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Most doctors with EHRs still not taking advantage of their benefits

Most doctors with EHRs still not taking advantage of their benefits | EHR and Health IT Consulting | Scoop.it

Interoperability of medical records across physician offices remained elusive in 2015, according to the latest data reported out by the Centers for Disease Control.

About 8 in 10 U.S. physicians had an electronic health records system in 2015. One-third of these doctors electronically sent, received, integrated or searched for patient health information — indicating that most physicians still aren’t using EHRs to their fullest extent. These findings come from the NCHS Data Brief from the CDC, State Variation in Electronic Sharing of Information in Physician Offices: United States, 2015.. Only 9 percent of physicians took advantage of all four functions.

 

Full use of EHRs varies by state:

  • The percent of doctors who electronically sent patient health information to other providers ranged from a high of 56.3 percent in Arizona to a low of 19.4 percent in Idaho.
  • The percent of doctors who electronically received patient health data from other providers ranged from a high of 65.5 percent in Wisconsin to a low of 23.6 percent in Louisiana and Mississippi.
  • The percent of doctors who electronically integrated patient health information from other providers ranged from a high in 49.3 percent in Delaware to a low of 18.4 percet in Alaska.
  • The proportion of doctors who electronically searched for patient information from other providers ranged from a high or 61.2 percent in Oregon to a low of 15.1 percent in Washington, DC (the District of Columbia).

These data come from the 2015 National Electronic Health Records Survey which polled a national sample of nonfederal office-based patient care physicians between August and December 2015.

 

Health Populi’s Hot Points:  Most U.S. physicians have purchased, installed and are using electronic health records systems, driven primarily by financial incentives they’ve derived from the HITECH Act — part of the Stimulus Bill (more formally, the American Recovery and Reinvestment Act of 2009). Why was this part of the Stimulus package? The policy thinking was that health care costs in America were a key driver of the long-term deficit and so the U.S. health system had invest in the means to measure health spending and outcomes and then manage what we measure.

Without interoperability — that is, the ability to move data where it needs to go throughout the continuum of care and shared across providers who all serve the patient — we can’t fully measure, and thus manage, costs and quality for that N of 1 patient.

U.S. taxpayers have made the investment into EHRs for their doctors. But we’ve still miles to go before we see and benefit from the ROI from fully interoperable digital health records systems. There are promising technologies and standards beginning to be adopted by pioneering informaticists and healthcare systems — FHIR standards for innovating within the EHR environment, and APIs bringing patient-generated data to their personal health records. May 2017 be a new year for health data liquidity and sense-making out of EHRs

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EHR and Health IT Consulting
Technical Doctor's insights and information collated from various sources on EHR selection, EHR implementation, EMR relevance for providers and decision makers
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EHR and Challenges of the Modern Medical Note

EHR and Challenges of the Modern Medical Note | EHR and Health IT Consulting | Scoop.it

There was a time when documentation was an almost inconsequential process. After seeing a patient, the doctor would scratch a note, close the folder, and file it on a shelf until the next visit.

 

Things are different and the medical note has evolved. As it’s evolved, electronic health records (EHR) have brought efficiencies to the medical note while introducing new challenges. And like the cognitive biases that impact patient care, the problems inherent in documentation need attention.

 

Thinking about these challenges becomes important in documenting care and training the next generation of health professionals. Here are a few that I think about

Auto Documentation

One of the powers of the EHR is that it allows users to auto-populate the medical record with chunks of pre-fabricated text known as smart phrases. But these personally created building blocks of the medical note create the potential for one-clip-fits-all documentation. As I’ve said in the past, the smart phrase is not new technology.

 

I work to keep smart phrases out of my history of present illness and impression where individualized narratives show what’s unique about a case. Free text keeps me real.

Replicability

While smart phrases represent the dropping of self-created language, we have the ability to clip and paste information from other parts of the chart. This may include bits and pieces from notes penned by another medical professional.

 

While we all lift bits of language from places like CT and biopsy reports, issues arise when the origination of our language is that of another health professional. Epic now allows visualization of a phrase’s origin when not created by the author.

 

I’m careful about what I copy. I’m twice as careful with what I paste as a representation of my own thinking.

Size and absence of constraint

While smart phrases are limited only by our imagination, a digital note with no constraints predisposes to note bloat, one of the looming threats to modern medicine. Pre-digital notes were constrained by writer’s cramp.

 

I’ve laboured through notes where every single lab drawn on a complicated patient is dumped into the note. Pages and pages of marginally abnormal CBC and metabolic panels create a scenario where it’s difficult, if not impossible, to discern what data is relevant to the decisions made.

 

I try to consider the needs of the end user of the note. Of course, this is challenging when our opinion of what constitutes a ‘good note’ varies from that of the note read.

Ambiguity of purpose

This is the most remarkable phenomenon of the modern medical note. Medical notes have traditionally had pet purposes. Medical students learn early on that ‘the right way to write a note’ varies not only by speciality but by the whim of the individual physician responsible for the note. Physicians with firm views regarding what constitutes the purpose of a note may even morph their perspective depending upon the nature of an individual case.

So if you ask 3 physicians the purpose of a medical note and you’ll get 5 answers ranging from billing and quality documentation to legal coverage and professional communication. Over time the medical note has morphed into all of these things at once.

 

The problem with an ambiguity of purpose is how to manage the expectations of the end user. A physician who feels compelled to paste three months worth of blood results into the data portion of a note will be at odds with someone like myself who believes that a note serves to offer nothing other than concise support for what I’m thinking and planning.

 

As notes become more visible to more folks we can expect ambiguity of purpose to become more pronounced. Digital notes and their capacity for customization amplify this divergence of purpose.

Scaling visibility of the EHR

Once restricted to the shelves of offices in big buildings, medical documentation has traditionally been siloed. This was fine because notes existed for the doctors who occupied those individual offices.  The medical note is now enjoying new freedom in its electronic shape. More notes are more visible to more professionals. This is evident within consolidated health systems where networks of offices connect to big hospitals.

 

Beyond professionals, patients are watching and, in some cases, editing their own notes. OpenNotes is a related program based in Boston’s Beth Israel hospital. Regular patient review and revision represent a revolutionary move in medical documentation.

This scaling visibility of the modern note brings greater scrutiny for what we do or don’t do.

 

This idea of the medical note and its evolution gets little attention yet it represents the core medium of all documentation by medical professionals. It deserves more thorough attention and study.

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EHRs and the Problem of Efficiency

EHRs and the Problem of Efficiency | EHR and Health IT Consulting | Scoop.it

Some doctors worry about how EHRs slow them down. I worry about how fast they let us go. Too much dropdown makes documentation too easy.

 

And when it comes to doctors and their EHRs, there’s a fine line between efficient and lazy.

 

Seeing the line is important because when it comes to workflow the drive to completion typically overpowers the obligation to showcase thinking and care. I know because I dance the line every day.

 

Four things I do to fight the downside of efficiency:

  1. Recognize that documentation is hard. Good clinical documentation takes work. When it becomes too easy I’ve typically crossed the line.
  2. Build narrative. My HPI and impressions represent an identifiable stream of thought. I don’t use smart phrases in my HPI or impression.
  3. Consider the end-user. How does what I create after a clinical encounter serve those who need to see my thinking?
  4. Stay aware. All of this is a struggle for me. But my discussion and thinking around this make me aware of it. And that’s the first step to staying on top of it.

 

All of this discussion is cause celebre for those interested in going back to manilla folders and clipboards. But don’t be fooled. Take any doctor from the analogue age, give him two glasses of wine and he’ll tell you it was easier to take shortcuts on paper. Illegibility and senseless scribbling was our analogue pulldown.

 

Perhaps most importantly, the problem of efficiency needs discussion among medical trainees who are preoccupied with the drive to completion.

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4 Key Considerations for Analysts When Implementing an EHR 

4 Key Considerations for Analysts When Implementing an EHR  | EHR and Health IT Consulting | Scoop.it

Implementing a new EHR system requires a great deal of collaboration between clinical and technical teams. Analyzing the legacy system and operational workflows, then successfully recreating—or better yet, improving—this experience in a new EHR takes finesse.

The foundation of every successful EHR and other large-scale implementation is a team of analysts who are knowledgeable, engaged and passionate about their work. From groundwork and discovery to build, acceptance testing and go-live support, analysts do it all. Here are four key considerations for analysts to keep in mind to help ensure their projects go well and they continue to thrive in their roles.

 

1 – Start with the end goal in mind.

When gathering requirements, project teams will often start by walking through every workflow in the legacy system with end users. This can be a long process and can lead to a lot of information gathering that is ultimately unnecessary. A better approach is to start at the end and work backwards. Ask users why they complete these workflows and what the expected outcome is. This will help get to the root of the requirements and allow analysts to immediately begin thinking in terms of the new EHR.

Here are several questions analysts can ask when gathering requirements:

  • What is the end goal or objective?
  • Why have you traditionally done it this way?
  • What would improve the process?
  • What is the clinical rationale for this workflow?

By starting at the end and asking users why they do what they do and what outcome they are hoping to achieve, analysts can more effectively and efficiently build a system that meets the needs of users.

 

2 – Be aware of the functional limitations of legacy systems.

A key point that is sometimes overlooked is that EHR workflows are often defined by—and limited by—the functionality of the EHR itself. Users will default to what they are familiar with, so if a certain workflow is used frequently in the legacy system, they will assume it is required in the new one. Some workflows may not be needed, however, because the new EHR is designed to achieve the objective in a different, more efficient way. If analysts do not understand this, they risk building in features that are counterproductive, or not needed at all in the new system.

For example, in her current workflow, a clinic manager needs to generate and print a report of all the assessments completed in the office each day. During requirements gathering, she may feel this is an important step to replicate in the new EHR. As it turns out, this workflow is a result of poor auditing functionality in the legacy system – to keep proper records, the clinic manager is required to generate and print these reports. Improved auditing functionality in the new EHR eliminates the need for the daily assessment report and makes this workflow unnecessary.

 

3 – Communication is key.

One of the most important things an analyst can do is to effectively translate the clinical and business needs of end users into technical requirements for the new EHR system. They must also communicate future-state workflows in a way end users can understand and relate to. Communicating effectively is vital to project success.

EHR transitions are often intimidating and frightening for users who have established a comfort level with the legacy system, and likely had little input in the decision to change platforms. Analysts can begin to alleviate concerns and increase user adoption by putting together a few “quick wins.” A quick win is when an analyst identifies a piece of functionality that is very important to users but is also easy to build and demonstrate in the new EHR. Quick wins communicate to users the team is not only listening to their needs but can also deliver solutions quickly and effectively. This also increases confidence, workgroup participation, and communication response time with users and stakeholders, all of which contribute to project success.

