In 2020, hospitals across the world were in the throes of the COVID-19 pandemic. Burnout was rampant among administrative and clinical staff. The promise of the EHR to reduce physicians’ and nurses’ burnout and administrative burden had failed to be fulfilled during a crisis in which time was paramount, with lives hanging in the balance. The pandemic caused innovation began to bubble up from hospitals’ leaders and frontline staff, ranging from hospital-at-home to automating clinical decision-making processes within the EHR to alleviate clinicians’ administrative burden and allow them to practice at the top of their licenses. However, the abatement of the pandemic did not end the quest for innovation in care delivery.

One of the ways that LifeBridge Health, a previous health system in which I worked, innovated was by creating a clinical decision-making AI algorithm in the Cerner EHR for patients who were potential palliative care candidates. The algorithm was comprised of clinical criteria, such as the primary diagnosis and the number of admissions in the past 30 days. The algorithm created a popup each time it identified patients as palliative care-eligible. If clinicians agreed that the patient was eligible then the algorithm automatically created a palliative care consult order.

Several steps were involved in creating the algorithm. First, the palliative care team (physicians, nurse practitioners, and the VP of Palliative Care) identified a need to facilitate deciding which patients were eligible for palliative care in the EHR. The team then contacted the team of data analysts and account managers at Cerner to brainstorm a solution. Together, they decided upon an algorithm that identified patients eligible to receive palliative care. The multidisciplinary team customized the algorithm to Baltimore and Carroll County’s unique patient populations.

Additionally, LifeBridge’s data analysts, database administrators, and clinical informaticists were included to design metrics to track the algorithm’s effectiveness. As a result, the number of palliative care patients increased substantially, while the administrative burden of clinicians to place a consult order and identify potential palliative care patients was reduced. Not only were patients identified as palliative care-eligible more quickly, but length-of-stay decreased. Operations and the discharge process were streamlined so that palliative care patients were moved in a timelier fashion to different units and post-acute facilities to receive optimal care. Patients’ loved ones appreciated that their family members were being cared for. Stories of the palliative care teams’ high-quality care abounded in LifeBridge’s internal monthly magazine, on the LifeBridge website, and during awards ceremonies. Involving a multidisciplinary team, especially physicians and users, early in the algorithm’s creation was necessary for their success.

At Lifepoint Health, we include multidisciplinary teams in creating algorithms and technology solutions for clinicians. Our performance improvement and technology implementation projects are closely aligned because operations and technology are closely related. The faster and higher-quality decisions are made, the more streamlined operations are. When a need is identified, our team goes to the site in-person to map the current process. Throughout the site visit, we ask clinicians about their workflow and gather their suggestions to provide the best recommendations and technology solutions.

One of our successful projects involved streamlining the prior authorization process at Lifepoint’s primary care practices. The prior authorization process was cumbersome for physicians and administrative staff. Our team first identified pain points, researched best practices, and then found an automated solution using a vendor. We received opinions from primary care physicians and administrative staff and pilot-tested the solution in several practices for proof of concept. We received and implemented positive, constructive feedback from physicians and administrative staff. We are exploring the expansion of the platform. The automated technology has enabled the task to be shifted to a centralized administrative team, increasing physicians’ clinical capacity.

In each of these cases, the algorithms and automated solutions could not have succeeded without the feedback of the clinicians, data specialists, and administrators. Each of our teams had the following takeaways from these projects:

• Involve representatives from different departments from the beginning to the maintenance phase of the projects. Representatives include physicians, nurses, data analysts, and operations experts.
• The project never truly ends. Team members should expect to be involved for several months, or perhaps years, as the algorithm and automated solutions are refined based on evolving patient and clinician needs. Expect the metrics to evolve as additional opportunities for improvement are identified.
• Communication is paramount to success. Each of our teams continues to meet regularly to review metrics, celebrate successes, and identify opportunities for improvement. We met more frequently at the beginning of the projects to discuss scope, roles and responsibilities, metrics, and potential impacts on clinical decision-making and non-clinical operations. Identifying the opportunity costs was important in decision-making, and ensuring that all team members’ voices were heard engaged them and allowed us to make the best, data-driven decisions for physicians, nurses, patients, and the organizations.
• Identify early adopters and allow them to conduct a pilot to ensure proof of concept. Physicians are often open to new ideas and solutions but would want to be involved early in the decision-making process and algorithm creation. Play to physicians’ autonomy to gain their buy-in, and explain solutions and algorithms so that they can connect how the solutions contribute to higher-quality patient care.

By including a multidisciplinary team in creating AI algorithms and technology to automate clinical decision-making, clinicians can return to what they entered medicine for: caring for patients as they would their own loved ones.

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Today’s health system pharmacy leaders face a myriad of challenges related to using technology in pharmacy practice. Strategic planning for capital support for larger systems has become a part of long-term financial planning as lead times for capital acquisition to support technology replacement on a ten to fifteen-year life cycle is required to maintain effective systems.

Electronic healthcare record (EHR) vendors are advancing in their support of pharmacy, but key areas such as sterile products compounding, pharmacokinetic dosing of medications to support personalized therapies, and lack of linkages between contracted payor reimbursement requirements and continued modifications of payment tactics between medical and pharmacy benefit in the ambulatory space offer areas for third party vendors to fill these gaps.

Human resources to manage these systems may or may not be located within the oversight of the health system pharmacy leader. Many organizations have created health informatics departments to support build for systems, but project management for large system implementations may need to be resourced, managed by the pharmacy operations team, or managed by the vendor. These scenarios create opportunities for governance as mergers and acquisitions occur to maintain standardization between EHRs, disparate pharmacy storage and dispensing systems, and various third-party vendor systems being used. Standardization efforts remain a focus as staff may need to rotate between facilities and efficiencies gained by having systems implemented in a standard fashion supports safe use and staff satisfaction. Other systems such as smart pumps may be purchased by Supply Chain leadership, maintained by Clinical Engineering, used by Nurses and Anesthesia, and have drug files maintained by Pharmacy or Health IT staff. These type of scenarios require multidisciplinary governance oversight to support change to drug libraries and maintain technology currency.

