Full-Time
$89.01 - $117.94/hr
Oakland, CA, USA
In Person
Company Size
10,001+
Company Stage
N/A
Total Funding
N/A
Headquarters
Palo Alto, California
Founded
2012
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LogicSource, a procurement services and technology provider, has been named to The Boston Globe and Statista's New England's Fastest-Growing Companies 2026 list. The company achieved 104% revenue growth during the recognition period whilst expanding its workforce by 20%. Based in Westport, Connecticut, LogicSource completed 40,000 sourcing events annually for clients using its OneMarket technology platform, which now holds over $200 billion in cross-industry spend benchmarks. The company focuses on indirect procurement across categories including marketing, logistics, packaging and facilities. LogicSource serves clients such as lululemon, Tractor Supply Co., and Stanford Healthcare. The ranking, published by The Boston Globe in partnership with Statista, evaluates businesses based on sustained revenue growth and operational scale.
Stanford Health Care took the stage at HIMSS to share their EHR training success. Amplifire + Kahuna Partnership were honored to see this work come to life during Stanford Health Care's presentation at HIMSS Global Health Conference & Exhibition last week. Anne Hyland, Vice President of EHR Learning, and Michael Walker, Senior Director of New Business at Amplifire, were able to hear first-hand how their team handled the challenges and the measurable outcomes they've achieved. It was a powerful reminder of what's possible when innovation is paired with a clear focus on outcomes. What stands out most is Stanford Health Care's thoughtful approach to modernizing onboarding. Rather than accepting traditional, one-size-fits-all training, they've embraced a more personalized, data-driven model that meets clinicians where they are, respecting prior experience while ensuring mastery of critical workflows. The result is not only greater efficiency, but a more confident, prepared workforce ready to deliver high-quality care from day one. As highlighted in their broader work, this approach has also enabled earlier identification of struggling learners and more targeted support, ultimately strengthening both performance and satisfaction. Stanford Health Care continues to set the standard for innovation in workforce development, and their recent feature in Healthcare IT News highlights just how impactful that work has been. By reimagining EHR training, their team has successfully reduced training time by 50% while simultaneously improving learning retention, an achievement that speaks to both their strategic vision and deep commitment to clinician success. Congratulations to the entire Stanford Health Care team on this well-deserved recognition. Their leadership is not only advancing their own organization, but helping to shape the future of healthcare workforce development across the industry.
Nikesh Kotecha on blueprint for trust: how ChatEHR establishes a framework for Responsible AI in clinical care. Stanford Health Care, part of Stanford Medicine, was awarded a 2025 InterSystems Impact Award for its AXIOM initiative for fast access to electronic health records. In turn, AXIOM underpins the ChatEHR medical chatbot that Nikesh Kotecha, head of the Data Science team at Stanford Health Care, presents below. The Impact Award recognizes the work of the team to deliver low-latency, comprehensive access to patient data from complex electronic health record (EHR) systems. This foundation has been essential to enabling the ChatEHR platform. Contribution by Nikesh Kotecha The integration of Large Language Models (LLMs) into health systems holds the promise of reducing administrative burden and cognitive overload for clinical teams. However, deploying such tools in clinical workflows requires a commitment to safety, governance, and continuous monitoring. Stanford Medicine's ChatEHR platform, an initiative developed as part of an enterprise investment in establishing a Data Science pillar, serves as an essential case study for any health system aiming for responsible AI adoption. Setting up a responsible clinical AI system requires focus on three key areas: a robust platform architecture, transparent governance, and continuous evaluation. A significant barrier to integrating AI tools into clinical workflows is often fragmented data sources and latency in data access. Traditional reporting systems were unsuitable for the real-time applications needed at the point of care. The ChatEHR Platform tackles this with a sophisticated, four-pillar architecture: * LLM Router: Provides secure access to a variety of models, standardizing calls and handling centralized logging. * Real-Time Data Access: Fetches and organizes clinical information using Fast Healthcare Interoperability Resources (FHIR). This enables near real-time responsiveness by combining FHIR and HL7v2 messaging with optimized query performance. * Function Server: Transforms generic AI capabilities into healthcare-specific functions and task-specific endpoints, powering workflow automations. * EHR Integration: Manages secure connections and integrates the custom UI directly into Epic Hyperspace, maintaining authentication and patient context. This scalable architecture, underpinned by Stanford's AXIOM framework, proved critical for performance. For instance, the system cut retrieval times by over 95% - from nearly two minutes to four seconds - for some AI workflows. This focus on low-latency data access is fundamental to clinical decision-making and the AXIOM initiative, which provides this breakthrough data capability, was recognized as an InterSystems Impact Award winner in 2025. Responsible AI deployment starts with organizational frameworks and strong governance models. ChatEHR is explicitly guided by Stanford Medicine's Responsible AI Lifecycle. Oversight is managed through the Data Science Executive Committee (DSEC), ensuring transparency and alignment throughout the project life cycle. Furthermore, all system operations adhere to HIPAA and HITECH standards, utilizing role-based access controls inherited directly from the EHR to limit data exposure. This structured approach ensures that AI deployment is treated not as a one-off technical build, but as a governed, enterprise-wide strategy. Crucial to maintaining trust and safety is developing approaches for evaluating LLM performance, a task made challenging by the flexibility and variability of generative AI outputs.ChatEHR implemented MedHELM (Medical Holistic Evaluation of Language Models), a generative AI evaluation framework developed in collaboration with the Stanford Center for Biomedical Informatics Research (BMIR) and the Institute for Human-Centered AI (HAI) By combining governance, an embedded platform for low-latency data access, and monitoring via the MedHELM framework, the ChatEHR initiative provides a replicable blueprint for health systems seeking to translate AI innovation into measurable clinical and operational impact while upholding standards of safety and responsibility. Nikesh Kotecha, Head of Data Science at Stanford Health Care, tasked with building a group to develop and deploy AI-guided models into clinical and operational workflows. Prior to that, Nikesh started and led the informatics efforts at the Parker Institute for Cancer Immunotherapy, a non-profit organization bringing together 7 top cancer centers Organization: Stanford Health Care Stanford Health Care's AXIOM initiative (Advance Extraction for Intelligent Orchestration and Medical Insight) is a transformative solution that enables fast access to complex electronic health record (EHR) data. Using a unique recursive data retrieval method, AXIOM minimizes duplication and reduces query times from minutes or hours to seconds. It leverages a FHIR (Fast Health Interoperability Resources) repository on InterSystems IRIS, to power advanced AI and large language model (LLM) applications. This architecture enables real-time clinical insights, enhances care team collaboration, and supports use cases such as augmented triage and optimized patient flow across a variety of care settings. Sponsored by InterSystems and selected by an independent panel of judges from Massachusetts Institute of Technology (MIT).
Stanford section chief of preventive cardiology to receive the 2025 Joseph A. Vita Award.
Stanford Health Care will host Modern Proton Radiation Oncology, featuring an exclusive tour of their new treatment room equipped with the MEVION S250-FIT system integrated with Leo Cancer Care's Marie solution.