Readers Write: ACA versus ICD-10: US Media Failure and Why I Really Can’t Sleep At Night

ACA versus ICD-10: US Media Failure and Why I Really Can’t Sleep At Night
By Rebecca Wiedmeyer

Thanks to the ever-pervasive, sound bite-driven American media outlets, many citizens have predisposed notions surrounding the Affordable Care Act (a.k.a Obamacare) and the “mishandling” of Healthcare.gov (for anyone out of the loop, there has been a struggle for individuals to log on and apply for the payer program offered by the ACA.) The  US mass media, along with the American government, has made this a key election issue and a prequel to the political debates  ahead of us in 2016. If the ACA is keeping you awake at night, I challenge you to consider the opinion of an insider in the field.

In its infancy, the ACA was a platform that immediately drew attention from political parties, physicians, and many in the healthcare field (myself included.) Subsequent to its introduction, this bill has morphed into a 2,700+  page, over-earmarked staple of Congress that, while admirably striving for change in healthcare, is not quite what either side of party lines was aiming to achieve. Meanwhile, there are initiatives and deadlines that loom ominously. Foremost, at least in my mind, is ICD-10 compliance.

Less than a year away, the ICD-10 movement is set to completely disrupt the current workflows, reimbursement  models, and documentation practices within healthcare IT. As a nation, we are set to transition between the current system of ICD-9 (~18,000 codes) to the WHO-approved (as of 20 years ago) system of coding, which utilizes around 146,000 codes. As anyone in HIT can imagine, this will have trickle-down effects that are unfathomable. Revenue will almost certainly be lost, practices will bankrupt, vendors will go out of business, and, the most incomprehensible part to me, this issue seems to be low on the list of agenda items for the American public, but also our field.

Not that there are a lack of exceptions. Many EHR vendors I have collaborated with, for instance, have a firm grasp of the gravity of ICD-10. Even more encouraging, there are vendors specializing in the education of physicians and directors, as well as billing offices and coders, with regards to compliance. However, with less than a year to go, the clock is ticking.

I have spoken candidly with industry executives who admitted building into budget up to a 70 percent revenue loss upon the introduction to ICD-10. Physicians deserve better than that and patients deserve better than that, not to mention the vendors that are at the mercy of government policy and its whim (not to mention client demands.) Agenda-setting has gone too far.

For any sleepless nights regarding the ACA, I am the first to concede it is far from perfect, so perhaps your anxiety is not unfounded. However, a lack of understanding of what is ahead looms as a far more dangerous challenge than a lackluster website performance of the moment.

Rebecca Wiedmeyer is chief communications officer of EHR Scope.

Readers Write: Big Data: Enabling the Future of Healthcare

Big Data: Enabling the Future of Healthcare
By Anthony Jones, MD

Everyone’s talking about the importance of big data in healthcare. Yet as the data piles up – most of it still in different silos – health systems are struggling to turn big data from just a concept into a reality. Here’s how I see big data having the biggest impact on the health of populations, both today and tomorrow.

Most healthcare organizations today are using two sets of data: retrospective (basic event-based information collected from medical records or insurance claims) and real-time clinical (the information captured and presented at the point of care  — imaging, blood pressure, oxygen saturation , heart rate, etc.). For example, if a diabetic patient enters the hospital complaining about numbness in their toes, instead of immediately assuming the cause is their diabetes, the clinician could monitor their blood flow and oxygen saturation and potentially determine if there’s something more threatening — like an aneurism or stroke — around the corner.

Where real pioneering technologies have succeeded is putting these two data pieces together in a way that clinicians can grasp the relevant information and use it to identify trends that will impact the future of healthcare – predictive analytics. So for example, if more diabetic patients start to present a similar trend of numbness in their toes, the coupling of real-time and retrospective data can potentially help doctors analyze how treatments will work on a particular population. This gives hospitals a much stronger ability to develop preventative and longer-term services customized for their patients.

Now what if we take data a step further and introduce gene sequencing into the picture? Today, gene sequencing is used primarily to determine the course of treatment for cancer patients. As we reach an inflection point in the cost of gene sequencing, this data will be routinely added to a patient’s health record. Imagine the kind of impact this data will have on treating infectious diseases, where hours and even minutes matter. The next time there’s a disease outbreak, we could potentially know the genome of the infectious organism, the susceptibility of the organism to various antibiotic therapies, and determine the correct course of action without wasting precious resources in trial and error.

Undoubtedly, we have yet to determine the most practical, cost effective way to manage this kind of data. To put it into perspective, the human body contains nearly 150 trillion gigabytes of information. Imagine collecting that kind of data for an entire population.

There’s no doubt this is a mammoth task, and while we might not be there yet, we are certainly getting closer. There are still challenges ahead: organizations are learning lessons from the early adopters and trying to determine the best ways to cooperate and share data. Undoubtedly the amount of investment required to make big data technologies work is more than what a single segment of the market can afford. That means all stakeholders, including pharma, will have to work toward a common vision. But with Accountable Care Organizations paving the path for payers and providers to work more closely together, we are heading toward success, and more importantly, better patient care.

Anthony Jones, MD is chief marketing officer, patient care and clinical informatics, for Philips Healthcare.

Readers Write: Epic Concerns

Epic Concerns
By Long-Time Epic Customer

Wake Forest Baptist is just the tip of the iceberg for Epic clients struggling with revenue, based on conversations I’d had with various contacts at UGM. There was quite the buzz about a large number of customers with revenue concerns who are not hitting the news. Yet.

We installed Epic years ago, but have seen a vast difference between our prior experience and a recent rollout of newer products. The method where time was taken to help us build our own system has been replaced by a rushed, prefab Model system installed by staff where even the advisers and escalation points at Epic have little knowledge of their applications. Epic has always had newer people, but it was much more common to have advisers during the install who did have experience to watch for pitfalls.

Though today’s economy is certainly a large factor in any revenue struggles, I am unsurprised by stories like Wake Forest or Maine and believe Epic should have seen some of it coming. We had enough experience with Epic to spot trouble with new products. New clients likely don’t have that built up yet, and they probably rolled off the cliff with nothing but green lights on Epic’s reviews of their install progress from newbies who didn’t know any better.

It feels like Epic tossed a winning formula in favor of a faster, cheaper install. What many of us are getting ends up being cheaper, indeed. That is a tough contrast to reconcile at UGM. After getting my ears blown out at an expensive, new, rarely-used auditorium that was just built to replace a barely older, rarely-used auditorium, Judy spoke at length about how the campus was cost-efficient and made employees more productive. Many of us are developing an alternative thesis, which is that productivity has been getting squeezed (and compromised) to support the costs of the campus.

I want to keep loving Epic. They are still good, but their services are declining.  The campus strikes a nerve with many clients who justifiably wonder whether our vendor is investing in the things that made them great when we’re getting answers, solutions, fixes, and reports slower than ever.