For health system pharmacy leaders who are supported by other departments from a systems perspective, maintenance of effective working relationships with health informatics departments, clinical engineering departments, nursing, anesthesia, respiratory therapy and other professions engaged in the medication management process are key to day to day as well as strategic planning for maintenance of these systems. Challenges in larger systems arise when lack of alignment in medication management-related initiatives arises. One part of the system may be advocating for expansion of bar code medication administration into ambulatory areas due to fatigue with manual documentation of vaccines during the pandemic, while the pharmacy may be advocating for implementation of image capture/gravimetrics to advance safety in sterile products operations, while others in the system focused on personalized medicine may be advocating for implementation of third-party vendors to support optimization of pharmacokinetics software. Division of focus may result in extended or inefficient implementation processes and when multiple vendors are introducing new products that require additional modification for optimization, getting systems to optimal operation may appear to be a never-ending process.

A new development for pharmacy leaders is the introduction of various interest groups to drive improvements in the healthcare automation space.

A new development for pharmacy leaders is the introduction of various interest groups to drive improvements in the healthcare automation space. Standardization of basic systems continues to be a need in the industry. Multiple platforms that do not interface in this age of health systems technology need to be mitigated. For example, this scenario currently exists in the RFID space. The UnitVis Alliance has been formed to advocate for industry standards in the RFID space to advance the use of this technology for tracking doses dispensed, managing inventory of high-cost medications, tracking temperature and humidity for medication storage and sterile products preparation areas and tracking equipment within health systems such as pumps, wheelchairs, beds and other durable medical equipment.

Another example in this space is the Autonomous Pharmacy concept being advocated by a cabinet vendor to address existing gaps in systems that require manual manipulation that result in inefficient systems and increased error. This group has published severalpeer-reviewed articles to support this advocacy and has launched a survey tool to help systems evaluate objectively where they are on the journey to fully automated systems. Expansion of efforts such as these to engage other vendors is complicated by concerns over competitive issues in the industry, but accomplishment of these long-term visions of fully automated systems with ISO 9000 levels of accuracy will require engagement across the industry to be successful.

Another approach in this space are institution-led grassroots efforts. Colleagues in Houston have recently launched the Boots and Roots Rx collaborative to bring together pharmacists, analytics, compliance specialists, project managers, health informaticists, and others to problem solve in this space.  

While these efforts are laudable to advance technology and practice, focusing on pharmacy informatics education and developing next generation of experts in this space remains a challenge for the health system pharmacy leader. Pharmacy informatics residency programs struggle to place residents and develop future practitioners in this space. Vendors have recently realized the dearth of training opportunities in this space and have funded fellowship programs to expose recent college graduates to various aspects of pharmacy informatics and industry-based informatics, along with graduate-level education in this space to support future iterations of leaps in pharmacy technology.

After thirty to forty years of EHR /cabinet/carousel/IV robotics/smart pump/, data visualization and analytics, health system pharmacy leaders must advocate for their systems with vendors and industry standard-setting organizations to vision the next generation of systems that fully interface throughout the medication use system from patient assessment to medication intervention via prescribing, through dispensing, to administration, and monitoring followed by assessment of contracting and reimbursement to support sustainable revenue cycles that support patient adherence and meet desired clinical treatment goals to improve patient quality of life must enter the broader conversation in this space. Without this focus, we are bound to continue limited improvement in these systems and will miss the opportunity for “moon shot” level initiatives that yield the technological advancements we need for our patients.

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One of the leading healthcare organizations in IL, Memorial Health based in Springfield is a five-hospital, community-based, not-for-profit organization that provides a full range of inpatient, outpatient, home health, hospice, behavioral health, primary and specialty care physician services in Sangamon and the neighboring counties. We deliver high-quality, patient-centered care in support of our mission to improve lives and build stronger communities through better health.

Like many other health systems across the country, Memorial Health is currently engaged in evaluating the “systemization” of clinical and financial systems. The value proposition of systemization was acutely present both at the start of the pandemic phase of COVID-19 – and even today as Memorial Health navigates the endemic stage of the pandemic itself. The ability to systemize clinical and financial systems presents the opportunity to streamline not only the patient experience across the continuum of care – but also improve the physician and colleague experience. In addition, the ability to manage our clinical and financial systems is critical given the current external pressures health systems are facing across the country.

The difference about Memorial Health is that our leaders and colleagues within our revenue cycle systems have the humility and willingness to not only “lean in” but to utilize technology to improve processes.

To give a sense of how immense this project is, Memorial is currently working to collapse four electronic health record (EHR) and patient billing systems underneath our Cerner enterprise strategy. Couple that with changes in how colleagues functionally interact with the electronic health record (EHR) and billing systems, one can see how big of a lift this priority is from a systemization perspective. This systemization strategy for Memorial Health is embodied in our “One Memorial” strategic priority, whereby all facility hospitals will reside on Cerner Millenium and ambulatory providers on Allscripts Touchworks. In terms of Memorial’s strategy for revenue cycle management (RCM), Cerner Patient Accounting was selected in 2015 as the source of financial record for both acute and ambulatory providers.

Memorial’s migration throughout our “One Memorial” strategy kicked off in 2019 with our transition to Cerner Patient Accounting. This transition, replacing two older, end-of-life systems, was immensely successful. With RCM system transitions, keeping steady cash flow post implementation along with recognition of system efficiencies is an absolute must. Memorial’s positive experience is attributable to each and every colleague within all of our revenue cycle departments. From Patient Access navigating a new registration system, utilization review nurses challenging level of care disputes within the electronic record and billing colleagues working with patients and insurance providers on account clearing, all members of our finance team “leaned in” throughout this implementation.

