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Readers Write: How Hard Is It?

November 15, 2017 Readers Write No Comments

How Hard Is It?
By Frank Poggio


Frank Poggio is president and CEO of The Kelzon Group.

In the October 28, 2017 issue of HIStalk, Mr. H made this critical observation and raised an important question. He wrote (finishing with tongue in cheek):

For those with short memories or short healthcare IT careers, it’s time to relearn the oft-repeated lesson that big companies dip their toes into and out of the healthcare IT waters all the time with little loyalty to anyone except shareholders. McKesson bailed out this year and now GE is apparently mulling its exit after wrecking a slew of acquisitions over many years. Siemens is long gone. Nothing good ever comes from conglomerates licking their chops at what they naively think is easy money and higher growth than their other verticals (see also: Misys and Sage). How hard could this healthcare thing be?

GE of course isn’t alone, but they may hold the prize for most kicks at the can. This will be their third time since 1970 — three tries and billons later and nothing to show for it. Ironically, GE has had great success in medical devices, so one could assume they know more about the healthcare business than a Revlon, Apple, IBM, NCR, Martin Marietta, Lockheed, Oracle, SAP, Microsoft, et al.

After some 45 years working in the healthcare IT arena, I believe I have the answer to Mr. H’s query. My qualifications in support of my response are:

  • Over four decades, I was a hospital CFO and CIO at a major teaching hospital.
  • I spent two intermittent decades as an industry consultant working with healthcare providers and system vendors of all sizes.
  • In the middle of my career, after my CIO stint, I founded a HIT startup that built both clinical and administrative systems, went public, and was later acquired by one of today’s major vendors.
  • Most importantly, I have designed clinical and administrative software systems, led installations, and written more than my share of program code.

To summarize, I have seen it from all four sides; buyer, builder, advisor, and patient.

There are four reasons that make healthcare IT hard, really hard.

Organizational Structure

Many people new to the healthcare readily compare it to commercial industry. Why can’t hospitals do as banks, or airlines, or Google, or…?

One reason is they are not organized like these entities. What other industry has as its primary customer the same person that sells and then performs the core services? That same person also defines the product and further determines how it is delivered and implemented. That person is the doctor. The PhDs at GE do not make the final decision on how to make a jet engine or how to deliver it. GE is run by a CEO and the buck stops there. Hospitals are run by a troika (or committee) of the board, the administrative CEO, and the chief medical officer.

In 1974, Professor William Dowling, University of Washington, published the book “Prospective Reimbursement for Hospitals,” which did research on hospital operations. His studies showed that the CEO of a typical community hospital directly controls only 25 percent of the resources and operations. The other 75 percent is controlled by the doctors. They decide what tests to run, when to run them, and what happens next. The fastest way for a CEO to lose his job is to directly challenge the medical staff.

What other industry is organized like this? If you are in the business trying to build and sell million-dollar systems, you had better understand this organizational dynamic and accept the fact it will take years to generate an acceptable return on investment.

Regulatory Quagmire

All businesses are struggling with regulation. I submit that healthcare far exceeds all others.

Case in point: in what other industry does the payer define the structure and content of the bill down to the very last data element? One that comes closest is the defense industry, and many of its idiosyncrasies are incorporated in healthcare regulations. In 1999, Price Waterhouse CPAs completed an analysis of how many pages in the federal register addressed income tax laws. They compared income tax against the number of regulatory pages need to create a payable UB bill for all payers in a given state. The results were 11,000 pages of regulations for taxes and over 50,000 for a hospital bill.

A further complication is the person receiving the care is not the one paying the bill. Sometimes the patient never sees the full bill, and when they do, they are inevitably confused.

Training, Structure, and Definition

Computer systems thrive on definition and structure. The easiest applications to develop are those where the target domain has a history and library of definition and structure. Lack of definition and structure are a programmer’s nightmare. Today there are many tools to help address gray areas, such a fuzzy logic and neural networks, yet learning and applying these tools significantly raises the complexity of the system, thereby increasing development time and costs.

A doctor’s adherence to medical terminology and structure is highly dependent on which medical school they attended. As an example, a study at the Milken Institute SPH at George Washington University found that physicians whose residencies were in higher-spending regions spent 29 percent more on average than their peers who had trained in lower-spending areas of the country. Different protocols for different regions based on training. The federal government spent $30 billion on EMRs and yet we still have wide gaps in medical lexicons, protocols, and the structure and content of EMRs.

Moving Targets

In IT, this is classically called a rolling design, again a developer’s nightmare. But the delivery of healthcare and the practice of medicine are rife with this burden. Medicine is in constant change, with new protocols, test procedures, quality measures, etc. presented every week. Old protocols are challenged on a routine basis, e.g., mammography screening, PSA testing, knee replacements, tonsillectomies, and more.

What if you were assigned to develop a production management system for an auto manufacturer and every month the manufacturing engineers told you that process A — which we coded last month — has now changed to process B? The solution in commercial industry is to freeze the design by freezing the process. Can’t do that in medicine — freeze your protocol and tomorrow it could be the basis of a malpractice suit.

Medicine has always been in constant change, and with personalized medicine around the corner, variation and complexity will grow by leaps and bounds. Scientists have been trying to reverse engineer the human body since the first autopsy a thousand years ago. If only when you were born your mother gave you a 5,000-page human spec sheet with schematics and diagrams, a user’s manual, a troubleshooting guide, and a 1-800 number to call when all else fails. They exist for every car, dishwasher, plane, and other device and sure make software development a lot easier.

When I was a CIO at the end of a difficult IT implementation, the dean of our medical school said to me, “There is a reason we called it the practice of medicine. If we practice long and hard enough, someday we’ll get it right.”

Many of these issues exist in other industries and disciplines. I submit that the depth and interaction to which they exist in medicine and healthcare is what makes IT development hard, very, very hard. All those big companies (and many small) that came into the healthcare industry failed because they did not allow for the depth and interaction of these challenges, and hence they did not prepare for them, lost patience and millions, then chose to cut their losses and run.

From the outside looking in, healthcare is twenty percent of the gross national product, which could support a very attractive business opportunity. It’s a beguiling number which has proved to be siren song for many a big and small firm.

Readers Write: Six Myths Debunked: The True Significance of Social Determinants of Health

November 15, 2017 Readers Write No Comments

Six Myths Debunked: The True Significance of Social Determinants of Health
By Erin Benson


Erin Benson is director of market planning with LexisNexis Health Care of Alpharetta, GA.

Predicting future health risks has always been important, but the ongoing move toward value-based care and the emphasis placed on health outcomes is driving the need for greater prognostic accuracy.

At least 25 cents of every healthcare dollar goes toward the treatment of diseases or disabilities that result from potentially changeable behavior. If you can identify risk factors in patients, you can potentially intervene and initiate change. That’s where social determinants of health come in, but first it’s important to separate the myths from the truth.

Myth #1: Adding socioeconomic data to the patient file causes information overload and makes it difficult for providers to zero in on what’s important and relevant.

Medical care determines only 20 percent of overall health, while social, economic, and environmental factors determine 50 percent, making them too significant to ignore. The National Quality Forum, Centers for Disease Control, and World Health Organization have all acknowledged the importance of socioeconomic data.

Incorporating the data into existing workflows and integrating it with electronic health record (EHR) systems makes risk assessment more efficient, not time-consuming. A Socioeconomic Health Score, for example, can provide an immediate picture of unforeseen and avoidable risks. It can then drive informed decisions regarding that patient’s care, as well as offer opportunities for patient-provider discussions about lifestyle.

Myth #2: Social determinants of health include everything related to a person’s lifestyle, environment, situation, and behaviors.

Only certain types of data have been clinically validated to predict health outcomes. Even when attributes are clinically validated, they may correlate to different outcomes with different accuracy strengths.

Improving predictive ability is not just a matter of adding more data. It is a science to determine which datasets enhance predictive power and how they should be weighted in drawing insights about a patient.

Myth #3: A patient’s socioeconomic attributes considered individually allow you to make accurate predictions about a patient’s overall health risk.

Any attribute examined on its own is not adequate to develop an accurate risk score understanding. A combination of relevant attributes—ranging from social and community circumstances to economic stability and education, to neighborhood and built environment—provide context and are critical to developing a complete, holistic picture of the patient.

Myth #4: Socioeconomic data comes from demographic data or must be gathered through the use of surveys.

Demographic data may be too limiting and census data tends to get outdated quickly. Survey data, too, can become outdated. Furthermore, the value of survey data depends on the accuracy of the patient supplying the information and on the staff member who manually enters the results into the system.

Research has shown that public records are a better source of socioeconomic data. Those records are vast, comprehensive, and reliable. Clinically validated information on social determinants of health can be extracted from these records to paint a picture of a patient’s social, environmental, and economic situation and predict future health outcomes.

For healthcare providers who have traditionally relied only on medical and pharmacy data, socioeconomic data can now help fill gaps in understanding the patient and provide actionable insights that can be used to improve patient care.

Myth #5: To personalize care for a patient, you can rely on aggregated data at the ZIP code or census level.

Aggregated levels of data can be useful for expanding a health system’s market share or determining resource allocation. They are not, however, suitable for predicting a patient’s individual health risk.

Within a single ZIP code can be a wide variety of income levels, crime rates, and other factors that are critical components of social determinants of health. An individual’s actual address allows for the collection of social determinants that are more accurate indicators. However, even address data alone are not effective predictive tools. They ignore the influences of education, economic stability, social context, and other important variables that impact health.

Myth #6: Socioeconomic data must be used in combination with clinical data and is not an effective risk predictor on its own.

