cancer screening questions 88% of the time in one 2023 study and offered adequate colonoscopy preparation information in another. However, patients remain cautious about AI-generated medical advice. A 2023 survey revealed that nearly half of respondents were concerned about potential misinformation, and many were unsure about the sources AI tools use. Addressing these concerns by validating source material and providing supplementary educational resources will be crucial for building patient trust. Patient Portal Messaging and Provider Communication Generative AI is also finding its place in patient portal messaging, where it can generate responses to patient inquiries, helping to alleviate clinician burnout. In a 2024 study, AI-generated responses within a patient portal were often indistinguishable from those written by clinicians, requiring human editing in only 58% of cases. While chatbot-generated messages have been found to be more empathetic than those written by overworked providers, it’s important to ensure AI-generated responses are always reviewed by healthcare professionals to catch any potential errors. In addition to patient engagement, generative AI is being used in clinical decision support and ambient documentation, showcasing its potential to improve healthcare efficiency. However, developers and healthcare organizations must remain vigilant about preventing algorithmic bias and other AI-related risks. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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Promising Patient Engagement Use Cases for GenAI and Chatbots

Promising Patient Engagement Use Cases for GenAI and Chatbots

Promising Patient Engagement Use Cases for GenAI and Chatbots Generative AI (GenAI) is showing great potential in enhancing patient engagement by easing the burden on healthcare staff and clinicians while streamlining the overall patient experience. As healthcare undergoes its digital transformation, various patient engagement applications for GenAI and chatbots are emerging as promising tools. Let’s look at Promising Patient Engagement Use Cases for GenAI and Chatbots. Key applications of GenAI and patient-facing chatbots include online symptom checkers, appointment scheduling, patient navigation, medical search engines, and even patient portal messaging. These technologies aim to alleviate staff workloads while improving the patient journey, according to some experts. However, patient-facing AI applications are not without challenges, such as the risk of generating medical misinformation or exacerbating healthcare disparities through biased algorithms. As healthcare professionals explore the potential of GenAI and chatbots for patient engagement, they must also ensure safeguards are in place to prevent the spread of inaccuracies and avoid creating health inequities. Online Symptom Checkers Online symptom checkers allow healthcare organizations to assess patients’ medical concerns without requiring an in-person visit. Patients can input their symptoms, and the AI-powered chatbot will generate a list of possible diagnoses, helping them decide whether to seek urgent care, visit the emergency department, or manage symptoms at home. These tools promise to improve both patient experience and operational efficiency by directing patients to the right care setting, thus reducing unnecessary visits. For healthcare providers, symptom checkers can help triage patients and ensure high-acuity areas are available for those needing critical care. Despite their potential, studies show mixed results regarding the diagnostic accuracy of online symptom checkers. A 2022 literature review found that diagnostic accuracy for these tools ranged from 19% to 37.9%. However, triage accuracy—referring patients to the correct care setting—was better, ranging between 48.9% and 90%. Patient reception to symptom checkers has also been varied. For example, during the COVID-19 pandemic, symptom checkers were designed to help patients assess whether their symptoms were virus-related. While patients appreciated the tools, they preferred chatbots that displayed human-like qualities and competence. Tools perceived as similar in quality to human interactions were favored. Furthermore, some studies indicate that online symptom checkers could deepen health inequities, as users tend to be younger, female, and more digitally literate. To mitigate this, AI developers must create chatbots that can communicate in multiple languages, mimic human interaction, and easily escalate issues to human professionals when needed. Self-Scheduling and Patient Navigation GenAI and conversational AI are proving valuable in addressing routine patient queries, like appointment scheduling and patient navigation, tasks that typically fall on healthcare staff. With a strained medical workforce, using AI for lower-level inquiries allows clinicians to focus on more complex tasks. AI-enhanced appointment scheduling systems, for example, not only help patients book visits but also answer logistical questions like parking directions or department locations within a clinic. A December 2023 literature review highlighted that AI-optimized scheduling could reduce provider workload, increase patient satisfaction, and make healthcare more patient-centered. However, key considerations for AI integration include ensuring health equity, broadband access, and patient trust. While AI can manage routine requests, healthcare organizations need to ensure their tools are accessible and functional for diverse populations. Online Medical Research GenAI tools like ChatGPT are contributing to the “Dr. Google” phenomenon, where patients search online for medical information before seeing a healthcare provider. While some clinicians have been cautious about these tools, research suggests they can effectively provide accurate medical information. For instance, an April 2023 study showed that ChatGPT answered 88% of breast cancer screening questions correctly. Another study in May 2023 demonstrated that the tool could adequately educate patients on colonoscopy preparation. In both cases, the information was presented in an easy-to-understand format, essential for improving health literacy. However, GenAI is not without flaws. Patients express concern about the reliability of AI-generated information, with a 2023 Wolters Kluwer survey showing that 49% of respondents worry about false information from GenAI. Additionally, many are uneasy about the unknown sources and validation processes behind the information. To build patient trust, AI developers must ensure the accuracy of their source material and provide supplementary authoritative resources like patient education materials. Patient Portal Messaging and Provider Communication Generative AI has also found use in patient portal messaging, where it can draft responses on behalf of healthcare providers. This feature has the potential to reduce clinician burnout by handling routine inquiries. A study conducted at Mass General Brigham in April 2024 revealed that a large language model embedded in a secure messaging tool could generate acceptable responses to patient questions. In 58% of cases, chatbot-generated messages required human editing. Promising Patient Engagement Use Cases for GenAI and Chatbots Interestingly, other research has found that AI-generated responses in patient portals are often more empathetic than those written by overworked healthcare providers. Nevertheless, AI responses should always be reviewed by a clinician to ensure accuracy before being sent to patients. Generative AI is also making strides in clinical decision support and ambient documentation, further boosting healthcare efficiency. However, as healthcare organizations adopt these technologies, they must address concerns around algorithmic bias and ensure patient safety remains a top priority. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

