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.

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EHR metadata provides useful objective metrics for assessing the impact of AI and automation on how physicians enter clinical notes and interact with patient records. However, from my perspective, leading a very gifted Wellness Informatics team that implemented an ambient AI transcription solution, a more meaningful measure of success comes directly from the lived experiences of the clinicians using it.

We are a clinical informatics team that prioritizes clinician wellness by living in the narrow yet very important intersection of technology and humanity. After thousands of interactions, our team has identified the main challenges that our physicians and APPs face. We also have corroborated our subjective findings with analytics tools offered by our EHR vendor to develop multiple avenues of personal, practice, and system-level support.

One of the ways we support our physicians and APPs is through direct observation. It gives us the privilege of being with our providers in the exam room with their patients. I remember thinking during one observation how marvelous a particular specialist physician was. Patients love this guy. He also has played a pivotal role in the health of a multitude of patients – including patients we shared.

I distinctly recall a 1:1 support session with him that made me realize we needed to take our advocacy and support to the next level. He confided that he wanted to leave the organization and possibly the profession. This doctor did not need to learn a new skill or technique. Instead, he needed to delegate some of his daily responsibilities to others. As we collected data, it became apparent that we needed a way to reduce our providers’ clinical documentation workloads.

Time previously spent writing notes can now be used for other complex tasks, such as addressing abnormal results.

We began in 2017 with in-person scribes. We still use the service today. The physicians who took advantage of it were extremely pleased. Job satisfaction improved and time available for other important tasks – such as in-basket management – increased. All combined, this decreased overall time in the EHR for these physicians. An unexpected benefit was the ability of these great physicians to mentor the next generation of practitioners. However, the cost of in-person scribes and staffing shortages precipitated by COVID-19 led us to look at AI-based options.

In 2020, we evaluated several vendors and selected one who provided AI transcription that was reviewed by a human before the final note was added to the physician’s preferred note template for review. Users felt that the service was hit-or-miss, with the quality of final note being highly dependent on the human reviewer. Most physicians who stayed with the service appreciated not having to worry about their documentation. Still, the inconsistent quality and cost were major drawbacks.

In 2022, we went live with a newer, fully automated version of the same company’s ambient AI transcription solution and we could not have been more pleased. Objective data show that the attrition rate is significantly lower than the version with human review, notes are delivered within seconds instead of hours, and any editing needed is much simpler and more efficient.

The subjective data obtained directly from the clinicians using the ambient AI solution is even more telling; participants have reported:

• Less burnout or fatigue.
• Reduced cognitive burden
• Better work/life balance
• Higher job satisfaction
• More likely to stay at their current organization
• More likely to remain in clinical practice

Specific comments from our physicians and APPs include:

• “Liberating! More time in the exam room where I can give the patient my undivided attention. I no longer feel like a well-paid data entry clerk!”
• “Much better documentation of historical data to support the level of visit.”
• “It might even give my career a few more years of longevity.”
• “Overall, very happy with this product. It has increased my job satisfaction and improved work-life balance.”
• “Wow! They documented things I would have forgotten.”
• “Very thankful for this service.”
• “I simply will not practice the rest of my career without some form of scribing, no matter the cost.”
• “I used to be working on labs from four to five days ago. Now, I work on yesterday’s labs.”
• “Another important part is that it allows me to look at my patients more and be more present to them during their appointments. I am no longer trying to partially complete notes in the room. The only things on the computer that I do in the room now are place orders or look up study results with the patients.”

As a user of ambient AI, I want to highlight the importance of reducing cognitive load. It feels very liberating to be able to concentrate on the patient and not have to stress about how to record what I am being told. Time previously spent writing notes can now be used for other complex tasks, such as addressing abnormal results.

Is this technology for everyone? No. Is it perfect? No. But it is incredibly good. Quite frankly, this technology is still in its early days and at its  “worst.” However, the learning nature of AI means that it will continue to improve and evolve. We have noticed significant improvements since we first went live, including stylistic changes in how the AI transcribes the note.

The sky’s the limit as to what this technology will do for us as clinicians. It will queue orders as it hears them. Also, it will soon generate summaries of relevant facts about a patient’s health issues. There are many more advancements planned, and I can’t wait to see what’s to come.

I appreciate a technology that enhances my human abilities when I am with my patients in the exam room. Simply put, it feels great to feel like a clinician again. 

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Healthcare is complicated. Knowing the correct medications, procedures, and care plans requires years of education and experience. The average family member of a patient does not have this knowledge, and most do not claim to have it.

However, what the average family member does know is their loved one who is lying in that hospital bed. They know their “normal” behavior and when the patient is deviating from that; what makes them comfortable, what will cause them distress, what will help with their healing and what will hinder it. Sometimes they know the patient’s past medical history better than the patient does.

Families can provide a wealth of knowledge that, combined with the expertise of medical professionals, can create an equation for better patient outcomes…as long as both sides take the other seriously.

Respectful and frequent communication with a patient’s family needs to be a priority in the healthcare environment. When a family member brings a concern to a care team member, it should be listened to and considered. While the requests or concerns may not always have merit, and the healthcare professional may have clinical knowledge that overrides the request, it is important that the family feels heard and considered. Sometimes what the family brings will truly impact the patient’s outcomes and overall health.

This collaboration can be facilitated using various technology platforms in the healthcare environment. If implemented effectively, they allow for information sharing that can lead to inclusive and effective care plans. The following sections outline some examples of technology that can assist in family-inclusive care.