Even in the absence of clinical data, using socioeconomic data has proven to more accurately predict risk based on total cost than traditional age/gender predictions alone. Small increases in accuracy of as little as a percent or two can have a substantial impact and should not be ignored.

Because higher-risk patients account for the majority of healthcare costs, using socioeconomic scores to more accurately identify them gives providers an opportunity to proactively address their care. The result can be a 10-20 percent savings over traditional age/gender model risk stratification alone.

Healthcare is on the brink of a significant transformation largely driven by the availability of vast amounts of socioeconomic data and advanced analytics. Now that we’ve separated fact from fiction, it should be apparent social determinants of health have great value as a reliable predictor of healthcare risk.

The truth is we’ve only scratched the surface of what can be learned and how the insights gained can be applied. What is clear now is that organizations that embrace using social determinants of health will be better able to understand and manage health risk in their patients, resulting in improved outcomes and reduced healthcare costs.

Readers Write: Why Healthcare Organizations Take So Long to Make Buying Decisions and How We Can Fix It (Part 4 of 4)

November 15, 2017 Readers Write No Comments

Why Healthcare Organizations Take So Long to Make Buying Decisions and How We Can Fix It (Part 4 of 4)
By Bruce Brandes


Bruce Brandes is founder and CEO of Lucro of Nashville, TN.

We have previously discussed the impact of organizational misalignment and lack of trust on slowing the buying cycle in healthcare. Once you decide which projects are worth tackling and you streamline getting the scoop from your trusted network, now you must challenge and simplify the deeply-rooted, legacy workflow to make a decision.

Let’s illustrate two examples of antiquated steps in most every vendor selection process in healthcare and discuss potential solutions.

Meetings about Meetings


For projects that require alignment and collaboration across many key stakeholders, unnecessary, unproductive meetings complicate and delay making a decision.

Politics and mistrust may artificially swell the number of required participants (healthcare is more than a catered buffet away from adopting Amazon’s two-pizza rule). Something as simple as setting a date for a meeting when everyone is available can push a process out by weeks, if not months. Inevitably, some important contributors will have a last-minute conflict. The original meeting agenda often devolves into a pontification session with distracted participants checking emails on their phones and little advancement toward a decision.

How can we ensure fewer meetings, using our precious time together to be true decision-making events to advance a project? The most common answer to date has been an untenable volume of fragmented emails, spreadsheets, SharePoint files (people really still use this!?), and other databases that do not spur action.

A better solution is to enable a more efficient platform for asynchronous collaboration among key contributors. Ideas, comments, and assessments can be solicited and shared at the availability of each stakeholder and captured in context of the problem statement, current solutions, or potential solutions being considered. Project owners control the appropriate balance of privacy and transparency to minimize duplication of effort across the organization.

Better asynchronous collaboration can ensure fewer people physically attend fewer meetings and calls,  and when they do, key information and opinions will be understood in advance, reserving meeting time to make decisions that more rapidly advance a project. Let’s stop having meetings about meetings that don’t offer any action items or decisions and ensure everyone’s time is spent more efficiently.



In an effort to de-risk a decision, get a fair price, and discern truth amid vendor marketing claims, we in healthcare add months to a procurement process with a request for proposal.

The greatest advance in the healthcare RFP process over the last 15 years is replacing FedEx’ing boxes of binders with emailing word documents and spreadsheets. Not exactly disruptive innovation on the most universally dreaded, antiquated step in the buying process (drawing disdain from both healthcare organizations and vendors alike).

Every RFI or RFP is created and sent as if it were being done for the first time and yet rarely is an original question asked. Just ask the vendors who jump through clerical hoops to nuance their library of prepared answers to meet the requirements and format of each set of questions, always wondering if they are wasting resources on a CYA exercise for a decision that has already been made.

Further, manual effort for project owners to cut and paste siloed answers among Word documents, spreadsheets, and PowerPoint to score, assess, and present results amplifies frustration.

How can health systems ensure the diligence and risk mitigation benefits of an RFP without the exorbitant time, resources, and costs associated with their current methodology?

A network of engaged healthcare organizations that share common challenges and opportunities can collectively engage with vendor partners in a new way that is more efficient and effective for all involved. Common questions and answers can be crowdsourced to minimize unnecessary duplication.

The future state of an RFI can be little more than an appropriate search and application of filters to instantly identify a relevant shortlist. For a deeper dive, posing general RFP-like questions in a common platform (with appropriate privacy controls) can help buyers ensure a more comprehensive question set while helping vendors avoid answering the same topic more than once. Enhanced by automatic comparison, simplified assessments and flexible analysis of results, the expectation is we can minimize decision-making risk for more vendor selections being made without the formal RFP we know today.

By reimagining meetings and RFPs, the healthcare industry can simplify and antiquated process and enable decisions to be made with significantly fewer resources, less elapsed time, and lower costs.

Readers Write: Detecting Healthcare’s Data Dilemma

November 1, 2017 Readers Write No Comments

Detecting Healthcare’s Data Dilemma
By David Lareau


David Lareau is CEO of Medicomp Systems of Chantilly, VA.

“It is a capital mistake to theorize before one has data.” – Sherlock Holmes, “A Study in Scarlett” (Arthur Conan Doyle).

The great detective Sherlock Holmes understood the important role that data plays in decision-making. Whether you’re sleuthing or delivering patient care, you need data in order to make sense of things.

Not long ago, before EHRs were pervasive across health systems, providers struggled to obtain the data they needed for good clinical decision-making. Today healthcare has an abundance of clinical data, along with a new data dilemma: finding the right data at the right time.

In a recent webinar, our team asked 76 healthcare IT professionals and physicians about their biggest data-related challenges. According to 43 percent of the respondents, the top struggle was not a lack of data, but finding the right data at the right time. An additional 25 percent claimed they did not have access to the data they needed; 9 percent said they did not have enough data; and 6 percent complained of having too much data.

In other words, providers are challenged by the inability to access the data they need when and where they need it.

Consider what happens when a physician sees a patient and lacks ready access to their medical history, problem lists, medications, and test results. If the physician does not have access to the results of a critical test, the provider may re-order the identical test, possibly wasting healthcare resources and creating confusion about the accuracy of the patient’s records.

Interoperability advances are making it easier to share data, but true interoperability continues to be a struggle, thanks to a lack of standards, inconsistent data, and inadequate monetary incentives. We asked our webinar participants about their biggest barriers to achieving interoperability and 42 percent pointed to the challenge of data exchange. An additional 35 percent expressed difficulty applying data and making it actionable, while 20 percent reported difficulties organizing the data they received.

New exchange standards, such as FHIR, are making it easier to send data, but typically the incoming data is highly disorganized and not stored in an easily searchable format that adds value for clinical decision-making. In fact, the flood of incoming, unorganized data is creating new concerns about potential medical liability risks for providers. For example, a physician that inadvertently overlooks a critical abnormal finding that’s hidden within an incoming record could be held accountable for any ensuing patient complications.

Despite new standards and APIs that facilitate the exchange of data, much of the data exists in unstructured formats that are difficult to organize, include too many duplicates, and are not easy to search. In fact, an estimated 80 percent of all health data is stored in unstructured formats, such as free-text or scans.

Many in healthcare are optimistic that new technologies such as natural language processing (NLP) and artificial intelligence (AI) can be leveraged to convert dictated chart notes to free-text, and free-text to data that is in a format that is actionable for clinicians. The reality is that these solutions are still not sufficiently mature for most healthcare applications: the error rates for converting speech to text to data are, at best, between 8 and 10 percent, which is not reliable enough to support clinical decision- making.

Not all data is created equal – and not all data is equally usable for advanced analytics or for clinician use at the point of care. In order to be actionable for providers and usable for AI and analytics applications, data must be structured and organized in a way that facilitates viewing across clinical domains. One way to do this is to leverage technology that intelligently identifies, interprets, and links medical concepts and maps them to standard nomenclature, such as ICD-10, SNOMED, RxNorm, and LOINC.

Once disorganized data is converted to structured, actionable formats, it becomes more accessible to clinicians, allowing them to easily find the information they need during patient encounters and within their normal workflows. The structured data is also properly formatted for input into AI systems that use advanced algorithms to deliver clinical insights.

To ensure the ongoing creation of high-quality, structured data, we need to give clinicians the ability to capture coded clinical data as a byproduct of the documentation process and within their normal workflows. With more usable data, physicians can more readily access actionable information at the point of care. Organizations can more easily exchange quality information, and not just chunks of data that must be manually interpreted and organized. And, health systems are better equipped to harness the power of AI and the advanced analytics that enhance the delivery of patient care.

Detective Holmes understood that he could not optimally perform his job without data. To optimally deliver healthcare, providers need more than just data, which is why the industry must embrace technologies that make it easy to access the right data at the right time.

Readers Write: How Technology Could Aid Amazon’s Prescription Drug Play

November 1, 2017 Readers Write No Comments

How Technology Could Aid Amazon’s Prescription Drug Play
By Thomas Borzilleri


Thomas Borzilleri is the founder and CEO of InteliSyS Health of San Diego, CA.

Amazon’s plans to enter the healthcare market may not be ready for prime time, but it is high time for the healthcare industry to take Amazon’s threat seriously. A recent report from Goldman Sachs notes that with 2016 prescription spending (net of rebates) topping $400 billion, high repeat purchases, lack of price transparency, and an increasing cost burden on the consumer, it’s no surprise that prescription drugs have attracted the attention of the 800-pound e-commerce gorilla. But the Goldman Sachs report goes on to warn Amazon of the complexity of the drug supply chain and the high barriers to entry for new players.

