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Best Ambient Intelligence Products

Best Ambient Intelligence Products

Technologies such unobtrusive sensors and devices embedded in the physical environment that continuously collect data and enable autonomous detection, prediction, intervention and other intelligent support. AmI systems are context-aware, adapting to changing needs, and offering real-time support like alerts or recommendations.

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Ambient Intelligence: Products


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AI to review all patient data, ensure diagnoses are not missed, and automating note-writing.

Regard uses proprietary algorithms to automatically diagnose and document conditions on behalf of inpatient providers. These automatically-generated notes save providers time, reduce coding queries, and have a dramatic impact to hospital finances.

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Andor Health was born over 4 years ago with a single mission; to fundamentally change the way in which care teams, patients, and families connect and collaborate. By harnessing the latest innovations in OpenAI/GPT models, our cloud-based platform unlocks data stored in source systems - such as electronic medical records - to deliver real-time actionable intelligence to care teams within ubiquitous virtual collaboration platforms like Zoom. By perfecting communication workflows, our platform accelerates time to treatment, decreases clinician burnout, and drives better patient outcomes.  

Healthcare institutions and providers use ThinkAndor® to enable providers to configure patient and clinician interactions with ubiquitous team collaboration platforms. This eliminates the need to manage added applications. ThinkAndor® enables a frictionless virtual interaction allowing physicians and patients to communicate without being distracted by disjointed technologies during a virtual consultation. 

ThinkAndor is the only integrated virtual collaboration platform that can truly bring together all aspects of outpatient, inpatient, post-acute and at home virtual care collaboration through the 5 Pillars of Virtual Health: Virtual Visits, Virtual Hospital, Virtual Patient Monitoring & Care Management, Virtual Team Collaboration, and Virtual Community Collaboration. 

Features include:

  • Virtual visits launched from the EHR
  • Voice-to-text clinical notes
  • Real-time alerts and notifications
  • Secure collaboration channels
  • ThinkAndor® AI Bot provides relevant content and clinical context to visits and care teams
  • Device-agnostic virtual rounding, nursing, sitting and remote consults to power the virtual hospital
  • Remote specialty consults such as Tele Stroke, Tele Psych, and Tele ICU
  • Access to a virtual on-demand network
  • Multi-room/patient virtual sitting for a variety of risk types
  • Virtual nursing to address staffing shortages

In 2020, Microsoft M12 took an investment position in Andor Health and works very closely to optimize virtual interactions leveraging OpenAI and GPT. Since then, Andor Health has grown to serve over 70,000 providers and over 500 hospitals leveraging the Andor Health platform across the US, Canada, and UK. Orlando Health, Medical University of South Carolina, Tampa General Hospital, Yale New Haven, and the National Institutes of Health are among some of the most notable. You may find some of our most prestigious partners here, https://andorhealth.com/partners.html. 

Most Importantly, Black Book has ranked Andor Health as the #1 Virtual Care Collaboration Solution with the Highest Client Satisfaction in 2023! Black Book Market Research used 18 key performance areas of operational excellence to rank Virtual Care Solutions vendors, and recognized Andor Health as the Highest in Client Satisfaction.  More importantly, Black Book reached out to nearly 1000 provider organizations, hospitals, and health systems to perform this independent market evaluation with Andor Health taking  #1 in 13/18 key performance indicators across all 5 pillars of virtual health & collaboration! This success is a proven indicator of Andor Health’s focus to empower clinicians and care teams with distinct, AI-powered virtual collaboration experiences. 

