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Finding Civility in Payer Relationships: Audits, Reviews and HIM – HIM Scene

Posted on July 19, 2017 I Written By

The following is a HIM Scene guest blog post by Greg Ford, Director, Requester Relations and Receivables Administration at MRO.  This is the first blog in a three-part sponsored blog post series focused on the relationship between HIM departments and third-party payers. Each month, a different MRO expert will share insights on how to reduce payer-provider abrasion, protect information privacy and streamline the medical record release process during health plan or third-party commercial payer audits and reviews.

Civility is defined by Webster’s as courtesy and politeness. It is a mannerly act or expression between two parties. While civility in politics has waned, it appears to be on the rise in healthcare.

New opportunities for civility between payers and providers have emerged with the shift from fee-for-service to value-based reimbursement. Population health, quality payment programs and other alternative payment models (APMs) are opening the door to better collaboration and communications with payers. Optimal patient care is a mutual goal between payers and providers.

HIM professionals can also contribute to stronger payer-provider relationships. Our best opportunity to build civility with health plans and payers is during audits and reviews. HIM professionals who take the time to understand the differences will make notable strides toward a more polite and respectful healthcare experience.

Payer Audits vs. Payer Reviews: What’s the Difference?

It’s no secret to most HIM professionals that the volume of health plan medical record requests continues to increase significantly. In fact, between 2013 and 2016 the number of requests for HEDIS and Risk Adjustment reviews increased from one percent to 11 percent of the total Release of Information requests received by MRO.

The main difference between audits and reviews is the potential negative financial impact to providers. Payer audits include risk for revenue recoupment while payer reviews do not.

For example, audits conducted by third-party payers are intended to recoup funds on overpaid claims. The most common reason for a post-payment payer audit is to confirm correct coding and sequencing as billed on the claim to determine if payment was made to the provider correctly. In audits, the health plan’s intention is to recoup funds on overpaid claims.

Payer reviews do not carry financial risk to the provider. Instead, payer reviews deliver valuable insights providers can use to improve their relationships with health plans and patient populations.

The Upside of Payer Reviews

HEDIS and Risk Adjustment reviews are the most common types of payer reviews. Payer data submissions for HEDIS are due to the National Committee for Quality Assurance (NCQA) by June of every year. Medicare Risk Adjustment results are due in January and Commercial in May.

Since these payer reviews both overlap and occur simultaneously, HIM departments are deluged with medical record requests. Understanding the importance of these reviews improves communication between HIM, Release of Information staff and health plan requesters.

HEDIS Reviews

HEDIS reviews can benefit providers during contract negotiations because the HEDIS performance rankings can be used to gauge the quality and effectiveness of different health plans for potential participation with the facility.

Risk Adjustment Reviews

With these reviews, health plans are required to prove the needs of the population to CMS so they can continue to provide services for higher risk patients and pay providers for the care of this population.

In both cases, medical records are needed to provide the analysis, so HIM is involved.

HIM’s Role: Reimbursable Release of Information

In 2015, 85 percent of MRO’s audit and review requests came from third-party vendors representing health plans. Both post-payment audit and review requests are typically chargeable to the requesting party. Due to the importance of collecting medical record documentation, health plans and payers are willing to pay for records.

HIM professionals are encouraged to pursue reimbursement for payer requests. This is especially true if your HIM department is working diligently to accommodate the payer deadline for record receipt.

A provider’s Release of Information staff should be able to work directly with these requesters to ensure payment for the timely delivery of records. HIM professionals can reduce payer-provider abrasion and ultimately strengthen relationships to improve compliance. It’s the first step to increasing civility in healthcare.

Watch for our August HIM Scene post to learn more about how to secure patient privacy when sending records to payers and health plans.

About Greg Ford
In his role as Director of Requester Relations and Receivables Administration for MRO, Ford serves as a liaison between MRO’s healthcare provider clients and payers requesting large volumes of medical records for purposes of post-payment audits, as well as HEDIS and risk adjustment reviews. He oversees payer audit and review projects end-to-end, from educating and supporting clients on proper billing practices and procedural obligations, to streamlining processes that ensure timely delivery of medical documentation to the requesting payers. Prior to joining MRO, Ford worked as Director of Operations and Sales at ARC Document Solutions for 15 years. He received his B.A. from Delaware Valley University.

If you’d like to receive future HIM posts in your inbox, you can subscribe to future HIM Scene posts here.

EMR Clinical Optimization Infographic – EMR Clinical Optimization Series

Posted on July 12, 2017 I Written By

The following is a guest blog post by Justin Campbell, Vice President, Strategy, at Galen Healthcare Solutions.


(See Full EMR Optimization Infographic)

In this infographic, Galen Healthcare Solutions provides critical information and statistics pertaining to EMR optimization including:

  • EMR Market Maturation
  • EMR Capital Investment Priorities
  • EMR as a Valuable Asset vs Required Repository
  • Clinical Optimization Goals & Benefits
  • Types of Clinical Optimization
  • Clinical Optimization Effort & ROI Matrix

EMR products get widely varying reviews. There is strong support and appreciation for EMRs in some HDOs, where the sentiment exists that the EMR is well-designed, saves time, and supports clinical workflows. That said, in other HDOs, providers using the same EMR complain that EMRs add work, decrease face time with patients and create usability issues and slowdowns. Multiple prompts and clicks in an EMR system impact patients and contribute to physician burnout. The resounding sentiment for these set of providers is that the EMRs are not designed for the way they think and work. Why then the varying response among providers to the same EMR products? Deficient implementations.

Under the pressure of moving ahead to meet the requirements of the Meaningful Use program, most EMRs were implemented using a Big Bang approach, and very rapidly. While this approach may have been the most effective to capture incentives, generic, rapid EMR implementation led to several unintended consequences, resulting in widespread user dissatisfaction. EMRs today serve more as a transactional system of record than a system of engagement. To be used to their full capacity, the different components and modules of the EMR should be evaluated against baseline metrics to harness additional capabilities including clinical decision support, analytics at the point of care, and efficiency of workflow. To realize lasting impact from the EMR, extensive post go-live enhancement and optimization is needed. Leveraging the operational data in the EMR system can support many initiatives to improve workflows, as well as clinical and financial performance. Prioritization of the levers that can be adjusted depends on the HDO’s implementation baseline and strategic goals.


(Click to see larger version of graphic)

A robust EMR optimization strategy can help HDOs realize the promised value from implementation of an EMR. EMR optimization is the driver of strategic value, and can become a sustainable competitive advantage through leadership, innovation and measurement. Success requires a disciplined, data-driven, outcomes-based approach to meet a defined set of objectives.

Gain perspectives from HDO leaders who have successfully navigated EMR clinical optimization and refine your EMR strategy to transform it from a short-term clinical documentation data repository to a long-term asset by downloading our EMR Optimization Whitepaper.

About Justin Campbell
Justin is Vice President, Strategy, at Galen Healthcare Solutions. He is responsible for market intelligence, segmentation, business and market development and competitive strategy. Justin has been consulting in Health IT for over 10 years, guiding clients in the implementation, integration and optimization of clinical systems. He has been on the front lines of system replacement and data migration, and is passionate about advancing interoperability in healthcare and harnessing analytical insights to realize improvements in patient care. Justin can be found on Twitter at @TJustinCampbell and LinkedIn.

About Galen Healthcare Solutions
Galen Healthcare Solutions is an award-winning, #1 in KLAS healthcare IT technical & professional services and solutions company providing high-skilled, cross-platform expertise and proud sponsor of the EMR Clinical Optimization Series. For over a decade, Galen has partnered with more than 300 specialty practices, hospitals, health information exchanges, health systems and integrated delivery networks to provide high-quality, expert level IT consulting services including strategy, optimization, data migration, project management, and interoperability. Galen also delivers a suite of fully integrated products that enhance, automate, and simplify the access and use of clinical patient data within those systems to improve cost-efficiency and quality outcomes. For more information, visit www.galenhealthcare.com. Connect with us on Twitter, Facebook and LinkedIn.

Deriving ROI from Data-driven EMR Clinical Optimization

Posted on June 28, 2017 I Written By

The following is a guest blog post by Justin Campbell Vice President, Strategy, at Galen Healthcare Solutions.  Learn more about their work by downloading their EHR Clinical Optimization Whitepaper.

