We had the opportunity to discuss the value impact of CX-focused tools in healthcare with Marcus Garcia, the Regional VP of healthcare at NICE. Marcus’ insights led us into the intricacies of patient-provider interactions and the need for AI-led automation that does not leave out human intuition and touch in NICE CXone.

Achieving PX is a Subtle Balancing Act!

Patient experience (PX) is a relatively new dimension in healthcare, driven by rising patient expectations. Marcus explains, “Patients now expect the same ease, convenience, consistency, and transparency they experience when booking a flight or ordering a product.” While digital interactions are becoming the norm in patient-provider communication, optimizing voice interactions remains critical.

“Patients also expect a seamless experience across digital, contact center, and mobile touchpoints, even though these systems are often managed separately,” Marcus adds. This complexity creates a need for a cohesive digital interaction strategy that balances automated and personal interactions to meet patient expectations.

“For tasks like booking, rescheduling, or canceling appointments, patients want fast and easy communication options,” Marcus continues. However, when the issue is more complex, patients often prefer speaking with a human agent to have a detailed conversation. “By automating repetitive tasks like appointment scheduling, contact centers can save valuable time, allowing agents to focus on meaningful, personalized interactions with patients,” he concludes.

CXone Mpower, NICE’s flagship platform, ensures all patient interactions, whether through voice, digital messaging, chatbots or live agents, are integrated in a single unified and scalable platform. When all interactions are handled from a single place, there is no need to manage multiple tools or platforms, there are no more silos between front and back office operations so customer queries move seamlessly across departments, and the system is continuously self-optimized – learning from past interactions to fine-tune future ones with maximum effectiveness and efficiency. CXone Mpower empowers healthcare organizations to deliver personalized self-service experiences, orchestrate human and AI agents in one place with bi-directional learning, and enhance the day-to-day performance of contact center.

CXone is built on the vision of helping hospitals and healthcare providers elevate patient centricity by transforming the way healthcare services are delivered.

In summary, CXone Mpower automates straightforward, repetitive patient interactions and enhances those requiring human involvement. This approach significantly improves patient engagement and experience, reduces friction, improves agent satisfaction, and ultimately leads to better patient outcomes.

Platforms Built for Positive Healthcare Outcomes

CXone is built on the vision of helping hospitals and healthcare providers elevate patient centricity by transforming the way healthcare services are delivered. By leveraging technologies and understanding the role of stakeholder challenges, NICE helps augment experiences that translate to positive healthcare outcomes through its platforms. Marcus helped us delve into each of these facets:

1. Self-Service Tools: In today’s digital-first world, consumers expect the convenience of managing various aspects of their lives through their personal devices. This includes making or rescheduling appointments and accessing test results at their convenience. The strategic use of automation and artificial intelligence (AI) can significantly reduce administrative burdens and streamline processes both before and after care. This involves offering self-service options for routine tasks such as scheduling and managing appointments, requesting referrals, refilling prescriptions, reviewing bills, and making payments. Studies suggest that 30 to 50% of interactions involve simple queries about scheduling, rescheduling, or canceling appointments—tasks that can be easily automated. By deflecting these to self-service, healthcare providers can focus on more complex interactions without the need for additional staff.
2. Proactive Customer Care: NICE’s proactive outbound AI communication engages patients early, automating their journey while addressing potential issues before they escalate into larger problems. Rather than reacting to patient calls or emails, our tools take the initiative to start conversations, anticipate questions, resolve concerns, and ensure patients enjoy a smooth and seamless experience throughout their care journey.
3. Analytics and AI: Leveraging insights from phone calls and digital interactions across all touchpoints is invaluable for any organization. It enables providers to apply analytics to understand the entire patient journey and identify areas for improvement. Combining this with post-care survey data provides a clearer picture. A comprehensive understanding of the patient journey requires a unified solution to measure and analyze customer experience and feedback data. This holistic approach helps identify opportunities for automation and self-service, further enhancing the patient experience.
4. Augmenting the Agent Experience: The agent experience is central to the patient experience. As routine tasks become automated, the skillset required for agents will evolve, emphasizing human intuition and empathy. We provide tools to augment agents’ capabilities, including real-time guidance, insights, and instant access to up-to-date knowledge articles, ensuring they always provide accurate and effective answers. Our tools also automate interaction summaries, allowing key points to be documented quickly and accurately, enabling agents to move seamlessly to the next interaction. With these tools, agents can assist patients efficiently without placing them on hold or transferring them. These insights are continuously refined as the system learns from prior interactions, driving ongoing improvements in agent efficiency and effectiveness.

One Medical’s AI and Human-led Experiences

To explain how NICE’s CXone platform addresses the challenges faced by most primary care providers, Marcus recounted One Medical, which bought the CXone platform. The customer aimed to improve the workforce, quality, performance, and after-call feedback management.

CXone tracked their inbound call volumes and call intervals. Using an IVR system, they observed trends and challenges in patient interactions. By leveraging interaction analytics, they were able to unlock insights to make their contact center services available 24/7 with the current staff and to expand their business. One Medical plans to expand with CXone and enable NICE’s GenAI capabilities with Copilot, Autopilot, and AutoSummary, all under a unified platform.

HOMELINK’s Efficient, Error-free Patient and Provider Experience

“There’s also another case study with HOMELINK. They were exploring ways to improve efficiencies to serve their customers better. They adopted NICE’s AI-driven proactive customer engagement technology,” Marcus adds. It helped their patients stay on top of their health plans with a multi-channel outreach campaign including text, calls, and email between patients and care providers for seamless communication. Previously, it involved many manual touch points with a high scope for errors, leading to no-shows and failure to follow up on patient appointments.

NICE’s proactive journey automation allowed HOMELINK to listen, identify, and start conversations while understanding when to bring in a human agent and update the data/feedback back to the systems. This resulted in improvement in efficiency and productivity for their patient engagements. “Nearly 9 in 10 users reported being able to report their updates in real time. HOMELINK also recorded a 30% increase in productivity per hour per employee,” Marcus shares.

Paving the Way Forward with PX

NICE’s platforms’ success is attributable to underlying technologies such as cloud, advanced analytics, digital tools, and AI. “It is a balancing act. NICE’s cutting-edge tools are also well-aligned with providers’ needs and recent regulatory standards.”