Family-inclusive care has immense potential to improve patient care and outcomes.

TeleSitter

TeleSitter technology has become more prevalent in healthcare settings in recent years, as the industry has faced staff shortages and a global pandemic. This technology utilizes cameras, two-way video and audio, an alarm system, and centrally located monitor technicians to monitor multiple patients at once.

When patients are placed on TeleSitter via a provider order, a reason is indicated (i.e., altered mental status, attempting to remove medical devices, fall risk, etc.). With this information, the monitor technicians know what to look for on the video feed, and if they see an issue requiring an in-person response they communicate that with the patient’s bedside care team. If the response is needed urgently, the monitor technicians can also set off a loud alarm in the clinical space.

TeleSitter monitor technicians should also be encouraged to communicate with the patient and their family members in the room via the two-way audio/video capabilities. These conversations have several benefits: the patient and family are able to meet the technician who will be keeping an eye on them, the family can convey any concerns they have about the patient, or give the technician tips on things to look out for, and everyone can feel more comfortable that the patient will be safe.

Perhaps the family knows a loud alarm would make the patient’s delirium worse because they suffer from PTSD. They could communicate this to the technician, who can then take all appropriate steps to avoid the need to use the alarm. Or the patient’s spouse knows they always get up at night to use the restroom. The technician can proactively be prepared to speak to the patient over the device and ask them to wait for assistance so they avoid a fall. These anecdotal pieces of information can significantly improve the patient’s experience.

EMR Patient Portals

Patient portals provide an easily accessible window into a patient’s medical record. Patients can see test results, notes, immunization history, problem lists, and other information. Patients can communicate with their providers via secure chats, and in some cases, schedule appointments. These tools have become commonplace in healthcare, with new features continually being developed.

If leveraged correctly, these tools can improve communication in the Inpatient setting. A perfect example would be configuring the Electronic Medical Record (EMR) to send provider and nursing notes to the portal. This allows the patient and their family to always be up-to-date on the patient’s status and the care provided without having to track down a staff member for a verbal report. This is particularly helpful when family members cannot physically be at the hospital. It is a streamlined and efficient way to communicate.

Family Participation in Provider Rounds

Multi-disciplinary provider rounds are a standard communication tool amongst healthcare team members, and have been shown to enhance patient care and decrease lengths of stay. Mobile access to the EMR via a smartphone or tablet can easily allow clinicians to reference patient data during these meetings, making the discussions more specific and effective. This rounding method could also easily be expanded to be inclusive of families with the help of some additional technology.

For example, the Case Management team could coordinate with the patient’s family member(s) and establish an audio or video call so the family could participate in the conversation with the care team. If Rounds occur outside of visiting hours when the family cannot be there, they would still be able to ask questions, share information, and be part of the care planning process.

Conclusion

Family-inclusive care has immense potential to improve patient care and outcomes. Family members bring valid and important information to the table, and with some mutual respect, the healthcare team and family members can collaborate to benefit the patient’s ability to heal. Technology can be leveraged to facilitate this inclusion. Health systems should be taking steps to make family-inclusion part of their culture, providing education and tools to the healthcare team to encourage collaboration.

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Regulatory changes in healthcare often arrive like sudden disruptions, throwing clinical workflows out of sync and distancing patients from quality care. Yet these regulations provide the crucial pathway towards ensuring patient safety and enabling excellence in healthcare delivery. The challenge for physician-owned health systems and smaller community hospitals intensifies as they must weather these regulatory storms while operating efficiently across disparate systems and infrastructures.

To truly grasp the profound impact of regulations, one must recognize their vital significance in safeguarding patient welfare. Like lighthouses guiding ships through turbulent storms at sea, healthcare regulations serve as indispensable guardrails on the delivery highway, directing providers toward practices that uphold the pillars of safety, efficacy, and ethical conduct.

In an era dominated by digital innovation, interoperability becomes our guiding compass, facilitating seamless data exchange and communication among diverse systems and stakeholders.

Let’s explore this analogy further:

Navigating Healthcare’s Seas: Envision healthcare as a vast ocean, with patients and providers navigating its waters. Regulatory changes act as powerful currents and tides, influencing the direction and pace of this journey. Without these regulatory guardrails, healthcare delivery could become akin to sailing without a compass, risking patient safety and compromising the quality of care.

Guardrails of Patient Safety: Just as guardrails prevent vehicles from veering off dangerous cliffs, regulations establish crucial boundaries to ensure patient safety remains the top priority. They meticulously dictate standards for documentation, medication protocols, treatment practices, and more, guiding healthcare providers toward practices that prioritize patient well-being above all else.

Highway of Delivery: Picture healthcare as a bustling highway, with patients moving along the lanes toward their respective destinations. Regulatory changes shape this highway, determining the speed limits, road signs, and traffic rules governing the journey. By diligently adhering to these regulations, healthcare providers ensure a smooth and safe passage for patients, minimizing risks and maximizing positive outcomes.

Consistent Care Delivery: Envision healthcare as a relay race, with the baton of care being passed from one provider to another. Regulations establish the rules of this race, ensuring that the baton is passed smoothly and efficiently without any hiccups or mishaps. By adhering to these regulations, healthcare providers maintain a consistent level of care delivery, ensuring that every patient receives the same high standard of quality treatment, regardless of where they are on their healthcare journey.

Accountability and Transparency: Regulations promote accountability and transparency within the healthcare system. They require healthcare providers to adhere to strict documentation standards, ensuring that every decision and action is recorded and traceable. This transparency fosters trust and confidence between patients and their care providers, bolstering the crucial patient-provider relationship.

