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.

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.

The post The Peak of EMR Despair appeared first on HealthTech Magazines.

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.

Thanks to technology, our lives are connected and convenient in so many aspects. However, while everything from getting a ride to ordering groceries is as simple as pressing a button, healthcare still lives in the dark ages.

If ten people are asked about their healthcare experience, around 8 would say it’s sub-par. Until now, consumers haven’t had real alternatives for healthcare and were forced to accept an experience that was difficult, lacked transparency, and cost more than it should.

But the landscape is changing. With major players entering the market, the threat to traditional healthcare organizations is real. These disruptors are part of patients’ daily lives, and have already perfected user experiences. If changes aren’t made to meet or beat disruptors in these spaces, hospital systems can expect to lose many high-volume encounters. 

Enter the product organization. Thinking about patients as customers and adopting the product-centric mindset of solving real needs and meeting people where they are is a new, but necessary trend for healthcare. Equally important, treating clinicians as true users can help decrease burnout and improve overall patient health.

Technology in healthcare is woefully behind, but technology alone can’t solve the problems. That’s what led to the mess of the EMRs we have in place today—built by software engineers to digitize a process without considering the impact to the end-user. Without a long-term, strategic, user-centric roadmap, EMRs are massively expensive solutions that make it nearly impossible to integrate or pass data outside the system walls. Patients suffer, doctors suffer, our collective health and wellbeing suffer.

Product teams ensure the voice of the user – patient, clinician, or consumer – is known, represented, and used to make strategic decisions about solutions. 

More than that, product teams allow operational and clinical staff to remove the “IT hats” they’ve historically worn and focus on their areas of expertise. Being fully embedded with operations, the product team lives and breathes their vision and strategy, and suggests products to help achieve targets. When operations teams can forget about IT, they can focus on streamlining operations, cutting costs, and improving care. 

By studying the industry, competitors, and keeping a keen eye on parallel industries, product teams not only know what exists today, but are in tune with trends to predict what will be important to users in five years, and build the foundation to get there.

The balancing act between ensuring a product adds value to the user, the business, and is technologically feasible is harder than it sounds. Many attempt to find this balance but allow egos to get in the way. Those who truly succeed in this space worry less about who generated ideas, and more about delighting users. These are products consumers gladly buy because the experience is superior to any other. The ones that integrate so seamlessly into life that moving to a different product is painful. These companies are consumed with the user experience. It’s their end all, be all, it drives every single decision they make, all the way down to the tiniest detail. They live and breathe product, and it’s why they excel.

It’s time for healthcare to shift their focus to the user, to make experiences so good, that the patient can’t justify a move, the best clinicians are fighting to work for institutions who have brought the joy back into healthcare. So good that people regain a sense of control over their health. It’s time for product to become the new norm in healthcare.

The post Why Healthcare Desperately Needs Product Teams appeared first on HealthTech Magazines.

At Henry Ford Health System, our Revenue Cycle leadership with support of the Revenue Cycle Transformation Consulting and Analytics team, utilizes an annual playbook to drive performance improvement for hospital and employed physicians, emphasizing patient experience, yield optimization, and lowering cost-to-collect. Playbook typically contains 70-100 projects related to enhanced workflows, technology, and performance. 

Our yield improvement initiatives have resulted in significant outcomes, including reducing preventable loss write-offs to 0.77%, raising residual self-pay collection rate to 65%, and improving risk scores by 31%. The improvements in these areas that we refer to as Revenue Cycle Classic have yielded cumulative gains of $572.6M through 2020. In recent years, Playbook programs have expanded beyond “Classic” into risk adjustment, value-based care and utilization management, reflecting industry trends shifting from pure fee-for-service payment models towards pay-for-value. The playbook is refreshed continuously, with a more thorough review and update on an annual basis. Playbook projects often span multiple years and a two-year Gantt model is maintained for tracking timelines.