Readers Write: Applying Lean Startup Principles to Optimization

Applying Lean Startup Principles to Optimization
By Tyler Smith

If you haven’t had the chance to read Eric Ries’ 2011 bestseller The Lean Startup, I highly recommend adding it to your reading list. Typically, I am not a big fan of business literature, but I found the book particularly stimulating, largely because its concepts can be readily applied to that currently hot phase of EMR projects – optimization.

After all, entrepreneurism, Ries insists, is not limited to dorm rooms and Silicon Valley garages. Instead, Ries contends that the processes inherent to entrepreneurism can and should take place in large, established institutions – say large healthcare organizations – via the efforts of "intrapreneurs.” Ries goes on to outline the principles of the lean startup and Ries’ fourth principle of the lean startup – Build-Measure-Learn – provides an excellent framework for the optimization phase of EMR systems projects.

The build-measure-learn feedback loop, according to Ries, is one of the key activities that entrepreneurs and “intrapreneurs” alike must perform. In the build-measure-learn feedback loop, minimum viable products (MVPs) are built by entrepreneurs to test certain product and market hypotheses. These MVPs are launched quickly in order to enable entrepreneurs to gather relevant data fast – prior to making large investments of time or money. Using the data generated by the MVP launch, entrepreneurs must then swiftly validate or refute their hypotheses. If the MVP data does not clearly point to success, then the entrepreneurs must use what they learn about their MVP to iterate by building another prototype based upon a modified or newly formed hypothesis and start the cycle all over again.

Here is an example of how I see the feedback loop being utilized during EMR system optimization:

1. Hospital administrators have mandated that population management be the first major undertaking of the optimization team.
2. As the first order of business for the population management initiative, the optimization team is tasked with implementing a health maintenance alert mechanism.
3. While there are a number of different ways that the activity can be instituted, the optimization team meets and decides that since feedback has indicated that providers prefer mobile alerts to desktop alerts, the team will implement the transmission of daily, HIPAA-compliant text message to providers that will provide the providers with patient specific alerts regarding patient health maintenance.
4. Using the small batch approach advocated by Ries, the optimization team implements the text messages for breast cancer screening and HIV screening only (their MVP) with the intention to expand the text message content to other conditions if the MVP is successful.
5. After implementation, the optimization team follows up with the end users every few days to check on the initiative, only to learn that most providers aren’t really using the functionality.
6. When the team queries staff, they learn that providers are not receiving the daily text message until after having seen the first patient of the day and are complaining that messages are long and cumbersome.
7. After reviewing the data, the team must decide whether the whole idea should be scrapped or whether a few tweaks will fix the MVP’s obvious issues.
8. The team theorizes that the lack of effectiveness of their MVP is due to lengthy and poorly timed text alerts.
9. Based upon their conclusion, the team makes the decision to send shorter messages at 5 a.m. each day.
10. The team builds and launches this new MVP and thus the loop starts over.

In many institutions where the build-measure-learn feedback loop is not utilized, optimization projects check off an optimization as complete after Step 4. What appears to be a premature ending of a particular initiative is not necessarily caused by a lack of understanding of the need for follow up, but is often due to the long list of optimizations that need to be executed. Teams falling into this category are often tasked with implementing a large quantity of optimizations or checking off a few high profile optimizations, but not explicitly tasked with actual optimization as the end result.

Teams in this aforementioned category fall prey to what Ries calls vanity metrics. As Ries warns, vanity metrics are sets of data which companies use to bolster their perceived success but do not really measure criteria that contribute to the actual stated goal. Teams tasked with long laundry lists of items to check off are prone to this trap. If simply going through and performing optimizations for a laundry list of topics allows the team to state that they have accomplished x number of optimizations and then tout this metric, but at the same time end users feel as if there has been no real optimization of the system, then this x number statistic is a vanity metric. Teams must avoid the allure of vanity metrics and ensure that a solid feedback loop is in place.

Recently, Dr. Val wrote of EMR, “My initial enthusiasm has turned to exasperation and near despondency.” She cited that she is not sure that simply getting the bugs out will fix the issue. I cannot comment specifically on Dr. Val’s issue, but I can only say that if the bugs are truly ever going to be got out, it is going to require more than checking optimization items off a list. The real optimization is going to come about via a fully robust effort by optimizers to build, measure, and learn. That is why the time is so ripe to apply lean startup principles to optimization.

Tyler Smith is a consultant with TJPS Consulting.

Readers Write: Organizational Mergers

Organizational Mergers
By Anonymous CIO

Last fall, a full asset merger of our hospital into a larger health system in the region was announced. This has become a common event in our state and was strategically important to our organization.

Both organizations had developed working relationships in several clinical areas over the years, so at least some synergy had already been established. Geographically, the merger appears logical and based on sound thinking. Ours will become branded as part of the larger, well-regarded health system, and positioned well to confront the ongoing evolution of health care in our region and the country.

The agreement amongst the parties established the agenda for IT. From the outset, project plans were developed and staffing focused on achieving important goals by the established milestone dates. Fortunately, some date slippage in the regulatory approval process provided us with a bit more breathing room than what was originally expected.

Short-term initiatives have included the following:

1. Establish connection between the entities and the trust among disparate networks to enable coexistence of e-mail, calendar, and access to each other’s systems.
2. Migration of all personnel to the health system’s payroll and human resources applications including the replacement of all aspects of time collection, payroll, and people management by Day 1.
3. Establish the larger health system’s financial systems as the final collector and reporter of all numbers and statistics, meaning that all data from our systems (comprised primarily of a core, integrated, community hospital system) would be fed to the designated systems of the larger enterprise. Support the consolidation of business office functions at the enterprise’s corporate headquarters.
4. Retain our clinical systems for now due to our progress with Meaningful Use, ICD-10, clinical documentation improvement, and local acceptance of that system. Become part of a larger enterprise-wide clinical system decision and migration within the next two to three years.
5. Continue local initiatives such as participation with HIE, ARRA Stage 2, expansion of our electronic patient records efforts, physician compliance with on-line documentation, and individual physician bonding efforts such as BYOD, electronic rounding tools, etc.
6. Replace our physician practice/EHR system deployment efforts with the solution provided by the health system.
7. Prepare for absorption of our IT infrastructure team (network, hardware, PC support) into that of the health system; retain the core applications team to continue to support our legacy system for the duration of its existence.
8. Prepare for my own absorption into the health system with a different title along with changing roles and responsibilities. This includes the adjustment of my vision and plans from that of a single entity CIO to a role that will cross all aspects of the enterprise.

