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Digital transformation essentials — Precision medicine

Precision medicine represents a transformative approach to healthcare delivery that tailors medical decisions, practices, and treatments to individual patients based on their genetic, environmental, and lifestyle factors. Digital solutions in this space integrate genomic analysis, clinical decision support, and advanced analytics to enable personalized care delivery at scale.

Digital precision medicine capabilities

Precision testing	Digital solutions for navigation, screening, risk assessment, test selection/ordering, and consent management that help identify the right patients for genetic testing. Example companies: Helix, Tempus
Precision analytics and insights	Platforms that enable data acquisition, results interpretation, de-identification/tokenization, risk stratification, and predictive risk algorithms. Example companies: SomaLogic, GenXys
Precision decision support	Clinical solutions that integrate genomic insights into EHR workflows through personalized treatment plans and order sets/protocols. Example companies: ActX, TabulaRasa
Precision virtual health	Solutions that facilitate results disclosure, care planning, and ongoing care management through virtual care delivery. Example companies: Genome Medical, WiserCare
Patient engagement	Comprehensive platforms for bidirectional clinical communication, care plan adherence, education, and digital therapeutics. Example companies: 2bPrecise, Syapse

The case for digital in precision medicine

Healthcare organizations face mounting pressure to improve patient outcomes while managing rising costs and operational complexity. Traditional one-size-fits-all approaches to care delivery are proving insufficient as our understanding of individual genetic, environmental, and lifestyle factors expands. While precision medicine offers the potential to transform care through personalization, health systems struggle to implement these capabilities at scale without robust digital solutions.

Transform clinical care delivery

Traditional population-based approaches to treatment result in significant variation in clinical outcomes due to unappreciated differences in disease drivers. Standard clinical guidelines miss up to 90% of patients with actionable genetic conditions.¹ Digital precision medicine platforms address this by enabling health systems to analyze individual patient genetics, environment, and lifestyle factors to deliver truly personalized care. Organizations implementing these solutions have achieved dramatic improvements in outcomes, including a 48% reduction in mortality rates for high-risk patients through early intervention and targeted therapies.²

Drive research and innovation

Healthcare organizations can create new value through precision medicine research and innovation. The total addressable market is projected to reach $141.70B by 2026, with opportunities ranging from clinical trial matching to biomarker development.³ Leading health systems are forming research collaborations that enable them to sequence hundreds of thousands of patients while creating new revenue streams. Population screening programs powered by digital tools have revealed that 90% of CDC Tier 1 genetic conditions were previously missed using standard guidelines, demonstrating the potential for discovery and impact at scale.⁴

Optimize provider workflows

Clinical staff productivity is significantly impacted by precision medicine complexity. With projected shortages of up to 124,000 primary and specialty care physicians by 2034, organizations need solutions that maximize existing expertise.⁵ Digital platforms have addressed providers’ workload by reducing clerical work by 75% when managing genetic testing data within the EHR.⁶ By automating routine tasks and providing point-of-care decision support, digital solutions can help organizations deliver precision medicine efficiently while improving provider satisfaction.

Sources

February 5, 2025

health system resources

Digital transformation essentials — Women’s health

Digital Women’s Health solutions encompass technological platforms and systems designed to help healthcare organizations deliver comprehensive, personalized care across a woman’s lifespan. These solutions are specialized to the woman’s experience and combine virtual care delivery, AI-enabled diagnostics, digital therapeutics, and analytics to enable more precise, accessible, and coordinated care while gathering valuable insights.

Digital women's health solutions

Navigational support	Digital solutions that identify care needs early and connect patients to the right women’s health resources efficiently through AI-powered navigation, risk identification, and provider matching systems. Example companies: Tia, Parsley Health
Planning and treatment	Clinical solutions that enable personalized care planning and delivery through evidence-based treatment protocols and clinical decision support tools. Example companies: Prosoma, Oleena, Kaiku
Ongoing monitoring and support	Comprehensive digital platforms that enable continuous engagement and monitoring through personalized education and support. Example companies: Lisa Health, Prosoma
Condition-focused care
Menopause management	Digital platforms specifically focused on supporting women through perimenopause and menopause with symptom tracking, treatment guidance, and specialized care. Example companies: Tia, Lisa Health
Oncology care	Solutions dedicated to cancer prevention, early detection, and comprehensive care support throughout the cancer journey. Example companies: Alis Health, Tia
Reproductive and maternal health	Platforms supporting women through fertility, pregnancy, and postpartum care with specialized monitoring and support. Example companies: Maven, Bloomlife
Chronic condition management	Solutions focused on conditions that disproportionately affect women or present differently in women, such as cardiovascular disease and autoimmune conditions. Example companies: Riva Health, tenacio

The case for digital in women's health

Women’s healthcare has evolved far beyond traditional boundaries of primary care, gynecological services, and pregnancy support. Today, it encompasses a comprehensive spectrum of needs throughout a woman’s lifetime – from reproductive health and fertility services to specialized care for perimenopause, menopause, oncology, mental health, and chronic condition management. Yet traditional healthcare models aren’t meeting these diverse needs, with health systems losing market share to direct-to-consumer companies and specialized women’s health providers. Digital solutions have emerged as a vital strategy for health systems to retain and better serve this crucial demographic, particularly during midlife years when healthcare needs are most complex and the opportunities for impact are greatest.

Address unmet healthcare needs

Traditional healthcare models are failing to meet women’s essential health needs, with serious implications for outcomes and access. Nearly half (45%) of women in the US have forgone preventive services, citing affordability and lack of provider recommendations as key barriers.¹ The provider knowledge gap compounds this problem with only 20% of OB/GYN residencies offering menopause training.² This is particularly concerning when considering that perimenopause and menopause affect more than 450 million women worldwide at any point in time, leading to increased risks of cardiovascular disease, neurological diseases, osteoporosis, and type 2 diabetes when left untreated.³ Digital solutions transform this experience by providing comprehensive care pathways, specialized virtual care teams, and continuous support throughout women’s health journeys.