Behind NICE’s new product launch and product enhancement lies the company’s R&D teams’ effort, where they invested nearly $346 million and hold more than 529 patents. It proves NICE’s strong foundation in IP for leading breakthroughs across AI-driven healthcare tools, patient-centric workflows, and secure and compliant digital engagements.

Marcus also spoke about NICE’s most awaited developments in 2025, which include the latest enhancements to the AI-driven features for proactive patient outreach with reminder notifications. NICE’s strategic partnership with EPIC helps deliver seamless workflows and a centralized view of patient interactions to providers. This will help achieve the company’s goal of pushing the boundaries of what healthcare organizations can do to enhance patient experiences and outcomes.

The post NICE: Putting Patients and Providers at the Heart of Care appeared first on HealthTech Magazines.

The Combined Forces of VRI and Higi Power Modivcare’s Monitoring Platform

Modivcare is a provider of innovative community and home monitoring solutions that leverage devices, digital tools, non-clinical, and clinical resources to efficiently and effectively engage populations in their care. The platform brings together two leaders in the monitoring space, combining the unique assets of each to create one powerful platform. VRI offers personal emergency response systems (PERS), vitals monitoring, and data-driven patient engagement solutions. While Higi brings forward its community network of Smart Health Stations and its telehealth-enabled Health Station model, digital engagement tools, and a national clinical network that powers its clinician-led home monitoring solution. This integrative solution suite offers a risk-appropriate service that evolves with the member over time to meet each member’s health and social related needs.

The combination of these two assets provides a glimpse into the company’s transformative vision and commitment to delivering meaningful engagement, data-driven insights, and compassionate care.

With proven outcomes aligned to member satisfaction, gap closure, and reduction in total cost of care, Modivcare’s monitoring platform proactively removes barriers to enable access for vulnerable populations by engaging with members in the ways that matter to them.

Modivcare’s Vision

Modivcare’s approach brings forward a new modality to support both rural and underserved populations who may lack access to traditional care settings, and who are more likely to suffer from adverse outcomes. The community screening platform can shorten the distance to healthcare, offering self-service vitals monitoring, risk assessment tools, and a platform to engage in virtual care. As risks and care needs are identified, home-based programs support a regular cadence of data collection, proactive monitoring of biometrics, clinical guidance via the clinical network, and access to support at the press of a button through PERS, text, or phone call.

The combined platforms offer an ideal complement to propel Modivcare’s vision forward. VRI’s incredible strength and legacy in PERS and vitals monitoring brings a strong history routed in outcomes tied to core customer objectives like driving member satisfaction, closing HEDIS care gaps, and reducing total cost of care, especially for the costliest members. Higi adds its clinical network to further strengthen the organization’s capabilities in alignment to its customers – a vision realized by Modivcare’s President and CEO L. Heath Sampson.

“We acquired Higi both for its Smart Health Station technology and network and its clinical network that serves as a backbone to care delivery offered by the newly imagined combined organization. Our strategy is to broaden our reach and deepen engagement with our members to meet their diverse needs,” Sampson says.

Mr. Sampson finds immense opportunity in rethinking how benefits historically considered to be supplemental can move the needle on important clinical measures that impact health plan outcomes, quality measures, and member satisfaction. Before becoming CEO, Sampson served as Modivcare’s CFO and led the business to focus on innovative healthcare offerings – specifically supportive care services.

Modivcare’s monitoring services are accessible to state agencies, Managed Care Organizations, Medicare Advantage Plans and care partners, with a special focus on helping its customers address vulnerable and underserved populations. The leadership team’s efforts to simplify healthcare for these communities through non-emergency medical transportation solutions (NEMT), in-home personal care, virtual and remote care, and integrated supportive care services are designed to positively impact their physical, emotional, and social wellbeing.

Member-Centered Care

Core to this vision is E3, another unique feature of the platform designed to enhance connections to care by prompting actionable steps and removing barriers for members. It fosters active participation by providing dynamic education tailored to each member’s health needs. By identifying individual needs and challenges, E3 empowers members to take control of their health.

The E3 platform evolves with members, adapting to changes in their health status and care requirements with continuous data collection that allows for proactive management and timely interventions. By integrating technology with personalized guidance, E3 sets a new standard in member-centered care, effectively prompting action and addressing barriers to health.

Impacting Members, Caregivers, and Healthcare Partners

The Modivcare monitoring team is consistently inspired by its mission to provide access to the care that matters for those who need it most. From digital experiences to human-touch, every interaction is a cause for inspiration that keeps teammates engaged in their work.

VRI’s in-home Vitals Monitoring Program serves as a powerful tool that provides a more complete picture of a member’s health and social needs, leading the provider to treat the patient more effectively resulting in better outcomes. In a study completed by Modivcare spanning 10 years of data, members with hypertension received an in-home blood pressure cuff that was monitored by VRI’s Care Center. The program included daily blood pressure monitoring, reminders for missed readings, 24/7 triaging for abnormal readings, and escalation reports to providers as appropriate. Results showed 52% of initially uncontrolled participants were within HEDIS control in six months.

Modivcare’s clinician-led service that collaborates with a member’s primary care provider, in partnership with the Michigan Center for Rural Health and three rural, critical access hospitals in Michigan, provided virtual care over the course of 18 months. Through clinician-led in-home monitoring and coaching with a dedicated nurse care manager, the number of individuals with controlled blood pressure readings doubled, increasing from 39% at the start to 78% by the end of the pilot period. Patients with previously uncontrolled hypertension experienced an average reduction of 27 mmHg systolic and 11 mmHg diastolic, achieving blood pressure readings in the normal range. In addition, many participating patients also improved their blood glucose and weight.

Modivcare’s self-guided monitoring services empower users with timely access to tools and information that makes a tangible difference. From the pregnant user who accessed a publicly available Higi Station to measure her vitals when something didn’t feel right – following the digital prompts to get to care immediately and ultimately crediting the platform with saving her baby’s life – to the platform user living alone who found comfort and reassurance in being able to regularly monitor their health, having access to self-screen and following actionable digital navigation made all the difference.