Observations on the effort to date:

1. Attitude. Although it’s clear who will run (or, is running) the larger health enterprise, those who we’re working with from the health system have the strength of character not to conduct this combined work effort as a siege of greater over lesser. As a result, our team does not feel besieged, and cooperation prevails.
2. Project management. Efforts of this magnitude don’t go well without the expertise of highly engaged and empowered professionals to oversee the details. The health system has several of those and the ones assigned to our project are excellent.
3. Few versus many. Many project teams have been established to execute each of the planned efforts. It’s truly comical when our community hospital team shows up with so many of the same people for each effort while the health system often brings a unique set of experts. It’s the best visual representation of working vertically versus working horizontally that I’ve seen in a while.
4. Disagreement management. Both sides need a clear path of hierarchy to resolve differences in understanding of the goals. Even in the best of cases this can (and does) occur so a time-efficient escalation process is needed to discuss, digest, and resolve issues as they arise.

Readers Write: ICD-10: The Race is On and the Clock is Ticking

ICD-10: The Race is On and the Clock is Ticking
By Honora Roberts

For providers, the reality of healthcare has changed greatly in the past couple of years. Practicing medicine now revolves around an electronic health record, clinical decision support, and analytics. Reality will soon change again with a new and expanded coding “formulary,” ICD-10.

It’s no secret that this coding change spreads across every facet of operations, from clinical care and administration to finance, IT, and more. The move from the ICD-9 code set that has been in place since 1979 to ICD-10 represents a five-fold increase in the number of codes to learn, know, and apply. ICD-10 consists of 69,000 diagnosis codes (up from 14,000) and 72,000 procedure codes (up from 4,000.) Administrators, physicians, allied health professionals, billing departments, coding professionals, IT departments, and more face a new reality. The time to begin embracing this new reality is now, but where do you begin?

This shift to ICD-10 is a lot like “The Amazing Race” TV show in which teams race across cities and continents to find clues to their next required destination. While providers know the destination, they face tough terrain and unexpected obstacles. Start by knowing your greatest exposures – physician education and documentation improvements; loss of reimbursement; coder education; computer system and payer readiness; and regulatory compliance. Then focus on a couple of critical areas to avoid getting lost in this amazing race toward ICD-10 compliance.

Prioritize the 141,000. Despite the spike in number of codes, reality is that providers often will use a small subset of codes. To compress the initial transformation, begin prioritizing the codes most relevant to your institutions, physicians, and specialists. Once these are prioritized, you can begin mapping ICD-9 codes to the new ICD-10 code set. In essence, you’re starting by building an initial cross-walk or critical path between the two coding standards.

Test and remediate. Make sure the technical upgrades perform and deliver as designed, then test and remediate before they are used in the real world. When testing, set up real people in real workflows. Include physicians and nurses, specialists, coders, and others who provide a broad view of the systems and workflows. This testing will allow you to pinpoint common errors so that the technology can be customized to catch errors that can harm patients.

Improve documentation. Physicians and clinicians don’t care about ICD-10. They do care about improving the quality of care and doing no harm. Emphasize documentation improvement and provide the education, tools and process improvements to achieve improved documentation that, by the way, also complies with ICD-10.

Pursue proficiency. Your people will make the difference in success. Making sure they succeed requires training. Be sure to target training programs to your personnel’s specific roles and usage of ICD-10 codes. Role-based learning will improve speed to proficiency, improved adoption rates, and overall sustainability of your organization. Once staff members gain confidence on routine tasks, they will quickly gain efficiency that is sustainable over time. Job aids and reusability of learning are tools that reinforce learning and confidence. Start with your coders, if you haven’t already. Track results — comprehensive adoption requires continuous oversight and measurement.

Optimize beyond the transition. Once you’ve met the deadline, perform a post-deadline assessment and chart review to begin a genuine clinical documentation improvement program. The baseline you established at the start of the process will help you identify problem areas and remediate.

Manage the risk. Knowing your current situation and associated risks is a great place to start. By knowing the risk, you can establish plans to lessen their impact such as:

• Adjust budgets and develop strategies for potential reimbursement reductions
• Plan for lower productivity during the transition, which might take up to a year beyond October 1, 2014
• Developing contingency plans for high-risk areas, such as high-volume departments or adoption concerns.
• Instituting a well-defined and well-communicated governance and escalation process for issues that arise

Lead the change. Acknowledge that this change isn’t a technology or systems integration project alone. It is a significant organizational change. It involves people, processes, workflows, and technologies that extend beyond walls and buildings. A change this large needs to be managed from the very top of the organization and employees need to hear frequent updates to let them know how the organization as a whole is doing.

Ultimately, most providers in the United States are scurrying to execute a plan to make the transition to ICD-10. You still have time, but the clock is ticking. Don’t get lost in the details; focus on the critical few areas that will make or break the transition for your organization. Through support from your internal team—and the expertise from quality vendors, consultants and other experts—compliance is achievable.

Honora Roberts is vice president of health provider services at Xerox.

Readers Write: ONC Mission Reflections

ONC Mission Reflections
By Helen Figge, CPHIMS, FHIMSS

The leadership at ONC will be shifting a bit as Farzad Mostashari and David Muntz return to the private sector, having given the industry another steep dose of healthcare leadership excellence. It has been appreciated for some time now that the Office of the National Coordinator for Health Information Technology (ONC) was meant to be a compass to support the adoption of various pieces of health information technology, to promote a unified health information exchange platform, and to improve health care for us all. But any compass needs great leaders to man the ship. Not only leaders with skills to lead, but character traits steeped in ethical and wisdom offering guidance. Farzad and David were those captains that moved us forward with the national healthcare IT efforts through their decency, ability to lead by example, and just a genuine sense of being a very nice person that anyone would want to follow or work side by side with.

Remembering the inception of ONC, where many of us hold this office with high regard and respect, hoping that policies created for our healthcare delivery will minimize medical errors while simultaneously aspiring healthcare stakeholders to share patient information all to improve patient care. Payer and the government had aspirations these ONC programs would save money by improving efficiency.

We can conclude however that not all healthcare providers have fully embraced these technologies, but many of the healthcare providers have indeed done so and successfully thanks to the leadership of the past ONC leaders but now recently these two respected individuals in healthcare IT today.

So as we see these two individuals depart ONC, their legacies have indeed culminated into an ongoing improvement in the delivery of healthcare and leaving their posts having helped and move forward the agenda for us all in healthcare reform.

Farzad, while intelligent was also extremely charismatic helping to catapult the acronym “EHRs” into our daily healthcare conversations. He talked about EHRs like the latest and greatest gadget we all needed to try. David will leave behind a legacy of true collaboration and mentoring others in the healthcare IT landscape where often times it was a language in and of itself. David made healthcare IT logical and worthy of conversation even to those not so tech savvy. David’s ability of being extremely diligent and insightful while creating the conversation around healthcare technology was welcomed by all the non-CIOs as well as his peers in the industry. That is a true leader.

Often times we hear the phrase “it takes a village” to accomplish something. And yes that is quite true, but a true leader of that village, listens, digests, analyzes, and then reacts to a situation. A true leader does not lead by intimidation or dictatorship, but though consensus and character traits of leaving a place better than how it was found. Farzad and David each had their own attributes, but together created a uniform approach to an otherwise confusing state of healthcare affairs. These two individuals leave legacies of offering leadership through example and while their physical presence will be missed, their polices and professional attributes that have created the current ONC landscape will move forward, with another group of leaders who we all hope have the same level of integrity and respect these two have had from the industry at large.

