Evidence-based medicine is universal—but its application is not. Clinical practice is shaped by differences in specialty, care setting, patient population, and individual preference, and supporting high-quality care means embracing this diversity. In traditional EHRs, dot phrases begin to address this need by allowing clinicians to define and share simple copy/paste text and templates. Dot phrases have become a valuable part of many clinicians’ practice, supporting personalized workflows that match the way each provider practices.

Dotflows represent the extension of dot phrases for full natural language customization in the AI-native era. Dotflows are reusable natural language prompts that customize how OpenEvidence responds. This simple concept enables a wide range of customization and personalization capabilities, expanding to the limits of clinician creativity. Some example uses include personalizing the response style, pre-defining recurring clinical context, and running structured workflows. Clinicians can create their own Dotflows or browse Dotflows shared and used by other clinicians in the community.

Also Read: HMA Acquires HealthTech Solutions, Expanding Technology Capabilities and Medicaid Expertise

“The value of any clinical tool depends on how well it fits into the way a clinician actually practices,” said Dr. Mondira Ray, SVP of Clinical Informatics at OpenEvidence. “Dotflows let users define that fit, encoding their personal styles and mental models into the platform itself.”

Clinicians invoke Dotflows by typing “.” in the search bar, or by setting them as defaults for all queries. Over time, these reusable commands enable OpenEvidence to become increasingly aligned with each clinician’s preferences and practice patterns.

The release also establishes a living library of community-created Dotflows. Clinicians can browse the library, clone Dotflows from the library, and share their own Dotflows with the broader community.

Source: BusinessWire

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Also Read: WellStack and Healthcare Systems of America Partner to Build Unified Data Foundation for AI-Driven Healthcare Analytics

In one oncology case, enrollment rose by 80%. This boost led to more revenue from improved screening capabilities. “Bringing Clinical AI to Google Cloud Marketplace will help customers quickly deploy, manage, and grow the company’s MAIA Prescreening solution on Google Cloud’s trusted, global infrastructure,” said Dai Vu, Managing Director, Marketplace & ISV GTM Programs at Google Cloud. The solution also supports broader workflows such as trial simulations, document processing, and multilingual capabilities, further enhancing clinical operations.

Read More: Clinical AI Announces the Launch of MAIA Prescreening on Google Cloud Marketplace

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Also Read: Databricks and Fivetran Bring Agentic AI to Streamline Healthcare Referral Management

By standardizing data across systems, HSA aims to strengthen operational visibility, financial outcomes, and scalability of analytics capabilities. “As healthcare systems continue to evolve, the ability to unify and activate data across the enterprise becomes a strategic priority. By partnering with WellStack to establish a modern data foundation, we are creating the infrastructure needed to improve operational transparency, strengthen financial performance, and support the next generation of analytics and AI-enabled insights,” said David Colarusso, CIO, Healthcare Systems of America.

Read More: WellStack Partners with Healthcare Systems of America to Establish a Unified Data Foundation and Enable Enterprise Analytics

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The acquisition of HealthTech Solutions enhances HMA’s capabilities in government health technology, adding advanced data, analytics, and systems modernization expertise to its established policy, regulatory, and operational advisory services. HealthTech’s specialization in Medicaid technology strengthens HMA’s ability to support state agencies with integrated solutions spanning strategy through technical implementation.

“HealthTech Solutions has an impressive track record of providing state-of-the-art IT solutions and strategic insights that deliver results for clients,” said Jay Rosen, HMA’s founder and current president and chairman. “Their expertise further expands the ways in which we can serve our clients now and into the future. We are excited to have HealthTech join the HMA team.”

Also Read: SEQSTER Unveils AI-Powered Patient Screening for Clinical Trials

“This acquisition marks an important step in HMA’s continued evolution as a comprehensive partner to state Medicaid agencies and government health programs. We are thrilled to welcome the talented HealthTech Solutions team to our distinguished group of colleagues,” said Chuck Milligan, chief executive officer of HMA. “HealthTech’s advanced technology platform, experienced leadership team, and strong client relationships enhance our ability to deliver innovative solutions that improve outcomes for the populations our clients serve.”

Sandeep Kapoor, co-founder and chief executive officer of HealthTech Solutions, added, “This acquisition marks an exciting new chapter for our company. Joining HMA will allow us to grow, expand the value we deliver to our clients, and build on the strong foundation we have created. At the same time, our commitment to excellence in service and products remains unchanged and will continue to be at the heart of everything we do.”

HealthTech Solutions will continue to operate as HealthTech Solutions, an HMA Company. Terms of the transaction were not disclosed. Synergy Advisors served as exclusive financial advisor to HealthTech Solutions in this transaction.