Resistance to change is natural. People are uncomfortable with it. Organizations are frightened by it. Acceptance of healthcare information technology took a long time and even in these first two decades of a new century, despite incentives such as the Meaningful Use program, and promises of increased efficiency, implementation of Electronic Medical Records has been a bumpy ride.

Between 2008 and 2016, healthcare organizations spent more than 20 billion dollars adopting electronic health record systems. Many different approaches were applied. Many HCOs decided to act quickly, using what we now call a “Big Bang” fix. Installations of generic systems were in place but users of the new systems were unhappy. In 2013, with the process well underway throughout the nation, two thirds of doctors polled said they used EMR systems unwillingly, with 87% of these aggravated physicians complaining about usability and 92% of physician practices complaining that their EMRs were “clunky” and/or too difficult. Specifically, only 35% reported that it had become easier to respond to patient issues, one third said they could not more effectively manage patient treatment plans, and despite the belief that technology would permit caregivers to spend more time with their patients, only 10% said this was occurring.

The medical side was not alone in expressing dissatisfaction. Hospital executive and IT employees who had replaced their Electronic Health Record systems reported higher than expected costs, layoffs, declining revenues, disenfranchised clinicians and serious misgivings about the benefits gained:

  • 14% of all hospitals that replaced their original EMR since 2011 were losing inpatient revenue at a pace that would not support the total cost of their replacement EMR
  • 87% of hospitals facing financial challenges now regret the decision to change systems
  • 63% of executive-level respondents admitted they feared losing their jobs as a result of the EMR replacement process
  • 66% of the system users believe that interoperability and patient data exchange functionality have declined.


Not all reviews are negative. There is strong support and appreciation for EMRs in some Healthcare Delivery Organizations (HDOs) who believe well-designed EMRs save time and support clinical workflows. But, there is no escaping the majority sentiment: EMRs are not designed for the way providers think and work.

Today, most HDOs are at a crossroads. They can start over with a new EMR or optimize the one they have. The case for a do-over is supported by sub-standard vendor support for their existing systems and the increase in mergers and acquisitions, which drive system consolidation. One fifth of large practices and clinics report they intend to replace their EMRs and studies show that the EMR replacement markets will likely grow at an annual rate of 7%-8% over the next five years. The case for the status quo is made primarily by the HCOs that do not have the financial resources to undertake EMR replacement.

All options face the same key inter-related questions: how to generate additional margin? How to maximize return on technology investments? Which path will best serve the HCO, caregivers and patients?

This is a bit of vicious circle. HCOs are cash-strapped and the transition from fee for service to value-based care exerts downward cost pressures, exacerbating the problem. But patchwork fixes have not resolved that problem. Alternatively, some attempted to do too much too quickly and became frustrated because they lacked the depth of experience and knowledge to perform remediation. And, as KPMG concluded after studying the problem, “The length of time to resolve the issues increased and frustrations mounted as clinical, senior management, IT and human resources staff found themselves spinning their wheels.”

Like a patient being pressured to swallow medicine, HDOs are beginning to accept their situation. According to a recent survey conducted by KPMG in collaboration with CHIME, 38% of 112 respondents ranked EMR/EMR optimization as their top choice for the majority of their capital investments for the next three years.

EMR adoption is already approaching maximum levels. Consequently, healthcare delivery organizations have begun to shift their EMR strategies from short-term clinical documentation data repositories to long-term assets with substantial functionality in support of clinical decisions, health maintenance planning and quality reporting. They are coming to see their IT investments as platforms rather than limited systems of record or glorified data banks. In short, they now understand that the capture of information is only the most basic attribute of an EMR, and that instead, the EMR in which they invest can be flexible and extensible, capable of adopting emerging technologies that are driving insights to the point of care.

Assess opportunity, formulate strategy, improve usability & derive additional ROI & by downloading our EHR Clinical Optimization Whitepaper.

About Justin Campbell
Justin is Vice President, Strategy, at Galen Healthcare Solutions. He is responsible for market intelligence, segmentation, business and market development and competitive strategy. Justin has been consulting in Health IT for over 10 years, guiding clients in the implementation, integration and optimization of clinical systems. He has been on the front lines of system replacement and data migration and is passionate about advancing interoperability in healthcare and harnessing analytical insights to realize improvements in patient care. Justin can be found on Twitter at @TJustinCampbell and LinkedIn.

About Galen Healthcare Solutions

Galen Healthcare Solutions is an award-winning, #1 in KLAS healthcare IT technical & professional services and solutions company providing high-skilled, cross-platform expertise and proud sponsor of the Tackling EHR & EMR Transition Series. For over a decade, Galen has partnered with more than 300 specialty practices, hospitals, health information exchanges, health systems and integrated delivery networks to provide high-quality, expert level IT consulting services including strategy, optimization, data migration, project management, and interoperability. Galen also delivers a suite of fully integrated products that enhance, automate, and simplify the access and use of clinical patient data within those systems to improve cost-efficiency and quality outcomes. For more information, visit www.galenhealthcare.com. Connect with us on Twitter, Facebook and LinkedIn.

Promoting Internal Innovation to Drive Healthcare Efficiency

Posted on June 1, 2017 I Written By

The following is a guest blog post by Peyman S. Zand, Partner, Pivot Point Consulting, a Vaco Company.

Technical innovation in healthcare has historically been viewed through the lens of disruption. As tech adoption in the industry matures, perceptions on the origin of innovation are evolving as well. Healthcare leadership teams are increasingly leaning on feedback from the front lines of care delivery to identify ways to eliminate waste and drive greater efficiency. Rather than leaving innovation up to third parties, many health organizations are formalizing programs to advance innovation within their own facilities.

There are two schools of thought on healthcare innovation. Some argue that the market’s unique challenges can only be understood by those in the field, leaving outside influencers destined to fail. Others view innovation success in outside markets as an opportunity for healthcare stakeholders to learn from the wins and losses of more technically progressive industries. By mimicking other industries’ approach to promoting innovation (as opposed to their byproducts) in our hospitals and health systems, healthcare can draw from the best of both worlds. What we know is that the process in which innovation is adopted is very similar in all industries. However, the types of innovations and specific models can and should be tailored to the healthcare industry.

Innovation in Healthcare: Three Examples at a  Glance

There are several examples of health organizations successfully forging a path to institutionalized innovation. University of Pittsburg Medical Center (UPMC), Intermountain Healthcare and Mayo Clinic have pioneered innovation programs that merge internal clinical expertise with technical innovators from vertical markets in and outside healthcare. This article highlights some of the ways these progressive organizations have achieved success.

Innovation at UPMC

UPMC Enterprises boasts a 200-person staff managed by top provider and payer executives at UPMC. The innovation team is presently engaged in more than a dozen commercial partnerships, including support for Vivify Health’s chronic care telehealth solutions, medCPU’s real-time decision support solutions and Health Catalyst’s data warehousing and analytics solutions. Each project is focused on the goal of improving patient outcomes. The innovation group was recently rumored to be partnering with Microsoft on machine learning initiatives and the results may have a profound impact on how we use technology in care delivery.

UPMC Enterprises supports entrepreneurs—both internal individuals and established companies—with capital, technical resources, partner networks, recruiting and marketing assistance to support innovation. Dedicated focus in the following areas lends structure to the innovation program:

  • Translational science
  • Improving outcomes
  • Infrastructure and efficiency
  • Consumer engagement

All profits generated from investments are reinvested to support further research and innovation.

Innovation at Intermountain Healthcare

Like UPMC, Intermountain’s Healthcare Transformation Lab supports innovation in the areas of telehealth and natural language processing (NLP), among others. Like most providers, one of Intermountain’s primary goals is controlling costs. The group’s self-developed NLP program is designed to help identify high-risk patients ahead of catastrophic events using data stored in free-text documents. Telehealth innovations let patients self-triage to the right level of care to incentivize use of the least expensive form of care available. Intermountain’s ProComp solution offers its providers on-the-spot transparency about the cost of instruments, drugs and devices they use. That innovation alone net the health system roughly $80 million in reduced costs between 2013 and 2015.

Most of Intermountain’s innovation initiatives are physician led or co-led. The program strives for small innovations in day-to-day work, supported by a suite of innovation support services and resource centers. Selected innovations from outside startups are supported by the company’s Healthbox Accelerator program involvement, while internal innovations are managed by the Intermountain Foundry. Intermountain offers online innovation idea submissions to promote easy participation. The health organization’s $35 million Innovation Fund supports innovations through formalized investment criteria and trustee governance resources. It is important to note that Intermountain Healthcare is interested in all aspects of innovation including supply chain and other non-clinical related projects.

