Survey: Hospital brand loyalty drives care access decisions

Copyright TechTarget - All rights reserved https://cyber.law.harvard.edu/rss/rss.html Techtarget Feed Generator en Tue, 21 Jul 2026 10:02:31 GMT https://www.techtarget.com/whatis editor@techtarget.com New survey <a href="https://health.usnews.com/health-care/best-hospitals/articles/how-patients-choose-hospitals-key-priorities-from-the-2026-us-news-survey">data</a> from U.S. News & World Report shows that hospital brand loyalty is one of the biggest drivers of patients' care access decisions, cementing consumer engagement as a must-have in today's healthcare landscape. The survey, which included 500 people in the U.S. who've sought care for themselves or a loved one in the past 24 months, revealed that most folks are interested in receiving all or most of their care within a single hospital system. When choosing a new healthcare provider, most (53%) patients either choose a hospital first or select a hospital and a provider at the same time. According to the researchers, this indicates that patients want a <a href="https://www.techtarget.com/patientengagement/news/366584447/Benefits-of-Care-Coordination-Tick-Up-with-Patient-Activation">cohesive healthcare experience</a>, with their doctor being affiliated with their hospital or health system of choice. Still, hospital brand loyalty hasn't completely taken over. The survey showed that patients who've built a relationship with a healthcare provider remain most interested in maintaining it. Specifically, 80% of patients would switch hospital systems, not providers, if their <a href="https://www.techtarget.com/patientengagement/feature/What-does-usual-source-of-care-mean-in-healthcare">usual source of care</a> were to make a switch. But that remaining 20% of patients are notable. It shows that a sizeable group of patients is prioritizing where they'd receive hospital care, potentially marking a shift toward hospital brand loyalty. "When patients seek care for a new health issue, they aren't just choosing a single provider -- they are choosing a comprehensive care partner for their full spectrum of care," Sumita Singh, executive vice president and general manager of Health at U.S. News, said in a <a href="https://www.usnews.com/info/blogs/press-room/articles/2026-07-20/u-s-news-survey-growing-importance-of-hospital-and-health-system-brands-in-patient-healthcare-decisions">press release</a>. "This strong hospital brand loyalty shows that consumers highly value the safety, technology and coordinated care that a trusted healthcare system provides." <section class="section main-article-chapter" data-menu-title="How do patients pick healthcare providers?"> <h2 class="section-title">How do patients pick healthcare providers?</h2> Of course, patients' decisions to find a new provider are more complex than brand affiliation. According to U.S. News, patients' decisions come down to various factors, including: <ul class="default-list"> <li>Clinical expertise/success rates (22%)</li> <li>Years of experience (17%)</li> <li>Location (17%)</li> <li>Referral from another clinician (17%)</li> <li>Patient experience ratings (10%)</li> <li>Referral from friends/family (9%)</li> <li>Gender, language or cultural compatibility (8%)</li> </ul> There's also <a href="https://www.techtarget.com/patientengagement/news/366584760/Travel-Times-Still-a-Challenge-for-Rural-Health-Access-Disparities">hospital or office location</a> to account for, the survey continued. Notably, the extent to which patients consider location differs depending on the type of care they access. Overall, convenient location is essential for patients. But between routine visits and more specialized care, some patients are more flexible, the survey revealed. For example, nearly two-thirds of respondents (62%) said office location was very important when accessing routine care. When accessing more specialized care, a third of patients said they'd be willing to drive more than three hours. </section> <section class="section main-article-chapter" data-menu-title="Where do patients find information about clinicians?"> <h2 class="section-title">Where do patients find information about clinicians?</h2> Before patients can book an appointment, they need to actually <a href="https://www.techtarget.com/patientengagement/news/366591748/Most-patients-find-new-doc-online-via-provider-directories">find a doctor</a>. And despite evolving technology, this process isn't changing, the U.S. News data showed. The referral is still king, with patients rating a provider referral a 4 out of 5 on a trustworthiness scale. Patients are also fairly trusting of online directories or hospital websites, ranking them 3.5-3.7 out of 5, the survey showed. But perhaps the biggest finding was the trust patients place in newer communication channels, such as social media, podcasts and even AI chatbots. Although industry experts have flagged these as emerging patient engagement channels, patients don't entirely trust them, rating them at 2.7-2.8 out of 5 on the trustworthiness scale. That doesn't mean patients are starting to experiment with AI-powered provider search. Earlier this year, data from rater8 showed that nearly <a href="https://www.techtarget.com/patientengagement/news/366643954/Almost-half-of-patients-use-AI-for-online-provider-search">half of patients are using AI for online provider search</a>. To that end, healthcare organizations must stay abreast of emerging best practices, especially as they pertain to <a href="https://www.techtarget.com/patientengagement/feature/AI-provider-search-is-here-How-can-health-orgs-stay-visible">AI search visibility</a>. However, the U.S. News survey confirms that patients still value the relationships they've developed with their providers, whether it's trust in a provider's referral or willingness to follow a provider to a new health system. Still, it would be prudent for health systems to also catch onto the growing emphasis healthcare consumers place on hospital brand loyalty. Patients are seeking a seamless and connected care experience, from outpatient routine care to any relevant inpatient stays. This will require organizations to focus on a range of issues from patient loyalty to staff retention. Sara Heath is an executive editor at Xtelligent Healthcare Media, where she covers patient engagement, healthcare policy and health IT. </section> U.S. News survey data show that patient loyalty is increasingly being placed in the hospital brand, likely because patients want a comprehensive care experience. https://cdn.ttgtmedia.com/rms/onlineimages/ai_a352095729.jpg https://www.techtarget.com/patientengagement/news/366646077/Survey-Hospital-brand-loyalty-drives-care-access-decisions Tue, 21 Jul 2026 07:00:00 GMT Survey: Hospital brand loyalty drives care access decisions Health information blocking has been in the federal government's crosshairs since the ONC's rules prohibiting efforts to prevent the exchange of health data <a href="https://www.techtarget.com/searchhealthit/news/366579231/ONC-Interoperability-Rule-Information-Blocking-Regulations-Launch">took effect in April 2021</a>. Though information blocking has decreased in recent years, health information organizations contend that some actors, particularly certified health IT developers, are continuing to engage in it.   At the end of last month, ONC <a href="https://healthit.gov/data/data-briefs/trends-in-health-information-organizations-experiences-of-perceived-information-blocking-2019-2025/">released a data brief</a> detailing state, local, and regional health information organizations' perceptions on information blocking. The brief mines the results of the 2019, 2023 and 2025 National Survey of Health Information Organizations to assess practices that HIOs believe may constitute information blocking. The HIOs include health information exchanges and emerging health data utilities. Overall, the share of HIOs reporting information blocking has decreased from 2019 to 2025. In 2019, 91% of HIOs reported at least one instance of potential information blocking, compared with 71% in 2025. However, HIOs noted that developers of certified health IT were the main culprit behind potential information blocking. Nearly two-thirds (62%) of HIOs reported that certified health IT developers engaged in information blocking in 2025, compared with hospitals and health systems (49%), national networks (20%) and other HIOs (7%). According to HIOs, certified health IT developers set unreasonable fees and pricing to potentially block information exchange. While the share of HIOs saying that developers use this tactic has decreased overall, from 81% in 2019 to 59% in 2025, it remains the most commonly reported information-blocking practice. HIOs also cited artificial barriers (40%) and contract language (30%) as tactics developers used in 2025 to block data sharing.   As for hospitals and health systems, HIOs stated that they use strategic affiliations, such as ownership structures, to potentially hinder data exchange. In 2025, 42% of HIOs said hospitals and health systems used this practice to block information exchange, down slightly from 45% in 2023. Notably, HIOs reported that information-blocking practices were not widespread among developers. While 55% of HIOs reported potential information blocking by some or most developers in 2019, only 27% did so in 2025. On the other hand, the share of HIOs reporting that some or most hospitals/health systems engage in information-blocking practices remained steady -- 24% in 2019 and 28% in 2025.   "Data also show that even though most HIOs report experiencing possible information blocking, a majority of HIOs that experienced potential information blocking indicated that these practices and behaviors are not widespread among hospitals and health systems or developers of certified health IT," the report stated. "Many HIOs, therefore, experienced potential information blocking but increasingly by a smaller group of entities." Still, potential information blocking significantly impacts information exchange, according to HIOs. About one in five HIOs reported that information-blocking behaviors had a great impact on information exchange.  "Based on these analyses, deterring the small group of actors who may be engaging in potential information blocking practices including those related to business, market, or other organizational constructs to not share information could make a substantial impact on improving information exchange activity among HIOs and HDUs," the report concluded. Anuja Vaidya has covered the healthcare industry since 2012. She currently covers healthcare IT and innovation, including artificial intelligence, digital healthcare, EHRs and interoperability. Organizations, including HIEs and HDUs, report that information blocking has declined from 2019 to 2025; however, they note that certified health IT developers remain the main culprit. https://cdn.ttgtmedia.com/rms/onlineimages/ehr_g1366566196.jpg https://www.techtarget.com/searchhealthit/news/366646094/Health-information-orgs-blame-developers-for-blocking-data-sharing Mon, 20 Jul 2026 16:30:00 GMT Health information orgs blame developers for blocking data-sharing With vector indexing a crucial aspect of AI development, the latest release of Zilliz's open source Milvus vector database is designed to improve the vector search results that feed AI pipelines. Milvus 3.0, which was made generally available on July 16, features an architectural update that simplifies development by adding lake-native data access. Native access to data lakes such as <a href="https://www.techtarget.com/searchstorage/news/366616623/Amazon-S3-storage-adds-new-capabilities-for-data-lakes">Amazon S3</a>, <a href="https://www.techtarget.com/searchdatamanagement/news/252515666/Google-grows-cloud-capabilities-with-BigLake-data-lakehouse">Google BigLake</a> and Microsoft <a href="https://www.techtarget.com/searchstorage/tutorial/How-to-create-an-Azure-Data-Lake-Storage-Gen2-account">Azure Data Lake Storage</a> enables Milvus to read, write and query data where it's stored using open file formats including <a target="_blank" href="https://iceberg.apache.org/" rel="noopener">Apache Iceberg</a>. Previously, users had to extract and load data from data lakes into Milvus as part of their development pipelines, adding cost, complexity and data movement that could accidentally expose proprietary data. In addition, Milvus now features an updated data retrieval engine to better discover and operationalize contextually appropriate vectors for agents and other AI applications that require large amounts of <a href="https://www.techtarget.com/searchdatamanagement/opinion/Context-is-the-make-or-break-layer-for-AI-in-production">relevant data to deliver accurate results</a>. Given that using Milvus now eliminates certain data migration projects, the latest update is significant for not only existing users but also potential new ones, according to Mike Leone, an analyst at Moor Insights & Strategy. "[It's valuable] as long as your data already sits in one of the open table formats Milvus can read," he told TechTarget. "If it does, adopting Milvus isn't a migration project, and that opens it up to teams that could never justify the migration in the first place." Based in Redwood City, Calif., Zilliz is a vector database vendor that competes with fellow specialists such as Pinecone, Qdrant and Redis, as well as broader-based data management providers that offer vector database capabilities, including AWS, Google Cloud and Oracle. In addition to Milvus, <a href="https://www.techtarget.com/searchdatamanagement/news/252524175/Zilliz-raises-60M-for-open-source-Milvus-vector-database">Zilliz</a> offers Zilliz Cloud, a managed service that includes Milvus' vector database capabilities. <section class="section main-article-chapter" data-menu-title="Aiding AI development"> <h2 class="section-title">Aiding AI development</h2> As interest in building agents and other AI applications <a target="_blank" href="https://www.gartner.com/en/newsroom/press-releases/2026-1-15-gartner-says-worldwide-ai-spending-will-total-2-point-5-trillion-dollars-in-2026" rel="noopener">has surged</a>, so has the importance of vector search. Vectors are numerical representations of data that make information, including unstructured data such as text and audio, searchable so it can found and used to feed inform applications. <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> [It's valuable] as long as your data already sits in one of the open table formats Milvus can read. If it does, adopting Milvus isn't a migration project, and that opens it up to teams that could never justify the migration in the first place. </figure> <figcaption> Mike LeoneAnalyst, Moor Insights & Strategy </figcaption> </div> </blockquote> As vector databases have <a href="https://www.techtarget.com/searchdatamanagement/feature/Vector-search-now-a-critical-component-of-GenAI-development">gained widespread popularity</a> over the past few years, providers have updated and improved their capabilities to deliver more accurate search results so that the data fed into AI pipelines enables organizations to build trustworthy AI tools. For example, <a href="https://www.techtarget.com/searchdatamanagement/news/366642768/MongoDB-adds-new-vector-performance-capabilities-to-aid-AI">MongoDB</a> and <a href="https://www.techtarget.com/searchdatamanagement/news/366639802/Teradata-updates-vector-indexing-suite-to-aid-AI-development">Teradata</a> have each added new vector embedding and search capabilities this year. Now, Zilliz is following suit with its latest Milvus database update, adding capabilities tailored to meet the needs of users doing more complex work than when they were building analytics and traditional AI tools such as predictive models, according to James Luan, co-founder and CTO of Zilliz. "[The update] was very much driven by what we were hearing from production AI users, including large language model labs and self-driving companies," he told TechTarget. "As AI workloads matured, teams weren't just doing simple search anymore." One of the most pressing problems organizations faced was wasted time, effort and money spent copying and <a target="_blank" href="https://getdeploying.com/reference/data-egress" rel="noopener">moving data</a> from data lakes into Milvus, Luan continued. "It's the kind of invisible infrastructure tax that slows AI teams down considerably," he said. "Milvus 3.0 tackles this by bringing production-grade vector indexes directly to lake-resident data. … Teams can search, analyze, and process from one copy, which is simpler to manage and much less expensive to operate." New Milvus database capabilities aimed at bringing vector search closer to where data is stored and improving the relevancy of vector search include the following: <ul type="disc" class="default-list"> <li>Loon, a new storage engine that optimizes <a href="https://www.techtarget.com/searchstorage/definition/object-storage">object storage</a> reads to reduce latency and improve the accuracy of searches.</li> <li>StructList, a multi-vector retrieval tool that enables users to discover documents, images and other data represented by more than one vector.</li> <li>An index that strengthens sparse and hybrid vector retrieval searches while reducing the compute power required to run such searches.</li> <li>External Collections, a feature that defines collections in Milvus over data stored in Apache Iceberg, Apache Parquet, Lance or Vortex to build searchable indexes.</li> <li>Snapshots, a tool that enables users to create point-in-time, read-only views of collections so they can perform offline jobs such as evaluations and validations while production work continues in online environments.</li> <li>A Spark connector that exposes Milvus as a data source for <a href="https://www.techtarget.com/searchaws/definition/Amazon-Elastic-MapReduce-Amazon-EMR">Amazon EMR</a>, Databricks and <a href="https://www.techtarget.com/searchdatamanagement/definition/Apache-Spark">Apache Spark</a> pipelines as part of standard batch data workflows.