Expand coordinated care delivery

The complexity of women’s health needs creates significant challenges for care coordination and management. With 54% of women aged 45-64 having multiple chronic conditions, fragmented care delivery leads to poor outcomes and increased costs.⁴ For example, women are more likely than men to die from an acute cardiovascular event, and on average, women are diagnosed with various diseases approximately 7 to 10 years later than men.⁵ Digital solutions address these challenges through integrated platforms that connect primary care, specialists, and ancillary services while enabling early detection and intervention. The market opportunity is substantial–for example, the market potential for interventions addressing menopause symptoms alone ranges from $120 billion to $350 billion globally.⁶

Drive system transformation

Healthcare facilities must evolve to meet the growing demand for comprehensive women’s health services while addressing significant operational and accessibility challenges. Traditional care settings and schedules often don’t align with women’s needs and preferences; data shows that 29% of women report feeling dismissed by their doctor during their most recent healthcare experience (Forbes), and about 20% of U.S. women do not routinely see a primary care physician.⁷ As a result, leading health systems are choosing to partner with these digital women’s health solutions to transform care delivery and expand their reach. For example, some health systems are partnering with women’s health platforms to extend their ambulatory footprint and create new front doors for care. These partnerships are showing impressive results citing that 83% of their patients are up-to-date on cervical cancer screenings (2.5x the national average) and 88% are screened for depression (nearly double the national benchmark).⁸ Through strategic implementation and partnership with digital women’s health solutions, healthcare organizations can expand access points, improve operational efficiency, and maintain strong patient relationships while delivering better health outcomes.

February 5, 2025

health system resources

Digital transformation essentials — Referral management

Referral Management solutions encompass technological platforms and systems designed to help healthcare organizations optimize the coordination and tracking of patient referrals across their networks. These solutions combine provider directories, scheduling capabilities, analytics, and communication tools to enable seamless referral workflows while gathering valuable operational insights and reducing network leakage.

Key digital capabilities in referral management

Referral operations	Delivers solutions for optimizing referral operations and business performance. Closed-loop referrals: Bidirectional and automated (where appropriate) communication of patient referral status and clinical information between the referring and receiving provider Decision support tools: Tools that expedite and inform the patient’s referral process, including insurance eligibility verification, service price, etc. Example companies: AgileMD, EvidenceCare, ReferralMD, Luma Health
Patient access and experience	Empowers healthcare organizations to guide patients to the right specialists while maximizing network utilization and efficiency. Provider directory: Ability to ingest and maintain up-to-date provider information (e.g., affiliation, skills) in a single, up-to-date directory Provider search and schedule: Ability for patients and providers to search and (direct and/or point-of-care) schedule with providers based on preference, provider skill, and other factors Patient engagement tools: Tools that enhance stickiness and reduce no-shows, including self-scheduling, appointment reminders, and educational materials Example companies: Phreesia, MDInsider, Luma Health
E-consults	Specialized platforms enabling provider-to-provider consultation and clinical decision support E-consults: Ability for referring providers to conduct secure online consults with specialists and other receiving providers Example companies: AristaMD, Caregility, RubiconMD
Marketing and analytics	Enables healthcare organizations to build lasting referral relationships and gain actionable insights that drive growth and optimize network performance Customer relationship management (CRM): Built-in CRM platform enabling marketing and patient outreach campaigns, paired with in-depth market analytics Analytics: Sophisticated communication and referral analytics, including but not limited to leakage rates, opt-in rates, and no-show rates Example companies: Arcadia, Innovaccer, Welltok

The case for referral management solutions

Healthcare organizations today face a critical challenge: efficiently coordinating patient care across increasingly complex provider networks while managing operational efficiency and care quality. As healthcare delivery becomes more distributed and specialized, traditional referral methods like fax and phone calls are no longer sufficient to meet modern needs. Digital referral management solutions have emerged as a transformative technology, offering not just referral coordination, but a pathway to improved network utilization, enhanced patient experience, and data-driven network optimization.

Reduce network leakage and optimize revenue

Provider network leakage represents a significant challenge to healthcare organizations’ financial health and patient care continuity. Up to 60% of referrals received never turn into scheduled appointments.¹ Additionally, studies show that 61% of patients would switch providers if scheduling were more convenient.² The financial impact is substantial–health systems lose 55-65% of referrals to out-of-network providers, which are about $821,000-$921,000 per physician.³ Digital referral management transforms this dynamic by providing intelligent provider matching, streamlined scheduling, and referral tracking capabilities. Organizations implementing these solutions have significant improvements in referral completion rates. Some organizations report up to 92% appointment follow-through rates demonstrating the technology’s impact on schedule adherence (AVIA Analysis).

Enhance care coordination and clinical outcomes

Poor referral coordination directly impacts patient care quality and outcomes. While 70% of referring providers report sending patient history and reason for referral, less than 35% of specialists report receiving that information.⁴ This communication gap leads to significant challenges – 20-30% of diagnosis errors are caused by breakdowns in the referral process.⁵ Digital referral management addresses these challenges through structured communication and information sharing. Organizations implementing comprehensive referral solutions have reported 90% reductions in incomplete referral information and significant improvements in care team communication (AVIA Analysis).

Improve operational efficiency and provider satisfaction

Healthcare facilities face significant administrative burdens from manual referral management processes. Referral coordinators and clinical staff spend considerable time managing referrals through fragmented channels like fax, phone, and email. Referral teams spend 15% of their time processing each referral manually, with complex cases taking significantly longer (AVIA Analysis). Manual processes also lead to high error rates with about 8% of neurology referrals being clinically inappropriate and over 50% of referrals being non-surgical when sent to surgical specialists, creating unnecessary work for both referring and receiving providers.⁶ Digital referral management solutions streamline these workflows through automation and standardization. Organizations implementing these solutions have reported up to a 50% improvement in administrative time spent processing referrals and a 76.9% increase in staff efficiency (AVIA Analysis). Beyond time savings, these solutions provide administrative teams with better visibility into referral status, automated insurance verification, and integrated prior authorization workflows. This results in a more efficient operation where staff can focus on high-value activities rather than manual coordination while maintaining better control over the entire referral lifecycle.

