What I learned at HFMA’s Revenue Cycle Conference at Gillette Stadium

(…while the Patriots prepared to get their butts kicked)

Right from Jonathan Bush, the co- founder and CEO of athenahealth [the keynote speaker]: “Make Hospitals Focus on What They’re Good At – Everything Else, “Seek Help!” I can help define “everything else”. For now, I will keep it generally confined to the world of healthcare data – because I would argue more time, money, and effort is wasted on getting good data than almost any other activity in a hospital.

If you are a Chief Quality Officer, or Chief Medical Informatics Officer, or Chief Information Officer – what would you rather spend your budget on?

Your analysts collecting data – plugging away, constantly, all-day into a spreadsheet?

Outcomes: Stale data in a static spreadsheet…that probably needs to be double/triple-checked…that probably is different than what the other department/analyst from down the hall gave you…that you probably wouldn’t bet your house on is accurate.

Or your analysts analyzing data and catalyzing improvement with front line leaders?

Outcomes: Real time data in a dynamic, flexible multi-dimensional reporting environment…that can roll up to the enterprise level…and drill down to the hospital → unit → provider → patient level.

Here’s a hint – this isn’t a trick question. Yet, for some reason, as you read this, you’re still spending more money on analysts reporting stale, static, inaccurate data than you are on analysts armed with real time data to improve the likelihood of higher quality and patient satisfaction scores and improved operational efficiency.

The majority of the speakers at this year’s HFMA Revenue Cycle conference seemed to accept that providers are NOT good at collecting and analyzing data, or using it as an asset to their advantage. They also seemed to align well with other speakers I’ve heard recently at HIT conferences. If you’re like 99% of your colleagues in this industry, you probably don’t understand your data either. So do what Jonathan Bush said and GET HELP!

Are you “ACO IT-Ready”?

First things first, I believe the push for accountable care is here to stay. I do not think that it is a fad that will come and go as many other attempts at healthcare reform have. Having said that, I also strongly believe that very few organizations are positioned to start realizing the benefits that will come from this reform any time soon. It’s not for lack of trying, as many organizations are already recognized as Pioneer ACO’s. But the hard part is not being established as an ACO – it’s proving you’re reducing costs and improving quality for targeted patient populations.

The first step will being January 1^st, 2013. Some ACO’s will be required to start reporting quality measures – for instance the Shared Savings program from CMS for both the one-sided and two-sided models require reporting 33 quality measures. Notice I said “reporting”. So for the first year, it’s “pay for reporting”. Years 2 and 3 is when the rubber really meets the road and it becomes “pay for performance”. “Don’t just show me you are trying to reduce costs and improve quality, actually reduce and improve or realize the consequences.“

With ACO’s come reporting requirements. We in healthcare are used to reporting requirements. And those of us willing to publicly acknowledge it, more reporting means more waste. Why? Because there is job security in paying people to run around and find data…and to eventually do very little with it other than plug it in a spreadsheet, post it to a SharePoint site, email it to someone else, or well, you get my drift. Regardless of your view on these new requirements, they’re here to stay. So the $64,000 question is, are you ready to start reporting?

There is a wide range of both functional and technical requirements that healthcare providers and payers will need to address as they start operating as an ACO.  Many of the early and emerging ACOs have started the journey from a baseline of targeted patient panels to the optimized management of a population, progressing through a model with some or all of the following:

These are 7 simple questions you must be able to answer and report on DAY 1:

1. Can you define and identify your targeted patient populations?
2. Are you able to measure the financial and quality performance and risks of these patient panels and populations?
   1. Can you quickly, easily and consistently report quality and financial measures by Physician, Location, Service, or Diagnosis?
3. Can you baseline your expenditures and costsassociated with various targeted patient populations?
   1. How will you benchmark your “before ACO” and “after ACO” costs?
4. Can you accurately monitor the participation, performance and accountability of the ACO participants involved in coordinated, collaborative patient care?
5. Will you be able to pinpoint where and when the quality of care begins to drift, so as to quickly intervene with care redesign improvements to limit the impacts on patients and non-reimbursable costs?
   1. Are you able to detect “patient leakage” and provide your organization the information for its’ management? (Patient leakage is when a patient that you are treating as an ACO for a bundled payment, leaves the network for their care)
      1. Is a particular provider/provider group sending patients outside of the ACO?  If so, is it for a justified reason?
      2. Does the hospital need to address a capacity issue?
6. Can you reconcile your internal costs of care with bundled reimbursements from payers?
7. Are you positioned for population health management and achieving the Triple Aim on a continuing basis?