</li> </ul> Kevin Petrie, an analyst at BARC U.S., noted that Zilliz's blending of database and data lake capabilities in Milvus 3.0, which helps users more easily combine previously disparate analytical and transactional data workloads, plays to a growing trend. Numerous vendors, including <a href="https://www.techtarget.com/searchdatamanagement/news/366638723/Databricks-launches-PostgreSQL-Lakebase-to-aid-AI-developers">Databricks</a> and <a href="https://www.techtarget.com/searchdatamanagement/news/366625068/Snowflake-acquisition-of-Crunchy-Data-adds-Postgres-database">Snowflake</a>, are now providing database capabilities that enable customers to unify data to build a foundation for AI. "Zilliz's support of lakebase environments plays well to the convergence trend, which leading platforms such as Databricks are pushing aggressively," Petrie told TechTarget. "Zilliz enables enterprises to deploy rich vector capabilities to support those converged workloads in lakebase environments." In addition, the Milvus update is significant for users given that it reduces the need to <a href="https://www.techtarget.com/searchstorage/definition/data-migration">migrate data</a> and improves the database's search and indexing capabilities, he continued. "Zilliz addresses several market requirements with this release," Petrie said. "First, data remains highly distributed, [so] Zilliz is wise to help customers index vectors in place without moving them. … Second, enterprises need multimodal AI that goes beyond basic vectorization to handle capabilities such as the full-text search and indexing that Zilliz provides." </section> <section class="section main-article-chapter" data-menu-title="Competitive standing"> <h2 class="section-title">Competitive standing</h2> Although Zilliz is addressing user needs with its latest Milvus database update, the vendor faces a significant challenge as it competes for market share, according to Petrie. With hyperscale cloud and data platform providers adding vector search and storage capabilities over the past few years, many enterprises that already use those providers for data management no longer need to seek out <a href="https://www.techtarget.com/searchdatamanagement/tip/Top-vector-database-options-for-similarity-searches">a specialist</a> for their vector database needs. Specialists sometimes still provide more robust vector embedding and search capabilities than broader-based vendors, which appeals to certain potential customers. But for many, simplification is a selling point. "Zilliz faces a similar challenge as all vector database companies, [which] is that vectors are just one piece of the multimodal puzzle," Petrie said. "Larger vendors such as Google manage and retrieve vector, graph and tabular data from the same multimodal database, which simplifies enterprise AI architectures compared with point vector solutions." Leone noted that Snapshots is perhaps the most valuable of the new features because it allows users to evaluate their <a href="https://www.techtarget.com/searchenterpriseai/tip/Tools-and-techniques-for-optimizing-AI-data-pipelines">retrieval systems</a> even if their data is continually changing. From a competitive standpoint, he added that, while certain new Milvus capabilities are found in other vector databases as well, indexing data formats that aren't converted to vectors -- Apache Iceberg, Apache Parquet, Lance and Vortex -- is a potential differentiator for Zilliz. "The area to pay attention to is indexing formats you never had to convert first," Leone said. "That's harder than it sounds, because serving live queries straight off object storage is slow. It's why Zilliz built Loon, the new storage engine underneath Milvus." </section> <section class="section main-article-chapter" data-menu-title="Looking ahead"> <h2 class="section-title">Looking ahead</h2> With the latest version of Milvus now GA, over the second half of 2026 Zilliz plans to add deeper integrations between the database and data lakes that better enable users to <a href="https://www.techtarget.com/searchenterpriseai/tip/How-to-audit-AI-systems-for-transparency-and-compliance">audit and debug</a> AI behavior, according to Luan. In addition, smarter storage and elasticity at scale to optimize usage are part of the product development roadmap for Milvus, he continued. Beyond Milvus, Zilliz plans to bring all the new capabilities planned for its open source database to its Zilliz Cloud offering. "Bringing the full Milvus 3.0 feature set into this managed platform is a key part of our [second half] roadmap," Luan said. Leone, meanwhile, suggested that Zilliz add <a href="https://www.techtarget.com/searchsecurity/tip/Evaluate-cloud-database-security-controls-best-practices">security capabilities</a> beyond access controls to reduce reliance on system administrators. "If Milvus is reading straight from a customer's tables, someone in security is going to ask who can see what," he said. "Milvus already has its own access controls, so next I'd want the permissions on those tables to carry through automatically. Otherwise, an admin is keeping two separate systems in sync by hand." Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than three decades of experience. He covers analytics and data management. </section> Native access to data lakes and a new data retrieval engine highlight the latest release as the vendor competes for market share amid a crowded field. https://cdn.ttgtmedia.com/rms/onlineimages/machine%20learning_g1186820873.jpg https://www.techtarget.com/searchdatamanagement/news/366646015/Zilliz-ups-vector-search-results-with-Milvus-database-update Mon, 20 Jul 2026 14:57:00 GMT Zilliz ups vector search results with Milvus database update As AI adoption continues to grow throughout the healthcare sector, primary care specialties will need to plan for patients who are both excited and fearful of how the technology affects their care. A new <a href="https://www.commonwealthfund.org/publications/issue-briefs/2026/jul/patients-perspectives-ai-primary-care">report</a> from the Commonwealth Fund, completed in partnership with the Public Policy Lab, aims to provide some guidance for primary care offices. The report is based on qualitative interviews with patients in New York City and rural West Virginia. It finds that patients have complicated feelings about AI. "These tools may aim to ensure primary care is coordinated, continuous, comprehensive, accessible, and patient-centered," the report authors said. "However, design and implementation of health technology tend to be top-down, without consideration for patients' perspectives. While the goal may be to improve the care experience, without their input, patients may be distrustful or hesitant to use these tools, and the tools may create inequities." Notably, patients see the potential for AI to improve their care, recognizing that it could deepen their understanding of their own health and care plans. But they also have their concerns, like how AI implementation might ignore the patient voice and create more friction for patients already <a href="https://www.techtarget.com/patientengagement/news/366584422/Patients-Overburdened-with-Care-Coordination-Hurts-Patient-Experience">bogged down by the complexities of coordinating their own care</a>. Primary care providers will need to create detailed AI implementation strategies to ensure the technology truly delivers on its promises. <section class="section main-article-chapter" data-menu-title="Patients see the potential -- and inevitability -- of AI"> <h2 class="section-title">Patients see the potential -- and inevitability -- of AI</h2> Patients' AI optimism might be largely driven by their understanding that AI is an inevitability, regardless of industry. But that didn't mean they didn't see the value AI could add to their primary care, the report's authors remarked. For instance, many patients expressed interest in sharing their medical data to help develop more sophisticated AI models, as long as their <a href="https://www.techtarget.com/healthtechanalytics/feature/Understanding-De-Identified-Data-How-to-Use-It-in-Healthcare">data is deidentified</a>. Respondents recognized that their data could help boost not just their own care but the care of others, saying their contributions could be a boon for the greater good. Additionally, patients lauded AI's potential to deepen their understanding of their own care. AI has proven effective in providing plain-language summaries of lab results or clinical notes. Patients also said AI has been useful when they <a href="https://www.techtarget.com/patientengagement/news/366644898/KFF-Healthcare-cost-pressures-lead-patients-to-use-AI-for-health-info">can't obtain or afford a medical appointment</a>, or when they want a second opinion. AI has been especially useful for people who've previously had negative experiences with a doctor, such as being judged or rushed during appointments. In those cases, AI gives patients another place to go for medical advice. </section> <section class="section main-article-chapter" data-menu-title="Patients worry about AI's potential consequences"> <h2 class="section-title">Patients worry about AI's potential consequences</h2> Patients acknowledged the possibility that <a href="https://www.techtarget.com/searchenterpriseai/tip/How-businesses-can-get-ahead-of-potential-AI-deskilling">AI could cause cognitive deskilling</a> in their healthcare providers, but that's not all. They are also jaded from previous technological innovations, fearing that AI could create more friction where it is intended to reduce it. This could be especially apparent when AI is inaccurate or hallucinates. Finally, patients are worried that AI use in primary care could deepen existing health disparities. This would be true of folks with unreliable internet, older devices or lower <a href="https://www.techtarget.com/patientengagement/feature/Digital-Health-Literacy-Why-Its-Important-and-How-to-Improve-It">digital health literacy</a>. Despite fears, there are certain safeguards that could compel patients to use and accept AI in their primary care. First, and perhaps most importantly, patients will need assurances that AI will not replace their doctor. They also want <a href="https://www.techtarget.com/patientengagement/news/366628054/How-to-request-patient-consent-for-using-ambient-listening">disclosure and consent processes for AI use</a>. Patients want this information at multiple touchpoints so they can assess the AI disclosure and ask questions. Patients also said they want to see AI enable accountability and accuracy in their care. For example, AI can help them translate complex medical jargon and create their own patient-centered "paper trail," the report authors said. This could help patients work with their primary care providers to verify information, dispute inaccuracies, prepare questions ahead of appointments and otherwise advocate for their health needs. To deliver on patient needs, primary care offices will need to develop detailed AI implementation plans. </section> <section class="section main-article-chapter" data-menu-title="How primary care can deploy patient-centered AI"> <h2 class="section-title">How primary care can deploy patient-centered AI</h2> The report authors grouped their recommendations for patient-centered AI development into three key buckets: transparency and consent, accountability and equitable patient benefit. <h3>Transparency and consent</h3> Clinics should explain AI use and consent via the <a href="https://www.techtarget.com/patientengagement/news/366645152/153-surge-in-patient-portal-messaging-imperils-provider-workloads">patient portal</a> before visits and with paper handouts upon visit. Clinics might consider when disclosure versus consent is necessary and determine key areas for opt-out, such as <a href="https://www.techtarget.com/patientengagement/news/366636579/What-patients-want-to-know-about-AI-ambient-scribing">ambient scribing</a>, patient message or clinical decision support. To that end, organizations must maintain patient engagement strategies that do not involve AI. <h3>Accountability</h3> Patients want to know that their PCP has the final say in their care. This requires health systems to train their providers in responsible AI use, including using it as a supplement to their professional expertise. Additionally, primary care organizations need to stress to patients that healthcare professionals have primary oversight over their care. <h3>Equitable patient benefit</h3> Notably, patients feared that AI would not center patient needs and could deepen the digital divide. Healthcare organizations should start addressing this by designing AI use cases that focus on patients, such as better comprehension of medical information. This will require organizations to also measure KPIs that center the patient, including patient satisfaction with technology. Primary care clinics should also do a health equity audit on potential tools, looking for compatibility with older devices, low bandwidth and different digital health literacy levels. Patient respondents were right -- AI is appearing to be an inevitability in healthcare. But that doesn't mean primary care providers don't need to be strategic about how they deploy the technology. "For health system leaders, successful adoption of AI tools in primary care will depend on their design and whether implementation is done with patients," the report authors concluded. "Primary care clinicians can help ensure that these tools are introduced clearly, used responsibly, and assessed in light of patients' needs and concerns." Sara Heath is an executive editor at Xtelligent Healthcare Media, where she covers patient engagement, healthcare policy and health IT. </section> Patients are aware of the risks of AI use, so primary care offices need to implement a patient-centered AI policy enabling disclosure and consent. https://cdn.ttgtmedia.com/rms/onlineimages/arvr_a199792447.jpg https://www.techtarget.com/patientengagement/news/366645868/How-primary-care-can-implement-patient-centered-AI-policy Mon, 20 Jul 2026 10:20:00 GMT How primary care can implement patient-centered AI policy NetApp's purchase of an AI data infrastructure company this week paves the way for it to move data processing closer to storage repositories, expanding the choices available to enterprises facing AI cost and data management challenges. The acquisition of California-based DataPelago for an undisclosed amount this week will push NetApp further into AI data management. NetApp began its move away from AI-ready data storage into the data management layer with the launch last year of its <a href="https://www.techtarget.com/searchstorage/news/366632757/NetApp-adds-AI-Data-Engine-expands-Nvidia-partnership">AI Data Engine</a>, a set of software tools that collect, curate, sync, protect and prepare data for use by AI applications. It also shipped a new AFX all-flash array that represented a first foray into disaggregated storage, which decouples storage controllers from storage capacity. DataPelago will help NetApp build on that foundation and move deeper into an area also sought after by competitors including <a href="https://www.techtarget.com/searchstorage/opinion/Turning-Data-into-Intelligence-for-the-AI-Native-Era">Dell</a>, <a href="https://www.techtarget.com/searchstorage/news/366641595/Nutanix-expands-flexibility-by-building-out-external-storage">Nutanix</a>, <a href="https://www.techtarget.com/searchstorage/news/366644759/Everpure-grows-into-data-management-with-Data-Intelligence-update">Everpure</a> and <a href="https://www.techtarget.com/searchstorage/news/366639519/Vast-Data-services-speed-up-AI-workloads-add-intelligence">Vast</a>, according to Rob Strechay, founder and principal at Smuget Consulting. <div class="imagecaption alignLeft"> <img src="http://cdn.ttgtmedia.com/rms/onlineImages/strechay_rob.jpg" alt="Rob Strechay, founder and principal, Smuget Consulting">Rob Strechay </div> "I believe this could evolve into the connective layer between NetApp's file and object storage platforms, multimodal enterprise data, and modern compute engines such as Apache Spark and other open analytics frameworks," Strechay said. "By bringing GPU- and CPU-accelerated processing, which is the direction <a href="https://www.techtarget.com/searchstorage/news/366637161/Nvidias-new-KV-cache-makes-waves-in-enterprise-storage">Nvidia is pushing</a> with its stack, directly to the storage layer, organizations should be able to execute analytics and AI data preparation without constantly copying data into separate compute clusters." That appears to be NetApp's intended direction with DataPelago and its Nucleus data processing engine, according to a company <a href="https://www.netapp.com/newsroom/press-releases/news-rel-20260716-210092/">press release</a>. Processing data at the storage layer rather than moving it to external compute clusters reduces infrastructure costs by up to 80 percent and delivers performance up to 10 times faster, the release said. <section class="section main-article-chapter" data-menu-title="AI data management heats up amid enterprise challenges"> <h2 class="section-title">AI data management heats up amid enterprise challenges</h2> Data management has emerged as a key challenge for enterprise AI, alongside security and governance, amid an industry shift toward agentic AI over the past year. Enterprise <a href="https://www.techtarget.com/searcherp/feature/AI-demos-are-not-enterprise-deployment-plans">AI agent deployments</a> at scale remain elusive, and data management is a key culprit, according to market research. A majority of 449 IT leaders <a href="https://research.esg-global.com/aim/en/reports/515202185/files/Complete-Survey-Resu">surveyed by Omdia</a> in September 2025 -- 68% -- identified data management as the most challenging aspect of a production AI implementation, according to Simon Robinson, an analyst at Omdia, a division of Informa TechTarget. As data storage vendors rush to seize that opportunity for expansion into a new market, "the Venn diagram of 'storage management' and 'data management' is increasingly overlapping," Robinson said. "All the other storage vendors are making similar moves." NetApp's longevity in storage management could be a strength as it makes the jump between specialties, he said. "They understand, store and manage a huge amount of unstructured data at scale," Robinson said. "Customers are looking to unite data across their distributed environment, and NetApp has a good story here. DataPelago potentially strengthens that." While competitors such as Vast and Dell share that vision, "DataPelago's architecture and potential integration across NetApp's broader ecosystem could provide a more open, broadly integrated execution model, provided NetApp can deliver on that vision," Strechay said. At least initially, DataPelago will operate as a wholly owned subsidiary of NetApp, according to the company's press release. DataPelago "is very much focused on the data processing layer -- they are not a storage engine, so they appeal to a different persona that NetApp has been looking to target, so it makes sense to keep it separate, at least for now," according to Robinson. "But we'll be looking for how NetApp plans to bring the technologies together." <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/lnPDoERKqPs?