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Access & Scheduling
Intake & Virtual Waiting Room
Virtual Encounter
Diagnosis & Documentation
Billing, Orders, & Follow Up
Technical Support
Flexible Staffing
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The Clinician Journey with Avo Assistant:

  • Reviews Patient Chart: Clinician reviews the patient chart prior to encounter, receiving an automated chart snapshot and best next step summary in the EHR based on the patient records and institutional guidelines.
  • Records Patient Conversation: Clinician meets with the patient and records the conversation on mobile using Avo’s scribe technology, or using existing ambient software. 
  • Generates Documentation: Clinician goes back to workstation and in one-click auto-generates documentation in any format, thanks to easy prompting available behind-the-scenes in Avo Builder.
  • Submits Orders and Billing Codes: Clinician uses Avo Pathway to check protocol for admitting this patient and pends orders based on the latest evidence. Clinician submits note with MEAT criteria for accurate billing. 
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Contextual understanding
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Ease the burden on care teams with an AI-powered solution that provides virtual monitoring around the clock, in every room. The care.ai Platform continuously monitors for potential risks and notifies care teams before problems arise.


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Conveyor AI is the cure for "Documentitis" - inflammation caused by burdensome documentation requirements imposed by EMRs, billing systems, etc.

Here's how it works:

  1. See your patient - with Conveyor AI enabled on your iOS device, tap “Start Encounter.” You can conduct your exam without worrying about taking notes or updating the EMR.
  2. Conclude the visit - After completing your encounter, tap the “Generate” button in the Conveyor AI app. In under a minute, you’ll have a fully-customized write-up of your encounter. No typing necessary! Do you need specific sections or formatting in your notes? Conveyor AI offers customizable templates so that we generate exactly the information you need.
  3. Close your charts 80% faster - Conveyor AI types your completed note directly into the patient’s chart in your EMR. Need to add anything? Conveyor AI offers best-in-class medical dictation so that you can dictate wherever you want and whenever you need.

Start a Free Trial: https://mobius.md/ios

Discover more here: https://mobius.md/conveyor%20ai/

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DeepScribe’s AI scribe automates medical documentation for doctors. Powered by the largest clinical dataset in healthcare, DeepScribe ambiently captures patient visits as they happen and then writes complete, billable documentation directly within a clinician’s electronic health record system. From small private practices to large healthcare organizations, DeepScribe is helping clinicians of all kinds reduce burnout, improve patient care, and increase revenue.

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Caregility Cloud™ connects patients and care teams everywhere on a secure, versatile virtual care platform that brings remote care support and AI capabilities to the patient's bedside, from the hospital to the patient's home. Reduce operational costs while keeping clinical teams and patients more connected and engaged. Intelligent telehealth edge devices integrate with clinically designed care applications to offer one-on-one and one-to-many remote patient engagement and care team support. Seamlessly integrate with leading EHRs, Clinical Decision Support (CDS) tools, connected digital health devices, interpreter services, and interactive patient consoles to modernize care models. Native and integrated AI tools enhance the art of what's possible in remote clinical workflows. 

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Artisight redefines the possibilities of healthcare through its Smart Hospital Platform and solutions for virtual care, quality improvement, and care coordination. Anchored in deep clinical knowledge and industry-defining artificial intelligence, Artisight’s state-of-the-art computer vision and robust multi-sensor network adapts in real-time to specific environments and workflows, unlocking previously inaccessible data and ensuring seamless integration into your healthcare ecosystem.

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Through its comprehensive integration of diverse data sources - including EHR, RPM and patient-generated insights - the Medical Brain has a complete understanding of the patient’s medical history and knowledge of the current situation in real-time. With this complete, whole-person understanding, the Medical Brain proactively identifies emerging health risks, care gaps, delays, and errors. 

The Medical Brain is being used by provider groups, health systems, ACOs to help providers manage patients on their behalf so they can succeed with value-based care. Brain contacts providers and orchestrates care. This patient-first, real-time approach helps patients control chronic disease, reduce hospital days, while increasing provider productivity by 92% by eliminating patient communication and follow-up tasks from provider and office staff.  

The Medical Brain is being used by provider groups, health systems, ACOs to help providers manage patients on their behalf so they can succeed with value-based care.