Source: PRNewswire

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Documentation is still a major source of workload for healthcare professionals as it is not only a source of the extension of clinicians work hours but also the limitation of the time that can be spent with patients. SpeechLive Health is here to solve this problem by recording doctor-patient discussions and thereafter producing automatically the structured outputs like SOAP notes, visit summaries, and referral letters. With this, clinicians will be able to dedicate more time to patient care, while still maintaining accurate and compliant documentation.

Unlike general-purpose AI tools, the platform is based on a domain-specific large language model that was created by medical professionals. This guarantees that the outputs are in line with the clinical workflows, coding standards, and regulatory requirements, thereby increasing both the accuracy and usability of the tools in healthcare environments.

Also Read: Bayer Consumer Health Scales Global Self-Service Analytics with Databricks Unity Catalog

“For more than 70 years, Speech Processing Solutions has helped shape professional dictation and transcription in healthcare and has established a reputation as a leading partner in the medical market,” said Dr. Thomas Brauner, CEO of Speech Processing Solutions. “Philips SpeechLive Health marks the next step in that journey – building on the strong foundation of superior dictation hardware and leading software solutions combined. By adding this healthcare-trained AI assistant, we’re creating the next generation of an integrated solution that further reduces administrative burden, simplifies workflows and multiplies customer benefits, giving clinicians more time for patient care.”

The platform is also secure, with AES-256 encryption, as well as being compliant with regulations such as HIPAA, GDPR, and ISO 27001. The clinicians are in complete control of their audio files and editable documents.

Finally, with the integration of the Philips SpeechMike Ambient Wearable AI Assistant, a hands-free wearable with advanced microphone capabilities and voice filtering, SpeechLive Health is able to provide a complete solution with accurate speech capture, even in loud clinical environments.

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Also Read: Provation Unveils Mira iPro Insights to Deliver Real-Time Perioperative Intelligence 

When these insights are put into practice in operational systems, organizations have a way to monitor the referral cycle via orders, scheduling, and completion of visits, as well as keeping record of patient journeys, provider capacity, referral leakage, and performance metrics throughout different healthcare networks. Deployment of production, grade AI agents is a major innovation flagship in the initiative, as these AI agents are capable of analyzing not only huge stacks of structured and unstructured medical data but also extracting insights, automating complex workflows. With Databricks Genie, healthcare executives, departmental leaders, and operational staff will using natural language to query their data, finding answers about, for example, patient flow, emergency room waiting time, or frequency of readmission, in a matter of moments via visualization, tables, and analytic results. This conversational analytics model diminishes the need for technical skills like SQL and empowers healthcare practitioners to get access to insights even within their day, to, day activities. The system also demonstrates how AI agents can process large document repositories, similar to enterprise use cases where AI analyzes extensive clinical trial documentation, allowing hospitals to extract structured information from decades of historical medical records without extensive coding. By integrating automated data ingestion, advanced analytics, and AI agents within a unified data intelligence platform, Databricks and Fivetran aim to help healthcare organizations transition from fragmented IT infrastructures to intelligent, data-driven care networks that improve operational efficiency and support better patient outcomes.

Read More: Transforming Healthcare Referrals with Fivetran, Agentic AI, and Databricks Genie

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The New Platform Provides Life Sciences and Healthcare Companies Access to Longitudinal Data from 150M+ Patients Across the U.S.

SEQSTER PDM, the leading healthcare technology company and the data connection, collection, and orchestration layer for patient health data, announced the launch of its 1-Click DataLake, the real world data (RWD) platform accelerating study design, recruitment, and evidence generation for life sciences and healthcare.

Built on more than a decade of aggregated electronic health record (EHR) data, 1-Click DataLake provides access to real-world data from more than 150 million de-identified patients and 200,000 clinicians nationwide. The platform securely queries patient-consented records to deliver real-time, longitudinal visibility into patient journeys. These insights support advanced analytics and real-world evidence (RWE) generation to inform trial design, feasibility, and execution.

Also Read: Johns Hopkins Launches Open Source Cancer Study Database 

“We are turning health data into medicine for our clients,” said Ardy Arianpour, CEO & Co-Founder of SEQSTER. “With longitudinal, research-ready data from 150M+ patients, we’re now providing a turnkey real world data infrastructure that accelerates study design, optimizes patient recruitment, and enables evidence generation. By rapidly unlocking insights directly from real clinical encounters, our platform delivers a step-change in speed, scale, and intelligence across the clinical research lifecycle.”

SEQSTER’s queryable platform spans a broad range of practices and specialties and includes deep integration with diverse and historically underserved populations. This capability directly supports recent FDA mandates promoting diversity in clinical trials, helping sponsors ensure that studies better reflect the populations they intend to serve. The platform includes robust patient populations across a wide range of therapeutic areas, enabling precise cohort identification and more effective recruitment strategies.