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> Beth Pariseau, senior news writer for Informa TechTarget, is an award-winning veteran of IT journalism. Have a tip? <a target="_blank" href="mailto:bpariseau@techtarget.com?subject=News%20tip" rel="noopener">Email her</a> or connect on <a target="_blank" href="https://www.linkedin.com/in/bethpariseau" rel="noopener">LinkedIn</a> </section> The acquisition strengthens NetApp's support for distributed data management, a key challenge for enterprises seeking to adopt AI. https://cdn.ttgtmedia.com/rms/onlineimages/storage_g922017556.jpg https://www.techtarget.com/searchstorage/news/366645908/NetAppDataPelago-deal-ups-AI-data-management-ante Fri, 17 Jul 2026 14:33:00 GMT NetApp-DataPelago deal ups AI data management ante A national coalition of civil rights groups is <a href="https://unidosus.org/publications/seamless-accountable-and-fair-civil-rights-agenda-reconstructing-insurance-affordability-programs/">warning</a> lawmakers that premium tax credit cuts to Affordable Care Act coverage, plus changes in Medicaid eligibility, will exacerbate racial health disparities in health plan enrollment. NAACP, Asian & Pacific Islander American Health Forum, the National Council of Negro Women, the National Urban League, the Southern Poverty Law Center (SPLC), UnidosUS, the Coalition on Human Needs, Community Catalyst and Families USA joined forces in publishing the report. According to the coalition, recent changes to the ACA Marketplaces and Medicaid eligibility will have dire consequences not just for health plan enrollment, but for health equity. Last July, Congress passed the One Big Beautiful Big Act, which set in place <a href="https://www.techtarget.com/healthcarepayers/news/366639720/OBBBAs-impact-on-state-Medicaid-funds-varies-nationwide">new eligibility requirements for the Medicaid program</a>. These provisions, which include new eligibility checks and the introduction of <a href="https://www.techtarget.com/healthcarepayers/news/366643893/CMS-framework-aims-to-clarify-Medicaid-work-requirements">federal work requirements</a>, are expected to reduce Medicaid enrollment. Meanwhile, the ACA Marketplaces are undergoing significant change, particularly after Congress allowed <a href="https://www.healthcaredive.com/news/enhanced-aca-subsidies-expire-congress/808418/">enhanced premium tax credits to sunset</a>. Those tax credits previously helped offset the rising cost of Marketplace premiums. Already, the industry has seen <a href="https://www.healthcaredive.com/news/aca-enrollment-2026-premium-effecuation-wakely/817680/">lower health plan enrollment</a>. Citing figures from the Congressional Budget Office, the coalition stressed that nearly <a href="https://www.cbpp.org/research/health/by-the-numbers-house-bill-takes-health-coverage-away-from-millions-of-people-and">16 million people will become uninsured by 2034</a> due to those ACA and Medicaid changes. The coalition found that racial and ethnic minorities will bear the brunt of those coverage losses, with 60% of the individuals who stand to lose Medicaid or ACA coverage coming from communities of color. This includes 4.3 million Latinos, 2.4 million African Americans, nearly 1 million Asian American, Native Hawaiian and Pacific Islanders (AANHPI) and around 100,000 Native Americans who will lose Medicaid or ACA Marketplace coverage, the coalition's report showed. More specifically, the share of uninsured is set to rise by 62% for Black people and 80% of AANHPI people. "These coverage losses will deepen current problems, putting great strain on hospitals, clinics and other healthcare providers that, in many cases, already struggle to meet community needs," the report authors said. Notably, these disproportionate coverage losses will reverse health equity gains made in recent years. Although there have long been racial health disparities in Medicaid and ACA Marketplace enrollment, the severity of those disparities declined between 2010 and 2024. For example, in 2010, the number of Latino uninsured people was nearly 20% higher than the national average. By 2024, that number shrank to a 12% difference. A similar trend was observed among Black, AANHPI, Native American and multiracial people. The coalition called not just for a reversal of coverage changes, but also a better overall infrastructure for health equity. This includes streamlining eligibility checks based on Supplemental Nutrition Assistance Program or tax return data, creating single eligibility for all health programs and funding independent customer service programs for health services. Additionally, the groups called for better accountability for health programs that might violate civil rights and extension of affordable healthcare regardless of race or zip code. "We have already seen millions lose coverage because of paperwork and bureaucratic obstacles rather than ineligibility," Derrick Johnson, president and CEO of the NAACP, said in a <a href="https://www.splcenter.org/presscenter/new-report-finds-funding-cuts-and-red-tape-could-drive-historic-health-coverage-losses/">statement</a>. "As lawmakers consider the future of our healthcare system, they must reject policies that widen racial disparities and instead build programs that are seamless, accountable and fair for the communities that have too often been left behind." Notably, the HHS and CMS do not bill ACA and Medicaid changes as ploys to undercut health equity. Rather, they have stressed that <a href="https://www.techtarget.com/healthcarepayers/news/366645280/HHS-cut-3M-ACA-Marketplace-enrollments-in-ongoing-fraud-efforts">these changes will root out healthcare fraud</a>. Be that as it may, structural inequities will inevitably influence how public policy plays out. In this case, the coalition argues that ACA and Medicaid changes are built on a system that disproportionately affects communities of color, further exacerbating inequities that were already present. Sara Heath is an executive editor at Xtelligent Healthcare Media, where she covers patient engagement, healthcare policy and health IT. Of the nearly 15 million people slated to lose ACA or Medicaid coverage, 60% will come from minority groups, which could worsen racial health disparities. https://cdn.ttgtmedia.com/rms/onlineimages/health%20analytics_g1347267548.jpg https://www.techtarget.com/healthcarepayers/news/366645863/Civil-rights-groups-ACA-Medicaid-cuts-exacerbate-health-disparities Thu, 16 Jul 2026 14:52:00 GMT Civil rights groups: ACA, Medicaid cuts exacerbate health disparities As AI becomes increasingly embedded in the nation's healthcare infrastructure, local and state public health agencies risk being left behind. The Coalition for Health AI, a collaborative that aims to advance AI in healthcare responsibly, is <a href="https://www.techtarget.com/healthtechanalytics/news/366590206/Coalition-Shares-Progress-Plans-to-Issue-Responsible-Health-AI-Guidelines">launching a national initiative</a> to help state, tribal, local and territorial public health agencies implement AI. Called PULSE, or Public health Use case and Learning Scaling Engine, the initiative will bring 2,000 public health practitioners together to develop playbooks across five use cases. CHAI's 17-member leadership council will select the participants and assign them to their preferred use-case committee. They will then work with Accenture's AI and public health experts to conduct AI pilots. Based on their learning, they will develop playbooks that provide best practices for adopting AI, particularly generative AI. OpenAI and Anthropic have donated 10 enterprise licenses to the initiative. "PULSE is designed to help public health agencies build trust, practical experience, and a path to responsible implementation of this powerful technology," said Brian Anderson, MD, CEO of CHAI, in the press release. "We're proud to provide a vehicle for these organizations to share what they learn using leading AI tools in real-world settings, facilitating adoption and helping accelerate responsible innovation that strengthens public health nationwide." CHAI's program comes as public health agencies fall behind in AI adoption, despite industry efforts. At the federal level, HHS <a href="https://www.hhs.gov/sites/default/files/hhs-artificial-intelligence-strategy.pdf">launched an effort in 2025 to integrate AI</a> into internal operations, research and public health. However, adoption appears to be lagging at the state and local levels. According to the <a href="https://www.naccho.org/uploads/downloadable-resources/2024-Public-Health-Informatics-Profile-Report.pdf?fbclid=IwY2xjawEskmVleHRuA2FlbQIxMAABHSIVs7MRo_2EVD59Q-fDlK725BTzppilptijAjXUK6TONqasH5Yy6v2fsw_aem_wGRBE8yGOYmJAFJMZZRbuA">National Association of County and City Health Officials</a>, only 5% of local health departments reported using AI in 2024, and a majority (84%) did not have plans to use AI in the following year. Still, of the local health departments not using AI, nearly 40% were somewhat or very interested in supplementing their efforts with AI in the future. For the initiative, CHAI will select participants from varied jurisdictions, including state and territorial health departments, local and county health departments, tribal authorities and Indian health organizations or large city health departments. The use cases for AI pilots will include: <ul class="default-list"> <li>Biosurveillance: Drug wave prediction</li> <li>Social determinants of health: SDOH mapping</li> <li>Operations and efficiency: Community feedback analysis</li> <li>Public communications: Multilingual translation hub</li> <li>Automated clinical data retrieval: FHIR query engine</li> </ul> "Every major technological transformation succeeds or fails based on trust, governance and execution. Public institutions have the added responsibility of doing so while maintaining transparency and accountability," said David Lakey, M.D., former commissioner of the Texas Department of State Health Services, in the press release. "PULSE will support agencies in this endeavor, and is specifically designed for practical implementation -- working hand in hand with the professionals that are actively using the generative AI tools." The AI pilots will begin in the fall, and the public launch of the playbooks is expected next year. Anuja Vaidya has covered the healthcare industry since 2012. She currently covers healthcare IT and innovation, including artificial intelligence, digital healthcare, EHRs and interoperability. As public health agencies fall behind in AI adoption, CHAI has launched the PULSE program to bring public health practitioners together in AI workgroups and develop playbooks. https://cdn.ttgtmedia.com/rms/onlineimages/health%20analytics_g690610092.jpg https://www.techtarget.com/healthtechanalytics/news/366645940/CHAI-launches-AI-adoption-support-for-public-health-agencies Thu, 16 Jul 2026 14:10:00 GMT CHAI launches AI adoption support for public health agencies Patients are warming to the notion of AI-drafted patient portal messages, with most saying in a small <a href="https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2851278">study</a> in JAMA Network Open that AI could actually help them find answers to their questions sooner and save providers' time. These findings come as industry experts work to fully understand the implications of embedding AI into patient portal messaging functions. This small study, which included qualitative interviews with 40 patients at an academic medical center, showed that AI could feasibly draft patient portal messages without damaging the <a href="https://www.techtarget.com/patientengagement/news/366585095/Good-Patient-Provider-Relationship-Proves-to-Boost-Outcomes">patient-provider relationship</a>. Notably, the interviews demonstrated that patients consider portal messaging as transactional. Patients send secure direct messages to get an answer to a medical question, <a href="https://www.techtarget.com/patientengagement/news/366585096/What-Patient-Demographics-Use-Patient-Portal-Appointment-Scheduling">book an appointment</a> or get a prescription refill -- not to deepen their relationship with their provider. "Many patients recognized clinicians as 'busy' and interpreted AI-generated drafts as a means to help clinicians respond more quickly while managing competing priorities," the researchers wrote in the report. "In this framing, AI-supported messaging was viewed as mutually beneficial because it could reduce clinicians' burden while increasing the timeliness of patient responses." But there are some key caveats. For one thing, patients nearly universally insisted that AI-drafted <a href="https://www.techtarget.com/patientengagement/news/366584256/Gen-AI-patient-portal-messages-OK-but-need-human-review">patient portal messages be reviewed by a clinician</a> before being sent. This reflects already accepted industry best practice. Moreover, most patients want to be informed when AI has drafted a message from their provider. However, patients did not display a clear preference for how such disclosures are worded or when. There's also the matter of tone, the qualitative data showed. When patients use the patient portal to perform a routine task, like refilling a prescription, they don't mind something that feels more clerical, as though written by AI. "However, for messages involving uncertainty, anxiety, or potentially concerning test results, many participants expected clinicians to communicate with greater care and reassurance," the researchers explained. "For some participants, this meant that they would prefer clinicians to draft higher stakes messages or would prefer to use in-person communication methods." <section class="section main-article-chapter" data-menu-title="Strategies for deploying AI-drafted patient portal messaging"> <h2 class="section-title">Strategies for deploying AI-drafted patient portal messaging</h2> Using these insights, the researchers developed a list of tips for implementing AI-drafted patient portal messaging. Foremost, hospitals and health systems need to define key performance indicators and goals for AI-drafted messages, they suggested. They should also regularly evaluate these metrics and determine whether the technology is helping them hit their targets. Next, organizations need to invest in mechanisms to ensure clinician review before hitting send. This must include a policy requiring human review, as well as EHR workflows that prevent clinicians from hitting send on messages that haven't yet been reviewed. Notably, organizations also need to establish a responsibility pathway for content included in AI-drafted patient portal messages. In terms of how AI is deployed in patient portal messaging, the researchers recommended that organizations create contextual guidelines. This means offering advice on which clinical contexts AI should be used in and allowing for flexibility based on patient preference. Importantly, patient and family advisory councils should be involved in this process. Finally, the researchers advised organizations to establish AI disclosure guidelines, including the messaging and where or when the disclosure occurs. Hospitals and health systems should periodically assess the disclosure guidelines for improvement, they said. </section> <section class="section main-article-chapter" data-menu-title="Do AI-drafted portal messages truly save clinicians time?"> <h2 class="section-title">Do AI-drafted portal messages truly save clinicians time?