Readers Write: Harnessing the Full Potential of AI in Healthcare Requires Carefully Prepared and Clean Data

Harnessing the Full Potential of AI in Healthcare Requires Carefully Prepared and Clean Data
By Brian Laberge

Brian Laberge is solutions engineer at Wolters Kluwer Health.

Artificial intelligence (AI) implementation in healthcare is gaining more and more traction. However, messy data can lead to challenges in training these platforms and helping uncover bias to ensure they offer the most impact. With 80% of healthcare data existing in unstructured formats, there’s often an extra step required to map these insights to more structured standards, enabling AI algorithms or large language models to parse through the information and distill takeaways in a clear and comprehensive way.

As the saying goes, garbage in means garbage out with these platforms. To fully embrace large language models in healthcare and capitalize on the opportunities for AI, it’s important to acknowledge the data quality challenges to overcome and tips for maintaining clean data for optimal use of advanced technologies.

When considering the use of AI in healthcare, there are two phases to consider — the training of the technology and the implementation and insights that will ultimately be delivered. When thinking about training the technology, one of the biggest challenges with healthcare data in particular is consistent data quality and accuracy. With multiple standards across healthcare, and valuable information stored in unstructured fields, it can be difficult to map insights from one care setting to another and ensure that data doesn’t lose meaning amid these bridges.

Additionally, lab or medical data often comes back with portions incomplete, inaccurate, or lacking validity, which skews the data from showing AI models the full picture. Adding further complexity, physicians often use different clinical verbiage to mean the same medical term. All of these data quality issues can result in a hallucination, where the model perceives a pattern that doesn’t exist, which results in made-up, incorrect, or misleading results. Knowing what those synonymous phrases are and being able to address them when training new models or tuning an existing large language model can help increase accuracy.

Another challenge comes from deciphering clinical notes. When you get a mix of data, these notes need to be extracted and properly codified to an industry standard. If this process cannot be completed, it’s often recommended to exclude them, as the data will lead to noise and bias within the AI models. This gap could represent a huge loss of insights that could be incredibly impactful for patient care and outcomes reporting.

In general, human error, or simply the large amount of disparate verbiage used in healthcare, doesn’t always translate easily for a uniform standard to train AI. In order to avoid this, healthcare organizations should make sure they have tools or processes in place to assess the quality of their data, clean their data, and standardize it before implementing LLMs.

Though it can be challenging to fully prepare data before training an AI model, it’s imperative to ensure that future AI use and insights are purposeful and accurate. It can be dangerous to train an AI with messy data for a number of reasons. Missing, incomplete, or incorrect information can reduce the accuracy and insert bias, which could lead it to infer incorrect assumptions that are then built into the core of the model.

Additionally, low quality or overly simplified data for minority populations could cause a bias to be built into the model. In data, race and ethnicity often are jumbled together. Sometimes, because of biases within the healthcare system itself, there is not as much data for certain groups compared to another. While addressing those care gaps is a much larger discussion, staying ignorant about the fact that the data gaps exist is also dangerous.

For example, if you are building a model to predict the most effective drug for a patient based on historical administration of various drugs, and the data used to train the model has data quality issues with race, then it is more likely not to detect a situation where a drug is more effective for a particular race and would result in a bad recommendation.

Maintaining the data, including knowing where the gaps are, and evaluating training data to address these gaps is a challenge. However, it’s essential to address from the get-go as bias or inaccuracy in the model will make the system harder to use, and ultimately, these biases will then be intrinsic to the AI platform and future insights.

Integrating data, particularly high-quality data, is proven to save hospitals money and reduce risks to compliance and industry standards. There are six core elements to maintaining data quality that organizations should consider when preparing to implement AI tools:

• Accuracy is important in reflecting the true outcomes of healthcare.
• Validity assesses the appropriateness of the data to support conclusions.
• Data integrity ensures the reliability of the data.
• Having complete data helps to identify any possible gaps within the data set.
• Consistency is important to maintain uniformity across the set.
• Timely data helps to harness the full potential of the data for meaningful actions.

All of these qualities will strengthen the data and create an easier AI implementation with less room for error.

While maintaining clean data for use by advanced analytic platforms can be challenging, there are steps that organizations should take to keep data ready for use in AI models. First, it’s important to have a strong data governance process to ensure accurate data, and to decipher good versus bad data before feeding it to an AI model. It’s also important to verify lab results against the appropriate codes to eliminate errors and incorrect codes being built into the model. We have found in one data set that the data quality was as low as 30% accurate as it contained invalid codes and incorrect codes for the labs.

Ensuring alignment of data, and validating codes to an industry standard, will help to streamline the process. The richer the data used to train the AI, the better the outcome will be. Normalizing and mapping the data can help to streamline data from multiple sources and authors. Mapping the information ensures accuracy in the data and helps break down any discrepancies between sources.

Lastly, constantly assessing and ensuring an understanding of data from the team that is responsible for training the model will help to identify gaps or potentials for biases within the data itself. It’s important for the team that is training the model to work with their data governance colleagues to ensure that they are aware of any missing data, such as gaps in lab results and member data, to remedy these gaps for more complete quality measure reporting.

By implementing these best practices, data can be properly utilized to its full potential to inform decision-making, increase quality, and enhance patient care.

Healthcare data can be messy, but creating a process where the data is properly assessed and cleaned can be beneficial in so many ways beyond AI. It’s encouraging to see an industry that has historically moved slowly be so eager to adopt new technologies. While the opportunity for AI use in healthcare is great, we can’t forget the basics of data quality that are essential in determining the future success of these platforms. With this process, organizations can make better use of AI and ensure the most accuracy in their models to help better serve patients.

Readers Write: The Uncomfortable Truth About Healthcare Data

The Uncomfortable Truth About Healthcare Data
By Mike Green

Mike Green, MBA is chief information security officer of Availity.

Cyberattacks have become an all-too-common occurrence, with no industry immune from their effects. In healthcare, the stakes have reached unprecedented levels, with the FBI recently identifying the sector as the top ransomware target.

Consider that in 2023, healthcare data breaches that impacted 500 or more records were reported to the Department of Health and Human Services (HHS) Office for Civil Rights (OCR) at a rate of 1.99 per day. The results of that equate to a whopping 364,571 healthcare record breaches every day and 133 million records exposed or impermissibly disclosed in 2023 alone.

Data like this, combined with lessons learned from previous cyberattacks, reveal the uncomfortable truth that healthcare data is increasingly vulnerable. Hardware, software, and the information that runs through it are more interconnected than ever. The vital nature of healthcare’s digital infrastructure, combined with increased cyber threats, magnify the vulnerability of this connectedness further.

Reflect on this year’s example in which a major clearinghouse experienced one of the worst cyberattacks in the history of the US healthcare sector, affecting up to one-third of the U.S. population. What makes this incident stand out is the company’s crucial role as a healthcare clearinghouse.

As digital super-highways, healthcare clearinghouses connect the healthcare ecosystem, routing billions of electronic transactions between health plans and providers and streamlining administrative processes that are associated with claims, prior authorizations, and provider payments. Yet today, under HIPAA, the closest thing to an information security standard is a catch-all “reasonable efforts” expectation. Such a standard, or lack thereof, was wholly inadequate to protect hundreds of thousands of providers and millions of patients across the interconnected healthcare landscape from this unprecedented cyberattack.

Members of Congress have caught on, announcing the proposed Health Infrastructure Security and Accountability Act in late September, which aims to direct HHS to craft a new set of minimum cybersecurity standards for healthcare providers, health plans, clearinghouses, and business associates. As calls for change such as this highlight, to truly improve cybersecurity across the US healthcare system and prevent this from happening again, the industry—and clearinghouses in particular—must do more to safeguard and swiftly recover with minimal disruptions.

The following best practices can help bolster cybersecurity posture and speed recovery time for healthcare organizations that are impacted by attacks.