Modivcare remains deeply committed to its mission of delivering care that makes a tangible difference in the lives of those who need it most. By blending cutting-edge digital tools with compassionate human touch, Modivcare’s monitoring services empower individuals to take control of their health while fostering meaningful connections that inspire both patients and care providers. Each success story fuels Modivcare’s drive to expand access to care and redefine healthcare delivery for all.

The post Modivcare Monitoring: VRI PERS & Vitals Monitoring Plus Higi’s Community Platform & Clinical Network appeared first on HealthTech Magazines.

Healthcare is evolving rapidly, and value-based contracts create the economic alignment to drive optimized outcomes at a viable cost. Diagnostic exam choices have a tremendous impact on outcomes and cost. With the proper understanding of value and evidence-based standards, providers are driving toward this change, continuing to improve patients’ health. However, the cost of care is difficult to wrangle. Creating standards that care teams and systems adhere to ensures that diagnostic choices represent clinically appropriate and cost-effective care. Health systems, provider networks, and medical groups each play a role in leading this change, and they must work together. The way out of the labyrinth of cost is an unwavering and shared commitment to leverage the evidence.

Aligning Payment Models to Best Practice

“Value-based care” is defined in several different ways; it is an approach to care delivery that prioritizes and rewards quality of care, efficiency of service delivery, and patient satisfaction with the care received. The caregivers must also be engaged and satisfied with the model for it to be viable and sustainable. The idea of care centered around the patient and provider requires all members and processes of health care delivery to work in concert with each other to achieve high-quality, evidence-based, and accessible care. In value-based models, payment economics may even penalize the participants financially when goals are left unmet. The alignment of performance and payment is the most important difference from a traditional fee-for-service payment model. Yet, it is fair to assess that not all value models recognize the evidence completely. Productive critique is needed and drives the evolution of payment.

The way out of the labyrinth of cost is an unwavering and shared commitment to leverage the evidence.

The Importance of Evidence-Based Diagnostic Choices

Diagnostics testing is an essential step in the clinical care process. The utilization of diagnostics is wildly different from one model of care or provider to the next. Inconsistencies create variability in cost, and ultimately outcomes suffer. The question is, “Why does variability exist?” A degree of variability is always expected in medicine, but as clinical care and medical training has evolved, inconsistencies are exacerbated while providers chase the latest guidelines and evidence.

Additionally, patients often demand testing from providers who recognize the most efficient best practice may not alleviate the fear that a test might. Many disciplines of providers, clinical staff, finance leaders, analysts, and care teams are nobly charging headlong to solve the value equation within their silos. Research yields multidisciplinary, evidence-based protocols that should supersede individual experiences.

Collaboration to Create Clinical Standards

Health systems, networks, and provider groups must work together to develop and implement these diagnostic standards within clinical protocols. Just as critical as the clinician is the expertise of the diagnostics teams. Intentional effort should be made to engage leadership from the clinical laboratory, imaging, cardiology, neurology, pathology, genetics, endoscopy, electrophysiology, etc. This collaborative effort extends into the multidisciplinary teams of clinicians, analysts, researchers, and experts in value-based care who can review the existing evidence and collectively establish best practices. Regular updates and reviews of standards ensure they remain current with the latest medical advancements and research findings. Many top academic and care delivery institutions have taken this step forward, engaging systematically across disciplines. They are unlocking value, publishing additional evidence, and as they do, the improvement cycle continues.

Measure, Measure, Measure

Once clinical standards are agreed on, monitoring adherence and outcomes helps sustain momentum. “Cost to deliver care” and “cost charged to deliver the care” are two separate crucial indicators that frequently get confused—the time burden and cost of each care staff member and how that value gets maximized. There are various approaches to analyzing these costs; all of them are tedious, but they are still equally worthy. Until the cost of each moment of care, each turn of the cog, and each unit of resource is identified, the true cost opportunity is unknown. Understanding the “cost to deliver care” creates transparency and repeatable value, reducing waste in the system from overutilization, errors, and inefficient processes.

Summarizing Success: Evidence-based Diagnostic Cost Containment

1. Engage Multidisciplinary Teams: Involve diverse groups of experts, including diagnostic experts. Their combined expertise ensures the protocols are comprehensive.
2. Leverage the Evidence: Allow the evidence to drive the decision-making, avoiding the variability and cost associated with preferences and habits.
3. Education and Training: Provide ongoing education and training for healthcare providers to ensure they are familiar with and adhere to the standardized diagnostic pathways.
4. Find the “Cost to deliver care”: Implement costing analysis as a standard. Start small, gain competency, then scale. Differentiate “cost to deliver” versus “price charged.”
5. Data and Analytics: Leverage clinical data to analyze the effectiveness and costs of different diagnostic tests, refining clinical pathways.
6. Monitoring and Feedback: Ensure mechanisms for surveillance of implementing diagnostic standards and adherence. Create a path for users of the protocol to give feedback.
7. Improvement Cycle: Engage multidisciplinary teams to consistently review and update diagnostic standards to reflect the latest evidence.

Improving value and achieving diagnostic cost containment requires engagement from your stakeholders – be sure to invite your diagnostic leaders to the table. Health systems leaders, provider networks, and medical groups are uniquely positioned to leverage their operational sophistication and influence to drive change. A consistent feed of new evidence into the improvement cycle unlocks the value of diagnostic choices, elevating effective and efficient care. A shared commitment to the evidence must prevail.

The post Unlocking Value in Diagnostics: Leveraging the Evidence appeared first on HealthTech Magazines.

AI-powered diagnostic tools have revolutionized healthcare across multiple domains. In medical imaging analysis, AI algorithms enhance radiologists’ ability to detect abnormalities in X-rays, CT scans, MRI scans, and mammograms, leading to more accurate diagnoses and treatment plans. Pathology and histopathology benefit from AI’s capacity to analyze tissue samples, aiding pathologists in identifying cancerous cells and other abnormalities with greater precision. Dermatology has seen advancements with AI analyzing skin images to detect conditions such as melanoma, improving early detection rates. Ophthalmology utilizes AI to analyze retinal images for diseases like diabetic retinopathy and macular degeneration, enhancing early intervention strategies. AI also plays a crucial role in cardiology by analyzing ECG signals and cardiac imaging to diagnose heart conditions like arrhythmias and coronary artery disease more effectively. In genomics, AI analyzes genetic data to identify disease patterns and personalize treatment plans. Clinical decision support systems (CDSS) integrate AI to synthesize patient data and medical knowledge, assisting healthcare providers in making informed decisions.