</h2> This advice hinges on the notion that using AI to draft patient portal messages actually saves clinician time. As observed during participant interviews, patients want speedy and informative answers to their messages, and they think AI could help make that happen. This is important, as providers sift through more patient portal messages than ever. Earlier this year, a JAMA report showed a <a href="https://www.techtarget.com/patientengagement/news/366645152/153-surge-in-patient-portal-messaging-imperils-provider-workloads">153% surge in patient portal messages</a> since 2020, adding to providers' already mounting workloads. Some data has shown that AI can help support providers sort through their EHR inboxes. According to a 2025 report from NYU researchers, AI can reduce patient portal message response times by 7%. However, that 7% only equates to about 20 seconds, the data showed. That limited time savings is coupled with the fact that some experts think <a href="https://www.techtarget.com/searchhealthit/news/366645706/AI-patient-portal-message-may-increase-clinicians-cognitive-burden">AI in patient portal messaging can actually add to providers' cognitive burdens</a>. A recent report from Dartmouth found that AI rarely drafts responses the way a provider would, warranting extensive edits and potentially adding to workloads. Of course, AI in healthcare is only in its infancy. As the industry continues to experiment with the technology, it will be critical to measure its genuine impact on the end-user experience. Sara Heath is an executive editor at Xtelligent Healthcare Media, where she covers patient engagement, healthcare policy and health IT. </section> Patients are receptive to AI-drafted patient portal messages, so long as a clinician reviews them and they're informed that AI was involved. https://cdn.ttgtmedia.com/rms/onlineimages/chatbot_g1250576673.jpg https://www.techtarget.com/patientengagement/news/366645920/What-patients-want-in-AI-drafted-patient-portal-messages Thu, 16 Jul 2026 09:00:00 GMT What patients want in AI-drafted patient portal messages Atlassian Jira is the latest software delivery vendor to jump on the spec-driven development bandwagon to address AI coding bottlenecks during deployment. Spec-driven development, which emerged from <a href="https://www.techtarget.com/searchsoftwarequality/news/366627952/Paylocity-plans-API-design-first-shift-to-modernize-apps">API development practices</a>, emphasizes defining a software system's structure and behavior before code is written. It's been embraced by AI coding tools such as <a href="https://www.techtarget.com/searchsoftwarequality/news/366627715/AWS-Kiro-coding-agents-highlight-spec-driven-development">AWS Kiro</a>, GitHub and Cursor over the past year as a way to improve organizational control and team collaboration compared to prompt-based AI coding. Atlassian's new Jira Planner, released in preview this week, brings that concept to a different part of the software development lifecycle (SDLC) -- the requirements planning stage, where Jira has traditionally been a strong choice among enterprise DevOps teams. Jira Planner can contribute enterprise context based on Atlassian's Teamwork Graph to development specifications, reducing the likelihood of conflicts further down the pipeline during testing and deployment. This is part of Atlassian's answer for alleviating a common <a href="https://www.techtarget.com/searchitoperations/news/366631493/Harness-takes-aim-at-AI-bottleneck-with-DevSecOps-agents">DevSecOps bottleneck</a> for enterprises, as large volumes of AI-generated code strain software testing and deployment systems on the way to production. <div class="imagecaption alignLeft"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/wu_ming.jpeg" alt="Ming Wu, head of engineering, Dev AI, Atlassian">Ming Wu </div> "It's pretty common knowledge that the coding stage itself accounts for only about 15% to 16% of the time developers spend across the SDLC, so more than 84% of that is a bottleneck that reduces productivity," said Ming Wu, head of engineering for DevAI at Atlassian. "So that's why, even though the adoption rate for coding agents now, on average, in the industry is above 90%, the productivity gain has actually plateaued at 10% to 15%, and the planning stage is one of the pain points we identified." Jira Planner pulls from a company's existing codebase, Jira and Confluence history and team context to generate a structured technical spec in Confluence that is readable by both humans and machines, according to a company <a target="_blank" href="https://www.atlassian.com/blog/company-news/ai-sdlc" rel="noopener">blog post</a>. Atlassian also made its new Jira Coding Agent, previously known as <a target="_blank" href="https://www.atlassian.com/blog/company-news/rovo-dev-in-jira" rel="noopener">Rovo Dev in Jira</a>, generally available within the main Jira interface. It's joined this week by support for third-party coding agent alternatives in the same drop-down menu in the Jira UI, including Claude, Code, Cursor and GitHub Copilot, with Codex coming soon. Spec-driven development at the planning stage and the team level could theoretically address both AI coding quality issues and costs down the line, said Jim Mercer, an analyst at IDC. "It helps to make smarter decisions upfront, earlier in the process, because agents will have access to this broader base of knowledge around how [a team is] doing things," Mercer said. "That helps with quality, keeps them from rolling back and should help make spec-driven development quicker, because [requirements] should be better understood." <section class="section main-article-chapter" data-menu-title="An ever-shifting AI coding cost equation"> <h2 class="section-title">An ever-shifting AI coding cost equation</h2> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Spec-driven development decreases token counts for coding, but tends to distribute them elsewhere. </figure> <figcaption> Rick GenevaAnalyst, Forrester Research </figcaption> </div> </blockquote> While spec-driven development can yield cost savings, it can sometimes also shift cost burdens to other parts of the enterprise application stack, said Rick Geneva, an analyst at Forrester Research, who recently implemented a spec-driven development project at his previous employer, S&P Global, where he was director of software engineering. "Spec-driven development decreases token counts for coding, but tends to distribute them elsewhere, such as Copilot for business users, project planning, test and outcomes planning, etc." Geneva wrote in an email to TechTarget. "More planning files are created than code. Today, this is also using tokens, but on different tools and models, so it doesn't necessarily show up in the engineering budget." As enterprises seek a more coherent strategic approach to AI, it remains difficult to find an "end-to-end" tool that brings together the entire SDLC for AI coding, Geneva wrote. "There are no tools that link the entire end-to-end development lifecycle from business plan to coding plan, but I see hints that the industry is headed in that direction," he wrote. "I have no idea how long it will take to get there, but you can now see a shift in products such as Jira (or anything that can maintain a persistent context) … This is the next big innovation in agentic coding. [Vendors] all want to own the larger project/business context 'source of truth' and 'standards'." <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/atlassian_jira_planner-f.jpg "> <img data-src="https://www.techtarget.com/rms/onlineimages/atlassian_jira_planner-f_mobile.jpg " class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/atlassian_jira_planner-f_mobile.jpg 960w,https://www.techtarget.com/rms/onlineimages/atlassian_jira_planner-f.jpg 1280w" alt="Atlassian Jira Planner" data-credit="Atlassian demo screenshot" height="317" width="560"> <figcaption> Atlassian Jira Planner blends context from its Teamwork Graph with spec-driven development to guide AI coding tools. </figcaption> <div class="main-article-image-enlarge"> </div> </figure> </section> <section class="section main-article-chapter" data-menu-title="Atlassian's enterprise AI rivalry with ServiceNow"> <h2 class="section-title">Atlassian's enterprise AI rivalry with ServiceNow</h2> Atlassian Jira faces stiff competition from business workflow management vendors, most notably ServiceNow, to serve as that overall business AI agent orchestration tool, but Atlassian's traditional strength in software development will help its appeal to some enterprises, Mercer said. "Planning is Jira's claim to fame, from long before we got into GenAI -- particularly if you're a long-term user, you've already got this rich data in there to make intelligent decisions," he said. "As we think about organizations adopting agentic ways of working, who's to say that Atlassian's position here doesn't put them in a strong spot to be that core data plane that can be used across the organization?" Other analysts have pointed out a <a href="https://www.techtarget.com/searchitoperations/news/366642661/Atlassian-MCP-updates-take-aim-at-AI-token-usage">lack of configuration management database</a> (CMDB), a historical strength for ServiceNow, as a potential weak spot for Atlassian, but Mercer disagreed. "Every organization I've spoken to outside of a ServiceNow customer who's tried a CMDB [finds] they're always out of date, out of sync," he said. "You hear a lot about it from ServiceNow because they built their company on it, but I don't see a future for CMDBs here." </section> <section class="section main-article-chapter" data-menu-title="Atlassian AI roadmap focuses on visibility"> <h2 class="section-title">Atlassian AI roadmap focuses on visibility</h2> Atlassian's to-do list, as it works toward a strategic 'system of work' for business and software workflows, includes improving visibility into AI usage, quality and activity, based on its 2025 acquisition of DX, Wu said. DX AI cost management, shipped this week, reports on spend and token data across AI coding tools, correlates them to teams and projects, and estimates cost per pull request. A <a href="https://www.computerweekly.com/blog/CW-Developer-Network/Atlassian-builds-enriched-AInative-engineering-with-new-functions-in-DX">previous release</a> offered users insights into how teams use AI tools, down to the session level, along with assessments of code repositories' readiness for AI use. Next, Atlassian DX will add support for local session writeback to capture AI activity on local developer machines for organization-level analysis, according to Wu. "Honestly, I think the entire industry is still at the beginning of this journey with AI visibility," Wu said. "This is definitely an investment area." <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/DJ23iTADFmI?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> Beth Pariseau, senior news writer for Informa TechTarget, is an award-winning veteran of IT journalism. Have a tip? <a target="_blank" href="mailto:bpariseau@techtarget.com?subject=News%20tip" rel="noopener">Email her</a> or connect on <a target="_blank" href="https://www.linkedin.com/in/bethpariseau" rel="noopener">LinkedIn</a>. </section> As enterprises grapple with tokenomics, Atlassian emphasizes upfront planning to improve downstream efficiency. But optimizing AI coding costs and quality remains complex. https://cdn.ttgtmedia.com/rms/onlineimages/arvr_a199792447.jpg https://www.techtarget.com/searchitoperations/news/366645858/Atlassian-Jira-Planner-joins-spec-driven-development-AI-coding-trend Wed, 15 Jul 2026 17:02:00 GMT Atlassian Jira Planner joins spec-driven development AI coding trend In contact centers, AI job replacement will not be evenly distributed. Two recent reports examine how AI is affecting customer service amid a massive disruption caused by the technology. Customers are making their expectations of AI service bots known, and they are not showing much patience for incorrect or off-target AI responses -- so they leave and try competing products. Meanwhile, several national, state and city governments are mulling over different regulatory approaches to slow AI's replacement of humans. Looking at the next two to five years, AI will transform the contact center workforce by eliminating some jobs while <a href="https://www.techtarget.com/searchcustomerexperience/tip/AI-creating-new-contact-center-jobs-for-agents">creating new</a> -- albeit fewer -- roles for specialists to monitor, update and manage AI agents, predicted Forrester Research in a report released July 1 titled "The Quantitative Employment Impact Of AI On Customer Service Jobs." Highly skilled and <a href="https://www.techtarget.com/searchcustomerexperience/tip/Empathy-in-customer-experience-drives-company-success">empathetic human agents</a> will always be needed to tackle complex cases that AI can't solve, said co-author and analyst Kate Leggett. What's more, different verticals will reshape their contact center workforces differently, depending on the complexity of the work and the human touch those industries require to maintain quality service and customer loyalty. Industries such as retail, hospitality and food service -- especially companies with large, high-volume contact centers -- will likely lose more jobs to AI automation than utilities, manufacturing, construction, banking and insurance. Employees at those companies, which require more specialized agent knowledge, are not only less vulnerable to <a href="https://www.techtarget.com/searchenterpriseai/feature/Is-AI-replacing-jobs-How-17-job-types-feel-the-effects">AI replacements</a>, but they also typically command higher salaries. "Some jobs in industries like retail and food services, arts and entertainment, your customer service reps are paid pretty poorly -- barely a living wage," Leggett said. "Those jobs are getting replaced by AI because they tend to the simpler questions [such as]: 'Where's my order?' 'Does this dress come in blue instead of green?' 'How do I do returns, exchanges, refunds?' <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/2KW7uzvxPxo?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> "In industries like utilities, mining, manufacturing -- where salaries are much higher, and where you're working on harder [cases] -- there's less pressure to get rid of jobs, because they're more complicated and harder to automate." But the adoption of AI also presents contact center leaders with several workforce issues to solve. One is <a href="https://www.techtarget.com/searchcustomerexperience/tip/Best-practices-for-call-center-agent-training-programs">onboarding and training</a> new contact center hires when all the entry-level jobs are gone. Another is deploying technically skilled workers on the front lines to keep AI agents updated and on point, especially when an issue -- for example, a newly discovered product defect -- causes a surge in calls and management sets return policies on the fly. One solution may be customer service teams, or pods, consisting of a couple of agents, a manager and an AI specialist within the contact center ranks, Leggett said. Such a model would also allow entry-level workers to apprentice alongside more seasoned veterans, learning to solve thorny customer issues. Regardless of how contact centers change their staffing models, she sees apprenticeship as an important component of AI transformations. Also, AI is unlikely to take over every contact center at once. "Not all contact centers are going to agentify their operations in two years or five years," Leggett said. "There's a lot of entry-level work that still exists. Some contact centers will never be able to get to the automation rates that we project because they're just not set up for it -- they're not technology-forward, they haven't cleaned up their data, they haven't cleaned up their processes. So, there are jobs that will be out there." <section class="section main-article-chapter" data-menu-title="Replacing humans with AI: Illegal?"> <h2 class="section-title">Replacing humans with AI: Illegal?</h2> Truth be told, AI has not precipitated significant job cuts in the economy overall, though there are some notable exceptions, specifically in customer service. Salesforce, for example, <a href="https://www.techtarget.com/searchcio/opinion/The-human-touch-A-CIOs-wake-up-call-on-customer-service-AI">laid off 4,000</a> customer support staff in 2025. This is probably in part why regulators have only begun to examine the idea of <a href="https://www.techtarget.com/searchenterpriseai/opinion/Bans-on-AI-layoffs-Current-laws-and-what-might-come-next">regulations that restrict employers' ability</a> to replace humans with AI agents. That said, efforts are underway globally to address the issue. In China, <a target="_blank" href="https://www.fisherphillips.com/en/insights/insights/chinese-court-rules-employer-cant-fire-worker-because-ai-took-his-job" rel="noopener">courts have limited</a> companies' ability to reduce head count due to AI. The <a target="_blank" href="https://artificialintelligenceact.eu/" rel="noopener">European Union's AI Act</a> has telegraphed possible future intent to limit AI layoffs. In the U.S, New York has a disclosure law on the books that requires companies to notify when AI precipitates layoffs -- which no company has done yet -- and a <a target="_blank" href="https://calmatters.digitaldemocracy.org/bills/ca_202520260sb951" rel="noopener">proposed bill</a> in the California Senate would require employers to give employees 60 days' notice for "technological displacement." Separately in California, last May, Governor Gavin Newsom <a target="_blank" href="https://www.gov.ca.gov/2026/05/21/governor-newsom-signs-first-of-its-kind-executive-order-to-prepare-workers-and-businesses-for-potential-ai-disruption/" rel="noopener">signed an executive order</a> exploring new policies for severance standards, employment insurance and support for workers displaced by "AI transition." Some U.S. attorney groups are <a target="_blank" href="https://lawreview.uchicago.edu/online-archive/nlra-protections-ai-driven-layoffs" rel="noopener">considering novel uses</a> of federal National Labor Relations Act protections to give unions negotiating power in the face of AI layoffs. The National Labor Relations Board has yet to issue an opinion on it. The upshot of all this? Regulations may eventually come, but right now, regulators and courts are in what developers might call early <a href="https://www.techtarget.com/searchsoftwarequality/definition/alpha-testing">alpha testing</a>. </section> <section class="section main-article-chapter" data-menu-title="Customers getting testy with AI service"> <h2 class="section-title">Customers getting testy with AI service</h2> Contact centers, as they grapple with the math of AI layoffs and upskilling the humans who are left, have another challenge: The majority of customers are growing increasingly impatient, expect AI to deliver better service than humans, and would literally rather do anything than contact customer service. Even CX leaders indicated they don't want to deal with customer service in their personal lives. That's according to the "2026 State of Customer Experience Report” of 5,800 consumers of all ages, across 20 countries -- and 1,500 CX leaders across numerous verticals, including telecommunications, automotive, manufacturing, airlines and retail, to name a few -- conducted by CX vendor Genesys. The <a target="_blank" href="https://www.genesys.com/resources/state-of-cx" rel="noopener">comprehensive survey</a> took place last March and April. Yet only 24% of CX leaders globally believe their service organizations are minimizing the effort required for consumers to resolve their issues, even as they hand off work to a hybrid human-AI agent workforce. Challenges to reducing customer friction in contact centers include a lack of data readiness, aging infrastructure and systems that still require customers to repeat their information -- or contents of a chatbot conversation -- to a human after an AI agent hands them off. But they're running out of time: 95% of consumers expect that they won't have to repeat these things to a human contact center agent. On top of that, 85% of consumers said they either spent less with a brand or stopped using it altogether because of poor customer service. "Poor customer service" in the context of AI means the agent has three attempts