• There is a pressing need to establish mandatory cybersecurity standards for all clearinghouses. The days of “please see attached HITRUST certification” are gone. That is simply not enough, and the false sense of security provided by these certifications is dangerous. These standards should be updated regularly to address evolving threats. Clearinghouses should be required to disclose the scope of their information security programs and demonstrate compliance with highly specific security standards, such as the US Defense Information Systems Agency Provisional Authorization Impact Level 2 (DISA IL2), which maintains cloud computing security requirements and the National Institute of Standards and Technology SP 800-171, a standard for safeguarding sensitive information on federal contractors’ IT systems and networks.
• Clearinghouses should also comply with SOC-2, a security framework that was developed by the American Institute of Certified Public Accountants (AICPA). SOC-2 specifies how organizations should protect customer data from unauthorized access and is built around five Trust Services Criteria: security, availability, processing integrity, confidentiality, and privacy. Not all healthcare organizations comply with SOC-2 criteria. Clearinghouses should be required to fully implement these cybersecurity standards, adjusting criteria over time to keep pace with evolving threats.
• It is crucial to implement stringent disaster recovery and business continuity standards. These standards should include annual reviews by boards of directors and mock cyberattack exercises to ensure preparedness. Clearinghouses must demonstrate the capability to recover from disruptions swiftly, with recovery times measured in hours and days, not weeks and months. Moreover, Recovery Time Objectives and Recovery Point Objectives should be shared with clients annually, with these metrics audited by credible third parties.
• Streamlining the administrative processes for providers is also essential. Simplifying and standardizing the enrollment process for electronic data interchange (EDI) with Medicare and Medicaid will reduce redundant requirements and enhance efficiency. Establishing a unified, automated EDI enrollment system across all Medicaid and Medicare programs will further ease the administrative burden on healthcare providers, saving time and money while ensuring the ability to run practices through a disruption of service to the primary clearinghouse.

While there’s no one-size-fits-all solution to addressing cyber threats in healthcare, the establishment of such clear standards and accountability measures can help better ensure the resiliency and security of the entire digital infrastructure. Strengthened cybersecurity practices can also instill confidence in the integrity of the healthcare ecosystem, which connects patients, providers, payers, and other stakeholders alike.

Readers Write: Healthcare Knows Everything About Patients, But Can’t Keep Them Engaged

Healthcare Knows Everything About Patients, But Can’t Keep Them Engaged
By Carrie Kozlowski

Carrie Kozlowski, OT, MBA, is co-founder and COO of Upfront Healthcare.

Part of what I love about leading a growth-stage health tech company is the chance to jump between worlds. From big-picture “how might we” brainstorming with innovators to in-the-trenches problem-solving with the health system leaders responsible for delivering patient care — I get to see healthcare from both sides.

The problem is, they often remain siloed. While there’s no shortage of ideas about how to solve healthcare’s biggest problems, teams on the ground are barely staying afloat in managing the day to day, let alone implementing big fixes. The industry as a whole gets stuck operating the same way it did 20 years ago.

That’s the paradox that has been on my mind since I spoke at South by Southwest earlier this year, when I addressed an audience of innovators about the future of data-driven care. That is an area of healthcare where the disparity between what we could do and what we do is striking. My co-presenter and I explored why 97% of all data produced by hospitals each year goes unused, even at the expense of transforming healthcare for the better.

Think about how much healthcare providers know about us. Our doctors know our kids’ names, when they were born, what we do for a living, when our schedule is usually free for appointments, and the likelihood that we’ll cancel last-minute. With this much information, healthcare should be creating incredibly personalized patient experiences, but is falling behind.

Healthcare leaders have an incredible amount of data at their fingertips. As an industry, it’s uniquely positioned to understand who consumers are, how they behave, and what services they still need.

I use the word “consumer” intentionally. No matter how healthcare is perceived, patients are consumers and healthcare enterprises are competing for their business. Patients are making consumer decisions, and these decisions hinge on factors like marketing, convenience, and personalization.

If healthcare made the most of its data, health systems could be running tailored engagement programs that are capable of predicting patients’ actions, speaking directly to their needs, and driving better outcomes across the entire healthcare industry to deliver on the promise of patient-centered care. That’s what’s at risk when it comes to data-driven care. Not just efficiency, but long-term success for patients and enterprises alike.

The average hospital produces 25 trillion pages of data each year. Healthcare’s data collection is growing at a staggering annual rate of 36%. That’s 11% faster than media and entertainment.

Not only is the data vast, it’s also accessible. Health systems already have patient information, collected safely and stored securely with no new data collection processes needed. They know about patients’ jobs, families, and modes of transportation. They know if they need translation services and if they have a history of canceling appointments at the last minute. In other words, they have the exact kind of consumer data to make healthcare more convenient, accessible, and effective.

While Netflix and TikTok use their consumer insights to engage viewers for hours each day, healthcare has so far failed to capitalize on patient data. The industry is sitting on a treasure trove of consumer insights, but they’re going unused. As a result, only 8% of patients complete all the screenings they need in a given year. Ignoring healthcare data isn’t just inefficient, it’s reckless.

It’s easy to point to the healthcare industry’s resistance to change as the problem, but we can be more specific. Let’s look at the challenges one by one.

• Privacy concerns. The words “patient data” often carry with them the fear that a health system will somehow violate a patient’s privacy. Patients might worry that their data will be used against them, preventing them from getting insurance, causing issues with their employer, or otherwise introducing bias into their care. The truth is that HIPAA already forbids this kind of unethical data use. When I talk about leveraging patient data, what I mean is taking the information patients have already willingly handed over and using it to improve their experience dynamically and securely.
• Fear of litigation. We’ve all heard healthcare described as a risk-averse industry. This makes it sound like individual healthcare leaders aren’t open to new ideas. What it really means is that healthcare lives and dies by compliance, sometimes to a fault. It’s worth a conversation about the difference between reasonable precautions and completely overblown fears. The concept of leveraging patient data might feel new, but the data itself is not. It’s already been collected and is being stored securely by health systems. The next step is as simple as using what’s already known about patients to make more practical decisions.
• Deficient tools. Patient data is available now, but that doesn’t mean that it’s easy to access or interpret. Health systems are burning money and human capital on often redundant or cumbersome software platforms. If these platforms don’t play well together, there’s no guarantee that they will produce useful insights on demand.

In many cases, these tools could be stripped back and replaced by one or two patient engagement solutions that integrate with the rest of a robust software suite. We don’t need a separate platform for every point of data collection. Instead, look to HIPAA-compliant engagement tools that speak directly to market-leading EHRs, which allow a bidirectional flow of patient data to empower truly personalized outreach.

Healthcare already has the ingredients to change how patients access and experience care. The challenge is actually making that happen, with data at the forefront. In an industry that is understandably reluctant to change, healthcare pioneers will be looked toward to lead adoption. Once processes are built around patients instead of bureaucratic restrictions, the foundation will be laid for a whole new era of healthcare, one in which care is personalized, patients are engaged, and data leads the way.

Readers Write: EHR Due Diligence: Five Questions That Could Save Millions

EHR Due Diligence: Five Questions That Could Save Millions
By Kem Graham

Kem Graham, MS is VP of sales for CliniComp.

Electronic health records (EHRs) have become an indispensable tool in healthcare today. As hospitals and health systems navigate the complex process of selecting an EHR vendor, avoiding hidden costs and ensuring transparency are paramount. Here are five key questions to consider when evaluating EHR vendors to maximize ROI, maintain workflow continuity, and achieve overall success.

1. How transparent is the cost breakdown?

With budgetary constraints more challenging than ever, it’s crucial to identify all contract elements comprehensively. Seek a detailed account of software, hardware, and services components, including costs for data migration, staff augmentation, medical device interfaces, and interoperability. Validate the scope of implementation, configuration, and ongoing support services. Determine any third-party costs that are not covered by the EHR vendor and confirm if there are monthly service support limits. Identify whether your organization will be billed by volume or a fixed cost solution and determine the total cost of ownership from contract signing to renewal.

2. Is the system adaptable and interoperable?

Look for an architectural framework that addresses evolving challenges in interoperability, scalability, and real-time performance data. The system should provide a comprehensive longitudinal patient record that can seamlessly cross multiple sites and environments, adapting to changing data needs over time. Seek a solution that can normalize disparate data sources for seamless interoperability, meeting both current and future innovation requirements.

3. How will it impact staffing?

Organizations often underestimate the staff that is required for EHR implementation and ongoing system management. With persistent clinical and IT staffing challenges, it’s important to understand a vendor’s staffing requirements and support services. Consider whether the new system offers a robust, out-of-the-box solution that can be customized, and how it will affect current clinical, administrative, and financial workflows. Look for a reliable and integrated system that is intuitive and user-friendly, built by clinicians for clinicians, with 24/7 end-user support to minimize the burden on staff.