By harnessing AI algorithms to analyze patient data remotely, telemedicine platforms can enhance diagnostic accuracy, expand access to specialized medical expertise, and improve patient outcomes.

Additionally, AI-powered remote monitoring systems analyze real-time patient data from wearable devices, enabling proactive health management and early intervention. These AI applications continue to evolve, promising to improve diagnostic accuracy, patient outcomes, and healthcare delivery efficiency. Equitable telemedicine continues to be a challenge, specifically in the underserved communities and geriatric populations. In some cases, it is believed to close the disparity gap by enhancing access in rural areas by utilizing eConsults, which can allow for specialized care, in areas where it was difficult to reach in the past.

AI diagnostics and telemedicine represent a powerful convergence that is reshaping healthcare delivery. AI enables telemedicine platforms to analyze patient data, including symptoms, vital signs, and medical history, to assist healthcare providers in making accurate diagnoses remotely. This integration facilitates more efficient and timely healthcare access, especially in remote or underserved areas where access to specialists may be limited. AI algorithms can interpret medical images, such as X-rays and CT scans, improving diagnostic accuracy in telemedicine consultations. Moreover, AI-driven chatbots and virtual assistants in telemedicine platforms can triage patients, provide preliminary assessments, and offer personalized health recommendations, thereby enhancing patient care and operational efficiency. As AI continues to evolve, its role in telemedicine is expected to further streamline healthcare delivery, improve patient outcomes, and expand access to quality care worldwide.

The uncertainty of reimbursement model in this new era of Telehealth/AI Diagnostics and the impacts of disruptive innovation have led to some uncertainties. Although data is still fuzzy around this, utilizing these platforms to deter long-term health cost consequences (preventing hospitalizations) in the risk-based value model as well as incremental cost savings in the fee-for-service model, seem promising. A fee that incentivizes the clinicians may be needed so that this type of virtual care is substitutive vs. additive in the grand scheme of things. They would also need to ease up on the regulations to improve continuum of care and transparency on a national level as the state-to-state restrictions have been challenging to overcome. In addition, a qualitative outcome worth assessing is the effect on clinician burnout. This will potentially play a role in either contributing to this or improving clinician satisfaction.

If the technology is accurate and reimbursements become more transparent, the next question will come down to equity. AI diagnostics have the potential to address healthcare equity by improving access to accurate and timely medical diagnoses across diverse populations. AI algorithms can analyze vast amounts of data efficiently, which is particularly beneficial in regions with limited access to healthcare professionals or specialized diagnostic services. By automating and standardizing diagnostic processes, AI can reduce disparities in healthcare outcomes caused by variations in access to resources or healthcare provider expertise.

However, there are challenges to ensuring equity in AI diagnostics. Biases in AI algorithms can perpetuate disparities if not addressed, as algorithms trained on biased datasets may produce inaccurate or inequitable results, particularly for underrepresented or marginalized groups. Ensuring diverse and representative datasets, along with rigorous testing and validation of AI models across different demographics, is crucial to mitigate biases and promote equity in AI diagnostics. Furthermore, the implementation of AI diagnostics must consider the digital divide, ensuring that all populations have access to the technology and infrastructure needed to benefit from AI-driven healthcare solutions. This includes considerations of internet access, digital literacy, and affordability of technology. Overall, while AI diagnostics hold promise in advancing healthcare equity by improving access to diagnostic capabilities, addressing biases and ensuring equitable access to AI technologies are essential steps towards realizing these benefits for all populations.

In summary, the integration of AI diagnostics into telemedicine represents a transformative advancement in healthcare delivery. By harnessing AI algorithms to analyze patient data remotely, telemedicine platforms can enhance diagnostic accuracy, expand access to specialized medical expertise, and improve patient outcomes. This synergy not only facilitates more efficient healthcare delivery but also addresses geographic and socioeconomic barriers to healthcare access. However, ensuring the ethical use of AI, addressing biases in algorithms, and bridging the digital divide are critical considerations to maximize the benefits of AI diagnostics in telemedicine while promoting equitable healthcare delivery for all populations. As AI technology continues to evolve, its role in telemedicine holds promise for shaping a more accessible, efficient, and patient-centered healthcare system globally.

The post Do AI Diagnostics have a role in telemedicine? What does this mean for healthcare equity? appeared first on HealthTech Magazines.

If we could save upwards of $30 billion a year on avoidable healthcare costs, why wouldn’t we? This is what the CDC estimates that hospital-acquired infections cost annually. 1 in 25 patients will suffer a hospital-acquired infection—many of these result in actual harm to the patient. For example, a central line or urinary catheter left in place too long causes an infection. Frustratingly, hospitals can also have these infections identified that may not be true infections, but fall into the NHSN criteria. These are costly in terms of unnecessary testing, financial penalties for hospitals, and lower publicly reported scores.

AI would alter the approach with an infection prediction with increased diagnostic accuracy. It could help discern acute inflammation from infection.

AI is poised perfectly to help us predict the patients that will get these infections through the use of predictive analytics scanning vast amounts of data combined with real time monitoring of the patient’s vital signs and other data points. This would allow us to mitigate those risks by removing or replacing the problematic lines. It can also predict multidrug-resistant organisms that could put a patient at risk. Multidisciplinary teams all have their roles in preventing these infections and AI suggestions and recommendations could be targeted towards the members of these teams.

AI would alter the approach with an infection prediction with increased diagnostic accuracy. It could help discern acute inflammation from infection.

While the risk of hospital-acquired infections depends on the hospital’s infection control practices, and those steps taken to reduce the risk, patient factors opposing these efforts are also at play which include immune status, recent antibiotic use, frequent visits to healthcare facilities, length of stay (LOS), major procedures, age, ventilatory support and intensive care stays. It seems quite plausible that artificial intelligence (AI) could identify risk factors and generate a score. Steps could be suggested and taken to mitigate infections by keeping devices out as much as possible and guiding clinician care decisions.

Cleveland Clinic investigators recently presented that AI could very accurately predict multi drug-resistant organisms days prior than a culture is available. It is exciting to think that we can use AI to predict and tailor antibiotics and isolation precautions towards these days ahead of a final culture. Taking antimicrobial stewardship to the next level to get patients appropriately treated earlier will save lives, time and money.