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Bidirectional Communication
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Ambience Healthcare’s AI technology for scribing, coding, referrals, and patient summaries has been deployed at health systems such as UCSF Health, St. Luke’s Health System, John Muir Health, and Memorial Hermann Health System. Ambience is the only AI scribing and coding solution designed to support 100+ specialties and subspecialties, and is directly integrated with Epic, Cerner, athenahealth, and other leading EHRs. 

 

By partnering with Ambience, healthcare systems reduce documentation time by an average of 80%, improve clinical documentation integrity, and achieve at least a 5X return on investment with more accurate E&M coding. Ambience is also the only AI solution that provides clinicians with AI-assisted CDI support. Ambience surfaces precise diagnosis codes for clinicians to review based on patient conversations, then structures documentation to support selected codes. 

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AVIA Marketplace offers a product grid that is a comprehensive resource for health care buyers in their research journey. The grid showcases products from leading vendors and ranks them based on compatibility level and market presence. This approach ensures that the products listed are not only relevant to the buyer's needs but also established in the market. With AVIA Marketplace's product grid, health care buyers can make informed decisions and select products that meet their specific requirements.

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Buyer's Guide


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A Buyer's Guide to

Ambient Intelligence

What is Ambient Intelligence?
Technologies that include unobtrusive solutions, sensors, and devices embedded in the physical environment that continuously collect data and enable autonomous detection, prediction, intervention and other intelligent support. AmI systems are context-aware, adapting to changing needs, and offering real-time support like alerts or recommendations.

Ambient intelligence relies on a combination of technologies, including:

  • Internet of things (IoT): Connecting everyday objects to the internet to collect and exchange data.
  • Artificial intelligence (AI): Enabling devices to learn from interactions and improve over time.
  • Sensor networks: Using sensors to gather data about the environment and user activities.
  • Natural user interfaces: Allowing interaction through voice, gestures, and other non-intrusive methods.

Solution framework

Ambient observation and monitoring: Technologies that passively collect data from the surrounding environment to gather health-related insights without requiring active input from individuals.
Inpatient ambient monitoring:
Systems that passively track patient vital signs, movements, and health indicators in hospital settings using unobtrusive sensors and devices, requiring no direct intervention from patients or staff.

  • Vital sign monitoring: Continuous, non-invasive tracking of patients’ essential physiological measurements (e.g., heart rate, blood pressure, temperature) using ambient sensors and technologies.
  • Patient movement tracking: Systems that monitor and analyze patient mobility patterns within healthcare facilities to assess recovery progress, fall risk, and overall well-being.
At-home ambient monitoring:
Technologies that passively collect health data in patients’ homes through smart home devices and wearables, enabling continuous health monitoring without active participation from the user.

  • Smart living integration: The incorporation of health monitoring capabilities into everyday living environments, using interconnected IoT devices to create a comprehensive health-aware ecosystem.
  • Medication adherence monitoring: Systems that passively track and verify patient compliance with prescribed medication regimens using smart pill bottles or other ambient technologies.
  • Passive wearable tracking: Unobtrusive wearable devices that continuously collect health data without requiring user interaction, providing long-term insights into activity levels, sleep patterns, and physiological trends.
Ambient clinical intelligence: AI and machine learning algorithms that analyze current and historical patient data in real time, providing actionable clinical insights without requiring manual input or immediate analysis by healthcare professionals.
Clinical intelligence: Advanced data analytics tools that continuously generate insights, predict outcomes, and support clinical decision-making by processing ambient data streams without direct user intervention.
Ambient documentation: Technologies that capture and analyze conversations and activities in clinical settings to generate accurate medical records, eliminating or significantly reducing the need for manual documentation.
Ambient scribes: Systems that automatically transcribe, summarize, and structure clinical conversations and observations in real-time, without requiring active input from healthcare providers.
Ambient assistants: AI-driven tools that passively support various aspects of healthcare delivery, workflows, and management by providing proactive task assistance and contextual information.
Voice activated assistants: AI-powered systems that respond to voice commands in clinical settings, facilitating hands-free access to information and workflow support.
Workflow orchestration: Intelligent systems that autonomously manage and optimize clinical workflows, automatically assigning tasks, prioritizing activities, and coordinating resources based on real-time data and predefined protocols.
Audio and speech recognition: AI-powered systems that handle patient calls, appointments, and inquiries using natural language processing, providing seamless communication without human intervention while also assessing the quality of the call.
Ambient experience: Technologies that passively respond to human actions and needs, dynamically adjusting the physical and digital environment to optimize patient comfort and provider efficiency.
Intelligent environments: Integrated systems of sensors, displays, and interfaces that autonomously transform a physical space to adapt to user needs, preferences, and clinical requirements in real time.
Asset tracking and resource management: Systems that automatically monitor the location and status of medical equipment, personnel, and resources within a healthcare facility, optimizing utilization and workflow efficiency.
Gesture-based control systems: Technologies that allow healthcare professionals to interact with medical devices, information systems, and environmental controls using intuitive hand gestures, reducing the need for direct physical contact.

