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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 Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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NetSuite Salesforce Collaboration

NetSuite Salesforce Collaboration

NetSuite Bets on Strategic Growth and Embraces Collaboration with Salesforce Growing on All Fronts At SuiteWorld 2024, the theme, “All Systems Grow,” reflected a pivotal moment for NetSuite. While the event lacked groundbreaking announcements, it showcased a fulfillment of past promises and a notable strategic shift toward openness and collaboration. Oracle and NetSuite are now welcoming competitors as partners, signaling a move toward interoperability that could redefine their market positioning. With over 40,000 customers, NetSuite continues its strong growth in the ERP space, particularly among SMBs. The company’s Q3 sales surged 20% year-over-year, underlining its momentum in the mid-market. Beyond traditional ERP capabilities, NetSuite’s expanded suite of solutions positions it as more than just an ERP provider. Delivering on AI Innovations While there were no splashy acquisitions, NetSuite made significant strides by rolling out 170 new modules and features, many leveraging AI. These enhancements blend predictive AI and generative AI to increase accuracy and user productivity. These updates aim to elevate both the platform’s quality and the efficiency of its users. Redwood Design: A Transformative User Experience NetSuite is adopting Oracle’s Redwood design language, promising a more intuitive and user-friendly interface. While Redwood is not new, its phased rollout within NetSuite is a significant step forward. Notable Additions: SuiteProcurement and Salesforce Integration SuiteProcurement: NetSuite’s new procurement automation solution integrates directly with Amazon Business and Staples Business Advantage, automating ordering, invoicing, approvals, and deliveries. Plans are underway to expand vendor support, offering broader applicability in the future. Salesforce Partnership: NetSuite’s most significant announcement was its strategic partnership with Salesforce, enabling real-time data exchange between the platforms. Evan Goldberg, NetSuite’s founder and EVP, explained the rationale:“It’s up to the customer to decide what software they want to use.” The partnership reflects NetSuite’s commitment to addressing customer needs, with more SaaS integrations expected in the future. Expanding Field Service Management (FSM) NetSuite’s Field Service Management (FSM) capabilities, acquired last year, are now better integrated into its platform. While development progress has been slower than anticipated, significant enhancements are expected in the coming year, leveraging Oracle technology to extend FSM’s functionality across industries. And Field Service Management is available in Salesforce, as well. Positioned for Continued SMB Growth NetSuite’s investments are yielding results, as demonstrated by its rapid growth and deeper integration of Oracle technology. The NetSuite Analytics Data Warehouse and Enterprise Performance Management are driving adoption among existing users, showcasing the platform’s scalability. NetSuite’s ability to quickly integrate Oracle updates into its infrastructure gives it a competitive edge, ensuring customers benefit from the latest innovations without delays. With its robust feature set, AI-powered tools, and strategic partnerships like the one with Salesforce, NetSuite has strengthened its position as a go-to ERP platform for SMBs. Its consistent 20% year-over-year growth indicates a bright future, making it an increasingly attractive option for mid-market businesses. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Rise of Agentforce

