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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.

Clinical System Replacement & Decommissioning: Migrate or Archive? – Tackling EHR & EMR Transition Series

Posted on September 21, 2016 I Written By

clinical-system-complexity
(See Full Healthcare Data Archival Infographic)

A Maturing Healthcare IT Landscape
If 2010 was the year of EMR implementations and optimization driven by initiatives like Meaningful Use, the ARRA, and Obamacare, then 2015 might be known as the year that clinical application retirement became a prevalent topic for many mature healthcare organizations.

Application retirement is nothing new. Large organizations both inside and outside of healthcare have had application retirement strategies in place (typically doled out by expensive consulting companies with fancy matrices, methodologies, and graphs in tow) for a decade or more. Anytime an organization outlives a large IT system (or, in many cases, that system’s vendor), retirement becomes a pressing need. In the case of healthcare, the two largest driving factors forcing clinical application retirement are the consolidation of organizations into large integrated care delivery networks, and replacement of existing electronic healthcare record systems due to poor usability or inadequate functionality.

Migration and Archival – Not Migration Versus Archival
One question that often comes up early on in the process of clinical application retirement is whether it’s necessary at all if the data in these systems is also being migrated into a new EMR. Conversely, the question of whether the cost of a migration is worth it if the archival solution being considered supports some sort of continuity of care solution like seamless single sign on from the new EMR. In most cases, it turns out that the ideal approach is migration and archival.

Just Migrate?
The process of EMR data migration almost always results in some fairly fundamental alteration of the legacy EMR data. The data models used by different EMRs are typically quite different, and it’s not a matter of export/import. Instead, it’s a true ETL process – extract, transform, load.

The shape of the data is changed. Sometimes data types undergo conversions, such as a number to a string, which if done poorly can result in loss of precision. Data sets, such as order codes, result codes, diagnosis categories, note types, and various other types of dictionaries are mapped from the values in the legacy EMR to the values used by the new EMR. Fields that have no apparent corollary in the new EMR are often just dropped entirely. It’s frequently not possible to know for sure what the data actually looked like in the legacy system once this process is complete and the legacy system is actually retired.
legacy-ehr-archive
Not only that, but from a clinical perspective, it’s probably not useful to take 15 years of legacy data and load that directly into your new EMR. Most organizations opt for something more likely to be relevant, while still remaining safe; perhaps 3 to 5 years of data. While the state and federal requirements for archival are clear on how long you need to preserve data (from 6 years to forever, depending on a variety of factors), they aren’t nice enough to say that the data you need to preserve is limited to what’s usually currently clinically relevant. In other words, that 10-year-old test result is still, technically, part of the legal medical record.
legal-medical-record-and-continuity-of-care
Some EMR vendors will even outright limit the mechanisms for data import to something like a CCD (clinical continuity document) import, which inherently limits the scope and quantity of available data that can be preserved.

Just Archive?
Ok. You give up. Obviously a migration isn’t going to cover us, and if the archive has everything we need legally and clinically, let’s skip that time consuming and expensive migration and just archive. Well, you can do that, but just archiving means that your organization is abandoning millions of dollars of hard won documentation and all the automation and analytics that goes with that.

An EMR is a lot more than a place to store clinical documentation. Virtually all modern EMRs have substantial functionality surrounding clinical decision support, health maintenance planning, and quality reporting. They also often are crucial source of data for analytics suites that are the pillars of population health management. In short, not migrating this data means you should have just stuck with paper charts until your latest and greatest EMR was available.

It’s certainly possible to bring over data in a manual, piece meal fashion as patients are seen or based on some other reasonably predicable event whose workflow can be augmented. This will, eventually, patch up the gaps in data that not performing a migration results in. If your organization is willing to suffer the significant, but probably short to medium term repercussions of temporarily losing this data in your EMR and related operational data repositories, then migration might not be necessary.

Not All Archives Are Created Equal
Inside the world of data archival, 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, 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 archiving is very appealing, but this approach can be a dangerous one. The needs of healthcare are not necessarily the same as the needs of other sectors.