Sources

January 31, 2025

health system resources

Digital transformation essentials — Chronic disease management

Digital Chronic Disease Management solutions encompass integrated technological platforms and interventions designed to help healthcare organizations systematically monitor, treat, and support patients with long-term conditions such as diabetes, heart disease, and COPD. These solutions typically combine remote patient monitoring, data analytics, patient engagement tools, and care coordination features to enable proactive, continuous care management outside traditional clinical settings.

Chronic disease management — Key digital capabilities

Decision enablement and clinical intelligence	Empowers healthcare organizations to make data-driven decisions through advanced analytics, evidence-based protocols, and actionable insights that improve clinical outcomes. Advanced analytics and risk management: Combines predictive modeling and risk stratification to identify high-risk patients and anticipate complications, enabling proactive intervention and resource allocation Care protocol optimization: Provides evidence-based clinical decision support with automated care gap analysis to ensure consistent delivery of guideline-based care across patient populations Clinical insights: Delivers comprehensive reporting and analytics on patient outcomes, quality measures, and program performance to drive continuous improvement Example companies: Innovaccer, Clarify Health
Connected care delivery	Extends care beyond traditional settings through integrated virtual care and remote monitoring capabilities that enable continuous patient oversight and timely intervention. Remote monitoring and alert management: Enables continuous patient monitoring through connected devices and biometric data collection, with configurable alerts to identify clinical deterioration early Virtual care integration: Combines telehealth capabilities with condition-specific assessment tools to extend care delivery beyond traditional settings while maintaining clinical quality Care transition management: Facilitates smooth transitions across care settings through automated workflows and communication protocols Example companies: Vivify Health, WellSky
Patient experience and engagement	Creates a comprehensive support system that empowers patients to actively participate in their care through personalized education, adherence tools, and seamless communication channels. Personalized support and education: Delivers targeted educational content and self-management tools based on patient condition, engagement level, and preferences Adherence management: Combines medication reminders, appointment scheduling, and adherence tracking with behavioral interventions to improve treatment compliance Connected communication: Enables secure messaging between patients, families, and care teams while facilitating caregiver involvement in the care journey Example companies: WebMD Ignite, Medisafe
Care team enablement	Streamlines clinical workflows and care coordination to maximize team efficiency while ensuring comprehensive documentation and appropriate reimbursement capture. Workflow automation: Streamlines clinical tasks through automated prioritization, documentation support, and care plan management to reduce administrative burden Care coordination tools: Facilitates collaboration across care team members through shared care plans, task management, and communication platforms Revenue cycle support: Automates tracking and documentation for chronic care management billing while ensuring compliance with reimbursement requirements Example companies: Notable, ThoroughCare

The case for digital in chronic disease management

Healthcare systems face mounting challenges in effectively managing their chronic disease populations, who account for 81% of hospital admissions, 91% of all prescriptions filled, and 76% of physician visits in the United States.¹ These high-utilizing patients create significant operational and clinical burdens for health systems, with chronic disease care consuming approximately 90% of the $4.5 trillion in annual medical costs.² Traditional care models struggle to provide the continuous monitoring and the personalized support these patients require, leading to preventable hospitalizations and strain on clinical resources.

Enabling continuous disease monitoring

Traditional episodic care models leave significant gaps between visits, making it difficult for health systems to detect and prevent patient deterioration. With 80% of serious medical errors involving miscommunication during care transitions, hospitals need more robust monitoring systems and patient touchpoints.³ Digital CDM solutions transform this paradigm by implementing continuous remote monitoring systems that track disease markers, symptoms, and medication adherence. Early detection and intervention capabilities have shown to reduce hospital readmissions among chronic disease patients.⁴ It is projected that systems deploying comprehensive CDM platforms can see upwards of $16,750 in savings for each hospitalization avoided.⁵ Organizations implementing comprehensive remote monitoring through digital CDM have also reported significant improvements in key clinical indicators for reduction in disease-relation hospitalizations.⁶

Optimizing clinical resource utilization

Healthcare providers face mounting pressures in chronic disease management, with more patients having at least one or multiple chronic conditions and chronic disease patients requiring more provider time than those with fewer to no chronic conditions, thus health systems need solutions that improve clinical workflow efficiency.⁷ Digital CDM solutions address this through automated documentation, streamlined workflows, and intelligent task prioritization. Healthcare organizations implementing comprehensive digital CDM solutions can leverage intelligent analytics to enhance resource allocation and clinical workflow efficiency, enabling care teams to effectively manage larger patient panels while maintaining high-quality care delivery through data-driven prioritization and automated care management tools.⁸

Driving revenue and risk management

Healthcare systems face significant financial pressures in chronic disease management, with over 2,000 hospitals receiving readmission penalties under the Hospital Readmission Reduction Program (HRRP), totaling $2 billion in penalties.⁹ These penalties particularly impact hospitals serving complex chronic disease populations, who are more likely to be readmitted within 30 days of discharge.¹⁰ Additionally, health systems struggle to comply with Chronic Care Management (CCM) billing code requirements that capture available chronic care management reimbursement, resulting in incomplete payments for the services they have provided.¹¹ Digital CDM solutions address these challenges through comprehensive monitoring and engagement to improve patient outcomes and meet reimbursement requirements. Organizations using these platforms report the opportunity to generate an additional $150,000-352,500 in direct revenue annually while preventing potential readmissions through early intervention.¹²

Sources

January 31, 2025

health system resources

Digital transformation essentials — Wayfinding

Digital Wayfinding solutions encompass technological platforms and systems designed to help healthcare organizations optimize navigation experiences for patients, visitors, and staff across their facilities. These solutions combine mobile applications, digital signage, indoor positioning systems, and analytics to enable intuitive navigation while gathering valuable operational insights.