Remember, someone wise once said, “Tthe world is filled with 99 percent followers and 1 percent true leaders”. Farzad and David fit into the 1 percent group quite comfortably.

Helen Figge, CPHIMS, FHIMSS is is VP of clinical integration for Alere ACS.

Readers Write: Maintaining Customer Loyalty Despite Our Mistakes

Maintaining Customer Loyalty Despite Our Mistakes
By Ryan Secan, MD, MPH

Who can spot the difference between these two uses of the words “I’m sorry”:

• “I’m sorry you have a black eye” vs. “I’m sorry I punched you in the face”
• “I’m sorry you lost money in a Ponzi scheme” vs. “I’m sorry I stole all of your money”
• “I’m sorry you need another operation” vs. “I’m sorry I left an instrument in your abdomen”

In the first cases, “I’m sorry” is an expression of sympathy, in the second, it is an apology. The word that follows “sorry” makes all the difference. “I’m sorry you…” is an expression of sympathy, “I’m sorry I…” is an apology (also note the passive voice in the first examples vs. active voice in the second – this is classic for the “mistakes were made” rhetorical device).

It’s easy to see the difference in the above examples. The tough part is that when we’re deep in a situation (and maybe we’re feeling shame, or embarrassment, or want to avoid responsibility) it is easy to offer sympathy to someone who really deserves an apology. The victim dealing with the bad outcome, while likely appreciative of your sympathy, really wants and deserves an apology. Regardless of how much sympathy you offer, on some level, they are not going to be satisfied without a true apology.

In all aspects of life, there are occasional bad outcomes. As a physician, I unfortunately see these far too frequently. These can be in our business or personal relationships as well. Bad outcomes often take place despite our very best efforts to prevent them. The universe isn’t always fair.

However, sometimes we make mistakes that lead to the bad outcomes. Since we all want to provide great customer service (or have high quality relationships in our personal lives), these bad outcomes need to be addressed. In medicine, culture is finally shifting away from the expression of sympathy to the apology (when appropriate). At the University of Michigan, a comprehensive medical disclosure policy (including an offer of compensation) has been put into place leading to a significant decrease in new claims, lawsuits, and costs. Part of the reason this policy has been successful is that it includes a discussion of the plan for preventing the same mistake for happening again.

Also, don’t use the word “but” in your apology and expect it to mean something. Think of one of the examples above, and how it would sound with a “but” in it:

• “I’m sorry I punched you in the face, but …”

What can you possibly say after the “but”, that isn’t an attempt to weasel out of responsibility and negate the apology? While you should explain what happened (and what you’re going to do to prevent it from happening again), don’t try to qualify your apology with it. Remember, even if they haven’t heard the saying before, intuitively, people know that “everything that comes before the ‘but’ is BS.”

The next time you make a mistake with a customer or in your personal life (and we know it’s going to happen soon enough), consider offering a sincere apology – (active voice, “I’m sorry I”, no “but”, best possible redress, and plan for prevention in the future). You might be surprised at how well this improves your customer’s loyalty.

Ryan Secan, MD, MPH is chief medical officer of MedAptus.

Readers Write: The True Benefit of Big Data in Healthcare: A Perspective from the Industry

The True Benefit of Big Data in Healthcare: A Perspective from the Industry
By Rich Temple

In response to a September 9, 2013 “Readers Write” article that suggests “big data” is the next boondoggle, I would like to illustrate the promise of big data, also referred to as business intelligence and analytics (BI) in healthcare. In that post, the author alludes to the challenges faced by industries embarking on big data journeys dating back to the 1960s.

While the struggles he noted were valid through those experiences, so much is different now in terms of the absolute necessity of big data in healthcare, as well as the exponentially-improved technology that can crunch numbers in nanoseconds. We need to recognize that the game has changed and now is the time for BI to make a significant impact to improve healthcare.

In general, broad concepts such as BI do have the potential to run aground in industries where they are treated as “nice to have.” The healthcare industry in 2013 is at a key inflection point where it absolutely cannot move forward without key BI and analytics as an engine for these healthcare reform initiatives, as well as many others:

• Accountable Care Organizations (ACOs)
• Population Health
• Health Information Exchanges (HIEs)
• Health Insurance Exchanges (HIXs)
• Value-based purchasing reimbursement initiatives
• Reporting regulatory requirements around quality and cost coming from the government

BI and analytics become the fuel that powers the healthcare industry’s ability to fulfill its obligations to all its stakeholders under healthcare reform. If we are going to improve the quality of care necessary for the above mentioned healthcare programs, BI will need to be used to provide information with the highest level of integrity possible for accurate decision-making across the healthcare industry. When a concept reaches a critical mass as an essential business driver for growth and sustainability for healthcare providers, it should not be seen as a boondoggle.

While healthcare still has quite a way to go on its journey toward true interoperability across systems, recent initiatives, such as Meaningful Use, ACOs, HIEs, among others, point to just how much has been achieved in mitigating the data integrity challenges that the author notes. These challenges are not only being addressed, but are in the process of being solved by current initiatives to connect systems and organization through:

• HIEs
• HIXs
• Interoperability between hospitals and their affiliated physician networks
• ACOs

Recent mandates involving coalescing around particular standards (e.g., LOINC) also help facilitate interoperability. As these challenges continue to be worked through, it becomes that much easier to extract truly actionable information from the mounds of data that are housed in our disparate healthcare information systems.

Another key differentiator that makes BI not only possible, but achievable in ways that it could never have been until recently, is the advanced technology that is now available to process staggering amounts of data in time units measured in seconds or minutes, as opposed to weeks, months, or years. With new BI technologies such as Hadoop, it is no longer ridiculous to assume that an organization can mine many terabytes of data in just seconds.

In the past, organizations had no way to access all that data in nearly real-time, rendering a lot of their efforts to come to naught. Today, we do have that capability. When today’s consumer cell phones contain more sophisticated computing technology than the Apollo rockets that landed on the moon, it has to be taken as a given that certain challenges that industries grappled with in the past no longer apply to today’s world of BI.

Given the tumult in healthcare and the new abilities to use data in ways previously thought impossible, I see BI not as a boondoggle, but as an essential component of any healthcare organization’s survivability. The author is spot-on when he expresses concerns about the challenges of harmonizing data across disparate provider and functional systems; all systems, whether they are EHR, payer, decision-support, financial, case management, or one of many others, need to communicate much richer information than ever before. But the changing face of healthcare is pushing these “conversations” along in ways we could not have imagined even a few years ago.

Without BI and analytics, the new paradigm of healthcare will fail if we don’t move forward full speed ahead. Stakeholders will need to bring the commitment and expertise to bear. By working through the challenges together and moving forward, we can finally unlock the potential of the systems we have invested in to provide real improvements in the quality of care and bend the cost curve to make the benefits of healthcare transformation available to all. BI will play a central role in this effort to take healthcare to the next level.