Source: Businesswire

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As a global health organization with business operations in many markets and products, Bayer Consumer Health faced the challenge of managing the growing volume of data that existed across regions, systems, and teams. The organization’s legacy architecture also did not allow business users to quickly discover trusted datasets to gain insights without having to rely heavily on the organization’s data engineering teams. To overcome the challenge, Bayer partnered with Databricks to deliver a self-service analytics environment that leverages the capabilities of Unity Catalog, the governance backbone of the Databricks Data Intelligence Platform for the management of enterprise data and analytics assets.

Unity Catalog offers a centralized governance layer that allows businesses to effectively manage permissions, data lineage, and security policies for data and AI workloads. The ability to unify governance and discovery for multiple workspaces has allowed business users, analysts, and data scientists to effectively collaborate with each other while maintaining complete control over sensitive data assets. With this strategy, Bayer has been able to simplify data access for its global teams and enable self-service analytics to minimize the need for centralized data teams.

This process has enabled Bayer Consumer Health to develop a unified data environment that facilitates quick generation of insights, collaboration between business and technical groups, and clear usage of data. It has become easy for analysts to find data sets, understand how the data was created, and utilize it to make business decisions without spending considerable time searching for or validating the data.

Also Read: SPS Adds Ambient Medical AI to Philips SpeechLive with Corti 

One of the major aspects of this initiative was to develop strong governance while allowing decentralized data ownership. Unity Catalog has enabled domain teams at Bayer to have complete control over their data sets while adhering to centralized governance principles. This has enabled flexibility in innovation with data in different regions while maintaining standardized principles for access, audit, and quality checks.

The platform also enables a new data mesh architecture, in which data is treated like a product and owned by domain teams, rather than IT groups. Bayer Consumer Health’s data architecture, organized in this way, has allowed for improved scalability and agility in its overall analytics ecosystem. This enables a more collaborative culture, in which teams can independently create and share data products.

With the expanded use of Databricks and Unity Catalog, Bayer Consumer Health has effectively democratized data access across its global workforce. Business users can now explore trusted datasets, perform advanced analytics, and build insights-driven strategies without waiting for data engineering teams to provision or prepare data.

This process is enabling Bayer to drive innovation and make better decisions in areas like marketing, supply chain, and product development. The company is laying the foundation for future AI and advanced analytics projects with high-quality and well-governed data through its self-service analytics and strong governance.

Bayer’s case study essentially demonstrates how big global companies can improve their analytics infrastructure to derive more value out of their data. Bayer Consumer Health is using Databricks Unity Catalog as its governance and discovery platform to drive innovation in terms of speed, collaboration, and scalability in its global operations.

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Called AstroID, the resource organizes clinical and correlating blood and tissue specimen information in six tiers, including information from the patient (deidentified to protect privacy); diagnosis; clinical events such as treatment or a blood draw; specimens such as material from a biopsy or serology; and then details about how those are processed by the lab into tissue blocks and vials, down to individual slides or aliquots.

The structure, built in a commercial web-based application called REDCap, can be subsequently scaled to accommodate thousands of patients and the spatial characterization of billions of cancer cells. A description of AstroID, which has been made available for any researcher to use, was published Dec. 25, 2025, in the Journal for Immunotherapy of Cancer. The work was supported in part by the National Institutes of Health.

Researchers at Johns Hopkins Medicine have now deployed this structure in their laboratories for 16 different patient groups with multiple tumor types, and they have over 1 billion cells spatially mapped and tagged with clinical information from patient experiences.

Typically, in oncology, each patient’s course includes multiple visits, treatments and outcome measures, explains Janis M. Taube, M.D., director of the Division of Dermatopathology and co-director of the Tumor Microenvironment Laboratory at the Bloomberg~Kimmel Institute for Cancer Immunotherapy. To identify and characterize biomarkers, these parameters need to be linked to multiple tests and assessments, including blood-based laboratory values, tissue-based pathology, radiography, genomic studies and more.

Also Read: AdvancedMD Launches AI to Streamline Workflows 

“What this structure does is allow me to ask questions across all of this data that’s already been gathered, and across tumor types, and combine it all together in the context of the longitudinal patient experience,” Taube says.

For example, her lab often conducts studies of patients with melanoma. If she conducted a study 10 years ago looking at patients’ age at diagnosis and what therapies they received, and then later wanted to do another study of this patient population and survival, she might have had to repeat some of the steps to compile a new cohort and regather information about treatments received, what specimens were collected, and clinical outcomes. “Investigators across the whole institution are also trying to tap into these patients and collect this information,” she says. “There were really huge inefficiencies across how we were working, and duplicating efforts.”

It had been painstaking for researchers to manually enter data, so cancer studies typically were designed around relatively small cohorts, adds Alexander Szalay, Ph.D., Bloomberg Distinguished Professor and professor in the Department of Computer Science at The Johns Hopkins University.