Digital wayfinding solutions

User navigation	Provide patients, visitors, and staff with clear and simple resources to physically navigate a health system’s campus. Example companies: Phunware, Eyedog
Patient flow optimization	Track patients and visitors on the health system’s campus to optimize hospital operations. Example companies: Intelligent Locations, Sonitor

The case for digital in wayfinding

Healthcare organizations today face a critical challenge: helping patients and visitors navigate increasingly complex medical facilities while managing operational efficiency and patient satisfaction. As healthcare campuses expand and services become more distributed, traditional wayfinding methods like static signs and paper maps are no longer sufficient to meet modern needs. Digital wayfinding solutions have emerged as a transformative technology, offering not just navigation assistance, but a pathway to improved operational efficiency, enhanced patient experience, and data-driven facility management.

Empower patients to confidently navigate the facility

Patient confusion and anxiety in healthcare facilities represent a significant challenge to care delivery and satisfaction. Nearly a third of first-time visitors feel lost and confused during their first visit to a healthcare facility, and 85% of patients ask for directions when they go to a hospital.¹ This confusion creates stress for patients who are often already anxious about their medical visits. Digital wayfinding transforms this experience by providing turn-by-turn navigation and pre-visit planning capabilities. Temple University Health System’s implementation of these solutions generated over 8,800 app downloads and 88,000 user sessions in the first year, with 74% of users returning to the app.² The technology provides patients with the tools to navigate complex facilities confidently, reducing anxiety and improving their overall experience with the facility.

Avoid missed appointments and optimize scheduling

Navigational challenges directly contribute to missed and late appointments, creating disruptions in care delivery and revenue loss. When patients struggle to find their destination, appointment schedules suffer, creating a ripple effect throughout the day’s operations. Digital wayfinding addresses this challenge by providing real-time navigation and proactive guidance. Organizations implementing these solutions have seen up to an 80% decrease in wayfinding-related questions and significant improvements in patient punctuality.³ Froedtert & Medical College of Wisconsin’s wayfinding app sees 125 daily uses, helping ensure patients arrive at their appointments on time and prepared.⁴ Some organizations report up to 22% appointment conversion rates through their mobile apps (AVIA Analysis), demonstrating the technology’s impact on schedule adherence.

Reduce staff burden

Healthcare facilities face a significant operational burden from navigation assistance, with patients and visitors depending on staff for directions. An estimated 15% of nursing and employee work time is spent answering route and directional questions from hospital users, taking valuable time away from clinical care.⁵ Digital wayfinding solutions free staff from these interruptions while providing better service to patients. Digital signage can also utilize real-time facility utilization metrics to improve queue management and reduce perceived wait times by 35%, making it so patients do not have to tap into clinical staff for assistance.⁶ The result is a more efficient operation where staff can focus on patient care rather than providing directions, while patients receive consistent, accurate navigation assistance whenever they need it.

Sources

January 31, 2025

health system resources

Digital transformation essentials — Population health

Digital population health solutions represent an integrated ecosystem of technologies designed to proactively manage the health outcomes of specific populations through data-driven insights, automated engagement, and coordinated care delivery. This framework encompasses key components that enable health systems to deliver preventive care, manage chronic conditions, and improve overall health outcomes.

Population health framework

Population intelligence and decision enablement	Solutions that provide data-driven insights and predictive capabilities to identify risks and prioritize interventions Data integration and analytics: Aggregates clinical, claims, and SDOH data to create comprehensive patient profiles and identify trends across populations Risk stratification and scoring: Uses advanced algorithms to segment populations by risk level and predict future health events or complications Care gap analysis: Identifies missing preventive services, screenings, and interventions across patient populations to drive proactive outreach Quality performance tracking: Measures and monitors clinical quality metrics, cost metrics, and outcome measures to support value-based care initiatives Example Companies: Innovaccer, Arcadia, Health Catalyst
Care journey orchestration	Platforms that coordinate and optimize the delivery of care across teams and settings Care planning and protocols: Creates and manages evidence-based care plans tailored to patient conditions and risk factors Team collaboration: Enables seamless communication and task management across care teams, including primary care, specialists, and community partners Referral management: Coordinates patient transitions between providers and care settings while tracking completion and outcomes Social care integration: Screens for social needs and connects patients with community resources through closed-loop referrals Example companies: ZeOmega, TigerConnect, ReferralMD
Patient activation and outreach management	Tools that drive patient engagement and behavior change through personalized communications and interventions Multi-channel engagement: Delivers targeted communications through text, email, phone, and apps based on patient preferences and needs Automated care gap closure: Proactively reaches out to patients for preventive services and follow-up care using automated workflows Digital self-service: Enables patients to schedule appointments, access health information, and complete pre-visit tasks through digital tools Education and self-management: Provides condition-specific education and tools to support patient self-management of health conditions Example companies: Luma Health, Notable Health, Welldoc
Virtual care and remote monitoring	Solutions that extend care delivery beyond traditional settings through technology Biometric monitoring: Collects and analyzes patient vital signs and symptoms through connected devices to enable early intervention Virtual visit solutions: Facilitates secure video visits and messaging between patients and care teams for routine and urgent care needs Ongoing clinical surveillance: Monitors patient data in real-time to identify deterioration and trigger appropriate interventions Condition management: Supports ongoing management of chronic conditions through remote monitoring and virtual check-ins Example companies: Datos Health, Teladoc, Omada Health
Healthcare navigation and support	Solutions that provide personalized guidance and advocacy to help members navigate their healthcare journey effectively Care navigation and advocacy: Guides patients through clinical decision-making and benefits optimization with personalized support and recommendations Benefits education and utilization: Helps patients understand and maximize their healthcare benefits while optimizing costs Provider matching and scheduling: Connects members with appropriate providers based on quality, cost, and accessibility factors Complex care support: Provides enhanced support for members managing complex conditions or treatment decisions Example companies: Cedar Gate Technologies, Included Health

The case for digital in population health

Healthcare systems today face numerous critical challenges that digital population health solutions are uniquely positioned to address. The rising burden of chronic diseases accounts for a significant portion of healthcare spending, while an aging population increasingly strains healthcare resources. These demographic shifts, combined with persistent health disparities among vulnerable populations, create a complex landscape that traditional care delivery models struggle to navigate effectively.

