AI Clinician Assistant

AI Ambient Scribes are companies that use AI to ambiently capture clinical encounters and generate notes and/or transcripts. Notably we do not include simple dictation tools or virtual/remote scribes here, but we do include platforms that integrate AI scribing with human oversight, where the human element typically acts as a verification layer before the clinical note reaches the physician-user for approval. AI Ambient Scribe core capabilities are to: - Ambiently capture both patient consultations and clinicians' dictation - Convert these audio recordings into written transcripts through speech-to-text technology - Synthesize a clinical note from the transcript by employing artificial intelligence, notably a large language model (LLM) specifically tuned for this application Additionally, Ambient Scribes are increasingly building additional capabilities, including prompts to address care gaps or coding suggestions.

AI Clinical Summary solutions use AI to ingest clinical information and generate a summarized output. There are a wide range of use cases for these solutions, including: pre-charting; referral intake; surfacing care and diagnosis gaps; quality measurement; curating real world evidence; clinical trial matching; clinical registry submissions; clinical documentation improvement; and medical record review for insurance and legal needs. There is overlap between this category and clinical decision support, care gap and contract performance analytics, patient intake, and clinical documentation improvement (CDI), as the generation of summaries is often paired with specific workflow-focused solutions.

The AI Inbox Management category focuses on solutions that automate and streamline the management of clinical inboxes within healthcare settings, reducing administrative burdens on providers and improving communication workflows. These tools integrate directly with EHR systems to process various types of patient communications, documents, and inquiries. By using AI to categorize and prioritize tasks—such as e-faxes, lab results, referrals, and patient messages—these platforms help clinicians efficiently manage their in-baskets and ensure timely responses to urgent needs. A key advantage of AI inbox management is its ability to reduce physician burnout by minimizing repetitive manual tasks and enabling faster triage of patient messages. These tools often include advanced features like sentiment analysis to assess patient satisfaction and context-aware response generation to help clinicians draft personalized messages. Automating the routing of messages and updates to patient charts also enhances care coordination and ensures that critical information is promptly addressed, contributing to better patient outcomes and more efficient healthcare operations.

The AI Surgical Clinical Decision Support category encompasses tools designed to enhance surgical procedures through advanced data analysis and real-time insights. These platforms integrate video monitoring and data streams from surgical tools, life support systems, and other instruments to provide surgeons and clinical teams with valuable feedback during procedures. By analyzing various data inputs, these tools can offer actionable insights that improve surgical precision, patient safety, and overall outcomes. They assist in real-time decision-making, allowing providers to make adjustments during operations based on up-to-the-minute data. A significant benefit of these systems is their potential to reduce variability in surgical practices and improve outcomes across a wide range of procedures. By providing clinical teams with AI-driven insights, they can better predict complications, identify optimal strategies, and ensure that surgical workflows align with best practices.

Clinical Decision Support (CDS) products offer real-time, patient-specific recommendations to improve decision-making across various clinical scenarios. These tools actively assist with differential diagnosis generation by analyzing patient data from the EHR or other sources and suggesting likely conditions based on symptoms, medical history, and lab results. CDS also aids medication management by calculating personalized drug dosages , checking for drug-drug interactions, and recommending alternatives. Embedded into workflows, CDS surfaces alerts, reminders, and diagnostic insights automatically, reducing cognitive load and minimizing errors. Its customizability allows providers to develop rules that align with their unique workflows, making it a flexible tool across care settings. Typical Capabilities of CDS Products: • Diagnostic Suggestions: Generate differential diagnoses based on patient data. • Medication Management: Provide alerts for drug-drug interactions, dosage recommendations, and cost-saving alternatives. • Drug Dosage Calculators: Adjust doses based on weight, age, renal function, or other clinical factors. • Clinical Reminders: Trigger alerts for preventive care, follow-ups, or critical care events. • Customizability: Enable providers to develop rules and alerts tailored to their workflows. • EHR Integration: Seamlessly embed into care workflows to deliver real-time, actionable insights. • Ad Hoc Decision Support: Assist with decisions at specific moments, across various clinical scenarios.

Clinical Pathways and Reference products provide evidence-based, structured guidance to manage specific diseases or conditions, with a focus on standardizing care and improving outcomes. While these products typically guide treatment after a diagnosis has been established , some may offer reference-based diagnostic tools for generating differential diagnoses. These tools allow physicians to input symptoms or clinical data and retrieve recommendations based on protocols or decision trees. However, unlike CDS, they are less integrated into real-time workflows and require the clinician to actively interact with the platform to extract insights. Pathways products are typically integrated into EHRs to ensure clinicians follow the recommended steps and monitor adherence to treatment protocols . Typical Capabilities of Clinical Pathways Products: • Evidence-Based Guidelines: Provide regularly updated protocols aligned with clinical research. • Condition-Specific Pathways: Include predefined pathways for managing diseases such as cancer or chronic illnesses. • Personalization: Tailor pathways based on individual patient demographics, comorbidities, and history. • Diagnostic Reference Tools: Offer decision trees or protocol-based support for exploring differential diagnoses. • EHR Integration: Ensure clinicians can access pathways directly within their workflow. • Real-Time Decision Support: Provide actionable recommendations during patient encounters. • Compliance Tracking: Generate reports to monitor adherence to guidelines and regulatory standards.

Smart EHR UI products sit on top of the EHR and other data sources, surfacing and summarizing workflow-specific, relevant information to clinicians, but also write back to the EHR in useful ways. They use AI and machine learning, in addition to NLP and advanced search capabilities, to deliver a more useful interface for specific workflows than the more fully-featured EHR beneath it.