4. Is System and medical device integration included?

Data migration and integration among systems, devices, and other technologies are critical components that can sometimes be costly add-ons. Understand exactly what elements are included, whether there are limitations around the EHR system’s technology, and what additional costs may be incurred to bridge those gaps. Consider future integration costs as well, such as migrating to different medical devices or vendors. Confirm that the EHR vendor does not limit the hospital’s options.

5. How will operational disruptions be mitigated?

Not all EHRs require downtime for scheduled updates, security patches, and upgrades. Seek a solution that delivers 100% uptime for maintenance, upgrades, and unplanned incidents. Investigate the vendor’s history to understand their experience in avoiding clinical dissatisfaction, poor patient care, and financial losses due to system downtime.

Choosing an EHR system is a pivotal decision with far-reaching implications on both the clinical and operational fronts. Trust and transparency are essential in fostering a successful relationship between the vendor and the hospital system. Healthcare organizations with a complete understanding of both upfront and long-term investments, including impacts on staff satisfaction, workflows, and patient care, will have the most satisfactory outcomes throughout the EHR acquisition, implementation, and utilization process.

The vendor’s success should be defined by the hospital’s success, reflecting a true partnership where the vendor acts as an extension of and integrates seamlessly into the organizational team. Transparency from the outset, and exploring all options, such as the comprehensive system as a service model, will set the system up for success for years to come.

Readers Write: AI is Here to Stay, So Don’t Miss Out on the Opportunity

AI is Here to Stay, So Don’t Miss Out on the Opportunity
By Greg Miller

Greg Miller is VP of business development at Carta Healthcare.

AI is going to take all of our jobs. At least that’s the impression one would get today from far too many media outlets. Alas, blatant scare-mongering works and generates advertising revenue.

We’ve talked recently with dozens of health system technology decision-makers who acknowledge that artificial intelligence (AI) can make their organizations more efficient and cost-effective. Yet some worry that AI will replace their employees. This isn’t just another concern; it’s the top concern that we’ve been hearing.

The prospect of losing valued employees to technology is one kind of AI-related anxiety among healthcare professionals. There’s also fear of missing out (FOMO). Healthcare IT pros are under heavy pressure from leadership to do something with AI or risk being left behind. However, these healthcare veterans have heard it all before about why they must implement a certain technology to keep up with competitors or face imminent doom. No wonder many have become immune to marketing hype.

Whether you’re in the fear of AI or FOMO camp, AI is happening with or without you. Provider organizations that fail to implement an effective AI strategy will struggle as their understaffed workforces become deeply buried under a backlog of clinical administrative tasks. As more healthcare data is generated and jobs go unfilled, healthcare organizations that lack AI capabilities won’t be able to keep up with clinical documentation.

But while many provider organization leaders fear that AI will replace humans, healthcare workers are more likely to welcome the assistance that AI can provide. In a survey from earlier this year, 77% of responding healthcare workers said that emerging technologies like AI could be useful in combating the healthcare staffing shortage.

AI implementations can optimize the return on investment for hospitals and health systems while providing a blueprint for future successful AI initiatives. There are pragmatic and safe ways for provider organizations to apply AI today that are affordable and designed to ease the administrative burden for clinicians.

One good example is using ambient listening to perform clinical documentation tasks. Physicians typically spend between 30 and 90 minutes at home completing clinical administrative work that they couldn’t finish during office hours. Ambient listening functionality can perform these essential clinical documentation tasks, improving efficiency and accuracy while vastly reducing clinician workloads and burnout.

Another strong use case for AI in healthcare is abstracting data from electronic health records (EHRs). On average, it takes an abstractor one hour to finish abstraction work for a single case. That’s a lot of costly time. In contrast, the right AI technology can perform abstractions for thousands of cases in minutes. Can a hospital or health system afford to pass up this opportunity?

It’s important to know where AI fits into your provider organization. AI is a tool and part of a process. It’s also familiar since we use AI every day in our regular lives through computers, smartphones, and other connected devices.

AI is going to help clinicians do more with the time they have. It will help physicians, nurses, coders, and clinical data abstractors by automating simple but necessary tasks. It will also help provider organizations improve efficiency, reduce costs, and enhance care quality. What AI will not do is replace medical professionals.

The already disruptive shortage of physicians and nurses in the US is expected to get worse as the nation’s population ages and our need for care services increases. Hospitals and health systems should embrace the opportunity to use AI in ways that enable their clinical staff to optimize their care for patients.

Readers Write: EHR Optimization: The New EHR Life Cycle

EHR Optimization: The New EHR Life Cycle
By Nathan Koske

Nathan Koske, MBA is director of Meditech professional services for CereCore.

Modern EHRs are significant investments that constantly change and require ongoing maintenance and improvement to realize value and benefits for patient care, satisfaction, and hospital operations. How can your optimization efforts be strategic ones? Let’s examine key ingredients for successful EHR optimization so that your healthcare organization can be prepared for the transition and understand the components of this ongoing life cycle. 

Optimizations are typically most successful when they are started one to two months post go-live. Even if you are amid an EHR implementation, it’s not too early to start making plans for optimization. Organizations often simply can’t fit everything into an implementation, making optimization efforts something to consider from the start.  

Regardless of the type of optimization you are planning, it is important to give your users sufficient time to become familiar with the product, as well as wind down from the grueling process of going live with a new EHR environment.  

Your new EHR offers capabilities that may spark ideas, and clinicians may have a new lens to explore what’s possible and how that can improve workflows and patient care. This adjustment period is important in helping users realize what is needed instead of reacting to what was just different from their previous system.  

The population of data into the live system is another big factor into that adjustment period. Simply put, some things you can’t optimize until the data and/or workflows exist. After the first month or so of use, users will also be able to identify which workflows actually need to be evaluated for improvement versus functionality that may benefit from more education. Focusing on workflows that need to be improved will go far in yielding value in your optimization efforts.  

Conduct a formal assessment of your current EHR environment as a first step in launching an optimization project. Review the system and workflows and gather feedback from everyday users within a formal process.  

A holistic EHR assessment can identify areas of improvement that weren’t apparent during earlier phases in the life cycle. It is important to understand that although the goal of both your organization and your EHR software provider is a solid implementation, the viewpoints and responsibilities are different. An experienced EHR partner can help you assess and bridge the gaps, whether that is a specific skillset or translating software speak into clinical operations reality. The scope of an EHR assessment can vary depending on the perspective of the stakeholder involved. 

Take these actions to assess your processes and inform your optimization priorities:  

• Start by rounding and talking to users about features that they may not understand fully. Quick wins are often gained by showing users how to do something on the spot. 
• Interview users from various departments and roles and ask them about pain points. What’s not working well? 
• Review system configuration details. 
• Observe users to identify opportunities for streamlining workflows. 
• Document all pain points and optimization opportunities and set a time to prioritize them. 
• Determine the EHR functionality that you have contracted for from your EHR vendor. When reviewing your list of functionality, it is crucial to determine what is being underused or possibly not used at all. 
• Collect your findings into a concise document that is grouped by impact areas such as patient safety, revenue, regulatory, user satisfaction, and patient satisfaction. Organizing this information will also help you prioritize findings and determine next steps. 

A thorough assessment of your EHR could produce optimization documents that contain a significant number of findings. The results may be overwhelming to leaders and project team members. Don’t get discouraged. It’s natural for EHR implementations to need optimization.  

Prioritizing the assessment findings will require strategic decisions, but in the end, your organization should walk away with a roadmap that will guide optimization projects and future investments.  

For example, you may need to weigh the benefit of certain optimization items based on whether it could improve physician productivity or just make life easier for clinical staff. Or, it could make sense to prioritize an optimization that would generate revenue because a manual process wasn’t leading to consistent revenue capture. Patient safety or potential regulatory compliance items are usually high impact items to consider, too.  

During the assessment prioritization review, the leadership team could decide to attack all high priority findings or those identified as low-hanging fruit as a way to make quick progress. It is often beneficial to break down the level of effort by service line or department to prevent putting too much strain on your healthcare system.  

IT teams should be prepared to have conversations with your leadership team and key stakeholders about the additional investment (time and money) and skillsets that will be needed to move forward with optimization efforts. For instance, Epic offers tools and recommendations for optimization, but you may need to request budget for those types of things or additional resources. When you request budget, It’s important to communicate how this technology aligns with and contributes to the organization’s goals.. It may be clear to IT that if we execute this initiative, we’re going to get to the anticipated goal, but that might not be clear to operations. It’s important to draw those lines of connection. 