Our experience with our Cerner Patient Accounting journey is summarized by these key takeaways:

1. Net Days in AR decreased by 16%
2. Year-over-year increase of cash collection of 7% or more

Our success in RCM can be attributable to all members of our team working toward fulfilling our mission to “improve lives and build stronger communities through better health”. Each colleague understands the immense responsibility of being a representative of Memorial, and advocates for patients facing their darkest hours. There are many analogies that are used to describe RCM. From comparing revenue processes to a factory production line or an orchestra playing Beethoven’s 5^th symphony piece, the similarity in all of these analogies is the need for every colleague and department to work together flawlessly to navigate an extremely complex system in order to work efficiently.

The difference about Memorial Health is that our leaders and colleagues within our revenue cycle systems have the humility and willingness to not only “lean in” but to utilize technology to improve processes. We do this to not only better our processes, deliver a better patient experience, or generate more return through collections, but because it is the right thing to do for our communities.

While we here at Memorial feel we have strong leaders, team and culture, there are several complexities we are contending with in our markets. The predominant stressor we face is the increase in the time and resources it takes to manage all aspects of the revenue cycle process. From disputing level-of-care payor denials on the pre-bill side to challenging payor policies and procedures, the cost to collect has exponentially increased over the last few years. The role of both technology and relationships is the strategy we have deployed to combat these stressors.

At Memorial Health, relationships matter. Whether it’s the relationship with our patients, providers, colleagues or payors, our respect for developing these relationships over time is an important tool in our toolbox to combat increasing revenue cycle complexities. At all spectrums within our revenue cycle teams, the value of these longstanding relationships allows to work through revenue cycle barriers through thoughtful, concentrated and transparent dialogue.

On the technology side, Memorial Health is always looking for opportunities to utilize technology to improve our RCM capabilities. This includes reviewing the latest trends within the industry, third-party vendor product offerings or improvements within our Cerner enterprise infrastructure. Especially poignant in RCM is the role of automation, API’s or AI-based functions that can help alleviate repetitive tasks experienced by our revenue cycle colleagues. While this is a newly forming capability within RCM, we understand that technology is evolving and will likely be a key part of our strategic vision as we continue our “One Memorial” systemization strategy.

In closing, we here at Memorial are committed to our “One Memorial” systemization journey. This is an exciting time for all of us in RCM to continue to improve our capabilities in order to improve the health of the people and communities we serve.

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Some of you may remember the 1982 blockbuster movie E.T. the Extra-Terrestrial, in which a young boy named Elliot finds an alien visitor from another planet stranded in his backyard. Like most kids, Elliot decides to keep E.T. and thus begins an epic adventure involving his newfound friend as they hide from government agents who want to capture and study him, to fighting for E.T.’s life as the earth’s atmosphere is slowly killing him, culminating in a daring escape via bicycle to reunite him with his home planet.  Communication is a common theme of the film and Elliott helps build a device so E.T. can “phone home.”  This is retro-interoperability at its finest – consider what Elliot used to create E.T.’s communicator: a circa 1970’s Speak & Spell!, a Sears solid-state record player, a set of Fisher-Price walkie-talkies, a UHF tuner, a lantern battery, a coffee can, a wooden hanger, and an umbrella. In the movie, it worked and allowed for this random set of combined products and systems to interoperate and successfully send a message to E.T.’s alien compatriots.  That was 40 years ago when roughly 50,000 transistors could sit on an Intel 80186 chip, whereas today’s high-end processors boast up to 50,000,000,000 transistors. With that level of technical complexity and an ever-moving target, it is no wonder that we are still seeing interoperability challenges between products and systems in healthcare today.

So why is interoperability still a challenge in healthcare? If we look at other industries – BFSI, manufacturing, retail, etc., they share a higher level of maturity for interoperability between differing systems and technologies. One could argue that the delta between healthcare and these other industries boils down to market pressures, incentives, consumer expectations and data complexity. Health systems are still figuring out that they are really in the retail business and learning to be more consumer-centric in delivering healthcare services. Many barriers to successful healthcare interop are not technical, rather business or culture roadblocks – but even these are not insurmountable. The following focus areas are a good jumping-off point for any health system looking to reach its interoperability goals.

Educate your patients on what you are doing to keep their trust as a good steward of their data.

Regulatory

The introduction of the 21^st Century Cures act regulates the currency of patient data by ensuring your data is readily available and accessible. Run afoul of this requirement and you could be reported and face penalties and labeled a data blocker.

Action Item: Ensure you are running an EHR platform that supports open and certified APIs that encourages secure access to data for third-party applications. An outdated EHR certification is inadequate and does not satisfy the new requirements of the Cures Act Final Rule.

For the vibrant application ecosystem to reach its full potential, it needs to be underpinned by the open API framework. This will support continued innovation and added functionality in the application development space. The outcomes will reduce costs, increase patient safety, and bring enhanced data understanding to patients, providers, and health systems.

Data Consistency

There is still a considerable amount of disparate data in multiple systems in most health system networks.  Much of this data is inconsistent, unstructured, and requires a significant amount of time from technology teams to search, abstract, load, transform and analyze. 

Action Item:  Create a unified network and data interface platform that will support uniformity across the various software platforms. Establishing a uniform dataset where siloed information is pulled and properly categorized is an initial step in being able to share the data. Patient portals are commonplace today, and your mileage may vary based on what data is being shared and how easily that data flows to that information hub. Consider AI and ML tools that can help in this process of getting your data house in order. 

Organization Resistance to Data Sharing

In many geographic regions, healthcare systems still run in competitive market environments. With shrinking reimbursements, alternative payment models, and shifting customer loyalty, there have been vested reasons for not sharing data with outside entities and providers. Consider big city ERs or urgent care centers where Regulation now calls for this data to be accessible and available to any organization and ultimately, the patients themselves. 