Innovation at Mayo Clinic

Mayo Clinic’s Center for Innovation (CFI) brings in innovation best practices from both healthcare and non-healthcare backgrounds to drive new ideas. The innovation team’s external advisory council is comprised of both designers and physicians to drive innovation and efficiency in care delivery. The CFI features a Multidisciplinary Design Clinic that invites patients into the innovation process as well.

CFI staff found it was essential to show physicians data that demonstrated known problems and how proposed innovations could make a difference to their patients. They emphasize temporary changes, or “rapid prototyping,” to garner physician buy-in. Mayo’s CFI promotes employee involvement in innovative design through its Culture & Competency of Innovation platform, which features weekly meetings, institution-wide classes, lunch discussion groups and an annual symposium. Mayo’s innovation efforts include these additional physician-led platforms:

  • Mayo Clinic Connection—supporting shared physician experience
  • Prediction and Prevention
  • Wellness—promoting patient education
  • Destination Mayo Clinic—focused on improving patient experience

While these innovation examples represent large healthcare organizations, fostering innovation does not require a big budget. Mayo Clinic’s “think big, start small, move fast” approach to innovation illustrates a common thread among successful innovation programs. Here are practical strategies to advance innovation in healthcare, regardless of organizational size or budget.

Four Steps to Implementing an Innovation Program in Your Organization

Innovation doesn’t have to be grandiose or expensive. Organizations can start small. Begin by opening a companywide dialogue on innovation and launching a simple, online idea submission process to engage personnel in your organization. The most important part of this process is educating your teams to understand how to evaluate new innovations against a relatively pre-defined set of criteria.  For example, are you trying to improve patient safety, quality of care, reduce cost, increase patient or physician satisfaction, etc.

Another key element of successful innovation is encouraging collaboration and participation across a wide variety of stakeholders. Cross-functional teams bring multifaceted perspectives to the problem-solving process. Strive for incremental gains in facilitating opportunities for cross-department collaboration in your organization. This is particularly important for the implementation step.

Measure success using performance metrics where clinical efficiencies are concerned. Physician satisfaction, while difficult to quantify, can also pose big wins. You can expect some failures, but stack the odds by learning from other departments, organizations and industries to avoid making the same mistakes.

To work, innovation must happen often and organically. Dedicate funding, establish cross-department teams and build a formal process for vetting internal ideas. Consider offering staff incentives to drive engagement. Not all ideas will succeed. Identify metrics that will help determine ROI (not all ROIs are measured in dollars) on pilot programs so you can weed out initiatives that aren’t delivering early on to protect resources. Also, keep in mind that you can improve these innovations at each iteration.  Make the process iterative and roll out the initiatives quickly. If it fails, shut the process down quickly and move on. If it is successful, improve it for the next iteration and scale it quickly to maximize the benefits.

Whether you’re cross-pollinating internal teams to promote innovation, building partnerships with other organizations or leveraging technology to better connect providers and patients, healthcare’s ability to successfully collaborate is vital to advancing innovation in healthcare.

About Peyman S. Zand
Peyman S. Zand is a Partner at Pivot Point Consulting, a Vaco company, where he is responsible for strategic services solving healthcare clients’ complex challenges. Currently serving as interim regional CIO for Tenet Healthcare, Zand was previously a member of the University of North Carolina Healthcare System, leading Strategy, Governance, and Program/Project Management. He oversaw major initiatives including system-wide EHR implementation, regulatory programs, and physician practice rollouts. Prior to UNC, Zand formed the Applied Vision Group, a firm dedicated to assisting healthcare organizations with strategic planning, governance, and program and project management for key initiatives.

Zand holds a Bachelor’s of Science in Computational Mathematics and Engineering from Michigan State University, and a Master of Business Administration from the University of Michigan.

Real-Time Health Systems (RTHS) and Experiential Wayfinding

Posted on May 19, 2017 I Written By

The following is a guest blog post by Jody Shaffer from Jibestream.

You have probably heard about Real-Time Health Systems (RTHS). This is a game-changing trend among healthcare providers where the delivery of healthcare is transforming to a more aware and patient-centric system. Providers are leveraging technology to get pertinent information to decision makers as quickly as possible empowering them to make more informed decisions in real-time. Facilities that are amenable to change will remain strong in competitive markets, while those who are reluctant to adapt will fall behind.

As we entered this new era in healthcare, providers are faced with a series of challenges. Smart medical devices are transforming the healthcare dynamic as medical data and information is produced and multiplying at an exponential rate, yet it’s use has not been keeping pace. This data overload has created a significant obstacle for healthcare providers to overcome. There is also intense pressure to create a consumer and patient experience that is dynamic, accessible and engaging.

So the question is, how can healthcare providers quickly process and interpret copious amounts of data into a digestible format for immediate patient consumption while internalizing and translating the same data into operational intelligence?

The answer lies in evolving to a paradigm that is situationally aware and patient-centric in both operations and management. Not only is this pivotal in successfully achieving a RTHS, it ensures that healthcare providers connect, communicate and collaborate more effectively than they have in the past.

When looking to achieve a Real-Time Healthcare System, there are four primary phases that need to be addressed:

Phase 1 – Collecting data

Phase 2 – Processing data

Phase 3 – Translating data into intelligence

Phase 4 – Utilizing/sharing data

The final two phases are essential for healthcare providers to excel in this changing market dynamic and meet increasing patient expectations.

To yield valuable intelligence, data needs to be presented with situational context. Raw data is in itself useful for analytics, but can only be leveraged to create spatial awareness when augmented with location-based data.

Consumers have grown accustomed to the convenience of real-time access to information from mobile devices and apps, and healthcare is no exception. Through a combination of location-aware technologies, hospitals can eliminate some of patient’s biggest frustrations fostering a more positive patient experience across the continuum of care.

Mobile apps, digital maps and interactive kiosks leverage connected technologies to help create a more familiar and engaging environment promoting an effortless and seamless patient experience.

Experiential wayfinding, made available through these technologies, form the foundation for enhancing patient experience, which is paramount to the success of a healthcare organization. Experiential wayfinding reduces the complexity of indoor spaces by anticipating where people are going and what they are looking for. It can be used to direct visitors to a facility and identify parking availability nearest their desired location. Once there, it can be used to guide visitors to destination(s) within a facility using turn-by turn directions making it easy and less stressful to get where they need to go.

An integrated platform can also enable proactive interactions engaging patients before, during, and after hospital visits. The use of mobile messaging to deliver contextual content based on a patient’s location and profile help create a more pleasant and efficient patient experience. Prior to a visitor’s departure to a hospital, the facility’s mobile apps can share information such as appointment delays or traffic delays to take into account on the way there. Mobile messaging also enables facilities to communicate with visitors by sending appointment reminders, context-aware messages, preparation guidelines, post-care instructions, and more. Another application of this can save patients the frustration of intolerable wait-times when a hospital is stretched beyond capacity by sending notifications to offer a change of appointment or alternate appointment location.

Location awareness and spatial context benefit both patients and healthcare providers alike. For clinicians and healthcare teams, this translates to accelerated productivity facilitated through visibility, the streamlining of processes resulting in the elimination of inefficiencies, minimizing staff interruptions, and a balance between resources and demand.

When managed properly, a RTHS enables healthcare providers to improve patient satisfaction and outcomes by leveraging the vast amount of data made available through connected computers, technologies and medical equipment across hospitals, clinics, and patient homes.

By merging the location dimension into healthcare systems, providers are able to bring order to complex data. Through geoenrichment and data visualization, providers can improve patient experiences and outcomes, uncover previously unseen data patterns, realize workflow efficiencies through connected technologies and enrich business insights leading to better more actionable decisions.

Behind the Scenes: Preparing for a RTHS Transition

  • Digitization of Space (converting CAD/DWG map files to SVG)
    Before data can be presented in the context of a map, healthcare providers need to digitize their space. This provides a scalable platform for plotting data to support multiple use cases.
  • Connect core systems and data
    Leveraging technology that offers interoperability allows for seamless integration of core systems and data
  • Connect assets and people
    Create situational awareness by connecting to assets and people
  • Connect maps to data with Indoor Positioning Systems (IPS)
    Look for a solution that offer a technology agnostic architecture to calibrate maps Indoor Positioning
  • Implementation
    Make all this available by extending solution to patient and nonpatient hospital workflows

About Jody Shaffer
Jody Shaffer is an experienced marketer with more than 13 years in the software industry. Jody currently leads the marketing department at Jibestream, an award-winning company specializing in indoor mapping and location intelligence solutions. The company’s platform provides developers with the tools to build custom map-enabled applications unlocking the full potential of the Internet of Things (IoT). Jibestream’s platform can be found implemented in hospitals and health care facilities across north America.