However, the ever-shifting regulatory landscape poses significant challenges, especially for community and physician-owned health systems with varying infrastructures and limited resources. Picture these healthcare institutions as a fleet of ships, each navigating its course through turbulent seas, where fragmented communication and data silos hinder the seamless delivery of optimal patient care.

To successfully navigate the regulatory maze while maintaining compliance and operational efficiency, health systems can employ strategic approaches:

• Embrace Innovation: Foster a culture of innovation within the organization, encouraging the exploration of novel solutions to regulatory hurdles. Streamline processes, enhance data security, and improve patient outcomes by leveraging emerging technologies such as AI and ML.

• Forge Strategic Partnerships: Cultivate collaborative relationships with regulatory agencies, professional organizations, and peer institutions. By sharing insights, best practices, and collective intelligence, health systems can strengthen their compliance efforts and navigate regulatory complexities more effectively through mutual support.

• Prioritize Patient-Centric Practices: Anchor every decision and action into the needs and preferences of patients. Implement personalized care plans, telehealth services, and other patient-centric initiatives to enhance patient engagement, satisfaction, and overall outcomes, fostering a culture of empowerment and partnership in healthcare delivery.

Furthermore, staying informed and maintaining vigilance is paramount in the face of regulatory changes. Just as navigators watch the horizon, healthcare systems must cultivate a culture of continuous learning and proactive compliance monitoring. By proactively anticipating regulatory shifts and mitigating risks, they can optimize their compliance efforts and adapt swiftly to emerging mandates.

In an era dominated by digital innovation, interoperability becomes our guiding compass, facilitating seamless data exchange and communication among diverse systems and stakeholders. Investing in integrated EHR systems is not merely a choice but a necessity, enabling healthcare organizations to navigate the regulatory seas with agility, precision, and foresight, ultimately reaching the shores of greatness in patient care delivery.

Collaboration also plays a crucial role in keeping health systems afloat during regulatory turbulence, providing them with an anchor to stand on during their regulatory journeys. By forging strategic partnerships with regulatory agencies, professional organizations, and peer institutions, health systems can share best practices, learn from collective experiences, and navigate common obstacles together, strengthening their resilience and adaptability.

Regulatory shifts in healthcare profoundly impact physicians, akin to navigating turbulent seas where each wave presents a new challenge. The enactment of legislation like the Health Information Technology for Economic and Clinical Health Act (HITECH) exemplifies this analogy vividly. HITECH’s primary objective was to revolutionize healthcare delivery by incentivizing the widespread adoption of EHRs, promising to usher in an era of enhanced patient care quality and efficiency.

However, the journey towards integrating EHR systems into medical practice was fraught with obstacles. Physicians encountered the daunting task of mastering unfamiliar interfaces and grappling with increased documentation burdens, threatening to disrupt established workflows and patient care routines that had been finely tuned over years of experience.

Dr. Atul Gawande, a renowned author and authority in healthcare compliance and innovation, emphasizes the importance of adopting a strategic and proactive approach to navigate regulatory transitions effectively. In his book, “The Checklist Manifesto,” he advocates for comprehensive training programs, robust support mechanisms, and a culture of continuous improvement to empower physicians in embracing change and leveraging regulatory mandates as catalysts for driving positive outcomes for patients. Through proactive adaptation and a steadfast commitment to excellence, physicians can weather regulatory storms and chart a course toward a brighter future in healthcare delivery.

As we embark on the future of healthcare delivery, let us draw wisdom from ancient mariners and modern navigators alike. The famous American rock band, The Doors, inadvertently suggested the right kind of wisdom applicable to healthcare readiness and ever-evolving regulations—”Keep our eyes on the road and hands upon the wheel”—to “Break on through the other side” of regulatory change with grace and confidence, heading towards an improved health and wellness outlook for all!

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Radiology is an essential part of the healthcare delivery system. Its presence in the clinical setting is steadily increasing year over year as overall healthcare demand increases, new technology is developed, and radiology needs continue to expand. Nationally, radiology has seen consistent annual growth over the last 50 years. This national growth is reflected in local departments, including those I have personally overseen. Additionally, most experts agree that radiology is expected to increase in demand over the next thirty years. With expected radiology growth, maintaining an efficient clinical workflow is imperative to proper operations and patient satisfaction. In my role of overseeing a very large outpatient imaging facility, I was living these struggles. Our department, specifically our MRI modality, struggled with in-efficiencies and throughput issues that reduced volume and sub-par patient satisfaction scores. We sought out on a mission to improve clinical workflows, efficiency, and throughput. But how can anyone achieve efficient clinical workflow in a high volume, hectic and unpredictable environment like ours? For us, leveraging technology was the answer.

We embarked on a journey to find a technology we could use to improve throughput and clinical workflow without any negative impact on safety and quality. This was not an easy task, but something we felt was imperative to the success of our facility. The first task was evaluating what technologies were available in the marketplace and which could work for our needs. Although this part of the process is often undervalued, we understood the importance of the selection process to ensure we chose the technology that would best fit our requirements and set us up for the best possible chance of success. We took our time to evaluate different vendors, perform demos, and talk to our peers to ensure we made the best decision. We settled on a technology that most imaging vendors offer: image acquisition accelerating software for our MRI scanners. Our MRI department was our most utilized modality and had significant challenges with clinical workflows and efficiencies. Therefore, MRI was the perfect place to implement this technology to have the biggest impact on our patients. Implementing this in our MRI department would allow us to perform MRI scans faster with no impact on image quality, ensuring we continue to provide the highest quality images efficiently.