Action Item: Health systems should focus on an open model of sharing patient data that still retains security and privacy while getting the right information to the right party, in the right format, at the right time. This does require collaboration and partnering with the needed tools to execute. Adopt proper data standards, HL7 2.0, HL7 FHIR, etc. and begin the move to data liquidity and transparency.

Security & Consumer Sentiment

Privacy concerns are still a main reason why many patients do not want their health data shared. This is becoming even more relevant as consumers begin to generate their health data with mobile phones and smart wearables that collect heart rate, blood sugar levels, physical activity, and sleeping habits. Federal HIPAA laws requires that healthcare organizations and providers protect patient records, which becomes very complicated when the data points of entry are entirely outside a provider’s physical network. 

Action Item:  The new consumer healthcare solutions that use wearables and mobile phones produce a lot of data and typically don’t have as robust protections as health systems require. Ensure that your data strategy addresses where the patient-generated data is landing, how it is appropriately scanned to meet security standards, and how it is secured. HIPAA is a bare minimum; you should aim for NIST or HITRUST certifications for added protection and privacy. Educate your patients on what you are doing to keep their trust as a good steward of their data.

The promise of better-coordinated care, lower costs, and increased patient safety cannot be fully realized without seamless data exchange and access. There are many paths to reach this interoperability goal, and most will need a new organizational mindset, adoption of standards, alignment of technical capabilities and reduction in data fragmentation – with hard work and a bit of luck, we can build something that even E.T. would be proud of.

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In my sixteen-year career at RWJBarnabas Health, I have seen the dawn of the modern-day Electronic Health Record (EHR). The health system has grown significantly since 2006 through mergers, acquisitions, and partnerships. This has resulted in the largest academic health system in NJ. Each time the health system grew, it introduced a new EHR or another instance of one already owned. At one time, there were seven different instances of an EHR. We are down to four, with plans to be on one by 2024.

EHRs have also grown since then, adding capabilities for interoperability because of enacted laws. Meaningful Use Stage 1 in 2010 was the beginning of EHRs as a sharing tool and has ushered in the interoperability features present today. The design of a health system plays a significant role, as it often decides the EHR infrastructure. Do you have a single instance of one EHR? Do you have one EHR with multiple instances? Multiple EHRs? *gasp*

Interoperability can be like Frankenstein or like an onion. Frankenstein interoperability is taking a piece-by-piece approach and hoping the patchwork will keep the system functioning. Often, this approach entails a sizable investment in both third-party software contracts and staff to support it, all to keep the clinician and customer experience consistent. The onion approach described below is the gold standard of interoperability. Each layer allows the organization to build its interoperability presence and maximize its reach for its patients throughout the community.

1. EHR

The core of the onion is the EHR. Intrinsically, the EHR is the most important part of building interoperability in an organization. Choosing one that easily sends, receives, and incorporates data, along with its ability to connect with third-party vendors to enhance capabilities, will decide how successful the health system can be in its interoperability journey. Choosing the wrong one can make the other layers of the onion impossible.

2. Sharing

The second layer of the onion describes how easily you can share your EHR with others. There are situations where a JV, partnership, or affiliate uses a different EHR to treat the same customers. Giving the ability to share the same instance lowers entrance costs, keeps one patient record, separates finances, and deepens the relationship of each organization.

3. Referral Network

The third layer of the onion describes connecting the rest of the community to your system. These are organizations that refer customers to your services (e.g., Laboratory, Radiology) but are not affiliated. E-Faxing is the preferred solution when an organization lacks this fundamental layer. EHRs can now supply “lite” versions of their software to allow groups to connect and keep consistency for the customer and health system. This approach tackles two key items. First, giving non-affiliated practices data they need to help the customer. Second, easing the burden of connectivity to foster the relationship of referrals to the health system.

4. Intra-EHR Data Sharing

The fourth layer is the exchange of data between health systems using the same EHR. This sounds simple, but often, EHRs miss the mark. Sharing can involve manual work by clinicians, which contributes to burnout. Sharing should be automatic and seamless. The intra-EHR sharing must go beyond the minimum Clinical Continuity Document (CCD). Data between like EHRs should share even more to complete the whole picture for a customer. The United States Core Data for Interoperability (USCDI) standardization is pushing this forward by expanding the amount of data shared in a CCD. This is a win for everyone.

5. Inter-EHR Data Sharing

The fifth layer is the exchange of data with dissimilar EHRs. When Meaningful Use (now Promoting Interoperability) began in 2010 with the introduction of the CCD, the bar of interoperability was set incredibly low. The CCD allows organizations to supply standardized blocks of clinical data to any other EHR system. There were two issues with this concept. First, programmers had to build logic into these systems (if they even could) to try to automate the process. Second, figuring out the direct addresses (think secure email) to send to was absurdly difficult, as there was no global address book to use. This often ended up with organizations meeting the bare minimum requirements to pass the Meaningful Use metric. Fortunately, Health Information Exchanges (HIE) are now prevalent and take the burden off the health system for exchanging data by serving as the repository for everyone connected.

6. Population Health Management

The sixth layer describes the health management of a population of customers. Health systems have a responsibility to care for the lives of assigned customers. Accountable Care Organizations (ACOs) help to improve care, control costs, and collect pertinent information about these customers. This allows customers get the right care, at the right time, while preventing duplicative tests and services. Having the ability for these ACOs to easily connect to the EHR and input this information is invaluable to the customers’ health journey.

7. Web services, APIs, FHIR, and SMART on FHIR

The final layer of the onion are third-party services. Third-party services should be complimentary. The extensibility of using web services, APIs, FHIR, and SMART on FHIR, allows the organization to enable services that will never be native to an EHR. Google & Apple Health, smart peripherals, and customer education services can pull and push data into the EHR through these means without intervention by clinicians and take the guesswork out for customers.