AI has recently been used to model new designs of urinary catheters to block the migration of bacteria towards the bladder. Catheters were made consistent with these designs, creating an obstacle course of geometric designs inside the catheter that blocked the migration of bacteria upstream. The design was optimized for E. coli, and testing showed that after 24 hours the bacterial burden was 1/100 of that of traditional Foley catheter design. This is exciting that we can use AI technology to predict the behavior of microbes and design ways to inhibit their growth and migration.

Machine learning (ML) algorithms have demonstrated value in predicting clostridium difficile infection with just 6 hours of data. With almost 30,000 deaths per year related to c. difficile infections, early diagnostics to treat, identify those at risk and isolate to prevent spread would be an incredible advance to saving lives.

CLABSI (central line-associated bloodstream infection) could be predicted allowing physicians to remove the lines prone to infection and avoid those consequences. Suggestions of treatment based on probability and risk would help discern true CLABSI from blood culture contamination.

The support for antimicrobial stewardship that AI could provide would adjust the approach toward treating infections. Currently, the physician evaluates data for the likelihood of an infection. Cultures are taken, the results of which will not be available for several days, and empiric antibiotics are started. When cultures and sensitivities are available, antibiotics are sometimes changed based on those results, or de-escalated. Have we then given a patient a toxic or broad-spectrum antibiotic for a few days that was unnecessary? Have we bred more resistance? AI would alter the approach with an infection prediction with increased diagnostic accuracy. It could help discern acute inflammation from infection. (Is this sepsis or something else?) The correct antibiotic could be chosen which would eliminate the need to de-escalate or change, and the best duration of therapy would be suggested.

Enhanced cleaning and sterilization practices could be suggested by algorithms to identify and mitigate risks with equipment and high touch areas in the healthcare setting.

Patient and caregiver education and engagement could be enhanced through AI based on their medical conditions or procedures to provide targeted and relevant material about their care and infection prevention practices. This would certainly foster a collaborative culture of safety, and mitigate the spread of infections.

I dream of a day when a patient is admitted to the hospital, using AI tools, we are able to get predictive scores on the likelihood of hospital-acquired infections or other complications. More informed decision-making can be made based on the probability instead of blindly pan-culturing when not needed or leaving devices in patients at high risk. Imagine that when a patient comes to the hospital, your risk of CAUTI, CLABSI or hospital-acquired pressure ulcer is present and available to the admitting team so that decision-making to reduce or eliminate this outcome altogether can be made. A most likely diagnosis and risks are presented along with the likely infection cause/ Is it MDRO or not? The right antibiotics are given and a short LOS gets the patient home safely and efficiently. Lives will be spared, and billions of dollars potentially saved.

The post AI to Combat Hospital-Acquired Infections – A Revolution for Patient Safety appeared first on HealthTech Magazines.

Chicago’s Rush University Medical Center’s (Rush) national leadership and vision for addressing healthcare’s past failings and today’s patients’ evolving expectations for how digital technology should shape healthcare delivery can combine to provide a compelling blueprint for how healthcare institutions can address the root causes of chronic diseases that shorten lives and cost the nation billions of dollars.   

Innovative population health-focused technology solutions are playing an essential role.   

In 2017, Rush became the nation’s first major hospital to establish health equity – everyone having the equal opportunity to be healthy – as a measurable, and accountable system strategy. At the core of this strategy was a mission shift to not only deliver the world-class patient care that has Rush consistently ranked among the nation’s top providers, but also to improve the health of the local communities Rush serves by thinking holistically about how health equity affects digital access and clinical outcomes.   

And Rush’s recent commitment to a transformative, multi-year digital experience strategy is accelerating efforts. Hence, patients are better able to access and navigate their health and wellness journeys while also working to improve digital health equity: Fair access to health technologies for those who need them most. 

Understanding how these parallel strategies’ reliance on new technologies that improve accurate clinical diagnostics intersects with population health efforts can help health systems better advance value-based care and health equity progress.   

More advanced technology not only collects and analyzes data, but also ensures that the insights derived are used to create inclusive and effective health solutions.

Addressing unacceptable gaps in lifespans 

Rush’s commitment to a health equity strategy is based on data showing a 14-year gap in lifespan between residents of downtown Chicago and those of primarily black neighborhoods just a few miles to the west. It recognizes the pivotal role of addressing the social determinants of health (SDOH) and lived experiences that shape many black and brown communities. Understanding these dynamics allows Rush to think about digital tools differently in terms of how they engage families on the economic spectrum. 

Partnering at the Intersection of value-based care and health equity 

Like most health systems, Rush has also been growing and improving value-based care approaches along several fronts. One of the highest profile and innovative is its partnership with a leading health solutions company which explores novel reimbursement models focused on health equity known as ACO REACH (Realizing Equity and Community Health), a pilot program from the Centers for Medicare and Medicaid Services (CMS) that tests alternative payment models. Traditional reimbursement models often fail to account for the unique needs and challenges faced by underserved populations. However, the ACO REACH model develops and implements digital strategies and partnerships that haven’t traditionally been attempted, especially addressing barriers to access, such as transportation and socioeconomic factors, which disproportionately affect marginalized communities. Aligning financial incentives with health equity goals is powered by analytics that provides insights on risk, member profiles, and actionable solutions related to demographics and evidence-based medicine. Population tools and analytics that assess the social and clinical risk factors allow our health system to apply accurate clinical diagnostics to the patients that need them the most.  

Rush has also joined forces with two leading population health technology providers to gain deeper insights into the health behaviors, social conditions, and care patterns of Medicaid populations. This allows for the development of targeted interventions addressing the root causes of chronic diseases, rather than just treating symptoms.  

An AI-powered analytics platform along with a healthcare technology company enables patients and providers to better manage chronic diseases that shorten countless lives in underserved communities. For example, we assume psychological factors are the drivers of Chicago’s lifespan gaps, but detailed analytics show that hypertension and other manageable chronic conditions steal thousands of life years annually.

For example, Rush care providers worked with a healthcare technology company to create tools for patients and providers that advanced data analytics capabilities, incentivizing populations to not only navigate their communities but be empowered to improve chronic conditions for themselves or loved ones. 