 

4 – Strike a balance between functionality and maintainability.

Enterprise EHR systems are complex and, depending on the size and diversity of the user base, may require a team of several hundred application analysts to maintain. In addition, it’s important to remember that every clinical user in a health system is depending on the EHR to complete their documentation and deliver the highest quality of care to patients. Because of this, it is important to strike a balance between functionality and maintainability.

 

If the project team attempts to build in every piece of functionality requested by end users, including things that are nice to have but not critical for the system to function, the EHR will become unwieldy and difficult to maintain. Future updates by the EHR vendor will likely break any customizations, cause unnecessary downtime, and push the volume of help desk requests beyond what the business can support.

In contrast, if the project team oversimplifies and standardizes too much, they risk building a system that does not meet the core requirements of end users. When users can’t leverage the system the way they need, they find “creative” approaches that don’t always work or simply don’t document everything needed. This can lead to a host of problems such as violating operational policy, regulatory reporting issues, loss of revenue due to incorrect documentation, HIPAA violations and, ultimately, lower quality of care for patients. A well-balanced system will keep the support team busy but not overwhelmed, include all required functionality as well as some quality of life features and allow clinicians to be at their best with patients.

In summary, by keeping workflow objectives in mind, understanding legacy system limitations, communicating effectively and balancing functionality and maintainability, analysts demonstrate the value of their critical role in EHR implementation success.

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Are Providers Satisfied With Their EHR?

Are Providers Satisfied With Their EHR? | EHR and Health IT Consulting | Scoop.it

Physicians are expected to document encounters with patients. This ensures there is a record of crucial information for decision-making and dispute. A decade ago, around 90% of physicians updated their patient records by hand. By the end of 2014, 83% of physicians had adopted EHR systems. The combination of government incentives, advances in technology, and improved outcomes and operations fueled this growth.

When healthcare providers have access to complete and accurate information, patients receive better care and have better outcomes. Electronic Health Records (EHRs) improve providers’ ability to diagnose disease and reduce medical errors. EHRs further help providers meet patient demands, provide decision support, improve communication, and aid in regulatory reporting.

A national survey of providers highlights their perspective on the benefits of having EHR in their practice:

  • 94% of providers report that their EHR makes records readily available at point of care.
  • 88% of providers report that their EHR produces clinical benefits for the practice.
  • 75% of providers report that their EHR allows them to deliver better patient care.

As the adoption of EHR grew over the last 10 years, so too did the need to change EHR systems within health systems, hospitals, and private medical practices. Growth in M&A activity fueled many healthcare organizations to combine data through EHR data conversion. Provider dissatisfaction has played a key role in encouraging change in EHR systems, also increasing EHR data conversion activity.

A study completed by Health Affairs showed, by and large, providers recognize the important advances that EHRs enable. Fewer than 20% of all providers said they would return to paper records. That being said, providers also noted negative effects of current EHRs on their professional lives and on patient care.  While excited about the possibilities provided by EHRs, providers have ultimately found poor usability that does not match clinical workflows, time-consuming data entry, interference with patient interaction, and too many electronic messages and alerts.

According to a 2014 survey of physicians conducted by AmericanEHR Partners:

  • 54% indicated their EHR system increased their total operating costs.
  • 55% said is was difficult or very difficult to use their EHR to improve efficiency.
  • 72% said it was difficult or very difficult to use their EHR to decrease workload.
  • 43% said they had not yet overcome productivity challenges associated with their EHR implementation.

These concerns about EHR usability are in alignment with others, including the American Medical Informatics Association, researchers, and practicing physicians. Given the rate at which many healthcare organizations have adopted EHRs, these organizations find themselves unable to wait for the long-run fixes. Healthcare organizations are now looking to change EHR providers in order to fix many of the providers’ concerns.

As healthcare organizations begin the process of changing EHR providers, there is an increased need for solutions to provide access to and maintain the integrity of data stored in the legacy systems. When this need arises, healthcare organizations have the choice to archive the legacy data, run multiple systems simultaneously, or complete an EHR data conversion.

Given the complexity of the data and variety of potential solutions, one might suppose that handling legacy data would be a complex affair. In many ways, that is true. However, it doesn’t have to be. To learn more about the state of EHRs and potential solutions for maintaining access and integrity of legacy data.

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EHR Data Architect: A successful conversion and data integrity

EHR Data Architect: A successful conversion and data integrity | EHR and Health IT Consulting | Scoop.it

Over the last decade, adoption of EHR systems has increased dramatically among providers. While many healthcare providers have made the shift from paper to electronic health records, there has simultaneously been a growing need among healthcare organizations to change EHR providers. The two largest reasons for this change in systems are dissatisfaction and mergers and acquisitions.

When changing EHR systems, many healthcare organizations turn to experienced EHR Data Architects to help ensure the integrity of their patient data. For those EHR Data Architects, it is the process, not the EHR provider, that allows them to guarantee a successful conversion and data integrity. 

As is true with the initial adoption of electronic records, changing EHR providers is a very large project. As healthcare organizations work to convert legacy records and adopt new systems, patients continue to generate more data.

It can be quite challenging to determine the best method for maintaining and storing legacy date while also utilizing a new system. As a result, most healthcare organizations opt to incorporate legacy data into the new EHR system from day one. Out of the myriad of options available for guaranteeing data integrity, the best way to accomplish this is through an automated EHR data conversion.

What is EHR data conversion?

EHR data conversion utilizes a process known as ETL to move patient data from one EHR system to another. During an ETL conversion, patient data is EXTRACTED from the legacy system, TRANSFORMED to align with the map created for the new system, and LOADED into the new system. EHR data conversion can either be performed manually or through an automated process.

 

Manual data conversion carries a significant risk of data manipulation. As a result, many healthcare organizations choose automated EHR data conversion when working with large sets of data.

During an automated data conversion, not a single record is touched. Companies who specialize in healthcare data conversion utilize a failsafe ETL methodology specifically designed to mitigate clinical risk.

What are EHR Data Architects?

EHR Data Architects are the specialists who structure and run an automated data conversion. They are experts in extracting data out of any source system/database, using the necessary means specific to that system. EHR Data Architects have customized toolsets that allow them to transform the data to meet the specific needs of the target system.

An EHR Data Architect has experience working with all genres of data. The process and tools allow for the Data Architect to perform an ETL for data from any system and to any system. They ARE NOT specific system experts, or specialists, in any specific system's operations, usability, or recommended workflows.

While they are not subject matter experts (SMEs) in any EHR system, they are in the process of data conversion. As a result, they are able to successfully convert data no matter what systems are being utilized.

It is important that your data conversion partner has developed a failsafe process for extracting, transforming, and loading data. A strong partner will have experience in many different EHR systems and potentially have extensive experience working with your EHR provider and system. However, experience working with your EHR provider is not enough.

Without a failsafe process and methodology, your patient data is still at risk. Furthermore, when the right process is in place, an EHR Data Architect can convert from any source system to any target system and ensure the integrity of your data.

To learn more about how you can adequate assess a potential EHR data conversion partner’s experience, download the EHR Data Conversion Guide and Workbook.

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EHR Adoption: Benefits and Challenges

EHR Adoption: Benefits and Challenges | EHR and Health IT Consulting | Scoop.it

Electronic Health Records (EHRs) are rapidly becoming an integral component of any efficient healthcare system.  Professional doctors and hospitals are required to demonstrate the meaningful use of certified electronic medical records. Meaningful use criteria in this regard refers to capturing electronic health information in a standardized format, using this information to track key clinical conditions, putting in place a care coordination process, report clinical quality measures and public health information and to use this information to engage with patients and their families. More sophisticated systems would also have the capability of enabling health information exchange, incorporating lab results, e-prescribing, transmit patient care summaries across multiple settings, provide patients access to self-management tools and improve the overall population health.  

 

Approximately, 78.4% of office-based physicians use EHR systems while 48.1% of those work with a basic level EHR system. According to findings of a patient experience survey with EHR systems, it was reported that physicians with EHR systems that meet meaningful use criteria felt that it provided time savings and resulted in enhanced confidentiality and less disruption in doctor-patient interactions. In addition, properly implemented EHR systems also provided greater financial and clinical benefits as compared to basic systems.

 

It is important to remember that electronic health record systems are not a novelty. In one form or another, healthcare providers have been using EHRs for many decades. In the past, doctors used standalone workstations to store patient data. However, with advancement in information technology, data storage as moved to the cloud and has become more efficient, portable and rapidly transferable.  

Benefits

EHR systems have made the healthcare system more efficient in following ways:

 

−    Ability to transfer medical records across geographic borders, to another hospital or department. This enables access to complete and accurate information at the point of care.

−    Help improves patient management and engagement. With just a few clicks providers can not only access patient medical records anytime and anywhere but also coordinate care with their peers to improve the quality of care delivered.

−  Lower operational costs with less labor expense to maintain paper records and reduced need for transcription services. Once a medical record has been added in electronic format, it requires almost no management which directly impacts operational cost.

−   Safer and reliable workflows with EHRs to enable e-prescribing, laboratory, and X-RAY ordering and reporting. An efficient EHR-based workflow can reduce chances of error and eliminate lost records to deliver effective and safer care.

−  Enabled Increased patient engagement between patient and providers. Electronic records allow patients to participate in their own care and let provider-patient to work on delivering better patient care collectively.

Challenges

Even with these benefits, implementation of EHR systems has proven to be a significant challenge for healthcare organizations.

 

−  EHR adoption substantially increases the effort needed to manage the privacy and protection of the patient records. Over the years,  there have been numerous incidents of security breaches and stolen patient health information. Although, healthcare organizations invest heavily in creating secure and compliant solutions but securing and managing connected electronic records is a dynamic process and requires constant monitoring and auditing to track down threats and flaws before they happen.

−   Higher start-up and maintenance cost of transitioning to electronic medical records – larger the organization, greater the cost. Resource training, culture change, new workflows adoption and constant need for support make EHR adoption an intimidating task for any organization.  The higher start-up costs for smaller practices make it difficult for them to recoup.

−    Delivering education & continuous training on the usage of the EHR is another challenge faced by organizations. Healthcare staff needs to be trained for compliance, maintenance, confidentiality, and various workflows on effective use of the system. Without a proper training program, user do not understand the system completely which directly impacts the quality of care.

−   Perceived depersonalization of provider and patient relationship as providers feel that they are spending more time interacting with the computer than with the patient.

−   Extensive data capturing hampers the clinical workflows of physician. Not only data entry is both cumbersome and time-consuming but providers are also put-off by UI/UX to manage  their workflows. Although keeping everything electronic gives them an ability to remain connected to their patients but unnecessary alerts and notifications also create an alert fatigue on both patient and provider side.