The strategic roadmap that results from the EHR assessment and optimization prioritization session will identify and help articulate the value that can be realized by the organization, and the true benefits are achieved through skillful execution.  

Once you have tackled your optimization roadmap, it’s time to kick off the optimization phase of your EHR journey. At this point, change management principles are critical for implementation and ongoing success. Regardless of what system you’re on, change management is pivotal to optimization success. Inform users about how to use the system in a new way, or even train them if it’s a significant change, so that they will begin the new approach rather than continuing to do the same thing that they’ve always been doing the same way that they’ve always been doing it. 

Take these actions to help make your optimizations a reality:  

• Assign specific staff to the optimization project. The optimization phase should be treated like any project, so you should assign a project manager to oversee the process. 
• Develop a clear project timeline. The project manager should set important milestones and outline go-live dates for new functionality in departments. 
• Communicate with staff about the optimization project and hold a kickoff. 
• Establish communication and project meeting cadences that make sense for those involved. Maintain a project plan to keep everyone on track. 
• Determine if any of the optimizations or new functionality being implemented will require end-user education and develop a training plan. 

The EHR is the lifeblood of any healthcare organization. Optimization that goes beyond basic maintenance and focuses on continuous improvement can provide significant tangible and intangible benefits across the organization. 

Readers Write: Leveraging the Power of Technology to Improve Behavioral Health

Leveraging the Power of Technology to Improve Behavioral Health
By Shana Hoffman

Shana Hoffman, MBA is CEO of Lucet.

We are living in an age of anxiety. Americans of all ages are increasingly struggling with their mental health. Half of young adults and one-third of all adults reported feeling anxious, either always or often in the past year, according to a 2022 survey. In 2023, 60 million Americans, roughly 23% of all adults, reported experiencing mental illness in the previous year.

Despite the growing need for care, millions of people are finding themselves without access to mental health treatment. The barriers they face in accessing behavioral health services are numerous and complex. Long wait times, a shortage of providers, geographical barriers, stigma, and cost all contribute to a system that is unable to meet the demand.

The shortage of mental health providers is a particularly acute problem. According to the American Psychology Association’s 2022 COVID-19 Practitioner Impact Survey, 60% of psychologists reported no openings for new patients. Nearly half of the US population in 2022 lived in a mental health workforce shortage area, with some states needing up to 700 more practitioners to close the gap.

The consequences of this inadequate access to care affect more than just individuals. On a micro level, insufficient healthcare access can impair a person’s ability to proactively manage their mental health challenges, leading to a worsening condition and potentially negative long-term health outcomes. On a macro level, unaddressed mental health issues can contribute to a range of problems, including homelessness, poverty, unemployment, and safety concerns. These have a cascading effect on the local,  and ultimately national, economies.

But there is hope. We may be living in an age of anxiety, but we are also living in an age of technology. Technology can help bridge the gap and improve access to behavioral healthcare. By using today’s advanced tools, we can address many of the barriers that have historically limited access to mental health services.

One of the most significant advantages of using technology in behavioral healthcare is its ability to improve access in areas where mental health resources are limited. Rural areas in particular have long struggled with a lack of mental health services. Tele-mental health services offer a solution for these patients, connecting them to the care they need regardless of their geographical location. Mental Health America reports that rural areas have 20% fewer primary care providers than urban areas, with 65% of rural counties lacking a psychiatrist and 81% without a psychiatric nurse practitioner. Technology can help close these gaps, ensuring that these rural patients are not left behind.

Technology offers flexibility, enabling patients to access care at times that fit their schedules to make it easier for them to commit to treatment. Technology also helps expedite the process of connecting individuals to care. Current average time between booking an appointment and a claims-confirmed connection is over 45 days, with some psychologists reporting wait times of three months or longer. Technology tools that quickly identify active, in-network providers who are accepting new patients can significantly reduce these wait times, ensuring that patients receive the care they need when they need it.

Providers benefit from technology-enabled care access as well. By giving patients more flexibility in how they access care, technology makes it easier for them to stick to their treatment plans over time, helping providers achieve better long-term results.

Most critically, technology can help address the issue of provider shortages by offering advanced and accurate insights into available care resources, minimizing the time it takes for providers and patients to connect, allowing for more efficient scheduling of treatment. By streamlining administrative tasks such as patient intake, documentation, and screening, technology can also help free up clinicians to spend more time on delivering care.

Use of technology can improve treatment adherence and expand access to care in underserved areas, leading to healthier populations and lower long-term costs for payers. Additionally, by improving the accuracy of provider directory management systems, technology can help eliminate “ghost networks” in which healthcare providers who are listed in a health plan’s network are not actually available to provide care. This not only enhances regulatory compliance, but also boosts member satisfaction.

Mental health technology solutions have enormous potential to increase access to care, enhance efficiency, and improve outcomes. To fully realize this potential, stakeholders must continue to invest in and support technological advancements in behavioral healthcare, because only then can we create a more equitable and effective behavioral healthcare system.

Readers Write: Virtual Care Isn’t What It Used to Be – It’s Getting Better

Virtual Care Isn’t What It Used to Be – It’s Getting Better
By Derek Streat

Derek Streat is CEO of DexCare.

Virtual emerged as a vital access bridge during the pandemic, ensuring that patients received on-demand care while living in lockdown. As society transitioned back to normal, public use of virtual care inevitably declined. Today, as we watch market shakeups as companies shutter and shrink, critics are quick to point out that virtual fell short and will never replicate in-person care. That’s a shortsighted outlook, because like any technology, virtual is undergoing a natural pivot.

The industry grew too fast, but disruption drives progress, creates new applications, and forges pathways for value creation. The technology that is powering virtual care has matured from simple, one-off video consultations into an adaptive strategy that complements in-person care to balance a health system’s limited capacity.

Virtual care 2.0 is underway, and at just the right time. With 11,000 Americans aging into Medicare each day and not enough primary care doctors, a new model for how care is accessed and delivered is required. Virtual is a critical backstop to meet the rising demand for care while reducing the pressures on clinicians.

The reality is that not everyone needs to see a doctor in person. It’s the type of appointment and routing to appropriate venues of care that counts. Instead of follow-ups, consultations, and common conditions clogging up urgent care clinics, emergency rooms, or taking away from a doctor’s finite time, health systems can redirect patients to a virtual appointment, a clinic, or a nurse practitioner. Modern care orchestration is multi-modal, predictive, and powered by real-time intelligence to ensure that patients receive the right care, at the right time, in the right setting.

But how can a health system guide a patient to the right modality on the fly? By operating in real time and having the digital flexibility to coordinate how, when, and where patients select care. It’s about having dynamic controls to precisely administer system-wide resources to match demand against capacity. Virtual is part of a broad portfolio of care that underpins convenience for patients while managing workforce resources by the hour, day, month, or quarter.

Consider Kaiser Permanente’s multi-modal approach. By integrating virtual consultations, online check-ins, and secure messaging, the health system enhances patient access while optimizing resources before and after in-person visits or by reducing the need for patients to physically see doctors altogether. The net result is more time for clinicians, greater choice for patients, and the delivery of quality, clinically appropriate care.

Virtual is no longer a button for patients to push, but rather a technology to promote flexibility and growth. For many health systems, virtual is being applied in innovative ways to address more complex patients’ needs.

Health systems can extend the reach of care by offloading routine visits to virtual. These can include check-ups, preventive, and chronic-condition management. The impact is time saved at multiple touch points throughout the delivery pipeline, allowing for a responsive patient experience while liberating resources to focus on acute care and higher complexity cases.

Disruption isn’t failure. It is fuel for innovation. Virtual care is evolving, not fading, and is a cornerstone to a growing mix of care venues, including services, locations, and providers. It’s not about replacing doctors, but rethinking how and where care is accessed to extend workforce resources. This isn’t the slow, phase out of virtual care. It’s just the beginning of a smarter, more agile health system.

Readers Write: Don’t Skip the Digital Wash: 3 Cyber Hygiene Tips for Healthcare Security

Don’t Skip the Digital Wash: 3 Cyber Hygiene Tips for Healthcare Security
By Greg Surla

Greg Surla is SVP/CISO of FinThrive. 