Healthcare Analytics are the Problem. Applied AI is the Solution.

Posted on May 17, 2017 I Written By

The following is a guest blog post by Gurjeet Singh, Executive Chairman and Co-founder of Ayasdi.

The combination of electronic medical records, financial data, clinical data, and advanced analytics promised to revolutionize healthcare.

It hasn’t happened.

The common excuse is that healthcare wasn’t really prepared for the enormity and complexity of the data challenge and that, over time, with the next EMR implementation, that healthcare will be positioned to reap the benefits. Unfortunately, the next generation of EMR, or the one after that, isn’t going to solve the problem.

They problem is on the analytics side.

Healthcare analytics are still driven by a question-first approach. The start of our analytics journey still begins with the question.  The challenge is which question? The more data we have at our disposal, the more potential questions there are and the lower the likelihood that we will ask the one that generates new value for the patient, the provider, or the payer. Even when we are successful in asking the right question, we have engaged in a confirmatory process – we have confirmed something we already knew.

Some will suggest that predictive analytics solves the problem, but it too is hypothesis driven – just in a different way. With predictive analytics, the set of variables selected, the choice of algorithms are, in effect, guesses as to what will produce the best outcome.

Ultimately, both approaches are flawed.

We need a new approach that surfaces trends we humans haven’t even considered, and that delivers a host of meaningful insights to clinicians before they even ask any questions. We need technology solutions that combine the best qualities of human intelligence (artificial intelligence) with the best computing capabilities that exceed human ability (machine learning).  When these technologies are operationalized systematically across an enterprise, it’s called Applied AI.  Applied AI is here to replace healthcare analytics, and we all stand to benefit.

Five Keys to Applied AI

Applied AI has already begun driving care improvement, cost-reduction, and improved clinical and financial decision-making across the healthcare enterprise – and the entire healthcare continuum. Applied AI is not a concept, but a series of intelligent applications that target discrete healthcare problems from clinical variation to population health. These intelligent applications have a collection of capabilities that make them intelligent – of which all need to be present. Let’s look at those capabilities:

DiscoveryIntelligent applications need to support both unsupervised and semi-supervised discovery. These capabilities are quite rare but serve as the foundation for our efforts to move past hypothesis driven inquiry. In practical terms, this means that an intelligent application considers all the data and all the possibilities within that data to detect the patterns, groups or anomalies that elude traditional approaches. Using their own systems of records, including EMRs, financial data, patient-generated data, and socio-economic data, healthcare organizations can automatically discover groups of patients that share unique combinations of characteristics. These groups can then be used to tailor and personalize diagnostics and care paths, for example. Alternatively, healthcare organizations may also discover unique patterns or outliers within their claims data to aid in member retention or preventing fraud or waste. This type of holistic discovery is unique to AI and improves prediction and makes operational insights possible.

Predictions Intelligent applications must also be able to predict the future with high accuracy. Holistic discovery enables even better predictive models through the unbiased creation of groups or the identification of patterns. Superior prediction gives healthcare organizations foresight into the future needs, costs, disease burden, and risks of patients. For example, intelligent applications can determine the groups of patients projected to have the highest escalation of costs over time, as well as other outcomes such as the conditions likely to appear for each group, and an individual’s predicted change in utilization. Predictions can be made across multiple targets and are multi-faceted, considering all factors whether they’re health- or non-healthcare-related occurring outside of the healthcare system.

JustificationAn intelligent solution must justify its predictions, discoveries, and actions in a transparent way so human operators feel confident to act upon its recommendations. For example, a healthcare app may reveal differentiating characteristics of patient risk trajectories, what factors make them high or low-risk, and descriptions of individual factors that lead to variation in cost and quality. Justification is key because without a thorough understanding of the “why” behind predictions, organizations are unable to adopt AI into day-to-day decision-making.

Action An intelligent system that is not effectively operationalized will become less intelligent over time. Actionable information that guides and augments human decision-making is what makes AI a part of daily operations. For these systems to deliver optimal value they need humans in the loop providing feedback and governance. Whether it be a recommended care path or a detailed risk profile, intelligent applications allow organizations to collaborate on the best actions tailored for each patient population, or to physicians or organizations. Across the care continuum, within health systems and health plans, this allows them to better assess individuals and the best course of care, and more confidently prescribe care and programs for each individual.

LearningIntelligent applications “learn” to improve predictions over time. As more and more data is analyzed, the technology learns from these complex data points to improve predictions over time. Whether it be claims, medical records, or socio-economic data, AI taps into these data points to generate more accurate, personalized predictions that continuously improve. Further, intelligent apps learn the impact of actions over time to support and continuously improve decision making.

Applied AI in action

A large hospital system decided it wanted to reduce clinical variation across its enterprise to improve outcomes for all patients. It implemented machine intelligence, including unsupervised machine learning techniques that run algorithms using the system’s own data—not benchmarks—to uncover actionable insights. The technology correlates and analyzes electronic medical record and financial data including treatments prescribed, procedures performed, drugs administered, length of stay, and costs per patient. The goal was to discover and refine clinical pathways that are optimized to drive higher quality of care and lower costs.

The machine intelligence solution identified a group of orthopedic surgeons who consistently had better outcomes among their knee replacement patients. These patients had shorter hospital stays and shorter time to ambulation than other total knee surgery replacements across the system. The solution also told clinicians why:  these doctors prescribed a unique, not widely used medication at an earlier postsurgical time than their peers. The medication reduced patients’ pain so they could get out of bed and walk around sooner – improving their outcomes and reducing costs.

Clinicians hadn’t previously known to look for variation based on what medication was given post-operatively. But machine intelligence identified a pod of doctors with better outcomes that were statistically significant. By comparing very large numbers of data points, the solution quickly uncovered why.  Now the hospital system has operationalized these best practices throughout their hospitals, lowering costs for knee replacement by more than 5 percent, and reducing pain for patients.

The last piece of the puzzle – AI applications

As healthcare organizations increasingly see the value of Applied AI, they may worry that more robust technology means greatly increased technical headcount to manage this strategy. But an important component of a successful Applied AI strategy is that it leverages the unique capabilities of both machines and humans. Hiring a dozen data scientists won’t make the most of the human intelligence within your organization. That’s because these new data scientists likely would not have the subject matter expertise needed to recognize and deploy the meaningful insights that surface. Meanwhile, the people who are the best suited to learn from the data, domain experts, usually do not have an interface to read data themselves. Subject matter experts typically only interact with data using rudimentary applications like PowerPoint or Excel.

So, the last key to a successful Applied AI strategy is to wrap the results of machine learning and artificial intelligence into business-facing applications. These applications can be customized for the types of insights they uncover, such as the optimal way to perform surgical procedures. It’s critical that the results of machine learning and machine intelligence actually make it to clinicians, instead of ending up siloed somewhere in the IT department. The successor technology to healthcare analytics must not only be more powerful and more precise, it must also be more user-friendly.

What’s Next

Healthcare analytics simply aren’t living up to their promise. We can wring our hands, we can wait, we can soldier on with insights that only marginally move the needle to improve outcomes and lower costs. Or we can combine artificial intelligence with powerful machine learning to turn enormous datasets into business insights that really matter. Then we can deliver those insights, via easy-to-use business applications, to the best clinician minds, to operationalize this machine intelligence approach across the enterprise. That’s Applied AI, and it’s a bright future.

About Gurjeet Singh
Gurjeet Singh is Ayasdi’s Executive Chairman and co-founder. As the Executive Chairman, he leads a technology movement that emphasizes the importance of extracting insight from data, not just storing and organizing it.

Gurjeet developed key mathematical and machine learning algorithms for Topological Data Analysis (TDA) and their applications during his tenure as graduate student in Stanford’s Mathematics Department where he was advised by Ayasdi co-founder Prof. Gunnar Carlsson.