In order to answer these questions you must have a highly integrated data infrastructure. It seems I’m not the only one who agrees with this tactical first step:

• The Cleveland Clinic Journal of Medicine agreed as it listed as one of its’ 5 Core Competencies Required to be an ACO “Technical and informatics support to manage individual and population data.”
• Presbyterian Healthcare Services (PHS) has been a Pioneer ACO for over a year. Tracy Brewer, the lead project manager was recently asked by Becker’s Hospital Review, “What goals did you set as an ACO in the beginning of the year and how have you worked to achieve them” and her answer – “One of the major ones [goals] was updating our administrative and IT infrastructure. We had to make sure we had all the operational pieces in place to function as ACO. We also completed some work on our IT infrastructure so that once we received the claims data from CMS, we could begin analysis and really get value from it.”

The ACO quality measures require data from a number of different data sources. Be honest with me and yourselves, how confident are you that your organization is ready? Is your data integrated? Do you have consistent definitions for Providers, Patients, Diagnosis, Procedure, and Service? If you do, great you don’t have much company. If you don’t, rest assured there are organizations that have been doing data integration for nearly two decades that can help you answer the questions above as well as many more related to this new thing they call Accountable Care.

What I Learned at Health Connect Partners Surgery Conference 2012: Most Hospitals Still Can’t Tell What Surgeries Turn a Profit

What I Learned at Health Connect Partners Surgery Conference 2012: Most Hospitals Still Can’t Tell what Surgeries Turn a Profit

As I strolled around the Hyatt Regency at the Arch in downtown St. Louis amongst many of my colleagues in surgery and hospital administration, I realized I was experiencing déjà vu. Not the kind where you know you’ve been somewhere before. The kind where you know you’ve said the same thing before. Except, it wasn’t déjà vu. I really was having many of the same conversations I had a year ago at the same conference, except this time there was a bit more urgency in the voices of the attendees. It’s discouraging to hear that most large hospitals STILL can’t tell you what surgeries make or lose money! What surgeons have high utilization linked to high quality? What the impact of SSI’s are on ALOS? Why there are eight orthopedic surgeons, nine different implant vendors and 10 different total hip implant options on the shelves? It’s encouraging, though, to hear people FINALLY admit that their current information systems DO NOT provide the integrated data they need to analyze these problems and address them with consistency, confidence, and in real time.

Let’s start with the discouraging part. When asked if their current reporting and analytic needs were being met I got a lot of the same uninformed, disconnected responses, “yeah we have a decision support department”; “yeah we have Epic so we’re using Clarity”; “oh we just <insert limited, niche data reporting tool here>”. I don’t get too upset because I understand in the world of surgery, there are very few organizations that have truly integrated data. Therefore, they don’t know what they don’t know. They’ve never seen materials, reimbursement, billing, staffing, quality, and operational data all in one place. They’ve never been given consistent answers to their data questions. Let’s be honest, though – the priorities are utilization, turnover, and volume. Very little time is left to  consider the opportunities to drastically lower costs, improve quality, and increase growth by integrating data. It’s just not in their vernacular. I’m confident, though, that these same people are currently, more than ever, being tasked with finding ways to lower costs and improve quality – not just because of healthcare reform, but because of tightening budgets, stringent payers, stressed staff, and more demanding patients. Sooner or later they’ll start asking for the data needed to make these decisions – and when they don’t get the answers they want, the light will quickly flip on.

Now for the encouraging part – some people have already started asking for the data. These folks can finally admit they don’t have the information systems needed to bring operational, financial, clinical and quality data together. They have siloed systems – they know it, I know it, and they’re starting to learn that there isn’t some panacea off-the-shelf product that they can buy that will give this to them. They know that they spend way too much time and money on people who simply run around collecting data and doing very little in the way of analyzing or acting on it.