In 2023, healthcare systems faced an alarming surge in cyberattacks, impacting over 100 million people across the US, according to The HIPAA Journal. This troubling trend continued into 2024, emphasizing the urgent need for advanced cybersecurity measures in healthcare.

With the rise of sophisticated ransomware attacks, such as those from BlackCat, and the increasing availability of ransomware-as-a-service, healthcare organizations must remain focused on cyber hygiene practices.

Cyber hygiene refers to the routine practices that are necessary to protect information systems and sensitive data. For healthcare organizations, effective cyber hygiene is particularly challenging due to factors such as outdated technology, stringent HIPAA regulations, and rapidly evolving cyber threats. Key cyber hygiene practices — regular credential rotation, MFA, and effective vulnerability management — are essential for mitigating the risk of breaches and ensuring regulatory compliance.

This article explores three essential cyber hygiene procedures for shielding healthcare data: credential rotation, multi-factor authentication (MFA), and vulnerability management.

Regular Credential Rotation

Regular credential rotation is a fundamental security practice that involves frequently updating passwords and access credentials. This process helps minimize the risk of unauthorized access, especially if credentials are compromised.

In healthcare settings, where multiple users with varying access levels are common, managing credential updates is a complex, but necessary, best practice.

• Develop a clear policy. Establish guidelines for how often credentials should be updated and assign responsibilities for managing this process.
• Use automation. Apply identity and access management (IAM) solutions to automate the credential rotation process and reduce manual effort.
• Educate and incentivize staff. Provide training on best practices for creating and managing secure credentials. Consider offering incentives for adherence to credential policies.
• Conduct regular audits. Regularly review and audit credential management practices to ensure compliance and identify areas for improvement.

Multi-Factor Authentication

MFA is a critical security measure that enhances protection by requiring multiple forms of verification beyond just a password. This additional layer of security is especially important in environments where unauthorized access to sensitive data has severe consequences.

• Select an integrated solution. Choose an MFA system that integrates well with existing infrastructure and is user-friendly.
• Deploy in phases. Start by deploying MFA in high-risk areas and gradually extend it across the organization.
• Train staff. Educate employees on the importance of MFA and provide thorough training on its use.
• Review practices. Periodically assess and update MFA practices to adapt to new security challenges.

Vulnerability Management

Vulnerability management involves identifying, assessing, and addressing security weaknesses within systems. Regular vulnerability management is crucial in healthcare.

This practice includes routine scanning, risk assessment, and timely patching to protect systems from potential breaches. Automated tools are available to frequently scan systems for vulnerabilities and rank risks based on their potential impact and the likelihood of exploitation. Look for emerging vulnerabilities and train staff to identify potential risks and deliver prompt resolution.

The most common attacks in healthcare attempt to exploit user accounts through social engineering methods such as phishing as well as brute-force types of attacks such as password spraying and credential stuffing.

By adopting the cyber hygiene practices list above, healthcare organizations can enhance their defenses against cyber threats, ensure compliance with regulatory requirements, and maintain the security of their systems. And as cyber threats continue to intensify, staying proactive and vigilant safeguards your organization’s sensitive healthcare information, preserving trust in the healthcare system.

Readers Write: Navigating the Talent Shortage: Strategies for Healthcare IT Recruitment

Navigating the Talent Shortage: Strategies for Healthcare IT Recruitment
By Eric Utzinger

Eric Utzinger is co-founder and chief commercial officer of Revuud.

The healthcare industry is facing an unprecedented talent shortage, particularly in the realm of IT. With the rapid advancement of digital health technologies, the demand for skilled IT professionals has never been higher.

However, the supply of qualified candidates is not keeping pace, leading to intense competition for top talent. This shortage poses significant challenges for healthcare systems that are striving to maintain and improve their IT infrastructure, ensure data security, and keep up with regulatory requirements.

The Pain Points: A Perfect Storm of Demand and Shortage

• Difficulty finding qualified IT professionals. The healthcare sector requires IT professionals with specialized skills, such as experience with electronic health records (EHR) systems, telemedicine platforms, and cybersecurity. Finding candidates with the right mix of technical expertise and healthcare knowledge is increasingly difficult. The pool of available talent is shrinking as more industries compete for the same skill sets.
• Competition for top talent. Even when qualified candidates are found, healthcare organizations face fierce competition from other sectors, including technology companies, financial services, and government agencies. These industries often have deeper pockets and can offer more lucrative compensation packages, making it even more challenging for healthcare systems to attract and retain top talent.
• Lengthy hiring processes. The recruitment process in healthcare can be notoriously slow, involving multiple rounds of interviews, background checks, and credential verification. In a market where top IT talent is quickly snapped up, a slow hiring process can result in losing out on the best candidates.
• Geographic limitations. Many healthcare systems, especially those in rural or less populated areas, struggle to attract IT professionals who are willing to relocate. The reluctance to move, coupled with a shortage of local talent, exacerbates the recruitment challenge.

Strategies for Overcoming the Healthcare IT Talent Shortage

While the talent shortage is a significant challenge, there are several strategies healthcare organizations can employ to improve their recruitment efforts and secure the IT professionals that they need.

• Expand the talent pool with remote work options. One of the most effective ways to overcome geographical limitations is to embrace remote work. The COVID-19 pandemic has normalized remote work across many industries, and healthcare IT is no exception. By offering flexible work arrangements, healthcare systems can tap into a broader talent pool that extends beyond their immediate geographic area. This approach not only increases the number of potential candidates but also appeals to IT professionals who prioritize work-life balance.
• Develop and promote internal talent. Investing in the development of existing employees can help mitigate the impact of the talent shortage. Healthcare organizations should offer training programs and certifications to upskill their current IT staff, preparing them for more advanced roles. By promoting from within, healthcare systems can retain valuable institutional knowledge while reducing the time and cost associated with external recruitment.
• Partner with educational institutions. Establishing partnerships with universities, colleges, and technical schools can create a pipeline of future IT professionals. Healthcare organizations can offer internships, co-op programs, and scholarships to students who are pursuing degrees in healthcare IT or related fields. These initiatives not only help attract new talent, but also provide an opportunity to shape the education and training of future employees to meet the specific needs of the healthcare sector.
• Leverage AI and technology for efficient recruitment. Advanced talent management platforms leverage AI to streamline the recruitment process. AI-powered matching algorithms can quickly connect healthcare systems with pre-vetted IT contractors who possess the specific skills that are required for the job. This technology reduces the time spent sifting through resumes and ensures that only the most qualified candidates are considered. By using AI, healthcare organizations can expedite the hiring process, reducing the risk of losing top talent to faster-moving competitors.

Conclusion

The healthcare IT talent shortage is a complex challenge, but with the right strategies, healthcare organizations can navigate it successfully. By expanding the talent pool, investing in internal talent development, and leveraging AI and technology, healthcare systems can improve their recruitment efforts and secure the IT professionals they need.

As the healthcare industry continues to evolve, the ability to attract and retain top IT talent will be critical to the success of digital transformation initiatives and the delivery of high-quality patient care. Be sure that you’re staying ahead in the race for talent to ensure that you are well equipped to meet the demands of the future.

Readers Write: What Separates Winners from Losers in Population Health Management? Three Lessons

What Separates Winners from Losers in Population Health Management? Three Lessons
By Billie Jo Nutter

Billie Jo Nutter is CEO of Chordline Health.

There’s an alarming range of success and failure in population health management initiatives, with an ROI that spans from -$244.65 to $1,592.48 per year. As healthcare providers and health plans accelerate investments, ensuring organizations have the right data, tools, and processes to improve risk identification, care management, and value will be vital.

One area of untapped opportunity, according to pwc: driving payer-provider collaboration with a single care plan that is customized to each patient’s needs.

To get there, health plans and health systems must understand where breakdowns in population health management typically occur, how to evaluate their approach, and ways to drive better results.

Breaking Down Population Health Pain Points

Lack of trust and cynicism are two of the biggest factors that get in the way of payer-provider collaboration around population health, according to healthcare C-suite leaders who attended an HFMA population health colloquium last fall. Transparency  around population health data, analytics, outreach, and referrals can help unlock collaboration, but only if the data used to inform population health analyses and care management response are credible and actionable.

