Healthcare is undergoing an unprecedented transformation with CMS (Centers for Medicare and Medicaid Services) and commercial payers increasingly tying reimbursement to performance on quality measures. Accountable Care Organizations, Bundled Payments, Value-Based Purchasing, and the Patient-Centered Medical Home are among the programs that heavily depend on the reporting of quality data sets by hospitals, physicians, and other providers. For healthcare organizations to succeed in the new world, they must devise novel and efficient ways to measure quality in order to improve care and reporting.

One of the recent changes tying quality to reimbursement is the new Group Practice Reporting Option (GPRO) for the Physician Quality Reporting System (PQRS).  You can read all the details here, but I will provide an overview below and explain why this seemingly small step has huge repercussions.

Practically speaking, reporting on these quality measures is an indispensable action for group practices, Accountable Care Organizations (ACOs), and similar types of healthcare providers, to stay in business. Using GPRO to report on standard quality measures enables them to earn their PQRS incentive bonus from Medicare, an incentive bonus they cannot afford to do without in today’s cost-conscious environment.

As is often the case, the challenge is not understanding “what” needs to be reported, rather it is figuring out a practical and cost effective “how” to accomplish this reporting.

In our discussions with numerous ACOs and other healthcare providers, this challenge is being met (at least initially) with manual processes that are extraordinarily time consuming and labor intensive.  In addition, the reporting is also subject to periodic audits that require on premise visits to pore through extensive records and further impact the time and attention of medical and support staff from their important daily duties.  Even where some hospital administration systems are attempting to automate some of the reporting, often an ACO has multiple systems across multiple hospitals and practices, so that partial mechanization cannot offer the consolidated view of the entire ACO without substantial manual intervention.

Solution Description

Together with our partner Zato, we have developed a straightforward and cost-effective solution to mechanize the preparation of the GPRO report – our system is called GPRO-EZ.  Here are the important characteristics and benefits of this solution. GPRO-EZ:

• Auto populates all GPRO fields. This mechanizes preparation of the entire report, with little to no manual intervention required – thus saving hundreds of hours of medical professionals and their staff that can be put to better use; a dramatic return on investment.
• Supports on site and remote auditing of the reporting data with the only requirement being access via a secure web browser – anyone can audit the information from anywhere, reducing travel-related expense and medical staff interruptions; another dramatic return on investment.
• Creates a GPRO report for the entire ACO by integrating relevant information from all clinics, practices and hospitals, without the need to centralize, copy or replicate the data.
• Automates information extraction and understanding from both structured and unstructured content by combing technologies with the world’s leading edge practical medical ontology; this creates a comprehensive view of data entered in fields in reports with important notations entered as commentary.
• Facilitates improved case management and automates risk stratification for impacting quality of care for the population.
• Enables continuous monitoring and automated alerting with dramatically fewer false positives and false negatives; rationalizes “alert fatigue” so that when alerts happen, they can and should be acted upon.

Initial implementations of GPRO-EZ are moving forward now. Contact us for more information on how we can plan together with you to begin generating nearly instantaneous return on investment from our GPRO-EZ implementation. Also, please use this link for more details www.gpro-ez.com.

Here’s my list of the top things that keep me from being truly productive. I suspect it will sound quite familiar to many of us, so I don’t claim any unique insight. I just found the points to be re-enforced as I try to improve my personal productivity, and as I have observed people waste my time and others.