Gurjeet is the author of numerous patents and has published in a variety of top mathematics and computer science journals. Before starting Ayasdi, he worked at Google and Texas Instruments. Gurjeet was named by Silicon Valley Business Journal as one of their 40 Under 40 in 2015.

Gurjeet holds a B.Tech. from Delhi University, and a Ph.D. in Computational Mathematics from Stanford University. He lives in Palo Alto with his wife and two children, and develops multi-legged robots in his spare time.

An Effective Strategy for Long-term Epic Training

Posted on January 27, 2017 I Written By

The following is a guest blog post by Chris Cooley, Training Advisor at Pivot Point Consulting, a Vaco Company.

Ensuring that you have enough staff to cover day-to-day, new-hire, remedial, and monthly EHR update training is not an easy task. At the most recent Epic User Group Meetings and Spring Councils, sessions dedicated to building steady training teams were among the best attended. To be sure, Epic training is a hot topic in healthcare organizations—particularly as it relates to new hires. Here are some best-practice suggestions to help establish a long-term and successful Epic training program.

The Necessary Evils

eLearning
Many organizations are opting for eLearning in lieu of classroom training to reach multiple groups. The difficulty with this approach is the inability to truly know if the participant grasped the material. Most participants can pass a quick post-exam without completely understanding or retaining the information.

Timing is also an issue. Even a two-day lapse between an eLearning session and practicing the learned material can pose the risk of an 80 percent information loss, requiring retraining or additional support during the first shift following training. That said, when used correctly, eLearning can be quite effective when used in conjunction with traditional classroom training and immediate practice.

For those familiar with Epic, an interactive eLearning session that speaks to the specifics of your organization can easily be implemented in lieu of classroom training. When using eLearning, make sure to follow adult learning principles. Keep courses short, interactive, and challenging to keep end users engaged. To help participants retain information, include built-in exercises to prevent advancing without completing an action.

Classroom Training
In a preceptor-led training model, about four to eight hours of classroom training should be sufficient. Stick to the basics of navigation, terminology, and one or two main workflows to get comfortable working in the system.

For physicians, schedule a one-on-one follow-up with the trainer to set up preference lists and customizations within the same week. Avoid doing this day one or two, as the physician will need to be familiar with the existing orders and sets before customizing further.

Beyond the Classroom

Routine Training Integration
Standard training and orientation programs offer great opportunities to incorporate Epic-specific training elements where applicable. Nurses, for example, have a day or more of skill validation when starting a new position. For every skill they perform, an Epic training opportunity exists. Have participants find the order in Epic, perform the skill, then document the appropriate procedure and follow up. Collaborate with the education department and affected department leaders to add Epic workflows into routine training outlets.

Preceptorship
Learning happens best when on the floor, in the department, or repeatedly completing a task. Assign new hires a preceptor who is well versed in Epic and department workflows. Have them log in and perform the work while the preceptor guides them through their duties. After two to three days of side-by-side work, your new employee should be off and running.

Draw preceptors from within the new employee’s department and remove them from their daily duties when onboarding new hires. Choose your preceptors wisely. Just because Jane Doe is the resident Epic expert on your floor doesn’t mean she’ll be the best preceptor. Look for someone who embodies your organization’s culture, is a cheerleader for Epic, and has the patience to answer the same question multiple times.

Other Considerations

Materials
Materials must be well written, well organized, and—most important—accessible. Often, materials are outdated, in print form only, or not easily found by the end user. The use and regular maintenance of Learning Home Dashboards can ensure the latest materials are organized, intuitive, and available.

Consider turning tip sheets into two-minute-or-less video snippets. More often than not, watching and then repeating a process is preferable to deciphering a tip sheet and/or screen shots—especially for physicians and millennials looking for the quickest answer.

Remedial Training
While new hires account for about 30-50 percent of a trainer’s time, some individuals or departments will always need a little extra help. For example, evaluating a workflow to offer a faster/easier process, retraining, or providing additional one-on-one time with the end user can account for another 20 percent of a trainer’s time.

Update Training
Each month, a new set of Epic updates must be showcased to employees. This can be accomplished via monthly training or eLearning. In my experience, the time to coordinate and deliver monthly update training accounts for about 10 percent of the trainer’s time.

Rounding
End users often struggle in silence. When my trainers are not actively training, or working on materials, they are rounding in the departments they support looking for opportunities to strengthen knowledge. In addition to rounding, trainers attend huddles and meetings, offer help, and bring vital intel about updated or ill-working workflows to the principal trainer’s attention.

Help Desk
Trainers will also spend a good deal of time working “tickets” to assist end users (and often analysts) in identifying and communicating problems and resolutions.

Learning Management System (LMS) Administration
Hundreds of small details go into ensuring that Epic training is meeting the needs of an organization.  Who is expected in training? When and where can training be held? Who has completed training and can be activated in the system? It is imperative to dedicate at least one full time LMS administrator or coordinator to these ongoing Epic needs. Depending on the organization’s size, this may require up to four full-time resources.

Effective Coverage 
The number of Epic trainers needed will vary according to the organization’s size and hiring volume. Depending on the application and the hiring schedule, your principal trainer may be able to handle all training without the support of additional resources. However, I recommend having at least one credentialed trainer available for backup—to cover vacations, assist in remedial training, etc. Consider cross-training to make trainers versatile in related apps. Maintain expertise amongst your trainers by limiting cross-training to three areas of focus.

The example below includes enough trainers to cover the needs of a two hospital system and surrounding clinics in the same geographical location.

CT1: SBO, HB/PB
CT2 ClinDoc, Stork, Orders
CT3 ClinDoc, Beaker, Orders
CT4 Ambulatory, HOD, Cadence
CT5 Ambulatory, HOD, Cadence
CT6 Radiant, Cupid
CT7 Beacon, Willow
CT8 ASAP, OpTime, ANA
CT9 HIM, GC
CT10 HIM, GC

 

PT1 GC, Cadence
PT2 Ambulatory, HOD
PT3 ClinDoc, Stork
PT4 Orders, ASAP, Beaker
PT5 OpTime, ANA
PT6 Radiant, Cupid
PT7 Beacon, Willow
PT8 HIM, HB, PB, SBO

 
Creating partnerships throughout your organization, along with a steady, recurring training schedule, is the key to running an efficient, low-budget training team. With exceptional, easily accessible training materials and operational preceptors, training can be efficient, low-cost, and have employees in their positions with minimal classroom time.

About Chris Cooley
Chris Cooley is a Subject Matter Expert for the LIVESite division of Pivot Point Consulting, a Vaco Company. Previously, she worked as a full-time training manager, with 14 EMR implementations under her belt. With a combined knowledge of adult learning principles, technical writing, project management and the healthcare world, Chris is known for her creative solutions.

EMR Replacement & Migration Perspective: Tim Schoener, VP/CIO, UPMC Susquehanna

Posted on December 8, 2016 I Written By

header-chime
In the midst of a merger with a major Pennsylvania healthcare organization, Tim Schoener is wholly focused on EHR transition. He outlines Susquennaha’s plan for each aspect of transition, offering innovative and unique approaches to each. In addition, Schoener provides cogent insights regarding the intricacies involved with a multi-database system, the expenses associated with archival solutions, and the challenges associated with migrating records. This interview touches on many of the considerations necessary for a successful EHR transition as Schoener discusses minimizing surprises during a transition; why migrating a year’s worth of results is optimal; and how their document management system fulfills archival needs.

CHIME Fall CIO Forum provides valuable education programming, tailored specifically to meet the needs of CIOs and other healthcare IT executives. Justin Campbell, of Galen Healthcare Solutions, had the opportunity to attend this year’s forum and interview CIOs from all over the country. Looking for additional EMR replacement perspectives & lessons learned? View a recent panel where HCO leaders discussed their experiences with EHR transition, data migration & archival.

KEY INSIGHTS

Absolutely, we have problem lists that can’t be reconciled; there’s a problem list in the Soarian world and a problem list in the NextGen world, and they’re not the same thing right now, not at all.

We’re being told, if you think you’re going to migrate and move all this data to some sort of other archiving solution, get ready for a sticker shock.

Our intent is to take it to each physician specialty to establish a good comfort level, so when the transition occurs, I don’t have physicians’ saying to me ‘no one ever asked me…’ or not be able to provide excellent patient care. It’s going to be critical to the success of our EMR transition to keep our physicians engaged and involved.

Let’s face it, no staff member has the desire to support the legacy application when all of their coworkers are learning the new application. That’s a career limiting move.