This is all certainly true. Most patients still buy their drugs the old-fashioned way, at retail pharmacies or through mail order services that reflect negotiated prices between public and private payers and pharmacy benefit managers (PBMs). These relationships will be challenging to break up. But as customers pay more for their prescription drugs, they will increasingly clamor for more price transparency and the ability to shop around, as they are starting to do for other healthcare services. As consumers increasingly drive decisions about their own care, Amazon may well find a path to success. The key is to partner with emerging technologies to bypass prescription drug middlemen and deliver real savings.

Amazon could wade in slowly to the healthcare sector. It could easily sell durable medical equipment online. There is no prescription needed and Amazon could most certainly lower prices if it can capture enough volume. At the very least, the e-tailer could offer free shipping as an incentive to choose Amazon over smaller DME vendors. Amazon could also, reasonably easily, get into the market to sell over-the-counter medicines, as discount clubs like Costco and BJ’s have already done with great success. Again, these purchases do not need to involve insurers or physicians, and Amazon can appeal directly to the consumer.

But this approach only scratches the surface of the opportunity for Amazon. If Amazon wants to go after the big Kahuna—prescription drugs—it will have to meet three essential goals

Inspire Trust

Amazon must inspire trust throughout the healthcare ecosystem, among patients, first and foremost, but also among doctors who agree to write e-prescriptions to a preferred pharmacy. Amazon may also have to inspire trust among insurers if it decides to partner with them to get access to drug coverage, formularies of preferred drugs, and guaranteed patient volume. They must convince all parties that the drugs they will deliver are as safe and effective as those found in retail pharmacies.

Promise Convenience

Amazon must offer added convenience over traditional mail-order pharmacies. The holy grail of two-hour or same-day delivery will require a large number of distribution centers, all of which need to be inspected by the US Food and Drug Administration and will require a high level of security. These demands, including added manpower to run these facilities such as highly-paid pharmacists, will be costly.

Deliver Value

Amazon can only succeed if it can offer a lower price point, and it can only offer better prices if it can capture significant patient volume. If Amazon simply seeks to replace existing pharmacy benefit managers by winning brand-new contracts with insurers, this will be a challenge. Amazon will not, starting out, have the volume-based discounts that PBMs enjoy. Meanwhile it will face a variety of new startup costs. Additionally, Amazon will face a fierce battle from entrenched PBMs.

Amazon must, as it has done in other markets, forge an entirely new path by connecting directly with consumers and offering reliable products conveniently and affordably. Amazon has chosen a fortuitous moment, as the consumerization of healthcare is finally gathering steam. Consumers are paying more out-of-pocket than ever for prescription drugs due to rising deductibles, co-pays, and co-insurance. Meanwhile, most patients have no idea that the price of drugs varies widely and that buying medications retail may be cheaper than their co-pays. This sets up a unique opportunity for Amazon to help lift the veil on drug prices and offer patients lower-priced alternatives.

By operating independently of insurers, Amazon can sidestep a head-on fight with established PBMs. Instead of spending resources trying to pick off patients one insurer at a time, they could choose to woo patients directly, competing on price at the point of care where prescribing decisions are made.

PBMs ostensibly exist to provide volume discounts to insurers on drugs. But in reality, these “discounts” are riddled with padding. Insurers are receiving volume discounts off the manufacturer’s retail price, but PBMs tack on something called “ingredient spread” while also charging a per-transaction fee. Meanwhile, prices vary widely from one pharmacy to the next, even in the same town, and consumers typically have no idea. Consumers who buy their drugs using insurance coverage usually accept the PBM-mediated price at their closest pharmacy because they don’t have the knowledge or the ability to shop around.

Instead of allying with manufacturers and insurers (the supply side of the prescription drug transaction), Amazon would do much better to join forces with the demand side, appealing to consumers and doctors. But how can Amazon get into a doctor’s office? Send sharply dressed salesmen and women like the makers of Lipitor and Viagra? Since the Sunshine Act and other rules regulate interactions between healthcare providers and the pharmaceutical industry, drug sales personnel have less access to providers than ever.

Amazon could instead leverage new technologies that help doctors and patients access real-time drug prices at nearby pharmacies. Amazon’s prices could be listed along those at traditional retail pharmacies to allow patients and doctors to choose the lowest-priced vendor, depending on whether the retail price or the co-pay is a cheaper option. These tools, if accessed seamlessly within the e-prescribing workflow, would integrate Amazon into the existing marketplace of drug retailers and give the e-tailing behemoth a seat right in the exam room alongside the doctor and patient, giving Amazon direct and immediate access to patients across different private health insurers, public payers, and the uninsured/underinsured.

Amazon would still face the challenge of establishing mail order centers and getting them certified by the FDA. But they wouldn’t be seeking to replace one middleman—pharmacy benefit managers—with another. By going straight to the consumer and the provider at the point of care, Amazon would have a unique opportunity to disrupt both the supply chain and the pricing models for prescription drugs. This could potentially have far-reaching benefits for consumers by causing overall downward price pressure and further exposing price-gouging that PBMs engage in, even while promising discounts.

The Goldman Sachs report posits that Amazon’s best chances for success rely on choosing a partner that can help it get into the market, such as an existing PBM. While this approach may be a boon for Amazon, it won’t do much to disrupt drug prices and transparency. If Amazon is serious about remaking the way Americans buy their prescription drugs, the e-commerce behemoth should look to cut out the middlemen—PBMs—and appeal directly to consumers to help tackle the prescription drug affordability crisis in the United States.

Readers Write: Why Healthcare Organizations Take So Long to Make Buying Decisions and How We Can Fix It (Part 3 of 4)

November 1, 2017 Readers Write 3 Comments

Why Healthcare Organizations Take So Long to Make Buying Decisions and How We Can Fix It (Part 3 of 4)
By Bruce Brandes


Bruce Brandes is founder and CEO of Lucro of Nashville, TN.

In Part 2 of this series, we discussed the importance of first clearly defining and aligning regarding the problem a buyer seeks to solve before evaluating products. The next key element is to invite trusted colleagues to contribute insights and experience in the context of that problem and possible solutions.

Below we will share more about the type of buying decisions most impacted by a lack of trust and explore how healthcare buyers can gain more confidence in the choices they must make.

There are three buckets of non-labor spend in health systems:

  1. Supply chain — traditionally influenced by group purchasing organizations (GPOs.
  2. Pharma — traditionally influenced by pharmacy benefit management companies (PBMs).
  3. “Everything else,” which falls into a category known as purchased services (traditionally managed less centrally).

Purchased services represent 20-30 percent of a hospital’s expenses and include a wide array of vendors ranging from health IT and digital health to outsourced professional and ancillary support services. Many health systems are seeking to drive standardization, minimize duplication, and realize greater value related to purchased services.

Vendor selections for purchased services are generally complex, collaborative processes. With input required from so many key stakeholders for a purchase commitment of a significant amount, how do risk-averse health systems ever make a buying decision? The challenge is exacerbated by an array of third-party sources of market insight, including consultants, industry associations, purchasing groups, etc., all with their own opinion about the “best” vendor for that area of focus.

If you are responsible for this buying decision, who do you trust? How can you efficiently synthesize so many disparate data points of opinion about the best product in the market to put them all into context to make the right decision for your organization?


Healthcare buyers take many of these outside opinions with a grain of salt, skeptical of the motivations of some. Vendors may compensate the “non-partisan” organizations to endorse their products. Unsolicited information received from cold calls or spam emails can rarely be trusted.

When you are making a strategic hire to your team, do you ever expect the personal and professional references given you by the candidate to say anything too negative? More commonly, even before an interview, it is wise to do a quick check of LinkedIn to seek common connections that you know will give you more clear and honest insight (this works in both directions for the candidate and organization).

Similarly, buyers want an efficient, private way to tap into trusted colleagues across their professional network,  those who have experience in tackling this same problem in an organization like theirs.

The time and cost associated with deciphering vendor claims, vs. hype, vs. reality are untenable for the entire industry. With today’s time and financial pressures, physical site visits and reference calls are (finally) antiquated. Thus, it is critical to gain necessary insights from those you trust to reduce the risk associated with strategic vendor selections.

The value of a trusted network is compounded when this collaboration is contextualized with the problem and potential solutions under consideration. As trusted communities come together, the entire industry can benefit.

News 11/1/17

October 31, 2017 News, Readers Write 2 Comments

Top News


CMS clarifies the information blocking requirement of MIPS for providers. Eligible providers must attest that they:

  • Haven’t disabled the interoperability capabilities of their EHR.
  • Have implemented their EHR without taking any actions to limit interoperability.
  • Quickly respond to requests from patients and other providers who ask for information retrieval or exchange.

CMS advises that no documentation is required to be submitted as part of the attestation. It also notes that while attesting providers aren’t expected to understand or enable the technical side of interoperability, it’s their job to let their implementers and EHR vendors know that they will be attesting and hold them accountable for enabling that capability.

Reader Comments


From Good-Time Charlie: “Re: Practice Fusion. I didn’t remember until your poll that they were even still around.” They are, but seemingly barely, well out of contention as an ambulatory EHR disruptor despite having raised $200 million from investors under that premise. ONC places Practice Fusion as the #9 most commonly used ambulatory EHR based on attestation data, which isn’t so good given that their product is free (and the products that follow them on ONC’s list aren’t really major-name EHR vendors). The company seemed unstoppable when doctors flocked to its product to collect $44,000 in Meaningful Use money in return for spending nothing, but the company’s business model was questionable, they were selling practice data in less-than-transparent ways (such as not naming who was buying it and for what purpose), its self-reported usage figures were head-scratching at times, and there was always the question of just how deeply practices engaged with the product since they had no skin in the game (no hardware cost, contract, training cost, etc.) The company fired founder and CEO Ryan Howard in mid-2015 right before a planned IPO, promoted a replacement with skimpy credentials for taking a company public, and largely fell off everyone’s radar.