So – what now?! For most of the attendees, it’s back to the same ol’ manual reporting, paper chasing, data crunching, spreadsheet hell. Stale data, static reports, yawn, boring, seen this movie a thousand times. For others, they’re just starting to crack the door open on the possibility of getting help with their disconnected data. And for a very few, they’re out ahead of everyone else because they already are building integrated data solutions that provide significant ROI’s. For these folks, gone are the days of asking for static, snapshot-in-time reports – they have a self-service approach to data consumption in real time and are “data driven” in all facets of their organization. These are the providers that have everyone from the CEO down screaming, “SHOW ME THE DATA!”; and are the ones I want to partner with in the journey to lower cost, higher quality healthcare. I just hope the others find a way to catch up, and soon!

What I Learned Last Week in Cambridge, MA at the World Congress Health Care Quality Conference

The subtitle for last week’s conference was “Moving from Volume to VALUE Based Care”. The theme’s that emerged from the speaker panels, presentations, and one-off conversations I had seemed well aligned:

1. Healthcare is currently experiencing a paradigm shift from the traditional provider-centric mentality to that of a patient-centric framework
2. One of the biggest challenges providers face in the pursuit of higher quality is figuring out how to appropriately leverage all of the data they’re currently collecting, manually and electronically
3. Emerging opportunities for reigning in costs and improving quality including ACO’s, AQC’s, PCMH’s, and others will only be effective if there are standards for implementation and measuring effectiveness consistently across the country
4. There are a handful of healthcare providers and payers who have taken significant strides in controlling costs while improving quality by implementing technology solutions that integrate data from across the continuum of patient care.

I was encouraged by the level of enthusiasm in the room. Dr. Allan H. Gorroll from Massachusetts General Hospital and Harvard Medical School made it clear that advancing the quality agenda will require significant investments in primary care; Dr. Kate Koplan spoke about Atrius Health’s push to reduce the problems of over testing and unnecessary treatments; Dr. John Butterly from Dartmouth Hitchcock Health discussed the Patient Centered Medical Home (PCMH) and suggested to all providers that they “have a patient on the team responsible for understanding how to establish the PCMH”; and Micky Tripathi the President and CEO of Massachusetts e-Health Collaborative mentioned the challenges of turning data into actionable information with problems like free text data, inconsistent data collection across care settings and the fear many clinicians have of “change” getting in the way.

I too was a co-presenter at the conference and was delighted by the response to our presentation. My counterpart Neil Ravitz, Chief Operating Officer for the Office of the Chief Medical Officer at the University of Pennsylvania Health System, and I discussed a recent solution we designed and implemented. We were able to automate the collection, integration, calculation, presentation and dissemination of 132 inpatient safety and quality measures across 3 hospitals and 7 source application systems. This new tool consolidates measures from across these hospitals and systems into one place for reporting and analysis through the use of dashboards and dynamic, drill down reports. The major benefits of the solution include:

1. Changed the focus of quality and decision support analysts from data production to data analysis and action;
2. Automated quality data collection to enable better accuracy and more timely data; and
3. Enabled a faster quality improvement cycle time by front line leaders

Dr. Atul Gawande recently suggested in an article in the New Yorker that healthcare should be prepared to start implementing standards for nearly all of the care delivered, from total hip replacements to blood transfusions. As we all know, he is a fan of checklists, one logical tool for standardization. He also states, “Scaling good ideas has been one of our deepest problems in medicine”. When I attend healthcare conferences like the one last week in Cambridge, I’m excited by the progress I see organizations making. When I leave the conference though, I’m quickly reminded of the grim reality of healthcare and Dr. Gawande’s point. And then I wonder, at what point will “patient centric”, “accountable care”, “value based purchasing” and all the other catch phrases of the past few years become the industry standard – and not the exception limited to conferences, New Yorker magazines, and headlines that are only ever heard or read, and rarely ever experienced.

Epic Clarity Is Not a Data Warehouse

It’s not even the reporting tool for which your clinicians have been asking!