For 2022, the playbook is incorporating a Mosaic methodology for the first time. Under this approach, Revenue Cycle is being thought of at a much more granular level than the usual front/middle/back model reflecting patient access, coding and documentation improvement, and business office. Planning is organized around 35 distinct functions, which include registration, insurance verification, authorization procurement, charge optimization, physician education, clinical documentation improvement, coding, billing, cash posting, and call center. For each of these functional areas, “tiles” have been developed to assess opportunities in the areas of yield, cost, productivity management, and technology. Additionally, for each of the 35 functions, a 10-year strategy has been created to plan for future Playbook content.

Common patterns are emerging within these Mosaic tiles, especially in automation, self-service patient experience, and payer connectivity. Technology deployment is the underpinning in almost all instances and will require forward-thinking to figure out how it will impact workflows and the patient/provider experience. However, predicting the top vendors and applications in this space after ten years from now is anyone’s guess.

Sifting through an array of innovative start-ups and development plans for scaled technology presents challenges between a provider’s short and long-term planning and aspirations for the future of revenue cycle. To that end, we’ve identified a few guiding principles that are enabling our organization to keep moving forward:

• Avoid paying twice for the same functionality. Because core technology providers are moving fast, gap analyses should be continuously performed to ensure that available features and functionality are deployed. Be aware of current and future capabilities. Core technology not only includes Revenue Cycle platforms such as EHR, but other major applications and services. It is important to assess each core application and how the platforms integrate.

• Consider the “Automation Hierarchy” in Technology Planning Efforts. Historical frameworks for how work is accomplished are no longer a viable option. Much like how early automobile designs emulated “horseless carriages” before departing into their own paradigm, automation that relies on existing workflows are transitional at best. Anthropomorphic models such as keyboard emulation vehicles underpinning Robotic Process Automation (RPA), high-volume screen-scraping of payer websites designed for human users and scanning will give way to higher-order automation such as core system optimization, direct payer connectivity, optimization of EDI data formats, and digitization of analytic material.

• Ensure a viable exit strategy when bridging core technology gaps with Best of Breed (BOB) point solutions. There is a place for filling Core Technology provider gaps with BOB solutions when done in the context of core provider development cycle knowledge.  However, be open-minded when other options become available. Cost, integration with core systems, and “loss of fidelity” of core technology are drawbacks, as are the complexities of implementing and maintaining interfaces. Rely on your ROI analyses and negotiate wind-down strategies for when Core technology gaps close or other better options arise.

• Be wary of gain-sharing arrangements for technology. We all know that technology will continue to revolutionize the workplace and further erode human touches at the individual transaction level. Provider organizations will understandably rely on this to meet economic headwinds facing the healthcare industry. However, payments under these gain-sharing arrangements could be redeployed to relieve the pressure on direct patient care investment. 

• Assess and categorize the Technology Provider landscape and timeline to deploy versus surveil continuum. Each Mosaic function presents a unique array of technology and technology partner options. In some cases, clear winners can be identified, and long-term partnerships can be pursued. Where technology approaches are more turbulent and emergent winners are unclear, consider a more cautious approach of utilizing short-term partnerships to achieve greater portability.

There is consensus that automation and other technology advances will radically change Revenue Cycle over the next decade, requiring discipline and a structured approach to enhance the patient experience and meet your financial goals. Having a clear understanding of your core system capabilities will put you on the right path forward.

The post Core Technology Drives Revenue Cycle Playbook at Henry Ford Health System appeared first on HealthTech Magazines.

Migration to the cloud is an ever-present reality in most organizations. Healthcare is certainly no exception. Healthcare was not as fast to adopt cloud strategies mainly due to the stringent requirements to safeguard data and be able to show compliance with HIPAA and other state and federal regulations. An effective cloud strategy is a must for organizations who want to become more focused on patients and effectiveness in outcomes-based research. 

It’s important to understand on large and complex applications that not everything which is required is necessarily a cloud resource. In the case of an electronic medical record (EMR), there are many services which help create a patient’s medical record, not all of which can be abstracted in the cloud with a vendor-provided resource. While the EMR vendor will provide a robust experience for physicians and patients, getting the data from your premises location into the EMR in the cloud still requires a hefty investment in on-premise infrastructure.