 

While the general dissatisfaction remains with adoption of EHRs, the fact remains that addressing above mentioned challenges as per your organizational goals can definitely lead  better, coordinated and cost-effective care.

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The Limits on Healthcare Learning From the Business World 

The Limits on Healthcare Learning From the Business World  | EHR and Health IT Consulting | Scoop.it

A favorite criticism of EHRs is that they are glorified billing platforms, rather than clinical tools.

 

Despite being sold to — and subsequently, by — the federal government as being healthcare’s ticket into the modern age, and to leveraging big data, EHRs haven’t so far facilitated the kinds of analytics initially touted as the new standard in medicine.

 

Part of the shortfall in realizing the potential of EHRs may be fairly ascribed to overselling; new technology and new applications of existing technology tantalize imaginations. In an industry with as many challenges and problems to solve as healthcare, it is understandable that advocates got carried away with silver bullet thinking about EHRs and let development and implementation — not to mention security — fall behind.

 

But part of the problem is also an overextension of the analogy that what works for the business world, ought to also work for healthcare. Even outside of EHRs and questions of technology, the assertion that business leaders, models, systems, and tools have pedagogical value for healthcare leaders, and practical value for clinics, has become so popular that for many it sounds indistinguishable from conventional wisdom

That may have its merits, but the reality (all too familiar for those actually working in healthcare) is that business lessons very often don’t apply to the health sector.

 

Are EHRs Failing to Deliver Analytics?

When big data doesn’t work, it isn’t necessarily a failure of information, but a user error; a failure to properly organize information, or to ask the right questions of that information. In other words, big data doesn’t just happen by virtue of keeping digital records or even hiring data scientists to get things in order. There has to be a compelling use case, a specific goal associated with the data to turn raw information into something actionable. This is where business and healthcare diverge most dramatically.

The business use case for big data is, first and foremost, about competition. A forensic look at marketing initiatives, supply chains, tax planning, even compensation, all serves to make businesses more lean, more efficient, more profitable, and ultimately, more resilient in the face of stiff competition. McDonald’s managed it before “big data” was a buzzword, by simplifying its menu and streamlining its kitchen. Today, it is synonymous with “fast food” not because it is holistically the best, but because it led the pack in turning analysis into a competitive advantage. And it continues to use technology, analytics, and big data to further hone everything from sandwich assembly to locating new franchises around the world.

 

It should hardly require saying so, but healthcare has no McDonald’s model to follow.

 

Healthcare data analytics — carried on the backs of EHRs — are not necessarily intended to support competitive improvements or advantages. By and large, major clinics and hospitals have a virtual monopoly, if not geographically, then often in terms of insurance networks, or both. So the idea that competition drives innovation, optimization, or introspection is a non-starter.

 

The Profit Motive

Businesses are looking for improvement opportunities not just to aid the bottom line, but to boost profitability. The majority of clinics in the United States are, at least on paper, nonprofits (or government-operated). So in these hospitals, that “bottom line” under scrutiny by CEOs and data scientists often has more to do with volume, sustainability of operations, and especially coordinating with insurers in order to remain solvent.

Big data in business enables corporations to minimize the costs of their own operations, and to pass on some measure of savings to customers. That boosts profitability not just by making the cost of business lower, but by incenting consumers to buy more, or at least, to elect to buy from the optimized company. Everyone along the supply chain is looking for the best, for the least.

 

Healthcare is never so straightforward. Prices are hopelessly opaque in healthcare, and the relationship between the many stakeholders along the supply chain — from universities to providers, clinics to insurers, consumers to pharmaceutical companies — is all but impossible to optimize because there are so many different motives, inputs, and contradictions involved. People are looking for the best, but seldom have any way to judge quality, or have no access to competitive alternatives, or to balance quality with cost, or to hold anyone along the way accountable for quality or, for that matter, setting prices.

 

What this all amounts to is a limitation on the ability of healthcare organizations to make use of their data in the same way their business sector counterparts have been doing with any hope for success, insight, or actionable conclusions. That the finances of free market corporations and health systems are different is itself not an especially novel observation, but the fundamental difference of motivation extends further than price-setting and value-shopping.

 

Optimizing for Engagement

Although broadly similar, and often looked for in the data, the effect of “engagement” in a normal business setting is critically different from the sort of engagement providers and health systems are trying to achieve with patients.

 

Engagement in marketing is a matter of driving conversions; the more consumers hang out on your site or are exposed to your brand, the more likely they are to convert to buyers. This kind of engagement takes shape as funnel: get the widest possible audience to begin engaging, then optimize every node, webpage, or conversation to drive them all toward one destination: purchase.

In the business world, you see this driven by big data in the form of things like A/B testing to maximize webpage performance. Optimizing ecommerce or brand websites, targeting marketing messages, streamlining design for user experience and ease of navigation — it all funnels down to that old bottom line. When a given consumer’s experience seamlessly and pleasantly flows from landing on a website to buying a product or service, the engagement effort has worked. Engagement for business, in other words, is discrete.

 

Engagement in healthcare has a very different connotation, with extremely different end goals: engagement is about adherence, first and foremost. Getting patients engaged with their care is a function not of encouraging brand loyalty or making a sale, but of trying to optimize the value of the care they have already received. In other words, engagement after the sale is more important than leading up to the sale, because what happens after a visit to the hospital can be more critical to patient health than the limited encounter they have with providers.

 

In medicine, engagement is continuous, and more a matter of perpetual relationship-building, of exchanging feedback, than of driving everyone to one universal outcome. Individual patient health goals are unique; sales goals are easily generalized. A/B testing a patient portal may help improve general user experience, but the substance of a patient’s chart, or conversation with a provider, can’t be optimized the same way a product page can. While a specific retailer or brand can optimize experiences to their specific consumer demographic, healthcare organizations have the impossible challenge of optimizing all patient engagement pathways to anyone and everyone who needs medical attention.

 

Redesigning Health Data

The other example of A/B testing in healthcare, of course, is the control study for medications, new procedures, or determining best practices. This is where the real value, the maximum return on investment, from adopting EHRs should be sought. The big data EHRs deliver can only do so much to highlight wasted revenue, inefficiencies, or optimized patient experiences in the sense that the business world so often makes use of. But outside of the profit motive, or of engaging consumers to make a sale, big data in healthcare can begin to reveal population trends, problems with current standards, pathways of disease, and where health resources are needed most.

 

The best use case for data in healthcare is not a matter of competition as it is in the business world. It is a matter of learning, of monitoring populations not to take advantage of trends, but to anticipate and prevent disaster or outbreaks. The best use of the data is not presenting it to leadership or business-minded members of the C-suite, but making it accessible to the academic community, to researchers and scientists who can turn it into a competitive advantage against death and disease, rather than the marketplace.

 

Achieving this takes standardization, interoperability, and some amount of relief for providers feeling taxed by the need to play data scientist and doctor at the same time. All easier said than done; what’s worse, interoperability among legitimate and authorized users is lagging behind security failures and vulnerabilities across the healthcare industry. But progress can start with recognizing that EHRs don’t need more help from the business world to fulfill their promise. EHRs, like scalpels or stethoscopes, don’t belong in the boardroom, and their use and design is best left not to administrative types, but to medical professionals.

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Is an Automated EHR Data Conversion Right for You?

Is an Automated EHR Data Conversion Right for You? | EHR and Health IT Consulting | Scoop.it

EHR data conversion is the process of taking data from a legacy electronic health record system and transferring it to a new system. EHR data conversion can either be performed manually or through an automated process. Manual data conversion carries a significant risk of data manipulation. As a result, many healthcare organizations choose automated EHR data conversion when working with large sets of data.

 

Determining if an automated data conversion is right for your healthcare organization can be a difficult challenge. Below you will find the types of questions you should ask your in-house team when considering if an automated EHR data conversion fits your organization’s needs.

 

In an automated conversion, source values are extracted from both the legacy (source) system and new (target) system to create a conversion map. That map is entered into a conversion utility software. Data from the legacy system is run through the conversion utility and transformed to meet the needs of the new system. While it is being transformed, the conversion utility is monitoring for errors and success rates. After the data has met the standards, it is then loaded into the new system.

 

  • Have we acquired or do we plan to acquire facilities with disparate EHRs?
  • Are we going to continue to acquire new practices or hospitals?
  • Are we struggling with a plan for handling and storing the data?
  • Do our providers and staff function out of more than one system?
  • Does our EHR have capacity we are not using?
  • Does our legacy system require internal experts?
  • Do we have specialties, such as Obstetric Gynecology or Pediatrics, that are required to store data for longer periods of time?
  • Do we have more than 30,000 records we need to convert?

If you answered “yes” to any or all of these questions, an automated EHR data conversion might be a good fit for your healthcare organization.

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Preparing Health IT Infrastructure for Artificial Intelligence

Preparing Health IT Infrastructure for Artificial Intelligence | EHR and Health IT Consulting | Scoop.it

Artificial intelligence requires much health IT infrastructure planning to support the storage and computing power needed for a successful solution.

Artificial intelligence (AI) has been working itself into health IT infrastructure as organizations need more advanced technology to handle the growing amount of healthcare data.

 

As AI becomes more of a reality, organizations have to realistically work AI solutions into their IT infrastructure. This can be a challenging process because AI requires a significant amount of computing power and skills to manage the new layers of technology.

 

Organizations are finding that it’s challenging to integrate AI into their operational processes, according to a recent Tractica report.

Dig Deeper

  • How Artificial Intelligence Can Shape Health IT Infrastructure
  • Artificial Intelligence Uses EHRs as Smart Analytics Tools
  • Artificial Intelligence Adds Pressure to Health IT Networks

AI was created to emulate the human mind and working processes, and can independently solve problems without needing to be programmed to do so. AI can accept new information and learn from it without human intervention.

 

The computing power behind AI allows it to process information exponentially faster than a human could, fixing problems or drawing conclusions that the human mind would never be able to achieve.

 

“Enabling AI at the enterprise scale is not a plug-and-play proposition,” Tractica Principal Analyst Keith Kirkpatrick said in a statement. “Significant time, resources, and capital must be deployed, and in most cases, internal company teams are not experienced enough with AI, nor do they have the cutting-edge data science skills to adequately embark upon a truly transformational AI implementation.”

 

Entities need to decide how they’re going to handle the infrastructure changes needed to process and store data. Organizations must also find the staff needed to manage and monitor the AI solution.

 

AI is one of the more robust technologies that’s part of the digital transformation, and can be applied to analytics and cybersecurity.

Healthcare entities having a broad surface area is one of the biggest IT infrastructure security challenges facing organizations today. The wider surface area means there are more potentially vulnerable places cyberattackers can take advantage of.