Ambient Intelligence in healthcare represents a paradigm shift in how we interact with our environment and deliver care. By enabling environments to be responsive, adaptive, and anticipatory, we can reduce the cognitive load on our clinicians and enhance patient experiences. The key is to implement these technologies thoughtfully, always keeping the human element at the center of our design and decision-making process.
Sonia Singh
— Sonia Singh
Chief Inights Officer at AVIA

The case for ambient intelligence

Healthcare systems are plagued with a myriad of problems that require a multitude of solutions to address concerns in patient safety, clinician burnout, efficiency, patient experience, and data management. Ambient intelligence (AmI) emerges as a transformative solution that offers health systems the potential to do more with less while reducing the need for fragmented solutions. By leveraging emerging technologies such as intelligent sensors and monitors, AmI enables healthcare providers to collect and analyze data more efficiently, reducing the burden on human resources. This capability allows for the augmentation of human decision-making with autonomous systems, leading to more informed and timely interventions. Additionally, by automating routine tasks and providing real-time, data-driven insights, AmI has the potential to significantly reduce clinician burnout, allowing healthcare professionals to focus on high-value patient interactions and complex decision-making processes. This overall approach not only enhances patient care and safety but also streamlines operations, potentially reducing costs and improving the overall healthcare experience for both patients and providers.
Patient safety and outcomes
One of the most pressing concerns in healthcare is patient safety and outcomes. Despite advances in medical knowledge and technology, preventable medical errors and hospital-acquired conditions continue to pose significant risks. Approximately 400,00 hospitalized patients experience some form of preventable harm each year, with more than 200,000 patient deaths occurring annually due to preventable medical errors. 1 Ambient intelligence addresses these challenges by introducing advanced monitoring systems that operate seamlessly in the background. These systems can continuously track patient vital signs, analyze patterns, and alert staff to potential issues before they become critical. By enabling proactive care, AmI has the potential to prevent complications, reduce hospital-acquired conditions, and ultimately improve patient outcomes.
Clinical experience
Clinician burnout has reached epidemic proportions, driven in large part by administrative burdens and documentation requirements that pull healthcare providers away from direct patient care. The constant need to input data into electronic health records, manage paperwork, and navigate complex workflows leaves clinicians feeling overwhelmed and dissatisfied. 2 Ambient intelligence offers a solution by automating many of these tasks. Through voice-activated assistants and natural language processing, AmI can capture and document clinical encounters automatically, freeing clinicians to focus on patient interactions. This shift not only reduces the administrative burden but also allows healthcare providers to practice at the top of their license, potentially improving job satisfaction and work-life balance.
Efficiency and cost management
Efficiency and cost management are perennial challenges for healthcare organizations. With tightening budgets and increasing demand for services, there’s a constant pressure to do more with less. 3 Workflows are often suboptimal, leading to wasted time and resources. Ambient intelligence addresses these issues by streamlining operations through intelligent workflow optimization. AmI systems can analyze patterns in patient flow, staff utilization, and resource allocation to suggest more efficient processes. For example, predictive staffing algorithms can forecast patient needs and ensure appropriate staffing levels, while smart resource allocation systems can optimize the distribution of medical equipment and supplies. These improvements can lead to reduced wait times, shorter lengths of stay, and significant cost savings.
Patient experience
Patient experience is another area where many healthcare systems struggle to meet rising expectations. Patients increasingly expect personalized, responsive care environments similar to what they experience in other service industries. 4 Traditional hospital rooms and care processes often fall short, feeling impersonal and outdated. Ambient intelligence transforms the patient experience by creating adaptive environments that respond to individual needs and preferences. Smart room systems can automatically adjust lighting, temperature, and entertainment options based on patient preferences. Moreover, AmI can facilitate better communication between patients, families, and care teams, providing easy access to relevant information and enhancing patient engagement in their own care.
Data management
Finally, healthcare organizations face challenges in leveraging the vast amounts of data they collect to drive meaningful improvements. Despite the wealth of information available, many struggle to turn this data into actionable insights. Although four out of five healthcare leaders believe most of their data is accurate, 47% of healthcare data, on average, is underutilized when making clinical and business decisions. 5 Ambient intelligence systems excel in this area, using advanced analytics and machine learning to process and interpret complex datasets in real time. This capability enables data-driven decision-making at both the individual patient level and for population health management. AmI can provide clinicians with contextual information at the point of care, support clinical research with rich, comprehensive datasets, and enhance quality improvement initiatives through detailed performance metrics.