Rise of Agentforce

The Rise of Agentforce: How AI Agents Are Shaping the Future of Work Salesforce wrapped up its annual Dreamforce conference this September, leaving attendees with more than just memories of John Mulaney’s quips. As the swarms of Waymos ferried participants across a cleaner-than-usual San Francisco, it became clear that AI-powered agents—dubbed Agentforce—are poised to transform the workplace. These agents, controlled within Salesforce’s ecosystem, could significantly change how work is done and how customer experiences are delivered. Dreamforce has always been known for its bold predictions about the future, but this year’s vision of AI-based agents felt particularly compelling. These agents represent the next frontier in workplace automation, but as exciting as this future is, some important questions remain. Reality Check on the Agentforce Vision During his keynote, Salesforce CEO Marc Benioff raised an interesting point: “Why would our agents be so low-hallucinogenic?” While the agents have access to vast amounts of data, workflows, and services, they currently function best within Salesforce’s own environment. Benioff even made the claim that Salesforce pioneered prompt engineering—a statement that, for some, might have evoked a scene from Austin Powers, with Dr. Evil humorously taking credit for inventing the question mark. But can Salesforce fully realize its vision for Agentforce? If they succeed, it could be transformative for how work gets done. However, as with many AI-driven innovations, the real question lies in interoperability. The Open vs. Closed Debate As powerful as Salesforce’s ecosystem is, not all business data and workflows live within it. If the future of work involves a network of AI agents working together, how far can a closed ecosystem like Salesforce’s really go? Apple, Microsoft, Amazon, and other tech giants also have their sights set on AI-driven agents, and the race is on to own this massive opportunity. As we’ve seen in previous waves of technology, this raises familiar debates about open versus closed systems. Without a standard for agents to work together across platforms, businesses could find themselves limited. Closed ecosystems may help solve some problems, but to unlock the full potential of AI agents, they must be able to operate seamlessly across different platforms and boundaries. Looking to the Open Web for Inspiration The solution may lie in the same principles that guide the open web. Just as mobile apps often require a web view to enable an array of outcomes, the same might be necessary in the multi-agent landscape. Tools like Slack’s Block Kit framework allow for simple agent interactions, but they aren’t enough for more complex use cases. Take Clockwise Prism, for example—a sophisticated scheduling agent designed to find meeting times when there’s no obvious availability. When integrated with other agents to secure that critical meeting, businesses will need a flexible interface to explore multiple scheduling options. A web view for agents could be the key. The Need for an Open Multi-Agent Standard Benioff repeatedly stressed that businesses don’t want “DIY agents.” Enterprises seek controlled, repeatable workflows that deliver consistent value—but they also don’t want to be siloed. This is why the future requires an open standard for agents to collaborate across ecosystems and platforms. Imagine initiating a set of work agents from within an Atlassian Jira ticket that’s connected to a Salesforce customer case—or vice versa. For agents to seamlessly interact regardless of the system they originate from, a standard is needed. This would allow businesses to deploy agents in a way that’s consistent, integrated, and scalable. User Experience and Human-in-the-Loop: Crucial Elements for AI Agents A significant insight from the integration of LangChain with Assistant-UI highlighted a crucial factor: user experience (UX). Whether it’s streaming, generative interfaces, or human-in-the-loop functionality, the UX of AI agents is critical. While agents need to respond quickly and efficiently, businesses must have the ability to involve humans in decision-making when necessary. This principle of human-in-the-loop is key to the agent’s scheduling process. While automation is the goal, involving the user at crucial points—such as confirming scheduling options—ensures that the agent remains reliable and adaptable. Any future standard must prioritize this capability, allowing for user involvement where necessary, while also enabling full automation when confidence levels are high. Generative or Native UI? The discussion about user interfaces for agents often leads to a debate between generative UI and native UI. The latter may be the better approach. A native UI, controlled by the responding service or agent, ensures the interface is tailored to the context and specifics of the agent’s task. Whether this UI is rendered using AI or not is an implementation detail that can vary depending on the service. What matters is that the UI feels native to the agent’s task, making the user experience seamless and intuitive. What’s Next? The Push for an Open Multi-Agent Future As we look ahead to the multi-agent future, the need for an open standard is more pressing than ever. At Clockwise, we’ve drafted something we’re calling the Open Multi-Agent Protocol (OMAP), which we hope will foster collaboration and innovation in this space. The future of work is rapidly approaching, where new roles—like Agent Orchestrators—will emerge, enabling people to leverage AI agents in unprecedented ways. While Salesforce’s vision for Agentforce is ambitious, the key to unlocking its full potential lies in creating a standard that allows agents to work together, across platforms, and beyond the boundaries of closed ecosystems. With the right approach, we can create a future where AI agents transform work in ways we’re only beginning to imagine. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial

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Salesforce Government Cloud Premium

Salesforce Government Cloud Premium

Software company Salesforce announced on Monday that it has rolled out a new version of its government cloud that has Top Secret authorization and is geared toward U.S. national security agencies and intelligence organizations.

The new offering, called Government Cloud Premium, is hosted on Amazon Web Services’ Top Secret cloud.