One way to build trust in population health data is by aggregating data from multiple sources, including community service organizations, to gain a whole-picture view of the patient, including the patient’s health-related social needs. Another is to tap into another organization’s data to compare a population against a similar population. This process can help uncover best practices in care management for a specific group. In instances where providers and payers are collaborating around population health management, it can also help to:

• Align resources for more effective care management.
• Point to opportunities to better manage multiple chronic conditions.
• Uncover instances where medication management could be streamlined, avoiding adverse effects and unnecessary costs.

Trust also comes down to the ability to use the data at the point of care to improve patient outcomes and to demonstrate the impact that was made in ways that all key stakeholders can understand. This is an area where the data must not only be credible, but also be delivered in such a way that clinicians can determine, at a glance, the health risks that a patient faces and the interventions that offer the best chance to improve health.

In addition, clinicians and value partners, like health plans, need to see the impact that they have made, such as the number of people for whom they have helped to avoid hospital readmissions or progression of disease. This level of clarity reinforces professional satisfaction. It also motivates all stakeholders to do more to strengthen the health of a population.

How can healthcare providers and health plans collaboratively develop a population health management approach that delivers clear wins for both stakeholders and their patients?

• Use shared data to develop a single care plan. Just as some providers leverage data from academic medical centers to better understand what works and what doesn’t in strengthening the health of specific populations, access to health plan data gives providers a more complete view of a patient’s healthcare utilization and care costs. From there, data scientists can not only analyze and forecast a population’s health needs, but also strengthen patient engagement in ways that improve overall health. That’s especially important for adults with chronic conditions, whose risk of hospitalization is two to eight times higher than that of adults without chronic disease.
• Explore innovative approaches to managing chronic conditions, especially within managed Medicare populations. When high-risk patients are identified, bring care managers from the health plan and the health system together to design and implement strategies for care coordination. Then, leverage technology for remote monitoring and support. One essential element for success: a population health analytics platform that can integrate with any data system. This ensures that no matter where a care manager or clinician works, that person has the same data view to make care decisions and view progress.
• Make it easy for clinicians to view population health data directly within their workflows. Intuitive patient dashboards can put population health data at clinicians’ fingertips, empowering them to understand the top factors that influence the patient’s health and population health. Such dashboards can also point to opportunities to reduce care costs, such as by highlighting medication prescribing trends for a particular population and ways to bring these patterns in line with evidence-based practices. One tip for success: make sure the dashboard offers flexible data filtering options to support the clinical team’s needs and enable the team to report on progress and opportunities in a variety of ways.

By taking a collaborative approach to population health management, health systems and health plans can more effectively improve the health of target populations while enhancing clinical workflows, patient outcomes and professional satisfaction.

Readers Write: Six Foundations of Highly Productive Technology Teams: How to Handle System and Talent Transitions

Six Foundations of Highly Productive Technology Teams: How to Handle System and Talent Transitions
By  Mark Thomas

Mark Thomas, MS, MBA is CTO of MRO.

There is one certainty in healthcare IT. Teams, tasks, and technology will always change. Maintaining a productive and efficient team culture during these transitions is essential to keep up with today’s fast-paced and connected health IT ecosystem.

A well-developed technology culture ensures optimal outcomes through months of high-volume activity, such as EHR conversions, and during regular day-to-day operations. And by focusing on high productivity, health system CIOs build a solid foundation to weather our industry’s inevitable shifts in strategic initiatives and organizational leadership.

This article explores six principles of developing a technology team culture for high production and resilience in healthcare. The leadership journey begins with flexibility and the willingness to accept change.

Embrace change and inspire flexibility

One of the most important qualities of a high-production culture is the ability to evolve. Effective technology leaders exhibit flexibility and welcome changes that drive positive outcomes for the team. This involves personal accountability at all levels to challenge barriers and work toward common goals.

A recent example is our company’s deliberate decision to rebrand the “IT” team to the “Technology” team. Rebranding the name of the department was a simple, yet effective way to help the team transition away from IT ticket-takers to strategic business outcome thinkers.

By fostering an environment where change is accepted and encouraged, CIOs ensure their systems and processes remain adaptable and responsive to advancing business needs.

Use data-driven decision-making

Predictability is important for sustaining high productivity. But predictability is often elusive during times of dramatic change and system transition. Savvy healthcare CIOs use data to build a bridge between opposing forces — doubt and certainty.

Whether with clients, partners, or internal stakeholders, data is a proven guide to effective technology leadership decisions. Teams make more informed decisions and remain focused on outcomes when performance can be tracked against data-driven commitments.

A variety of metrics can be used to measure the impact of team culture. This includes use of the Westrum culture survey, delivery predictability, and alignment of talent with skills and interests. By continuously monitoring these metrics, organizations can ensure teams are performing well and remain engaged and motivated. This data-driven approach enables the organization to make informed adjustments and sustain high productivity over time.

Finally, rewarding transparency when teams go off track further reinforces a culture of honest and continuous improvement.

Build composable and collaborative teams

Organizing teams around domains that require cohesive changes fosters a composable culture. This means aligning teams with a common backlog and driving toward shared outcomes.

This approach, coupled with a systems-thinking mindset, ensures that each team understands its role within the broader system and takes personal accountability for its contributions. By empowering teams to self-regulate, technology leaders also quickly identify necessary shifts and improvements to maintain high productivity.

Encourage extreme ownership for optimal availability

In today’s 24/7 plugged-in healthcare environment, system availability is non-negotiable. The concept of extreme ownership holds teams accountable for their systems end to end, from implementation to bringing disabled systems back online.

Eliminating handoffs and ensuring continuous monitoring helps teams proactively address issues before clients are affected. This cultural shift drives significant technological progress and ensures systems experience upmost reliability.

This type of accountability model eliminates reliance on project managers. Teams and individuals are directly responsible for their outcomes, fostering a sense of pride and ownership while delivering remarkable improvements in release frequency and quality.

Use telemetry and feature flags to support scalability

All systems must be scalable to enable future growth. Build telemetry into every step of the development life cycle, providing visibility into system performance and identifying bottlenecks.

Feature flags are another proven tool for health IT leaders. With these flags, technology teams release features at a controlled pace that enables organizations to scale effectively. This continuous improvement mindset should be ingrained in the team culture to ensure the organization is able to grow alongside new technological capabilities and industry demands.

Gather direct feedback from end users

A user-focused culture is essential for delivering valuable products. Routine inspections and direct feedback from end users are integral to the development process.

Teach your technology teams to speak the language of the business for each department or service line they support. Knowing the proper vernacular (e.g., nursing, laboratory, revenue cycle) helps teams effectively communicate with stakeholders and translate technical requirements into business value.

Frequent feedback loops with end users are also encouraged to ensure constant refinement and alignment with departmental needs.

With these six principles in mind, CIOs turn their leadership focus to individuals within and across their teams, ensuring the right people are in the right roles to drive technical excellence.

Translate Culture into Sustained Productivity

A new talent management strategy is the final cornerstone of its high-production culture. Instead of traditional promotion paths that elevate individuals based on technical skills, consider identifying specific strengths, interests, and weaknesses that suggest positions as individual contributors or talent managers.

By embedding these principles into your team’s culture, organizations create an environment where high productivity is both achievable and sustainable. Hospitals and health systems looking to embark on a similar journey should apply these strategies to transform their technology culture and achieve exceptional results.

Readers Write: The Future of Healthcare Data: Unveiling the Potential of Vector Databases

The Future of Healthcare Data: Unveiling the Potential of Vector Databases
By Faiyaz Shikari

Faiyaz Shikari is CTO of HHS Tech Group.

Healthcare information technology (HIT) leaders are the last people who need to be convinced of the transformative power of data in healthcare. However, many leaders may have given little thought to a pervasive industry problem that limits the potential of HIT to fully deliver the value that it is capable of — the traditional relational databases that have served the industry well for decades are reaching their limits when it comes to managing the ever-growing complexity and volume of healthcare data.

This is where vector databases emerge as a game-changer, offering a paradigm shift in how we store, analyze, and leverage healthcare information.

Traditional databases excel at storing structured data, neatly organized in rows and columns. But healthcare data is a different beast. It encompasses a rich tapestry of patient demographics, medical history, lab results, imaging data – often in diverse formats and constantly evolving. Vector databases tackle this challenge head-on by representing these diverse data as “vectors,” mathematical entities with magnitude and direction. This allows for efficient storage and retrieval of complex information, particularly for tasks like patient similarity analysis and drug discovery.