This collaboration is particularly significant in the context of what is known as digital health equity, or fair access to health technologies for those who need them most. More advanced technology not only collects and analyzes data, but also ensures that the insights derived are used to create inclusive and effective health solutions. For instance, a better understanding of the barriers that prevent populations from accessing care led to the design of more user-friendly mobile health tools that helps patients both embrace local resources and incents them to engage in behaviors proven to lower blood pressure.   

This holistic approach recognizes that technology, when used equitably and complementary to population-based tools, has the power to transform health systems and close the life expectancy gap. And doing so on Chicago’s West Side can also show that creating an equitable health system that reduces cost and improves the lives of individuals and communities alike is possible.   

The post Health Equity and Digital Equity Insights: Addressing Past Inequities and Tomorrow’s Expectations appeared first on HealthTech Magazines.

The integration of Artificial Intelligence (AI), automation, and data analytics into the revenue cycle management (RCM) of healthcare facilities marks a transformative leap toward operational excellence. In an era where financial sustainability is as crucial as clinical outcomes, these technologies are pivotal in optimizing processes from patient intake to final billing, ensuring that healthcare providers not only survive but thrive in a competitive market.

At our infectious disease lab, the implementation of AI and data analytics has revolutionized how we manage our revenue cycle. By automating routine tasks, we have freed up valuable time for our staff to focus on more complex, value-added activities. Automation of data entry and claims processing reduces the likelihood of errors and speeds up the turnaround time, directly impacting our cash flow and reducing the days in accounts receivable.

One of the most significant advantages of using AI is its ability to analyze vast amounts of data to identify trends and patterns that would be impossible for a human to discern. This capability allows us to anticipate issues before they become problematic, such as identifying which claims are likely to be denied based on historical data. With predictive analytics, we are proactive rather than reactive, which not only increases our revenue but also reduces the stress on our staff and improves our relationships with patients and insurers.

AI transforms data into actionable insights, enhancing efficiency and profitability in healthcare.

Moreover, machine learning (ML) models within our AI systems continuously learn from new data. As they become more sophisticated, they offer increasingly accurate forecasts and deeper insights into our lab’s financial operations. This ongoing learning process is crucial for adapting to the ever-changing landscape of healthcare regulations and insurance policies.

Our organization has also capitalized on data analytics to fine-tune our pricing strategies and to ensure compliance with billing regulations. By analyzing the outcomes of thousands of past transactions, we can set competitive prices that maximize our revenue without compromising patient care. Furthermore, compliance monitoring through AI-driven systems ensures we adhere to all billing regulations, reducing the risk of costly penalties and legal issues.

The integration of these technologies extends beyond internal operations to enhance patient interactions. Our patient portal, powered by AI, offers personalized experiences where patients can easily access their billing information, understand their payment options, and communicate with billing representatives seamlessly. This not only improves patient satisfaction but also expedites payments, positively affecting our cash flow.

In addition to these operational improvements, AI and data analytics significantly enhance our strategic decision-making capabilities. With access to real-time data and advanced analytical tools, our management team can make informed decisions quickly, addressing potential financial discrepancies and optimizing overall financial health.

Furthermore, the ability of AI to integrate with other technological advancements, such as electronic health records (EHRs), further streamlines our operations. This integration ensures that all patient data is synchronized across platforms, minimizing the risk of data silos, and ensuring that every department has access to the same accurate and updated information. This seamless integration helps in maintaining consistency in billing practices and patient care services.

Our commitment to leveraging AI extends to training our staff to effectively utilize these tools. By holding regular training sessions and workshops, we ensure that our team is not only comfortable but also proficient in using the latest technologies. This empowerment enables them to contribute actively to our ongoing efforts to refine and improve our revenue cycle processes.

Additionally, AI tools help us manage the complexities of insurance verification and eligibility checks with greater accuracy. By automating these processes, we reduce the instances of claim rejections due to coverage errors. This not only speeds up the billing process but also decreases the burden on our patients, who can be confident that their coverage is correctly verified at the outset of their healthcare journey.

Moreover, AI-driven analytics assist us in identifying inefficiencies in our billing and service delivery models, allowing us to make necessary adjustments. These adjustments are often predictive rather than reactive, positioning us to address potential issues before impacting our operations. This foresight saves time and resources and supports our strategic goals of maintaining financial health and patient satisfaction.

The adoption and continual advancement of these technologies in our revenue cycle processes illustrate a commitment to innovation and excellence in healthcare management. As these tools evolve, so too does our ability to meet the needs of the patients we serve and the staff we support, ensuring a future where healthcare and technology work hand in hand for the betterment of all involved. As we continue to harness these powerful technologies, we not only foresee a more robust financial footing for our lab but also a greater capacity to provide exceptional care to our patients.

Through ongoing investments in AI and data analytics, we not only optimize our current operations but also pave the way for future innovations. These technologies allow us to stay at the forefront of the healthcare industry, continually improving our services and outcomes. By embracing AI and automation, we not only enhance our operational efficiencies but also ensure a higher standard of care, which is the cornerstone of our mission in healthcare.

The post Leveraging AI in Revenue Cycle Management for Healthcare appeared first on HealthTech Magazines.

The rise of physician advisors has been a transformative development in 21^st century healthcare. Many healthcare systems have adopted an enterprise physician advisor model to streamline workflows and enhance efficiency, moving away from reliance on individual hospital-based advisors. This change allows physician advisors to support multiple facilities and optimize operations. As healthcare systems continue to merge or expand into larger networks, the need for standardized revenue cycle management (RCM) practices becomes increasingly critical.

As physician advisors, our responsibilities include utilization management, denial prevention, and revenue cycle optimization. We take pride in our data-driven decision-making approach, especially in managing the revenue cycle. Collaborating with robust analytics teams, we meticulously track various metrics, such as length of stay per provider or service line, readmissions, peer-to-peer overturn rates, and insurance denials. These examples illustrate the data we use to perform our roles effectively. The implementation of automated bots to handle repetitive tasks and the creation of user-friendly dashboards have allowed staff to focus on more complex and high-value activities.

With the abundance of big data, selecting the right data to create the most significant impact is crucial. It is easy to become overwhelmed by extensive tables with countless rows and columns. The key is determining which data should be utilized and which should be set aside. Online dashboards, which enable instant data review and sorting as needed, have greatly simplified this process for users.