Facilitating holistic connected care

Healthcare organizations today struggle with tracking and managing patients across different care settings, with limited visibility into patient care outside their immediate system. This fragmentation leads to poor outcomes, increased costs, and frustrated patients and providers alike.¹

Digital population health management platforms have revolutionized this landscape by providing unified patient views and automated workflows, allowing providers and their systems a holistic view of the patient at all times even after they have left the walls of the facility. Organizations implementing these comprehensive solutions have witnessed remarkable improvements, with reducing hospital readmissions and improving post-discharge outcomes.²

Data driven decision making

The shift toward value-based care has intensified the pressure on health systems to simultaneously reduce costs and improve outcomes. Particularly, organizations face the complex challenge of managing chronic diseases–which account for 90% of the nation’s $4.5 T in annual healthcare expenditure–while meeting increasingly stringent quality requirements and performance metrics.³ Traditional approaches to cost control often fall short, lacking the predictive capabilities and automated systems needed for effective population-wide management. Digital PHM solutions have emerged as a powerful answer to these challenges through predictive analytics that identify high-risk patients before costly events occur, combined with automated quality measure tracking and sophisticated cost analytics. Remote monitoring capabilities and personalized interventions provide proactive strategies that prevent expensive complications and hospital admissions. These digital innovations have transformed the economics of care management, with organizations significantly reducing the total cost of care while simultaneously improving quality measure performance.⁴

Improving access and equity

Healthcare systems have long struggled with profound disparities in care access and delivery, particularly among vulnerable populations. Geographic isolation in rural communities creates barriers to regular care access, while urban underserved populations face challenges with transportation, work schedules, and healthcare literacy. Traditional healthcare models have failed to address these systemic barriers, resulting in delayed care, poor chronic disease management, and worse health outcomes for these populations.⁵ The cost of traveling to appointments, taking time off work, and navigating complex healthcare systems has historically placed quality healthcare out of reach for many communities, perpetuating cycles of health inequality.

Digital health solutions have transformed this landscape by fundamentally reimagining how care can be delivered and accessed. By leveraging telehealth services, culturally appropriate resources, and remote monitoring capabilities, these platforms have eliminated many traditional barriers to care. Virtual visits reduce transportation burdens and lost work time, while multilingual digital resources and culturally tailored education materials make healthcare more accessible and relevant to diverse populations. Mobile health applications and remote monitoring tools bring healthcare directly into patients’ homes, enabling consistent care management regardless of location or socioeconomic status. Organizations implementing these solutions have witnessed dramatic improvements in care delivery and access.⁶ The digital transformation has particularly benefited traditionally underserved communities, with studies showing significant improvements in chronic disease management and preventive care compliance among vulnerable populations.⁷

Elevating patient engagement and empowerment

Traditional healthcare models have long suffered from a fundamental disconnect between periodic clinical visits and ongoing health management. Patients often struggle with understanding and following complex treatment plans, leading to poor medication adherence and suboptimal self-management of chronic conditions.⁸ The limited touchpoints between healthcare visits create gaps in care continuity, while insufficient education and support leave patients feeling overwhelmed and disconnected from their healthcare journey. These challenges are compounded by communication barriers, lack of timely feedback, and difficulty in accessing healthcare resources between scheduled appointments.

Digital population health platforms have revolutionized this paradigm by creating a continuous, interactive healthcare experience. These solutions deploy comprehensive engagement tools that maintain ongoing connections between patients and care teams through multiple channels. Automated education systems deliver personalized health information at the right time and in the right format, while smart reminders and monitoring tools help patients stay on track with their care plans. Interactive platforms enable patients to ask questions, report symptoms, and receive guidance in real-time, creating a more responsive and supportive healthcare environment. The integration of mobile apps, wearable devices, and remote monitoring capabilities provides patients with immediate feedback on their health status and behaviors, fostering greater engagement and accountability in their health management. These innovations have yielded impressive results, with organizations reporting significant improvements in patient engagement and care compliance, resulting in earlier detection, better clinical outcomes, and reduced complications.⁹

Sources

January 28, 2025

health system resources

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 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, 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.

Sources:

Visit AVIA Marketplace ahead of your next purchasing decision for unbiased third-party information, ratings, and reviews for hundreds of the leading digital health companies and solutions.

October 21, 2024

health system resources

A buyer’s guide to revenue cycle management (RCM)

What is digital in revenue cycle management?

Digital RCM solutions are software platforms and technologies that automate and optimize the healthcare revenue cycle. These tools leverage advanced algorithms, artificial intelligence, and data analytics to streamline financial processes, improve efficiency, reduce errors, and provide actionable insights.

Solution framework

Front-end
Credentialing	Systems that verify and assess the qualifications, experience, and professional background of healthcare providers to ensure they meet the standards required to practice within a specific healthcare organization or network.
Insurance eligibility verification and prior authorization	Systems that confirm a patient’s insurance coverage, benefits, and obtain approval from the insurance provider for specific medical procedures or treatments before they are performed.
Price transparency and cost estimation	Systems that provide clear, accessible information about the costs of healthcare services to patients, including estimated out-of-pocket expenses, and facilitating various payment options to improve financial clarity and patient satisfaction.

*Scheduling and Pre-Registration are crucial parts of the Front-End Revenue Cycle process. Please see our Digital Front Door categories for companies in the Scheduling and Pre-Registration space.

Mid-cycle
Clinical documentation integrity	Systems that ensure patient medical records are accurate, complete, and properly reflect the patient’s condition, treatments, and outcomes to support quality care, appropriate reimbursement, and regulatory compliance.
Medical coding	Systems that translate medical diagnoses, procedures, and equipment into universal alphanumeric codes based on standardized coding systems (e.g., ICD-10, CPT) for accurate billing and reporting.

Back-end
Claims management	Systems that prepare, submit, track, and resolve healthcare claims with insurance payers to ensure timely and accurate reimbursement for services provided.
Denials and appeals management	Systems that identify, analyze, and address denied claims, including the process of appealing incorrect denials to maximize reimbursement and improve future claim submission accuracy.
Patient billing and payment collection	Systems that generate accurate patient bills, communicate financial responsibilities, offer payment options, and collect payments for healthcare services rendered.
Revenue cycle analytics and intelligence	Systems that use data analysis tools and techniques to gain insights into the revenue cycle performance, identify trends, predict outcomes, and make data-driven decisions to optimize financial performance and operational efficiency.