Better is possible. It does not take genius. It takes diligence. It takes moral clarity. It takes ingenuity. And above all, it takes a willingness to try. – Atul Gawande

Once we had identified the technology and appropriate vendor, it was time to purchase and implement.  Proper implementation is critical to success. We created a multi-disciplinary approach to implementation inclusive of clinical (technologist, radiologist, and referring physicians), support staff, local IT staff and vendors. The implementation was methodical to ensure our end users, including technologists and radiologists, were not only trained in proper usage of the technology, but trained in full optimization of the technology. This ensured that staff were confident in the software and systemic in its use.  

Once implemented, we looked at data analytics to monitor the success or evaluate opportunities to improve our process. We utilized key data metrics to see exactly what scans, by specific patient types and specific times where impacting clinical workflows. We then utilized the same metrics post-implementation to validate the value of the technology and its impact on our patients and workflow.  The data was astounding. The data showed that by leveraging technology, we were able to increase our capacity by 28 percent, adding an additional 1,177 MRI studies annually. This increased capacity significantly improved our clinical workflow and efficiency. We were able to increase outpatient satisfaction scores by 40 percent largely due to the significant reduction in wait times created by the improved efficiencies. Lastly, the increased volume added an additional $1 Million annually to our bottom line. With that additional revenue, the return on investment (ROI) was less than a year, making this a true success for the department, healthcare system and, most importantly, the patients we serve.

Leveraging technology to improve key metrics that drive success in your departments makes sense. With the increased use of Artificial Intelligence (AI), we now have a new plethora of options to evaluate and utilize. AI will impact all sectors of life, particularly healthcare. Radiology has been using AI for over thirty years and therefore, can be considered the healthcare trailblazer when it comes to AI. As this technology continues to develop and be utilized, we can better evaluate the beneficial impact on our patients.

The journey to improve our clinical workflow, efficiencies and throughput in a large outpatient imaging center started with a thorough evaluation. Evaluating technologies that work best for our needs and positively impact our patients. Once identified, the systematic implementation was critical in ensuring confident and effective use of the technology. Using data analytics to either validate success or evaluate the opportunity to pivot and adjust after implementation allowed for the flexibility that is indispensable when introducing a new technology. Additionally, with the incremental development and adoption of AI, the technological options available to leverage have increased dramatically. Most importantly, it’s fundamental to ensure that whatever tool you utilize to improve processes within your departments truly impacts the patients and communities we serve. After all, our purpose is to improve the health of our communities and the patients we serve.

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Interoperability enables the exchange of data from different healthcare providers, patients, and other stakeholders to access and share relevant medical information across various platforms and settings, regardless of the system or vendor they are using. Addressing interoperability challenges in healthcare requires a multifaceted approach involving technology, standardization, and collaboration.

What can Stakeholders expect from healthcare interoperable systems?

Interoperable systems enable seamless communication and data exchange among healthcare providers, facilitating better coordination of patient care across different settings and specialties. This leads to more informed decision-making, reduced duplicate testing, and enhanced continuity of care. These systems help reduce errors and adverse events by ensuring that accurate and up-to-date patient information is readily available to clinicians at the point of care, including medication lists, allergies, medical history, and other critical data that can impact treatment decisions and patient outcomes. Interoperability streamlines administrative and clinical workflows by automating data exchange and eliminating manual processes. This allows clinicians to focus more on patient care and less on paperwork.

Interoperable systems enable the aggregation and analysis of healthcare data from multiple sources, leading to valuable insights into population health trends, disease management, and treatment outcomes. Stakeholders can identify patterns, monitor performance, and make data-driven decisions to improve healthcare delivery and outcomes. Interoperable systems empower patients to become more active participants in their healthcare journey by providing access to their health information and enabling communication with their healthcare providers.

Unlocking seamless healthcare: The power of interoperability.

Healthcare interoperable systems often support integration with third-party applications and devices, allowing seamless connectivity and interoperability across the healthcare ecosystem. This includes patient portals, mobile health apps, wearable devices, remote monitoring tools, and telemedicine platforms, expanding access to care and enabling innovative healthcare delivery models.

Key problems with interoperability in healthcare

Interoperability in healthcare faces several key challenges that hinder seamless communication and data exchange among healthcare systems and stakeholders. Some of the key problems include:

Avalanche of Standards: One of the primary barriers to interoperability is the stream of standardized data formats, terminologies, and communication protocols. Variability in data structures and coding systems makes it difficult for systems to interpret and exchange information accurately, leading to interoperability gaps and data fragmentation.

Legacy Systems and Infrastructure: Many hospitals still rely on legacy systems that were not designed with interoperability in mind. These systems may use outdated technologies, proprietary formats, or closed architectures that hinder data exchange and integration with modern interoperable solutions.

Data Privacy and Security Concerns: Healthcare data is highly sensitive and subject to stringent privacy and security regulations, such as HIPAA (Health Insurance Portability and Accountability Act) in the United States. Ensuring secure transmission and storage of patient information while maintaining compliance with regulatory requirements adds complexity to interoperability efforts and may limit data sharing.

Cost and Resource Constraints: Implementing interoperable systems and standards requires significant investments in technology, infrastructure, and personnel. Many healthcare organizations, especially smaller providers and rural facilities, may lack the resources or expertise needed to upgrade their systems and achieve interoperability effectively.