It used to be something that struggling organizations were forced to pursue, but now very successful organizations are starting to affiliate and merge with other organizations because it’s just the state of healthcare.

CHIME is a great way to challenge yourself as a CIO and in your leadership. It pushes me in my leadership skills and helps to focus me back to what’s critical in the industry.
tim-schoener
Campbell: Tell me a little about yourself and your organization’s initiatives

Schoener: I’m Tim Schoener, the VP/CIO of, originally Susquehanna Health, which, as of October 1st, is now a part of the University of Pittsburgh Medical Center (UPMC) and re-named to UPMC Susquehanna. We’re located in central Pennsylvania, four hours away from Pittsburgh.

A major IT initiative for us is that we’re swapping out our EMR over the next couple of years. We are currently a Cerner Soarian customer. In fact, we were the initial Soarian beta site for Financials and second for Clinicals. We determined we eventually need to migrate to something else – that’s an Epic or Cerner decision for us at this point. UPMC’s enterprise model is Cerner and Epic, Cerner on the acute care side and Epic on the ambulatory side. As of this writing, we’ve made the decision to migrate to the UPMC blended model. Over the past nine months we’ve been focused on an EMR governance process, trying to get our team aligned on the journey that we’re about to take and by late next year we will likely be starting an implementation.

We currently leverage NextGen on the Ambulatory side, with approximately 300 providers that use that software product. We’re a four hospital system: two of which are critical access, one which is predominately outpatient, and the other a predominately inpatient facility. We were about a $600MM organization prior to our UPMC acquisition.

Campbell: Related to your current implementation, tell me a little bit about your data governance strategy and dictionary mapping that may occur between NextGen and Soarian.

Schoener: We definitely have a lot of interfaces, a lot of integration between the two core systems. From an integration perspective, we have context sharing, so physicians can contextually launch and interoperate from NextGen to Soarian, and vice-versa. We do pass some data back and forth—allergies and meds can be shared through a reconciliation process—but we certainly aren’t integrated. It’s the state of healthcare.

Campbell: That’s why you anticipate moving to a single platform, single database?

Schoener: Absolutely, we have problem lists that are not reconciled. There’s a problem list in the Soarian world and a problem list in the NextGen world, and they’re not the same thing right now, not at all. Meds and allergies are pretty much all we get in terms of outpatient to inpatient clinical data sharing today.

Campbell: Do you leverage an archival solution for any legacy data?

Schoener: We use EMC and have large data storage with them. I wouldn’t call it archival, but we have an electronic document management system – Soarian’s eHIM.

There’s a huge amount of data out there and I know you have some questions related to our thinking with respect to migration. I have some thoughts around that related to levering our document management system versus archiving into a separate system. I’m pretty certain we would be thinking ‘why not use eHIM as our archival process, and just put other data in that repository as necessary?’ For results data, for instance, what we’re thinking of migrating, or what our providers are requesting, is a years’ worth of results. ‘Give me a year’s worth of results, and then make sure everything else is available in eHIM.’

Campbell: As such, your default is to migrate a year’s worth of data?

Schoener: Yes. We would presume that the provider is probably not going to refer back to lab results or radiology results beyond a year, other than for health maintenance kind of things such as mammograms, pap smears, PSAs; those types of things.

Campbell: What expectations have you set with physicians when they go live on the new EMR?

Schoener: From an ambulatory perspective, we’re thinking that it would be nice to have the most recent note from the EMR available. All of the other notes for that patient would be consolidated into one note via a single pdf attachment. The note that’s the separate most recent note, we envision that being in a folder for that particular date. That note would reside in the appropriate folder location just like it would in the current EMR. Our goal is to bring the clinical data forward to the new EMR, taking all the other notes and placing them in a “previous notes” folder.

Campbell: Can you elaborate on your consideration of PAMI (Problems, Allergies, Medications, Immunizations) as part of the data migration?

Schoener: Sure. The disaster scenario would be the physician sits down with patient for first time with new EMR, and there are no meds, no allergies, and no problems! They’ll spend 25 minutes just gathering information, that would not work.

We’re thinking of deploying a group of nurses to assist with the data conversion and migration process. Our intent is to have them to retrieve CCDAs to populate those things I mentioned by consuming them right into the medical record, based on the physicians’ input. We expect there to be a reconciliation process to clean-up potential duplicates. Or, to be candid, we’ve talked about automating the CCDA process, consuming discrete clinical items from it by writing scripts and importing into the new EMR. I think we’re leaning towards having some staff involved in the process though.

Now if you share the same database between your acute and ambulatory EMR, and the patient was in ambulatory setting but now they’ve been admitted, it’s the same database: the meds are there, the problems are there, the allergies are there; it’s beautiful, right? If they weren’t, then the admission nurse is going to have to follow the same CCDA consume process that the ambulatory nurse followed. Or you start from scratch. On the acute side, we start from scratch a lot. Patients come in and we basically just start asking questions in the ER or in an acute care setting. We start asking for their meds, allergies, or problems – whatever they may have available.

Campbell: We’ve discussed notes, results and PAMI. Are there other clinical data elements that you’ve examined? How will you handle those?

Schoener: From an acute care perspective, our physicians are very interested in seeing the last H & P (History & Physical Examination) and the last operative note, so we’re going to consider two different ideas. One would be that all of that data would still reside in document management, which has the ability to be sorted. It’s currently very chart centric. For instance, you can easily pull the patient’s last acute care stay. There is the ability, however, to sort by H & P, operative note, or discharge summary—something along those lines for the separate buckets of information. Therefore, a physician could view the most recent H & P or view all sorted chronologically. In addition, they’ll be able to seamlessly launch directly from the new EMR to the old EMR, bypassing authentication, which is important to mitigate context switching.

One of the areas we’re struggling with is the growth chart. A physician would love the ability to see a child’s information from start to finish, not just from the time of the EMR transition. So that means some sort of birth height/weight data that we would want to retrieve and import into the new system so a growth chart could be generated. The other option is to somehow generate some sort of PDF of a growth chart up until the place where we transitioned to the new EMR. The latter however, would result in multiple growth charts, and a physician’s not going to be happy with that. So we’re trying to figure that one out.

Another area of concern is blood pressure data. We’re struggling with what to do with a patient we’re monitoring for blood pressure. We’d like to see more than one blood pressure reading and have some history on that.

Campbell: Thank you for elaborating on those items. What about data that is not migrated. How will that be addressed and persisted going forward?

Schoener: For the most part, everything else would be available in the document management system. We can generate that data from document our document management system and make it available to be queried by OIG or whoever else requires that data from a quality perspective. We are aware that an archival solution is very expensive. We’re being told, ‘if you think you’re going to migrate and move all this data to some sort of other archiving solution, get ready for a sticker shock.’ If that’s what the advisors and consultants are saying, then our thought is that probably isn’t going to be the direction we’re going to go. We’re likely going to stick with some type of document management system for archival.

Campbell: Very good. How are you gathering feedback from different specialties and departments? Do you have a governance process in place?

Schoener: So as you may have gathered, we’re getting ready. I don’t want surprises. I want physicians to be prepared and to set expectations for what’s going to be available. What I just described to you, we’ve vetted that out with our primary care docs. Now we’re going to take that to our cardiologists and ask them what they think. Then on to our urologists to allow them to weigh in. Our intent is to take it to each physician specialty to establish a good comfort level, so when the transition occurs, I don’t have physicians’ saying to me ‘no one ever asked me…’ or not be able to provide excellent patient care. It’s going to be critical to the success of our EMR transition to keep our physicians engaged and involved.

There will definitely be a learning curve with the new EMR, but we want to be clear and set expectations with respect to data migration and conversion, so that when the physician does use the new EMR they’re not saying ‘that darn Cerner or Epic.’  It’s more ‘that’s a part of the data migration process and we weren’t able to accomplish that.’

Campbell: What about legacy applications support. Will all of your staff be dedicated to the new project?

Schoener: I mean, let’s face it, no staff member has the desire to support the legacy application when all of their coworkers are learning the new application. That’s a career limiting move. We still haven’t decided what to do.

Campbell: I agree that no staff member wants to be left behind. I’ve talked to organizations where they use folks for both and it just doesn’t end well. You can’t expect them to do both, learning the new system while supporting the old one.