I have attended between four and eight patient safety and quality healthcare conferences a year for the past five years. Personally, I enjoy the opportunities to learn from what others are doing in the space. My expertise lies at the intersection of quality and technology; therefore, it’s what I’m eager to discuss at these events. I am most interested in understanding how health systems are addressing the burgeoning financial burden of reporting more (both internal and external compliance and regulatory mandates) with less (from tightening budgets and, quite honestly, allocating resources to the wrong places for the wrong reasons).

Let me be frank: there is job security in health care analysts, “report writers,” and decision support staff. They continue to plug away at reports, churn out dated spreadsheets, and present static, stale data without context or much value to the decision makers they serve. In my opinion, patient safety and quality departments are the worst culprits of this waste and inefficiency.

When I walk around these conferences and ask people, “How are you reporting your quality measures across the litany of applications, vendors, and care settings at your institution?,” you want to know the most frequent answer I get? “Oh, we have Epic (Clarity)”, “Oh, we have McKesson (HBI),” or “Oh, we have a decision support staff that does that”. I literally have to hold back a combination of emotions – amusement (because I’m so frustrated) and frustration (because all I can do is laugh). I’ll poke holes in just one example: If you have Epic and use Clarity to report here is what you have to look forward to straight from the mouth of a former Epic technical consultant:

“It is impossible to use Epic “out of the box” because the tables in Clarity must be joined together to present meaningful data. That may mean (probably will mean) a significant runtime burden because of the processing required. Unless you defer this burden to an overnight process (ETL) the end users will experience significant wait times as their report proceeds to execute these joins. Further, they will wait every time the report runs. Bear in mind that this applies to all of the reports that Epic provides. All of them are based directly on Clarity. Clarity is not a data warehouse. It is merely a relational version of the Chronicles data structures, and as such, is tied closely to the Chronicles architecture rather than a reporting structure. Report customers require de-normalized data marts for simplicity, and you need star schema behind them for performance and code re-use.”

You can’t pretend something is what it isn’t.

Translation that healthcare people will understand: Clarity only reports data in Epic. Clarity is not the best solution for providing users with fast query and report responses. There are better solutions (data marts) that provide faster reporting and allow for integration across systems. Patient safety and quality people know that you need to get data out of more than just your EMR to report quality measures. So why do so many of you think an EMR reporting tool is your answer?

There is a growing sense of urgency at the highest levels in large health systems to start holding quality departments accountable for the operational dollars they continue to waste on non-value added data crunching, report creation, and spreadsheets. Don’t believe me? Ask yourself, “Does my quality team spend more time collecting data and creating reports/spreadsheets or interacting with the organization to improve quality and, consequently, the data?”

Be honest with yourself. The ratio, at best, is 70% of an FTE is collection, 30% is analysis and action. So – get your people out of the basement, out from behind their computer screens, and put them to work. And by work, I mean acting on data and improving quality, not just reporting it.

BIG DATA in Healthcare? Not quite yet…

Let’s be honest with ourselves. First –

“who thinks the healthcare industry is ready for Big Data?”

Me either…

Ok, second question,

“who thinks providers can tackle Big Data on their own without the help of healthcare IT consulting firms?”

Better yet,

“can your organization?”

“Big data” seems to be yet another catch phrase that has caught many in healthcare by surprise. They’re surprised for the same reason I am which was recently summed up for me by a VP of Enterprise Informatics at a 10 hospital health system – “how can we be talking about managing big data when very few [providers] embrace true enterprise information management principles and can’t even manage to implement tools like enterprise data warehouses for our existing data?” Most people in healthcare who have come from telecommunications, banking, retail, and other industries that embraced Big Data long ago agree the industry still has a long way to go. In addition vendors like Informatica who have a proven track record of helping industries manage Big Data with their technology solutions, still have yet to see significant traction with their tools in healthcare. There are plenty of other things that need to be done first before the benefits of managing Big Data come to fruition.

Have we been here before? Didn’t we previously think that EMR’s were somehow going to transform the industry and “make everything simpler” to document, report from, and analyze? Yes we now know that isn’t the case, but it should be noted that EMR’s will eventually help with these initiatives IF providers have an enterprise data strategy and infrastructure in place to integrate EMR data with all the other data that litters their information landscape AND they have the right people to leverage enterprise data.