Rich Temple, MBA is national practice director for Beacon Partners.

Readers Write: Connecting the Divide between Inpatient and Outpatient Care

Connecting the Divide between Inpatient and Outpatient Care
By Michelle R. Troseth, MSN, RN, DPNAP, FAAN

Premier Healthcare Alliance’s spring 2013 Economic Outlook predicts a major shift in admissions from inpatient to outpatient settings. With such predictions, healthcare organizations must connect episodes of care, closing the gap between inpatient and outpatient care. Only then will healthcare develop integrated networks that include hospitals, health systems, ambulatory care centers, community clinics, long-term care facilities, home care agencies, and medical groups, that can work together to coordinate care and share accountability for quality, cost, and outcomes.  

Accountable care demands the reform of healthcare delivery. The key to successful clinical integration is to build high-performance organizations of physicians, specialists, hospitals, and others that are willing to adopt and use information technology and innovative care systems to prevent illness, enhance safety and quality, and coordinate and integrate care. In the process, these organizations become accountable for the quality and cost of care delivered to a defined patient population.     

Equally relevant to closing the inpatient/outpatient divide are the escalating requirements of Meaningful Use, as well as clinical integration, which demands information systems designed to provide clinicians with access to meaningful, actionable information at the point of care decision making. 

The great challenge to achieving new ways of thinking and practicing in the midst of the shifting landscape remains in the how to best create integrated healthcare systems.  While an interoperable technology platform is unquestionably needed, so is an interoperable practice platform to expedite the seamless transition of care between inpatient and outpatient. 

In developing a common practice framework that can be embedded in any technology platform, the following components have been validated as essential for high-quality seamless care:

• Shared purpose and values 
• Dialogue skills
• Polarity thinking skills
• Competency in full scope of practice
• Integrated competency to halt duplication of services
• Partnerships to support networking across the continuum
• Evidence-based tools to develop individualized, interdisciplinary, integrated plans of care
• Integrated documentation that reflects the patient’s story, plan, progress and outcomes across the continuum
• Exchange processes and handoffs that ensure safe, quality care

If providers hope to close the gap between inpatient and outpatient care, they should adopt such an infrastructure that supports continuity of care. Among the most essential steps are: 

• Provide teams with interprofessional, evidence-based tools
• Implement integrated clinical documentation
• Engage patients and family members
• Insist on interoperable HIT systems
• Develop professional exchange/ handoffs processes that ensure safe, quality, coordinated care
• Allow professionals to practice to their full scope of practice

We can bridge the gap between inpatient and outpatient care if we remain aware of the shifting demands of accountable care, population health management, clinical integration and collaborative, coordinated and consistent care by government, payers, patients, and provider partners. Instead of another high-tech fix, implementation of a comprehensive practice platform that blends evidence-based tools with team competency and compassion should be considered. 

Just as important is the investment in smart content that supports integrated documentation, patient engagement, interoperable systems, professional exchange, advanced practice professionals, and intentionally designed tools to support coordinated, collaborative care.    

Michelle R. Troseth, MSN, RN, DPNAP, FAAN  is chief professional practice officer of Elsevier.

Readers Write: The Changing Physician-CIO Relationship: Do You have a Strong Partnership?

The Changing Physician-CIO Relationship: Do You have a Strong Partnership?
By Rob Culbert

Building a relationship is hard. Managing a successful and long-term partnership is even harder.

That’s what most healthcare chief information officers (CIOs) are finding out as they examine their rapport with physicians. Productive relationships take effort and a commitment to change. Successful healthcare organizations can strengthen the physician-CIO dynamic by making a concerted effort to involve physicians in their technology adoption efforts.

Consider these questions as you determine how your organization stacks up in fostering positive interactions with your physicians and what you need to do to build a stronger physician-CIO partnership.

What’s driving the changing relationship between your CIO and physicians?

In most healthcare organizations, physician and CIO responsibilities have historically been siloed—the CIO drove technology, physicians drove clinical care. Now the relationship is changing as physicians expect the hospital to provide greater technology support, which in turn allows the physician to provide higher quality care. More than ever, physicians demand a system that provides full access to both ambulatory and inpatient clinical data.

Yesterday’s hands off approach with physicians no longer works. Healthcare CIOs must employ an intentional strategy to involve their physician partners and meet their new requirements for support and information.

What specific roles are physicians playing in your technology deployment?

Technology is becoming more directly linked to patient care, so much so that physicians now expect systems that seamlessly support their work and improve efficiencies. This is even more the case with younger physicians, who grew up using technology and can’t imagine delivering care without it.

To capture physician opinions and requirements for technology, organizations may want to create a physician steering committee, which involves physicians in major decisions about system design, functionality, and content. Organizations are using these committees to fix and improve specific technology. For example, working as a subset of the steering committee, a physician ICD-10 committee may focus on the required workflow changes and corresponding system changes needed to support a smooth implementation of the new code set. After implementation, physician practice user groups can be leveraged to educate physicians on advanced features and to gain feedback for system adjustments.

Are you providing opportunities for physicians who don’t want to be heavily involved in technology?

It’s a fact: some physicians simply want to be doctors, not IT gurus. Yet, they still can provide a wealth of information through their frontline system knowledge. Avenues for feedback include physician surveys, informal focus groups, or even hallway conversations. Site visits to physician practices can clearly reveal how the system is being used and highlight opportunities for improvement. Garnering involvement and feedback from as wide an audience as possible leads to a healthy and dynamic physician-CIO rapport.

What benefits can your organization realize through physician-CIO alignment?

Perhaps the biggest benefit of physician-CIO alignment is that it’s just good for business – for the physician and the healthcare organization. Most practices don’t have the resources for a sophisticated IT structure with 24/7 support, clinical system protection, disaster recovery, and guaranteed uptime performance. However, healthcare organizations often have extensive IT capabilities and can provide the needed support and resources at a reasonable cost.

Healthcare organizations benefit because strong alignment between physicians and technology leaders can ultimately improve patient care and foster greater efficiency. In addition, it can positively impact a physician’s choice where to practice. Because most physicians want to partner with an organization that is responsive to physician involvement, this strengthened relationship allows organizations to be more competitive in recruiting and retaining physicians.

Strong physician-CIO interactions can also help a healthcare organization strategically position itself for quality improvement and agility with the coming healthcare legislation, ultimately improving payment and reimbursement rates for both parties.

Establishing and maintaining strong partnerships between physicians and technology leaders is essential to navigating the evolving healthcare landscape. As information technology becomes more critical to care delivery, the strength and resiliency of the physician-CIO relationship will determine your organization’s ability to successfully deliver quality care and maintain financial viability.

Rob Culbert is president and CEO of Culbert Healthcare Solutions.