 

With more ground to cover, IT security staff can be stretched thin and legacy network security systems might not be able to catch evolving security attacks.

 

Applying AI to cybersecurity solutions will help organizations find gaps in their security infrastructure and prevent future attacks.

AI is also used heavily in healthcare analytics. A computer with AI can look at an image of a healthy brain scan and an image of a brain scan with tumors. The device could then recognize the difference between the two images by breaking them down into machine-readable patterns.

 

The machine can remember and reference these patterns, then apply them to future images to determine which patterns indicate that a brain tumor is present.

 

Most healthcare organizations cannot afford to deploy an AI solution on-premises or have the space to accommodate the required hardware.

 

Cloud-based AI solutions and cloud storage are good options for healthcare organizations.

 

Cloud-based storage is a flexible storage solution, and often provides healthcare organizations with a more cost-effective storage strategy over traditional on-premise deployments.

When organizations begin to consider the future costs of scaling up based on the increased amount of data, budget concerns come to the forefront of the decision-making process.

 

On-premise storage solutions require organizations to purchase hardware and only offer a finite amount of space available before additional hardware needs to be added. Cloud services act as a utility with organizations paying monthly or yearly fees based on what they are using.

 

As organizations need more space, they scale up their cloud service requirements and increase payments accordingly.

AI is still a young technology when it comes to enterprise IT infrastructure implementation, but it is expected grow significantly worldwide over the next several years.

 

As healthcare organizations look to implement an AI solution in the near future, ensuring the organization’s health IT infrastructure can support it is key to deploying a successful AI analytics solution.

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Lessons Learned from EHR Integration of Medical Devices 

Lessons Learned from EHR Integration of Medical Devices  | EHR and Health IT Consulting | Scoop.it

Human lives depend on how well a healthcare organization manages its EHR integration of medical devices.

As the assigned project manager spearheading numerous large health system enterprise-wise medical device integration programs for over a decade, I’ve learned an essential lesson about EHR integration of medical devices.

Data captured from thousands of heart monitors, ventilators, balloon pumps, and other bedside devices must be perfectly managed, seamlessly integrated, and standardized to each patient’s electronic health record (EHR) and then made accessible to multiple providers. Once synced properly across the care continuum, connected medical devices play a critical role in the transfer of near real-time, reliable data to EHRs that improve both the safety and quality of patient care.

Otherwise, failing to do so can prove fatal.

Lessons borne out of experience

My role in bringing together clinicians, IT experts and device vendor representatives is to achieve that goal through flawless organization of precise integration methods and over-communication. Sharing information among these three teams is paramount to our success — that is, we’re managing vital data used by physicians and nurses as analytics in making life-changing medical decisions as quickly as possible.

Additionally, I have learned other valuable lessons about EHR integration of medical devices.

Start with a clean inventory list of biomedical devices and equipment planned for the device integration project. This list should comprise the number counts of all devices and supporting equipment including firmware versions and serial ports in addition to Ethernet gateway connections.

At the project’s onset evaluate and identify devices lacking the capability to integrate. Identify older firmware versions and research feasibility of cost to update as opposed to replacement.

Conduct walkthroughs on clinical rounds to determine data points for integration in order to identify network cabling and power needs. At that time, initiate engaging device vendors and setting clear deadlines and key parameters for the EHR integration.

Ensure middleware vendors partnering with the medical facilities supply all security-related product information upfront.

Invite middleware vendors to an onsite visit to determine exactly how much hardware is needed to ensure connectivity with other devices. Also include them in weekly or biweekly team update meetings. They are oftentimes overlooked.

Be adaptable and versatile to make quick adjustments while also striving to deliver impeccable results. Since workflows are not usually established upfront, responsibilities get shuffled around and integration details quickly become overwhelming.

Find creative ways to facilitate communication among the different team members. For example, assign color-coded status levels — green, yellow and red — to flag a change in project progression to speed up problem resolution. When senior management tackles red status issues as a group, expect people to pay attention!

Organization translates to project acceleration

Finally, organization of every integration detail is imperative. Associated device hardware, such as installing mounting hardware and new monitors in each patient room, must be managed. Biomedical managers, hospital IT groups, and clinical administrators must work concurrently to coordinate every step. In my experience, managing all of these different teams is by far the most challenging aspect of device integration.

Our healthcare ecosystem is slowly but surely modernizing, and we must leverage our technologies every possible way to maximize delivery of patient care to improve outcomes and the patient-provider experience. Ultimately, the success of any enterprise-wide EHR integration of medical devices is founded on strong communication and organization in addition to data management.

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EHR Training: How to Help Users End Frustration, Overcome Fear and Engage 

EHR Training: How to Help Users End Frustration, Overcome Fear and Engage  | EHR and Health IT Consulting | Scoop.it

During EHR implementations, trainers are frequently the first to introduce end-users to the new technology. Users often come to EHR training frustrated about the change and nervous about acclimating to a new system. Adding to the pressure they feel, EHR training may only entail a one-time training class that delivers an immense amount of information in a short period of time—unless the healthcare organization offers on-site interim training opportunities, users often never touch the EHR again until after go-live. Under those circumstances, trainee resistance and fear are understandable.

What I’ve discovered in my years as a trainer is that successful EHR adoption is not just about the technical training. The biggest part of my job is to give end-users encouragement and confidence that they will be able to adapt to the EHR even though they may forget some of what is taught during training. People learn the best when they feel personally engaged and know that the trainer cares about them. Trainers play a key role in promoting not only technical EHR know-how, but cultural buy-in.

Given the right training environment, EHR trainers can help healthcare organizations diffuse negativity and push-back while bringing end-users up to speed on new EHR workflows. A trainer’s ability to successfully empower users truly does come down to training delivery. Here are some of the best practices that I’ve cultivated over the years to help maximize staff acceptance of the EHR.

Little things matter when creating a welcoming learning environment. When EHR users come to class, stand by the door and greet them. Smile, ask trainees their name and introduce yourself. Don’t just sit behind the desk. Don’t underestimate the power of a smile to make people feel comfortable. Remind trainees that you are there as a resource for them.

Address end-user frustrations head-on. As part of class introductions, ask trainees to comment on how they are feeling about the EHR migration. If necessary, purge EHR transition angst and negativity by letting users briefly share how they feel at the very beginning of class. After that catharsis, implement a strict “no complaining” policy and start working to shift end-user thought patterns. I encourage users to change their internal talk track from one of resistance to one of acceptance.

Employ compassion and empathy to understand where end-users are coming from. Trainees may come to class with feelings of nervousness, fear and anxiety. This is particularly true among non-computer natives, who are pervasive in healthcare. I like to share my personal story of being hired to be a trainer based on my background as a speaker and a nurse, and having to learn the technical aspects of training along the way. Shared experience and understanding go a long way in establishing rapport.

Build a sense of safety and community among end-users. To avoid trainee feelings of inadequacy, I offer patience to those in the class and work to foster a growth mindset. In peer training settings, clinicians often feel they are expected to know everything. Actively work to make end-users feel comfortable asking questions. Remind them that just because they don’t know something yet does not mean they can’t learn it.

Create a different training environment than people expect. Infusing unanticipated elements into the training program can make it more memorable. I like to bring laughter to the training program because if people are laughing, they are learning. Humor can help diffuse tension and put people at ease.

Always opt for words of encouragement. Remind EHR trainees that they can all do it and they will succeed, regardless of age or technical aptitude. Point out that people often learn the same thing in very different ways and warn against comparing one’s learning speed to that of others. All end-users will inevitably forget a portion of what is covered in training but, with the right mindset, they will be able to learn it again.

I can’t say enough about the need for words of affirmation in healthcare. A lot is expected of staff members during an EHR implementation. The stress of training while managing the day-to-day work of patient engagement can be overwhelming. If nothing else, give them hope. We all feel the strain of change in healthcare and we could all use an encouraging word!

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Health IoT creates huge opportunities for public health and software companies 

Health IoT creates huge opportunities for public health and software companies  | EHR and Health IT Consulting | Scoop.it

It was evident from this year’s Consumer Electronics Show (CES) earlier this month that there’s a great deal of interest in the Internet of Things (IoT) in general and for Health IoT in particular. Given that interest I thought I would reach out to a couple of experts to help explore the IoT landscape. Murali Kurukunda is Director of IT and Lead Architect at Medecision and Dr. Peter L. Levin, is CEO at Amida, director of ConversaHealth, and a father of the BlueButton initiative (which he helped launch as CTO of VA). Murali and Peter (along with Medecision and Amida) are right in the middle of intersection of data, interoperability, hardware, software and services for IoT in healthcare; they were kind enough to share with me what they’re seeing as the major opportunities in the space.

 

Here’s what they think, in their own words:

 

Connecting smart biological sensors to the internet is not a new idea. There are already dozens of products in the market that continuously monitor blood glucose and heart function, for example, and enable secure remote management for clinicians and caretakers. The safety of life implications are enormous, and the commercial opportunities untold. Some analysts predict a $100 billion-plus market for the healthcare segment of the “internet of things” (IoT).


What is new and emerging is the physical scale of the devices on the one hand, and the need to aggregate, reconcile, and consolidate those data streams for downstream clinical care services. Advances in semiconductor device manufacturing will relentlessly drive down the price and the size of these electro-physiological sensors, literally to nanometer scale, which will ultimately be able to do more than detect, they will be able to intervene. At the same time, our ability to make sense of the torrents of information is catching up to our ability to create them.

We believe that these are tremendous opportunities for public health and software companies like ours. It is why we are investing so much of our own resources to promote the open design, secure exchange, and value-added analysis of health data systems. Perhaps the largest inhibitor to a promising future of longer, healthier, less expensive life are the software merchants and device manufacturers who still and astonishingly insist on keeping data closed, isolated, and trapped in proprietary systems. We believe this is about to change too.

 

The interoperability troubles with electronic medical records are legion, and we won’t waste our page space or your attention lamenting the deeply ignorant and the nearly criminal. The immortal words of Forest Gump’s assessment about doing dumb things finds purchase here.

 

What we can do, however, is find clever ways leverage of IoT as yet-another, and maybe decisive, fulcrum of connected care. For what is today true in isolation – progressive plans, concerned parents, engaged patients – will soon-enough be more the ubiquitous standard of coordinated care; that coordination will reach deeply into pocketbooks as well as bodies.

We know that there are legitimate concerns about individual privacy and device safety, and that some people would literally rather die than compromise on either. We respect that, even as we actively promote more automation and digital services in health care.

 

Some of us believe that the existential benefits of independence and longevity outweigh the potential risks of intrusion and malfunction, some of us don’t. The point is that everyone should have the choice, and that no one should be coerced or manipulated into choosing one side of the argument. Fear mongering (about privacy) and fabrication (about intrusion) are forms of manipulation. In the case of health care they cost lives and money.