Interoperability is one cornerstone of customer and provider experience. When an organization has a Frankenstein approach, customer experience dips and clinicians become overburdened. The onion framework ties together the organization’s footprint, customer expectation, employee satisfaction, and connection to the community. So, which are you? A Frankenstein or an Onion?

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The need for agile IT infrastructure has never been greater. Two years into the pandemic, healthcare IT leaders face numerous challenges and increasing pressure to be more responsive to changes in care access and delivery. This is compounded by declining healthcare delivery organization (HDO) margins, cost improvement programs, lack of available SMEs, rising costs and supply chain issues. All of these are drivers for rethinking how IT services should be delivered in the future.

HDO technology professionals must remember they are in the business of delivering patient care, not IT. IT staff need to focus on how their subject matter expertise can support patient care and move away from core technology functions such as infrastructure and hosting. This is coming to life in many HDOs as a cloud-first strategy.

Identifying the Catalyst for the Cloud

The move to a cloud-based EMR was a key part of Seattle Children’s digital transformation strategy. We needed to unify and simplify our systems, be fortified to consume applications at a faster pace, promote seamless security, and make our system more agile and accessible. It was also critical our entire staff could access the EMR application at the point of care, anywhere at any time. These needs were heightened by the pandemic and a cloud-based system offered a myriad of benefits, including:

• Offloading responsibilities to the service provider (with a cloud-based managed EMR model), freeing up internal IT staff to deliver more innovation and focus on patient care initiatives.
• Building a technology platform that is future-proof and allows hosting of Epic applications and systems, as well as third-party ancillary and supporting applications that run alongside it.
• Maintaining high application availability and performance.
• Eliminating the need for in-house technical Epic SMEs to manage the system.
• Achieving predictable capped costs per year for the managed service and hosting.
• Maintaining a strong security posture and HIPAA-HITECH compliance.

On October 3, 2020, while navigating the pandemic, we replaced two highly customized EMR systems with a standard set of pediatric tools. We implemented an integrated EHR with Epic across 46 sites in four states. This was Seattle Children’s largest undertaking in the last 15 years and a momentous step forward to helping us provide the best possible care to every patient and their family.

We learned that demonstrating and communicating how the change will impact the IT team was a critical component for better change management and buy-in.

Changing the Culture

Implementing an enterprise-wide information system, such as a new EMR, is a major change project with a significant cost, which should not be underestimated. Moving to the cloud directly impacts IT staff, who will inevitably resist losing control of directly managing infrastructure they are familiar with. Early IT staff engagement outlining the upcoming changes and a good communication plan is important. In addition, having a well-defined process, some important milestones should be part of your framework: Building a business case, identifying the key considerations for your specific organization, and including your security team in the reviews. While many of these steps might seem obvious, when done right, you will gain credibility with your key stakeholders and simplify your approval process when it comes time to get funding for a project of this size.

In any project, there are always some failures; communication and engagement were areas we did not focus enough of our energy on. We learned that demonstrating and communicating how the change will impact the IT team was a critical component for better change management and buy-in.

When deciding on which vendor to select, we evaluated the costs and options for hosting with the internal IT team and two vendors, Epic and Virtustream (Dell). We explored fixed costs (per year), guaranteed service levels for availability and performance (with financial penalties), vendor size and capability, Epic certifications and subject matter expertise, track record of delivery, availability of a dedicated service desk, ServiceNow integration, green data centers, contractual flexibility, and the ability to connect data centers via multi-vendor, large bandwidth, dual resilient and diverse network circuits. With these criteria, we chose Virtustream (Dell) as our partner to host and fully manage the EMR.

Realizing the Benefits

Seattle Children’s hosted system has been live for over 18 months. Some of the benefits delivered include:

• Consistently exceeding uptime of 99.995%.
• One of our two data centers is 100% solar powered.
• Service levels at the infrastructure level for the cloud environment are backed by financial penalties.
• Log-in times, performance and user experience have improved compared to on-premises, and changes are delivered in days versus months.
• Epic upgrades are completed in 40 minutes versus 4 hours previously.
• The speed and ability to scale up and perform change control on the cloud environment improved. Changes can be made in days versus months.
• Costs are now predictable and future-proofed against increases with a shift from capital to operating expenditure.
• More advanced disaster recovery capability.
• Seamless integration with ServiceNow minimizes manual cycles for the staff while improving response times and reducing errors.

Considerations for Adopting a Cloud-Based EMR

As a starting place, organizations who are contemplating a move of their EMR to the cloud should:

• Inventory, review and refresh all your third-party applications and contracts.
• Develop a strong communication plan. Focus energy on change management.
• Build and manage the relationship. Your cloud provider needs to be a trusted advisor. Be diligent in the evaluation and select people-minded people. Retrain existing internal IT staff to manage the vendor rather than implementing the infrastructure.
• Properly prepare for contracting; it is time-consuming. Get an appropriate expert legal counsel to ensure that the terms and conditions and service level agreements are guaranteed and backed by financial penalties.
• Check the network bandwidth between data centers and ensure all network circuits are multi-vendor, dual, resilient and follow diverse routes.
• Guarantee flexibility. Work with a vendor who can adjust as plans change and is flexible, quick to respond and willing to negotiate terms.
• Ensure that the vendor has the right Epic certifications and SMEs, has a track record of delivery, provides a 24×7 dedicated service desk and integrates with your service desk ticketing system.

The post Why Moving the EMR to the Cloud Is the Next Natural Evolution appeared first on HealthTech Magazines.

One of the more interesting challenges that health system IT executives face today is evaluating and prioritizing new clinical applications for AI. Among the rapidly expanding number of innovations covering nearly every aspect of health system clinical and administrative operations, ambient AI is one of the more compelling technologies because of the immediate and longer-term value it provides. In our experience, the process of implementing an ambient AI solution can also serve as a model for testing and deploying other advanced intelligence solutions.