Readers Write: The Increasing Enforcement of HIPAA and What It Means To You

The Increasing Enforcement of HIPAA and What It Means To You
By Kent Norton

Since the inception of HIPAA and its enforcement, there have been nearly 100,000 cases or complaints investigated. Among those, many have resulted in fines ranging from thousands of dollars to more than two million. Today the fines have a cap per penalty and per calendar year, restricting the fines to $50,000 per penalty and $1.5 million per calendar year.

Fortunately, the Office for Civil Rights has allowed entities to correct the aberrations of noncompliance within 30 days if the failure to comply was not willful neglect. The likelihood that your organization is audited is small when considering that in 2012 only 150 entities were scheduled to take place. The main issue of concern is that a patient, for whatever reason, will file a complaint about HIPAA noncompliance.

With the addition of the HITECH amendments in 2009, HIPAA enforcement has been on the rise, with more than five times as many cases settling after 2009 than before 2009. HITECH has certainly done more to change the face of protected health information or PHI than HIPAA originally did.

For most organizations the first thing that should be scrutinized when considering HIPAA and HITECH compliance is a risk analysis. This is a terribly large task especially when your IT department must do their analysis while still fielding their daily IT requests. Because of the large strain this puts on an organization, a new section in the IT industry has come about to do this type of risk analysis and HIPAA/HITECH compliance implementation. It may be wise to consider employing an IT risk analysis and implementation team in order to help your organization become HIPAA/HITECH compliant as quickly as possible.

The second thing to examine about your PHI is the defense your IT department has against attacks from both internal and external fronts. An efficient and effective PHI defense needs not only intelligent, self-aware, and careful staff and policies, but also complete control of physical data and data transfer. Once these are in place, your IT department can look at how PHI is accessed and the possible avenues hackers would use to bypass the security measures that are in place. One of the most subtle possible leaks of physical data or PHI is often overlooked and that is personal mobile devices. Developing controls and checks to keep PHI from being transferred, copied, or changed via a personal mobile device can greatly improve an organizations risk of noncompliance.

Lastly, inspecting the systems you have in place in order to determine the necessary frequency of periodic risk evaluations and assessments and to develop a monitoring and security mitigation plan. Having these two systems in place will help keep your organization compliant as the IT industry evolves with the changes in health care and technology.

As enforcement of HIPAA continues its upward trend, more and more organizations will need to take a better look at how they have implemented their compliance programs. They’ll need to make sure that they have taken the right steps in order to be safe from the steep fines and penalties that could come as a consequence.

Kent Norton is a HIPAA security analyst with HIPAA One.

Readers Write: Nay for CMS Proposed Rules on ED Facility Fees

Nay for CMS Proposed Rules on ED Facility Fees
By Robert Hitchcock, MD, FACEP

The calendar year 2014 Outpatient Prospective Payment System Proposed Rule (CMS-1601-P) proposes several changes that I believe will negatively impact emergency departments (EDs).

The two proposed changes in particular that have me concerned are:

• Consolidation of the five ED facility level evaluation and management (E&M) codes into a single code
• Packaging of add-on services

Consolidation of facility level codes

Without clear facility level guidelines, determining accurate codes is challenging for hospitals and potentially responsible for the recent media stories suggesting that upcoding is occurring. Despite repeated requests for CMS to develop guidelines and much industry input and willingness, no action has been taken. I’m concerned that the proposed consolidation is a substitute for clear facility level guidelines. The methodology for determining reimbursement amounts for the proposed codes are unclear and no impact analysis on hospitals has been performed, or could be from the data presented.

The logic currently used by most hospitals to determine facility E&M codes for ED visits relies on evaluation of the resource requirements to care for the patient during the visit. In many cases, the distribution of patient complexities, and thus facility codes, is often a result of multiple factors – many of which the hospital has no control over.

For example, hospitals in areas where Medicare patients have limited access to primary, preventive, and specialty care may see patients with poorly managed chronic diseases who are more complex and resource intensive. These hospitals may well experience a significant decrease in reimbursement, which may negatively affect their ability to continue to provide healthcare services. In addition, increasing the number of lower acuity Medicare patients treated in the ED will significantly increase total federal healthcare expenditures for unscheduled care.

A tiered structure is essential to the financial stability of hospitals and would help protect against shifting care patterns that could unnecessarily raise healthcare expenditures. Clear, concise guidelines should be developed that allow hospitals to accurately and reproducibly assign the appropriate tiered services code for a particular visit. If simplification of coding guidelines and reimbursement is a main goal, I would suggest one approach would be to shift from five tiers to three. This will allow the healthcare system to continue to track and manage the resources required to provide unscheduled care.

Packaging of add-on services

The proposed packaging of add-on services has a commendable goal of simplifying reimbursement and encouraging hospitals to seek efficiencies in the care they provide. However, some of the proposed packaging involved are for specific therapeutic services that are often required to provide high quality care. I believe that the broad brush of unconditional packaging of all add-on services is inappropriate and could lead to circumstances that are directly detrimental to patient care.

The packaging of add-on services in certain circumstances would be beneficial, such when the provision of the service is not directly related to therapeutic delivery of care, especially medications. For instance, providing additional intravenous doses of an identical medication are often required to provide optimal care (e.g., analgesic administration for pain control or additional intravenous hydration for dehydration). There’s really not much opportunity for improving efficiencies here; either we provide appropriate pain management, or not. The concern lies in that packaging these services may create situations where optimal patient care is pitted against the financial pressures of the hospital.

Preservation of EDs

I believe that the proposed modifications to these two areas would have a negative impact on both national healthcare costs and quality of patient care delivered. As a safety net for healthcare in the US, the preservation of EDs is critical.

The final rule is expected around November 1 and will take effect January 1, 2014.

Robert Hitchcock, MD is chief medical informatics officer of T-System Inc.

Readers Write: Meaningful Use to the Maximum: Keeping the Focus on the Patient

Meaningful Use to the Maximum: Keeping the Focus on the Patient
By Gary Hamilton

Across the country, healthcare organizations are evaluating their ability to meet the Centers for Medicare & Medicaid Services (CMS) Meaningful Use (MU) requirements. Data recently released by CMS revealed that more than 23,000 family physicians became first-time “meaningful users” last year, a 180 percent increase from 2011. At the same time, CMS data showed a 21 percent drop in the retention rate of attesting physicians.

Although these statistics reflect one portion of the physicians seeking to attest for MU, they point to a bigger issue among all entities involved in this effort. While MU Stage 1 attestations are up, the number of providers dropping out of the program before reaching Stage 2 is also on the rise.

The question is: Why?

One contributing factor may be the lack of focus on “meaningfully” using technology. As physicians and hospitals embark on the MU journey, they often focus their attention on technology purchases and upgrades, losing sight of the true intent of the government’s program—to improve patient care.