We can deliver high-quality care while maintaining financial stability by leveraging advanced analytics and standardizing processes across expanding healthcare networks.

A core function of physician advisors is denial management. A comprehensive dashboard that tracks denial cases selected for peer-to-peer review and appeal, along with their outcomes, enables a more efficient and balanced workflow. Both payers and hospitals can use the dashboard to dissect data, identify trends, and monitor expected versus actual reimbursement. This valuable information can pinpoint denial categories and their root causes, leading to educational opportunities to improved documentation and adherence to evidence-based medicine, ultimately reducing the administrative burden on providers and payers.

Utilization management benefits significantly from dashboards that assist with status management and identify areas for improvement, such as incorrect status selection on admission, which can lead to denials and compliance issues, especially in short-stay cases. Accurate status selection ensures better revenue and avoids unnecessary denials and out-of-pocket patient costs. Additionally, these dashboards monitor denials by location and payer, identifying trends and patterns among payers with high denial rates. This facilitates discussions between providers and payers about high denial rates and their causes compared to similar payers, encouraging process improvements such as data exchange method with payers.

A Resource Utilization dashboard identifies how services are used across hospitals, departments, nursing units, or outpatient facilities, helping control utilization and direct resources to areas with higher demand. This improves resource management and reduces costs. Physician advisors often lead utilization management committees and conduct discussions to optimize resource utilization.

Care management dashboards facilitate discharge planning. A dashboard that tracks the number of patients discharged home with and without home care versus post-acute facilities provides a better understanding of post-acute denials, streamlining discharge distribution, or improving documentation to support the need for such services. The dashboard also allows monitoring of precertification times and designing process improvement plans to reduce these times. Physician advisors play a crucial role in supporting care management, especially with complex discharges.

Observation of patients is increasingly attractive to health systems, given the growing frequency and the ability to manage some patients in outpatient settings with appropriate resources. Established benchmarks for observation cases are lacking, especially since each facility may have different case types, making it challenging to create standard and reliable benchmarks. Several metrics can be included in an observation dashboard, such as cost per case including direct and indirect cost, length of stay, number of consults per case, conversion rate, ancillary services performed, relevance to the acute presentation, and how quickly they were performed. Data can be reviewed by payer, diagnosis, location, and provider, helping improve efficiency and identify outliers. This data also supports the case for observation units and monitors their effectiveness and productivity.

A Medical Staff Scorecard/dashboard is a valuable tool for providing feedback to providers, including physicians and advanced practice practitioners. Many providers lack access to performance data. A dashboard that displays the length of stay, procedure times, time to round, and ancillary requests provides valuable insights for physicians to understand their performance and compare it to their peers using risk-adjusted data. The scorecard helps reduce inappropriate utilization and enhances success in value-based programs. The quality section of the dashboards can include the number of preventive services, medications used, chronic disease management, and vaccinations, enabling physicians to practice better population health management and prioritize care for those who need it most. The scorecard can also include readmission data, helping providers identify opportunities, create mitigation plans, increase access, and collaborate with other services such as care coordination.

The potential for utilizing data is limitless. Dashboards allow administrators, caregivers, and medical staff to monitor outcomes and make necessary adjustments without missing opportunities. This reduces costs, waste, and administrative burden while increasing efficiency and access to healthcare. A data-driven approach and commitment to continuous improvement ensure an enhanced revenue cycle and reduce denials and controllable loss. We can deliver high-quality care while maintaining financial stability by leveraging advanced analytics and standardizing processes across expanding healthcare networks. Physician advisors involved in these tasks cannot emphasize enough the value of having this data available and updated instantaneously.

The post The Power of Numbers and Dashboards: A Data-Driven Strategy for Optimizing Revenue Cycle Management appeared first on HealthTech Magazines.

Healthcare is a business unlike any other. Many economists describe healthcare as an imperfect market, where the consumer is not the one paying for the goods and services; they have limited knowledge on what they are buying, and they have little to no ability to shop for a deal in many scenarios. Healthcare has similar imperfections on the provider side in terms of reimbursement. From service line directors to physicians, many do not fully understand what they are or are not getting paid for. Providers are continuously dealing with multiple nebulous policies across several different payers that can have a material impact.

Currently, nearly every provider in the country is experiencing a similar top-down directive to decrease costs and increase revenue with the ultimate goal of increasing cash in the door. Once again, the idea of an imperfect market in healthcare appears. How can these clinical leaders improve cash flow if their primary source of truth is a revenue and usage report?  

There is value in the collaboration of revenue cycle staff in many committees and initiatives, given the current strain of hospital finances.

Since 2011, when incentives appeared promoting the adoption of electronic health record (EHR) systems, the ability to acquire detailed data has improved significantly. One can extract virtually any clinical or financial data point from these systems, and business intelligence (BI) tools can visualize the data. This financial data has not always been readily available, shared, or interpreted by clinical stakeholders for a multitude of reasons. First, it could simply be company culture, keeping reimbursement and money talk away from clinical practice. Secondly, it could be the fact that reimbursement data can be difficult to interpret and there may be significant manual lifting to get it in comprehensible format for clinicians; as electronic remittance info can make little sense and payers make it intentionally confusing. Because of this, the Revenue Cycle (or their data) may have been siloed from project management and clinical decision-making. 

With these silos in place, service line directors are placed in a poor position to succeed under the direction of increasing cash. Not understanding concepts like the impact of payer mix has enormous strategic implications. Shifts in the payer mix as small as one percent can mean missing revenue targets for the department or for the facility. 

Capital requests for new, high-tech equipment to complete procedures, tests, or treatments have billing implications that should be stamped by the revenue cycle. The pro formas that can be driven by vendor information should be confirmed by revenue integrity for accuracy. Payer policy and national/local coverage determinations should be confirmed by patient financial services. Not understanding the payer policy and billing requirements can utterly derail any value gained by the capital request.

Medicare is the largest payer for many facilities. With Medicare comes the diagnosis-related group payment, and with bundled payments comes the need to manage length of stay (LOS). While moving LOS is multi-faceted, there are ways to quantify the metric. Imagine the impact on physician and case management leadership if you can report how much impact 0.1-day improvement in LOS has on the bottom line. Expected payment-to-charge ratios, cost data, or contractual expected reimbursement can be applied to LOS metrics to drive home the importance of throughput. 