to resolve a customer query. That's it, said 84% of consumers. They've thrown down the gauntlet and given CX leaders more information to feed into their algorithms, calculating what they will lose if they mismanage AI layoffs and hand over too much to the bots. Don Fluckinger is a seasoned B2B technology journalist with more than 30 years of experience specializing in enterprise IT, digital experience and content management. As a senior news writer at Informa TechTarget, he delivers award-winning analysis that helps IT and business leaders navigate complex technologies to enhance customer and employee experiences. Got a tip? <a href="mailto:don.fluckinger@informatechtarget.com?subject=Tip%20from%20article" target="_blank" rel="noopener">Email him</a>. </section> Apprenticeship may solve the problem of training new contact center hires after AI vacuums up all the entry-level jobs humans now perform. https://cdn.ttgtmedia.com/rms/onlineimages/ai_a205627811.jpg https://www.techtarget.com/searchcustomerexperience/news/366645896/World-leaders-confront-AI-layoffs-more-in-store-for-contact-centers Wed, 15 Jul 2026 15:30:00 GMT World leaders confront AI layoffs; more in store for contact centers Startup database vendor Regatta Data on Wednesday made its entry into a market populated by long-established vendors, launching RegattaDB to provide users with a unified data foundation for developing agents and other AI applications. Traditionally, databases have separated transactional processing, analytical processing and <a href="https://www.techtarget.com/searchdatamanagement/feature/Vector-search-now-a-critical-component-of-GenAI-development">vector search</a> to avoid potential performance bottlenecks that can occur when systems get overloaded. However, to be accurate, agentic and generative AI (GenAI) tools require far more data  than business intelligence or traditional AI applications such as predictive models. Fragmented, isolated data doesn't provide agents and GenAI chatbots with enough context. Instead, they need unified data layers to properly interpret <a href="https://www.techtarget.com/searchdatamanagement/opinion/Context-is-the-make-or-break-layer-for-AI-in-production">business context</a>, deliver accurate outputs and avoid <a href="https://www.evidentlyai.com/blog/ai-hallucinations-examples">misleading hallucinations</a>. In response, long-established database providers such as Couchbase, Microsoft, MongoDB and SingleStore now offer unified platforms. In addition, data platform vendors Databricks and Snowflake each made acquisitions in 2025 to add <a href="https://www.theserverside.com/tip/MySQL-vs-PostgreSQL-Compare-popular-open-source-databases">PostgreSQL databases</a> that can be used to unify data for AI workloads. Now, San Francisco-based Regatta Data is making RegattaDB generally available to similarly provide customers with a data foundation for AI. However, unlike many of its predecessors, RegattaDB was purpose-built for AI workloads rather than retrofitted or rearchitected to unify disparate database workload types. Of particular significance for Regatta Data's users is the potential reductions in cost and complexity when compared with maintaining separate databases for <a href="https://www.techtarget.com/searchdatamanagement/definition/OLAP">analytics</a>, <a href="https://www.techtarget.com/searchdatacenter/definition/OLTP">transactional</a> and vector workloads, according to Stephen Catanzano, an analyst at Omdia, a division of Techtarget. "For organizations deploying AI agents at scale, this means they can finally support the massive concurrency and real-time demands of agent workloads without the fragmentation and latency issues that plague traditional architectures," he told TechTarget. Devin Pratt, an analyst at IDC, similarly noted that potential performance gains are a significant aspect of RegattaDB's launch. "Rebuilding the engine to collapse three systems into one is where the real efficiency comes from," he told TechTarget. <section class="section main-article-chapter" data-menu-title="Made to meet modern demands"> <h2 class="section-title">Made to meet modern demands</h2> Most databases were designed for a bygone era. <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> For organizations deploying AI agents at scale, this means they can finally support the massive concurrency and real-time demands of agent workloads without the fragmentation and latency issues that plague traditional architectures. </figure> <figcaption> Stephen CatanzanoAnalyst, Omdia </figcaption> </div> </blockquote> They were built for business intelligence, feeding dashboards and reports that displayed monthly or quarterly information rather than autonomous agentic AI applications that demand large volumes of fresh, relevant, <a href="https://www.techtarget.com/searchbusinessanalytics/feature/GenAI-demands-greater-emphasis-on-data-quality">high-quality data</a> to properly perform. Even the data management platforms that launched last decade, such as Databricks and Snowflake, weren't originally designed to meet the demands of autonomous AI applications. With enterprises now <a href="https://www.gartner.com/en/newsroom/press-releases/2026-1-15-gartner-says-worldwide-ai-spending-will-total-2-point-5-trillion-dollars-in-2026">investing heavily</a> in building agents, but <a href="https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.html?id=us:2ps:3gl:aisgm26:awa:CONS:em:K0218784:012626:kwd-430833501819:195648817121:794247818306::&gclsrc=aw.ds&gad_source=1&gad_campaignid=23269751971&gclid=CjwKCAjw6MPRBhBTEiwAd-7Mrwla_c_gzzSu2TNPVBWdBS4INV4yNdYgtukO2OU2-zWBAuwZE-s3mBoCwegQAvD_BwE">often struggling</a> to develop AI tools that can be trusted in production, user feedback led Regatta Data to design a database that unifies usually disparate data workloads, according to Regatta Data CEO Boaz Palgi. "Customers demanded [RegattaDB's] capabilities," he told TechTarget, noting that much of the innovation many databases still rely upon dates back to the 20th century. "Modern data … is very different from data in the 1950s, 1960s, and 1970s." RegattaDB is a SQL database built on a concurrency model developed by Regatta Data to unify data and deliver consistent performance for analytical, transactional and vector search workloads. In addition, the concurrency eliminates the need for Regatta Data customers to build pipelines that <a href="https://www.techtarget.com/searchdatamanagement/feature/5-data-integration-challenges-and-how-to-overcome-them">unify data</a> or create synchronization layers. The result is performance at scale, reducing workloads that normally take hours down to less than 5 minutes, according to Regatta Data but not independently verified. "Many agents, one correct picture, in real time -- that's the target, and the concurrency model is built to hit it," Pratt said. Catanzano likewise noted that, based on Regatta Data's performance claims, the vendor's concurrency model appears appropriately constructed to power unified <a target="_blank" href="https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-next-big-shifts-in-ai-workloads-and-hyperscaler-strategies" rel="noopener">workloads at scale</a>. "RegattaDB does appear properly built for its intended purpose, as its patented distributed concurrency control protocol enables it to deliver serializable cross-node consistency across all three workload types simultaneously, and … it can handle [high volumes] of ACID-compliant transactions while executing complex analytics." Meanwhile, with many database providers now unifying previously separate workloads, RegattaDB is somewhat distinguished by an underlying architecture purpose-built for AI rather than one retrofitted or redesigned to handle AI workloads, Catanzano continued. "The company's emphasis on eliminating pipelines entirely and delivering true unification across workload types, rather than just co-locating them, seems to be a key differentiator," he said. Pratt similarly noted that unified databases are becoming more common with <a href="https://www.techtarget.com/searchdatamanagement/news/366583139/Oracle-adds-vector-search-capabilities-to-database-platform">Oracle adding native vector search</a> to its line of databases, PostgreSQL similarly adding support for vector search with pgvector, and the acquisitions made by <a href="https://www.techtarget.com/searchdatamanagement/news/366623864/Databricks-adds-Postgres-database-with-1B-Neon-acquisition">Databricks</a> and <a href="https://www.techtarget.com/searchdatamanagement/news/366625068/Snowflake-acquisition-of-Crunchy-Data-adds-Postgres-database">Snowflake</a>. All, however, are adding capabilities to an engine originally built for one workload. "Everyone says converged, [but]Regatta actually means one engine," Pratt said. </section> <section class="section main-article-chapter" data-menu-title="Next steps"> <h2 class="section-title">Next steps</h2> Just as RegattaDB was built in response to customer demand, user feedback will shape Regatta Data's product development roadmap, according to Palgi. "We will continue to … prioritize the delivery of capabilities that our customers request," he said. Whether asked for by customers or not, Regatta Data would be wise to add integrations with AI frameworks and <a href="https://www.techtarget.com/searchcustomerexperience/news/366636690/Agentic-orchestration-the-next-AI-issue-for-CIOs-to-tackle">agent orchestration platforms</a>, according to Catanzano. By doing so, the vendor can reduce the complexity required to connect RegattaDB with the environments developers and engineers use to build agents. In addition, there is room for Regatta Data to expand its offering by adding new capabilities, Catanzano continued. "Regatta can continue serving current users and attract new ones by expanding its ecosystem integrations with popular AI frameworks and agent orchestration platforms, providing comprehensive tooling and observability features that make it easier for developers to build and monitor agent systems, and demonstrating clear ROI through case studies," he said. Likewise, Pratt suggested that Regatta can grow by doing case studies of companies benefiting from its capabilities. In addition, demonstrating RegattaDB's performance and cost-savings potential through independent <a href="https://www.techtarget.com/searchcio/definition/benchmark">benchmark</a> testing, he added. "Land a workload, prove the savings, and the rest of the estate tends to follow," Pratt said. Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than three decades of experience. He covers analytics and data management. </section> The database vendor is entering a crowded market with the launch of a database purpose-built for agents by unifying disparate data workloads. https://cdn.ttgtmedia.com/rms/onlineimages/iot_g1224942277.jpg https://www.techtarget.com/searchdatamanagement/news/366645786/Regatta-Data-launches-unified-base-for-AI-with-RegattaDB Wed, 15 Jul 2026 11:00:00 GMT Regatta Data launches unified base for AI with RegattaDB The Centers for Medicare & Medicaid Services has <a href="https://www.federalregister.gov/public-inspection/2026-14327/medicare-and-medicaid-programs-calendar-year-2027-payment-policies-under-the-physician-fee-schedule">released</a> the proposed rule for the Medicare Physician Fee Schedule for the 2027 calendar year, which federal leaders say contains some of the most significant Medicare reforms in years. The proposed rule announced yesterday includes an overall reduction to PFS conversion factors following a one-year reprieve from scheduled cuts, as well as an overhaul of physician quality reporting and value-based care systems, including the Medicare Shared Savings Program. "These changes would make it easier for clinicians to focus on prevention, improve coordination for patients, and ensure Medicare rewards better outcomes rather than more services," Oz said in the emailed statement. However, physician groups have already <a href="https://www.amga.org/about-amga/newsroom/press-releases/2026/july/2027-cms-proposed-physician-fee-schedule-rule-illustrates-need-for-systemic-reforms">slammed the conversion factor updates</a>, saying neither conversation factor will cover the actual costs of delivering quality care. <section class="section main-article-chapter" data-menu-title="Proposed Physician Fee Schedule payment policies"> <h2 class="section-title">Proposed Physician Fee Schedule payment policies</h2> The rule provides two conversion factors: one for physicians participating in a qualifying alternative payment model under the Quality Payment Program and one for those reporting under the program's Merit-Based Incentive Payment System. If finalized as is, the rule would enact a qualifying APM conversion factor of 0.75% and a non-APM conversion factor of 0.25%. However, the CMS clarified that the conversion factors would ultimately decrease under the rule. Federal law requires a 2.50% reduction in Medicare payments under the PFS, which was avoided last year under Public Law 119-21, also known as the One Big Beautiful Bill Act. Therefore, the proposed CY 2027 qualifying APM conversion factor would be $33.10, a decrease of about $0.40, and the non-qualifying APM conversion factor would be $32.80, a decrease of about $0.56. The proposed CY 2027 conversion factors reflect a major change that would affect the work relative value units for some services. CMS is on a broader effort to reform the practice expense methodology. The agency will begin this process by reducing the reliance on specialty-specific practice expense per-hour data as told by physician surveys conducted by the American Medical Association. The agency said that the surveys have historically had low response rates and discrepancies between actual data, when available, which have been particularly problematic for specialty providers. The proposed rule would initiate a multi-year shift from the surveys, beginning with phasing out the methodology that ensures the overall number of practice expense RVUs by specialty is consistent with data from 2007 or earlier. Eventually, CMS hopes to replace it with a practice expense stabilizer that anchors values to a specific point in time. The rule would also adjust the allocation of indirect practice expense for physician visits to patients in skilled nursing facilities, aligning with the current site-of-service payment differential policy finalized last year. The proposed rule would also decrease payment by 50% when a separately identifiable office or outpatient evaluation and management visit is done by the same physician or practice on the same day as a global procedure. The least expensive service -- surgical or E/M -- would be subject to the reduced rate. As part of President Donald J. Trump's Make America Healthy Again initiative, the CMS is also seeking to create an HCPCS code for shared medical appointments, which the agency said help to reduce and manage chronic illness while addressing <a href="https://www.techtarget.com/pharmalifesciences/feature/How-Do-Social-Isolation-and-Loneliness-Impact-Healthcare-Outcomes">social isolation and loneliness</a>. The rule would also create two additional HCPCS codes for advanced care planning services, which would distinguish the work done by billing from the time spent by clinical staff. The existing ACP CPT codes 99497 and 99498 would only be used to report time personally spent by billing staff, CMS explained. </section> <section class="section main-article-chapter" data-menu-title="Transforming value-based care for physicians"> <h2 class="section-title">Transforming value-based care for physicians</h2> Physician quality reporting and value-based care programs are also slated for major reform in the coming years. By 2029, the CMS wants to sunset the traditional MIPS reporting system in favor of MIPS Value Pathways, specialty-specific sets of measures and activities for MIPS reporting. The MVPs have been voluntary since their introduction in 2023, but the CMS wants clinicians to transition fully to the sets, which it considers more clinically meaningful. The agency also proposed three new MVPs focused on diabetes, hypertension and hospital-based care. If finalized, the CMS said the updated MVP options would provide a relevant reporting option for about 98% of specialties. Physicians have long complained that <a href="https://www.techtarget.com/revcyclemanagement/news/366600573/Study-Finds-MIPS-Scores-Dont-Reflect-True-Quality-Performance">MIPS has not captured actual patient outcomes or the true quality of care</a>, while also being a heavy administrative burden and disproportionately penalizing smaller or safety-net practices. The proposed rule also included a major overhaul of the MSSP, with updated benchmarking and financial methodologies. Under the rule, the CMS intends to balance incentives for accountable care organizations in the higher levels of the BASIC and ENHANCED tracks. As such, the agency proposed a 60% shared savings rate (up from 50%) for Level E of the BASIC track and a 35% maximum weight (up from 50%) for the positive regional adjustment for ACOs in the ENHANCED track. The CMS said that reducing this gap in savings percentages should increase participation and the long-term success of ACOs, especially since ACOs in Level E have generated higher Medicare savings than those in the ENHANCED track. The proposed rule would also increase the prior savings adjustment's scaling factor from 50% to 75% to provide relief from the rebasing "ratchet effect," in which the savings an ACO generates later reduce its rebased benchmark. This ratchet effect has made it harder for cost-cutting ACOs to generate savings later. To encourage new ACO participation, the CMS also proposed a benchmark growth adjustment for practices with limited experience with risk or value-based care. The adjustment would be applied to the highest existing benchmark adjustments eligible to the ACO, not exceeding the proposed risk adjusted 5% cap. The rule would also implement a guardrail limiting the Accountable Care Prospective Trend to no more than 1 percentage point below (or 1.5 percentage points above) national growth rates, with retroactive application of the lower guardrail for PY 2025 reconciliation. "Expanding accountable care is a critical part of making the Medicare program work well for patients," John