From Dinky McQueen: “Re: GE’s rumored discussion about selling its healthcare IT business. Is it everything from Centricity on down, or just smaller, unaligned divisions such as the GE-Intel Care Innovations JV?” I haven’t heard specifics but would be interested. The health IT business includes the many products labeled as Centricity, workforce management (the old API Healthcare), Health Cloud, diagnostic-related software, and some analytics stuff. It’s hard sometimes to figure out where healthcare IT begins given the overlap with the company’s diagnostic business, which I assume won’t be dealt off. GE has built a poorly managed, unfocused portfolio of acquisitions that will be hard to sell off to a single buyer, which will probably elongate any process to make its unlamented healthcare IT exit.


From Just Saying: “Re: speech recognition. You mentioned years ago using speech recognition to write HIStalk. Do you still do that?” I don’t. Three or so times I bought the latest version of Dragon and got excited about how much easier it was to “write” HIStalk by talking instead of typing, but the sheen wore off due to Dragon’s heavy system usage, occasional mysterious errors that lost what I had dictated, and the time required for me to fix its mistakes (nearly always caused by my not articulating crisply enough). I’m thinking about trying again with LilySpeech, a cloud-based system that uses Google’s speech-to-text system. I don’t need voice-controlled system automation – I just want to dictate into a text box and paste the result into my editor or Gmail. I’ll give the 30-day free trial a shot.

HIStalk Announcements and Requests


I enjoyed reading a recent interview with freshly named economics Nobel winner Richard Thaler and was therefore happy to see his “Misbehaving: The Making of Behavioral Economics” pop up as a free Prime Reading Kindle book this week. I was engrossed and entertained by it, to the point that I ordered a softcover version (at full price) just so keep it handy and to be able to lend it out. This book and his earlier “Nudge” explain why humans don’t always follow rational economic thought, which of course has healthcare implications along with big-time business impact. I highly recommended the first book and will no doubt do the same for the second once I’ve read it. He’s a great explainer and pretty funny besides.

The only iOS device I have left is my iPad Mini, but even that is now a little closer to Android – I replaced the default iOS mail app with Gmail and like it much better, especially for deleting endless streams of spam without having to swipe emails individually and trying to recall the difference between “archive” and “move to trash.”


November 8 (Wednesday) 1:00 ET. “How Clinically Integrated Networks Can Overcome the Technical Challenges to Data-Sharing.” Sponsored by: Liaison Technologies. Presenters: Dominick Mack, MD, executive medical director, Georgia Health Information Technology Extension Center and Georgia Health Connect, director, National Center for Primary Care, and associate professor, Morehouse School of Medicine;  Gary Palgon, VP of  healthcare and life sciences solutions, Liaison Technologies. This webinar will describe how Georgia Heath Connect connects clinically integrated networks to hospitals and small and rural practices, helping providers in medically underserved communities meet MACRA requirements by providing technology, technology support, and education that accelerates regulatory compliance and improves outcomes.

November 15 (Wednesday) 1:00 ET. “How Hospitals and Practices Can Respond to Consumerism by Better Engaging Patients Through Price Transparency and Payment Options.” Sponsored by: Change Healthcare. Presenters: Kathy Moore, president, Moore Martini Medical; Linda Glidewell, VP of business development, consumer payment solutions, Change Healthcare. Healthcare consumerism and high-deductible health plans require providers to offer upfront estimates and payment options throughout all points of service. In his webinar, we’ll discuss consumerism as a critical area of opportunity in revenue cycle management and review numerous areas across the revenue cycle where your staff interacts with patients and leaves lasting impressions. From your first interaction with patients on the phone to discuss financial responsibility; to collecting payments at all points of service; to offering payment plans and various payment options — these are all areas that can be game-changing. With the right approach to consumerism, you can improve patient collections and optimize revenue from the start while also improving the overall patient experience.

Previous webinars are on our YouTube channel. Contact Lorre for information.

Acquisitions, Funding, Business, and Stock


Meditech announces Q3 results: revenue up 9.8 percent, EPS $0.47 vs. $0.68. Product revenue jumped 50 percent, but a slight drop in services revenue and an 18 percent increase in operating expense drove earnings down 31 percent.


Roper Techologies (Sunquest, Strata Decision Technology, Atlas Medical, Data Innovations, CliniSys) announces Q3 results: revenue up 23 percent, adjusted EPS $2.36 vs. $1.96, meeting revenue expectations and beating on earnings.


Germany-based Ada Health, which offers consumers an AI-powered health chat app that also connects users to doctors, raises $47 million and announces plans to open a US office.



Hospital for Special Surgery (NY) will expand its use of Docent Health to provide customized, whole-person support that addresses each patient’s needs, fears, and concerns.


Orlando Health chooses Phynd to manage the information of 25,000 providers across nine hospitals.



Geoff Hogan (Imprivata) joins Diameter Health as chief commercial officer.

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Impact Advisors promotes VPs Paula Elliott and Bill Faust to leadership roles over its quality services and strategic implementation services practices, respectively.

Announcements and Implementations


Casenet’s TruCare is named Best Population Health Management Software Provider in a UK healthcare and pharmaceutical awards program.


HIMSS announces that Alphabet Executive Chairman Eric Schmidt will deliver the opening keynote at HIMSS18 in the “still seems weird” time slot of Monday, March 5 at 5:00 p.m. PT. Schmidt provided the very long keynote at HIMSS08 in Orlando, where he pitched since-failed Google offerings like Health and Flu Trends. 

Government and Politics


Politico reports that HHS privacy leader Deven McGraw, JD has left government service to join an unnamed Silicon Valley health technology startup.

Publicly traded, Cincinnati-based Chemed, which owns the country’s largest for-profit hospice chain, will pay $75 million to settle False Claims Act charges that it billed Medicare for services involving patients who were not terminally ill and paid its employees bonuses for recruiting new patients. Three whistleblowers will share in the payout. Trivia: Chemed’s other big holding is Roto-Rooter. 


Vanderbilt University Medical Center (TN) will go live on Epic this week.


The April 1 Cerner go-live at Medical Center Health System (TX) led to billing delays that left it behind for the fiscal year ending September 30. A consultant’s report says that hospital executives blamed staff for lack of commitment and not paying attention during training, but most employees said that training was insufficient for doing their jobs. 


A study finds that 10 percent of Massachusetts residents who were revived from opioid overdoses with rescue drug Narcan died within a year, highlighting that only five percent of overdose survivors receive longer-term treatment drugs such as Suboxone.

Brilliant: a company in Japan gives non-smokers an extra six days of vacation, both as an incentive for smokers to quit and to give non-smokers the same amount of non-productive time enjoyed by smokers.


Weird News Andy helpfully notes that maybe the patient should have considered flossing. Doctors examining a woman with a decades-long history of nosebleeds believed to be caused by rhinitis finally determine the cause – a fully grown tooth embedded in her nasal cavity. Dentists say “supernumerary teeth” can grow in odd spots on the face in the 4 percent of people affected, but having them erupt in the nasal cavity is extremely rare. 

Sponsor Updates

  • Meditech, which has 20 customer sites in Puerto Rico, donates money to United for Puerto Rico.
  • AdvancedMD will exhibit at APTA’s Private Practice Section event November 1-4 in Chicago.
  • HIS 2017 recognizes Agfa Healthcare in the IT Industry category – RIS and PACs during its annual awards ceremony.
  • AssessURHealth publishes a new white paper, “The Missing Piece: Holistic Care through Preventive Screenings.”
  • Bernoulli Health will exhibit at HealthAchieve November 6-7 in Toronto.
  • Besler Consulting will present at the Minnesota HFMA Regulatory Conference November 2 in Bloomington.
  • CSI Healthcare IT completes the first wave of Epic go-lives at Lovelace Health System (NM).
  • Clinical Architecture will exhibit at the AMIA 2017 Annual Symposium November 4-8 in Washington, DC.
  • CoverMyMeds, CTG, and Cumberland Consulting Group will exhibit at the CHIME Fall CIO Forum October 31-November 2.

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Readers Write: Interoperability and Standards Will Be Areas of Focus Through Year End

October 9, 2017 Readers Write 4 Comments

Interoperability and Standards Will Be Areas of Focus Through Year End
By Michael Burger


Michael Burger is practice lead, EHRs and EDI, for Point-of-Care Partners of Coral Springs, FL.

While there are many uncertainties in healthcare, interoperability and standards will undoubtedly be areas of focus through the end of 2017. To that end, the government and industry will continue to refine existing standards and address interoperability challenges. This involves activities by the Office of the National Coordinator (ONC) and ongoing efforts by standards development organizations (SDOs) and electronic health record (EHR) vendors.

Despite potential severe budget cuts, ONC says it is committed to interoperability and standards as main areas of emphasis. For example, ONC is putting the finishing touches on its Proposed Interoperability Standards Measurement Framework, the final document for which will be issued this fall. It also is accepting comments through November 20 for the Interoperability Standards Advisory, which is a stakeholder-informed catalog of the standards and implementation specifications that can be used to meet interoperability needs in healthcare. The newly created Health Information Technology Advisory Committee will also be influential with regard to standards and interoperability. Its recommendations to ONC doubtless will be translated into rulemaking and policy.

The next few months also should see continued progress by SDOs in refining standards for interoperability with a focus on practical use cases by EHR vendors.