Same can be said of Big Data. It should be relatively easy for providers to develop a technical foundation that can store and manage Big Data compared to the time and effort needed to leverage and capitalize on Big Data once you have it. For the significant majority of the industry the focus right now should be on realizing returns in the form of lower costs and improved quality from integrating small samples of data across applications, workflows, care settings, and entities. The number of opportunities for improvement in the existing data landscape with demonstrable value should be top priority to mobilize stakeholders to action. Big Data will have to wait…for now.

Please Stop Telling Everyone You Have an Enterprise Data Warehouse – Because You Don’t

One of the biggest misconceptions amongst business and clinical leaders in healthcare is the notion that most organizations have an enterprise data warehouse. Let me be the bearer of bad news – they don’t, which means you also may not. There are very few organizations that actually have a true enterprise data warehouse; that is, a place where all of their data is integrated and modeled for analysis, from source systems across the organization independent of care settings, technology platform, how it’s collected, or how it’s used.  Some organizations have data warehouses, but these are often limited to the vendor source system they’re sitting on and the data within the vendor application (i.e., McKesson’s HBI and Epic’s Clarity). This means that you are warehousing data from only one source and thus only analyzing and making decisions from one piece of a big puzzle. I’d also bet that the data you’ve started integrating is financial and maybe operational. I understand, save the hard stuff (quality and clinical data) for last.

This misconception is not limited to a single group in healthcare. I’ve heard this from OR Managers, Patient Safety & Quality staff, Service Line Directors, physicians, nurses, and executives.

You say, “Yes we have a data warehouse”…

I say, “Tell me some of the benefits” and “what is your ROI in this technology?”

So, what is it? Can you provide quantitative evidence of the benefits you’ve realized from your investment and use of your “data warehouse”?  If you’re struggling, consider this:

• When you ask for a performance metric, say Length of Stay (LOS), do you get the same results every time you ask independent of where your supporting data came from or who you asked?
• Do you have to ask for pieces of information from disparate places or “data handlers” in order to answer your questions? A report from an analyst; a spreadsheet from a source system SME, a tweak here and a tweak there and Voila! A number whose calculation you can’t easily recreate, that changes over time, and requires proprietary knowledge from the report writer to produce.
• What is the loss in your productivity, as a manager or decision maker, in getting access to this data? More importantly, how much time do you have left to actually analyze, understand and act on the data once you’ve received it?
• Can you quickly and easily track, measure and report all patient data throughout the continuum of care? Clinical, quality, financial, and operational? Third-party collected (i.e., HCAHPS Patient Satisfaction)? Third-party calculated (i.e., CMS Core Measures)? Market share?

Aside from the loss in productivity and the manual, time-consuming process of piecing together data from disparate places and sources, a true enterprise data warehouse is a single version of the truth. Independent of the number of new applications and source systems you add, business rules you create, definitions you standardize, and analyses you perform, you will get the same answer every time. You can ask any question of an enterprise data warehouse. You don’t have to consider, “Wait, what source system will give me this data? And who knows how to get that data for me?”

In the event you do have an enterprise data warehouse, you should be seeing some of these benefits:

1. Accurate and trusted, real–time, data-driven decision making
   • Savings: Allocate and deploy resources for localized intervention ensuring the most efficient use of scare resources based upon trusted information available.
2. Consistent definition and understanding of data and measures reported across the organization
   • Savings: Less time and money spent resolving differences in how people report the same information from different source systems
3. Strong master data – you have a single, consistent definition for a Patient, Provider, Location, Service Line, and Specialty.
   • Savings: less time resolving differences in patient and provider identifiers when measuring performance; elimination of duplicate or incomplete patient records
4. A return on the money you spend in your operating budget for analysts and decision support
   • Savings: quantitative improvements from projects and initiatives targeted at clinical outcomes, cost reductions, lean process efficiencies, and others
   • Savings: less time collecting data, more time analyzing and improving processes, operations and outcomes
5. More informed and evidence-based negotiations with surgeons, anesthesiologists, payers, vendors, and suppliers

In the end, you want an enterprise data warehouse that can accommodate the enterprise data pipeline from when data is captured, through its transformations, to its consumption. Can yours?