Key attributes of ambient intelligence solutions

Effective ambient intelligence (AmI) solutions in healthcare share several critical attributes that enable them to seamlessly integrate into and enhance the care environment. When evaluating AmI solutions, healthcare organizations should look for the following key characteristics:

Context-awareness
  • Utilizes contextual and situational information from the environment
  • Understands the current usage scenario and provides appropriate responses
  • Integrates data from multiple sources to create a comprehensive view of the care situation
Example: An AmI system that adjusts alarm thresholds based on a patient’s current activity level and medical history.
Multisensory and multimodal intelligence
  • Processes and integrates data from multiple sources (e.g., microphones, cameras, sensors)
  • Has a comprehensive understanding of varying complex healthcare environments
  • Provides appropriate responses in various modalities (speech, text, visual outputs)
  • Enhances situational awareness and context-based decision making
Example: An AmI system in an ICU that combines audio, visual, and biosensor data to detect early signs of patient deterioration and alert staff through their preferred notification method.
Personalization
  • Tailors interactions and interventions to the needs of each individual
  • Learns from user preferences and behaviors over time
  • Adapts to different user roles (e.g., patients, nurses, physicians) and their specific needs
Example: A room environment system that automatically adjusts lighting, temperature, and entertainment options based on patient preferences and clinical requirements.
Anticipatory capabilities
  • Predicts user needs without requiring explicit input
  • Leverages historical data and patterns to forecast future events or requirements
  • Proactively offers suggestions or initiates actions to prevent issues
Example: A clinical decision support system that anticipates potential drug interactions based on a patient’s medication history and current condition.
Adaptability
  • Evolves and adjusts in response to changes in the environment or user behavior
  • Continuously learns from new data and experiences to improve performance
  • Flexibly accommodates different clinical scenarios and workflows
Example: An AI-driven scheduling and staffing system that sends certain clinicians based on changing patient acuity levels and staff availability.
Ubiquity and seamless integration
  • Embeds unobtrusively into everyday healthcare environments
  • Integrates with existing systems and workflows without disruption
  • Provides consistent experience across different devices and platforms
Example: Voice-activated clinical documentation that works across various areas of the hospital, from patient rooms to operating theaters.
Natural and intuitive interaction
  • Offers multimodal interaction methods (e.g., voice, gesture, touch)
  • Minimizes the learning curve for users through intuitive design
  • Reduces cognitive load by presenting information in easily digestible formats
Example: A gesture-controlled imaging system that allows surgeons to manipulate scans without breaking sterility.
Robust privacy and security
  • Ensures strong data protection and compliance with healthcare regulations
  • Provides granular access controls and audit trails
  • Maintains patient privacy while enabling necessary data sharing for care coordination
Example: An AmI system that only shares patient information with relevant care team members.
Scalability and interoperability
  • Scales effectively from individual rooms to entire healthcare systems
  • Interoperates seamlessly with other healthcare IT systems and devices
  • Supports open standards to facilitate integration and future expansion
Example: An ambient clinical documentation system that can be deployed across multiple hospitals and integrates with various EHR platforms.
Reliability and fault tolerance
  • Maintains functionality even in degraded network conditions
  • Provides fallback mechanisms to ensure critical functions remain available
  • Offers clear indicators of system status and any limitations
Example: A patient monitoring system that continues to function and store data locally during network outages, syncing once connectivity is restored.
Measurable impact
  • Provides clear metrics and analytics to demonstrate ROI and clinical impact
  • Offers tools for continuous quality improvement and performance optimization
  • Aligns with organizational goals and key performance indicators
Example: An AmI solution that tracks and reports on its impact on patient outcomes, clinician efficiency, and operational costs.