One example is FHIR (Fast Health Interoperability Resources), which is one of the newest standards from Health Level 7 (HL7). Vendors are beginning to embrace the most recent iteration of the standard for various clinical use cases and FHIR is being used to extract relevant clinical data from EHRs.

Also, the National Council for Prescription Drug Programs (NCPDP) is refining the SCRIPT standard to facilitate the transition to electronic prescribing of specialty medications. Today, specialty prescribing is largely a manual process that isn’t easily adapted to existing electronic prescribing workflows. An NCPDP task group is looking at ways in which new data elements could be added to the SCRIPT standard to handle enrollment for specialty medications, which accompanies the prior authorization that is required for nearly all such medications. The goal is to enable enrollment and electronic prior authorization (ePA) for specialty medications. Changes to the standard will enhance the ePA functionality, which EHR vendors have already built for non-specialty medications.

There are still obstacles that must be overcome to move health IT interoperability down the field. Three come to mind:

  • Lack of a national patient identifier. One of the biggest interoperability challenges is the lack of a national patient identifier. While industry solutions are being developed, they are one-offs that are not totally standards based. True interoperability cannot be achieved unless this problem is solved.
  • Changes in business models. There is much talk around data-blocking by EHRs, but this is not so much a technology challenge as a business one. The competitive nature of healthcare delivery is primarily what prohibits the exchange of clinical information, as competitors don’t want to make it easy for patients to seek care outside of their networks. When there is demand among customers to connect systems, software vendors respond by building and selling connectivity solutions. The most successful of these solutions rely on standards that have been created and vetted through SDOs.
  • Variations in standards implementation. Other interoperability challenges are created by variations in how standards are used in application program interfaces (APIs) with EHRs. Sometimes these APIs rely on technology that is not standardized, thus adding to the complexity and inconsistency in how data are exchanged among EHR platforms. The goal of using standards to achieve interoperability can only be met when standards are interpreted, implemented, and used consistently.

These are but some of the opportunities and challenges we see in the waning months of 2017 when it comes to standards and interoperability. These issues are not going away anytime soon and will continue to occupy stakeholders’ attention in 2018.

Readers Write: The Untapped Data That Can Improve Lives and Lower National Healthcare Spending

October 9, 2017 Readers Write No Comments

The Untapped Data That Can Improve Lives and Lower National Healthcare Spending
By Kurt Waltenbaugh


Kurt Waltenbaugh is founder and CEO of Carrot Health of Minneapolis, MN.

Ask 10 mechanics which costs more — preventive or corrective maintenance — and each will likely give the same answer. It’s cheaper to change a car’s oil regularly than to repair a seized engine. The same principle holds true for healthcare.

In 2015, US healthcare spending reached $3.2 trillion. More than half of that went toward hospital care and physician / clinical services, which increased by 5.6 percent and 6.3 percent, respectively, according to the Centers for Medicare and Medicaid Services (CMS). The surge in payouts for these services was due to “non-price factors,” specifically an increase in “use and intensity of services.”

This makes sense given that the coverage expansion under the Affordable Care Act (ACA) gave more Americans access to healthcare than ever before. But at a time when the public and healthcare professionals have centered their focus on reducing insurance premiums and the cost of care, there is one question missing from the debate. Could the need for some of these services have been prevented?

The answer lies in a well of big data that has, until recently, been untapped by the healthcare industry.

In the health insurance market, there exists a disconnect between medical costs and an individual’s health quality. Behavioral and socioeconomic factors determine roughly 60 percent of their overall health, yet 88 percent of the country’s healthcare spending goes towards medical services, which impacts merely 10 percent of a person’s healthiness.

A study entitled “Health and social services expenditures: associations with health outcomes” compared spending by 11 nations on medical care against social care and the impacts on health outcomes. The findings showed that not only was the US the only country to spend more on healthcare than social services as a percentage of GDP, but that a higher ratio of spending on social services was also associated with better outcomes in infant mortality and life expectancy.

Access to this socioeconomic and behavioral data gives payer organizations a clearer picture of a member’s health risks. For example, detailed knowledge about where a person lives — such as neighborhood crime rate, average household income, and availability of healthy food — provides more predictive information than higher-level information on the coverage region, data that delivers far more accurate insights into quality of life. Environmental factors like “walkability” can help determine how easy it is to exercise, while air quality can indicate a person’s risk for lead exposure. For individuals living in a low-income, high-risk area, education and local job opportunities can determine their probability for upward mobility and, by extension, how likely they are to improve the socioeconomic factors impacting their health.

On the surface, proponents of data privacy might argue that these companies would push to use this information to raise premiums for those whose socioeconomic and/or behavioral patterns make them more susceptible to life-altering medical conditions. A deeper examination, however, reveals an opportunity for payers to cover more individuals with less-costly interventions without losing any competitive ground. By connecting these individuals with services that help address social and behavioral determinants of health, payer organizations help them improve their lives while also reducing the potential need for higher-cost care interventions, such as emergency room visits or hospitalization.

In fact, this approach has the potential to change the way insurance operates throughout the country. Rather than balancing enrollment with enough low-risk members into a health plan to cover the care costs for high-risk members, a strategy centered on preventive care through social and behavioral interventions means payers become more invested in their members’ total quality of life, thereby creating a healthier population.

Readers Write: Sepsis Risk Intervention: You May Be Doing It Wrong

October 4, 2017 Readers Write No Comments

Sepsis Risk Intervention: You May Be Doing It Wrong
By Jennifer Knapp


Jennifer Knapp is director of strategic partnerships and solutions for Vocera of San Jose, CA.

September was Sepsis Awareness Month. Many hospitals and health systems, propelled by CMS penalties for avoidable hospital-acquired infections, have made important investments in sepsis risk intervention. But these efforts have introduced new challenges.

As nurses are put on high alert for a growing number of risk factors—including falls, drug interactions, etc.—they are struggling to attend to and prioritize all of these different alerts. For long-term success against the scourge of sepsis, the health IT industry must work to mitigate and manage the negative impact of alarm fatigue on our frontline healthcare providers.

Sepsis is an important target of hospital quality and safety programs. It is a leading cause of death in the U.S., claiming 750,000 lives annually. With $24B spent annually, it is the costliest medical condition to treat in this country. Luckily, strong evidence shows that early, tailored intervention can significantly reduce the likelihood of sepsis-related complications and death.

To this end, many hospitals have deployed EHR-based pop-up advisories to identify patients at risk for sepsis. But there are three problems:

  • Nearly half of these alerts are false-positives.
  • They get mixed in with the routine pop-ups nurses have learned to quickly click through.
  • Nurses will only see these alerts if they are working in the EHR. Since nurses can walk up to five miles a day during a 12-hour shift, they are often away from the EHR.

Sepsis rates will not fall dramatically unless risk intervention alerts are accurate, reliable, and actionable. Alerts must give nurses the right information at the right time in the right way.

The algorithm used to detect sepsis must include nursing and provider documentation, in addition to data from the EHR, to improve the precision of risk determination. Alerts should only be delivered when they provide new information to the staff or when appropriate treatment steps have not been completed. Sending only actionable alerts will significantly reduce alarm fatigue.

Move sepsis alerts out of the routine flow of EHR notifications where they are likely to get lost in the shuffle. Instead, deliver them to caregivers on mobile devices at the point of care. The bottom line is that if you don’t use a mobile alert solution, you are leaving sepsis detection to chance because caregivers may not check the EHR for long periods of time.

Don’t just tell the nurse there’s a septic patient in Room 101. Provide more detailed information about the level of his or her condition (such as severe sepsis), why the alert was triggered (for example, hypotension), and what to do next. Consider functionality that would automatically alert another group, such as the rapid response team, after the alert is accepted by the frontline nurse on duty.

Hospitals are more committed than ever to reduce sepsis rates and intervene early to save lives. Health IT solutions should support, not stymie, these efforts. Deploying the right workflows and technology, driving care team engagement, and managing performance improvement against goals are keys to a successful sepsis program. Do it right and you can significantly improve patient outcomes.

Readers Write: Centralized or Decentralized Revenue Cycle After an Acquisition? Maybe There’s Another Option

October 4, 2017 Readers Write No Comments

Centralized or Decentralized Revenue Cycle After an Acquisition? Maybe There’s Another Option
By Jim Denny


Jim Denny is founder and CEO of Navicure of Duluth, GA.

According to a recent AMA survey, for the first time, there are as many hospital-owned providers as there are physician practice owners. As this acquisition trend continues to grow, health systems are evaluating the best way to coordinate and consolidate revenue cycle management (RCM) across the entire organization. Typically, to streamline patient billing, healthcare data analytics, and reporting, organizations take one of the following approaches:

  • A centralized approach. All RCM processes are combined across all entities into a single revenue cycle with a central billing office.
  • A decentralized approach. All billing remains separate across all entities.

The path chosen often varies depending on the organization and its structure.

However, in many cases, neither option may be the perfect approach. Instead, organizations may choose to employ a customized billing approach, leaving a majority of each acquisition’s processes, technologies, and best practices separate and in place, which are evaluated over a defined time frame.

A short-term, slower, methodical approach allows the health system and acquisition time to get to know more about each other and can be much less disruptive. A slower integration, perhaps a year or year-and-a-half, allows both to understand how the other works and to work as a team to come up with a plan as how to grow together.

During this period, it is important to establish a common electronic data interchange (EDI) solution so data and reports can be standardized and summarized across all organizations. Then, the health system can review standardized performance data to better understand each acquisition’s approach to RCM, working to identify each one’s uniqueness, strengths, and challenges. From there, they can determine the best way to proceed for the long term. A customized approach is considered a hybrid because it allows the health system to decide whether centralization or decentralization is the right option, and choose from the best of existing RCM approaches, or determine that it’s time to incorporate new ones.