Here are things I observe that contribute to the time trap, sink-holes that suck productivity from ourselves and our colleagues:

1. Checking email – real time.  Unless you are waiting for an email that will change the course of history, likely it can wait a bit.  Reading email is a poor substitute for accomplishing something.
2. Copying everyone you can think of on email correspondence.
3. Overthinking things.  What I mean is that instead of asking or answering a question simply, we create lengthy and long-winded “pre-ambles” or “post-ambles”.  Rarely is much context required to get a useful question asked or answer given.
4. Talking about problems or issues with no intent to create or take any action.
5. Talking about the shortcomings of others with no intent to create or take any action.
6. Having no system for keeping track of what one needs to accomplish.  I have no idea what the one best system is, I just know that most of our lives are far too complicated to keep everything in our heads.
7. Failing to take notes of conversations or meetings.  See number 6 above… impossible to remember everything said and who is supposed to do what afterward.
8. Going to meetings without a writing instrument and something to take notes in – see numbers 5 and 6 above
9. Seeking to address issues by creating a virtual tennis match of emails going back and forth…walk over to someone’s work area or pick up the telephone – have a real person-to-person conversation.
10. Allowing interpersonal conflict to persist.  Resolve conflicts now.
11. Allowing many tasks to get to 90% but never quite get completed, usually because other tasks intercede, and the urgent squashes the important. Finish things.

Do you recognize yourself in any of these?  Let’s resolve together to minimize our contribution to these time traps.

Nothing better exemplifies the transforming world of healthcare than the emergence of Accountable Care Organizations (ACOs).  To be effective, an ACO must create an efficient delivery model that constantly improves upon the quality of care while reducing the total cost of care for an assigned population of patients.

To make matters more challenging, this needs to be done in an ecosystem where the ACO provides regular quality metrics to Medicare and other overseers, while operating in a world of massive consolidation – where one of the ways to achieve these objectives is to have massive scale, so the law of averages works in your favor.

Conventional wisdom says that the only way to make accurate information available to support your ACO is to consolidate data from sources as disparate as Electronic Medical Records, labs, pharmacy data, and other systems, into a single data center. Then hire a lot of Data Scientists to formulate queries across this mass of structured and unstructured data. However, no one can explain how to finance this or live with the timeline to complete it.

Here is an example to make this point starkly clear.  I was recently speaking with the CEO of an ACO.  I asked him about some of his greatest challenges.  He replied, “We are creating our ACO from seven disparate organizations with 24 hospitals, 326 clinics, 7,000 physicians, and over 100,000 patients.  Since any of these patients can use all of our facilities, their information needs to be readily available throughout our ecosystem.”  I suggested that sounds like a fairly daunting challenge,. I asked him, “How are you going to accomplish it? ” He responded, “I have no idea. We don’t have the money, time, or inclination to create a massive consolidated data center, which everyone is suggesting is the only solution.”

At Chiliad, we take a radically different point-of-view to solving this challenge. Chiliad creates a “virtual consolidated data center” that acts as if all the information is centralized without the need to do so – no copying, no replicating, no data cleansing.  Going even further, with our partner Zato, we have automated an ACO’s  quality reporting requirements using our technology to work through structured and unstructured information to generate these reports with little to no human intervention. And we do it meeting all HIPAA requirements for data security.

If this sounds to good to be true, make us prove it to you – we thrive on just these challenges that we have been meeting in the Government world of intelligence and law enforcement for a decade.

I was chatting with one of our key employees today. She indicated she was struggling with what she perceived to be a conflict of statements I have made to our company.  On one hand, I tell our folks we want to hire the best, most capable people we can, and on the other hand I have said that any of us can get run over by a truck and the company will still sustain itself.  She asked, “Aren’t those conflicting messages?”

Little Myths are untrue, but they only keep us from doing something that might otherwise be valuable. For example, until the 19th Century people thought tomatoes were poisonous because they are related to deadly nightshade. But the only bad thing this little myth caused was less-delicious salads and pizza.

A Big Myth, on the other hand, causes us to do something destructive. 

One of the more morbid Big Myths was blood-letting: removing blood from sick patients to heal them. Of course removing blood actually made them weaker and less able to resist disease. Witch burning in 17th century Salem also fits this terrible “Big Myth” category.