Brooks, CMS Deputy Administrator and Director of the Center for Medicare, said in the press release. "Our goal is simple: deliver better outcomes for patients by appropriately incentivizing providers, improving quality measurement, and reducing administrative burden." Jacqueline LaPointe is an Executive Editor at Xtelligent Healthcare Media, covering revenue cycle management, healthcare payers, health policy and health IT since 2016. </section> The 2027 Medicare Physician Fee Schedule rule would cut conversion factors, sunset traditional MIPS and overhaul the Medicare Shared Savings Program despite provider pushback on costs. https://cdn.ttgtmedia.com/rms/onlineimages/medical%20revenue_a53814245.jpeg https://www.techtarget.com/revcyclemanagement/news/366645846/Physician-pay-cuts-loom-as-CMS-unveils-major-Medicare-reforms Wed, 15 Jul 2026 10:46:00 GMT Physician pay cuts loom as CMS unveils major Medicare reforms Healthcare cyberattacks have shown no sign of slowing in 2026, according to a new <a href="https://www.comparitech.com/news/healthcare-ransomware-roundup-h1-2026-stats-on-attacks-ransoms-and-data-breaches/">report</a> from Comparitech. The company's worldwide ransomware tracker recorded a 14% increase in healthcare ransomware attacks, from 360 in the first half of 2026 compared to 410 in the second half of 2025. Healthcare organizations faced an average of 2.3 ransomware attacks per day. Of the 410 recorded ransomware attacks, 247 targeted hospitals, clinics and other direct care providers, while 163 affected other healthcare businesses, such as pharmaceutical manufacturers, health tech companies and medical billing providers. While the industry as a whole saw an increase in ransomware attacks, that increase was largely driven by attacks against healthcare businesses and vendors. Ransomware attacks on healthcare providers worldwide rose just 3% from the second half of 2025, while attacks targeting healthcare businesses rose 36%. In the U.S., attacks on healthcare providers actually dropped by over 7%. Still, the U.S. saw the highest number of attacks overall, accounting for 225 of the 410. Cyberthreat groups Qilin, The Gentlemen, LockBit and INC were the most active in the first half of 2026, the report showed. The report is the latest addition to a growing body of research and threat briefs that show why healthcare organizations should remain on high alert. <section class="section main-article-chapter" data-menu-title="More health data threats arise"> <h2 class="section-title">More health data threats arise</h2> In addition to the Comparitech research, other industry reports have shown that healthcare organizations are struggling to balance growing cyber risk with adequate mitigation efforts. For example, a new <a href="https://www.techtarget.com/healthtechsecurity/news/366645829/Healthcare-struggles-with-risk-remediation-in-first-half-of-2026">report</a> from Fortified Health Security showed a 60% increase in critical and high-risk vulnerability findings in the first half of 2026 compared to last year. The increase in findings indicates that organizations are improving their ability to identify vulnerabilities and risk areas. However, risk remediation dropped to 6.4% in the first quarter of 2026, down from 23.3% in the same period in 2025, indicating they still struggle to obtain the resources to fix them. In other cyberthreat news, the National Security Agency, alongside various national and international cybersecurity leaders, issued a <a href="https://www.ic3.gov/CSA/2026/260713.pdf">warning</a> on July 13 that Russian state-sponsored hackers are exploiting poorly configured networking devices worldwide, "opportunistically compromising multiple critical infrastructure sector networks." Healthcare is one of the handful of critical infrastructure sectors that the NSA said is most at risk. </section> <section class="section main-article-chapter" data-menu-title="Regulatory efforts on pause"> <h2 class="section-title">Regulatory efforts on pause</h2> As healthcare faces mounting cyber threats, major regulatory updates that would have changed how the industry responds to threats are now on the back burner for another year. In January 2025, the HHS Office for Civil Rights <a href="https://www.techtarget.com/healthtechsecurity/news/366617620/HHS-proposes-HIPAA-Security-Rule-changes">proposed modifications to the HIPAA Security Rule</a> to address the increasing frequency of healthcare cyberattacks and strengthen security requirements for covered entities to account for modern-day threats. The final rule, which was expected to be released in May 2026, has now been <a href="https://www.reginfo.gov/public/do/eAgendaViewRule?pubId=202510&RIN=0945-AA22">pushed back to July 2027</a>, according to the Office of Management and Budget website. The rule would have incorporated sweeping changes that would require covered entities to meet stricter standards -- from mandating annual penetration tests and a specific risk analysis methodology to requiring multifactor authentication. The proposal was met with <a href="https://www.techtarget.com/healthtechsecurity/news/366636104/Providers-urge-HHS-to-scrap-proposed-HIPAA-Security-Rule-updates">mixed feedback</a> from the industry. In December 2025, more than 100 hospital systems, provider organizations and associations urged HHS Secretary Robert F. Kennedy, Jr., to rescind the Biden-era proposed rule in favor of conducting a collaborative outreach initiative to develop actionable cybersecurity standards without increasing regulatory burden. HHS stood its ground, with OCR Director Paula M. Stannard saying at the HIMSS conference in March 2026 that "there's a very high cost of doing nothing." At the time, Stannard said that OCR had yet to decide which, if any, of the proposals would ultimately be finalized, but stressed that the proposal's core principles remain sound best practices for healthcare entities. Now, healthcare organizations have been left in limbo for another year as healthcare cyberattacks continue to impact the sector. Jill Hughes has covered health tech news since 2021. Her coverage areas include cybersecurity, HIPAA compliance, interoperability, AI and EHRs. </section> A new report shows that healthcare organizations have faced 410 ransomware attacks in the first half of 2026, as regulatory efforts to bolster healthcare cybersecurity stalled. https://cdn.ttgtmedia.com/rms/onlineimages/security_a135187239.jpg https://www.techtarget.com/healthtechsecurity/news/366645935/Healthcare-ransomware-attacks-surge-14-amid-growing-cyberthreats Wed, 15 Jul 2026 09:32:00 GMT Healthcare ransomware attacks surge 14% amid growing cyberthreats Observability challenger Cribl laid the groundwork for expansion into SecOps tools this week by acquiring CardinalOps, as the company competes for enterprise attention amid a crowded AI data management landscape. Cribl, which started as a log management system that reduced the data users sent to Splunk's analytics backend, has since <a href="https://www.techtarget.com/searchdatamanagement/news/366609255/Cribl-positions-for-IPO-with-319M-in-latest-funding-round">pivoted toward an IPO</a>, focusing on AI-based telemetry management and data routing tools that plug into multiple observability and security systems. This is Cribl's first step beyond data routing and management into providing data analytics content. In this case, CardinalOps, which has offices in Boston and Tel Aviv, will contribute content in detection engineering, the process of mapping the observed behavior of users and systems to recognized attack signatures documented by standard frameworks such as <a href="https://www.techtarget.com/searchsecurity/tip/Mitre-ATTCK-framework-use-cases">Mitre ATT&CK</a>. Detection engineering is a key component of security information and event management (SIEM) systems. Cribl is headed in that direction with the acquisition of CardinalOps' IP and some 20 security engineers, according to Cribl CEO and co-founder Clint Sharp in an interview with TechTarget this week. <div class="imagecaption alignLeft"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/sharp_cllint.jpg" alt="Clint Sharp, CEO and co-founder, Cribl">Clint Sharp </div> "We needed to bring that DNA into the company as we continue to expand, responding to the pull we're seeing from our customers to be a more full-stack security company," Sharp said. Detection engineering fits well with Cribl's experience at the data control layer, said Sean Sosnowski, a research director at Software Analyst Cyber Research in Toronto, in an email to TechTarget this week. "Security teams are no longer only asking how to collect and route telemetry more efficiently; they are asking whether their data architecture actually improves detection coverage," Sosnowski wrote. "CardinalOps adds a detection posture layer that can identify coverage gaps, rationalize SIEM content, map detections to frameworks like Mitre ATT&CK, and help teams understand whether they have the right detections for the threats they care about." <section class="section main-article-chapter" data-menu-title="Standing out from the AI data management crowd"> <h2 class="section-title">Standing out from the AI data management crowd</h2> This move by Cribl sits at the nexus of multiple industry trends as enterprises struggle to <a href="https://www.techtarget.com/searchitoperations/news/366645026/AgenticOps-for-infrastructure-faces-a-deterministic-dilemma">move AI agents into production at scale</a>: emphasis on a strong telemetry and data foundation for agent context; consolidation of observability and security monitoring data, tools and companies; expanded "Bring Your Own Cloud" support for SaaS observability tools; and <a href="https://www.techtarget.com/searchitoperations/news/366639662/SaaSpocalypse-Maybe-not-but-SaaS-applications-are-changing">AI's effect on software UX</a>, where end users increasingly use bespoke agents instead of packaged user interfaces. <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> In an agentic future, what customers are going to be looking for is a place where they can put petabytes of telemetry data, but they don't necessarily want the user experience a vendor designed for them. </figure> <figcaption> Clint SharpCEO and co-founder, Cribl </figcaption> </div> </blockquote> Given those multiple industry inflection points, Cribl also faces a broad array of potential competitors -- some of them its partners -- as it integrates CardinalOps. In addition to established SIEM and security platform vendors such as Splunk, Microsoft Sentinel, Palo Alto Networks, Google SecOps, Elastic and Datadog, Cribl must also differentiate itself from data management generalists such as Snowflake, which bought the observability startup <a href="https://www.techtarget.com/searchdatamanagement/news/366637059/Snowflake-storms-into-IT-monitoring-with-Observe-acquisition">Observe in January</a>, and Databricks, which acquired the AI security operations center company <a href="https://www.computerweekly.com/blog/CW-Developer-Network/Panther-AI-SOC-platform-closes-loop-on-security-Ops">Panther Labs in June.</a> None of that is lost on Sharp, who said Cribl plans to compete on its existing strengths in observability with a flexible, customizable approach to SecOps tools. "We're giving you the same output as you are getting from a SIEM, hopefully significantly more cost-effective, and then with a platform-first approach, you can start to build your own experiences," Sharp said. "In an agentic future, what customers are going to be looking for is a place where they can put petabytes of telemetry data, but they don't necessarily want the user experience a vendor designed for them."  As Splunk and other vendors have in the past, Cribl charges based on data volume, but Sharp claimed its pricing also significantly undercuts competitors' rates. "We're trying to give [customers] double the data for the dollar," he said. "There's an old [Jeff] Bezos adage: 'Your margin is my opportunity.' That's just what we're doing." Meanwhile, Cribl also offers a more purpose-built, packaged backend for telemetry data than general-purpose data analytics systems such as Snowflake or Databricks, Sharp said. "Our buyers don't have time to write <a href="https://www.techtarget.com/searchdatamanagement/definition/Extract-Load-Transform-ELT">ETL jobs</a>," he said. "They just need to be able to collect log data and metric data and tracing data [with] all the properties of a data warehouse, but [they] don't want to have to manage schemas and data definition language and all the stuff that goes along with doing databases." </section> <section class="section main-article-chapter" data-menu-title="SIEM scaffolding, not a full structure"> <h2 class="section-title">SIEM scaffolding, not a full structure</h2> Still, Sharp and a company press release this week were careful to call CardinalOps' initial integration "SIEM-like" rather than positioning it as an immediate replacement for a full SIEM platform. While detection engineering is a major piece of the puzzle, Cribl would still need a few other key components to become a full-fledged SIEM. Threat intelligence and threat-hunting workflows are the most significant gaps Cribl must fill to reach full SIEM status, said Michelle Abraham, an analyst at IDC, in an interview with TechTarget. <div class="imagecaption alignLeft"> <img src="https://cdn.ttgtmedia.com/rms/onlineimages/abraham_michelle.jpg" alt="Michelle Abraham, analyst, IDC">Michelle Abraham </div> "With Cribl Search, they have that part of the capability -- with all of the data that they have in there, you know, you can do proactive threat hunting by querying it yourself," Abraham said. "Many of the SIEM vendors have their own threat intelligence teams in addition to being able to bring in threat intelligence from <a target="_blank" href="https://www.cisa.gov/resources-tools/services/mandiant-threat-intelligence" rel="noopener">outside providers</a>." Established SIEMs also offer stronger native analytics, investigation workflows, case management, detection content, alert triage and response workflows, and analyst experiences, Sosnowski wrote. "Cribl is approaching the market from a different control point," he wrote. "Its near-term role is more likely to be a vendor-neutral layer that helps enterprises decide what telemetry matters, where it should go, and how it supports detection coverage across the tools they already use." Other emerging security vendors have tried to differentiate with the "Bring Your Own" approach in the past, which often works well for early adopters with the expertise to build tools in-house, Abraham said. But established SIEM vendors also support AI agents as an interface; as SecOps processes mature, "Bring Your Own" often migrates back toward outsourcing to a vendor, she said. "In my experience of looking at this from the outside, an enterprise may build something themselves, thinking, 'We can do better than what's in the market,'" Abraham said. "The thing is, are you able to maintain it to be better than what's in the market? That tends to trip a lot of organizations up when, two years later, they're looking at what they built versus what's in the market, and they're going, 'Oh.'" <div class="youtube-iframe-container"> <iframe id="ytplayer-0" src="https://www.youtube.com/embed/nVYzxWhtokY?autoplay=0&modestbranding=1&rel=0&widget_referrer=null&enablejsapi=1&origin=https://www.techtarget.com" type="text/html" height="360" width="640" frameborder="0" loading="lazy"></iframe> </div> Beth Pariseau, senior news writer for Informa TechTarget, is an award-winning veteran of IT journalism. Have a tip? <a target="_blank" href="mailto:bpariseau@techtarget.com?subject=News%20tip" rel="noopener">Email her</a> or connect on <a target="_blank" href="https://www.linkedin.com/in/bethpariseau" rel="noopener">LinkedIn</a>.  </section> Erstwhile Splunk nemesis adds a "SIEM-like" experience, with IP and engineering from CardinalOps folded into its "Bring Your Own Agent" pitch to IT buyers. https://cdn.ttgtmedia.com/rms/onlineimages/security_a254815015.jpg https://www.techtarget.com/searchitoperations/news/366645843/Cribl-buys-CardinalOps-for-detection-engineering-edges-into-SecOps Tue, 14 Jul 2026 16:51:00 GMT Cribl buys CardinalOps for detection engineering, edges into SecOps Health plans and their pregnant members might agree that member communication is a priority, but they aren't on the same page about what good communication actually looks like, according to a new <a href="https://sage-growth.com/market-report/a-generation-of-new-mothers-confused-about-benefits-and-newborn-care/">report</a> from Sage Growth Partners. <a href="https://www.techtarget.com/healthcarepayers/feature/Top-Member-Education-Strategies-for-High-Performance-Network-Benefits">Member communication</a>, particularly about maternity care, is flagging, the report showed. Only 4% of the 50 surveyed health plan leaders said their members understand their maternity and postpartum coverage "very well," and more than half (58%) said members understand coverage only "somewhat well." Members tell a similar story, with 56% of the 300 recently pregnant health plan members surveyed saying as much. "At one of the most important and vulnerable points in a family's healthcare journey, too many women are struggling to understand their coverage, navigate their care and find the support they need," Dan D'Orazio, CEO of Sage Growth Partners, said in a <a href="https://www.prnewswire.com/news-releases/new-research-reveals-major-communication-gap-between-health-plans-and-new-mothers-302824037.html">statement</a>. All of this paints a fractured landscape for member communication, the report authors indicated. And although members and health plan leaders alike agree that better member communication before, during and after pregnancy is key, they aren't on the same page about how to fix it. <section class="section main-article-chapter" data-menu-title="Member communication doesn't resonate"> <h2 class="section-title">Member communication doesn't resonate</h2> The problem isn't that health plans aren't communicating; it's that they aren't communicating in ways that resonate with members. That leaves members feeling ill-informed and alone, which could ultimately adversely affect outcomes -- and health plans' bottom lines. In some cases, payers and members literally aren't speaking the same language. A third of members said they don't receive communications in their <a href="https://www.techtarget.com/patientengagement/feature/Understanding-Patient-Rights-to-Medical-Interpreters-Language-Access">preferred language</a>, rendering messages useless for folks with limited English proficiency. In other cases, the disconnect comes down to poor messaging. For example, only 30% of members said the resources their health plan gave them were helpful. And while 53% of members said they receive text message outreach from their health plans, only 28% said those messages were helpful. The risks of poor member communication are real. According to the survey, 41% of members didn't feel confident taking their babies home from the hospital. Another 56% said they were at least a little confused about their health plans, as well as health risks during pregnancy. To their credit, health plans are aware of their member communication problems and are eager to fix them. In fact, 68% of health plan leaders said member engagement and navigation is a key maternal health priority for the next 24 months. But there's a disconnect between member needs and health plan approaches to communication. </section> <section class="section main-article-chapter" data-menu-title="Health plans off-base about member communication needs"> <h2 class="section-title">Health plans off-base about member communication needs</h2> Although plans identified member communication as a strategic priority, especially regarding maternity care programs, they aren't hitting on the topics members need. For example, although health plans think items like cost-sharing, covered benefits, <a href="https://www.techtarget.com/healthcarepayers/feature/Whats-ahead-for-prior-authorizations-as-new-requirements-loom">prior authorization requirements</a> and eligibility or redeterminations are most confusing for members, the member survey told a different story. Recently pregnant people said they are more worried about how long their coverage lasts and what services are covered. Health plans and members are also not in agreement about the most <a href="https://www.techtarget.com/patientengagement/news/366585026/What-Are-Omnichannel-Patient-Engagement-Technologies">effective communication channels</a>. Health plans think live phone calls, text messages, and community outreach are most effective, but they are only somewhat correct. Members early in their pregnancy value text messages, mobile apps and printed materials. For those later in their pregnancy, they value engagement that actually supports them in taking care of their baby -- phone or text check-ins with nurses, lactation support and behavioral health support (such as for postpartum depression). This discrepancy could be risky for health plans, 70% of which said they face significant financial pressures in maternal health. As health plans target their biggest cost centers -- preterm births, long NICU stays and high-cost inpatient stays -- they will need to consider the engagement strategies that will resonate with members and move the needle on outcomes. </section> <section class="section main-article-chapter" data-menu-title="Opportunities to connect with pregnant members"> <h2 class="section-title">Opportunities to connect with pregnant members</h2> Health plans need to consider their members' biggest pain points. According to the report, members are most confused about these key health plan details: <ul class="default-list"> <li>How long postpartum coverage lasts (38%)</li> <li>What services are covered (37%)</li> <li>Copays and deductibles (30%)</li> <li>Which hospitals or providers are in network (29%)</li> <li>Pre-admission approval requirements (21%)</li> </ul> Health plans should ensure their member communication strategies hit on these topics, but that's not all. Members noted that they don't feel supported, particularly during the postpartum period, with nearly a tenth of respondents saying they didn't hear from their payer or provider after being discharged from the hospital. As a result, nearly four in 10 members said they felt underconfident in taking their babies home from the hospital. Ramping up communication during the fourth trimester -- the three months after a member gives birth -- would <a href="https://www.techtarget.com/healthcarepayers/news/366603128/3-Key-Metrics-that-Determine-Member-Satisfaction-for-Health-Plans">improve member satisfaction</a> and prevent adverse medical events. Finally, health plans need to ensure communication is written to actually resonate with members. This doesn't just mean adhering to members' language preferences, although that is important. It also requires keen attention to <a href="https://www.techtarget.com/patientengagement/news/366585260/The-Difference-Between-Patient-Education-and-Health-Literacy">health literacy</a> and <a href="https://www.techtarget.com/patientengagement/feature/Cultural-Competence-in-Healthcare-Why-Its-Important-How-to-Build-It">cultural competence</a>. "Health plans need to rethink how, when and where they communicate with pregnant and postpartum women," according to D'Orazio. "Closing this chasm isn't about increasing the volume of communication. It's about making every interaction more relevant and actionable." Sara Heath is an executive editor at Xtelligent Healthcare Media, where she covers patient engagement, healthcare policy and health IT. </section> Health plans and their members have different ideas of what constitutes good member communication during pregnancy, a new report shows. https://cdn.ttgtmedia.com/rms/onlineimages/chatbot_g1132487500.jpg https://www.techtarget.com/healthcarepayers/news/366645771/Health-plans-fall-short-in-maternity-care-member-communication Tue, 14 Jul 2026 14:10:00 GMT Health plans fall short in maternity care member communication Where hospital care happens is fundamentally shifting, according to the latest hospital financial performance data from Kaufman Hall. The healthcare consulting firm released its monthly <a href="https://www.vizient.com/insights/reports/national-hospital-flash-report/may-2026-data">National Hospital Flash Report</a> yesterday, drawing on data from more than 1,300 hospitals. In addition to outlining operating margins for the month of May, the report also highlighted an ongoing trend  -- the shift from inpatient to outpatient hospital care. Year-to-date, daily discharges remained stable, while adjusted daily discharges increased by 2%. The average length of stay also fell by 2% during that period. But daily outpatient revenue was significantly up by 6% year-over-year and 8% year-to-date. Notably, the metric increased by 26% year-to-date compared to this time three years ago. This underscores the ongoing shift of care outside the hospital, Kaufman Hall explained. A move that should prompt hospitals and health systems to rethink resource allocation as cost pressures continue to challenge finances. Recent health policy changes have supported this transition of care out of the hospital. CMS is in the <a href="https://www.techtarget.com/revcyclemanagement/news/366645250/CMS-takes-aim-at-340B-site-neural-payments-in-OPPS-proposal">second year of phasing out Medicare's inpatient-only list</a>, which details procedures that Medicare only covers when a patient is formally admitted as an inpatient. The list will no longer exist by 2028, giving hospitals and ambulatory surgical centers more flexibility for site-of-care service. CMS has also aggressively revised criteria to make more surgeries eligible for reimbursement at freestanding ASCs. The agency also implemented more site-neutral payment policies to make hospital-based outpatient care more affordable. Hospital financial leaders are making moves to shift resources from the traditional inpatient centers to these more convenient, lower-overhead community care sites, imaging centers and ASCs. However, they are also considering how the expansion of site-neutral payment policies, which bring down reimbursement rates to those of physician practices, could dampen profitability. They are also considering how their organizations' revenue cycle management technology can handle higher volumes of low-dollar claims compared to more complex, costly inpatient services. This shift of more straightforward surgeries to outpatient centers is also leaving remaining inpatient beds dominated by highly complex, acute cases. This requires leaders to restructure the organization's cost structure to align with higher-acuity, resource-intensive cases within the hospital. "Health systems must adapt their portfolios and operations to support the future of care delivery," Erik Swanson, managing director and leader of the Data and Analytics Group at Kaufman Hall, said in a <a href="https://www.kaufmanhall.com/news/hospital-and-health-system-ma-activity-among-highest-q2-levels-2019">press release</a>. "Reevaluation of organizational strategies and resource allocation may also unlock new opportunities to maximize effectiveness going forward." <section class="section main-article-chapter" data-menu-title="Hospital margins dip in May"> <h2 class="section-title">Hospital margins dip in May</h2> The report also revealed slightly lower operating margins in May than in the previous month and over the last year. Researchers calculated a calendar year-to-date operating margin index of 2.9% and a monthly operating margin index of 2.7%. Both figures are medians without accounting for allocations. This compares with April 2026, when hospitals were performing significantly better, with a year-to-date operating margin index of 3.6% -- the highest so far this year. The monthly operating margin index was also higher in April, at 3.6%, following another high of 3.7% in March. Hospital financial performance seemed to be on an upswing, but labor and expenses have put further downward pressure on hospitals. In May, both areas remained elevated, up 5% each compared to this time last year. Additionally, bad debt and charity care increased over the last year, with year-over-year increases of 16% per calendar day and 7% of gross operating revenue. This comes on the heels of the expiration of the enhanced premium tax credits for coverage through the Affordable Care Act Marketplace, which has <a href="https://www.techtarget.com/healthcarepayers/news/366645717/ACA-premiums-set-to-surge-14-as-tax-credits-expire">decreased enrollment and increased premiums</a>. Many people have already chosen to forgo comprehensive health insurance to avoid significant cost increases. Hospital financial leaders are monitoring how these reforms and those to Medicaid will affect the uninsured rates and where their patients will seek care, whether in an outpatient center or the emergency department. <a href="https://www.techtarget.com/revcyclemanagement/news/366645250/CMS-takes-aim-at-340B-site-neural-payments-in-OPPS-proposal"></a><a href="https://www.kaufmanhall.com/news/hospital-and-health-system-ma-activity-among-highest-q2-levels-2019"></a>Jacqueline LaPointe is an Executive Editor at Xtelligent Healthcare Media, covering revenue cycle management, healthcare payers, health policy and health IT since 2016. </section> Outpatient revenue jumped 8% YTD while operating margins fell to 2.7% in May, prompting strategic changes, Kaufman Hall reports. https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/healthcare-medical-statistics-stethoscope-adobe.jpeg https://www.techtarget.com/revcyclemanagement/news/366645808/Care-continues-shift-to-outpatient-as-hospital-margins-dip Tue, 14 Jul 2026 13:21:00 GMT Care continues shift to outpatient as hospital margins dip To bring AI agent development under one roof, Oracle today updated AI Agent Studio for Fusion Applications. The AI agent builder combines no-code, low-code and pro-code tools, which can accommodate line-of-business users building simple task-based agents. It also supports developers, who can build more complex agents with Git-based workflows and coding tools such as Claude Code, and they have access to sandboxes and other familiar testing tools. Oracle also released Fusion Agentic Applications, native runtime apps that can manage Oracle and third-party AI agents and AI automations within Fusion cloud apps, spanning CX, HR, ERP and supply chain. The new tools and apps build on Oracle's previous <a href="https://www.techtarget.com/searchdatamanagement/feature/4-trends-that-will-shape-data-management-and-AI-in-2026">"agent swarm"</a> orchestration, which deploys multiple lightweight agents together to execute more complex work, said Holger Mueller, an analyst at Constellation Research. Fusion AI Apps update traditional apps for the AI era. "You don't use your Fusion apps and add the agent," Mueller said. "You build a new app, which uses an agent for what an agent does well, and then there's other stuff that the human still has to do." Many cloud companies in the CX realm -- including Pegasystems, Adobe <a href="https://www.techtarget.com/searchcustomerexperience/news/366626390/Genesys-Cloud-AI-Studio-enables-generative-AI-agents">and Genesys</a> -- are working to <a href="https://www.techtarget.com/searchcustomerexperience/opinion/Customer-service-AI-pricing-just-turned-into-the-biggest-shell-game">limit LLM calls</a> by combining deterministic workflows with probabilistic ones and by setting limits such as monthly caps on AI agent costs. Mueller added that, compared to this time last year, enterprises are no longer looking to LLMs to accomplish everything in sight. Rather, they want to apply AI only where it makes sense -- logically and economically -- in the workflow. "Either my agent returns me my sales numbers, or it doesn't," Mueller said. "There's nothing probabilistic in that." Fusion Apps aren't strictly an <a href="https://www.techtarget.com/searchapparchitecture/tip/Harness-engineering-Agent-harnesses-as-critical-infrastructure">AI harness</a>; they are business applications with an outcome in mind, such as improving collections, workforce optimization or service call deflections. But they utilize some of the same capabilities, such as security and governance rules within the Fusion environment, said Kaushal Kurapati, group vice president of applications development at Oracle. "[It's a] combination of AI-assisted reasoning with LLMs, but yet a deterministic runtime execution," Kurapati said. "So you get the flexibility and power of the LLM and the predictability, reliability, consistency and speed you need for executing an enterprise workflow." <figure class="main-article-image full-col" data-img-fullsize="https://www.techtarget.com/rms/onlineimages/screenshot_meg-f.jpg"> <img data-src="https://www.techtarget.com/rms/onlineimages/screenshot_meg-f_mobile.jpg" class="lazy" data-srcset="https://www.techtarget.com/rms/onlineimages/screenshot_meg-f_mobile.jpg 960w,https://www.techtarget.com/rms/onlineimages/screenshot_meg-f.jpg 1280w" alt="Screenshot of Oracle's AI agent builder " data-credit="Oracle" height="272" width="559"> <figcaption> Oracle's AI agent builder can accommodate line-of-business users describing what they need in plain language. </figcaption> <div class="main-article-image-enlarge"> </div> </figure> <section class="section main-article-chapter" data-menu-title="Studio merges development modes"> <h2 class="section-title">Studio merges development modes</h2> AI Agent Studio for Fusion Applications brings together plain-language coding tools with a pro-code environment that includes app lifecycle management, local validation, debugging and <a href="https://www.techtarget.com/searchsoftwarequality/CI-CD-pipelines-explained-Everything-you-need-to-know">CI/CD workflows</a>. In doing so, Kurapati said, line-of-business users -- the ones who know where the workflow bottlenecks are -- can work with developers to resolve them with new apps. Non-developers can write or describe agents, and when necessary, developers can step in to apply an enterprise's testing and deployment methodologies. Pro developers can also build AI agents, <a target="_blank" href="https://docs.oracle.com/en-us/iaas/Content/generative-ai/skills.htm" rel="noopener">AI skills</a> and Fusion Agentic Applications in popular AI coding tools such as OpenAI Codex and Anthropic Claude Code, which integrate with AI Agent Studio. "A business user, if they're comfortable with a natural language interface, can go in and build it," Kurapati said. "They can [also] quickly prototype, show it to a developer and say, 'Look, why don't you harden this with all the safeguards, guardrails, testing use cases and everything, and build me that same thing in Codex?" Don Fluckinger is a seasoned B2B technology journalist with more than 30 years of experience specializing in enterprise IT, digital experience and content management. As a senior news writer at Informa TechTarget, he delivers award-winning analysis that helps IT and business leaders navigate complex technologies to enhance customer and employee experiences. Got a tip? <a href="mailto:don.fluckinger@informatechtarget.com?subject=Tip%20from%20article" target="_blank" rel="noopener">Email him</a>. </section> AI apps: Oracle's latest answer to mixing deterministic and probabilistic automations with governance. https://cdn.ttgtmedia.com/rms/onlineimages/machine_learning_g1184268577.jpg https://www.techtarget.com/searchcustomerexperience/news/366645665/Oracle-AI-agent-builder-brings-no-code-low-code-and-pro-code-together Tue, 14 Jul 2026 12:00:00 GMT Oracle AI agent builder brings no-code, low-code and pro-code together Alation is taking on AI governance to aid enterprises attempting to build agents that can be trusted in production. Many organizations, despite investing heavily in agentic AI development, <a href="https://www.techtarget.com/searchdatamanagement/feature/Good-governance-key-to-reducing-high-AI-project-failure-rate">still struggle</a> to move AI experiments beyond the pilot stage. While myriad reasons contribute to failed experiments, including outdated technology infrastructures and lack of buy-in from executives, data-related problems are prominent among them. In particular, the inability to connect agents with the appropriate data and <a href="https://www.techtarget.com/whatis/definition/business-logic">business logic</a> that gives them the context to deliver accurate outputs has hampered agentic AI development