 

Let’s, instead, imagine a world of seamless, secure, and reliable health data interoperability. Let’s find a better way to safely liberate data at its source – labs, pharmacies, hospital and clinics, insurance claims, as well as implantable and wearable devices – pass it through hygienically sealed pipes, and receive it in places where it does the most good. That may be during a clinical care or remote telemedical encounter (to give you the best possible advice based on evidence and your personal health history), it may be when you pick up your medicines (to check for interactions with other medicines), or it may be to help your insurance company help you (because they have always had a bird’s eye view of your services, and they can’t kick you out for pre-existing conditions anymore).

 

Because of changes in the law, it may be with a loved one or trusted caretaker. It may be you.

 

The data could be as simple as a reminder message about an upcoming appointment, a warning message that a clinical value seems out of range, or an answer to a securely-texted question to your doctor. We have imagined that future and it is, as Ray Kurzweil likes to say, near.

 

There are two challenges, and they are slowly receding.

 

The first is that the data holders are still reluctant to share, even though it isn’t “their” data.  This will become less of a problem, as forward-looking providers like VA and DoD have shown, as well as payers like CMS, Aetna, and HCSC among many others have demonstrated.  All are outspoken supporters of the Blue Button program, now in its fifth year, and still growing.

 

The second falls squarely on our shoulders:  we need to make the user experience attractive, convenient, and useful.  The health IT community has made terrific strides recently – we-two have worked on the InCircle and a soon-to-be announced medication management app, for example –  and there are many companies that target data-driven patient-provider interactions, including AmericanWell and ConversaHealth.

 

The beautiful thing is that IoT fits so neatly into this conversation. The goal, of course, is to help us achieve our best-possible health. The best way to do this is with data. And the best data is coming at us in ever more granular packages, from patient-hosted sensors that monitor, detect, interact, and intervene. Weaving those into the tapestry of your personal health history is the next vanguard of coordinated and managed care.

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6 Ways Health Informatics Is Transforming Health Care 

6 Ways Health Informatics Is Transforming Health Care  | EHR and Health IT Consulting | Scoop.it

The fact that technology is rapidly transforming health care should come as no surprise to anyone. From robotic arms that perform surgery tonanorobots that deliver drugs through the bloodstream, the days of being tended to by the human country doctor seem to have fully given way to machines and software more in keeping with the tools of Dr. McCoy from “Star Trek.”

 

However, technology’s evolutionary impact on health care isn’t all shooting stars and bells and whistles. Some of health care’s most important changes can slip beneath the radar due to their more pedestrian presentation, but that doesn’t mean they aren’t just as revolutionary as mini robots zipping through veins. Take the burgeoning field of health informatics, for example. A specialization that combines communications, information technology, and health care to improve patient care, it’s at the forefront of the current technological shift in medicine. Here are six ways it’s already transforming health care.

 

1. Dramatic Savings

Health care isn’t just expensive; it’s wasteful. It’s estimated that half of all medical expenditures are squandered on account of repeat procedures, the expenses associated with more traditional methods of sharing information, delays in care, errors in care or delivery, and the like. With an electronic and connected system in place, much of that waste can be curbed. From lab results that reach their destination sooner improving better an more timely care delivery to reduced malpractice claims, health informatics reduces errors, increases communication, and drives efficiency where before there was costly incompetence and obstruction.

 

2. Shared Knowledge

There’s a reason medicine is referred to as a “practice,” and it’s because health care providers are always learning more and honing their skills. Health informatics provides a way for knowledge about patients, diseases, therapies, medicines, and the like to be more easily shared. As knowledge is more readily passed back and forth between providers and patients, the practice of medicine gets better — something that aids everyone within the chain of care, from hospital administrators and physicians to pharmacists and patients.

 

3. Patient Participation

When patients have electronic access to their own health history and recommendations, it empowers them to take their role in their own health care more seriously. Patients who have access to care portals are able to educate themselves more effectively about their diagnoses and prognoses, while also keeping better track of medications and symptoms. They are also able to interact with doctors and nurses more easily, which yields better outcomes, as well. Health informatics allows individuals to feel like they are a valuable part of their own health care team, because they are.

 

4. The Impersonalization of Care

One criticism of approaching patient care through information and technology is that care is becoming less and less personal. Instead of a doctor getting to know a patient in real time and space in order to best offer care, the job of “knowing” is placed on data and algorithms.

 

As data is gathered regarding a patient, algorithms can be used to sort it in order to determine what is wrong and what care should be offered. It remains to be seen what effects this data-driven approach will have over time, but regardless, since care is getting less personal, having a valid and accurate record that the patient and his care providers can access remains vital.  

 

5. Increased Coordination

Health care is getting more and more specialized, which means most patients receive care from as many as a dozen different people in one hospital stay. This increase in specialists requires an increase in coordination, and it’s health informatics that provides the way forward. Pharmaceutical concerns, blood levels, nutrition, physical therapy, X-rays, discharge instructions — it’s astonishing how many different conversations a single patient may have with a team of people regarding care, and unless those conversations and efforts are made in tandem with one another, problems will arise and care will suffer. Health informatics makes the necessary

coordination possible.  

 

6. Improved Outcomes

The most important way in which informatics is changing health care is in improved outcomes. Electronic medical records result in higher quality care and safer care as coordinated teams provide better diagnoses and decrease the chance for errors. Doctors and nurses are able to increase efficiency, which frees up time to spend with patients, and previously manual jobs and tasks are automated, which saves time and money — not just for hospitals, clinics, and providers, but for patients, insurance companies, and state and federal governments, too.  

 

Health care is undergoing a massive renovation thanks to technology, and health informatics is helping to ensure that part of the change results in greater efficiency, coordination, and improved care.

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EHR and the Failure to Communicate

EHR and the Failure to Communicate | EHR and Health IT Consulting | Scoop.it

Clinical workflow in my early career included the ritual of phone messages. Every day, at least once and usually in the afternoon, I would sit with my clinic nurse and a pile of manila folders to discuss phone calls. Details were discussed, recommendations were made, triage assessments were cosigned and I would hold the charts of those patients needing a callback. The ritual began with the daily call to action, “Let’s do calls.”

EHR and the disruption of the nurse-doctor interaction

About 15 years ago when our first EHR, Logician (evolved as Centricity), came along the process of handling calls changed. It was Texas Children’s first venture into EHR and with it we began the long calculation of how electronic records fit our clinical flow.

My nurse at the time was a pediatric nurse with years of experience. Seasoned and crusty, her capacity for laser-sharp phone triage was impeccable. She was a stickler for tight documentation.

 

As we grew comfortable with Logician, the ritual of call review evolved. While we began doing calls around the screen, my nurse began to insist that our daily rendezvous was no longer necessary. “It's’ all in the message. Just read the message, Dr V,” she would crow from her cramped desk. “And the documentation is better. Trust me.” Despite my insistence, she ultimately became an unwilling partner in a clinical dance for two.

 

Our digital phone messages involved a back and forth of queries and replies through the EHR. Documentation was tight. But something was missing.

Not all media are created equal

When it comes to communication not all media are created equal. The assumption on the part of my nurse was that communication through the EHR was the same independent of how it was transmitted. A message, in the end, was just a message.

As it turns out, there are different ways for patients and health professionals to exchange information with one another. All bring different affordances to a human encounter.

 

  • In person (mano y mano)
  • Asynchronous text (Epic MyChart, email)
  • Synchronous text (Live texting)
  • video stream (Skype)
  • audio transmission (phone)
  • And there are lots more.

 

All represent ways for us to exchange health information. As I have written, different problems call for different media depending on the type of problem at hand. Text works well for simple problems. But the text isn’t always enough. A video is an overkill for simple issues. And as inconvenient as it may be for both the patient and the doctor, sometimes a patient needs to be seen, heard or touched in person.

The EHR and the subtle dimensions of the human experience

So when my nurse stopped talking to me about my understanding of what was happening with my kids fell off significantly. The notes were impeccable and the transmission instant. But something was missing.

 

So what was missing from the EHR? As it turns out in human exchange there are subtle elements that get lost in the type. There are critical bits of information during a phone exchange that get picked up by an experienced pediatric nurse. Often there are subtle contextual elements of a social situation that are never properly documented. Some of these things can’t be documented.

 

Sometimes these details only come to my attention when face-to-face with my staff. And there are things that come from the gut that we don’t share in the record.

 

Paper charts didn’t solve this problem with the EHR. Written messages are exactly the same. They just forced us to sit at a table because there was no way to send a paper message across the office and easily back again.

 

Humans are messy. They rarely fit the constraints of the technology we create. The dimensions of the human experience are rarely felt through typewritten messages. Consequently, the accurate exchange of information and documentation of human interaction is potentially more challenging than we think.

 

Communication through and around the electronic health record is an inevitable part of medical practice. But we have a long way to go with regard to capturing the subtle elements of human engagement.

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The future of EHRs - and it's not even in the EHR 

The future of EHRs - and it's not even in the EHR  | EHR and Health IT Consulting | Scoop.it

Voice recognition and natural language processing will enable doctors and nurses to interact with electronic health record platforms in more comfortable ways.

 

Along with a fistful of cutting-edge technologies, an interesting trend has begun to emerge that may help predict a direction forward for the way users interface with electronic health records.

Hint: It’s not in the EHR. Instead, emerging technologies such as ambient listening, voice assistants and natural language processing will provide a subtle buffer between EHR data and users. Clinicians will be able to access and contribute to data within electronic health records software or cloud services, in fact, without having to touch the EHR itself.

 

Let’s take a look at how this could play out.

EHRs today

As they have evolved, EHRs have also become more complicated and “busy.”  They require significant investment in training, both prior to adoption and ongoing as new features are released. 

Telling a primary care group back in 2000 that 6-8 hours of classroom training was required for every physician would have been the ultimate non-starter. Today, this is the norm and accepted as reasonable and it also holds true for the analysts who configure and support these systems of record.

 

Documentation requirements continue to increase, too. The push to document in a codified way has become more important in order to inform not only electronic decision support but also to support population health management initiatives and advanced data analytics. Plus, medical knowledge is eclipsing providers’ capabilities to internalize it and incorporate it into their practice.

So what does this point to?

Voice recognition, NLP and remote scribes

Providers have already begun to adopt technologies such as voice recognition and natural language processing that allow them to distance themselves from the complexities of the EHR.

Since a clinician is technically in the record while dictating via voice recognition, he or she is interacting with the system with a software buffer that the typist does not have.

 

A more pronounced example is the scribe. Far from a new idea, the scribe allows the provider to see the patient and remain fully focused on the task at hand while someone else does the documentation on their behalf.  While this comes with a certain level of awkwardness for the patient, it has been widely adopted in some clinical settings.

