In the Field with our Experts

Healthcare Data’s Baby Steps: Meaningful Use, Pay for Performance, Quality Improvement (Part 1)

By Carol Newcomb, Senior Consultant

When I think about all the time and energy that has been spent and dollars invested in collecting and analyzing healthcare data over the past 30 years, it makes me crazy!!  From fee-for-service to HMOs to PPOs to HDHPs, billions of patient records exist that could inform policy on quality, safety, outcomes, effectiveness and efficiency, but as with our little Christmas-day Bomber incident, “We had the data, we just couldn’t put it all together.”  In the time that it has taken banks, retailers, even government to retool their operations to provide real-time, web-enabled, customer-focused applications, healthcare has gone nowhere.  The government is literally bribing healthcare organizations to convert from paper-based systems (or from stand-alone off the shelf-applications) to integrated electronic systems.  “Meaningful Use” is being touted as the newest data reporting incentive to show that your EHR system is up and at least partially running.  The first phase of evidence will include attestations that providers are using certain features of the system.  Not data, attestations!! 

And this isn’t the first attempt to get healthcare organizations to willingly embrace their data.  For the past two decades, outfits like the Joint Commission, AHRQ, NCQA, NQF and many others, have developed reporting metrics, hoping to drive down not just the cost of care, but the inefficient, wasteful and sometimes harmful practices that exist in our provider organizations.  Tying these measures to accreditation, CMS reimbursements, Pay for Performance and other carrot-or-stick mechanisms hasn’t been enough for hospital CIOs to seriously undertake more than just one-off fixes to their data infrastructure.  What they need is a back-to-basics roadmap for enterprise data management to integrate and govern data as it is gathered and aggregated over time.  Data governance is virtually non-existent in healthcare as a formal program.  Without governance, an organization cannot stand on its own data.

Healthcare is swimming in data.  Some would argue that what healthcare needs is better business intelligence.  Sure enough, it’s pretty hard to analyze a lot of loosely-coupled data that resides under any one healthcare organization’s roof, much less tie it to any one patient or doctor.  What good are analytics if the data haven’t been through rigorous quality controls?  What if the data aren’t stable or even accurate?   How many people contribute diagnosis and procedure and billing codes and modifiers to any single patient record?  How many people change it before a claim is submitted to a payer?  How many different sets of rules are there and who enforces them?  A few months ago, I went for an elective outpatient surgical procedure, but due to complications they were unable to operate.  Two days later, Blue Cross notified me of a claim for the full procedure.  When I called to contest it, they told me they couldn’t second-guess the doctor’s office.  Huh??  They paid for the un-performed procedure in full.  Wither our scarce healthcare dollars? 

(To be continued……)

photo by marisag via Flickr (Creative Common License)

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Carol Newcomb is a Senior Consultant with Baseline Consulting. She specializes in developing BI and data governance programs to drive competitive advantage and fact-based decision making. Carol has consulted for a variety of health care organizations, including Rush Health Associates, Kaiser Permanente, OSF Healthcare, the Blue Cross Blue Shield Association and more. While working at the Joint Commission and Northwestern Memorial Hospital, she designed and conducted scientific research projects and contributed to statistical analyses.

The Change Paradox

By Carol Newcomb, Senior Consultant

Change is hard.  How does your company manage change?  How do you personally respond to change?  Why does it seem like everything changes at the same time, or that it’s never-ending?  How can you possibly do your daily job while incorporating all the NEW ideas and NEW technologies and NEW demands on your time?  When are you supposed to get a chance to actually think about the purpose of changes, and figure out how to put them all together into a manageable pattern?  Sometimes it just seems like all too much!

I recently worked for a few years studying patient safety in hospitals, and collecting a lot of data from across the country on types of errors.  Humans, it turns out, are very adaptable, but also very entrenched in our learned patterns of behavior and physical agility.  By this I mean that things like driving a car, while initially quite challenging (remember how to slip the clutch while starting from a dead stop on a snowy uphill slope?) become simple with repetition.  After a while, you don’t even think about all the little steps involved, and you just quickly let out the clutch, gage the slipperiness of the slope, and adjust the gas.  No problem.  And when some smarty-pants (like your husband) tells you you’re doing it all wrong, the response is undoubtedly scornful.  Such is most people’s response to change.  “I can handle this myself, thank you very much.”  Remember your first response to having to use a mouse or a keyboard?  Several doctors I know were not too tickled.