Fragmented Governance and Incentives: The lack of cohesive governance structures and aligned incentives across the healthcare ecosystem poses challenges to interoperability initiatives. Different stakeholders may have conflicting priorities or lack incentives to invest in interoperability, leading to fragmented efforts and slow progress.

Vendor Lock-in and Proprietary Solutions: Some healthcare IT vendors offer proprietary solutions that lock organizations into their ecosystems, limiting interoperability with other systems and vendors. This vendor lock-in creates barriers to data exchange and interoperability, hindering innovation and competition in the healthcare IT market.

User Resistance and Workflow Disruption: Healthcare professionals may resist interoperability initiatives due to concerns about workflow disruption, increased workload, or perceived usability issues with new systems.

Overcoming resistance and gaining buy-in from end-users are critical for successful interoperability implementation and adoption. Following is our hospital’s interoperability expedition:

Implementing Health Information Technology (HIT) Standards for Interoperability: Adherence to standards such as HL7 (Health Level Seven), FHIR (Fast Healthcare Interoperability Resources), and DICOM (Digital Imaging and Communications in Medicine) ensures that systems can communicate effectively with each other. Hospitals must prioritize to assess current state and needs, select appropriate HIT standards and integration engines that act as intermediaries between disparate systems, enabling data translation and communication, develop implementation plans, update policies and procedures, test and validate implementation, monitor and maintain compliance, promote adoption and collaboration of these standards in IT infrastructure.

Promoting Data Governance and Quality Assurance: Establishing robust data governance policies ensures that patient information is accurate, consistent, and secure across different systems. Quality assurance measures help identify and resolve data discrepancies, enhancing the reliability and usefulness of interoperable data.

Training and Education for Staff: Healthcare professionals need to be proficient in utilizing interoperable systems and understand the importance of data exchange in improving patient care. Provide comprehensive training programs to ensure that staff members are equipped with the necessary skills and knowledge.

Engaging in Collaborative Initiatives: Collaboration among healthcare stakeholders, including hospitals, payers, technology vendors, and regulatory bodies, is essential for accelerating interoperability initiatives. Participation in collaborative projects and industry consortia can help hospitals stay updated on best practices and emerging standards.

Continuous Evaluation and Improvement: Interoperability efforts should be subject to ongoing evaluation and refinement. Regularly assess the effectiveness of interoperability strategies, solicit feedback from end-users, and implement improvements based on evolving technology and regulatory requirements.

By addressing these challenges, hospitals can overcome barriers to interoperability and unlock the full potential of connected health information systems to improve patient care and outcomes.

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Before joining Valley Health, I served as the Global CMIO for The Aga Khan University (AKU) and its international network of hospitals. In addition to co-founding and managing a busy internal medicine hospitalist practice, I served as an executive physician advisor for dozens of healthcare systems across the United States and internationally. Appreciating the impact that technology has on people’s lives, I’ve always been a strong proponent of pushing technology to its limits to help improve healthcare. 

In the ever-evolving journey of advancing healthcare, the pursuit of optimizing clinical workflows is riddled with stories of failure and success. Over the years, I have witnessed both success and failure with different hospital systems using the same technology, no matter how fantastical its developers claimed it to be. From grappling with inefficient processes to celebrating breakthroughs in patient care delivery, there are key elements of a healthcare system ecosystem that must be present to ensure ongoing success with clinical workflow optimization.    In and of itself, simply plugging in a new software system into a clinical workflow process does not improve outcomes. So, what are the other main ingredients if technology is seen as a catalyst for improvement? 

The journey to optimize clinical workflows with new technology is not without its challenges, but it is also rich with opportunities for growth and innovation.

In my recent role as the global CMIO for a multinational healthcare network, one of our academic hospital systems, with its busy main campus and over fifty outpatient clinics, embarked on an ambitious initiative to implement a state-of-the-art electronic health record (EHR) system aimed at streamlining clinical workflows and enhancing care coordination. However, despite significant investments in technology, I realized that our efforts would be hampered by several pitfalls:

1. Poorly Defined Governance Structure: Our clinical governance framework lacked clarity and accountability, leading to conflicting priorities and decision-making bottlenecks. Without clear governance structures, key stakeholders would be left feeling disconnected and disempowered, hindering our ability to drive meaningful change. In the past, administrators simply shrugged off busy clinical providers who could not reliably participate in the frequent committee meetings and would make clinically impacting decisions without them.
   
   
2. Lack of Clinical Engagement: While the EHR system promised to revolutionize how care was delivered, its adoption was initially hindered by a lack of buy-in from frontline clinicians. Without their active participation and feedback, the system would fail to align with existing workflows, resulting in frustration and resistance.
   
   
3. Absence of a Clinical Informatics Team: Another critical factor contributing to our struggles was the absence of a dedicated clinical informatics team. Without experts to bridge the gap between clinical workflows and technology solutions, we would face significant challenges in optimizing system functionality, providing user support, and driving user adoption. Understanding the end-user component is best done by having a dedicated team of experienced end-users developed into a core team of clinical informaticists.