The Unknown Cost of “High Quality Outcomes” in Healthcare

“You were recently acknowledged for having high quality outcomes compared to your peers, how much is it costing you to report this information?”

I recently read an article on healthcareitnews.com, “What Makes a High Performing Hospital? Ask Premier”. Because so many healthcare providers are so quick to tout their “quality credentials” (yet very few understand how much it costs their organization in wasted time and money running around to collect the data to make these claims) and this article sparked the following thoughts…

The easiest way to describe it, I’ve been told after many times trying to describe it myself, is “the tip of the iceberg”. That is the best analogy to give a group of patient safety and quality executives, staffers, and analysts when describing the effort, patience, time and money needed to build a “patient safety and quality dashboard”  with all types of quality measures with different forms of drill down and roll up.

What most patient safety and quality folks want is a sexy dashboard or scorecard  that can help them report and analyze, in a single place and tool, all of their patient safety and quality measures. It has dials and colors and all sorts of bells and whistles. From Press Ganey patient satisfaction scores, to AHRQ PSIs, Thomson Reuters and Quantros Core Measures, TheraDoc and Midas infection control measures, UHC Academic Medical Center measures….you name it. They want one place to go to see this information aggregated at the enterprise level, with the ability to drill down to the patient detail. They want to see it by Location, or by Physician, by Service Line or by Procedure/Diagnosis. This can be very helpful and extremely valuable to organizations that continue to waste money on quality analysts and abstractors who simply “collect data” instead of “analyze and act” on it. How much time do you think your PS&Q people spend finding data and plugging away at spreadsheets? How much time is left for actual value-added analysis? I would bet you very little…

So that’s what they want, but what are they willing to pay for? The answer is very little. Why?

People in patient safety and quality are experts…in patient safety and quality. What they’re not experts in is data integration, enterprise information management, meta-data strategy, data quality, ETL, data storage, database design, and so on. Why do I mention all these technical principles? Because they ALL go into a robust, comprehensive, scalable and extensible data integration strategy…which sits underneath that sexy dashboard you think you want. So, it is easy for providers to be attracted to someone offering a “sexy dashboard” that knows diddly squat about the foundation, or what you can’t see under the water, that’s required to build it. Didn’t anyone ever tell you “if it sounds too good to be true, it is!?”

Why EMR’s Are Not Panacea’s for Healthcare’s Data Problems

So, you’ve decided to go with Epic or Centricity or Cerner for your organization’s EMR.

Think your EMR is Hamlin’s Wizard Oil?

Good, the first tough decision is out of the way. If you’re a medium to large size healthcare organization, you likely allocated a few million to a few hundred million dollars on your implementation over five to ten years. I will acknowledge that this is a significant investment, probably one of the largest in your organizations history (aside from a new expansion, but these implementations can easily surpass the cost of building a new hospital).  But I will argue: “Does that really mean the other initiatives you’ve been working should suddenly be put on hold, take a back seat, or even cease to exist?”Absolutely not. The significant majority of healthcare organizations (save a few top performers) are already years and almost a decade behind the rest of the world in adapting technology for improving the way the healthcare is delivered. How do I know this? Well, you tell me, “What other industry continues to publicly have 100,000 mistakes a year?” Okay, glad we now agree. So, are you really going to argue with me that being single-threaded, with a narrow focus on a new system implementation, is the only thing your organization can be committed to? If you’re answer is yes, I have some Cher cassette tapes, a transistor radio, a mullet, and some knee highs that should suit you well in your outdated mentality.