And yet humans are also very adaptable.   The literature on patient safety, and use of other technologies for that matter, document how once the brain stops consciously THINKING about how to do something, the subconscious brain kicks in and takes over, instinctively executing each step of a process without needing to affirm the need for each particular step.  It becomes part of a repeatable pattern—like lifting a beer mug without spilling a drop—or speaking a different language—that you can do without conscious or deliberate parsing of each micro-step.  With enough time and practice, humans can adapt pretty well.

As consultants, what we work on with clients ALWAYS entails change.   And here lies the paradox.  While most clients look for consultants to make recommendations—to help them  with things they are challenged with, to provide expert advice, to design a new way of managing their business, to recommend new technology, to train staff on new ways of collecting information, etc.—the ability to consume that advice or to incorporate new practices is tempered by the organization’s sensitivity to the impact such changes will have on their environment.

How many times have you heard, “That’ll never work here; our culture just isn’t like that” or “That may be a ‘best practice’ but who has time for all the extra work?”  New ways of doing things may be good ideas, but deliberate attention needs to be spent on incorporating them, digesting them—so to speak—so that they are not only accepted, but willingly practiced and even improved on over time.  The biggest risk, when we leave a consulting engagement, is that the organization will simply ignore or reject our suggestions, and go back to business as usual.

This is the Change Paradox: Change is good, but change is bad. Change is hard when there is too much change at the same time.  Change is necessary, but it can be overwhelming and destabilizing, especially if it compromises the work at hand.   Change can be refreshing if the purpose and the steps are broadly understood and accepted, otherwise it can be a needless waste of energy that ultimately accomplishes nothing.  Change can introduce new ways of thinking about the business and smarter ways to achieve business goals, but if can feel like chaos if not managed in digestible increments.

As you embark on a new project or a new set of practices, take the time to enlist the understanding and acceptance of those who will be most impacted by the proposed changes.  Provide the time, the training, the leadership vision and purpose, and the support resources to ensure that all the ‘newness’ can be incorporated, repeated and rewarded.  Change is simple, but it’s also complex.

Image by Rafa Garcés via Flickr (Creative Commons License)

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Carol Newcomb is a Senior Consultant with Baseline Consulting. She specializes in developing BI and data governance programs to drive competitive advantage and fact-based decision making. Carol has consulted for a variety of health care organizations, including Rush Health Associates, Kaiser Permanente, OSF Healthcare, the Blue Cross Blue Shield Association and more. While working at the Joint Commission and Northwestern Memorial Hospital, she designed and conducted scientific research projects and contributed to statistical analyses.

Selling Enterprise Information Management

By Andy Field, Senior Consultant

I find it interesting how companies tend to focus on the hot issue of the day—and then fire up ad hoc teams of available resources to attack the immediate problem. For those of us who have had a long-term career focus on enterprise information management, this behavior has been a recurring source of frustration. This is because many of the problems being addressed in this manner are the result of not having good data management practices in place. Not only that, but each one of these ad hoc projects typically compounds the data management problems in a never-ending cycle. Let me explain.

The “best” example I have seen of this was working for a company that had embraced agile development. Every time there was a request from the business for new systems capability, the agile team would take great pride in building something quickly in response to the business demand. The business was initially happy that IT was responsive to their needs, and IT was proud of the statistics that showed they had delivered 240 new applications in the prior year. This was a very large company, so the number of systems is not an exaggeration.

The problem was that to sustain this pace of delivery, there was no attempt to engage enterprise architecture—let alone analyze information requirements against existing data sources. The result was that in the year mentioned, nearly 240 new SQL Server databases got built to support the 240 new application systems. After some time, the business realized there was some redundancy in these applications when they began to use them to report operational statistics and corporate performance indicators. They began to realize there were irreconcilable differences between these databases due to semantic inconsistencies. The application owners began to bicker over the differences and ended up divorcing themselves of each other. This resulted in fire drills every time a VP demanded that someone “just give me the numbers.” This wasn’t easy since they weren’t talking to each other anymore. Ad hoc queries, Access databases and spreadsheets began to spread like wildfire throughout the organization.