 

Natural language processing has been discussed in concept and used in pockets for many years. While loaded with potential and extremely appealing, it has yet to take off as a full-fledged documentation solution.

 

More innovative alternatives are also being explored. Remote scribes allow the transcriptionist to listen to the visit in real time and document as the provider speaks their way through the examination.  his may be implemented as an audio-only solution or with audio and video through the use of a tablet or some other video-enabled device in the exam room. Ambient devices are also being investigated as alternatives — pairing voice recognition with a mostly hands-free documentation experience minus the scribe. Google Glass is another interesting alternative. In this concept, the provider is not only dictating as they examine the patient but also visualizing elements of the record as they go without having to refer to a computer or tablet.

Tech challenges and costs

These novel technologies are not without challenges.  For the remote scribe model to be successful – especially in the case of audio-only – providers need to run through their visits in a common way for the process to be accurate and efficient. The scribe also must document the right information in the right place in the record. If they are merely typing a free text note – the value of the data is lost. Decision support is one of the most compelling reasons to use an EHR. How can the provider receive this guidance if they are not interacting directly with the system? A hybrid solution could solve for this – with the provider manually performing order entry and prescribing tasks. Alternatively, technology developers may come up with an innovative solution to address the requirement in the future.

 

Patient perception is also a concern. As with the traditional human scribe, patients may react negatively to the notion of a virtual third party participating in their visit. How can the patient be sure that only the identified third party is listening/watching? How can they be assured that the visit is not being recorded or shared? What type of consent is required and what details need to be shared with the patient in order for them to be aware of the process? What if the patient declines to participate in this type of visit?

 

Security, of course, will be paramount both for the patient and the hospital.  We all hear of major security breaches on a weekly basis. Executives and (increasingly) patients will need guarantees that these solutions are secure and insulated from the risks that come with the possibility of a data breach.

 

Traditionally the solutions that allow providers to document patient care without interacting with the record have been utilized mainly in the ambulatory, urgent care, and emergency department settings. Is there an option that would work for inpatient providers? Is there an option that would be suitable for nursing documentation? It may very well be that the answer is “no” and that these caregivers will continue to document directly in the record (either manually or with traditional voice recognition) for the foreseeable future.

Back to the future

There is, of course, a financial component to all this as well. Scribes and the more advanced technologies described are not inexpensive.  It will be up to technology developers and service providers to clearly articulate the return on investment.  It is noteworthy that some of that ROI will be difficult to quantify in terms of dollars or efficiency as it relates to provider happiness.

Even with all of these questions, it is clear that the trend of providers moving further away from direct interaction with the EHR is real and likely to continue. 

 

Ideally, EHR developers and regulatory agencies will see this as a challenge to simplify their products and documentation requirements. It’s possible that this is the push the industry needs to rethink usability and truly develop intuitive systems that are easy to learn and easy to use. This will require not only creativity and skill but also a willingness to rethink many of the constructs the industry has operated under for the last decade-plus.

 

It is more likely that the burgeoning trend will continue to progress and we will find ourselves in a “Back to Future” scenario where providers use the medical record to access information but harness various forms of new age dictation to keep it updated.

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5 Steps to EHR Data Conversion

5 Steps to EHR Data Conversion | EHR and Health IT Consulting | Scoop.it

EHR data conversion is the process of moving patient data from legacy EHR system to a new EHR system. While automated EHR data conversion seems like a complex affair, it doesn’t have to be. When an experienced vendor partners with strong internal leadership, the data conversion will follow a proven, 5-step process, and the data will undergo a failsafe ETL.

Why Change EHR?

Healthcare providers are expected to document patient encounters. Traditionally, this documentation has been completed on paper and stored in file cabinets. However, the last decade has seen significant growth in provider adoption of Electronic Health Records (EHRs). The combination of government incentives, advances in technology, and improved outcomes and operations have fueled this growth.

When healthcare providers have access to complete and accurate information, patients receive better care and have better outcomes. EHRs improve providers’ ability to diagnose disease and reduce medical errors. EHRs further help providers meet patient demands, provide decision support, improve communication, and aid in regulatory reporting.

While EHR adoption has increased, so too has the need to change systems while maintaining the access to and integrity of patient health information. Healthcare administrators point to provider dissatisfaction and mergers and acquisitions as the primary contributors for changing EHR providers within their organization. In preparing for the implementation of a new EHR, healthcare organizations have been grappling with how to handle the data in the legacy systems.

What is EHR Data Conversion?

In response to this challenge, many healthcare organizations are turning to automated EHR data conversion to maintain data integrity. An automated ETL (Extract, Transform, Load) process avoids risks related to data manipulation, because not a single patient record is touched.

 

In an automated conversion, source values are extracted from both the legacy (source) system and new (target) system to create a conversion map. That map is entered into a conversion utility software. Data from the legacy system is run through the conversion utility and transformed to meet the needs of the new system. While it is being transformed, the conversion utility is monitoring for errors and estimated completion. After the data has met the standards, it is then loaded into the new system.

The process of an automated EHR data conversion may seem like a complicated and difficult undertaking. It doesn’t have to be when it is handled by an experienced vendor working with strong internal leadershipundergoing a recognized data conversion process.

5 Steps to EHR Data Conversion

1. Discovery

During the discovery phase of the process, the healthcare organization team will play a large role. An EHR vendor will ask internal IT staff to extract all data from the current system. Working together with an internal designated leader, IT staff, and Physicians Advisory Committee (PAC), the data conversion vendor will work to identify how much data is available, what data needs to be converted, and the accuracy of the legacy data.

2. Scope Definition

The scope definition phase of the process is the point at which both parties come to an agreement on which portions of the data need to be converted, the method of the conversion, and the prioritization of the data. During this time, the two teams should schedule time to review the records, format them to meet the new formatting requirements, and set the processes to updated record fields not available in the conversion.

3. Testing

Once the scope has been fully defined, and the formatting requirements are completely understood, the primary responsibility of the conversion then shifts to the vendor. Based on the input gathered during the scope definition step, the data architects working for the vendor will map the data fields and formatting from the old system to equivalent data fields and formatting in the new systems. After the map has been created, the data architects upload the test conversion data to a testing site.

4. Validation

This step is a shared responsibility between the healthcare organization and EHR data conversion vendor. Once the data has been loaded to the test site, the data architects validate the data. Then the healthcare organization leaders review the content, validate the records, and sign off on the final data set. This step may require several cycles. However, it is imperative for the success of the conversion.

5. Migration

Once the data has been validated, the vendor will executive the final migration. While the data is migrating, the vendor’s conversion utility should be monitoring total errors, parsing errors, mapping misses, percent complete, date/time to finish, and success rate. When all the data is converted and migrated to the new system, the healthcare organization will go live!

Throughout the EHR data conversion process, healthcare organizations are tasked with making important, and often tough, decisions about how to handle data, the methods of conversion, and data prioritization. It is important that healthcare organizations plan ahead, schedule the necessary time, and work closely with EHR data conversion vendors who are well versed in the each step of the process.

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What Your Healthcare Organization Needs to Know About Measure Selection and EHR Configuration

What Your Healthcare Organization Needs to Know About Measure Selection and EHR Configuration | EHR and Health IT Consulting | Scoop.it

Participation in pay-for-performance plans like MACRA’s Quality Payment Program (QPP) poses new challenges for resource-strapped healthcare organizations. Many provider sites lack the time and technical expertise needed to retool their EHR implementation to document new metrics under value-based reimbursement models like the Merit-based Incentive Payment System (MIPS).

Nonetheless, that is precisely what clinicians must do to deliver on quality reporting requirements. When using EHR documentation tools, many factors must be considered for a provider to get credit on having met clinical quality measures (CQMs). How that information gets stored in the EHR directly affects reporting. Many healthcare organizations are finding that customizing an EHR to recognize when a measure has been met—preferably in a manner that poses as few interruptions to patient engagement as possible—is easier said than done.

 

Overcoming EHR Limitations

Many outpatient and inpatient settings still struggle with common EHR data management headaches. As clinicians bring new quality measures into the EHR, those underlying data management issues can foil even the best-laid reporting plans.

Discrete Data Capture

The push to better document clinical quality is causing a transition in EHRs to focus more on structured or discrete data that is easier to trend over time. Unfortunately, many healthcare providers still receive patient data from healthcare affiliates via fax. Those faxed documents show up as attachments in the patient chart and are not fully integrated into the patient data file. If that information was sent via HL7 interface instead, details on the care rendered by that hospital or other healthcare entity would flow into the EHR as discreet data variables. For many providers today, capturing that information in a manner that makes it usable in reporting and analytics still requires timely, manual data entry.

Documentation and Data Consistency

Provider sites with multiple clinicians may also encounter issues related to the slightly different way that each EHR user documents care. MIPS and other quality programs require consistency and a high degree of specificity in clinical documentation. If a clinician does not get diagnosis specifics into the patient chart, that patient may not be included in the CQM calculation they need to be included in. Many clinicians are having to modify their documentation process during patient encounters so they and the staff can capture all the necessary information in the EHR.

Clinical documentation will have even bigger repercussions under the Cost component of MIPS, which is slated to be factored into performance scores in coming years. Take, for example, a patient that is in for the flu. That patient has a certain anticipated cost impact (the average Medicare spending per beneficiary), calculated based on past medical history and services rendered. If a patient goes to a physician and has the flu but also has diabetes, heart failure, and asthma, that flu patient is probably going to cost more to care for. If the physician only submits the flu diagnosis and fails to document patient co-morbidities then the healthcare organization will not get the same allowance under the MIPS Cost category and could be labeled as “higher cost” than a comparable provider encounter for a patient that required fewer resources to care for.

Clinicians, coders, and staff need to make a mental transition away from “we’re submitting claims” to “we’re submitting data” to better serve clinical reporting initiatives and patient care analysis.

 

Making Informed CQM Selections

Beyond adapting to new data management processes, clinicians reporting under value-based programs also have a great deal to learn as they layer in additional quality measures under MACRA. One of the biggest challenges clinicians and administrators face is selecting the best measures for their specific healthcare organization. With limited spare time on their hands, many healthcare teams are leaning on outside expertise to help them evaluate the implications of various measure selections.

Measures Without Benchmarks

Many quality measures under MACRA are carry-overs or “relics” from other reporting programs. For these CQMs, providers can look to prior performance averages to evaluate the likelihood of success should the healthcare organization elect to report on those measures. That data does not exist for some CQMs, which are referred to as “measures without benchmarks.” On measures that have no benchmark data available, providers will be limited to a maximum of three reporting points instead of the ten points available on measures with benchmarks established.