Sadly, finding meaning when you have a great deal of information suffers from a Big Myth. The fact is every enterprise of significant size has data spread across multiple locations. Every single one. Many people believe—and some very smart people will tell you—the only way to extract meaning when you have data spread across locations is to bring all that data together into one place. This is called ”data consolidation.”

Data consolidation may sound easy, but actually moving and gathering information from many locations into a single building, a single data center, is wildly expensive, incredibly time-consuming, and surprisingly risky. It is risky because many of these projects get started and end up failing after wasting years and enormous amounts of money.

I’d like to tell you a true story: John, that’s not his real name—but he told me the story himself—is the CIO at a major healthcare system. He told me he had been in the job for three years and his predecessor, the previous CIO, lost his job because the employees of the company needed to find a way to do analysis using all their information and the previous CIO did not know how. Employees knew they wanted their analysis to build on all the information they owned—across hospital systems, clinics, specialists, etc.—and they were told they needed to consolidate that information into one location to let people do that analysis. But they had no idea how to start and neither did the old CIO.

So they fired the old CIO and hired my new friend, John, specifically to consolidate all the data from all the data centers. 

Because he came in behind a significant failure, John was able to ask for and receive a large budget, and he had the full backing of management and employees, and he had a plan on how to get the job done. 

At this point I was pretty excited. John had been on the job for three years with a primary focus goal of consolidating all of their national data. So I ask the obvious question: “How’s it going?”

“Oh,” he said quietly, “we haven’t consolidated anything yet.” 

He had spent plenty of money…and at this point, years were passing quickly, but they had not actually made any progress. Three years later.

To be fair, the need to consolidate your information to analyze it is only a “big myth” if doing it destroys value, right? That is, consolidation is only destructive if there is a path to the same goal which is quicker, less expensive, and less risky.

And that’s the point. There is.

Chiliad allows any authorized person to find and analyze any information—in any format, any volume, and any location—as if it were all consolidated in one place. That multi-year, multi-million dollar, risky process…is no longer needed.

To be sure, there are still some uses of data for which consolidation still makes sense. But do you have to consolidate just to find meaning, relationships, and themes to make better decisions?

No. That would be a Big Myth.

Greg Brooks is the Director of Development at Chiliad.

Actually, Chiliad truly is a Greek word; here is a good definition from thefreedictionary.com:

chil·i·ad (kl-d, -d)

[Late Latin chlias, chliad-, from Greek khlias, from khlioi, thousand; see gheslo- in Indo-European roots.]

As any of you who have ever started a company know, naming a company is critically important – particularly because one of the key requirements for the name is that the URL is available so that a website can be created. Once upon a time that was easy, now, not so much.

But Chiliad was not so much named with websites in mind, but rather to give a sense that we were all about dealing with data in massive volumes — so the Big Elements or Big Time notion that launched the name of the company, pre-dated the notion of the term, Big Data. From its earliest inception, the idea behind the company was, how to get useful information and meaning out of massive amounts of data.

The goal of finding actionable meaning in an ocean of data is as old as the phrase “Information Explosion.” Unfortunately, the software industry evolved in a way incompatible with the way data evolved. To deliver products quickly, for-profit software companies assumed data wouldn’t be larger than 10s of terabytes, would be located in one physical location or could be aggregated into a data center, and would be clean or could be cleansed (or extracted, transformed and loaded “ETL-d”) for consistency. These assumptions were the fastest way to profit in the 2000s.

Unfortunately, data has grown to 100′s of terabytes or petabytes, is spread all over the world, and exists in myriad formats, and is “messy”. But the dream of finding meaning remains. Chiliad’s roots were in the not-for-profit sector—at the University of Massachusetts, with a pure research focus on what would happen when data was measured in petabytes or more, was distributed widely, and was wildly diverse. Those roots put Chiliad in a unique position to solve today’s real-world Big Data challenges.

Chiliad’s technology is at the vortex of the two biggest forces in technology – Big Data and Cloud Computing; we have been there for the past decade, before these trends evolved or were named, but now the market has caught up with us Big Time.