With more than 2,000 clinicians, my organization is engaged in the largest and costliest project ever next to constructing new buildings. What is the project?  We are migrating from an on-premise implementation of an EMR to a cloud-hosted EMR with a different vendor. As an academic health science center, we are primarily dedicated to outpatient services and advancing health science careers through six distinct graduate-level schools in the health sciences. 

As the decision to migrate to a cloud EMR emerged, people at various levels in the organization started to shave off large costs associated with things such as running a data center, maintenance software, personnel, and other expenses. It came as a surprise to many of us that going to the cloud is not always as simple as standing down all your on-premises infrastructure. 

Our current EMR, and its many tertiary systems which feed into it, require more than 1,000 servers spread across multiple data centers with advanced real-time failover clustering technologies. The expense to maintain this environment, regardless of the EMR software licensing costs, is immense in hardware, software, advanced private fiber-optic networks, and personnel. The migration to the cloud is an obvious choice for an EMR as you get to invest less in local infrastructure and turn large capital investments into a recurring and known operational expense.

In our example, we will be standing down more than 850 physical and virtual servers currently providing access to our on-premise EMR. These servers provide all user entry and backend services such as reporting and analytics. As the project was just getting started, we thought we might not be standing up any additional new servers and services, but that changed quickly into the first set of meetings. It started simply enough with how users will login to the cloud-hosted EMR. It seems simple enough, but you may need to extend your login directory servers into your cloud-hosted EMR datacenters in many cases. In fact, when it comes to users, you may be responsible for all account and role provisioning, which is then synchronized to your cloud-hosted EMR. All of this could require new authentication and directory system, which you do not have deployed today, which was the case for us.

Don’t forget you need to feed your EMR from many connected systems you have on-premises.  Those systems remain and you will have to develop new routines to interface these into your cloud EMR.  These could be laboratory and imaging systems from varying modalities. Most cloud EMR vendors do not handle electronic FAX directly, so you may have to extend, replace, or modify your existing FAX product to interface with your new product. The last item may be one of the most mundane but vitally important to be certain to understand early, printing. As much as we like to believe it’s an all-electronic world, physical printing is still a standard practice in most outpatient clinics and hospital wards. This printing includes everything from standard reports to labels and patient armbands. Getting your print jobs from your cloud-hosted EMR down to your local printers will require new infrastructure and lots of planning before production and after go-live. 

You may also find yourself developing custom automation scripts for the movement of lots of data between systems that you did not have to perform before migrating to the cloud. We have currently created more than 150 automation routines which accomplish certain tasks, such as moving an incoming FAX from the FAX server to a location to be ingested by our patient documentation system, which can then be viewed by the physician in the EMR.

My organization is set to go-live with our cloud-hosted EMR in May 2021, and here are some observations I think are important for anyone else looking to make a similar move.

1. Make no assumptions plan on asking your cloud EMR vendor a lot (LOT!) of questions. In large and complex applications such as EMR, many things are included, but not everything. You will need to formulate many questions around your current environment and processes and make sure you fully understand your responsibilities before moving forward.
   
   
2. Your TCO will be an estimate. If you have done even your best accounting homework, you will discover that your total cost of ownership is estimated. Many items come to light as the project planning starts with your cloud EMR vendor, which can derail your TCO in significant ways. Plan a fund reserve with a process to approve and track expenditures over a certain value. A good governance process can provide great value in this regard.
   
   
3. Give yourself some time in the schedule. Much like your early TCO projections, your estimated timeline should be considered a starting point, but flexibility may be required. Depending on your vendor and access to specialized personnel resources required, you may have to alter your go-live dates. This can be especially difficult when you are already paying for an on-premises EMR and starting to incur costs for your cloud EMR. However, best to plan the extra time and go-live with the best product.

The post Infrastructure Needed For Cloud EMR appeared first on HealthTech Magazines.

On June 30, 2020, IBM Watson Health announced the annual 15 Top Health System awards based on published quality outcomes from the Centers for Medicare and Medicaid Services (CMS). A truly remarkable feat for the 15 systems that were recognized and, more importantly, the patients of these top-in-class systems. The top system in the large system category was the HCA Healthcare Continental Division, with hospitals located across Denver, Colorado, and Wichita, Kansas.