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Embedded Salesforce Einstein

Embedded Salesforce Einstein

In a world where data is everything, businesses are constantly seeking ways to better understand their customers, streamline operations, and make smarter decisions. Enter Salesforce Einstein—a powerful AI solution embedded within the Salesforce platform that is revolutionizing how companies operate, regardless of size. By leveraging advanced analytics, automation, and machine learning, Einstein helps businesses boost efficiency, drive innovation, and deliver exceptional customer experiences. Embedded Salesforce Einstein is the answer. Here’s how Salesforce Einstein is transforming business: Imagine anticipating customer needs, market trends, or operational challenges before they happen. While it’s not magic, Salesforce Einstein’s AI-powered insights and predictions come remarkably close. By transforming vast amounts of data into actionable insights, Einstein enables businesses to anticipate future scenarios and make well-informed decisions. Industry insight: In financial services, success hinges on anticipating market shifts and client needs. Banks and investment firms leverage Einstein to analyze historical market data and client behavior, predicting which financial products will resonate next. For example, investment advisors might receive AI-driven recommendations tailored to individual clients, boosting engagement and satisfaction. Manufacturers also benefit from Einstein’s predictive maintenance tools, which analyze data from machinery to anticipate equipment failures. A car manufacturer, for instance, could use these insights to schedule maintenance during off-peak hours, minimizing downtime and preventing costly disruptions. Personalization is now a necessity. Salesforce Einstein elevates personalization by analyzing customer data to offer tailored recommendations, messages, and services. Industry insight: In e-commerce, personalized recommendations are often the key to converting browsers into loyal customers. An online bookstore using Einstein might analyze browsing history and past purchases to suggest new releases in genres the customer loves, driving repeat sales. In healthcare, Einstein’s personalization can improve patient outcomes by providing customized follow-up care. Hospitals can use Einstein to analyze patient histories and treatment data, offering reminders tailored to each patient’s needs, improving adherence to care plans and speeding recovery. Salesforce Einstein’s sales intelligence tools, such as Lead Scoring and Opportunity Insights, enable sales teams to focus on the most promising leads. This targeted approach drives higher conversion rates and more efficient sales processes. Industry insight: In real estate, Einstein helps agents manage numerous leads by scoring potential buyers based on their engagement with property listings. A buyer who repeatedly views homes in a specific area is flagged, prompting agents to prioritize their outreach, accelerating the sales process. In the automotive industry, Einstein identifies leads closer to purchasing by analyzing behaviors such as online vehicle configuration and test drive bookings. This allows sales teams to focus on high-potential buyers, closing deals faster. Automation is at the heart of Salesforce Einstein’s ability to streamline processes and boost productivity. By automating repetitive tasks like data entry and customer inquiries, Einstein frees employees to focus on strategic activities, improving overall efficiency. Industry insight: In insurance, Einstein Bots can handle routine tasks like policy inquiries and claim submissions, freeing up human agents for more complex issues. This leads to faster response times and reduced operational costs. In banking, Einstein-powered chatbots manage routine inquiries such as balance checks or transaction histories. By automating these interactions, banks reduce the workload on call centers, allowing agents to provide more personalized financial advice. Einstein Discovery democratizes data analytics, making it easier for non-technical users to explore data and uncover actionable insights. This tool identifies key business drivers and provides recommendations, making data accessible for all. Industry insight: In healthcare, predictive insights are helping providers identify patients at risk of chronic conditions like diabetes. With Einstein Discovery, healthcare providers can flag at-risk individuals early, implementing targeted care plans that improve outcomes and reduce long-term costs. For energy companies, Einstein Discovery analyzes data from sensors and weather patterns to predict equipment failures and optimize resource management. A utility company might use these insights to schedule preventive maintenance ahead of storms, reducing outages and enhancing service reliability. More Than a Tool – Embedded Salesforce Einstein Salesforce Einstein is more than just an AI tool—it’s a transformative force enabling businesses to unlock the full potential of their data. From predicting trends and personalizing customer experiences to automating tasks and democratizing insights, Einstein equips companies to make smarter decisions and enhance performance across industries. Whether in retail, healthcare, or technology, Einstein delivers the tools needed to thrive in today’s competitive landscape. Tectonic empowers organizations with Salesforce solutions that drive organizational excellence. Contact Tectonic today. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. 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Salesforce AI Tools for Healthcare