Transforming revenue cycle management (RCM) through digital innovation is no longer just a back-office necessity; it’s a strategic imperative for healthcare organizations. By leveraging advanced RCM solutions, organizations can not only reduce administrative burdens and improve cash flow but also elevate the patient financial experience. A seamless, data-driven revenue cycle empowers healthcare providers to reinvest in their mission, delivering higher-quality care, expanding access, and driving sustainable growth in an increasingly complex environment.

— Beth Konczakowski, Director of Strategic Advisory Services

The case for digital in revenue cycle management

Healthcare systems today face numerous challenges that impact their financial stability and operational efficiency through increasing complexity of reimbursement models, rising costs, and growing patient financial responsibility. In this landscape, digital solutions for revenue cycle management have the potential to address these issues and optimize healthcare financial operations.

Key drivers for digital in RCM

Financial performance

One of the most pressing concerns in healthcare is maintaining financial stability while delivering high-quality care. Many healthcare organizations struggle with narrow margins and financial pressures with the average operating margin for hospitals performing at a loss of 13.5% in 2022.¹ Effective RCM addresses this challenge by streamlining revenue capture, reducing claim denials, and accelerating cash flow. By implementing robust RCM solutions, healthcare organizations can improve their financial performance, ensure proper reimbursement for services rendered, and maintain the resources necessary to provide excellent patient care.

Administrative burden

Administrative costs in healthcare have reached unsustainable levels, accounting for 15-25% of total healthcare spending in the United States.² Much of the administrative load falls on clinical staff, contributing to burnout and job dissatisfaction. RCM solutions offer a way to alleviate this burden by automating many administrative tasks related to billing, coding, and claims processing. Through intelligent automation and workflow optimization, RCM not only improves operational efficiency but also has the potential to enhance job satisfaction and retention among healthcare professionals.

Patient financial experience

As patient financial responsibility continues to grow, with out-of-pocket costs rising exponentially year-over-year, healthcare organizations face increasing pressure to provide a transparent and consumer-friendly financial experience.³ Traditional billing practices often lead to confusion, frustration, and ultimately, lower collection rates. RCM solutions address this by offering patient-centric billing options, unified billing, clear cost estimates, and flexible payment plans. By improving the patient’s financial journey, healthcare organizations can increase patient satisfaction, boost collection rates, and build long-term patient loyalty.

Regulatory compliance

Healthcare organizations operate in a highly regulated environment, with complex rules governing billing, coding, and reimbursement. Non-compliance can result in significant financial penalties and reputational damage. The total cost for non-compliance is currently deemed greater than $14M.⁴ RCM solutions help organizations navigate this regulatory landscape by embedding compliance checks into workflows, automating documentation for audits, and staying up-to-date with changing regulations. This proactive approach to compliance not only reduces risk but also improves the accuracy and efficiency of the revenue cycle.

Key attributes of revenue cycle management solutions

Effective Revenue Cycle Management solutions share several critical attributes that enable them to optimize financial performance and enhance operational efficiency. When evaluating RCM solutions, healthcare organizations should look for the following key characteristics:

End-to-end coverage	• Manages the entire revenue cycle from patient scheduling to final payment • Complements existing practice management systems to streamline financial operations • Provides a unified platform for all revenue cycle functions Example: An RCM ecosystem that handles scheduling, eligibility verification, coding, billing, and collections within a single integrated platform.
Intelligent automation	• Utilizes AI and machine learning to automate routine tasks • Employs robotic process automation (RPA) for repetitive, rule-based processes • Reduces manual data entry and associated errors Example: An RCM solution that automatically codes encounters based on clinical documentation and updates claims in real-time.
Advanced analytics and reporting	• Offers real-time financial dashboards and key performance indicators • Provides predictive analytics for denials management and cash flow forecasting • Enables drill-down capabilities for detailed analysis of revenue cycle performance Example: A system that predicts which claims are likely to be denied and suggests preemptive actions to prevent denials.
Patient-centric financial experience	• Offers clear, upfront cost estimates and explanations of benefits • Provides multiple payment options and flexible payment plans • Enables self-service portals for patients to manage their accounts Example: A patient portal that allows individuals to view their bills, set up payment plans, and make payments online or via mobile app.
Compliance and security	• Ensures adherence to healthcare regulations (e.g., HIPAA, HITECH) • Provides robust data security measures to protect sensitive financial information • Offers audit trails and reporting for compliance monitoring Example: An RCM system with built-in compliance checks that flag potential regulatory issues before claims are submitted.
Real-time eligibility and benefits verification	• Performs instant insurance eligibility checks • Provides detailed breakdowns of patient benefits and coverage • Updates patient financial responsibility in real-time Example: An RCM tool that automatically verifies insurance coverage when appointments are scheduled and updates information at check-in.
Denial management and prevention	• Identifies root causes of denials through pattern analysis • Offers workflow tools for efficient denial follow-up and appeals • Provides education and training to prevent future denials Example: A denial management module that categorizes denials, assigns them to appropriate staff, and tracks appeal outcomes.
Continuous performance improvement	• Benchmarks performance against industry standards • Identifies areas for process improvement and cost reduction • Provides ongoing training and support for optimal system utilization Example: An RCM system that compares an organization’s key metrics to peer benchmarks and suggests improvement strategies.

Organizing for success with revenue cycle management

To successfully implement Revenue Cycle Management solutions, health systems must consider several key factors. By keeping these principles in mind, organizations can effectively optimize their revenue cycle operations and achieve financial goals.