initiatives. Alation, which already provides data catalog capabilities that enable organizations to govern data, on Tuesday launched the Alation Intelligence Operating System (AIOS). The OS, which works in conjunction with existing Alation governance capabilities, is aimed at better enabling customers to build AI tools that can be <a href="https://www.techtarget.com/searchcio/feature/Startup-founder-says-trust-is-biggest-barrier-to-AI-agents">trusted in production</a> by connecting data, context and agents in a unified environment. Features include Agent Studio to develop agents and agentic governance capabilities, such as lineage and access controls, that automate manual work. "AIOS is a meaningful expansion for Alation customers because it delivers needed AI governance atop the existing foundation rather than asking enterprises to start another isolated AI-governance program to manage agent data intelligence," Michael Ni, an analyst at Constellation Research, told TechTarget. Alation's introduction of AIOS follows its <a href="https://www.techtarget.com/searchdatamanagement/news/366642977/Alation-intros-AI-governance-suite-to-ensure-compliance">unveiling of AI Governance</a> to help organizations remain regulatory compliant as they deploy agents, <a href="https://www.techtarget.com/searchdatamanagement/news/366639805/Alation-automates-governance-with-latest-AI-powered-suite">outcome-based governance</a> to govern data using agents, and <a href="https://www.techtarget.com/searchdatamanagement/news/366634209/Alation-unveils-agentic-AI-suite-for-governing-critical-data">CDE Manager</a> to better oversee data related to critical operations such as reporting and risk management. For AIOS to deliver on its promise, it needs to easily integrate with Alation's other agentic AI governance capabilities, according to Ni. "Alation has historic strength in data discovery and governance but now has to show that its new solution areas of Agent Studio, AI governance, compliance and feedback deliver one integrated system at enterprise scale," he said. <section class="section main-article-chapter" data-menu-title="Building for success"> <h2 class="section-title">Building for success</h2> With the failure rate of AI projects <a target="_blank" href="https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.html?id=us:2ps:3gl:aisgm26:awa:CONS:em:K0218784:012626:kwd-430833501819:195648817121:794247818306::&gclsrc=aw.ds&gad_source=1&gad_campaignid=23269751971&gclid=CjwKCAjw6MPRBhBTEiwAd-7Mrwla_c_gzzSu2TNPVBWdBS4INV4yNdYgtukO2OU2-zWBAuwZE-s3mBoCwegQAvD_BwE" rel="noopener">still higher than the success rate</a>, connecting agents with context has emerged as the dominant trend in data management and AI development. In June alone, AWS, Databricks, Microsoft and Snowflake unveiled new capabilities to connect agents with context. <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> AIOS is a meaningful expansion for Alation customers because it delivers needed AI governance atop the existing foundation rather than asking enterprises to start another isolated AI-governance program to manage agent data intelligence. </figure> <figcaption> Michael NiAnalyst, Constellation Research </figcaption> </div> </blockquote> Vendors have taken different approaches, such as improving the data retrieval process, upgrading vector search and <a href="https://www.techtarget.com/searchdatamanagement/opinion/Why-data-semantics-matters-for-context-aware-systems">adding semantic layers</a>. Alation, through agent-powered governance, is similarly trying to help customers build agents they can put into production. "We developed AIOS from a mix of customer demand and a fundamental shift we observed in how AI is redefining data management," Satyen Sangani, Alation's co-founder and CEO, told TechTarget. "AI provides so much power to do the work that historically has been side-of-desk, things like stewardship, quality, lineage. [Additionally], the result of this work is now so much more critical and impactful." In particular, the work is needed to catch <a target="_blank" href="https://www.evidentlyai.com/blog/ai-hallucinations-examples" rel="noopener">incorrect outputs</a> that agents are confident are correct, he continued. "When software breaks, it throws an error, but when an AI agent breaks, it produces a confident, incorrect answer, and most organizations have no system of record to catch it," Sangani said. "AIOS closes that gap … so enterprises can trust the AI they're already running instead of finding out after the fact." Data-related problems that frequently stall agentic AI projects include bad data causing an agent to act on improper context, agents misreading context that isn't clear, and <a href="https://www.techtarget.com/searcherp/feature/How-leaders-can-spot-AI-drift-before-it-hurts-the-business">agent drift</a> with instructions, tools and training degrading over time and causing the agent to diverge from its intended goal. Alation's new operating system is designed to address each problem by providing the following capabilities: <ul type="disc" class="default-list"> <li>Agent Studio, an environment aimed at enabling users to develop trustworthy agents that call on governed proprietary data and business logic for context.</li> <li>Governed data and AI workflows to ensure that agents remain in compliance with <a href="https://www.techtarget.com/searchenterpriseai/tip/Global-AI-legislation-and-regulation-tracker">changing regulations</a>.</li> <li>Control over context, access and lineage so that each agent-powered decision can be traced and certified.</li> <li>Conversational analytics so users can query and analyze governed data.</li> </ul> "The AIOS represents a notable shift toward automation by using agents to proactively curate metadata, map data lineage and scale enterprise governance," William McKnight, president of McKnight Consulting, told TechTarget. "It's a clever way to prevent confident fails [by agents, but] introduces some vendor lock-in for the sake of faster AI deployment." By pre-certifying <a href="https://www.techtarget.com/searchdatamanagement/tip/Metadata-management-standards-examples-that-guide-success">metadata</a> and enforcing governance policies, AIOS appears appropriately constructed to reduce agent hallucinations, he added. Meanwhile, AIOS is in step with current AI governance trends rather than pacing the market, according to McKnight. "The entire enterprise data governance industry has simultaneously pivoted to launch specialized suites for governing autonomous AI agents," he said. "They are all racing to solve the exact same enterprise problem -- ensuring that autonomous AI does not act on bad data or violate compliance boundaries." Ni likewise noted that by connecting AIOS to <a href="https://www.techtarget.com/searchdatamanagement/news/252499007/Alation-brings-data-catalog-technology-to-the-public-cloud">Alation's catalog</a> and other governance capabilities, the new operating system seems logically put together to aid customers as they build and manage agents. However, for it to truly operate as intended, AIOS needs to not only help govern agents under development but also once they're deployed, he continued. "AIOS has the foundational components," Ni said. "The open question is how far governance extends into production execution. A complete offering should continuously monitor agent behavior, propagate the correct user identity and entitlements, enforce policies at the point of action, and provide a runtime audit trail." From a competitive perspective, Ni noted that Actian, Atlan, Credo AI, IBM, Microsoft and ServiceNow are all addressing <a href="https://www.techtarget.com/searchenterpriseai/feature/Agentic-governance-must-go-beyond-traditional-IT-practice">agent governance</a>. However, Alation is among the first to unify capabilities such as context, lineage and conversational analysis in an open architecture. "The real test will be if context advantage can demonstrably translate into stronger runtime decisions and fewer operational failures," Ni said. </section> <section class="section main-article-chapter" data-menu-title="Plotting the future"> <h2 class="section-title">Plotting the future</h2> With AIOS now generally available, Alation is preparing to release new ontology capabilities – governed definitions of data and relationships similar to semantic models – and improving its existing lineage, data quality, data observability and AI governance tools, according to Sangani. Following the introduction of AIOS, Ni noted that there's an opportunity for Alation to turn the new OS into <a href="https://www.techtarget.com/searchdatamanagement/opinion/Context-is-the-make-or-break-layer-for-AI-in-production">a context layer</a> for agents working across environments such as databases, multiple cloud data platforms and an array of SaaS applications. "Alation's opportunity is to connect what the enterprise knows with what its agents are doing right now, while opening a much larger market among AI platform and operations teams," he said. McKnight, meanwhile, suggested that Alation could better serve existing customers and perhaps attract new ones by integrating AIOS with <a href="https://www.techtarget.com/searchdatamanagement/opinion/Data-observability-for-AI-helps-curb-poor-model-performance">data observability</a> capabilities and advancing its agentic AI tools to include more autonomous insight generation and automation. "Furthermore, expanding the platform to support unstructured and multimodal data is considered crucial for building a comprehensive AI ecosystem," he said. Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than three decades of experience. He covers analytics and data management. </section> While not the first AI governance suite, the vendor's Intelligence Operating System is somewhat unique by unifying data, context and agents in one environment. https://cdn.ttgtmedia.com/rms/onlineimages/ai_a264431831.jpg https://www.techtarget.com/searchdatamanagement/news/366645666/Alation-launches-OS-for-building-governing-AI-agents Tue, 14 Jul 2026 10:03:00 GMT Alation launches OS for building, governing AI agents Maintaining visibility into incoming cyber threats has long been a challenge for healthcare organizations. But, according to a new <a href="https://fortifiedhealthsecurity.com/horizon-reports/">report</a> from Fortified Health Security, the industry is getting better at it. The company's analysis of rolling <a href="https://www.techtarget.com/healthtechsecurity/news/366594008/NIST-Releases-CSF-20-Caters-to-Audience-Beyond-Critical-Infrastructure">NIST Cybersecurity Framework 2.0</a> client assessment data showed a 60% increase in critical and high-risk findings in the first half of 2026 compared to last year. However, remediating those risks is something healthcare has not yet mastered. The report found that risk remediation dropped to 6.4% in the first quarter of 2026, down from 23.3% over the same period in 2025. What's more, on average, an identified risk remained unresolved for 345 days. "This isn't the story of a single catastrophic breach," the report stated. "It's the story of visibility outpacing capacity." <section class="section main-article-chapter" data-menu-title="Increased framework adoption highlights high-risk areas"> <h2 class="section-title">Increased framework adoption highlights high-risk areas</h2> The good news is that healthcare organizations that have adopted the NIST CSF 2.0 are benefiting from it, the report stated. The framework is effectively highlighting cybersecurity gaps. Identifying these vulnerabilities is half the battle, and healthcare is getting better at it. The report found that supply chain risk management findings are on track for a 6x increase in 2026 compared to 2025. Identity management, authentication and access control findings are trending toward a 4x increase. Although an increase in vulnerability findings may seem like a red flag, it shows that healthcare organizations have increased visibility into vulnerabilities that might have otherwise gone unnoticed. Fortified Health Security assessed where the healthcare sector stands regarding the six functions of the NIST CSF 2.0: govern, protect, identify, detect, respond and recover. Overall, the analysis found that healthcare organizations are getting better at incident eradication, defining roles and responsibilities and responding to cyber incidents. However, assessing critical supplier risk, continuous monitoring, oversight and training are all areas in which they continue to lag. These shortcomings are largely due to operational constraints, such as staffing shortages, the report said. "The human capital challenge is not new to healthcare cybersecurity. Modern tooling and security frameworks are just making the gaps it leaves more visible," the report noted. "Even where teams have prioritized well, remediation has stalled because you simply can't close a finding if you don't have the people to do the work. No framework fixes a headcount problem." Along with finite resources, prioritization challenges remain a bottleneck to effective remediation. With a multitude of vulnerabilities to address in a given day, security teams must determine whether a vulnerability is associated with an active ransomware campaign, whether the system is patient-facing and other important considerations. This time-consuming process, however necessary, can delay risk remediation, especially when staff is limited. Overall, healthcare organizations are getting better at identifying their risk areas. The next step is effectively mitigating those risks. "The organizations that use that visibility to drive prioritization, a strategic roadmap, and the resourcing towards remediation will be the ones that turn a growing list of findings into risk reduction rather than the next headline," the report stated. Jill Hughes has covered health tech news since 2021. Her coverage areas include cybersecurity, HIPAA compliance, interoperability, AI and EHRs. </section> Healthcare organizations are improving at identifying cyber threats, but remediation efforts continue to lag due to resource constraints and operational challenges. https://cdn.ttgtmedia.com/rms/onlineimages/health%20security_g1302091582.jpg https://www.techtarget.com/healthtechsecurity/news/366645829/Healthcare-struggles-with-risk-remediation-in-first-half-of-2026 Tue, 14 Jul 2026 09:23:00 GMT Healthcare struggles with risk remediation in first half of 2026 Though AI is increasingly used to generate patient portal messages, new research shows it tends to write responses that don't necessarily align with what a clinician would write. This increases clinicians' cognitive burden, defeating one of the reported benefits of using AI to generate these notes in the first place. The research, conducted by Dartmouth researchers and<a href="https://aclanthology.org/2026.acl-long.1505/"> presented at the 2026 annual meeting of the Association for Computational Linguistics</a>, aimed to compare the alignment between LLM-generated patient portal drafts and responses written by clinicians. For the study, the researchers created a tool to compare AI-generated notes to clinician-written ones. They collected 146,000 patient-clinician conversations from a large academic hospital in the United States. The researchers included Claude, Gemini and ChatGPT as well as three smaller commercial platforms, Llama, Aloe and Qwen, in the study. They also assessed different adaptation approaches to align LLMs with clinicians. The study shows that LLMs that were not adapted at all tended to over-treat and over-diagnose, generating more medical assessment and treatment-planning themes than clinicians did. This could include long explanations of test results, symptoms, and potential diagnoses, as well as recommendations of various forms of treatment. Additionally, responses from expert clinicians and adapted LLMs tended to ask the patient more follow-up questions; however, unadapted LLMs rarely asked follow-up questions, even though their responses tended to be longer. "You don't want to integrate large language models into the workflow and just shift the bottleneck so that doctors are devoting their cognitive energy to playing AI janitor and fixing mistakes," said Sarah Preum, Ph.D., the study's co-corresponding author and an assistant professor of computer science at Dartmouth, in <a href="https://www.eurekalert.org/news-releases/1134481">a press release</a>. "But if we're not careful, that's a likely outcome." Thus, the study concluded that adapting AI to align with clinicians' communications is necessary to "increase the reliability and responsibility of LLM use for patient message response drafting." The study showed that adapting LLMs can improve accuracy by 33% and reduce editing by 26%. A technique developed by the Dartmouth team, called Thematic Agentic Direct Preference Optimization for Learning Enhancement, or TADPOLE, was especially effective at drafting responses that better matched physicians' standards. The researchers noted that future research needs to assess how much time clinicians actually spend editing AI message drafts and to further evaluate TADPOLE, including examining whether and how it lightens a physician's workload.  "This is one of the first studies that uses real patient portal messages to establish a generative AI model. In that regard, it's innovative and shows us that this is not a simple task," said Tim Burdick, M.D., a study co-author, an associate professor of community and family medicine and a family medicine physician at Dartmouth. "We're still nowhere near the point of having clinicians removed from the workflow." Anuja Vaidya has covered the healthcare industry since 2012. She currently covers healthcare IT and innovation, including artificial intelligence, digital healthcare, EHRs and interoperability. AI-generated patient portal messages often misalign with clinician responses, increasing cognitive burden, but adapting LLMs can improve accuracy and reduce editing, new research shows. https://cdn.ttgtmedia.com/rms/onlineimages/keyboard_g164210754.jpg https://www.techtarget.com/searchhealthit/news/366645706/AI-patient-portal-message-may-increase-clinicians-cognitive-burden Mon, 13 Jul 2026 14:49:00 GMT AI patient portal message may increase clinicians' cognitive burden WhatIs 60 webmaster@techtarget.com