The IBM Watson Award is based on its Top 100 Hospital methodology, which uses data from publicly available sources including MEDPAR, the CMS Hospital Compare data set, Medicare spending, and HCAHPS patient experience survey data. From these data sources, IBM Watson derives ten quality performance metrics. The leading health systems are then segmented into small, medium, and large systems. The HCA Healthcare Continental Division was recognized as #1 in the large system category.

The HCA Healthcare Continental Division uses the Meditech Magic EMR since it is long-implemented, very stable, and has low support expenses. This award shows that health systems can achieve quality excellence without paying a premium for their EMR. From an IT perspective, while the EMR is essential, many other IT factors and technology developments play a substantive role in delivering and monitoring quality.

So how is the HCA Healthcare Continental Division leveraging its less expensive EMR platform and related technologies to achieve these stellar patient outcomes? The focus is primarily on:

• Tight collaboration between the key health system constituents at every phase (planning, delivery, and review)  including the clinicians, support teams, and IT;
• This results in well-defined clinical quality goals and achievable action plans;
• Clinician-centric, intuitive interfaces and order sets that drive high-quality care implicitly and also build into the ordering and documentation processes;
• The power of data, broadly aggregated in HCA Healthcare’s non-EMR data warehouse, analyzable not just retrospectively, but increasingly in real-time;
• The live delivery of actionable information and clinical recommendations, in a concise, meaningful way to the target clinicians– increasingly via HCA Healthcare’s internal non-EMR clinical mobile platforms;
• Constant performance review – which leads to adjustments in all of the above;
• And respect for the adage – People, Process, and then Technology.

In the United States, many health systems began broad EMR implementations in the 1990s, and thus the US is in its 4^th decade of EMR usage. Interestingly, the three most sizeable system EMR vendors in the US today – Cerner, Epic, and Meditech – have their business and technology roots in the 1970s. This length of time and the penetration of EMRs in health systems indicate EMR technology is a mature industry – as is the data organization in the EMR and many of the user assumptions, workflows, and experiences that occur within it.

EMRs are essential to a health system, but often their information presentation methods are dated. They are analogous to a card catalog system in an extensive library assuming the library user has some idea what they’re looking for and where to ‘pull it.’

Modern data/analytics tools and mobile data delivery systems turn this approach on its head.  They enable identifying actionable data and clinical paths, and can ‘push’ such data and recommendations to the right clinical users, often via mobile platforms.

As Professors Lakhani and Iansiti advocate in their recent book “Competing in the Age of AI,” an intuitive user interface is critical, but the real power of software systems is in the data. HCA Healthcare’s Continental Division increasingly benefits from HCA Healthcare’s substantial investments in its enterprise data warehouse, analytics tools, and flexible messaging layers to deliver data, and mobile apps and hardware that put actionable information in the clinician’s hand.

Examples include real-time analytics that trigger text alerts to the clinical team that reduces the central line and other hospital-acquired infections, sepsis risk alerts, and proactive messages to mitigate pressure ulcers. Additionally, HCA Healthcare has developed and deployed machine learning algorithms to screen for and intervene when a patient may be decompensating in an acute care setting based on a variety of clinical data feeds. 

Nearly 50 years ago, Dr. Avedis Donabedian proposed a model to achieve  quality care in health services via “structure, process, and outcome.” HCA Healthcare Continental IT leaders have adopted that, and refer to “People, Process and Technology” every day. Clinicians always consider and acknowledge primarily the people part of this equation and consider the impact of technology on our ‘clinical customers.’ After all, it is the 24/7 bedside clinicians delivering that care where patient outcomes achieve true greatness. And similarly, it cannot be over-emphasized the clinical leaders’ central role such as CMOs, CNOs, VPs of quality and process improvement, and medical directors.

HCA Healthcare’s increasing focus on data, analytics, and actionable clinical information delivery has enabled the HCA Healthcare Continental Division to achieve this IBM Watson recognition, and most importantly, benefit our patients. During this challenging period in the history of humanity, this award further inspires us to continue our clinical collaborations and maximally leverage modern technologies to improve human life.