To further complicate things, details on the availability of some benchmark data will not be calculated until after the March 2018 QPP reporting deadline. Providers may wish to further diversify or report on additional measures that could help offset low point earnings on measures without benchmarks.

Topped Out Measures

Another CQM caveat that providers should be aware of relates to “topped out” measures. These relic measures from other reporting programs are very engrained in many healthcare settings. Medication reconciliation, for example, was a requirement under Meaningful Use. Widespread adoption and universally high compliance rates on that measure makes it more difficult for clinicians to out-perform peers. Achieving maximum points on such measures requires a perfect or near-perfect score.

Keep average performance thresholds in mind when evaluating CQM selections, not just the healthcare entity’s individual performance track record. Look at a broader set of measures to maximize MIPS score potential. Clinicians could earn more points by scoring 70 percent on a non-topped out measure than they would earn scoring 95 percent on a topped out measure. Some topped out measures will likely be eliminated in future years to help diversify CQMs, as was the case under Meaningful Use.

Understanding the intricacies of CQM selection and EHR data management will be vital to success under value-based payment programs. Healthcare administrators and clinicians who proactively work to better understand the impact of various measures and streamline EHR processes will be best positioned to maximize program incentives.

 

Does your organization have the resources it needs to successfully navigate MIPS? Learn how Pivot Point can help with your value-based strategy.

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Tips for Fixing a Botched EHR Implementation

Tips for Fixing a Botched EHR Implementation | EHR and Health IT Consulting | Scoop.it

Organizations face many challenges when implementing electronic health records platforms (EHR), but fixing a botched implementation can be among the most stressful.  Problems with EHR implementation can reverberate throughout a healthcare organization and must be recognized and fixed as soon as possible.

The first step of a successful remedy is to create an action plan that prioritizes the fixes that will have the most immediate impact in helping operations return to optimal performance. Once those pressing problems are solved, it’s time to address all of the other issues. Here are a few useful tips to help guide you through that process.

Establish A Task Force

It’s wise to establish a task force to deal with each particular problem. The task force should include members whose specialties overlap with the problem area. For example, someone directly involved with the revenue side should be involved with resolving all revenue issues.

The task force should closely analyze the problem, and look for the breakdowns in the system. One might start by looking at whether staff members are able to input data. If so, check to see where it ends up. By taking a systematic approach, the task force will be able to get to the root of the problem more efficiently.

Carefully Calibrate Staffing

It’s quite common for healthcare organizations to wonder whether outside resources should be brought in to help rectify problematic EHR implementations. There are a couple of different approaches that work quite well.

[Related: How “The RightFit” Process Guarantees You’ll Get the Best Quality Consultants]

One option is to remove the appropriate internal staff from their normal day-to-day duties and have them focus exclusively on fixing the EHR platform issues (staff augmentation). Outside resources would then be brought in to handle the day-to-day responsibilities of those internal staff resources until the issues are resolved and they can resume their normal duties.

Another option is to bring in third-party consultants to solve the EHR application problems and allow the internal staff resources to continue concentrating on their normal day-to-day duties.

Which option is better depends on a variety of factors, including the size of the organization, the nature of the EHR problems, and the level of expertise the internal staff resources have in regards to the EHR platform.

Ensure Sufficient Resources and Track Progress

It’s important to engage key stakeholders throughout this process. The financial side of the organization must be included in the decision-making, so that adequate support can be provided to execute the fixes. To help build trust with the financial side, it’s imperative to establish metrics for success. This not only serves to prove the business case for the implementation fixes, but also ensures the project stays on track throughout the process.

Engage with End Users

In a situation in which the EHR solution is not performing as expected, perhaps the most vital tip is maintaining some degree of buy-in among the clinicians and staff who use the application on a daily basis. It’s essential to work closely with key stakeholders and influencers, like the chief medical officer, the nursing leadership, and even the financial department to ensure that everyone is on the same page. Have them propagate the message that the problems are being worked on and will soon be fixed.

After a botched implementation, IT staff might encounter a lot of resistance, but it’s important to break through this and emphasize what the long terms benefits of the EHR project will be once it is done correctly. By making these benefits clearer, it will become easier to keep everyone on board during a period of difficulty.

By following these EHR best practices, organizations will be able to more effectively overcome botched implementations, and will be better situated to have more success once they start on their EHR optimization projects.

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Digital Health Funding On The Rise

Digital Health Funding On The Rise | EHR and Health IT Consulting | Scoop.it

The digital health industry is continuing its growth in record-breaking ways, as funding to the industry pushed past $6.5 billion in the first half of 2017, according to a recent report by StartUp Health. This year’s numbers are already well on their way to overtaking the annual totals of previous years.

 

As the digital health industry has continued to mature, interest from new investors has likewise grown. This was noted in Rock Health’s comprehensive Digital Health Funding 2017 Midyear Review, a report that analyzed US deals disclosed at over $2 million during Q1 and Q2.

 

Pull factors, such as (but certainly not limited to) Apple’s not-so-secret work on diabetes health tech, have contributed to investors seeing the industry as a more attractive, tangible marketplace. More investors are interested in the industry, and more importantly, they’re investing much more on average: seven out of the top ten deals this year so far have involved over $100 million each. Outcome Health, the company that set the largest digital health deal on record, came out with $500 million in funding earlier this year.

 

The widely accepted reality is that the health industry is taking an inevitable shift towards digital health aids. And as digital health technology advances, their use becomes more widespread, with hundreds of millions of potential users in some cases. Belief in this potential can be seen in this year’s top deals in digital health. As the health industry continues its transition towards digital health aids, and as digital health companies continue to develop pertinent, breakthrough technology, the industry is poised to continue its growth undeterred.

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How to Get More Loyal Patients

How to Get More Loyal Patients | EHR and Health IT Consulting | Scoop.it

The success of your practice is dependent on your patients. The more loyal patients you have, the better your practice’s growth. But good treatment alone is not sufficient. For loyalty, you need to build an emotional connection with your patients that makes them feel valued and cared about.

Establishing an emotional connection helps patients remain stress-free, adhere to your advice and talk about their health issues honestly. Let’s see the possible ways to create a connection with your patients when they visit your practice and after they leave.

During visit to practice

Stay calm: Off course, you have a very limited time of 15 minutes for face-to-face interaction with your patient. Being in a rush and showing impatience would look awful. Instead, you should stay calm and make your patient feel relaxed with a warm handshake or a pat on the shoulder.

Be empathic: You need to offer an empathic response, especially when discussing life-threatening diagnoses. Likely the response of patients get better and descriptive. You and your team need to develop empathy skills. Also, make conversation with patients; don’t conduct an interrogation. Along with health issues, discuss different subjects such as pets, celebrations, etc. that makes them feel comfortable and more like they’re talking to a friend. Be an active listener. It gives your patient silent support. Instead of looking at your watch or a laptop screen, nod in agreement to what your patient says. For emotional connection, it is necessary to listen to your patients, express empathy and offer personal warmth.

Follow-up plans

To ensure loyalty, you need to make efforts to stay in touch with your patients after their visit to your practice. This makes them feel cared for.

Emailer: Email is one of the best marketing mediums to interact with your patients. Connect by sharing health-related newsletters that focus on patient ailments or general health issues. Don’t send out the same mailer to everyone; rather, use segmentation. Craft each mailer to focus on a set of people based on age, gender, geography or ailment. Also, keep your newsletter crisp and concise instead of publishing long stories.

To get more leads, put a call to action (CTA) button at the top. Another major characteristic of a successful mailer is a catchy subject line. Set regular intervals for email campaigns. Too many mailers can get you dumped in the spammer list, but too few mailers can make you lose potential patients.

Social media: Another way to connect with your existing patients and potential ones is via social media platforms. So you need to stay active on your social media accounts. Follow a trend in your posts such as daily posts, weekly posts, etc. Showcase your thought leader personality by sharing your blog posts or webinars. You can send appointment reminders or general health tips via social media channels such as Facebook, Twitter, etc.

Website: Your website should have a patient portal where they can post their question, check their appointment schedule, view their test reports and much more. This is a kind of communication initiator that helps you connect better with your patients.

Seminars: Last but not least, participate in local healthcare campaigns and seminars to get involve with people living around you. Participate in school and college health camps. These places help you to interact with more people and showcase your skills and knowledge to your potential patients.

A connection is necessary for building any relationship. The better connections you have with your patients, the stronger your relationships will be. Subsequently, they will do word-of-mouth marketing for you, thereby building your practice.

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EHR Optimization as a Bridge to Population Health Management 

EHR Optimization as a Bridge to Population Health Management  | EHR and Health IT Consulting | Scoop.it

In the quest to meet value-based care, population health and quality reporting goals, healthcare leaders face an array of avenues and tactics. While the strategies differ, one constant in virtually all efforts to bring structure to new care delivery models is the improved use of technology and systems, and the troves of data they store and transmit.

 

Analytics has a pivotal role in meeting healthcare’s triple aim of reducing the per capita cost of care, improving patient experience (including quality and satisfaction) and improving population health. Without the support of the clinicians using these technologies and the information they hold, however, it is difficult to succeed. This has prompted some healthcare organizations to champion a quadruple aim that also seeks to improve the work life of healthcare providers.

 

To develop and execute on a quadruple – or even triple aim – healthcare leadership teams must answer the question:

How can our organization capture the information needed to deliver effective, data-driven care in a manner that benefits patient outcomes and compliments provider workflows?

Through a disciplined EHR optimization methodology, a structured plan, and input from providers and clinicians on goals and practical ways to meet those goals, it is possible to adopt a data-capture care strategy that minimizes impact on provider workflow while maximizing return on reimbursement.

 

Optimization in Action
Consider how EHR Optimization can aid population health management efforts.

 

Many healthcare organizations are analyzing patient data to identify high-risk and/or high-utilization patient populations that could pose savings opportunities if their care interventions are migrated from high-cost emergency department and inpatient settings to preventive and primary care, but how many are truly looking up-stream at how the configuration and use of the EHR impacts their success?

 

When developing and deploying an organization’s population health goals and identifying target patient populations, consider how your organization can engage and support your clinicians in this evolution. What clinical workflow supportive functionality is available in your EHR to aid and prompt care team members to ask the right patients the right questions, proactively screen, and implement low-cost interventions to quickly put population health management into action?  How can these opportunities be implemented without disruption of patient care flow?