Schoener: I guess it depends on the capacity and the expectation of that particular project they’re working on. Maybe there is a person who has less involvement with the new EMR and they have availability where they can support both, although it’s unlikely. Sometimes you end up having someone who wants to retire within the time period. In that case, they can almost work their way to retirement and then not ever support the new EMR, although that situation is also unlikely.

It’s a great question, and one we’re going to have to have folks help us determine.

Campbell: Shifting gears a little bit, what are your thoughts on health data retention requirements? Too loose? Too stringent?  As you know, it varies state-to-state, from 7-10 years, but I feel like there’s a huge responsibility that is placed on organizations to be the custodians of that data. Do you agree?

Schoener: I think that’s just healthcare. A lot of it is legal considerations and our need to protect ourselves. That’s why do we do a lot of the things we do. We’re protecting ourselves from lawsuits and litigation. I think it’s expected; it’s just the nature of the business. Just think of what we had in a paper world. We used to have rooms and rooms full of charts and now that’s all gone. With our current process, any paper that comes in is scanned in within the first 24 hours. So it’s not something I worry about. My focus now is making sure our providers can perform excellent patient care on the new EMR.

Campbell: Could you provide some advice, insight or wisdom for healthcare organizations pursuing EMR/EHR replacement & transition?

Schoener: Get ready for some fun! Affiliations and acquisitions are greatly impacting these decisions. It used to be something that struggling organizations were forced to pursue, but now very successful organizations are starting to affiliate and merge with other organizations because it’s just the state of healthcare. One bit of wisdom for anyone is: if you’re not interested in that type of transition and change occurring, healthcare’s not for you. That’s the nature of the business we’re in.

I would say from an EHR transition process, I found that having an advisor is extremely beneficial to help me think outside of my day-to-day operations. They’re able to look outside of your organization and ask the right questions. If you pick the right advisor, they’ll protect you and protect your organization. I think it’s been very healthy for us to have someone from the outside give us counsel and advice because it’s a tough process. It’s extremely expensive, and extremely polarizing.

Campbell: Outside of the networking, what did you come to CHIME focused on this year?

Schoener: CHIME is a great way to challenge yourself as a CIO and in your leadership, it pushes me in my leadership skills and helps to focus me back to what’s critical in the industry. It helps me to think more strategic and broad, not to get too engaged in one particular topic. I think it’s just great for professional development. CHIMEs the best out there with respect to what I do.

This interview has been edited and condensed.

Evaluate options, define scope and formulate a strategy for EHR data migration by downloading Galen’s EHR Migration Whitepaper.

About Tim Schoener
Tim Schoener is the Vice President/Chief Information Officer for UPMC Susquehanna, a new partner of UPMC since October 1, 2016, which is a four-hospital integrated health system in northcentral Pennsylvania including Divine Providence Hospital, Muncy Valley Hospital, Soldiers + Sailors Memorial Hospital and Williamsport Regional Medical Center. UPMC Susquehanna has been Most Wired for 14 of the last 16 years and also HIMSS Level 6. Tim has worked at Susquehanna for over 24 years, 19 of those years in Information Technology.  He also has responsibilities for health records, management engineering and biomedical engineering. He is a CHCIO, HIMSS Fellow and CPHIMS certified. Tim received his undergraduate degree from The Pennsylvania State University with a BSIE in Industrial Engineering and his MBA from Liberty University. 

About Justin Campbell
Justin is Vice President, Strategy, at Galen Healthcare Solutions. He is responsible for market intelligence, segmentation, business and market development and competitive strategy. Justin has been consulting in Health IT for over 10 years, guiding clients in the implementation, integration and optimization of clinical systems. He has been on the front lines of system replacement and data migration and is passionate about advancing interoperability in healthcare and harnessing analytical insights to realize improvements in patient care. Justin can be found on Twitter at @TJustinCampbell and LinkedIn.

About Galen Healthcare Solutions
Galen Healthcare Solutions is an award-winning, #1 in KLAS healthcare IT technical & professional services and solutions company providing high-skilled, cross-platform expertise and proud sponsor of the Tackling EHR & EMR Transition Series. For over a decade, Galen has partnered with more than 300 specialty practices, hospitals, health information exchanges, health systems and integrated delivery networks to provide high-quality, expert level IT consulting services including strategy, optimization, data migration, project management, and interoperability. Galen also delivers a suite of fully integrated products that enhance, automate, and simplify the access and use of clinical patient data within those systems to improve cost-efficiency and quality outcomes. For more information, visit www.galenhealthcare.com. Connect with us on Twitter, Facebook and LinkedIn.

Population Health 101: The One Where It All Starts

Posted on December 7, 2016 I Written By

The following is a guest blog post by Abhinav Shashank, CEO & Co-founder of Innovaccer.
population-health-101
Former US President Abraham Lincoln once said, “Give me six hours to chop down a tree and I’ll spend four hours sharpening the ax.”  After having a look at the efficiency of the US healthcare system, one cannot help but notice the irony. A country spending $10,345 per person on healthcare shouldn’t be on the last spot of OECD rankings for life expectancy at birth!

Increasing Troubles
report from Commonwealth Fund points out how massive the US health care budget is. Various US governments have left no stone unturned in becoming the highest spender on healthcare, but have equally managed to see most of its money going down the drain!

Here are some highlights from the report:

  1. The US is 3rd when it comes to public spending on health care. The figure is $4197 per capita, but it covers only 34% of its residents. On the other hand, the UK spends only $2,802 per capita and covers 100% of the population!
  2. With $1,074, US has the 2nd highest private spending on healthcare.
  3. In 2013, US allotted 17.1% of its GDP to healthcare, which was the highest of any OECD country.   In terms of money, this was almost 50% more than the country in the 2nd spot.
  4. In the year 2013, the number of practicing physicians in the US was 2.6 per 1000 persons, which is less than the OECD median (3.2).
  5. The infant mortality rate in the US was also higher than other OECD nations.
  6. 68 percent of the population above 65 in the US is suffering from two or more chronic conditions, which is again the highest among OECD nations.

The major cause of these problems is the lack of knowledge about the population trends. The strategies in place will vibrantly work with the law only if they are designed according to the needs of the people.

population-health-trends

What is Population Health Management?
Population health management (PHM) might have been mentioned in ACA (2010), but the meaning of it is lost on many. I feel, the definition of population health, given by Richard J. Gilfillan, President and CEO of Trinity Health, is the most suitable one.

Population health refers to addressing the health status of a defined population. A population can be defined in many different ways, including demographics, clinical diagnoses, geographic location, etc. Population health management is a clinical discipline that develops, implements and continually refines operational activities that improve the measures of health status for defined populations.

The true realization of Population Health Management  (PHM) is to design a care delivery model which provides quality coordinated care in an efficient manner. Efforts in the right direction are being made, but the tools required for it are much more advanced and most providers lack the resources to own them.

Countless Possibilities
If Population Health Management is in place, technology can be leveraged to find out proactive solutions to acute episodes. Based on past episodes and outcomes, a better decision could be made.

The concept of health coaches and care managers can actually be implemented. When a patient is being discharged, care managers can confirm the compliance with health care plans. They can mitigate the possibility of readmission by keeping up with the needs and appointments of patients. Patients could be reminded about their medications. The linked health coaches could be intimated to further reduce the possibility of readmission.

Let us consider Diabetes for instance. Many times Diabetes is hereditary and preventive measures like patient engagement would play an important role in mitigating risks. Remote Glucometers, could be useful in keeping a check on patient sugar levels at home. It could also send an alert to health coaches and at-risk population could be engaged in near real-time.

Population Health Management not only keeps track of population trends but also reduces the cost of quality care. The timely engagement of at-risk population reduces the possibility of extra expenditure in the future. It also reduces the readmission rates. The whole point of population health management is to be able to offer cost effective quality-care.

The best thing to do with the past is to learn from it. If providers implement in the way Population Health Management is meant to be, then the healthcare system would be far better and patient-centric.

Success Story
A Virginia based collaborative started a health information based project in mid-2010. Since then, 11 practices have been successful in earning recognition from NCQA (National Committee for Quality Assurance). The implemented technologies have had a profound impact on organization’s performance.

  1. For the medical home patients, the 30-day readmission rate is below 2%.
  2. The patient engagement scores are at 97th percentile.
  3. With the help of the patient outreach program almost 40,000 patients have been visited as a part of preventive measures.

All this has increased the revenue by $7 million.