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The healthcare industry is constantly changing in ways that healthcare providers cannot control.  Changes in payor billing requirements and payment models, along with fluctuations in patient demographics and health conditions can cause struggles for organizations with poor processes. Successful organizations must optimize their controllable procedures and create the bandwidth to address industry changes they simply cannot control. The use of technology to maintain financial stability is essential in this ever-changing industry.

Front end revenue cycle begins with patient registration and ends once payments are collected. Obtaining the correct insurance information and patient health profile upfront allows a company to develop the appropriate plan of care tailored for that specific individual. Many patients need health care right now and time is of the essence when verifying benefits and communicating patient financial responsibilities. Utilizing technology to verify eligibility automatically decreases the chance of human error, while providing faster results. Some insurance providers only authorize a certain level of care or visit count, depending on the patient’s health condition. Setting up system holds in the EMR will ensure that the company won’t provide unauthorized services that most likely will be uncollectible. A correct patient profile at the start of care sets the groundwork for the most efficient claim submission and collection process. Using online payment systems to collect known balances prior to the start of service significantly decreases the amount of uncollectible dollars at the end of care.

The automation of processes not only saves time, it reduces the chances of errors to allow for a steady stream of revenue and cash collections.

Healthcare revenue cycle can be challenging due to the length of time it may take to submit a claim for services provided. Many insurance providers require a significant amount of documentation to be completed before a claim can be submitted. In these instances, the provider must rely on the physician overseeing the care to complete and sign documentation. Since the remainder of the patient balance is contingent on the final claim submission, the lag in billing makes it difficult to collect a patient balance for a service that was provided long ago. Technology can play a key role in this process.  By selecting a robust EMR that allows an agency to properly setup billing holds, eligible claims can be easily identified and sent out immediately when ready. Partnering with a vendor that assists with electronic document management is also essential in reducing the time it takes to receive these required documents.   Creating this streamlined workflow to receive incoming documentation allows for a quicker review and attach process. From optical character recognition to utilizing a barcoding system, each document can be uniquely identified and attached to the correct patient record with a simple touch of a button. The time savings this creates from both a workload and claim submission perspective is vital.

Typewritten claims, paper billing, and mailing documents are something of the past.  To maintain the optimal level of success, companies now utilize clearinghouses to submit claims electronically. A clearinghouse allows an agency to monitor the life of the claim from submission to payment. Receiving an automatic alert for a problem claim has now replaced the need for manual inquiries on payment status.  This allows an agency to redistribute their resources from claim follow-up to claim submission.  Denial management services are also key to success in an industry of varying payor requirements. These systems allow visibility into denied claims and suggestions on how to properly appeal the denial.  Not only does this automation save time, but it also increases cash flow and collectability. To further complicate the billing process, many payors have different timely filing limits, so it is essential to automate submission reminders based on timely filing. This automation allows the billing team to prioritize time sensitive payors to ensure claims are sent before the deadline has passed. Without technology, it would be impossible to keep track of these different protocols and securing payment for services would be even more challenging.

Reporting and monitoring key performance indicators are an essential part of maintaining the integrity of the entire revenue cycle system. Many EMRS offer automated reporting that can be measured monthly to determine opportunities for improvement.  These reports highlight anything from days to collect A/R, problem payors, and operational deficiencies that lead to collection issues. Investing in an EMR which presents these metrics at a glance allows an agency to proactively fix an issue before it becomes a financial loss. Agencies should continuously review the services offerings of vendor partnerships to ensure they are keeping up with the latest advances to address changes in the fast-paced health industry.

There is no doubt that technology has transformed the world of revenue cycle. Technology is no longer a choice within the health care industry; it’s a requirement. The automation of processes not only saves time, it reduces the chances of errors to allow for a steady stream of revenue and cash collections. Shorten the revenue cycle, decrease costs and increase revenue by transforming your revenue cycle through technology.

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In 2012, Children’s Health^SM faced two significant environmental changes that held the potential to impact provider workflow vis-a-vis additional documentation requirements. And if these changes were not handled well, they could result in a significant negative impact to provider efficiency, clinical communication, and revenue capture. With the possible financial impact being in the millions, we needed to “fuel up” for these changes. What were they?