Here are three reasons why a customized approach can make sense for your organization following an acquisition:

This hybrid approach provides time to assess the acquired practic.e

Customized RCM can give leadership the time needed to evaluate the success of a newly acquired practice, while enabling the practice to maintain productivity and conduct business as usual. Questions to ask can include the following:

  • What’s working and what’s not?
  • Does the practice need guidance to improve their efforts? This includes looking at the statistics – days in accounts receivable (A/R), denial rate, and success in patient collections.
  • What IT systems and vendor relationships are yielding the best results across claims management, patient payments, and reporting?

A customized approach allows a health system to choose from best-in-class vendor partnerships.

It benefits both the practice and the health system by allowing practices to maintain their own systems without having to conform to a billing office’s mandate immediately, while enabling the health system time to evaluate a number of systems and vendors and then making a best practice recommendation that fits the health system’s strategic roadmap. This is the time to assess what’s involved in streamlining and integrating technology from a process, people, and data perspective, regardless of whether the organization ultimately chooses a centralized or decentralized strategy.

This method provides breathing room to evolve over time while establishing a strong foundation for future growth.

Using a hybrid model for the short term can offer an organization the opportunity to mesh with other groups in an optimal way. With this approach, health system leadership does not need to force physician practices within the system to conform to the organization’s existing processes immediately. Instead, practices are given flexibility at a critical time that can ultimately lead to a successful merger. Even more importantly, it allows for necessary breathing room for the health system so it can prepare to adapt to industry shifts – such as building a bridge to move from fee-for-service models to value-based care, or in defining the best ways to evaluate when and where to participate in taking on risk-based contracts.

Choosing a short-term hybrid approach yields the opportunity to create a transition plan based on thorough evaluation to help ensure the health system capitalizes on the right processes, technology, and vendor relationships. And while there’s no easy answer, ultimately, the decision to centralize or decentralize an organization’s revenue cycle can be made together with buy-in from each organization, which is the best way to ensure long-term success.

Readers Write: Value-Based Healthcare Drives “Left of Bang” Approach for Risk Management and Compliance

October 4, 2017 Readers Write No Comments

Value-Based Healthcare Drives “Left of Bang” Approach for Risk Management and Compliance
By Mark Crockett, MD


Mark Crockett, MD is CEO of Verge Health of Charleston, SC.

In 2007, the Marine Corps deployed to Iraq and Afghanistan had a problem: how to identify an enemy that blended in with the population. They developed a behavioral approach to helping teams sharpen their tactical awareness skills to remain “left of bang,” or to fend off hostile actions before they culminate in the “bang” of conflict. In 2017, healthcare needs to deploy the same approach to managing risk and improving outcomes.

Healthcare is currently focused on right of bang, or the future correction of adverse events. Too much effort is expended to react to problems that have happened, and aren’t directed to preventing failure. The military (and other industries) expect that more than 80 percent of efforts should be spent left of bang to reliably prevent failure. A shift to a balanced approach is beginning to happen in top health systems for the first time, and it’s critically important for healthcare leaders to understand the how and the why.

How we got to the current right of bang problem is pretty clear. As a physician, I see failure all the time. Kidneys fail, hearts fail, and ultimately people fail. Dealing with that compassionately and professionally is part of the territory. Financial models have not helped at all. Under straight fee-for-service medicine in the past, if I gave someone an infection, it was quite possible I could bill them for a follow-up visit and perhaps even the antibiotics. In that kind of model, preventing failure is working against your economic model, making success in prevention just that much harder.

Times are changing fast. In the last few years, an array of accrediting bodies, regulatory entities, and payment model changes have made failure punishing to a health system’s finances and reputation. It’s now possible to see quality and adverse events on a dozen web sites, and more every day. Readmission prevention, Healthcare-Acquired Conditions, MACRA, MIPS, etc. are all ways of demanding reliable and efficient care. Health systems fail to execute on quality and safety at their risk: competitors across town that are doing it well are looking to expand and acquire patients and even facilities.

For one California-based hospital system, their timeline-oriented thinking – and solutions – needed to become left of bang. One of their hospitals had implemented a Six Sigma plan to reduce central line infections. Six Sigma is a popular methodology that takes a data-driven approach to eliminate defects in any process. The approach aims for six (or fewer) standard deviations between the mean and the nearest specification limit.

Using Six Sigma, the hospital system found a catheter that was superior in their opinion and a skin sterilization technique they knew worked. That single hospital then worked through the purchasing process, the stocking of the catheter, the sterilization procedures, and finally, implemented a process that ensures no one touches the catheter until the surgeon is ready to insert it into the patient. These improvements eradicated central sepsis at that hospital for more than five years. It was an amazing feat compared to industry standard. This completely redefines the concept of “expected complication” to “zero complications,” and unequivocally saved lives.

It’s a great thing when you can eliminate sepsis in central lines. But five years later, the multiple-hospital system still had a small number of hospitals using the technique. They had no means of assessing system-wide compliance with the Six Sigma process design, which at best was being implemented inconsistently. They simply have not organized left of bang. They admitted they lacked the ability to bring about system-wide change from what was learned at one hospital.

“We know how to prevent central line infections,” said one team member. “But without strong leadership, and the technology to implement the safety procedures system-wide, we find ourselves fixing the same problem every three years. We get serious about a problem, design a solution, and implement it. Then institutional inertia takes over. Two years later we are seeing adverse events, or worse, and ask ourselves ‘Where is that folder on the way we prevent catheter infections?’ It’s just not good enough.”

Getting hospitals to look for patterns in identifying adverse events, and working to identify them before they occur, keeps clinicians and staff in perpetual left of bang mode. But process improvement through Six Sigma isn’t going to enable this essential shift to a safety-first culture. Neither will the latest software or the best management training. It’s going to take all of these approaches – and more – for healthcare to truly see the results and outcomes that payers demand from providers.

Readers Write: Why Healthcare Organizations Take So Long to Make Buying Decisions and How We Can Fix It (Part 2 of 4)

September 27, 2017 Readers Write 4 Comments

Why Healthcare Organizations Take So Long to Make Buying Decisions and How We Can Fix It (Part 2 of 4)
By Bruce Brandes


Bruce Brandes is founder and CEO of Lucro of Nashville, TN.

As any industry observer knows, health systems continue to consolidate in an attempt to ensure their viability given unprecedented financial and operational pressures.  Many organizations struggle to fully leverage their scale post-merger. Most often the difficulty is to align focus, priorities, internal knowledge. and industry experience across the expanded team as they integrate.  

Misalignment is usually the main contributor to the length of the sales and purchasing process. Too often people fall in love with a PRODUCT without first clearly defining the PROBLEM they seek to solve. This challenge is exacerbated by complex purchasing decisions that require collaboration across multiple stakeholders to make the right choices.

My 16 year-old daughter, Lily, recently got her driver’s license and immediately spent lots of time and energy looking to buy a car (product). Much to her chagrin, the head of home operations (my wife) and the economic buyer (me) defined the problem as our daughter needing transportation, and buying a new car was only one of several options for us to address this issue. As we considered how to best solve her transportation problem weighed against other family priorities, we decided to simply get Lily an Uber account and an extra key to use our cars when available.

The same disconnect happens every day in healthcare. So much sales activity and investment are squandered on potential buyers who are only empowered to say no — not yes — to an actual buying decision. With the best of intentions, they may not be aware they are wasting time pursuing deals that will never come to fruition. Just like the sales guy at the car lot with my daughter.

By first defining the problem and enabling appropriate enterprise visibility, we can avoid projects that are misaligned with organizational priorities.  Further, we may also discover that due to poor or fragmented communication, we are pursuing a project where:

  • An organizational decision on how to address this problem has already been made.
  • Others within the same organization are already pursuing a similar project in parallel.
  • The organization already owns existing products, best practices, or internal resources that should be compared as an alternative to buying something new

In working with many health systems to design a solution to this common inefficiency, we borrowed concepts from established solutions we all now use to make buying decisions in our personal lives (Amazon, Airbnb, Yelp, Angie’s List, Pinterest, TrueCar, Zillow, etc.) Healthcare organizations need a better, digital way to define and share the ideas or projects they are considering, to detail objectives, success measures, categories, budgets, timelines, etc. to promote transparency and alignment. 

Additionally, while vendors use a CRM like Salesforce to track their sales activity with prospective and current clients, health systems do not have a similar system to capture and coordinate buying activity with the vendor community (and Salesforce is too complex to serve that purpose for buyers). Gaining visibility into past and current interactions and assessments of vendors and their products is essential to unify knowledge across diverse stakeholders.

As we focus as an industry on important topics like care coordination, healthcare organizations must also apply coordination to implement modern tools and processes that achieve the efficiency and alignment needed to make better decisions faster regarding vendor partners.

Readers Write: The Treatment for BCD (Big Company Disease): How to Streamline EHR Decision-Making

September 27, 2017 Readers Write 1 Comment

The Treatment for BCD (Big Company Disease): How to Streamline EHR Decision-Making
By David Butler, MD


David Butler, MD is associate CMIO of the Epic/GO project of NYC Health + Hospitals of New York, NY.

I’ll never forget it. I was presenting to a large group of physicians about how we need to implement, adopt, and standardize the EHR to meet quality metrics and decrease total cost of ownership. Before I could finish stating the “S-word” (standardization), a more senior physician looked over his glasses and declared, “Son, I’ve been in healthcare for over 30 years and I can tell you for a fact that this is simply not going to work.”