Our journey to ambient AI

We first considered ambient AI technology after Nuance Communications introduced its DAX system in late 2019 to mitigate physician burnout by reducing clinical documentation workloads. We were generally familiar with the Nuance system because it uses speech processing technology that evolved from its Dragon Medical One software used by physicians at SCL Health and other health systems. In mid-2021, we began deploying Nuance’s DAX system at our $2.8 billion faith-based, nonprofit healthcare organization serving patients in Colorado, Montana and Kansas.*

The tool works automatically in the background, securely capturing conversations between clinicians and patients during in-person or telehealth visits. The keyboard and screen that typically require the physician’s attention are replaced by an unobtrusive, low-cost device like a smartphone or tablet. DAX records and converts the interaction into AI-generated clinical notes which are routed through a quality review process to ensure accuracy. The system continuously learns and becomes increasingly accurate and efficient with each word.

The resulting documentation is presented to clinicians to quickly and easily review and approve in the EHR system as part of their day-to-day workflow. If a physician has any questions about the generated notes, the recorded interaction is available for review.

Goals and deployment plan

We first defined how the system aligned with our strategic goals for improving physician satisfaction, expanding digital patient engagement, and using EHR system as a platform for innovation. We also viewed our implementation of the Nuance system as a critical opportunity to work with a technology vendor as a trusted partner vs. following the traditional buyer-supplier model.

We then identified cohorts of providers as early adopters. We included specialties best suited for DAX usage including cardiology, orthopedics, and other clinical areas with relatively standardized terminology and exam procedures. We also incorporated family medicine providers to assess the system’s ability to learn more diverse vocabulary and patient scenarios. In addition, physician need was determined by analyzing signal data from our Epic EHR showing providers who spent more time working on documentation either during or after clinic hours.

We narrowed an initial target list of 50 providers to 25, 10 of whom declined to participate in the initial deployment for various reasons. Deployment began in May, followed in September by an assessment of system performance in a total of 5,426 patient encounters.

AI outcomes and benefits

We evaluated the AI system’s performance based on:

• Increased operational efficiency through reduced documentation time, increased throughput, and greater access to care:
  • An average of 13minutes saved per encounter (family medicine)
  • A 50% reduction in physician documentation time
  • An average of 1.7 appointments added per clinic day (family medicine)

• Higher clinician satisfaction from reduced administrative workloads and higher quality documentation:
  • 50% reduction in feelings of burnout and fatigue
  • 60% of physicians were satisfied with documentation turnaround time
  • 60% would be disappointed if they no longer had access to this system
  • 70% of physicians say the system has improved documentation quality

• Better financial outcomes through time savings and incrementally higher revenue from more accurate clinical documentation and appropriate coding:
  • $104,537 in annual added value through time-saving per provider (family medicine)

• Improved provider and patient experiences with clinicians feeling more rested, focused, and engaged with patients, and patients having positive experiences in encounters with physicians using AI. Patients familiar with consumer voice applications felt comfortable with the system and felt they had chosen modern, well-equipped providers and facilities:
  • 80% overall increase in the quality of the overall patient experience
  • 60% of physicians report higher-quality patient interactions
  • 70% of patients report an increase in provider face time

Additionally, documentation turnaround time steadily declined from 5.26 hours in May to 2.19 hours in September, while utilization of the system increased to 60% of scheduled appointments.

Today, we have a fully voice-enabled and ambient exam room environment using this AI technology. The system frees clinicians to focus on their patients, gives them back time in their day, and enables them to practice at the top of their license. From an IT perspective, the system reduces complexity because it enables a single cloud platform and single workflow solution for all clinical environments.

Implementing ambient AI represents an opportunity to establish partnerships with IT vendors.

Best practices and outlook

Implementing ambient AI represents an opportunity to establish partnerships with IT vendors. We worked closely with Nuance, collaborating on everything from iterative system changes and improvements to pricing, and making service level agreements and shared risk an integral part of our relationship. In addition, Nuance has consistently shown a willingness and ability to respond to user feedback. The DAX systems we use today are small, inexpensive devices that replaced the bulky, wall-mounted, first-generation designs introduced in 2019.

We also worked closely with physicians who understood the challenges and opportunities of implementing ambient AI to empower them as technology champions for their peers.

Looking ahead, we plan to offer DAX to clinicians in other clinical areas through a repeatable process of expanding small, targeted deployments to more users, incorporating learnings from each one to maximize the value of our investment. We see this process as a transferable model to future implementations of advanced technologies.

* SCL Health and Intermountain Healthcare are planning to merge in early 2022 and form a 33-hospital system with more than 58,000 caregivers across six states and provide about one million people with health insurance.

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We are at the peak of electronic medical record (EMR) despair. We were promised a utopian future where EMRs would improve communication, reduce the burden on handwritten notes and flowcharts, make administrative tasks more seamless, and hasten clinical research. While it seems our peers in other industries are charging into the information age, we in healthcare seem stuck firmly in its infancy. While the road is long, the destination is promising; and, like objects in the rear-view mirror, closer than they appear.

Twitter is awash with clinicians complaining about the additional overhead and stress caused by clunky EMRs. Some suggest that the added burden of EMRs contributes to provider burnout. Small physician groups or solo practitioners have suffered under the financial burden—many forced to close shop or join larger physician groups. As IT professionals, we are acutely aware of the difficulty of building custom applications on top of EMRs or integrating with other systems. As a result, EMR vendors have been forced to build integration and interoperability but aren’t going down without a fight.

Is the benefit worth the cost?

Are we seeing the benefits we were promised?

The answer: yes… almost.