Over time, nobody knew what was where, as the ad hoc teams that had been put together for each of these fire drills had moved onto other things once the immediate problem was resolved.

Businesses are no different than individuals in their behavior.  If someone tells us we should plan for medical emergencies or, heaven forbid, our own demise by saving or acquiring adequate insurance, we may put this off because we have more immediate pressures from our family to purchase a new car or buy a bigger home. These are things we can realize immediate gratification from—not something that may happen in the foggy distant future. The problem becomes exacerbated when we not only put off investments to provide for our financial security, but we also mortgage our future by acquiring debt to satisfy our immediate personal and family desires.

In the company I talked about above, that’s what was happening. They were not only not investing in data management practices that would have curtailed the proliferation of standalone application databases, but they were also incurring a growing debt in terms of the cost and effort that, at some point in the future, would have to be accounted for. The ad hoc reporting currently taking place was becoming increasingly unsustainable. This was recognized and an enterprise data warehouse was seen as a more strategic solution to consolidated reporting in the long-term. However, they kept digging a bigger hole in terms of the number of source systems and mapping complexity that would need to be dealt with to build an EDW. Also, with every ad hoc solution came more Access databases and spreadsheets that took on a life of their own and further compounded the data management issues.

There is one significant difference, however, between our personal lives and business. Most of us are taken care of to a certain extent by our employer’s benefits plans and government programs—such as social security that automates these savings and would otherwise require us to make a conscious effort to not participate in these programs. This is not the case in business. In business, there is stiff competition for every cent to be spent that mandates the development of a strong business case if you hope to acquire the funding you need for your purposes. So rather than the relatively passive approach we take in our personal lives to ensure our long-term financial security, there is a need to aggressively secure funding to reduce our businesses data management risks.

So if you’d like to improve data management at your company, but have been frustrated by the lack of authority, resources, or company politics, there are a couple of things you can do:

• Make a business case—so they’ll give you the money. 
• Institutionalize data management—so it becomes like a benefits program that just keeps getting contributed to.

The most success I have had in addressing these two recommendations centers on cost justifying an Enterprise Information Management Competency Center (EIMCC) and embedding its roles into the company’s management, systems development, maintenance and compliance processes.  The following is the approach I successfully used at one company to do this:

• First, I analyzed the costs of the data management work (data architecture, data analysis, data modeling, DB design & support, ETL, data integration, information delivery, data policies and access, etc.) that had been done for all significant projects over the last couple of years. This provided heuristics to use for projecting the costs of this work against all future projects.
• I then analyzed the redundant data infrastructure and databases that had been created and were continuing to grow.

Using this information, I was able to develop a business case to demonstrate that had the company implemented an EIMCC, the costs for these activities and infrastructure would have been approximately 50% less than had been incurred. The main reason for the reduction in costs would be that data infrastructure and data content would have been leveraged across multiple projects instead of duplicated.  By using EIMCC resources on each of these projects, they would have also executed more efficiently because the specialized resources would already have the core data knowledge, designs and metadata available to them to support the new initiatives. The business case also addressed compliance by identifying data governance and compliance accountability and embedding the processes for these into the SDLC.

After implementing the EIMCC and institutionalizing the appropriate management disciplines and development processes, the cost of these activities after two years had dropped to 30% of what they were prior to having the EIMCC in place.  Some new resources had to be hired with the appropriate skills; however, these were more than offset by reductions of staff, primarily in the application development and maintenance groups.

Hopefully, you can use what’s been said here to help you come up with a successful strategy for your business and get beyond your data management frustration.  I’d love to hear from you about what approaches you have tried and what has and hasn’t worked.

photo by Daniel Voyager via Flickr (Creative Commons License)

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Andy Field has been involved in information management activities for over thirty years in both the private and public sectors internationally and domestically. He has held senior leadership positions accountable for establishing Enterprise Information Management practices in several organizations, including Fortune 500 companies. Andy has also consulted with clients from many industries and government sectors over the years and established and ran as president a consulting firm specializing in strategic information systems planning. He has broad experience in both operational and data warehouse projects from both a hands on and leadership perspective. Andy is currently a consultant specializing in Enterprise Information Management.