Conduct a comprehensive revenue cycle assessment
1. Analyze current performance metrics across all stages of the revenue cycle
2. Identify pain points, inefficiencies, and opportunities for improvement
3. Benchmark performance against industry standards and best practices
Optimize existing technology and processes
1. Assess current RCM technology for underutilized features and potential upgrades
2. Identify and address user issues regarding existing systems
3. Explore opportunities for automation and improvement within existing systems to maximize efficiency with current and new technologies
Invest in staff training and change management
1. Provide comprehensive training on new RCM systems and processes
2. Educate all staff on the importance of accurate documentation and coding
3. Offer ongoing education to keep staff updated on best practices and regulatory changes
4. Encourage open communication about revenue cycle challenges and solutions
5. Recognize and reward staff contributions to revenue cycle improvement
Establish key performance indicators (KPIs) and monitoring processes for continuous improvement
1. Define clear, measurable KPIs for each stage of the revenue cycle
2. Use analytics tools to identify trends, patterns, and opportunities for improvement
3. Implement data-driven decision-making processes across the revenue cycle
4. Regularly review and act on insights generated from RCM analytics
Optimize front-end processes
1. Implement robust patient registration and eligibility verification processes
2. Develop clear financial counseling protocols for patients
3. Establish processes for accurate charge capture and coding at the point of service
Stay current with regulatory changes and industry trends
1. Establish processes for monitoring and implementing regulatory updates
2. Participate in industry associations and conferences to stay informed of best practices
3. Regularly evaluate new technologies and solutions that could enhance RCM performance

Sources:

Visit AVIA Marketplace ahead of your next purchasing decision for unbiased third-party information, ratings, and reviews for hundreds of the leading digital health companies and solutions.

October 17, 2024

health system resources

A buyer’s guide to remote monitoring

What is remote monitoring?

Remote monitoring provides the ability for patients to share physiological or other data with their care teams from home or other locations outside of a traditional in-person clinical encounter.

Remote monitoring framework

Remote monitoring is no longer a nice-to-have tool–it’s a critical component of modern care delivery that extends the reach of clinicians beyond traditional settings. Health systems that strategically implement remote monitoring solutions can expect to enable proactive and personalized care at scale. The most successful implementations will prioritize an enterprise-wide approach that complements existing initiatives and reaches diverse population groups.

— Diya Vuthandam, Manager, AVIA Center for Care Transformation

The case for remote monitoring

Creating a remote patient monitoring strategy should start with the questions: What problem are we trying to solve, and what is the value to be gained for our patients and our business?” Your RPM service can power up several benefits to multiple stakeholders. For health systems that operate under a fee-for-service model or are shifting to a fee-for-value model, remote patient monitoring offers unique and substantial benefits, from increasing capacity and driving revenue to increasing opportunities for shared savings or reducing the risk of penalties associated with avoidable utilization.

Fee-for-service

Health systems primarily using a fee-for-service model are finding significant value in remote patient monitoring due to improved patient experience and increased revenue when implemented at scale. RPM allows patients to have a stronger connection to their care team, driving satisfaction and loyalty, while new reimbursements for RPM services can enhance margin. A number of research studies have demonstrated patient satisfaction in the ninetieth percentile, as indicated by likelihood to recommend and user-friendliness.¹ From a direct reimbursement lens, it’s estimated that the total monthly reimbursement for RPM is up to $120 per Medicare beneficiary.²

Fee-for-value

Health systems that are making the move to fee-for-value are increasingly looking to RPM to help them reduce costs and support people’s best health, using real-time data to prevent or slow disease progression and avoidable utilization. These systems – and their patients – are seeing value in RPM due to improved clinical outcomes and quality of life, reduced readmissions and avoidable ED visits, and increased use of primary care services. Studies from Mayo Clinic, Kaiser Permanente, Veterans Health Administration, and members of the AVIA Network, such as Froedtert & The Medical College of Wisconsin, report reduced hospitalizations and shorter lengths of stay when hospitalized. Many health systems operating with more value-based arrangements have been experimenting with a wide variety of RPM capabilities, either during COVID-19 or before. These early adopters are now looking to build an integrated, enterprise-wide RPM strategy to scale what’s working with greater efficiency and impact.

Key attributes of remote monitoring solutions

Effective RM platforms offer a comprehensive suite of features designed to enhance patient care, improve outcomes, and streamline clinical workflows. Key attributes of leading RM solutions include:

Organizing for success with remote monitoring

Remote patient monitoring can be a lifeline for hospitals when treating the increasing number of patients with chronic conditions and can be expanded to provide proactive services to rising-risk patients from the comfort of their own homes. When done well, RM can provide significant value for patients, improve clinical outcomes, and serve as a revenue driver for health systems.

Prioritize populations: Different patient groups and acuity levels within chronic populations require varying interventions and tools. Lower-risk patients will likely not need the same resources, staff, and tools that higher-acuity patients need. Implement risk stratification or analytics to understand patient needs and provide appropriate RM support.
Prepare for data management: Establish a clear plan for handling incoming data. With the adoption of RM, patient biometric data can impede clinicians with an overflux of new information. Ensure there is an infrastructure in place to monitor and act on the information to address any possible clinician apprehensions about data influx.
Integrate with broader care initiatives: Consider how remote monitoring ties in with other existing programs such as low-acuity care, high-acuity care, hospital-at-home, and post-discharge monitoring. Each use case may require different platforms and teams and the RM solution should seamlessly work across existing care initiatives.
Adopt an enterprise-wide approach: Minimize point solutions by organizing around a single platform. Develop a broader strategy to prevent siloed implementations by specific service lines. Consider solutions that can support multiple conditions and acuity types, allowing for a more unified and scalable approach to remote monitoring across the entire organization.

Visit AVIA Marketplace ahead of your next purchasing decision for unbiased third-party information, ratings, and reviews for hundreds of the leading digital health companies and solutions.

Sources:

September 25, 2024

health system resources

Smarter hospitals: Unleashing data with generative AI

Hospitals increasingly use real-time location systems (RTLS) to track patients, staff, and equipment to improve operational efficiencies, generating billions of micro-interactions and data points across the care delivery journey. Most RTLS vendors have a minimal investment in the data they produce, creating all the bricks but on its own doesn’t build a structure.