• Texas was moving to Prospective Payment System (PPS) for Medicaid inpatients Sept. 1, 2013
• Roll out of the International Classification of Diseases Version 10 on Oct. 1, 2015

Being an organization that seeks to leverage the power of technology tools to improve care delivery and outcomes, we thought this challenge represented a perfect opportunity to draw on the collaborative spirit of our team members, to develop processes that would enable us to meet the requirements of PPS and ICD-10, and employ the robust technology tools we have deployed across our organization.

This initiative resulted in Children’s Health in Dallas rolling out a Clinical Documentation Integrity Program that was fueled by a combination of technology, data analytics, and process changes that ultimately helped us increase overall case mix index (without additional employees), improved clinical communication, and streamlined provider documentation.

People and Process:

We assembled a multidisciplinary workgroup comprised of physicians, advance practice nurses, nutrition, coders and clinical documentation integrity specialists. The work effort began with the team defining the problem and conducting an extensive literature review. Our plan was to begin the process with our Gastrointestinal division and then expand the project to all departments. As such, we secured a physician champion from the gastrointestinal division and sought participation from disciplines to serve as subject matter experts. The clinical documentation integrity specialist facilitated the meetings, pulled the information together and wrote/managed the multiple drafts. Then the document was socialized, which enabled us to receive valuable feedback. The socialization process included meeting with providers one-on-one, department meetings, case studies, posters, and lunch-and-learn engagement. This resulted in extensive changes to the document, which was then triangulated against literature review to ensure we were maintaining a solid scientific base. With the vetting process being tied to scientific evidence, we were able to accomplish and sustain the culture change necessary to gain adoption.  The Health Information Management (HIM) team served as the leadership force in the project, with the IT team supporting the “power pack” behind the solution that was embedded in the workflow.

The Power Behind the Program (Technology)

Children’s Health used its electronic medical record (EMR) and clinical decision support tools to support this initiative. The EMR tools used included the clinical documentation integrity application, template redesign, and reporting tools. The clinical decision support tools included computer assisted coding, APR-DRG enhancer, and auto-generated queries. Clinical communication was improved with the increased capture of co-morbid conditions, and provider documentation was streamlined to improve efficiency without the need for additional full-time employees (FTEs) for the effort. Implementation of the EMR allowed us to shift staff that had previously performed other roles into clinical documentation integrity (CDI) positions. There were also additional benefits to case management department.

The technology was finalized in 2013, clinical definitions were published on an internal website dedicated to physicians and circulated to the medical community. For example, in 2013, there were 878 inpatients with the diagnosis of malnutrition and 1,104 in 2014. We believe these statistics are the result of acceptance across the disciplines and recognition of the value of a standard definition for malnutrition in the pediatric population.  The table below illustrates the progression of the process, growing acceptance, and sustainability.

The following matrix demonstrates the Documentation Integrity rollout of People, Processes, Technology, and Tools: 

Communication Plan

Initial discussions took place in which the Chief Health Information Management and Exchange Officer and the Chief Information Officer met with the Division Chiefs, and Chair of Pediatrics to lay out the planned approach of “people, processes, and tools” in this initiative. Once these senior leaders were comfortable with the tools and approach, the communication planning began. A project of this magnitude required a solid communication plan in which we crafted and targeted our communication by discipline, providing routine updates to Division Chiefs, Health Electronic Record / Health Information Management members and Utilization Review Committee members. From there, we asked these team members to cascade this information to their peers. At first, communication was provided monthly until we determined an appropriate cadence to the messages. Now, these updates are delivered quarterly.  We sought to augment our communications with a more “grass roots” approach through numerous lunch-and-learn events within departments. We also conducted (and continue to conduct) face to face meetings with providers as needed. In addition, the team participated in clinical rounding; however, after discussion with medical staff, we determined that this wasn’t the most appropriate vehicle for this communication. Rather, the team found that it was most effective when monthly communication and engagement was reported to the Health Information Management / Health Electronic Record Committee and Utilization Review Committee.