Salesforce AI Tools for Healthcare

Salesforce to Launch Pre-Built AI Tools for Healthcare in October Salesforce is introducing a new library of out-of-the-box AI tools specifically designed for healthcare operations, available through its Health Cloud. These generative AI features aim to streamline time-consuming tasks by integrating directly into clinician workflows, enhancing both the quality and efficiency of patient care. Key Features and Benefits Part of Salesforce’s broader initiative to address operational challenges across 15 industries, these healthcare-specific AI tools are embedded in each of its industry clouds. The Einstein Copilot, for example, will allow healthcare providers to generate patient summaries in natural language, leveraging new data management capabilities. This could enable care coordinators to view comprehensive patient summaries—such as care plans, prescriptions, and prior authorizations—before appointments. According to Salesforce, these AI-driven services, powered by Einstein prompts, are integrated within Health Cloud’s member accounts, simplifying administrative tasks like sending referrals and booking appointments. Data privacy and security remain a priority, with Einstein’s data masking and zero data retention layer ensuring patient information is protected. Beyond patient care, the new AI features will support business operations, including verifying insurance coverage, determining out-of-pocket costs, and ensuring eligibility—all designed to reduce administrative burdens and improve operational efficiency. Why It Matters Healthcare organizations often lack the resources to build and train their own AI models, a process that can cost upwards of 0 million. Salesforce’s pre-built AI capabilities provide an accessible solution, allowing organizations of all sizes to adopt AI tools tailored to their specific needs. By automating administrative processes, healthcare providers can focus more on patient care, with faster approvals and fewer manual tasks. Salesforce is positioning these tools to help organizations streamline workflows, reduce inefficiencies, and ultimately improve the patient experience. The features will be generally available in October, with pricing based on specific implementations. Industry Impact and Larger Trend The release of these healthcare-specific AI tools is part of Salesforce’s broader push into industry-specific AI. In March, Salesforce launched the Einstein AI Copilot within its Einstein 1 Platform, designed to leverage healthcare organizations’ unique data within its Health Data Cloud. New capabilities, such as patient services and benefits verification, aim to reduce platform switching, enabling faster approvals and supporting clinicians in real-time patient record updates. Salesforce’s investment in industry-specific AI comes at a time when many healthcare organizations are grappling with the rising costs of technology and labor. At the HIMSS AI in Healthcare Forum in Boston, leaders echoed the challenges of managing expansive technology footprints while balancing the need for AI-driven transformation. Operational workflows, particularly back-office processes, offer a low-risk area for AI deployment, as noted by Lee Schwamm, chief digital health officer at Yale New Haven Health System. On the Record “Organizations of every size and budget can now easily get started with practical AI tools that were purposefully designed to solve their unique challenges,” said Jeff Amann, executive vice president and general manager of Salesforce Industries. Salesforce’s new AI use case library, featuring more than 100 AI capabilities embedded across 15 industry clouds, underscores the company’s commitment to developing industry-specific solutions. For healthcare, these tools include automated patient matching for clinical trials, AI-generated prescriptions, and pre-visit summaries—helping organizations accelerate time to care and improve clinical outcomes. In addition, a new auto-matching tool for life sciences will assist in identifying eligible clinical trial participants, using both structured and unstructured data to reduce assessment time. These features allow healthcare CIOs to easily deploy AI capabilities designed to address their organization’s unique needs. Looking Ahead Salesforce’s latest AI tools for healthcare represent a significant step in the company’s strategy to bring industry-specific AI to market, with healthcare, life sciences, financial services, and retail among its top priorities. By offering pre-built, customizable solutions, Salesforce is making AI accessible to a broader range of organizations, enabling them to deliver value quickly while navigating the complexities of modern healthcare operations. 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Challenges for Rural Healthcare Providers