In fact, some organizations have been so preoccupied with the technical components of their IT systems and how they meet Stage 1 requirements that they fail to realize their current technology is not capable, or does not have the necessary certifications, to help them meet Stage 2. As organizations become increasingly concerned with Stage 2’s escalating requirements, some providers are deciding it is easier to drop out of the MU process than to continue to the next level.

For those physicians and hospitals that do decide to forge ahead, it’s imperative not to lose sight of the intent of MU: a better patient experience both in terms of outcomes and satisfaction. To do this, healthcare providers must go beyond merely viewing MU attestation as a “check the box” exercise; instead, they must take a more strategic approach that puts the patient at the center of the process.

Here are some key questions to keep in mind when developing a MU strategy that maximizes the “meaningful” in Meaningful Use.

1. How would you use technology to improve patient care if the government’s incentive program didn’t exist?

Elevating patient care and making it more patient-centered cannot be viewed as a separate initiative from MU attestation. To keep the patient firmly at the forefront of MU efforts, an organization first must consider how to foster patient-centered care and then think about the technology that will best enable the work. Many MU standards represent activities that organizations should be doing to make the care experience more patient-driven, regardless of the decision to attest. These efforts can also streamline operations, enhance workflow ,and facilitate strong care coordination. For instance, patient-focused organizations should consider implementing technology that enables electronic scheduling and appointment reminders as both a convenience for patients and a time-saver for staff. Or, electronic forms should be used to speed new patient registration, eliminating the need to scan or key paper documents and control delivery.

2. Is the technology you’re considering “smart” for your organization and your patients?

For technology to be beneficial, patients and providers must fully embrace and use it. To realize this level of interaction, an organization must consider both patient and provider needs and workflows when selecting technology. Getting a firm grasp on this information may require an organization to conduct focus groups, interviews, or surveys to learn more about both groups’ needs and how the technology can best meet those needs. Things to look at include how the technology can improve convenience, enhance information sharing, further efficiency, and foster communication. By taking the time to fully appreciate and respond to patient and provider input, an organization can ensure the selected technology is appropriate and “smart” for the organization.

3. Is your patient-centered approach enabling the transition to MU Stage 2 and beyond?

MU Stage 1 requires organizations to prepare to involve patients in their care by providing patients the ability to request and view an electronic copy of their health information. Beginning in 2014, a key Stage 2 objective will require at least five percent of a health organizations’ patient population to download, view, and transmit health information. When organizations attest for MU Stage 1 with an eye toward patient-centered care and strong information sharing, they not only meet MU Stage 1 requirements, but also lay the groundwork for MU Stage 2 and beyond, progressing toward the next stage faster and more efficiently. More importantly, they are able to maintain greater patient focus and foster satisfaction because patients are interacting with the technology in a way that is both convenient and enhances the care experience.

Successfully meeting MU criteria requires patient-centered care to remain the central focus, regardless of the stage. Without maintaining this attention, an organization can quickly get lost in the weeds of technical specifications and lists of requirements. By intentionally selecting technology that keeps the patient at the forefront, organizations can provide a positive patient experience while bolstering patient loyalty. Engaging this approach can effectively underpin efforts to not only meet the MU criteria, but also put the “meaningful” back in Meaningful Use.

Gary Hamilton is president and founder of InteliChart of Fort Mill, SC.

Readers Write: Healthcare Talent Shortages: So Where Are All the Mentors?

Healthcare Talent Shortages: So Where Are All the Mentors?
By Helen Figge, PharmD, MBA, CPHIMS, FHIMSS

Healthcare is a business from every angle, and from each of these angles there is a need or a demand for something, whether it is a skill or some other attribute. It’s all about supply and demand. The age-old problem in healthcare of finding qualified staff never seems to land on a solution. It is now pointed out in virtually every article of why milestones are missed or professional burnout occurs.

Even a new survey from SSi-Search reports, for example, that the CIO is now more than ever under pressure to perform and execute day-to-day issues and processes to move their institutions to the next level. In this recent study, it was again pointed out that CIOs are finding it hard to find qualified help to diffuse the pressures being felt on them and their IT teams in order to execute the various technology projects within their organizations.

Most of these pressures being discussed and felt firsthand reportedly are mapped back to the HITECH Act of 2009 and healthcare reform in general. In the end, to add to the conundrum, these various healthcare reform changes are all dependent on technology enablers and qualified help to use these technologies to support the various healthcare programs being implemented in the institutions. Alas, potential full circle turmoil.

This particular survey even catalogued the “standard” CIO as a “highly educated male, who has served in the role for 10 years and earns $286,000.” Approximately 178 individuals responded to the survey, probably even adding to their stress load of the day. The study also presumed that increased responsibilities would result in greater compensation, but the findings did not support this line of thought. In the end, workload was viewed as not being compensated compared to job responsibility and stress of performing.

But when all was said and done, the CIOs queried really focused on having the right teams in place to support the ability to continue to deliver good quality results. Those who answered the survey wanted “more and/or better qualified resources." What is a CIO, or for that matter anyone, facing this issue in healthcare today possibly doing to resolve this?

Not sure, but one suggestion: create a mentoring program and create others who “grow up to be just like you.” The gaps we are seeing in healthcare today will never be filled by “Stepford wives” or cookie cutter personnel. These individuals just don’t exist and probably never did or will. But the healthcare IT roles in particular out there today can be filled with those in the lower ranks of many organizations. If these individuals have the base skills and degrees required and then get groomed and cultivated by those who have been there and done that, we might be surprised just how effective this approach might be filing the healthcare IT void once and for all.

Early in American history we had apprentice programs for virtually everything from growing crops to shoveling coal in the coal mines. These industries survived and flourished. Why not create the same programs in healthcare IT and address the workforce shortage once and for all? Besides, there are some really great CIOs out there (and they know who they are) who have lectured, cultivated, mentored, and even picked up the phone to answer a question from a nobody like me to offer up guidance, patience, and direction to help the cause. These are the true leaders out there today and we need them now more than ever.

I say create a true mentoring program with these individuals (and not all are male or award winners) and create bonds between a these giants of healthcare IT industry ( the mentor) and the “I want to be a CIO someday” (the mentee). This in turn can create an opportunity to train by example of what needs to be done and the necessary steps involved in making things happen in healthcare IT.

Be a mentor, personally achieve some personal growth and career satisfaction, learn more about yourself as a human being, and really make a difference in your life and those you touch. This approach might not help the healthcare IT shortage immediately, but within three to five years if we have enough good mentors training mentees, this conversation would most likely be not worthy of much discussion.

Helen Figge, PharmD, MBA, CPHIMS, FHIMSS  is advisor, clinical operations and strategies, for VRAI Transformation.

Readers Write: Provider Charges: An Excellent Start

Provider Charges: An Excellent Start
By Data Nerd

Any data nerd worth his or her salt will tell you that a thorough analysis starts with vetting, mining, scrubbing, and purging compilations of data. Most of my time on any analysis project is spent understanding the context and cleansing data to the point that I can work with it confidently. So, when I came across this Medicare and Medicaid Research Review article, I wanted to bring it to the HIStalk readership’s attention as an excellent methodology for doing meaningful cost analysis across the country.