Outcomes

In the first year of the Clinical Documentation Integrity program, prospective payment for Children’s Health showed an increase in reimbursement rather than a decrease—this was an expected result. Case Mix Index continued to increase annually until 2016, when we reached a plateau. Bill drop days declined from 5 days in 2011 to 3.5 days in 2016. Of note, however, is the fact that as of 2017, the bill drop days has increased to 5 days due to other factors. The increase in CMI was FTE-neutral in that no new FTEs were needed as a result of the CDI initiative.

With implementation of computer-assisted coding, data analysis showed that coders captured an average of two additional diagnosis codes per inpatient discharge, which resulted in an increase in case mix index (CMI) of 7% prior to clinical documentation team staffing. These results proved to us that technology is a big contributor to improved documentation, and to this day, CMI continues to grow with clinical documentation team staffing.

As a specialty referral system, many of our providers see a set population of patients with similar documentation requirements. This presented an opportunity for us to standardize templates for these patient populations, due to the general lack of variation in documentation. The design process focused on evaluating workflow and providing drop downs with co-morbid conditions that were usually present in the population. Once we rolled out standardized templates, the CMI increased, documentation was completed in less time, and provider satisfaction improved.

Our analysis showed a prevalence of documenting manifestations of the disease process rather than documenting classifiable conditions. With this understanding, the multidisciplinary team developed standardized clinical definitions, which led to agreement across the medical staff on diagnosing co-morbid conditions, improving efficiency of clinical communication and increasing CMI. The net result is that clinical communication was streamlined and improved by standardization.

Additionally, our analysis showed providers were not consistently capturing co-morbid conditions that were associated with the principal diagnosis. This finding led to Children’s Health and the team to work with providers to redesign their templates, resulting in a more effective means of capturing these diagnoses without adding to the standard workflow.

Case managers have an increased awareness of APR-DRGs, severity of illness and expected length of stay, allowing them to be more actively engaged in assuring complete documentation.

Lessons Learned:

• The value of the CDI team working closely with the medical staff, leveraging focused communication, is immediately evident at month end when there is a drop.
• Monitoring KPIs and reacting/responding quickly assures no slippage.
• Keeping material fresh and relevant is the key.
• Provider response to queries time decreased immediately when providers were given a visual queue that a query was older than 24 hours (measured in June of 2014 and then again June of 2017 following the query redesign). Automated queries on specificity in 2018 also showed the same trend.
• Continued refreshing and packaging of the material within the provider workspace has allowed sustained improvements in our documentation.

Clinical documentation integrity can improve provider workflow, assure accurate population representation, support more complete clinical communication, and provide positive financial impact. Our CDI program has shown the test of time, accurately representing the acuity of our patient population.

Scenario: How more accurate CMI impacts the bottom line

To understand the impact, you need to know that total reimbursement is figured by multiplying an organization’s base rate by the CMI weight (Base Rate x CMI Weight).

Each hospital’s base rate is different, so we’ll use hypothetical numbers to illustrate the impact. Let’s say that your base rate is $10K. Under this scenario (using the CMI example below), in 2012, our organization would have been reimbursed $17.6K per patient ($10K x 1.76), but in 2019, the same patient population would be reimbursed at $26.1K ($10K x 2.61), an increase of nearly $10K. While this is a general illustration, it’s easy to see how even a small incremental change in CMI accuracy can result in significant impact to your organization’s bottom line.

Our goal is for programs to accurately reflect acuity and capture co-morbid conditions. One example is our nutrition program, which expanded based on our ability to capture more frequently the diagnosis of malnutrition. Ultimately, our efforts have helped us better support the unique healthcare needs of our community.

Summary:

• A multidisciplinary clinical documentation integrity program supports success
• Technology underpinning is fundamental
• Restructuring templates can more accurately reflect patient acuity, streamline documentation efficiency, and improve provider satisfaction
• Automated queries in workflow facilitates provider response
• KPIs and data analytics keep you on track

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One of the new trends in health IT is the use of Artificial Intelligence (AI) in Healthcare settings. It has been a black box to many healthcare professionals and front end caregivers as they try to conceptualize it at point of care. Many hospitals, ambulatory clinic and post-acute settings are using decision support systems in some shape or form though some of these techniques don’t really fit in Artificial intelligence definition or methodologies and many people define AI in completely different ways.