“What we are trying to do is to scale out so we can handle patients on the order of hundreds or thousands of patients in a study,” says Szalay, who also is the director of the Institute for Data Intensive Science at Johns Hopkins. “One of our postdoctoral students, Elizabeth Will, in partnership with graduate student Benjamin Green, came up with this wonderful idea of how to organize all the medical and specimen data into multiple hierarchical tiers, which then can be easily translated to a query-oriented platform based on a large relational database.”

While the Johns Hopkins team for now is using this platform for cancer studies, the structure could be adapted to characterize longitudinal biospecimens from any disease process, they said.

Source: Johns Hopkins

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AdvancedMD is officially launching its AI Clinical Assistant, giving providers access to new AI features aimed at helping reduce time spent on documentation and charting tasks.

AdvancedMD, a provider of cloud-based healthcare software for independent medical practices, announced the launch of its 2026 Winter Product Release. The latest updates to the unified EHR, practice management, and patient engagement platform include highly effective AI-enabled features designed to help private practice providers and staff spend more time with patients and less time on administrative work.

The AdvancedMD 2026 Winter Product release represents significant focus on creating a more efficient practice with the official release of the AdvancedMD AI Clinical Assistant, in addition to new patient engagement tools and a newly added “Password Breach Detection” security feature.

According to a recent Medical Group Management Association survey of practice leaders, 55% of respondents report that their practice does not conduct compliance training or refreshers beyond “at-hire or hire-date” training programs. The AdvancedMD “Password Breach Detection” feature offers additional levels of security across the entire platform, ensuring compromised passwords from a data breach cannot be used when setting or resetting a password to access the system. When a compromised password is detected, the user is prompted to reset their password.

Also Read: Flatiron Launches AI Global Prostate Cancer Data 

“We are starting this year out with a bang, delivering all new AI features designed to improve security functions, enhance practice efficiencies, and elevate the user experience for thousands of private practices that rely on AdvancedMD to streamline their daily workflows,” said AdvancedMD CEO Amanda Sharp. “The AI-enabled features we’re releasing today can significantly reduce the amount of time providers and their staff spend on tedious documentation and charting tasks—giving providers more time to focus on patient care.”

The AdvancedMD 2026 Winter Product Release includes more than twenty total updates across the EHR, Practice Management, and Patient Engagement platform. Here is a snapshot of the highlights:

EHR

• AI Clinical Assistant Ambient Listening & Transcription: The newly added AI Clinical Assistant Ambient Listening and Transcription tool can help practices automate clinical documentation and tasks, giving providers the option to use AI to capture patient conversations during a visit. Providers are always in control of the AI transcription tool and can pause or stop recording at any time.
• AI Clinical Assistant Action Items: The AI Clinical Assistant Action Items features automatically analyzes patient visit transcripts and generates suggested action items for the patient chart, reducing manual data entry tasks during and after each visit. Action items can include patient issues, medical histories, allergies, medications, and lab orders, in addition to various note suggestions, such as chief complaint, reason for visit, or vitals.
• Manage requests from Pharmacy Benefit Managers (PBMs): AdvancedMD customers can now receive and manage requests from pharmacy benefit managers directly in the AdvancedMD platform. The newly added PBM requests include new prescriptions or changes to existing therapies based on clinical insights, formulary updates, or cost-saving opportunities. This update can improve care coordination, reduces gaps in therapy, and streamline prescribing workflows.

Practice Management Platform

• Enhanced Scheduler: The Enhanced Scheduler now has a new interface and features to provide more intuitive workflows and faster loading times, especially for schedules with multiple pages and columns. Additionally, changed appointments, blocks, and holds now update immediately. Other updates to the Enhanced Scheduler include better visibility into time zones and time and date indicators, new customization and “My Page” viewing capabilities, new search features, and more.
• Cancel/No-show (CNS) Appointment Entries: The CNS Appointment feature now allows users to automatically charge a fee for a canceled appointment or no-show based on the patient’s carrier, helping practices comply with various carrier policies. AdvancedMD customers can also charge CNS fees based on appointment type. If a practice clears a canceled or no-show status from an appointment, the related charge is automatically voided and the CNS note is deleted.
• AI Narrative Insights in the Analytics & Reporting: The newly added AI Narrative Insights uses artificial intelligence to analyze and interpret key data patterns from the AdvancedMD dashboard, offering a narrative explanation to better understand patterns and trends in the practice’s data, highlight potential issues, and uncover business-critical data relationships. AI Narrative Insights update automatically whenever underlying chart data changes.

Patient Engagement

• Calendar Links: The new “Add to Calendar” feature allows patients to automatically save an appointment to their online calendar, improving patient engagement strategies and helping to reduce no-show rates. Practices can include “Add to Calendar” links in key patient engagement touchpoints, including appointment reminders, telehealth appointments, patient portal, and online scheduling.

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