Organizing for success with ambient intelligence

To successfully implement ambient intelligence solutions, health systems must consider several key factors. By keeping these principles in mind, organizations can effectively tailor their ambient intelligence initiatives to meet the needs of providers, patients, and the organization as a whole.
  • Choose the right spaces, environments, and use cases.
    1. Carefully select provider populations and clinical areas, considering factors such as potential for impact and environmental readiness and capabilities to support an ambient use case.
    2. Prioritize use cases that offer the most significant benefits in terms of workflow improvement, efficiency and patient care.
  • Establish clear consent processes and patient education.
    1. Develop a consent process that balances efficiency with legal requirements. Options include:
      1. Verbal consent initiated by the provider, emphasizing efficiency and patient focus.
      2. Written consent, potentially with separate consent for data used to train the model.
      3. Embedding ambient clinical recording language in the universal consent process.
    2. Proactively educate patients on the positive outcomes of the solution, such as increased provider focus during visits.
  • Plan for data management and security.
    1. Establish policies for data retention, such as timed access to recordings and data post-capture.
    2. Ensure compliance with relevant federal and state specific privacy laws and regulations.
    3. Implement secure storage and access protocols for captured data and insights.
  • Define accountability and response protocols.
    1. Clearly delineate responsibilities for responding to signals and alerts generated by the ambient intelligence system.
    2. Establish protocols for managing false positives and autonomous alerts.
    3. Implement a system of checks and balances to ensure appropriate use and response to AI-generated insights.
  • Plan for workflow changes and staffing impacts.
    1. Analyze how ambient intelligence will alter existing workflows across different specialties and roles.
    2. Assess the impact on staffing needs and role definitions.
    3. Provide robust support during implementation, including “at-the-elbow” assistance from clinical training specialists.
  • Develop comprehensive training programs.
    1. Create tailored training programs for different user groups (e.g., physicians, nurses, administrative staff).
    2. Include training on system use, new workflows, and how to interpret and act on AI-generated insights.
    3. Offer ongoing education to keep staff updated on system capabilities and best practices.
  • Address legal considerations.
    1. Consult with legal experts to ensure compliance with relevant laws and regulations.
    2. Develop protocols for managing legal risks associated with false positives and autonomous alerts.
    3. Establish clear policies on data ownership, access, and use.
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