Challenges for Rural Healthcare Providers

Rural healthcare providers have long grappled with challenges due to their geographic isolation and limited financial resources. The advent of digital health transformation, however, has introduced a new set of IT-related obstacles for these providers. EHR Adoption and New IT Challenges While federal legislation has successfully promoted Electronic Health Record (EHR) adoption across both rural and urban healthcare organizations, implementing an EHR system is only one component of a comprehensive health IT strategy. Rural healthcare facilities encounter numerous IT barriers, including inadequate infrastructure, interoperability issues, constrained resources, workforce shortages, and data security concerns. Limited Broadband Access Broadband connectivity is essential for leveraging health IT effectively. However, there is a significant disparity in broadband access between rural and urban areas. According to a Federal Communications Commission (FCC) report, approximately 96% of the U.S. population had access to broadband at the FCC’s minimum speed benchmark in 2019, compared to just 73.6% of rural Americans. The lack of broadband infrastructure hampers rural organizations’ ability to utilize IT features that enhance care delivery, such as electronic health information exchange (HIE) and virtual care. Rural facilities, in particular, rely heavily on HIE and telehealth to bridge gaps in their services. For instance, HIE facilitates data sharing between smaller ambulatory centers and larger academic medical centers, while telehealth allows rural clinicians to consult with specialists in urban centers. Additionally, telehealth can help patients in rural areas avoid long travel distances for care. However, without adequate broadband access, these services remain impractical. Despite persistent disparities, the rural-urban broadband gap has narrowed in recent years. Data from the FCC indicates that since 2016, the number of people in rural areas without access to 25/3 Mbps service has decreased by more than 46%. Various programs, including the FCC’s Rural Health Care Program and USDA funding initiatives, aim to expand broadband access in rural regions. Interoperability Challenges While HIE adoption is rising nationally, rural healthcare organizations lag behind their urban counterparts in terms of interoperability capabilities, as noted in a 2023 GAO report. Data from a 2021 American Hospital Association survey revealed that rural hospitals are less likely to engage in national or regional HIE networks compared to medium and large hospitals. Rural providers often lack the economic and technological resources to participate in electronic HIE networks, leading them to rely on manual data exchange methods such as fax or mail. Additionally, rural providers are less likely to join EHR vendor networks for data exchange, partly due to the fact that they often use different systems from those in other local settings, complicating health data exchange. Federal initiatives like TEFCA aim to improve interoperability through a network of networks approach, allowing organizations to connect to multiple HIEs through a single connection. However, TEFCA’s voluntary participation model and persistent barriers such as IT staffing shortages and broadband gaps still pose challenges for rural providers. Financial Constraints Rural hospitals often operate with slim profit margins due to lower patient volumes and higher rates of uninsured or underinsured patients. The financial strain is exacerbated by declining Medicare and Medicaid reimbursements. According to KFF, the median operating margin for rural hospitals was 1.5% in 2019, compared to 5.2% for other hospitals. With limited budgets, rural healthcare organizations struggle to invest in advanced health IT systems and the necessary training and maintenance. Many small rural hospitals are turning to cloud-based EHR platforms as a cost-effective solution. Cloud-based EHRs reduce the need for substantial upfront hardware investments and offer monthly subscription fees, some as low as $100 per month. Workforce Challenges The healthcare sector is facing widespread staff shortages, including a lack of skilled health IT professionals. Rural areas are disproportionately affected by these shortages. An insufficient number of IT specialists can impede the adoption and effective use of health IT in these regions. To address workforce gaps, the ONC suggests strategies such as cross-training multiple staff members in health IT functions and offering additional training opportunities. Some networks, like OCHIN, have secured grants to develop workforce programs, but limited broadband access can hinder participation in virtual training programs, highlighting the need for expanded broadband infrastructure. Data Security Concerns Healthcare data breaches have surged, with a 256% increase in large breaches reported to the Office for Civil Rights (OCR) over the past five years. Rural healthcare organizations, often operating with constrained budgets, may lack the resources and staff to implement robust data security measures, leaving them vulnerable to cyber threats. A cyberattack on a rural healthcare organization can disrupt patient care, as patients may need to travel significant distances to reach alternative facilities. To address cybersecurity challenges, recent legislative efforts like the Rural Hospital Cybersecurity Enhancement Act aim to develop comprehensive strategies for rural hospital cybersecurity and provide educational resources for staff training. In the interim, rural healthcare organizations can use free resources such as the Health Industry Cybersecurity Practices (HICP) publication to guide their cybersecurity strategies, including recommendations for managing vulnerabilities and protecting email systems. Does your practice need help meeting these challenges? Contact Tectonic today. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. 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