We are tired from climbing to the peak, but as we summit the rise of EMR despair, we have an easier journey ahead of us. This utopian future is not inevitable. It will take a concerted effort on the part of providers, developers, EMRs vendors, regulators, and the broader HIT community to move the industry forward. At the core of this revolution are API-based integration and open standards such as FHIR that will enable secure, seamless integration between applications and building-block-like microservices. Advances in machine learning, artificial intelligence, and information retrieval will help reduce the burden on the end-user to sort through thousands of irrelevant data points, highlighting the most relevant information and aiding in diagnosis, communication, and disease management. Sensors, wearables, and IoT devices will further reduce the burden on clinicians to document and interact with the EMR directly.

As artificial intelligence/machine learning becomes more ubiquitous and easier to deploy in production, these tools will become increasingly important in information retrieval and reducing the clerical burden on clinicians.

The EMR is the glue that binds various systems in a healthcare system. As such, the EMR should act more like a platform than a stand-alone product. At the heart of any platform is a set of APIs and integrations. FHIR is a promising start and essential to achieving the ultimate vision. Future development on FHIR, such as bulk patient reads, will be critical to executing this vision. The EMR should be the central touchpoint for a provider and abstract away the various services and components working behind the scenes.

As artificial intelligence/machine learning becomes more ubiquitous and easier to deploy in production, these tools will become increasingly important in information retrieval and reducing the clerical burden on clinicians.

Currently, we rely on hard-coded alerts such as critical lab values or we expect clinicians to review results manually. Manual review of results does not scale, especially as the number of inputs and the frequency of data increases. For example, to efficiently manage a large remote patient monitoring practice that may enroll thousands of patients, manual human review of the data would be inadequate. Imagine streaming data from a wearable or implanted device and reviewing heart rate, respiration, EKG, pulse oximetry, fluid status, and steps manually. To efficiently implement such a program, one would need to use machine learning to alert where a clinician may need to intervene. This series of machine learning models would need to remove anomalies (we don’t want alerts every time a patient walks up the stairs), and potentially integrate with the EMR or other clinical systems to learn the clinical context.

Artificial intelligence and machine learning will also help summarize a patient’s past medical history and current clinical conditions and should help extract the findings from the totality of their medical record that are relevant to a given clinician. Improvement in semantic search will further reduce the burden on the clinician, allowing them to quickly find results or notes that are relevant to their query.

The proliferation of sensors, wearables, digital assistants, and IoT devices will further reduce documentation burden. A smart syringe may know what medication is being drawn up by a nurse, how much of that medication, and which patient is getting the medication. Nurses will not have to document vital signs, medication administrations, and other events that can be gathered from alternative sources.

Digital assistants will be installed in exam rooms and listen to a doctor’s conversation with a patient and will be able to pre-populate notes. Not only will this reduce the documentation burden on the clinician, but it will also capture a complete record of the encounter, and allow the doctor to speak to the patient without worrying about taking notes, clicking boxes, or dealing with the EMR during the visit—we will start to bring humanity back to medicine using technology.

Hang in there! While we are currently at the peak of EMR despair, the future is bright. By focusing on building EMRs with clean, intuitive user interfaces that act as a platform for uniting other technologies, we can reinfuse humanity into medicine.

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The Changing Healthcare Business Model: Do we really need an EMR?

It is interesting that we see that “necessity is the mother of invention” coming to become so true in the times of the pandemic. Using the past 18 months as a catalyst for innovation, the healthcare industry has been transformed to accept the ability for remote care. It has improved patients’ ability to take care of themselves. We have seen anecdotal information about patients getting better at home using hospital at home capabilities.

We still live in a hefty fee-for-service world. We have some sprinkling of value-based care, but our system is based on traditional medicine. Another key factor was based on how the system reimburses for care. The question is: Is this the most effective? Are we going to continue to do this for the next 20 years while we keep complaining that our healthcare costs us too much with lower outcomes? We, as an industry must change. We need to embrace the catalysts and catapult us to a broader outcomes-based model. Situational awareness and incentive to life are key to understanding the patient and the delivery system for better outcomes.

The tech is available today, however, our shackles of regs and compliance force us to thwart newer models of care.

The Dichotomy (FFS and VBC): Can we co-exist in this dichotomy model of fee for service (FFS) and value-based care (VBC) together? Some evidence points to us that it is hard. Hard on the people who work in it (clinicians and RVUs) and hard on the people who experience it (patients – perceived loss of freedom). The administrators perceive a loss of revenue due to lost inpatient bed days while the VBC physician is trying to keep the patient out of the hospital in a VBC world. Compromise and conquer for better outcomes.

Patients and their info: Why do we make it this hard? Information is what gives our patients power? We saw this during the time of the pandemic. Why do we not provide the information our patients need in their portals? Example: Link lab results directly with approved ranges so they can understand what it means (they do this anyways – “Hello Google”). How many other consumers have the same range in their lab values? How do they connect with them? What did those other consumers do to get back in the range? Ultimately that is the outcome the physician expects out of the patient, correct?

These are the questions we must ask ourselves. Why cannot we provide complete transparency to their eligibility? Can a customer execute a HIPAA 270/271 transaction to understand what is their eligibility in English? Can the customer arm themselves with pre-authorization so that they do not have to rely on the provider’s office or the hospital to do that? Empower the patient (rather, get them to do the work. When last did we call an agent to book our flights?). Are we afraid that our patients will get better care somewhere else? If so, is that not providing better value to the healthcare system as a whole?

A few weeks ago, we talked with the Center for Medicare and Medicaid Innovation (CMMI) leadership. The ability to get virtual care is here to stay. We can extend every possible opportunity for the patient to get care on their own at home.

At Franciscan, we are making a paradigm shift in care processes. For example, we did what we call virtual inpatient multi-specialty rounding. A group of consulting physicians: a pulmonologist, a cardiologist, an intensivist, a hospitalist and a dietician meet and talk about a patient while the patient is in bed through a virtual iPad-based TEAMS call. Change meds, order labs and collaborate care leading to a lower length of stay. Ok! It is not that easy, but you get the point. Changing our care processes will deliver better value and ease physician burnout (six patients in half an hour).