 

Here are specific strategies for building an EHR Optimization plan targeted toward enabling population health while supporting your providers:

  • Engage your clinicians early on. Including your providers and allowing them to tell you how they work and what will work for them to support your effort makes a successful initiative.
  • Integrate with established workflows when possible. Data entered correctly into your EHR supports your analytics needs. You will depend upon your providers to capture this for you.
  • Prioritize your target patient populations. Which initiatives will yield the highest return? Start with a single impactful goal and fine tune processes, measurement and engagement around it.
  • Ensure consistency in design. Provide consistency in data standards and naming conventions. This can go a long way to eliminate redundancy in documentation for clinicians. This is particularly important when planning to expand your program

EHRs and supporting technologies are an incredible data source and the key to value-based care and population health management success. EHR implementation and optimization strategies that keep the quadruple-aim top-of-mind can support organizational initiatives while enhancing, or at very least not burdening, clinical workflows of your EHR users.  Engaging your end users in the process inspires a collaborative, supportive environment while encouraging a successful outcome to organizational directives.

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Lessons Learned from EHR Integration of Medical Devices

Lessons Learned from EHR Integration of Medical Devices | EHR and Health IT Consulting | Scoop.it

Human lives depend on how well a healthcare organization manages its EHR integration of medical devices.

The assigned project manager spearheading numerous large health system enterprise-wise medical device integration programs for over a decade, I’ve learned an essential lesson about EHR integration of medical devices.

 

Data captured from thousands of heart monitors, ventilators, balloon pumps, and other bedside devices must be perfectly managed, seamlessly integrated, and standardized to each patient’s electronic health record (EHR) and then made accessible to multiple providers. Once synced properly across the care continuum, connected medical devices play a critical role in the transfer of near real-time, reliable data to EHRs that improve both the safety and quality of patient care.

Otherwise, failing to do so can prove fatal.

Lessons borne out of experience

Dig Deeper

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My role in bringing together clinicians, IT experts and device vendor representatives is to achieve that goal through flawless organization of precise integration methods and over-communication. Sharing information among these three teams is paramount to our success — that is, we’re managing vital data used by physicians and nurses as analytics in making life-changing medical decisions as quickly as possible.

Additionally, I have learned other valuable lessons about EHR integration of medical devices.

 

Start with a clean inventory list of biomedical devices and equipment planned for the device integration project. This list should comprise the number counts of all devices and supporting equipment including firmware versions and serial ports in addition to Ethernet gateway connections.

 

At the project’s onset evaluate and identify devices lacking the capability to integrate. Identify older firmware versions and research feasibility of cost to update as opposed to replacement.

Conduct walkthroughs on clinical rounds to determine data points for integration in order to identify network cabling and power needs. At that time, initiate engaging device vendors and setting clear deadlines and key parameters for the EHR integration.

Ensure middleware vendors partnering with the medical facilities supply all security-related product information upfront.

Invite middleware vendors to an onsite visit to determine exactly how much hardware is needed to ensure connectivity with other devices. Also include them in weekly or biweekly team update meetings. They are oftentimes overlooked.

 

Be adaptable and versatile to make quick adjustments while also striving to deliver impeccable results. Since workflows are not usually established upfront, responsibilities get shuffled around and integration details quickly become overwhelming.

Find creative ways to facilitate communication among the different team members. For example, assign color-coded status levels — green, yellow and red — to flag a change in project progression to speed up problem resolution. When senior management tackles red status issues as a group, expect people to pay attention!

 

Organization translates to project acceleration

Finally, organization of every integration detail is imperative. Associated device hardware, such as installing mounting hardware and new monitors in each patient room, must be managed. Biomedical managers, hospital IT groups, and clinical administrators must work concurrently to coordinate every step. In my experience, managing all of these different teams is by far the most challenging aspect of device integration.

 

Our healthcare ecosystem is slowly but surely modernizing, and we must leverage our technologies every possible way to maximize delivery of patient care to improve outcomes and the patient-provider experience. Ultimately, the success of any enterprise-wide EHR integration of medical devices is founded on strong communication and organization in addition to data management.

 

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8 Best Practices for Building Better Relationships During EHR Implementation and Training 

8 Best Practices for Building Better Relationships During EHR Implementation and Training  | EHR and Health IT Consulting | Scoop.it

New software implementations can be a high-stress scenario in the hectic and sometimes change-averse world of healthcare. End users are under pressure to adapt to new resources while continuing to tend to the high-stakes business of patient care. Instilling confidence in users’ ability to make thorough and efficient use of new technology plays a big role in successful tech adoption. Comfort with new tools is particularly important in patient-facing roles like scheduling where staff frustration can negatively influence a patient’s first impression of the facility.

 

As EHR consultants, project managers and trainers, one of our primary goals is to engage and encourage end-users during software transitions. We lead the charge to get projects done on time and under budget without having official authority over team members within the client organization. Throughout my years working as an Epic principal trainer one thing has consistently helped me garner buy-in with project teams: building good relationships.

Good relationships with stakeholders play a pivotal role in maintaining project momentum and getting through the inevitable stress points that arise during implementation. Here are some best practices to keep in mind to put your best foot forward when building relationships with clients and end-users.

Make communication a key priority. Make sure everyone clearly understands the objective of the project and the overall plan up front to set the tone and establish team buy-in. Demonstrate that leadership is on board.

Address team expectations openly and honestly. Clearly define the expectations you have of people involved in the project. Identify and articulate specific deliverables and due dates. Meet on a weekly basis to review plans, get progress updates and identify risks that may have cropped up. Maintain a living document that changes with every meeting.

Encourage team members to take ownership. No one likes a know-it-all. One tactic I use even when I know the answer to a problem is to pose a probing question to the team and let the group come up with the solution themselves. This boosts staff confidence, helps team members feel they are contributing and keeps you from having to micromanage.

Build trust with project staff. Teams want leaders who will act as a voice for end-users. Spend at least a couple of hours with team members each week to get to know them, their pain points and their motivators. Walk throughs offer great opportunities for engagement.

Honor individuality. Don’t expect individuals to change who they are to fit the culture of the team. Some people, for example, work better independently. Recognize that and let them go. Refrain from forcing end users too far out of their comfort zone to avoid unnecessary friction.

Leverage rewards and recognition. Make it a point to celebrate staff accomplishments big and small. Peer recognition can be a strong motivator, but not all people appreciate public acknowledgement. Different rewards work for different people. Find the trigger that works for that individual. Small things like taking people to lunch can help you celebrate achievements and further develop relationships.

Make team participation fun. Humor can help diffuse project resistance and apprehension. Open presentations with a cartoon to bring fun to team meetings. During stressful times, a cartoon slide that acknowledges the pressure staff members may be facing can remind end users that they are not alone.

Invite end user feedback. Feedback loops help project managers and trainers continually get better. All EHR trainers and classes should be evaluated by end-users. This helps reveal improvement opportunities for future client projects.

At the end of the day, EHR training is not about you and how much you know. It is about making sure that users get what they need out of class. Don’t overflood their minds on day one. Demonstrate patience as staff members acclimate. Remember that relationship building and team engagement is a great way to not only share your knowledge but to learn from others as well.

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Adopting Electronic Health Records

Adopting Electronic Health Records | EHR and Health IT Consulting | Scoop.it

Solo and small-practice physicians and dentists have had the lowest rate of the adoption of Electronic Health Records (EHRs), in which over 50% of physicians who had not adopted an EHR cited financial difficulties as the main reason for not participating in the nation-wide push towards the goals set forth in the American Recovery and Reinvestment Act of 2009 (ARRA of 2009). Understanding the difficulties for small practices to invest in new technology and to adhere to new standards, the Federal Government set aside billions of dollars to award to physicians and dentists to help them achieve the goal of “interoperability”; which can only be reached if all health care professionals are using certified EHR systems.

 

The EHR Incentive Program is grant-like funding available to help off-set the cost of acquiring a certified EHR. Well over 1.3 billion dollars has already been distributed to physicians, dentists and other eligible professionals that chose to participate in the EHR Incentive Program. Each eligible professional that qualifies and applies for funding through the program receives $21,250 for their first year, and can receive up to $63,750 over the course of the 6-year program.

 

The goal of the EHR Incentive Program is to provide the financial means, especially for small practices, to meet the national goal of interoperability through the use of certified EHRs. Not only is a significant financial benefit offered for qualifying professionals, but EHRs themselves are designed to protect and expand the bottom line. EHRs are specifically designed to save you money and time- which is also money- and to encourage patient health with comprehensive digital records, prevention, drug interaction warnings, appointment reminders via text and e-mail as well as numerous additional benefits of advancing technologies embedded into EHRs.

 

Don’t miss your opportunity to get paid to save money and join the new age of health care. Let EHR Funding see if you qualify for Incentive Funding at no cost.

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Philips Launches EHR-Integrated Patient Monitoring Solution for Clinicians

Philips Launches EHR-Integrated Patient Monitoring Solution for Clinicians | EHR and Health IT Consulting | Scoop.it

Philips has announced the launch of their next-generation Patient Monitoring solution, an enterprise-wide system that consists of bedside, transport, mobile and central station monitoring technology backed by a new approach of consulting, training, service and customer support.

Helping Clinicians Improve Patient Care

When patients are admitted to the hospital, they are frequently transferred between departments, which can make it difficult for clinicians to obtain complete data from monitoring systems that operate independently of one another. Incomplete data not only limits clinicians’ view into the patient’s condition, but can put a patient’s safety at risk. In a recent Philips-sponsored study, results revealed patient safety is still a top concern for physician and nurse leaders in the U.S.

In an effort to alleviate this concern, Philips designed this solution to help clinicians improve patient care, drive clinical performance and assist health systems in lowering costs, by harmonizing monitoring system updates and improved service agreements.

IntelliVue X3 Patient Monitor

The IntelliVue X3 is a highly portable, dual-purpose monitor with intuitive smart-phone-style operation. With this monitor, there is no need for caregivers to change patient cables during transport or at bedside, allowing them to spend less time dealing with equipment and more time caring for the patient. With alarm fatigue a top concern for healthcare professionals, the Patient Monitoring solution also includes IntelliVue bedside monitors with Alarm Advisor, a tool that tracks how clinicians respond to alarms and alerts them when set thresholds may be too sensitive.

EHR-Integrated Patient Monitoring

As a comprehensive system, the Patient Monitoring solution captures a steady stream of detailed patient data from monitors and medical devices, and feeds it securely to the hospital’s EMR for virtually gap-free patient records from admission to discharge, even during transport. The integrated solution fits securely into health systems’ existing IT environment, delivering vital signs, waveforms and alarms directly to caregivers.

By incorporating these clinical decision support tools and advanced algorithms, caregivers have better visibility into a patient’s changing condition. All Philips bedside, transport, and mobile monitors share the same look, feel, and interface for consistency and to reduce complexity, accelerate care, making it easier for clinicians to provide the best quality care throughout patients’ transports around the hospital.

Technical Dr. Inc.'s insight:
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inquiry@technicaldr.com or 877-910-0004
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