Many bedside and clinical staff have little understanding of the back-end impact of the work they complete on a daily basis. Processes like registration and prior authorization have significant impacts down the line. Meetings with ancillary outpatient departments and clinics to review preventable denials create a sense of value in the work these registration teams complete. The processes in these satellite areas are harder to keep reigns on. Providing this simple data can add allies to your initiatives which improve margins and reduce revenue leakage through denials. 

While not applicable to all facilities, the revenue cycle staff typically have strong knowledge of payer contracts which again can provide valuable insights. Many health systems closely guard what is in their managed care contracts and the rates they contain. It may not be great to share these with all clinicians, but understanding the impacts these agreements could have on operations and reimbursement can be beneficial.

Finally, if clinicians understand their charges, reimbursement, and revenue, they can escalate if a process breaks down or the EHR misbehaves.

There is value in the collaboration of revenue cycle staff in many committees and initiatives, given the current strain of hospital finances. The financial and clinical data is there. It should be time to consider merging this data, as the value may be surprising.

The post Clinicians and Revenue Cycle: Why the separation? appeared first on HealthTech Magazines.

The healthcare industry faces continuous challenges in maintaining efficient RCM, which is essential for the sustainability and operational success of healthcare providers. A particularly challenging aspect of RCM is the management of denials and appeals, a process fraught with complexities that can significantly impact the financial health of medical institutions. As healthcare providers strive to minimize these financial disruptions, a deeper understanding of the causes and effective management strategies is vital. This piece delves into the intricacies of why denials occur, the consequential effects they have on healthcare operations, and the strategic measures that can be adopted to mitigate their impact.

Understanding Denials in Healthcare

Denials are a critical pain point in the revenue cycle, representing instances where a payer, such as an insurance company, refuses to pay for a service that has been provided, citing various reasons. These reasons can range from coding errors, for example, mismatches between provided services and billing codes, to administrative oversights like incomplete patient information or lack of prior authorization. Each denial has to be reviewed, corrected, and resubmitted, which is time-consuming and costly.

The reasons behind denials are manifold and often interlinked, requiring a multi-faceted approach to understanding and addressing them. For instance, a common cause of denials is failing to verify a patient’s insurance coverage before providing services. This can lead to claims for services not covered under a patient’s current policy, resulting in a denial that could have been avoided with proper insurance verification. Similarly, inaccuracies in coding, whether due to human error or misunderstanding of the latest coding standards, can lead to claims that payers will refuse to reimburse.

Effective denial and appeal management is crucial for the financial viability of healthcare providers.

The Impact of Denials

Denials not only delay payments but also require significant administrative effort to rectify, which can strain resources and reduce overall efficiency. AHIMA published an article on a step-by-step approach to resolving claims denials that reports the average denial rate across the healthcare industry can reach 20%, with each denial costing $25 to $181 to rework depending on the patient setting. When multiplied by the volume of denials a typical healthcare facility faces, the total cost can quickly escalate. This financial strain underscores the importance of implementing strategies aimed at reducing the occurrence of denials.

Strategies for Managing Denials

1. Preventative Measures: The cornerstone of effective denial management is robust front-end processing. This includes meticulous collection of patient data, thorough verification of insurance details, and strict adherence to coding protocols. Regular training for administrative staff, coupled with periodic audits, can enhance the accuracy and efficiency of these processes.
2. Technology Integration: Modern RCM solutions employ sophisticated software that can preemptively identify potential errors in claims through processes known as claim scrubbing. These solutions integrate seamlessly with electronic health records (EHRs), ensuring that claims are accurate before submission, thus reducing the likelihood of denials.
3. Data Analytics: Advanced data analytics tools play a crucial role in identifying trends and patterns in past denials. By analyzing this data, healthcare providers can pinpoint common pitfalls in their billing processes and implement targeted improvements to prevent future denials.

The Appeals Process

Following a denial, healthcare providers can initiate an appeals process, which involves challenging the payer’s decision and providing additional documentation to justify the claim. This process is critical in overturning unjustified denials and recovering revenues that are rightfully due.

Key Steps in the Appeals Process:

1. Review and Response: It starts with thoroughly reviewing the denial notice to understand the payer’s reasons for rejection. This understanding guides the collection of necessary documentation and evidence to construct a robust appeal.
2. Timely Filing: Adherence to the payer-specified timelines is crucial. Failure to file an appeal within the designated timeframe can permanently impact the provider’s ability to recover the funds.
3. Follow-Up: Persistent follow-up is essential to keep the appeal moving through the process. This includes regular communications with the payer to ensure the appeal is being considered and to submit any additional information required swiftly.

The Critical Role of RCM in Government-Dominated Payor Environments

Given the financial intricacies of healthcare institutions with a predominant payor base consisting of governmental entities, where approximately 85% of revenue comes from Medicare, Medicaid, and other government-funded programs, the importance of meticulous RCM cannot be overstated. For these institutions, every dollar is crucial not just for operational sustainability but also for fulfilling their fundamental mission to deliver quality healthcare. Governmental payors often have strict reimbursement criteria and complex billing protocols, making the management of denials and appeals even more critical.

Institutions with a high proportion of government payors frequently operate under tight financial constraints, often running at negative margins. This economic environment amplifies the significance of every claim processed and requires a heightened focus on the accuracy and timeliness of billing and coding practices. Efficient management of denials and appeals in these settings is not just about financial survival; it is about ensuring that resources are available to continue providing essential healthcare services to the community. Through strategic improvements in denial management and the thoughtful integration of technology, these healthcare providers can significantly enhance their operational efficiencies, reduce financial waste, and, more importantly, uphold their mission to deliver exceptional care.

Effective denial and appeal management is crucial for the financial viability of healthcare providers. Through a comprehensive understanding of denial causes, strategic process implementation, and the adoption of advanced technologies, providers can enhance their RCM processes, reduce the impact of denials, and ensure robust financial health. As healthcare landscape continues to evolve, staying informed and agile will be key to success in RCM.

The post Navigating the Complexities of Denials and Appeals in Healthcare Revenue Cycle Management (RCM) appeared first on HealthTech Magazines.