Imagine a scenario where a physician is treating a patient with a rare disease. With traditional databases, pinpointing similar cases might involve laborious manual searches. Vector databases, however, can analyze a patient’s unique medical profile and identify others with similar vector representations, potentially leading to faster diagnoses and treatment options. This personalized approach empowers physicians to move beyond a one-size-fits-all model and tailor care to everyone’s needs.

The potential of vector databases in healthcare extends far beyond patient similarity analysis. Consider the realm of drug discovery, a notoriously time-consuming and expensive process. Vector databases can store and analyze vast datasets of molecular structures, accelerating the identification of potential drug candidates. By comparing the vector representation of a disease target with potential drug molecules, researchers can prioritize promising avenues for further investigation.

Furthermore, vector databases play a crucial role in unlocking the potential of artificial intelligence (AI) in healthcare. AI algorithms thrive on large amounts of diverse data, and vector databases can provide the efficient foundation for their operation. Imagine AI-powered systems that can analyze medical images with unprecedented accuracy or predict potential health risks based on a patient’s unique profile. Vector databases can empower these powerful tools, paving the way for a future of data-driven precision medicine.

The new AI algorithms use two main components. Sparse vectors handle exact word matching, like traditional keyword search, such as identifying specific symptoms in a patient. Dense vectors capture overall meaning and context, like how our brains understand language, such as grasping the overall health profile of a patient. These algorithms employ a method called Reciprocal Rank Fusion to blend results from both approaches, ensuring precise matching and contextual understanding.

The impact is evident in several practical scenarios. For customer support, AI-powered chatbots can find relevant information from knowledge bases, providing faster, more accurate responses. In legal research, lawyers can quickly locate relevant case law and legal documents, understanding both terminology and legal concepts. In medical diagnosis, healthcare systems can search medical literature for studies and case reports matching symptoms and patient context. For content recommendation, streaming services and online retailers can offer more accurate recommendations, understanding user preferences and broader trends.

Integrating any new technology requires careful consideration. Security and privacy remain paramount in healthcare. Vector databases must be designed with robust security measures to ensure patient data remains confidential. Additionally, establishing clear guidelines for data governance and ownership will be crucial for fostering trust and promoting responsible use of this powerful technology.

In conclusion, vector databases hold immense potential to revolutionize healthcare. From enabling personalized medicine to accelerating drug discovery, these innovative databases offer a future where data truly empowers better patient care. As we navigate this exciting landscape, collaboration between healthcare professionals, data scientists, and cloud computing companies will be essential to unlocking the full potential of vector databases and ushering in a new era of data-driven healthcare.

Readers Write: A New Industry Standard: How the VBPR IG Is Advancing Value-Based Care

A New Industry Standard: How the VBPR IG Is Advancing Value-Based Care
By Michael Pattwell

Michael Pattwell is principal business advisor for value-based contracting at Edifecs.

The introduction and adoption of the HIPAA transaction standard X12 837 for electronic claim submission revolutionized the way providers were reimbursed in the early 2000s. This standard eliminated administrative overhead for both payers and providers by shifting from paper-based claim submission to electronic submission, reducing claims processing time, errors, and reimbursement turnaround. The standardized structure allowed healthcare providers and payers to communicate efficiently and accurately in a universal format while maintaining security and privacy standards.

Fast forward two decades and the transition from fee-for-service to value-based care has necessitated a new shift. To address this challenge, a new open industry standard has been published to facilitate this transition to value-based care. This standard was designed and developed by the HL7 Da Vinci Project.

The Da Vinci Project is a private sector initiative that addresses the needs of the value-based care community by leveraging the HL7 Fast Healthcare Interoperability Resource (FHIR) platform. The HL7 FHIR platform enables payers, health systems, and other industry participants to identify and enumerate healthcare business use cases that involve managing and sharing clinical and administrative data between industry partners.

On June 17, 2024, The Da Vinci Project published its newest business use case called the “Value-Based Performance Reporting (VBPR) Implementation Guide (IG).” The VBPR IG is designed to support a standards-based exchange of financial and quality performance data based on contractual performance measurements agreed to by payers and providers. The VBPR IG is designed to leverage the existing FHIR resources created for other business use cases. The VBPR IG profiles the “measure report” resource. This existing FHIR resource is profiled by the VBPR IG as is and consumed using the FHIR framework that facilitates this interoperability standard.

This new VBPR IG interoperability standard is designed to solve many of the challenges payers and providers have faced implementing value-based care contracts over the past decade. Some of the challenges that can be solved by implementing the VBPR IG include:

• The timely tracking of performance across contractual measures. It is difficult, if not impossible, for providers to understand how well they are performing prior to various settlement dates.
• Lack of a standard format for value-based care contract performance reporting. There is variation in metrics and methodologies used across payers including financial terms, quality measures, attribution, and reconciliation periods. Reconciling the numerous reports providers receive from multiple payers in unstructured formats. This process is time intensive because reports come from various portals.

The immediate goal of the VBPR IG standard is to enable payers to summarize provider performance across different categories, including lines of business, contracts, populations, quality measures, financial metrics, and reporting periods on a scheduled and ad-hoc basis. Based on the calculated performance scores, incentives are calculated and distributed to providers as rewards or penalties, encouraging continuous improvement in care quality and efficiency.

Solving these critical business problems with value-based care contract transparency and standardization will accelerate the transition away from a fee-for-service reimbursement model to the value-based care model. This will lead to the ultimate goals and objectives to encourage superior care, enhance patient outcomes, and lower costs by compensating providers according to their quality performance, as opposed to the quantity of services provided.

So, what is next for the multi-stakeholder VBPR IG Team at The Da Vinci Project? The next release is is in development. Future releases will continue to extend the VBPR IG and include consuming and leveraging additional FHIR resources. These additional resources include, but are not limited to, CRD IG – Coverage Requirement Discovery and DTR IG – Document Templates and Rules.

Members of HL7’s Da Vinci Project will continue to advance the HL7 FHIR standards and collaborate with all industry stakeholders to accelerate the adoption of a digital future across healthcare. The Da Vinci Project founders and private sector partners are supporting the implementation of the VBPR IG and looking forward to seeing it in action across the industry.

Readers Write: The Advantages and Misconceptions of Being a 1099 Contractor in Health IT

The Advantages and Misconceptions of Being a 1099 Contractor in Health IT
By Eric Utzinger

Eric Utzinger is co-founder and chief commercial officer of Revuud.

Are you a health IT professional who is debating between the freedom of being a 1099 contractor and the stability of a W2 employee? Understanding the nuances can make all the difference in your career path.

Each option offers distinct advantages and misconceptions, particularly within the healthcare industry. I will delve into the specific benefits and clarify common misunderstandings about being a 1099 contractor compared to a W2 employee in health IT.

Advantages of Being a 1099 Contractor in Health IT

• Flexibility and control. Health IT contractors enjoy unparalleled flexibility. They can set their own schedules, choose projects that are aligned with their expertise, and often work remotely. This autonomy is invaluable for navigating the demanding schedules that are often required in healthcare settings.
• Potential for higher earnings. 1099 contractors in health IT frequently have the potential to earn more than their W2 counterparts. They can negotiate competitive rates that are based on their specialized skills and experience without the constraints of a fixed salary. Additionally, deductible business expenses can significantly lower their taxable income.
• Diverse opportunities. Working as a 1099 contractor in health IT allows professionals to diversify their experience across various healthcare organizations. This exposure to different systems, workflows, and clinical environments enhances their skill set and professional growth.
• Tax benefits, Health IT contractors can leverage substantial tax deductions, including expenses that are related to home offices, travel, professional development, and health insurance premiums. These deductions provide financial advantages that are not typically available to W2 employees.

Misconceptions About Being a 1099 Contractor in Health IT

• Lack of Stability. It’s often assumed that 1099 contractors lack job stability in health IT. However, skilled contractors can maintain a steady stream of projects by establishing relationships with multiple healthcare facilities or organizations. The demand for specialized health IT expertise ensures ongoing opportunities.
• No benefits. Contrary to common belief, 1099 contractors in health IT can access benefits like health insurance and retirement plans, albeit through individual arrangements. They can purchase health insurance through marketplaces and establish retirement accounts such as IRAs or Solo 401(k)s, ensuring financial security.
• More taxes. There’s a misconception that 1099 contractors in health IT face higher tax burdens. While they do pay self-employment taxes, the ability to deduct business expenses often offsets these taxes. With strategic tax planning, contractors can effectively manage their tax liabilities.
• Isolation. Some perceive health IT contractors as isolated due to their independent work status. However, technological advancements and collaborative platforms enable contractors to engage in virtual healthcare teams, participate in professional networks, and attend industry conferences, fostering connections and support.