I had to agree with a portion of his statement. I also had a degree of skepticism about whether this would work or not. However, the former part of his statement caused me to pause and ask, “With all due respect, Doctor, have you been in THIS healthcare for 30 years?”

While I’m not sure he appreciated my Gen X retort, what I said was true. No one has been in today’s healthcare environment for 30 years. A senior executive mentor from McKinsey once told me, “If someone tells you that they understand healthcare today, they’re either lying or just have not been paying close enough attention.”

How We Got into This Mess

The US has wrapped technological advancements in healthcare around an antiquated legal and compliance system that was designed for the long-gone days of paper-based record keeping. We have essentially paved the cow path. Years after these technical infrastructures in healthcare have been hardwired and codified, we are now asking the question, “How can we unwind this and do it the right way?”

Unfortunately, much of the capital dollars and funding that attained the EHR are no longer available to optimize the EHR (understatement of the year). Very few practicing physicians have the time or legal prowess to navigate a fleet of internal compliance, risk, legal, and information technology “experts” who have all agreed that “x should not be turned on.”

All is not lost, though. We have figured out ways to map and execute the transition to digital healthcare, but we must do it together. EHR optimization starts with governance. In this article, I will share three guiding questions that physicians and physician executives can use to assure that their voices are heard and prioritized when EHR decisions are being made. Just as we do not triage a patient with a cough prior to one with chest pain, we must use this same approach when we collectively request changes to the EHR software.

BCD: Big Company Disease

Rule of thumb: The bigger the healthcare system, the slower it is to change.

At one large multi-hospital facility that shared a single instance of the EHR, a physician stated that it took three months for their EHR team to fix a misspelling on the after-visit clinical summary that we give to the patient. The road to EHR optimization is not a straight one, and you need a team to decide what you’re going to do every time you encounter a fork or a bend. Who makes decisions about EHRs in health systems? If you’re like most, this is a staggeringly complex and confusing process (and calling it a process at all might be generous). You’re likely suffering from BCD, or big company disease.

BCD is an epidemic. Hospitals and health systems must implement technology that helps them meet the goals of 2017 healthcare, Value-based purchasing, consumerism, MIPS/MACRA, ACOs … the list goes on. These goals require change in clinical and technology operations and this change must occur rapidly — or at least much more rapidly than the current pace at most organizations — to meet them.

BCD is fraught with complex requirements, departmental silos, poor stakeholder representation, and highly-educated and well-intentioned leaders whose decision-making authority has been stretched much further than their own comfort zones (and pay grades). As we’re working on the cure for BCD, these treatment options will alleviate many of its symptoms.

Three Questions to Establish Governance for EHR Optimization

1. Who makes the decisions about the EHR?

The first step of governance for EHR optimization is determining who the decision-makers are. If you employ a democratic philosophy of governance, then you must first decide what is your constitution (some call it a mission statement). This constitution drives every decision that you make, including who needs to be at the table from the key stakeholder groups: operations, clinical, and IT. These three functional branches of government compose the three-legged stool governance model. If you’re a large system, you’re also going to need three levels of stakeholders: site/local leadership, regional leadership, and corporate/system leadership. No matter how you answer this question, your governance model must be clearly defined and communicated throughout the organization.

2. What are your priorities?

Everything can’t be a priority. All optimization efforts, requests, and enhancements are certainly NOT created equal. After asking the two most critical questions—“can we?” and “should we?”—I often use and recommend adapting an impact effort matrix to determine the clinical impact and resource requirements for EHR project request prioritization:

  • Quadrant 1: The “Just do it” quadrant. High clinical impact, minimal resources.
  • Quadrant 2: The “Get the geeks, the execs, and the checkbook” quadrant. High clinical impact, high resources.
  • Quadrant 3: The “That’s cool” quadrant. Low clinical impact, low resources.
  • Quadrant 4: The “Diva” quadrant. Low clinical impact, high resources.


Before you do anything, make sure you know what quadrant you’re working in! Many organizations have found success building upon this simple framework with Lean or other process improvement methodologies.

3. How are we going to make this happen?

You have your governance model established with balanced representation or your three-legged stool. Now, how do you get these people together to actually use the framework to make critical EHR optimization decisions? This is one that plagues virtually every organization I work with. “I didn’t know WE decided that” or “when are the meetings even held?” are common stakeholder grievances.

When the governance group can’t all come together, you end up making decisions based on time constraints instead of thoughtful ones with the right people around the table. Keys to recovering from BCD include:

  • Clear roles and responsibilities. What is each committee responsible for accomplishing at the end of the day? (Oh, this is called a charter.) These obligations should be fully defined and every committee member should know this for their committee, as well as the others in their organization.
  • Effective meeting management and tools. Before each governance meeting, tackle these items. Determine which decisions, if any, can be made without meeting. Pre-plan the meeting – set the agenda for this meeting by highlighting what was discussed at the last meeting and the action items/decisions to be made at the meeting. Meeting polls — If your governance committee is large, this is a great way to determine consensus quickly. Virtual meeting tools exist that make interaction and measurement much easier.
  • Transparent decision-making and prioritization. You have to share information and you have to share it often. Send out a post-meeting debrief to the committee and the other committees within your organization. Make sure everyone knows how the decision was made and how they can escalate an issue. IT should not be the first place to go to get an EHR solution fixed—physician leadership should determine this. Remember: EHR optimization is a clinical project, not a technical project.

Large-scale EHR optimization starts with an effective, mission-aligned, and accountable governance process. Nagging symptoms of BCD may linger longer than you care for, but with the treatment plan I’ve prescribed above, you’ll be in a much better state to move your organization forward.

Readers Write: The Problem List is the Problem

September 27, 2017 Readers Write 7 Comments

The Problem List is the Problem
By Sam Bierstock, MD


Sam Bierstock, MD is president and founder of Champions in Healthcare, LLC. He developed and trademarked the concept of Thoughtflow.

For years we have heard that the goal is for complete interoperability of electronic health record systems (EHRs). While this must certainly be achieved in the ultimate attainment of confluent data availability, it is important to be sure that exchanged data from differing systems is consistent. In this regard, we have a huge problem – problem lists.

As an interesting exercise, ask any physician the difference between a diagnosis and a problem. It will readily be seen that very few know the difference, and those that offer an explanation of the difference will provide a wide variety of definitions. As a result, problem lists are loaded with a combination of current and inactive complaints, symptoms, and diagnoses, and generally are a mess. They are inconsistent, unmaintained, confusing. and vary between systems for the same patient. A patient who has been admitted to different hospitals using different EHRs will have a different problem list at each hospital, not to mention any problem lists that may exist in EHRs of physicians that they have seen as outpatients.

While I am unaware of any actual studies to assess the cost of inconsistent problem lists to the healthcare system, these costs must be enormous. Medical record departments and coders spend hours sorting out diagnoses since problem lists frequently populate discharge summaries from which billing data is extracted. Active and inactive problems must be identified and separated out. For instance, “Status Post Myocardial Infarction 1999” may be on the list but is not billable. Symptoms frequently appear and may confuse or diminish reimbursement or be entirely non-reimbursable. Productive cough for three days for instance is a symptom, not a diagnosis, and yet is typical of the types of problems currently listed.

In 1970, I was a medical student at the University of Vermont when a dynamic, energetic, brilliant, and visionary physician who had recently joined the university staff brought his radical ideas about computerizing patient histories and findings to the attention of the industry. His name was Larry Weed, MD, and his system, “The Problem-Oriented Medical Record”, was rapidly changing clinical documentation across the country. A level of logic and thinking that had been missing in the assessment, planning, and treatment of patients’ conditions was being recognized for its enormous value. Problems included medical diagnoses as well as social issues and all matters that need to be considered to treat patients in their entirety.

But Dr. Weed’s system got sidetracked in the ensuing years by the introduction of independent electronic record systems designed by corporate vendors. In general, these system designers had a very poor understanding of the Problem-Oriented Medical Record, and as a result, all tended to handle diagnoses and problem lists differently (if they had them at all). As a result, decades later, few physicians can differentiate between “problems” and “diagnoses” and problem lists have degenerated into a morass of confusion.

For more than a decade, I had been advocating an approach to EHR design that differed from the standard approach of existing systems which were based upon reproduction of text-book clinician “workflows.” Although they frequently followed the textbook workflows, these designs were inefficient and had nothing to do with the way physicians think and work and have historically been abysmally received. Most physicians use EHRs today primarily because of legislative mandates and Meaningful Use requirements, but there is almost universal agreement that they are cumbersome and reduce efficiencies.

Since 2003, I have advocated a different approach which I call (and have trademarked) Thoughtflow and which I first described in the literature in 2004 – supporting the way physicians access, assess, prioritize, and act upon data. In other words, how they think and act.

One of the areas that can be addressed using this approach is the Problem List. As a first step, I had to decide what made it to the list in the first place, what constitutes a “problem.” I picked up the phone and I called Larry Weed. Now well into his 90s, Dr. Weed was as brilliant as ever, and I quickly learned the answer to my question about the difference between a problem and a diagnosis.

A problem, Dr. Weed explained, is the highest level of the current diagnosis. Understanding this basic principal provides a path to cleaning up problem lists, keeping them consistent and updated and maintaining active and inactive problems. EHR system designers do not understand this any better than most physicians do, and as a result, each has a different approach to the construction of problem lists in their systems.


Consider the following scenario:

A patient is seen in the emergency room with a five-day history of abdominal pain and constipation of unknown origin, and subsequently admitted for evaluation. The diagnosis is constipation and abdominal pain, which may appear as a combined problem or two separate problems on the admitting history and physical.