Barriers in the journey of Population Health Management
Currently, population health management faces a lot of challenges. The internal management and leadership quality has to be top notch so that interests remain aligned. Afterall, Population Health Management is all about team effort.

The current reimbursement model is also a concern. It has been brought forward from the 50s and now it is obsolete. Fee-for-service is anything, but cost-effective.

Patient-centric care is the heart of Population Health Management. The transition to this brings us to the biggest challenge and opportunity. Data! There is a lot of unstructured Data. True HIE can be achieved only if data are made available in a proper format. A format which doesn’t require tiring efforts from providers to get patient information. Providers should be able to gain access to health data in seconds.

The Road Ahead
We believe, the basic requirement for Population Health Management is the patient data. Everything related to a patient, such as, the outcome reports, the conditions in which the patient was born, lives, works, age and others is golden. To accurately determine the cost, activity-based costing could come in handy.

Today, the EMRs aren’t capable enough to address population health. The most basic model of population health management demands engagement on a ‘per member basis’ which can track and inform the cost of care at any point. The EMRs haven’t been designed in such a way. They just focus on the fee-for-service model.

In recent years, there has been an increased focus on population health management. Advances in the software field have been prominent and they account for the lion’s share of the expenditure on population health. I think, this could be credited to Affordable Care Act of 2010, which mandated the use of population health management solutions.

Today, the Population Health Management market is worth $14 billion and according to a report by Tractica, in five years, this value will be $31.8 billion. This is a good sign because it shows that the focus is on value-based care. There is no doubt we have miles to go, but at least now we are on the right path!

EMR Data Archival Strategy Deep Dive – Tackling EHR & EMR Transition Series

Posted on November 14, 2016 I Written By

The following is a guest blog post by Robert Downey, VP of Product Development at Galen Healthcare Solutions.

Inside the world of data archival (Download this Free Data Archive Whitepaper for a deep dive into the subject), there are nearly as many different types of archives as there are vendors. Many of the existing archival solutions that have gained popularity with large healthcare organizations are ones that are also frequently utilized by other sectors and often claim to be able to “archive anything.”

This can be very appealing, as an organization going through a merger will often retire dozens or even hundreds of systems, some clinical, but most only tangentially related to the delivery of care. HR systems, general ledger financial systems, inventory management, time tracking, inventory tracking systems, and CRMs are just a few of the systems that might also be slated for the chopping block. The idea of retiring all of these into a single logical archival solution is very appealing, but this approach can be a dangerous one. The needs of healthcare organizations are not necessarily the same as the needs of other sectors.
ehr-data-archiving-process
To understand why some archival approaches are superior to others, it’s useful to visualize the way each of the solutions extract, store, and visualize data. The methodologies used typically trade fidelity (how well it preserves the original shape and precision of the data) for accessibility (how easy it is to get at the information you need), and they trade how easily the solution can archive disparate sources of data (such as archiving both an EMR and a time-tracking system) with, again, accessibility.

There are certainly other ways to judge an archival solution. For instance, an important factor may be whether or not the solution is hosted by the archival vendor on-premises or remotely. Some factors, such as the reliability of the system, service level agreements, or its overall licensing cost are big inputs into the equation as well, but those aren’t necessarily specific to the overall archival strategy utilized by the solution. There are also factors that are so critical, such as security and regulatory compliance, that deficiencies in these areas are deal-breakers. Now that we have the criteria with which to judge the solution, let’s delve into the specific archival strategies being used in the marketplace.

Raw Data Backups
raw-healthcare-data-backups
A shockingly large number of organizations treat raw data backups of the various databases and file systems as their archival solution. There are some scenarios in which this may be good enough, such as when the source system is not so much being retired as it is being upgraded or otherwise still maintained. Another scenario might be when the data in question comes from systems so well known that the organization won’t have significant issues retrieving information when it becomes necessary. The greatest benefit to this approach is that acquiring the data is fairly trivial. Underlying data stores almost always offer easy built-in backup mechanisms. Indeed, the ability to back up data is a certification requirement for EMRs, as well as a HIPAA and HITECH legal requirement. This strategy also offers “perfect” data fidelity, as the data is in the raw, original format.
health-data-archive-fidelity
Once it actually comes time to access the “archived” data, however, the organization is forced to fully reverse engineer the underlying database schemas and file system encodings. This leads to mammoth costs and protracted timelines for even simple data visualization, and it’s a major undertaking to offer any kind of significant direct clinician or compliance access to data.

Another danger with raw database backups is that many clinical system vendors have language in their licensing related to the “reverse engineering” of their products. So while it may be “your” data, the vendor may consider their schema intellectual property — and the act of deciphering it, not to mention keeping a copy of it after the licensing agreements with the system vendor have been terminated — may well be a direct violation of the original licensing agreement.

Hybrid Modeled / Extracted Schema
extracted-schema-data-archiving
A common approach utilized by healthcare-specific archival solutions is to create a lightweight EMR and practice management schema that includes the most common data attributes from many different source system vendors and then map the data in the source system to this fully modeled schema. The mapping involved is usually limited to fieldtype mapping rather than dictionary mapping, although occasionally, dictionary data which feeds user interface aspects such as grouping (problem categories, for instance) may require some high-level mapping.

This approach usually yields excellent clinical accessibility because the vendor can create highly focused clinical workflows just like an EMR vendor can. Since these visualizations don’t need to be created or altered based on the source system being archived, it means that there is generally no data visualization implementation cost.
healthcare-data-archiving
As the mapping is limited to the schema, the extraction and load phase is usually not as expensive as a full EMR data migration, but because every required source field must have a place in the target archival schema, the process is typically more time-consuming and expensive than the hybrid modeled / extracted schema or non-discrete document approaches. That said, vendors that have a solid library of extraction processes for various source systems can often offer lower initial implementation costs than would otherwise be possible.

The compliance accessibility and data fidelity of this strategy can be problematic, however, as unknown fields are often dropped and data types are frequently normalized. This fundamentally alters a substantial portion of the data being archived in the same way that a full data migration can — although, again, not as severely given the typical lack of data dictionary mapping requirements. In some cases, vendors will recommend that a full backup of the original data be kept in addition to the “live” archive, providing some level of data fidelity problem mitigation. Should a compliance request require this information, however, the organization may be left in a similar position to those utilizing raw data backups or extracted schema stores with no pre-built visualizations.

Archival solutions utilizing this strategy may also frequently require augmentation by the vendor as new sources of data are encountered. This can make the implementation phase longer, as those changes typically need to happen before any data can be loaded.

Summary
There will never be a one-size-fits-all archival solution across organizations, and even within an organization, when determining the strategy for multiple systems. Another key takeaway is to always be wary of all the “phases of implementation.” Many vendors will attempt to win deals with quick and inexpensive initial implementations, but they leave significant work for when the data actually needs to be visualized in a meaningful way. That task either falls on the organization, or it must be further contracted with the archival solution provider.

It also is valuable to consider solutions specifically designed for archival purposes and, ideally, one that focuses on the healthcare sector. There are simply too many archival-specific scenarios to utilize a general purpose data backup, and many organizations find that the healthcare-specific requirements make general purpose archival products ill-suited for their needs.

Download Galen Healthcare’s full archival whitepaper to evaluate available EMR data migration & EMR data archival options and processes critical to EMR replacement and legacy system decommissioning.

About Robert Downey
Robert is Vice President, Product Development, at Galen Healthcare Solutions. He has nearly 10 years of healthcare IT experience and over 20 years in Software Engineering. Robert is responsible for design and development of Galen’s products and supporting technology, including the VitalCenter Online Archival solution. He is an expert in healthcare IT and software development, as well as cloud based solutions delivery. Connect with Robert on LinkedIn.

About Galen Healthcare Solutions
Galen Healthcare Solutions is an award-winning, #1 in KLAS healthcare IT technical & professional services and solutions company providing high-skilled, cross-platform expertise and proud sponsor of the Tackling EHR & EMR Transition Series. For over a decade, Galen has partnered with more than 300 specialty practices, hospitals, health information exchanges, health systems and integrated delivery networks to provide high-quality, expert level IT consulting services including strategy, optimization, data migration, project management, and interoperability. Galen also delivers a suite of fully integrated products that enhance, automate, and simplify the access and use of clinical patient data within those systems to improve cost-efficiency and quality outcomes. For more information, visit www.galenhealthcare.com. Connect with us on Twitter, Facebook and LinkedIn.