An EMR implementation is a game-changer. Every single one of your clinical workflows will be adjusted, electronic documentation will become the standard, and clinicians will be held accountable like never before for their interaction with the new system. Yes, it depends on what modules you buy – Surgery, IP, OP, scheduling, billing, and the list goes on. But for those of us in the data integration world, trying every day to convince healthcare leaders that turning data into information should be top of mind, this boils down to one basic principle – you have added yet another source of data to your already complex, disparate application landscape. Is it a larger data source than most? Yes. But does this mean you treat it any differently when considering its impact on the larger need for real time, accurate integrated enterprise data analysis? No. Very much no. Does it also mean that your people are suddenly ready to embrace this new technology and leverage all of its benefits? Probably not. Why? Because an EMR, contrary to popular belief, is not a panacea for the personal accountability and data problems in healthcare:

• If you want to analyze any of the data from your EMR you still need to pull it into an enterprise data model with a solid master data foundation and structure to accommodate a lot more data than will just come from the system (how about materials management, imaging, research, quality, risk?)
  • And please don’t tell me your EMR is also your data warehouse because then you’re in much worse shape than I thought…
  • You’re not all of a sudden reporting real time. It will still take you way too long to produce those quality reports, service line dashboards, or <insert report name here>. Yes there is a real time feed available from the EMR back end database, but that doesn’t change the fact that there are still manual processes required for transforming some of this information, so a sound data quality and data governance strategy is critical BEFORE deploying such a huge, new system.

The list goes on. If you want to hear more, I’m armed to the teeth with examples of why an EMR implementation should be just that, a focused implementation. Yes it will require more resources, time and commitment, but don’t lose sight of the fact that there are plenty more things you needed to do with your data before the EMR came, and the same will be the case once your frenzied EMR-centric mentality is gone.

Personnel, personnel, everywhere, nor any data to drink.

IT’S UNFORTUNATE: Large amounts of money are spent on new hires, yet little is left for employee and data improvement

I recently had an Executive Director of a Cancer Institute tell me,

“At this time, we plan to use simple spreadsheets for our database.  We are committing more than $500,000 for investment in personnel to start our translational laboratory this year.  I hope  we can subsist with simple spreadsheet use for our pilot studies.”

This sentiment immediately followed a detailed discussion, one that I’m very familiar with, concerning disparate researchers’ databases and how organizations’ needs remain unsatisfied, suffering from lack of integrated data.

Just so we’re all on the same page, let me make sure I understand this situation correctly –

1. You are currently using “simple spreadsheets” to assist researchers with all things data. You’ve astutely noticed that these stale methods don’t meet your needs, and you agreed to a meeting with Edgewater because you’ve heard positive success stories from other cancer centers.
2. You just spent three quarters of a million dollars on fresh staff for a new translational lab.
3. You are now budget-constrained because of this arrangement and want these new hires to use “simple spreadsheets” to do their new job… the same ineffective and inefficient spreadsheets, of course, that caused the initial trouble.

Did I understand all that correctly? I didn’t grow up in the ’60s, so I’ll continue to pass on what he’s smoking.

So who wins with this strategy, you ask? No one!

We keep buying things thinking ‘that’ll look better’ and it just doesn’t

It’s unfortunate for the researchers because they continue to rely on an antiquated approach for data collection and analysis that will continue to plague this organization for years to come.

How many opportunities will be overlooked because a researcher becomes overwhelmed by his data?

It’s unfortunate for the organization because it’s nearly impossible to scale volumes (data aggregation, analysis, more clinical trials, more federal/state grant submissions, etc.) with such a fragmented approach. How much IP will walk out of the door for these organizations on those simple spreadsheets?

It’s unfortunate for the brand because it can’t market or advertise any advances, operationally or clinically, that will attract new patients.

It’s unfortunate for the patients because medicine as an industry collectively suffers when:

• Surgeons under the same roof don’t recognize and notify their counterpart researchers that they have perfect candidates for the clinical trials they’re unaware of.
• Executives continue to suffer budget declines from lower patient volumes and less additional revenue from industries partnering with cancer centers that have their act together.
• Researchers under a single roof don’t know what each other are doing.

As in the picture above, “more” doesn’t necessarily mean “better.” Ancillary personnel and sheets of data don’t necessarily equate to a better outcome. Why continue to add more, knowing that this won’t solve the problem? Why infect more new hires with the same sick system? Why addition instead of introspection?

So, just as I told him in my response, I look forward to hearing from you in about 12-18 months; that’s roughly the amount of time it took the last dozen clients to call Edgewater back to save them from themselves.