With my prior experiences working with almost two dozen other hospital systems, it was generally accepted that any major effort to improve clinical workflows requires executive sponsorship and likely investment in IT infrastructure and resources; and such was the case at my organization. However, as frequently experienced, dealing with the three factors above was under-appreciated and alarmingly, at some organizations, actively discouraged! As CMIO, it was my mission to have these key factors addressed immediately. Despite the setbacks encountered along the way, our organization evolved, learning valuable lessons from past failures and leveraging them to inform our approach going forward. Through a concerted effort to foster innovation and collaboration, we ultimately achieved success with key initiatives:

1. Establishing Clear Governance Structures: We revamped our clinical governance framework, establishing clear lines of accountability and decision-making authority.  Committee membership included technology support leaders, clinical end-user representatives, and administrative leadership. This enabled us to align our initiatives with organizational goals, streamline processes, and ensure that resources were allocated effectively to support our strategic objectives. 
   
   
2. Engaging End-Users from the Onset: Recognizing the importance of clinician input, we actively involved frontline staff in designing and implementating technology solutions. We fostered a culture of ownership and empowerment by soliciting feedback and tailoring our approach to meet their needs, driving widespread adoption of new workflows.
   
   
3. Building a Dedicated Clinical Informatics Team: Perhaps the most transformative step we took was the establishment of a dedicated clinical informatics team. Comprising expertise in healthcare IT, workflow analysis, and user support, this team played a central role in optimizing system functionality, providing user training and support, and driving continuous improvement efforts.

With the formation of end-user workgroups led by our clinical informatics team, we were able to solicit feedback, identify targeted training and support, and leverage the expertise of our clinical informatics team to ultimately achieve widespread acceptance and adoption. Our hospital went live with the new EHR system with almost 100% clinical adoption. Seemingly overnight, we successfully transformed our healthcare organization into an integrated health data ecosystem, which would further enable data-driven analytics for ongoing clinical workflow optimization, as well as education and research. This journey of clinical transformation served as a catalyst for cultural change, reinforcing the importance of collaboration and teamwork between all the various departments.

The journey to optimize clinical workflows with new technology is not without its challenges, but it is also rich with opportunities for growth and innovation. By reflecting on past failures and successes, we gain invaluable insights that inform our approach to driving meaningful change in healthcare delivery. Through a combination of cohesive governance, end-user engagement, and dedicated support, we can successfully apply innovative technologies to help navigate the complexities of workflow optimization with confidence, ultimately improving patient outcomes and advancing the mission of healthcare excellence.

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Introduction

AI is rapidly becoming a game changer with its next generation technologies in improvising clinical workflows, promising enhanced diagnostics, personalized treatment plans and optimized healthcare operations. From automation in diagnostics to predictive analytics, AI has the potential to revolutionize every aspect of patient care delivery.

AI can mean different things, from specific kinds of AI, like machine learning, to the possible AI that has awareness and feelings.

AI in Clinical Diagnosis and Decision-Making

The use of AI algorithms is quite versatile in automatic diagnostics of different diseases simply by analyzing medical images like X-rays, MRIs, and CT scans. These AI systems can now discover patterns and anomalies that may not be visible to the naked eye. It leads to detecting cancer, cardiovascular problems and also neurological disorders earlier.

AI in breast cancer diagnosis is one of the common instances. AI algorithms have been built that can read a mammogram and detect cancers with a high accuracy, often better than human radiologists. For example, an AI system has been able to detect cancer of the breast with 90% accuracy, which is more than 87% compared to radiologists.

AI will be the challenge of humans who should show wisdom and willingness to define the AI’s role in twenty-first-century healthcare and to determine when AI helps humanity and when it hurts it.

AI clinical decision-support is a kind of medical application, which is based on the integration of big data and machine learning (ML) to give personalized medical advice. Employing patients’ data, including history of illness, genetics and determining the response, is the AI system that recognizes risk factors, predicts outcomes and provides personalized treatment plans. The AI breaking into electronic health records (EHRs) is a source of data upload, input and retrieval. It is also an analysis that helps healthcare providers in making decisions and this can be done quickly.

“AI will transform the healthcare sector, particularly diagnosis in the field of medical imaging.”

AI in Treatment Planning and Delivery

AI provides automated dosage calculations and medication management through algorithms that determine the most suitable dosages for patients based on their unique features and medical history. By having automated calculations, AI contributes to reducing the risk of dosage errors committed by people, helping to guarantee that patients are given the exact medications in adequate amounts. 

AI-empowered robotic systems are driving a paradigm shift in surgery through increased accuracy, stability, and reduced people mistakes during surgeries. These robotic systems help surgeons see better and enter into areas of the body that are impossible to reach for normal human beings, thus making it possible to conduct further complicated surgeries using a minimally invasive approach.

AI-infused wearable devices and sensors allow healthcare providers to monitor patients at a distance and provide telehealth services by gathering continuous data regarding patient’s health status and intervening with this data as needed. These gadgets can track or measure vital signs, activity level, drug compliance, and other health metrics and give experts a way to control patients remotely.

A world-renowned company in cancer treatment technologies, has introduced an AI-powered treatment planning product. This product employs machine learning (ML) algorithms to design effective radiation therapy treatment plans based on patient’s past information, thereby substantially reducing planning time and degrees of inaccuracy.

AI in Clinical Workflow Optimization

AI can, in many ways, speed up insurance claims and billing processes through automating the verification of insurance coverage, accurately coding medical procedures, and submitting claims to the insurance company. AI algorithms can utilize medical records, treatment codes, and insurance policies for claim processing and ensure the accuracy that may lead to claim denials or delays.