Some factors that make healthcare different include:

  • The highly complex data models used by electronic healthcare record systems.
  • The common need for specialized user interfaces to properly visualize the data.
  • The continuing need for clinicians to seamlessly access the archived data with minimal workflow interruption.
  • The incredible variety of source systems that are in need of archival.
  • The lack of data format standards to make it easy to determine what needs to be archived.
  • The need for HIPPA and HITECH compliance (think encryption and auditing).
  • The massive size of the data to be archived, the need to constantly add new sources of data to an existing archive as the organization expands.
  • The frequent need to rapidly produce specific subsets of archived data during an eDiscovery proceeding or other legal compliance scenarios.

Summary:

  • There must be a clear distinction made between “migrated” or “converted” data and archived data, as the drivers and considerations for each are different. Retiring a legacy application and housing the data in an archival solution has markedly different requirements than migrating data from an existing clinical application to another.
  • Retiring legacy systems typically do not necessitate changing the “shape” of the data to fit a particular model. A data archival solution facilitates legacy system retirement, providing a storage solution for clinical data archival in compliance with state and federal regulations for protected health information (PHI).
  • With EMR migration, data typically needs to be mapped and translated to facilitate proper import into the target system. This is critical for the clinical impact and workflow integration required to support a discrete clinical data migration.

Download the 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.

10 Reasons for Full EHR Data Migration – Tackling EHR & EMR Transition Series

Posted on September 7, 2016 I Written By

top-10-reasons-for-ehr-data-migration

(Check Out the Full Top 10 Reasons for EHR Data Migration Infographic)

At Galen Healthcare Solutions we’ve found some important considerations and benefits during EHR data migration, including:

  • Legacy application licensing, and on-going support & maintenance.
  • Avoidance of data redundancy and improvement of data integrity.
  • Productivity and efficiency gains through enhanced clinical decisions support and consolidated clinical data access.
  • Enhanced regulatory reporting with programs including PQRS & PCMH.

When undertaking an EHR replacement project, there is a general misconception that the all of underlying patient clinical data is migrated systematically with ease. However, due to cost and complexity constraints, in most cases only patient demographics and basic clinical data elements are migrated to the new EHR system. In these cases, the legacy system is left operational in a read-only capacity; used as “system of record” for compliance, audits and responses for requests for information. Contrary to popular thought, this approach can actually end up being costlier than pursuing EHR data migration and archival, especially considering clinical efficiencies and patient care benefits associated with each of the latter.
legacy-ehr-data-migration
Understanding available EHR data migration & EHR data archival options and processes are vital to EHR replacement. Not doing so potentially leaves providers and staff inaccurate, unusable or missing data at go-live, compromising patient care. It’s important to evaluate scoping considerations, including options for import of discrete and non-discrete migrated data the new EHR systems provides, expertise of internal or external resources to migrate the data, and data retention requirements. Typically, the data elements & amount/duration of data to be migrated vs. archived is driven by organizational requirements related to continuity of care, patient safety, and population-based reporting requirements. Further, care needs to be taken to ensure data integrity when migrating clinical data – mapping nomenclatures and dictionaries where possible to avoid duplication, and facilitating reconciliation of the data to the existing chart in the target system.

At the heart of the EHR data migration process, it’s important that clinically driven workflows across various user roles are supported, transitioned, and maintained to the greatest extent possible. EHR data migration and archival allows for successful retirement of antiquated legacy applications, and ensures seamless and successful transition to the new EHR system.

Evaluate options, define scope and formulate a strategy for EHR data migration by downloading our EHR Migration 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.