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Collaborative Business Intelligence

Collaborative Business Intelligence

Collaborative Business Intelligence: Connecting Data and Teams In today’s data-driven world, the ability to interact with business intelligence (BI) tools is essential for making informed decisions. Collaborative business intelligence (BI), also known as social BI, allows users to engage with their organization’s data and communicate with data experts through the same platforms where they already collaborate. While self-service BI empowers users to generate insights, understanding the data’s context is critical to avoid misunderstandings that can derail decision-making. Collaborative BI integrates BI tools with collaboration platforms to bridge the gap between data analysis and communication, reducing the risks of misinterpretation. Traditional Business Intelligence Traditional BI involves the use of technology to analyze data and present insights clearly. Before BI platforms became widespread, data scientists and statisticians handled data analysis, making it challenging for non-technical professionals to digest the insights. BI evolved to automate visualizations, such as charts and dashboards, making data more accessible to business users. Previously, BI reports were typically available only to high-level executives. However, modern self-service BI tools democratize access, enabling more users—regardless of technical expertise—to create reports and visualize data, fostering better decision-making across the organization. The Emergence of Collaborative BI Collaborative BI is a growing trend, combining BI applications with collaboration tools. This approach allows users to work together synchronously or asynchronously within a shared platform, making it easier to discuss data reports in real time or leave comments for others to review. Whether it’s through Slack, Microsoft Teams, or social media apps, users can receive and discuss BI insights within their usual communication channels. This seamless integration of BI and collaboration tools offers a competitive edge, simplifying the process of sharing knowledge and clarifying data without switching between applications. Key Benefits of Collaborative Business Intelligence Leading Collaborative BI Platforms Here’s a look at some of the top collaborative BI platforms driving innovation in the market: Conclusion Collaborative BI empowers organizations by improving decision-making, democratizing data access, optimizing data quality, and ensuring data security. By integrating BI tools with collaboration platforms, businesses can streamline their operations, foster a culture of data-driven decision-making, and enhance overall efficiency. Choosing the right platform is key to maximizing the benefits of collaborative BI. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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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 Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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TEFCA could drive payer-provider interoperability

TEFCA could drive payer-provider interoperability

Bridging the Interoperability Gap: TEFCA’s Role in Payer-Provider Data Exchange The electronic health information exchange (HIE) between healthcare providers has seen significant growth in recent years. However, interoperability between healthcare providers and payers has lagged behind. The Trusted Exchange Framework and Common Agreement (TEFCA) aims to address this gap and enhance data interoperability across the healthcare ecosystem. TEFCA could drive payer-provider interoperability with a little help from the world of technology. TEFCA’s Foundation and Evolution TEFCA was established under the 21st Century Cures Act to improve health data interoperability through a “network of networks” approach. The Office of the National Coordinator for Health Information Technology (ONC) officially launched TEFCA in December 2023, designating five initial Qualified Health Information Networks (QHINs). By February 2024, two additional QHINs had been designated. The Sequoia Project, TEFCA’s recognized coordinating entity, recently released several key documents for stakeholder feedback, including draft standard operating procedures (SOPs) for healthcare operations and payment under TEFCA. During the 2024 WEDI Spring Conference, leaders from three QHINs—eHealth Exchange, Epic Nexus, and Kno2—discussed the future of TEFCA in enhancing provider and payer interoperability. ONC released Version 2.0 of the Common Agreement on April 22, 2024. Common Agreement Version 2.0 updates Common Agreement Version 1.1, published in November 2023, and includes enhancements and updates to require support for Health Level Seven (HL7®) Fast Healthcare Interoperability Resources (FHIR®) based transactions. The Common Agreement includes an exhibit, the Participant and Subparticipant Terms of Participation (ToP), that sets forth the requirements each Participant and Subparticipant must agree to and comply with to participate in TEFCA. The Common Agreement and ToPs incorporate all applicable standard operating procedures (SOPs) and the Qualified Health Information Network Technical Framework (QTF). View the release notes for Common Agreement Version 2.0 The Trusted Exchange Framework and Common AgreementTM (TEFCATM) has 3 goals: (1) to establish a universal governance, policy, and technical floor for nationwide interoperability; (2) to simplify connectivity for organizations to securely exchange information to improve patient care, enhance the welfare of populations, and generate health care value; and (3) to enable individuals to gather their health care information. Challenges in Payer Data Exchange Although the QHINs on the panel have made progress in facilitating payer HIE, they emphasized that TEFCA is not yet fully operational for large-scale payer data exchange. Ryan Bohochik, Vice President of Value-Based Care at Epic, highlighted the complexities of payer-provider data exchange. “We’ve focused on use cases that allow for real-time information sharing between care providers and insurance carriers,” Bohochik said. “However, TEFCA isn’t yet capable of supporting this at the scale required.” Bohochik also pointed out that payer data exchange is complicated by the involvement of third-party contractors. For example, health plans often partner with vendors for tasks like care management or quality measure calculation. This adds layers of complexity to the data exchange process. Catherine Bingman, Vice President of Interoperability Adoption for eHealth Exchange, echoed these concerns, noting that member attribution and patient privacy are critical issues in payer data exchange. “Payers don’t have the right to access everything a patient has paid for themselves,” Bingman said. “This makes providers cautious about sharing data, impacting patient care.” For instance, manual prior authorization processes frequently delay patient access to care. A 2023 AMA survey found that 42% of doctors reported care delays due to prior authorization, with 37% stating that these delays were common. Building Trust Through Use Cases Matt Becker, Vice President of Interoperability at Kno2, stressed the importance of developing specific use cases to establish trust in payer data exchange via TEFCA. “Payment and operations is a broad category that includes HEDIS measures, quality assurance, and provider monitoring,” Becker said. “Each of these requires a high level of trust.” Bohochik agreed, emphasizing that narrowing the scope and focusing on specific, high-value use cases will be essential for TEFCA’s adoption. “We can’t solve everything at once,” Bohochik said. “We need to focus on achieving successful outcomes in targeted areas, which will build momentum and community support.” He also noted that while technical data standards are crucial, building trust in the data exchange process is equally important. “A network is only as good as the trust it inspires,” Bohochik said. “If healthcare systems know that data requests for payment and operations are legitimate and secure, it will drive the scalability of TEFCA.” By focusing on targeted use cases, ensuring rigorous data standards, and building trust, TEFCA has the potential to significantly enhance interoperability between healthcare providers and payers, ultimately improving patient care and operational efficiency. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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AI Agents and Open APIs