AI predictive analytics plays a major role in forecasting patient volume, staffing needs, and healthcare facilities as far as resource allocation is concerned. By investigating historical data, patient trends, and external factors, AI algorithms help to predict future demand for health services. Thus, healthcare organizations can reallocate staff, optimize resource usage and improve operations planning.  
For instance, a leading AI-based workflow solution is capable of automating and optimizing several radiology workflows. It deploys machine learning (ML) for automating functions such as image work, finding lesions and report creation, improving radiologists’ efficiency and productivity.

Challenges and Considerations

“AI will be the challenge of humans who should show wisdom and willingness to define the AI’s role in twenty-first century healthcare and to determine when AI helps humanity and when it hurts it”.

The key challenges and considerations in implementing AI in healthcare, including data security and privacy, are the most essential aspects of consideration, as patient’s data can be leaked and AI processing these data leads to the loss of patient trust. In addition to adopting regulations like HIPAA, clinical settings must guarantee the secrecy and safety of private patient information. Clinical decision-making entails the ethical use of AI in AI deployment, which is also a very complex issue. The visible and honest ways of reaching the decision by AI systems must be guaranteed, and it is important to get rid of bias and prevent unfairness in such scenarios to avoid discriminating results. The complex integration of AI technologies into the present healthcare system and workflow flows is the key technical and organizational problem to resolve. Interoperability between AI systems and EHRs gets involved in effective and integrated healthcare provision.

Conclusion

Finally, the use of AI along with clinical workflows presses several benefits in providing patients the best care, improving operations, and advancing medical outcomes in the long run. Yet, the challenges that need to be thoroughly considered are data security, ethical issues, and systemic integration. These are vital factors that must not be disregarded in order to fully harness AI in healthcare.

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A baby girl comes to the pediatric ophthalmologist. She bounces happily in her mother’s lap but has a pronounced crossed eye. Infantile esotropia is usually a surgical condition. However, there is always a small chance of an underlying neurologic cause. The doctor asks questions about onset, progression and family history, then finds an otherwise unremarkable exam. The risk is of a brain problem is low, but how low? Is the next step surgery or an MRI?

Similar questions play out in doctors’ offices thousands of times every day. Artificial intelligence (AI) is suddenly everywhere these days, and the hype keeps building. For healthcare, an industry under constant pressure to do more with less and do it better, AI seems like the right tool at the right time. Can we use this technology to help us do a better job caring for our patients?

In the broadest sense, AI is a computer-driven supplement to human decision-making. With alerts built into our electronic medical record (EMR), we have been using this type of AI for years, although most would agree that these alerts are not very intelligent Artificial Intelligence. Recently, Large Language Models (LLMs) have achieved the success that had seemed years, if not decades away. LLMs work by predicting the next word in a sentence, and when given a hugely sophisticated algorithm and essentially all the data on the internet, they can produce output that feels very human-like. At MultiCare, a twelve hospital healthcare system in Washington State, we have been focusing a how to use this seemingly magical technology to improve performance.

We have heard the promise of technology in healthcare before. A dozen years ago, healthcare systems across the country adopted EMRs in response to the HITECH Act and Meaningful Use. Things did not go as planned. While most clinicians would not go back to paper charts, the EMR came with unintended consequences and unfulfilled promises, including the promise to help doctors make better decisions. This is exactly where AI could help. But before we rush to incorporate AI into clinical workflows, we should apply the hard-earned lessons we learned from EMR clinical decision support (CDS) implementation.

For one thing, it is not enough for an AI to be “right”. While it is impressive to see LLMs pass standardized medical exams, this alone does not make them helpful. For AI to add value and help phycians (rather than replace them) the AI must be correct when the clinician would otherwise be wrong. While we certainly make mistakes, we usually get  things correct. Many EMR alerts are overridden more than 90% of the time and do little more than create a cognitive burden. If a busy doctor sees too many “I already know that” suggestions from an LLM, they will click right through them.

We don’t need AI to tell us what we already know. What we need is an AI to give us the information we need to do a better job.

Further, making a medical diagnosis is more than finding a single correct answer. Early in the process, what matters is generating a reasonable list of possible diagnoses—a differential diagnosis—and then working through that appropriately. Improving this process could reduce medical errors since doctors will not work up what they do not consider.

While premature closure is a concern, common problems are, well, common. Generating a lengthy differential is a medical student game. When the condition is straightforward, working through an exhaustive list with the extra labs and imaging studies that entails could unnecessarily increase cost and documentation burden. Again, the question is not whether the AI is right, but whether it adds value.

What could be helpful is an AI to help us identify those uncommon diagnoses we otherwise would have otherwise missed. But the laws of statistics make it hard to predict rare events. When the probability of a diagnosis is very low, even an accurate test still results in many false positives. When an AI tries to predict rare diagnoses, we can expect a lot of useless alerts, which could even be harmful if they lead to unnecessary invasive tests.

There are some ways AI could help. One is as a consultant: “Hey AI, can you read this patient’s chart and see if I’m missing anything?” Rather than firing unhelpful suggestions, an on-demand AI might add value in situations when a doctor is uncertain. The doctor would need to think to ask the AI, and once the novelty wears off, they would need to get valuable insight consistently, not just recommendations to order more low-yield tests.

AI, in its current form, may struggle to add value, but it will not be in its current form for long. One active area of development is retrieval augmented generation, where the AI uses its understanding of language to query a separate data source. Rather than just a differential diagnosis, LLMs could find information on the appropriate work up of a condition and the cost of each test. Knowing the most cost-effective way to work up a problem, one that minimizes both cost and risk to the patient, would not only help us provide better care, but improve efficiency. Instructing the LLM to limit its responses to data in the database could even reduce the risk of hallucinations. We don’t need AI to tell us what we already know. What we need is an AI to give us the information we need to do a better job.