Chiliad, however you choose to pronounce it, is a great illustration that the visionaries who started the company had thought through a unique approach to solving a very difficult problem that the market had yet to discover, but that has stood the test of time.

Fortunately, it did not take 1,000 years for the market to catch up with us.

Craig Norris is the President and CEO of Chiliad.

I spent a number of years at Gemini Management Consulting. As you may know, selling consulting services is a significant challenge. In consulting the only thing you have to sell is your collective brainpower – no product to test, nothing tangible you can try out before you buy.  This is a much more intangible sale than software or hardware or consumer goods, and as a result, is in some respects more difficult.  David Tieger was the Chairman of Gemini at the time I worked there, and he preached to all of us the Trust Formula. I am not sure he actually invented it, but he may as well have since it became part of the core of who we were as a firm, and at the heart of why I think we were successful for so many years.

When I first joined Chiliad, we started out by defining our values as a company. Our goal at Chiliad is to generate a very high level of trust with all the people we touch – inside and outside of the company.  We recognize we need to earn that trust every day, and that one thoughtless action of putting self-interest ahead of the interest of others can ruin trust forever. We don’t claim to be perfect, but we strive to live our values, and you can hold us accountable to them. This Trust Formula carries a special significance for us, since our software is used every day to literally save lives, whether in the Intelligence Community or in Healthcare.

This is the kind of company I want to lead and whose values describe a company that I would want to do business with. If you agree, check us out.

Craig Norris is the President and CEO of Chiliad.

For many years, the companies where I have been CEO have practiced variations of Agile development. We have all seen numerous papers and blogs about the  Agile, as well as the benefits of using this approach; so I will avoid covering the same ground.  Other than to say this, in my experience it is less important to be fanatical about a particular Agile approach, than it is to be particular about fanatically using Agile methods consistently, to drive repeatability and predictability.

Our entire user experience is built around a methodology that is a core value Chiliad delivers; it supports the way users have described to us how they want and need to work in order to be productive. We define this methodology as Iterative Discovery, and we believe our support of this approach is what truly distinguishes us. However, that would not matter much if our underlying technology did not deliver value across massive amounts of information as well as it does.

Part of the power of our approach, and the UI that we developed to support it, is that it allows users to start analyzing data anyway they want. Our methodology is not a straight-jacket that enforces a particular way of problem-solving; rather, it is a framework that is flexible by design. Our new user interface was not developed in response to competitors or in hopes of getting a box checked on a customer evaluation form.  Instead, it was developed to enable users to work they want to work. In the process, users indicate that they have become far more knowledgeable and productive.

When results are returned from an iterative discovery query, we say reading is not the first thing a user should do, but the last thing a user should do. We emphasize this approach because reading is more effective when one has a global context about the corpus of information that is returned as part of the iterative discovery query.

Because users have context for their query, they become aware of things they were oblivious to:

• They can alter their course of discovery in ways they had not envisioned initially.
• They can invalidate their hypotheses and pursue an entirely different path.
• They can add new terms to their initial discovery entry and try it again.
• And they can save both the results of their query and the query itself to continue working in the background to alert them to new, relevant information in real time. 

Certainly, they can also go to our globally ranked results at any point in their iterative discovery process and read, with confidence, how Chiliad has done a superlative job of ranking the results (see Howard Turtle’s blog on how we do our ranking: Result Ranking)

Chiliad did not add pizazz and sizzle to the new user interface because everybody else does it. It is far more profound than that. It reinforces the iterative discovery process that is at the heart of our approach to business and how we answer “Why should you consider Chiliad?”

We strive to have every person working for Chiliad understand and internalize this message. The marketplace reaction we are getting to our approach and solution is quite gratifying. We hope it makes sense and matters to you as well. It is that important.

Craig Norris is the President and CEO of Chiliad.