Problem #1: Abdominal pain x 5 days
Problem #2: Constipation

The admitting doctor orders a GI consultation and some baseline studies including a flat plate x-ray of the abdomen. On the first day of admission, the x-ray shows an abdominal mass. The Problem List may now look like this:

Problem #1: Abdominal pain x 5 days
Problem #2: Constipation
Problem #3: Abdominal mass

On day 2, the patient has an exploratory laparotomy and is found to have carcinoma of the colon.

Problem #1: Abdominal pain x 5 days
Problem #2: Constipation
Problem #3: Abdominal mass
Problem #4: Carcinoma of the colon

At this point, and at the sole discretion of the attending physician, Problems 1, 2 and 3 may be removed entirely from the Problem List, may be moved to inactive problems, or may stay on the list. They may stay there for some time or be moved by a future physician providing care for a different problem. There are no fixed rules.

However, if Dr. Weed’s dictum is applied, consistency is attained.

On day 1, when the x-ray shows an abdominal mass, “Abdominal mass” becomes the highest level of the current diagnosis, and therefore replaces both “Constipation” and “Abdominal pain X 5 days,” becoming Problem # 1. In my system design, clicking on the updated Problem #1 “Abdominal mass” resulted in a drop-down menu showing, in chronological order, the previous problems leading to the most current and the dates. So clicking on “Problem # 1 Abdominal mass” produced a drop-down that looked like this:


On day 2, after a diagnosis of Carcinoma of the colon, Problem #1 is further updated:

Clicking on each drop-down menu reveals configurable granular data dependent on user preferences.

Consistent with the concept of Thoughtflow as opposed to workflow, the design minimized any requirement for the user to update the problem list. Using vocabulary standards, clinical decision support software, language processing, and automated ICD-10 coding, the Problem Lists can be automatically updated. They can also automatically exported to an evolving discharge summary from which the automated coding provided billing and reimbursement data. The potential savings in time spend scouring charts by coders can be appreciated, as well as the accuracy of coding and assurance of reimbursement.

In addition, updated and current Problem Lists can also populate any medical summary screens which may have displayed overall summary data such as medications, allergies, past surgeries, etc. This assures an accurate, consistent summary of past maximally updated problems, or in other words, the highest level of current diagnoses. Symptom and other extraneous data will then not appear to congest the list and add to assessment and billing confusion.

Rapid maintenance of the list can be attained by simply dragging a problem that was inactive or resolved to the corresponding list. A problem “Myocardial Infarction 1990” could be moved at a physician or coder’s discretion to an Inactive or Resolved Problem list, while “Atherosclerotic Coronary Vascular Disease” remains as an active problem. Problems could be prioritized in order by simply dragging them to the desired position, and numbers changed automatically as the new position was attained or as
problems were added or removed.

The inconsistency of Problem Lists is an inadequately discussed, but universally recognized issue with enormous costs to the healthcare system, both financial and with respect to quality of care. The issue also generates an enormous challenge to EHR design and to the assurance of interoperable, consistent patient information across the spectrum of healthcare systems, physician offices, disparate hospitals, and payers.

Readers Write: Malware Lessons Shared: Seven Key Questions for Health Leaders to Ask About Cyber Preparedness

August 30, 2017 Readers Write 1 Comment

Malware Lessons Shared: Seven Key Questions for Health Leaders to Ask About Cyber Preparedness
By Joe Petro


Joe Petro is SVP of engineering for the healthcare division of Nuance Communications.

As business leaders, we must confront a new reality: our organizations are facing an unprecedented threat from cybercrime. The number of cyber incidents is growing and the nature of the attacks is evolving. They are becoming faster, more sophisticated, and more potentially destructive. As the severity of incidents increases, the knowledge to address the technical aspects and manage through an attack has become essential to our skill set.

For those reasons, we think it’s important to share some of the lessons we’ve learned since we were affected by a global malware incident on June 27. Cybersecurity experts later identified the malware as NotPetya, highly sophisticated malware written to provide disruption and destruction rather than to demand ransom. It spread quickly, and unlike some malware, patching alone would not have stopped its propagation.

Our first priority was to contain the incident and protect our customers. This meant immediately commencing shut-down procedures across our global network to contain the spread of the malware. These actions affected our ability to communicate with our customers, employees, and other stakeholders, and we immediately sought alternative ways to alert them to the situation. To ensure they had up-to-date information, we hosted daily conference calls and corresponded via email with affected clients. We regularly posted updates to a dedicated Web page in addition to conducting a very large number of one-on-one client calls and meetings.

Importantly, we were able to tell them that NotPetya does not have the ability to copy or extract file contents from affected systems or allow any unauthorized party to view file contents on affected systems. In other words, no Nuance customer information was altered, lost, or removed by the malware.

After containing the spread of the malware, our focus turned to restoring our clients to full functionality. Our dedicated staff—along with third-party experts in cybersecurity and forensics—rapidly initiated restoration efforts. At the same time, we enhanced our security against similar future incidents to ensure we emerge from this incident with an even more secure operating environment.

We are committed to sharing the knowledge we have gained from our own response and recovery process. The more we know about malware like NotPetya, the more powerful we all can be in combatting future cybercrimes. Early lessons include:

  • Incident notification protocols should be as simple as possible, with multiple layers of redundancy to ensure stakeholder communication can continue at all times. This is particularly critical in the early days of response, when normal channels may not be viable.
  • Increase network segmentation, including adding micro-segmentation.
  • Even fully patched Windows machines remain vulnerable to certain exploits and vulnerabilities. We have deployed a hardening process that disables SMBv1, enables additional blocks on host-based firewalls including blocking unnecessary SMB ports, disables unnecessary usage of WMI and PsExec, disables unnecessary admin shares, increases logging levels, and validates that each system meets a minimum baseline of security measures.
  • Cyberattacks can occur very quickly, challenging even the best prevention systems. Thus, the best strategy is a combination of prevention, detection, and containment.

Healthcare and IT leaders need to ask the right questions now so that they can be better prepared for a malware incident in the future. Below are seven important security questions every leader should consider:

  1. Cybercrime is part of the new reality for every company, organization, and person. What can you be doing now to prepare for this scenario?
  2. How comprehensive are your security policies, and do those policies actually translate into deployed security capabilities?
  3. Have you developed a crisis and disaster plan and communicated it broadly throughout your organization?
  4. How would you communicate to your staff, your board, your customers, and your patients?
  5. What are your primary vulnerabilities? What measures are you taking to ensure patient data is protected?
  6. Do you understand and align with your vendors’ security policies and do you have the appropriate validation and/or risk assessment programs in place?
  7. Have you identified a team of outside experts to help in case of an incident, including cyber security firms?

    Readers Write: Response to Webinar, “3 Secrets to Leadership for Women in Healthcare IT”

    August 30, 2017 Readers Write 1 Comment

    Response to Webinar, “3 Secrets to Leadership for Women in Healthcare IT”
    By Helen Waters


    Helen Waters is executive vice president of sales and marketing with Meditech of Westwood, MA.

    Recently, I was inspired by a HIStalk webinar, “3 Secrets to Leadership Success for Women in Healthcare IT,” hosted by two female executives of health IT companies, Liz Johnson and Nancy Ham. During the webinar, Ham and Johnson provided valuable advice to women who are interested in progressing in their careers to a leadership position, but who may experience unconscious or conscious gender bias.

    I wasn’t surprised to see that organizations experience higher profits when women represent at least 30 percent of their executive leadership teams. I believe when men and women rid themselves of gender biases and come together at the table, great things will happen.

    There are thousands of women in high-powered positions making a difference around the world every day. Still, as Ham and Johnson pointed out, the percentage of women in leadership positions — particularly in healthcare IT — remains low. In addition, there are thousands of women who are capable of so much more, who would make great leaders and heads of companies, but who lack confidence.

    I wholeheartedly agree with Ham and Johnson’s three secrets  — mastering negotiation, closing the confidence gap, and the networking effect. However, if I could add one more key ingredient to the list, it would be to channel your passion.

    Climbing the corporate ladder and breaking the glass ceiling is no easy feat. It takes focus, drive, the belief that you will succeed, and the passion to make it happen. Not only have passion for what you do and your company, but for your customers and the industry you work in. If you don’t love the company you work for or enjoy your day-to-day life at work, then maybe it’s time for a change.

    When you love what you do and show up to work excited about what you will tackle and overcome each day, the confidence gap will get smaller and smaller. Why? Because when you’re passionate about something, it will be noticed by others. The enthusiasm and positive energy you bring to work and how you treat and communicate with others will have an impact on your ability to inspire and lead others.

    The determination and motivation that passion drives will set you apart, push you to produce your best work, excite others, build awareness, and lead you to your goals, whether it’s a position in management, the C-suite, or on the board.

    My passion, commitment, and love for my company and industry runs deep. My love of healthcare and technology has kept me intrigued and stimulated at my company for over 25 years. I believe in my case, knowing that what I do contributes to keeping people safe in one of their most vulnerable times in life (as a patient) is what keeps me going and gives a great sense of fulfillment.

    My goal is to help my company continue to grow and flourish, but more importantly, to help staff grow. I strive to develop the next generation of leaders who are as passionate and inspired as I am when it comes to healthcare. Hopefully during my tenure, I will have influenced a substantial number of people and contributed to the future of the company through them.

    In my personal life, my family is my passion. I’ve always wanted to show my daughters that anything is possible, to always be open to learning something new, to follow their passion, and do what makes them feel fulfilled.

    What are you passionate about?

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