AI Agents and Open APIs

How AI Agents and Open APIs Are Unlocking New Rebundling Opportunities While much of the 2023-24 excitement surrounding AI has focused on the capabilities of foundational models, the true potential of AI lies in reconfiguring value creation across vertical value chains, not just generating average marketing content. The Vertical AI Opportunity Most AI hype has centered on horizontal B2C applications, but the real transformative power of AI is in vertical B2B industries. This article delves into the opportunities within vertical AI and explores how companies can excel in this emerging space. Short-Term and Long-Term Strategies in Vertical AI In the short term, many vertical AI players focus on developing proprietary, fine-tuned models and user experiences to gain a competitive advantage. These niche models, trained on domain-specific data, often outperform larger foundational models in latency, accuracy, and cost. As models become more fine-tuned, changes in user experience (UX) must integrate these benefits into daily workflows, creating a flywheel effect. Vertical AI companies tend to operate as full-stack providers, integrating interfaces, proprietary models, and proprietary data. This level of integration enhances their defensibility because owning the user interface allows them to continually collect and refine data, improving the model. While this approach is effective in the short term, vertical AI players must consider the broader ecosystem to ensure long-term success. The Shift from Vertical to Horizontal Though vertical AI solutions may dominate in specific niches, long-term success requires moving beyond isolated verticals. Users ultimately prefer unified experiences that minimize switching between multiple platforms. To stay competitive in the long run, vertical AI players will need to evolve into horizontal solutions that integrate across broader ecosystems. Vertical Strategies and AI-Driven Rebundling Looking at the success of vertical SaaS over the last decade provides insight into the future of vertical AI. Companies like Square, Toast, and ServiceTitan have grown by first gaining adoption in a focused use case, then rapidly expanding by rebundling adjacent capabilities. This “rebundling” process—consolidating multiple unbundled capabilities into a comprehensive, customer-centric offering—helps vertical players establish themselves as the hub. The same principle applies to vertical AI, where the end game involves going vertical to later expand horizontally. AI’s Role in Rebundling The key to long-term competitive advantage in vertical AI lies not just in addressing a single pain point but in using AI agents to rebundle workflows. AI agents serve as a new hub for rebundling, enabling vertical AI players to integrate and coordinate diverse workflows across their solutions. Rebundling Workflows with AI Business workflows are often fragmented, spread across siloed software systems. Managers currently bundle these workflows together to meet business goals by coordinating across silos. But with advances in technology, B2B workflows are being transformed by increasing interoperability and the rise of AI agents. The Rebundling Power of AI Agents Unlike traditional software that automates specific tasks, AI agents focus on achieving broader goals. This enables them to take over the goal-seeking functions traditionally managed by humans, effectively unbundling goals from specific roles and establishing a new locus for rebundling. Vertical AI Players: Winners and Losers The effectiveness of vertical AI players will depend on the sophistication of their AI agents and the level of interoperability with third-party resources. Industries that offer high interoperability and sophisticated AI agents present the most significant opportunities for value creation. The End Game: From Vertical to Horizontal Ultimately, the goal for vertical AI players is to leverage their vertical advantage to develop a horizontal hub position. By using AI agents to rebundle workflows and integrate adjacent capabilities, vertical AI companies can transition from niche providers to central players in the broader ecosystem. This path—going vertical first to then expand horizontally—will define the winners in the AI-driven future of business transformation. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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AI Potential to Improve Prior Authorizations