Advantages for Health Systems

• Flexibility in scaling workforce. Health systems benefit from the flexibility of engaging 1099 contractors, allowing them to scale their workforce based on current needs without being bound to a set number of hours. This adaptability helps save time and money, ensuring that resources are used efficiently.
• Improved workforce management platforms. The rise of 1099 arrangements has driven the development of marketplace platforms that offer better workforce management solutions for clients. These platforms often take on and manage risks similarly to staffing companies, providing a reliable and streamlined process for hiring and managing contractors.
• Fair and efficient time tracking. Unlike traditional staffing models, 1099 contractors are not always pushed to work a standard 40-hour week. This ensures that contractors only track and bill for actual hours worked, leading to fairer time management and cost savings for healthcare organizations.

Evolving Trends and Future Outlook for Health IT Contractors

• Increasing demand for specialized expertise. As healthcare systems continue to adopt advanced technologies and digital solutions, the demand for skilled health IT contractors is expected to rise. Contractors with expertise in areas such as electronic health records (EHR), telemedicine, cybersecurity, and data analytics will find ample opportunities in the evolving healthcare landscape.
• Embracing remote work and virtual collaboration. The COVID-19 pandemic accelerated the adoption of remote work and virtual collaboration across industries, including healthcare. Health IT contractors can capitalize on this trend by offering remote services and supporting healthcare providers with virtual solutions that enhance patient care and operational efficiency.
• Shifting regulatory landscape. Healthcare regulations and compliance requirements are constantly evolving. Health IT contractors must stay abreast of these changes and offer solutions that ensure data security, patient privacy, and regulatory compliance. Contractors who can navigate and adapt to regulatory shifts will remain in high demand.

Conclusion

Choosing between being a 1099 contractor and a W2 employee in health IT hinges on personal career goals and preferences. Both options offer unique advantages and challenges within the healthcare industry. By understanding these nuances and dispelling misconceptions, health IT professionals can make informed decisions that align with their professional aspirations.

Readers Write: Why RCM is the Most Interesting Opportunity in Healthcare

Why RCM is the Most Interesting Opportunity in Healthcare
By Kim Waters

Kim Waters, MBA is principal advisory at CereCore.

Revenue cycle management (RCM) isn’t for everybody, but it certainly is for me. I actually enjoy talking to someone about their revenue cycle plans and opportunities. In fact, I maintain that RCM is the most interesting opportunity in healthcare. If you can’t relate, perhaps the reasons I’ve listed below will convince you. If you agree, I hope that you will share new reasons to add to my list.

Research supports RCM opportunities. In a 2023 study, HFMA reported on the rising cost of claims, with as much as 60% of claims not resubmitted and the average denial rate’s total percentage of gross revenue at 11%. What’s more is that they found that the cost per claim appealed is $118 and the denial rate is increasing 20% year over year. In an era when budgets are tight and margins are lower, organizations need to improve on these numbers to survive and eventually thrive.

Opportunities for improvement can be easy to see. Reconsider any processes or solutions that:

• Are still accomplished on paper.
• Involve a fax machine.
• Have not changed in the last five years.
• Are repetitive.
• Don’t involve peer or higher-level review.
• Consistently receive low engagement scores.
• Are not documented.

Every organization has opportunities for quick wins, while other areas for improvement may not seem so obvious but are just as promising.

Reporting is key. The best RCM decisions are made based on actionable data. On average, healthcare organizations use around 30 vendors across the revenue cycle. Disparate data sets complicate clear, actionable reporting and limit the ability to see patterns and identify areas of opportunity. RCM leaders need effective reporting and road mapping tools to tell their story, presenting a fresh vision around the use of technology and resources and the impact they can make.

Important processes are up and downstream from revenue cycle. From patient access, financial clearance, provider documentation to discharge and final payment for services, RCM processes run through the entirety of a patient’s experience and involve touchpoints with all the departments that a patient’s care requires. This presents complexity and opportunity for RCM, starting with adoption of a unified vision and strategy, change management practices, governance policies, and system interoperability development.

Each organization holds different improvement opportunities. The areas to focus on are a matter of an organization’s current state, their strategic goals, the needs of their community, and their competitive position. That’s what makes it fun. No two systems are alike, but sound revenue cycle management processes can support any endeavor and improve financial performance. In turn, improved financial performance is fundamental to realizing improved quality, outcomes, and all the meaningful reasons we chose healthcare in the first place.

The Healthcare Financial Management Association (HFMA) recently released the Revenue Cycle Technology Adoption Model (RCMTAM), a benchmarking framework to help healthcare’s financial leaders design a personalized RCM modernization roadmap, with the goal of correlating technology improvements to financial performance. RCMTAM is specifically for healthcare and is providing much-needed insight and direction for uncovering and addressing opportunities.

RCM calls for compassion. Working on improvements to revenue cycle management processes looks and feels like improving cash flow, increasing reimbursement rates, reducing denials, and enhancing overall performance. All of the above play a part in the delivery of care to the people who entrust their care to your organization. What’s a more interesting opportunity than that?

Readers Write: Healthcare’s Biggest Hidden Asset

Healthcare’s Biggest Hidden Asset
By Aasim Saeed, MD, MPA

Aasim Saeed, MD, MPA is founder and CEO of Amenities Health.

Health systems across the US continue to grapple with a host of financial challenges, from staffing shortages to lower reimbursement rates to increasing competition from new players in the market. However, most organizations have an unused resource at their disposal that is worth significant value and that is not leveraged to its full potential: MACC credits.

Microsoft Azure Consumption Commitment (MACC) credits are pre-purchased credits that health organizations commit to spending on Microsoft’s Azure cloud services over a specific time. If you remember the old cell phone plans before rollover minutes were introduced, you understand how these “use or lose” benefits work. It’s like buying a golf club membership that requires a minimum purchase of food or drink at the clubhouse.

MACC agreements allow customers to commit to a minimum level of Azure consumption in exchange for discounted pricing and additional benefits. But they are lost if you don’t consume the benefits within a year. You can’t carry them over.

In my opinion, these agreements are probably one of the most underutilized IT resources in healthcare. Many IT and innovation teams have forgotten about them, or don’t even know that they exist. As a result, few are using all the capacity that they paid for. We’re now six months into 2024, and chances are most MACC credits are still sitting, gathering dust. Given the financial strains facing the healthcare industry, technology teams need to use these funds before they expire at the end of the year.

Accessing a third-party app is one of the easiest, but often overlooked, ways to accomplish this. Many valuable third-party applications are available via the Microsoft Azure Marketplace. If healthcare organizations have MACC allocations that are at risk of going to waste, they can adopt these applications at no net new cost. For instance, a hospital might fold a new chatbot application, advanced online scheduling, or billing software into its MACC agreement.

The marketplace is also designed to streamline the contracting process. It allows healthcare systems and other organizations to transact automatically without having to complete a bunch of paperwork on the back end. Rather than getting bogged down in the contracting process, healthcare systems can purchase the applications directly through Azure, install them immediately, and use them to improve their operations.

Another option is to use the credits to build cloud environments. All MACC agreements come with cloud support built into the offering, which presents an opportunity for health systems to migrate some of their on-premises resources to the cloud, helping them eliminate some of the capital costs that are associated with data center refreshes. Also, the cloud presents an opportunity for hospitals to pilot new tools, paying only on a per-user basis rather than making the serious capital investments that are frequently associated with on-premises solutions.

Healthcare organizations should carefully prioritize their technology needs when using resources under their MACC agreements. This involves weighing the potential impact of new applications against factors like ease of implementation, necessary training, and ongoing management. It’s crucial to begin with a comprehensive evaluation of the organization’s overarching digital transformation goals and how cloud services can effectively align with these objectives.

By increasing awareness of their Azure commitments and actively taking advantage of these hidden assets, healthcare systems can enhance and streamline their technology environments without any additional costs to their technology budgets.