• Identify potential of leveraging AI in population health management

Let’s walk through a population health management typical workflow. Population health is the philosophy of having a holistic view about individuals in certain groups that support the transformation from fee for service model to a value-based. It includes interacting with patients during hospitalization or ambulatory visits in addition to monitoring targeted patients at any point pre-admit or post-discharge. It starts with identifying emerging or high risk patients whether they are grouped by specific clinical conditions, co-morbidities or driven by predictive risk models. Then the next step is to outreach targeted patients either actively during their hospital encounters or proactively before events occur with an aim to do proper care coordination to keep patients healthy. The ultimate goal is to reduce unnecessary hospitalizations, improve readmission rates, shortening length of stay and assign a care navigator who will follow up with the patients to do better care coordination to achieve these goals. Additionally part of the workflow is to identify gaps in care, social determinants of health, link patients to the right services whether internally if we have the right type of service/ resources or externally to community based organizations (CBO).

“In a nutshell, the aim is to connect all the dots about our patients across the continuum by making data actionable.”

• Do we need to use AI in population health management?

The question is not whether we need to use AI or not but is really to understand the problem we are trying to solve then evaluate if AI is the right solution. It is like any other technology we try to implement in clinical settings. Clinical workflow comes first and AI needs to support that model otherwise it will always be considered as an extra effort for our clinicians and would face a resistance otherwise. Here are common opportunities to think about in population health management:

Patient Identification, Risk Stratification: We have used many direct approaches and predictive analysis to identify high risk patients mostly from EMR data that includes a combination of length of stay, chronic conditions, previous ED visits, etc. In recent years, many AI vendors started to leverage more advance technologies that consume external data from community to fill social determinants of health, other public data that feeds the machine to give a comprehensive view about targeted patients. The new vision is to uncover emerging risk patients in addition to focusing on high risk patients.

Identifying care plans and Improving interventions: This is an interesting area that requires some automation if prior knowledge exists about the targeted patients and ability to suggest certain interventions by using machine learning approach that gives probability of successful outcome by performing interventions or enhancing efficiencies by doing tasks in a specific order that proved positive outcome previously.

Care Coordination, Patient Engagement: Shifting from silos to a holistic view about the patient. Leveraging wearable devices to better understand physiological changes while the patient is at home and leverage that data to predict high risk events and bring that data to action.

Identifying gaps in care, social determinants of health: There is a huge need to fill that gap. Some data are embedded within progress notes, discharge summaries or other nursing notes that would add a great value to fill that gap. AI has the potential to assist in searching internal notes and look for unstructured data leveraging Natural Language Processing (NLP) or also by linking to community related data that gives more insight on surrounding circumstances then use that to identify certain trends about individuals and communities.

Internal/ external referrals with ability to close the loop: How do we match the patient with the right service? How do we pick from a list of choices based on quality of service, response rate, and financial agreements. How do we close the loop once we refer patients out of network? Many of these questions could be answered by simple algorithms but also in some area by applying AI or a combination of AI and other products.

Patient Engagement, personalized data: This area overlaps with population health as we think out of the box and try to leverage data driven by patients directly including texting platforms, mobile devices or accessibility of data through social media. There is a huge debate about using that information to impact treatment plan (personalized approach).

Operational and technical considerations: Since we are still in an exploratory phase, it is recommended to use an agile implementation methodology and continues evaluation/ validation cycles of machine learning algorithms throughout development cycle and post go live. Also to make AI solution scalable, there is a need for a good representation of data even if that means more investment to make data available, data interoperability and data warehousing.

Most of the time in order to get buy-in from executive leaderships on using AI there is a need to show a proof of concept and potential return of investment especially that many AI solutions are not financially feasible and some organizations have that on their wish list but still have a skepticism on how to mobilize funding on big scale projects.

The last recommendation is to keep it simple. Whether to partner with vendors, optimize EMR AI tools or build internal teams, always think about a feasible solution that fits smoothly in existing workflows and start addressing problems one at a time to make sure AI is the right solution for problems we are trying to solve.

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