AI Potential to Improve Prior Authorizations

AI’s Potential to Reduce Provider Burdens in the Prior Authorization Process Artificial intelligence (AI) has the potential to significantly ease the documentation and substantiation burdens providers face during the prior authorization process. Prior authorization, a critical step where health plans approve or deny coverage for services or prescriptions before they’re administered, is a key cost-control mechanism in the U.S. healthcare system. While it helps payers avoid unnecessary spending, the process poses significant challenges, especially for healthcare providers tasked with gathering and submitting documentation. AI Potential to Improve Prior Authorizations examined. Historically, prior authorization has been a major regulatory challenge for providers, surpassing other issues such as electronic health record (EHR) interoperability and compliance with the No Surprises Act. Despite its cumbersome nature, prior authorization isn’t likely to be eliminated, as it plays a crucial role in balancing healthcare affordability and access to quality care. AI Potential to Improve Prior Authorizations The transactional nature of many prior authorization tasks makes them ripe for automation. Increasingly, stakeholders are turning to AI and other technology-driven solutions to streamline the process, making it less burdensome for providers. How AI Can Streamline Prior Authorization AI has already been applied to various aspects of healthcare, from automating hospital discharges to alleviating the administrative burdens of nurses. When applied to prior authorization, AI can speed up the approval process for both providers and payers, reducing delays in patient care and lowering administrative costs. Health insurance companies are already beginning to leverage AI to expedite prior authorization and claims decisions. However, concerns are growing over whether the use of AI in these areas complies with state and federal regulations. For example, a 2023 AMA Annual Meeting resolution cited an investigation revealing that Cigna doctors denied over 300,000 claims in two months, spending an average of just 1.2 seconds per case using AI. UnitedHealthcare has also employed AI to make “fast, efficient, and streamlined coverage decisions,” raising questions about whether these decisions adhere to regulatory standards for fairness and accuracy. AMA’s Call for Oversight on AI in Prior Authorization Recognizing the risks, the American Medical Association (AMA) has called for increased regulatory oversight of AI in prior authorization. Specifically, the AMA advocates for: AI could potentially reduce the time-consuming, manual tasks associated with prior authorization. However, as AMA Trustee Dr. Marilyn Heine cautioned, “AI is not a silver bullet.” The increasing reliance on AI for prior authorization must not add to the already overwhelming volume of requirements that burden physicians and hinder patient care. Nor can it increase the threat of cyberattacks. Fixing Prior Authorization: AMA’s Role Addressing the challenges of prior authorization is a key part of the AMA’s Recovery Plan for America’s Physicians. The organization is committed to reducing the overuse of prior authorization and improving the fairness of existing processes, ensuring that the use of AI in healthcare supports—not hinders—patient care. To that end, the AMA continues to research the costs and impacts of prior authorization on healthcare providers and patients. To learn more about the proper use of AI in medicine and the AMA’s efforts to reform prior authorization, visit the AMA’s resources on healthcare AI. Content updated September 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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