Doctors do not routinely access risk and cost databases, but the data are there. The limiting factor has been integration into clinical workflows. LLMs, with their ability to make sense of clinical scenarios, may be the bridge that allows doctors to make truly informed clinical decisions. The real benefit of AI may come not by supporting current processes, but by helping us do things differently and better. What is the risk of a brain problem in a baby with strabismus? The doctor and family may be able to make a data-driven decision.

The post There’s a Thin Line Between Copilot and Backseat Driver: What Informatics Can Tell Us About Healthcare AI appeared first on HealthTech Magazines.

Helping Hospitals Get Measurable ROI from Technology

Ascom’s expertise focuses on improving workflows in acute care hospitals and long-term care facilities. The company’s products are used in more than 46% of teaching hospitals in the U.S., and Ascom systems handle more than 800 million alerts every day. The Ascom Healthcare Platform (AHP) encompasses four key areas – nurse call, mobile devices, software and professional services. When customers standardize on the AHP portfolio, they realize the compounded benefits of Ascom’s comprehensive solutions, which are configured to their unique needs; however, being vendor neutral, the AHP also offers the flexibility for customers to integrate Ascom with other vendors’ solutions. Ascom’s solutions enable customers to implement important capabilities, from clinical surveillance with medical device integration (MDI) and clinical decision support, to remote patient monitoring of medical devices, and smart alarming and alerting.

David Gutillo, Director of Field Marketing Innovation in Healthcare at Ascom Americas, believes Ascom and its products are poised to become the enabling platform to which medical devices and systems in a hospital connects, and this will help shift the model to proactive, predictive care.

“We’ve designed our solutions and services to be highly configurable while also supporting standards and best practices to help hospitals meet their goals, whether it be increasing quality of care, reducing nursing turnover, improving patient outcomes or otherwise.”

We bring data to life. Every single second, Ascom systems generate 1.3 million data points, so making sense of all that information is extremely important for clinicians.

Powering Clinical Insights with Ascom Clinicians

The Ascom Healthcare Platform provides the clinical communication and workflow orchestration tools needed to meet a variety of challenges. Our team of veteran clinicians working directly with hospital staff in designing and optimizing workflows, makes a difference in deploying effective solutions that are truly force multipliers. Ascom Americas’ Clinical Application Specialist Kenneth Catoe states that the clinical data analytics team helps hospitals better understand the information their technology is generating by analyzing it and consulting with customers to improve care quality. Because hospitals are dynamic environments this service helps them manage the changes with actionable and goal-oriented insights.

“We bring data to life. Every single second, Ascom systems generate 1.3 million data points, so making sense of all that information is extremely important for clinicians”, Catoe shares. He goes on to add, “When we’re consulting on workflow design, we’re trying to look at the entire picture, from the data our systems are generating and taking other data into account too. Then we combine data analysis with what we’ve seen and learned onsite along with our clinical expertise to provide recommendations for improvements.”

Fellow Ascom Americas clinician Huyen Cam notes that, “This process of identifying areas for continued improvements helps hospitals meet their KPIs, whether it’s being more efficient with nurses working at their top of license to discharging patients faster and increasing throughput.”  

Empowering Customers with Solutions That Make a Difference

Ascom solutions are making a difference for customers. For example, RiverSpring Living, a senior living facility in New York, is using the complete AHP, beginning with implementing the Ascom nurse call system. Staff use an Ascom Myco smartphone to receive alerts from Ascom’s Unite software, so as soon as a resident presses the nurse call button, staff can respond immediately. During the first year of operation, RiverSpring Living processed more than 90,000 alerts and answered 95 percent of calls in less than two minutes. This ROI is making a difference in both resident and nurse satisfaction. 

In another example, Ascom’s Unite software solution helped a Southern California Hospital experience a 32% reduction in alarm notification messages sent to caregivers through basic filtering rules. By using a 10-second alarm filtering delay, the hospital saw a 38% reduction in alarm notification. This improvement resulted in smoother, more efficient workflows and made alarms more actionable and relevant.

A Complete Provider for Clinical Workflow Solutions

Ascom offers a full range of services through its network of more than 150 partners and 2,000 technicians to help hospitals realize the benefits of Ascom solutions. Technical services include plans for hardware repair, software upgrades and technical support as well as remote monitoring of a customer’s IT infrastructure connected to the AHP.

Delivering Continuous Innovation and Sustainability

A five-point strategic plan guides Ascom Americas and its regional leadership team, consisting of Kelly Feist, Managing Director; Corrado Grieci, Vice President of Sales; Tom McKearney, SVP Business Development and Marketing; Michael Augusti, Head of Market Innovation; Nancy Duffy, Finance Head; Robert Wittwer, SVP Professional Services and Chris LaFratta, SVP, Customer Success. For the near term, Ascom is delivering against four strategic pillars to accelerate growth and performance. Continuous innovation underpins this focus to further embed Ascom as a critical infrastructure at the center of delivery of care in the acute care environment. Over the longer term, many of Ascom’s solutions will continue evolving to become a cloud-native platform while enhancing MDI, alarm management, clinical collaboration, and augmented intelligence capabilities. Smart Nurse Call will evolve with enhanced software and hardware capabilities, and better designs will streamline installing and configuring them. With the Ascom Healthcare Platform, the future for clinical workflow technologies that help hospitals solve some of their biggest challenges looks bright and laden with opportunity.

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