Picture this: An infusion pump equipped with an RTLS tag sends a location ping to a database every minute of every day so we know where it is at all times. A nurse needing an infusion pump checks the tracking data and discovers it is on the hospital’s second floor. Is this information valuable? Sure, it saves nurses time and effort searching for equipment. But what about the 303 million additional data points for that specific pump that are recorded throughout the day? What can be done with that information?

Much of the data that hospitals generate from care operations remains unused and untapped, representing a missed opportunity to lower costs, boost care quality, and drive operational efficiencies.

By combining GenAI and RTLS with a single-source enterprise data platform, hospital administrators can gain a holistic perspective of the patient journey and quickly obtain novel insights from operational data that improve care delivery and save costs. Specifically, GenAI enables providers to predict patient demand for admissions, optimize resources, improve space utilization, automate discharge planning, and orchestrate care operations, among other operational advancements.

To identify areas where generative AI can yield operational value, begin by identifying a health system’s “known unknowns” and “unknown unknowns.” Stated differently: Seek out answers to the important questions administrators are already aware of, such as bottlenecks that impact patients’ length of stay. Then evolve those newly gained insights to apply them to problems administrators do not yet know exist but should ask about.

For example: historical data show that a laparoscopic appendectomy patient is usually in the hospital for 1 to 2 days. Patients undergoing laparoscopic surgery can sometimes be discharged within 24 hours. When they are discharged 3 days after admission, what caused the delay? How to address it? Another example: How much time do nurses in one department spend bedside versus out of the department? How does this compare to the other hospitals in my system? Now show me the three most frequently visited locations nurses go to in the hospital.

Five ways GenAI drives operational improvement for providers 

GenAI offers strong potential to create numerous benefits for provider organizations, including:

Predicting patient demand for admissions: Armed with data on historical patterns, seasonal trends, and external factors, GenAI can help health system leaders anticipate upcoming bed-capacity needs. By predicting patient demand, leaders can better align staffing and resources with individual patient needs, depending on factors such as diagnosis and treatment plan.
Optimizing resource allocation: By forecasting when various hospital wards or departments will be busy, administrators can leverage GenAI to optimize staff schedules to ensure adequate on-the-floor coverage. Additionally, GenAI can predict patient demand for important medical equipment like MRI machines and ventilators, reducing the likelihood of bottlenecks.
Automating discharge planning: Hospital administrators can automate discharge planning by leveraging GenAI to create personalized plans for patients that account for historical patient recovery patterns and post-discharge needs. Automated discharge planning saves resources and enables seamless transitions from hospitals to post-acute providers or other receiving facilities.
Improving space utilization: GenAI can improve bed management by predicting when beds will be available and then assigning incoming patients to beds in the most appropriate locations based on patient needs and health system capacity. Additionally, GenAI can be used to increase the efficiency of room turnover by creating post-discharge room cleaning and preparation schedules, minimizing the time rooms remain unoccupied.
Orchestrating care operations: At the heart of care operations is the patient journey. Health systems need to move from data creation to consolidation to recommendations, using AI to uncover patterns and trends that impact the entire patient journey. By training AI to orchestrate care operations, such as automated notifications and scheduling, hospitals can optimize queues, manage capacity, deliver just-in-time services, and recommend the next best course of action.

It’s time for health system leaders to dive into the data they have created to yield fast outcomes, higher efficiency, and greater patient satisfaction. With GenAI, hospital leaders gain the ability to converse with their data, understanding not only what’s happening now but also why it happened and what will happen next, to ultimately generate ROI and improve care quality.

Rom Eizenberg joined Kontakt.io as Chief Revenue Officer (CRO) in 2020. Prior to joining Kontakt.io, Rom was the VP of Global Sales at Bluvision – HID, part of Assa Abloy, where he led sales and marketing following the acquisition of IoT startup Bluvision by HID. Throughout his career, Rom has led enterprise software commercial organizations from Fortune 500 to tech startups, twice as a founder. Educated in computer science and international economics, Rom holds three registered patents.

September 19, 2024

health system resources

Digital precision medicine capabilities

The case for digital in precision medicine

Transform clinical care delivery

Drive research and innovation

Optimize provider workflows

Sources

Digital women's health solutions

The case for digital in women's health

Address unmet healthcare needs

Expand coordinated care delivery

Drive system transformation

Key digital capabilities in referral management

The case for referral management solutions

Reduce network leakage and optimize revenue

Enhance care coordination and clinical outcomes

Improve operational efficiency and provider satisfaction

Sources

Chronic disease management — Key digital capabilities

The case for digital in chronic disease management

Enabling continuous disease monitoring

Optimizing clinical resource utilization

Driving revenue and risk management

Sources

Digital wayfinding solutions

The case for digital in wayfinding

Empower patients to confidently navigate the facility

Avoid missed appointments and optimize scheduling

Reduce staff burden

Sources

Population health framework

The case for digital in population health

Facilitating holistic connected care

Data driven decision making

Improving access and equity

Elevating patient engagement and empowerment

Sources

What is ambient intelligence?

Solution framework

The case for ambient intelligence

Key attributes of ambient intelligence solutions

Organizing for success with ambient intelligence

Visit AVIA Marketplace ahead of your next purchasing decision for unbiased third-party information, ratings, and reviews for hundreds of the leading digital health companies and solutions.

What is digital in revenue cycle management?

Solution framework

The case for digital in revenue cycle management

Key drivers for digital in RCM

Key attributes of revenue cycle management solutions

Organizing for success with revenue cycle management

Visit AVIA Marketplace ahead of your next purchasing decision for unbiased third-party information, ratings, and reviews for hundreds of the leading digital health companies and solutions.

What is remote monitoring?

Remote monitoring framework

The case for remote monitoring

Key attributes of remote monitoring solutions

Organizing for success with remote monitoring

Visit AVIA Marketplace ahead of your next purchasing decision for unbiased third-party information, ratings, and reviews for hundreds of the leading digital health companies and solutions.

Five ways GenAI drives operational improvement for providers

About AVIA Intelligence Platform

Five ways GenAI drives operational improvement for providers 