Remember earlier this summer when CMS unleashed the tip of the kraken with average DRG charges for hospitals? I say the tip of the kraken because (1) it was really a minute slice of a much larger pie, and (2) the data was sliced, diced, and visualized to a bloody pulp and although we haven’t seen a new release of data to confirm, we certainly aren’t hearing about any major price shifts in the market. As a similar release for individual providers is being considered, here is something meaningful we can do to actually understand and do something about real price variation.

Adjusting for acuity and policy factors that influence prices is essential to understanding why one provider charges more than another. Just like it was insufficient for CMS to release DRG data with average charges when patients could be treated for up to 25 diagnoses and 25 procedures in the same charge amount, it will be meaningless to release individual provider charges without the context of treatment.

Usually, I’m the first to ask for atomic “Collect Once Use Many Times” data elements (hard numbers on which to base other calculations), but in this case, relative weights really are more meaningful if you want to scout out the root of price differences. Are abnormally high salaries driving price? Supply chain inconsistencies? Medical errors? If you really want to know why one provider charges more than another, you need to hold all things constant, and the methodology outlined in this paper is an excellent start.

What do you think? Is it more meaningful to look at hard numbers (Hospital A charges $x vs Hospital B charges $y) or a relative weight holding wage and policy initiatives constant? Do relative weights obstruct meaning or provide a lens through which we can view data more clearly?

Readers Write: Big Data – The Next HIT/EMR Boondoggle?

Big Data – The Next HIT/EMR Boondoggle?
By Frank Poggio

Here we are on the back side of the HITECH wave. EMR vendors can see that the government-sponsored manna will soon end, so IT marketers have been prospecting for the next gold mine. They found it and it’s called “Big Data and Analytics.”

It really makes perfect sense. After they install the deca-million dollar EMR systems that capture and track mountains of healthcare operational data and send it to the government, what else are can they do with it? Analyze it! Analysis for clinical and administrative purposes, analysis for planning, analysis for diagnosis, for prognosis, for best practices, for financial management, growth strategies, market penetration, and more. To paraphrase an old cliché, “There’s got to be a pony in all that data somewhere.”

It is often repeated and rarely challenged that healthcare providers are a decade behind commercial industry when it comes to IT tools and implementation. That clearly is the case when we look at Big Data (BD). But before healthcare jumps into this numerical ocean, maybe we can learn something from commercial industry and bypass many of the hurdles and errors private industry hit during its initial foray into the world of analytics.

First, a little history. Today it’s called Big Data and Analytics, but in the 1960s it was called Operations Research, Management Science, or Quantitative Analysis. Operations research was actually an outgrowth of World War II. The Defense Department asked mathematicians to identify more effective and efficient methods for bombing the enemy. The British used modeling and data analysis to improve submarine warfare.

After the war, these sophisticated mathematical tools were applied to volumes of operational data captured by many business transaction systems of the 1970s. The focus was on optimizing production and improving forecasting in order to reduce the risk embedded in strategic decision making. The former used mathematical models such as linear programming and queuing theory aimed at maximizing throughput and minimizing costs. The latter was typically done with regression analysis, probabilistic models, and Monte Carlo simulation to assess and minimize risk. In the 1980s and 1990s, more sophisticated tools such as random walks, chaos theory, and fuzzy logic were developed and applied to financial and other business problems.

Today the thinking in healthcare is that with our ever-expanding sea of Big Data, we should start applying these same tools to help address the healthcare cost crisis. Not at a bad idea. But before we spend billions searching for our “pony,” we should at least learn something from the sins of our brothers in the commercial world.

During the ’70s and ‘80s, commercial industry spent billions trying to apply these concepts with only marginal benefit. It has only been in the last 10 or 15 years that analytics in commercial industry has really paid off with leaps in improved logistics and productivity, while the jury is still out on management, strategic, and predictive applications. It took decades for commercial industry to see measurable benefits from BD. Here are two of the reasons and their implications for healthcare.

Bad or insufficient data. Thirty years ago when commercial firms crunched big wads of financial data, they found that there were significant problems correlating econometric data with accounting data, and more so with tax and government data. Earlier in my career I worked for GE in one of their OR groups. We found that merging or correlating the data originally captured for the different audiences rendered unusable results. Much time and effort had to be spent reclassifying financial data to make it sync properly with econometric and government data. In addition, we came to realize that volume and statistical data not captured at the source was fraught with errors and misclassifications. Thousands of hours were spent normalizing, scrubbing, and disaggregating data before we could make reliable correlations for decision making.

Healthcare has some very similar challenges. The issue with accounting data versus econometric data is the same, but the disparities between reimbursement data (tax) and business operation or econometric data is far greater. As an example, commercial industry had to invest billions in sophisticated product/service costing systems, while today in healthcare, many institutions still rely on Medicare cost analyses, which any financial manager would classify as nothing better than gross approximations.

Many of the BD analytics will incorporate and be driven by cost comparisons. Medicare cost analysis is a long way from a true product/service cost accounting system.

Merging clinical data and financial data is currently the rage, but another big hole will be using billing documents, charges, or RVUs as a basis for analysis. Provider charges are not related to service cost because they have been warped by decades of government policy and payment nuances. They are as far from financial reality as we are from the sun. In addition, the coding and classifications embedded in billing documents have been twisted to meet the objectives of payors and payment rules. Everybody agrees that ICD-9 coding is inadequate if not inaccurate, yet no doubt it will be a core element in many of the BD analytics clinical  / financial models.

Reality versus the “model.” After several decades, commercial firms came to realize that many of the mathematical models they employed only loosely fit the real world. Models are far simpler representations of the real world and typically model builders fill in the blanks and more complex parts with assumptions.

The real world keeps changing. Yet many of the predictive tools we use such as regression analysis are based heavily on past performance and have limited ability to reflect change. Medicine is in constant change. Hardly a week goes by without a new research report that retires an old protocol and replaces it with a new one, while new drugs, modalities, and technologies are introduced almost every day.

The practice of medicine is both science and art. It is difficult to properly model the science part, let alone the art component. The same can be said for management: science or art? It took decades and millions of dollars before commercial industry realized the limitation of many of the predictive models they applied and how sensitive the predictions were to the underlying assumptions. Correctly modeling the subjective judgment component of management and medical decision making will be a very expensive task.

Clearly the old GIGO rule applies to Big Data as much as it applies to our day-to-day EMR transaction systems. The significant difference will be in the investment needed for BD just to get past level one GIGO. When we implement a transaction system we can see if it works effectively or has bugs in a matter of days. With Big Data and Analytics measuring the efficacy and impact can take years, be very expensive, and a financial boondoggle for vendors.

Next up: five things to check before diving into the Big Data ocean.

Frank Poggio is president of The Kelzon Group.