Decommissioning Legacy EHR systems with Data Archival – Tackling EHR & EMR Transition Series

Posted on August 25, 2016 I Written By

EMR Data Archival

In their latest infographic (Check out the full infographic), Galen Healthcare Solutions provides critical information and statistics surrounding EMR data archival including:

  • Healthcare Data Growth
  • Healthcare Data Archival Drivers
    • Mergers & Acquisitions
    • Legacy System Retention Requirements
  • Healthcare Data Archival Benefits
  • Average Patient Digital Footprint
  • Industry Leading Archival Solution

Healthcare Information Technology leaders face challenges in keeping pace with new initiatives and consequently, managing a growing collection of legacy systems. With drivers including mergers & acquisitions, vendor consolidation, application dissatisfaction and product sunsets, it’s estimated that 50% of health systems are projected to be on second-generation technology by 2020, according to the IDC. As these new systems are implemented, multiple legacy systems are left behind, requiring healthcare IT staff to provide support and maintain access.

The strategy of keeping a patchwork of legacy systems running in order to maintain access to data is risky, resource intensive and can be quite costly given licensing, support, and maintenance needs. Decommissioning legacy systems with a proven archival system reduces cost and labor, minimizes risk, ensures compliance, simplifies access and consolidates data.

  • Reduce Costs: Streamlining the long-term storage of historical PHI now will save money in the long-run. Not only will it reduce costs paid for the support and technical maintenance of the legacy system, but it will also save on training new staff on the new system over the next 7-25 years. In addition, incorporating data archival efforts with a discrete data migration provides significant economies of scale.
  • Minimize Risk: Preserving historical patient data is the responsibility of every provider. As servers and operating systems age, they become more prone to data corruption or loss. The archiving of patient data to a simplified and more stable storage solution ensures long-term access to the right information when it’s needed for an audit or legal inquiry. Incorporating a data archive avoids the costly and cumbersome task of a full data conversion.
  • Ensure Compliance: Providers are required to retain data for nearly a decade or more past the date of service. In addition, the costs of producing record for e-Discovery range from $5K to $30K/ GB (Source: Minnesota Journal of Law, Science & Technology). Check with your legal counsel, HIM Director, medical society or AHIMA on medical record retention requirements that affect the facility type or practice specialty in your state.
  • Simplify Access: We all want data at the touch of a button. Gone are the days of storing historical patient printouts in a binder or inactive medical charts in a basement or storage unit. By scanning and archiving medical documents, data, and images, the information becomes immediately accessible to those who need it.
  • Consolidate Data: Decades worth of data from disparate legacy software applications is archived for immediate access via any browser-based workstation or device. Also, medical document scanning and archiving provides access to patient paper charts.

Because the decision to decommission can impact many people and departments, organizations require a well-documented plan and associated technology to ensure data integrity.

Download the full archival whitepaper to understand the drivers that impact archival scope specific to both the industry and your organization.

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

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.

EHR Data Migration – Tackling EHR & EMR Transition Series

Posted on August 10, 2016 I Written By

EHR Data Migration
(See Full EHR Data Migration Infographic)

In this infographic, Galen Healthcare Solutions provides critical information and statistics pertaining to EHR data migration including:

  • Healthcare Data Growth
  • EHR Data Migration Drivers
    • Mergers & Acquisitions
    • System Consolidation
  • EHR Data Migration Challenges
  • Industry Leading EHR Migration Solution

The demand for data migration within the U.S. healthcare market is growing exponentially. The increase in mergers and acquisitions is driving system consolidation as is the increasing number of HCOs seeking EHR replacements to address usability and productivity concerns. A recent survey by Black Book Rankings found that nearly one-fifth of large practices and clinics intend to undergo an EHR replacement by the end of 2016. In addition, a 2015 Kalaroma report shows that the EHR replacement market will grow at an annual rate of 7-8% over the next five years.

EHR Data Migration Process

The process of migrating from one EHR to another is among the most difficult technical and functional projects a healthcare organization will ever confront. The EHR transition requires vendor selection, assessment and scoping, legacy system optimization, data migration, legacy application support, data archival, and new system implementation. If organizations fail to address any of these components properly, their migration could leave healthcare providers without the information needed to make the best patient care decisions, and organizations without easy access to the historical data necessary for participating in quality reporting initiatives and other current and emerging value based care reimbursement methodologies.

Learn more about EHR transition, replacement and migration strategies, methodologies, tips & tricks, and best practices by downloading our EHR Migration 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

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.