Here is another one. A patient does not want to walk in to see his cardiologist but is willing to drive to the clinic due to poor internet (for a virtual visit). He drives into the parking lot; an iPad is given to him and he has a virtual visit and gets his prescription with his favorite pharmacy on his way home. Could we convert all visits this way if the patient does not have to drive in?

The Hospital – is considered the epitome of care today. But is it so? We have then to take care of CLABSI, CAUTI, Sepsis and dozens of hospital-acquired conditions while the patient is in. But we have seen evidence of the dozens of patients who got faster and better care if they stayed at home. Not all patients have the capability, but can we allow those patients who can do that to stay home and deliver virtual care maybe thrice a day?

The EMR – a cornerstone of documenting for the sake of compensation. While we have taken every possible action to drive discrete data capture, do we need that in an AI-based natural language processing (NLP) world? Can we not make this all interactive that the physicians can talk to their patients while the ambient sound system captures the conversation and auto-create a note and bills for it? The tech is available today, however, our shackles of regs and compliance force us to thwart newer models of care. Guess what? We have almost all our data on the internet and are willing to freely share with other patients to learn what they did to get better. And, of course, we are “death by consent” conscious.

Unless we think globally, we cannot change. Seize the moment and drive change for the better! Hopefully, we all will come out with better outcomes, with lower cost and greater access in the next 15-20 years.

The post Seize the moment and drive change for the better! COVID-19! A Catalyst for Innovation appeared first on HealthTech Magazines.

Physicians hate change. Physicians hate technology. Although erroneous, these beliefs are pervasive in the tech world: an overwhelming attitude that physicians are technophobes. I’m here to tell you the opposite: physicians love change. We willingly chose a profession where we know that we are standing in a place of ever-changing protocols and procedures. There is always a new medicine, a new device, a new theory of disease and a new pathogen to fight. If there is one single concept that underlies the practice of medicine: it is change.

Physicians also don’t hate technology. We embrace the newest technology in a heartbeat. CT scans instead of X-Rays and then MRIs. Cancer treatment protocols change every few months.  We also embrace technology in our personal lives. Many physicians drive the most technologically advanced cars, have the latest gadgets in their homes. The difference is: change in medicine works for our patients; change in technology works for our lives at home and makes it better – change in healthcare technology often does neither.

The ability to understand the fundamentals of the technology and to give critical feedback is a crucial part of enthusiastic physician adoption.

So what do physicians want and need from technology to help them embrace change? I’m here to tell you the top three things that make a difference for your doctors, and by proxy, for their patients.

It Works In Our Ecosystem

Healthcare is complicated. Most health systems have adopted electronic health records, but there are also multiple other systems that clinicians need to interact with. In the hospital – proceduralists often have to log into separate systems. In the ambulatory space, in order to view images or records from other systems, we often have to log out of our primary system and into another source. Every log-in is a challenge to remember the new password, make sure that you have the right security and seldom achieved in 3 clicks or less. Every additional log on is a burden. The question, therefore, to ask about any new technology is – does it work in your ecosystem. Do your providers have to enter a new password and switch back and forth to the product, or is it seamlessly integrated into their day-to-day workflow. Every additional log-in is a barrier to adoption, even if the product has genuinely revolutionary features.

Less Data, More Information

Health care electronic health records (and many products being developed) are data rich, yet information poor. EHRs have made data abundant, but the information actually needed to properly care for a patient is often buried and poorly curated. As we enter into our 40th year of EHRs, the data is overwhelming. Every physician has a story of how a crucial finding, such as a suspicious lung nodule, was buried in the mass of data of a recent complex hospitalization for another reason and therefore almost missed. Does your tech give data or does it provide information? A great example is the use of remote patient monitoring. Tech gurus these days evangelize about being able to wear your device and have your health information delivered directly to your doctor’s office. As a physician, I cringe, thinking of getting every slightly abnormal heart rate from all of my patients. As it is now – the typical primary care physician receives 100 or more “messages” a day which can range from labs, to patient concerns, to imaging study results, all of which have to be placed in the context of the right patient and interpreted according to their unique situation. The onus of that interpretation is all on the physician or another licensed provider. What if our systems actually gave us information – not data? Right now, EHRs get around this issue by presenting all this data on one screen for the physician to consolidate all that data into information. Wouldn’t it be revolutionary if our tech did that for us? In short, don’t aim to give physicians and advanced practice providers data – aim to provide them with information.

Let Us Look Under the Hood

One of the newest levels of computers and/or artificial intelligence challenges is that the technology and algorithms are considered proprietary. Until this stage of scientific development in medicine, physicians and advanced practice providers have always had a way to review, challenge and innovate around any technology. Now, the technologies are all proprietary, leaving physicians to trust blindly that it works. Physicians are trained that if things are not making sense to challenge the basic assumptions. It’s not unknown for physicians to request the lab take a look at, and if needed, recalibrate the instrument, if the results for a group of patients seem abnormally high or low. With tech – we’re asked to trust that the algorithm is working a certain way. The proprietary nature of intellectual property surrounding much of 21^st century technology makes the ability to “look under the hood” harder. We understand the need to protect one’s work, but the inability to get the fundamental understanding of how a product works to produce the end product, at the very least breeds inherent mistrust (because, in the end, it’s our medical licenses that we risk with every clinical decision) and at the worst, produces inequitable outcomes, like the reported results seen in 2019 with Optum’s algorithm to predict the illness severity of patients. The ability to understand the fundamentals of the technology and to give critical feedback is a crucial part of enthusiastic physician adoption.

If you can deliver any, or preferably, all of the above to your physicians and care teams: tech that works in their ecosystem, delivers valuable information and in a format where they understand and, if needed, can challenge the tech and make it better, you will have an engaged and involved team of physicians who will not only adopt but champion your next big technological advancement.

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