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Time for Health Plans, Providers, and Patients to Team Up
By S. Michael Ross, MD, MHA
Current healthcare spending is unsustainable and driving us over a cliff. Despite having some of the most expensive healthcare in the world, the United States consistently underperforms on most care quality metrics. Take, for example, a 2010 report published by The Commonwealth Fund comparing healthcare in the U.S. with healthcare in Australia, Canada, Germany, the Netherlands, New Zealand, and the United Kingdom. The upshot: Our system ranks low on quality, access, efficiency, and equity.
A major driver is that incentives are misaligned between health plans and providers. It can all be blamed on economics. Health plans typically sell insurance to employers based on the lowest price, while providers typically try to negotiate the highest possible fee schedules.
Whether we stand in the shoes of providers or health plans, I’m convinced that our goals must be the same: improve the quality and outcomes of healthcare and reduce costs. To achieve these shared goals, there needs to be alignment of payment to providers. Collaboration is one of the best ways to reach this end result. To foster a successful partnership, health plans and providers must get past this traditional adversarial relationship and facilitate a dialogue about delivering value.
It’s no secret that fragmented care is one reason our healthcare costs are so high and that patient safety is at increased risk. More than half of Medicare beneficiaries have five or more chronic conditions such as diabetes, arthritis, hypertension, and kidney disease, so they’re routinely receiving care from multiple physicians. Failure to coordinate that care often results in patients not getting needed care, receiving redundant care, or suffering an increased risk of medical error.
A major emerging trend to address care fragmentation is the patient-centered medical home (PCMH). PCMH is designed to introduce accountability for ensuring coordinated care across the healthcare continuum. Early adopters of this model report superior clinical outcomes, more satisfied patients, and lower total cost of care. Health plans are quickly moving to PCMH. Likewise, providers are showing high levels of interest; a recent Medical Group Management Association (MGMA) survey shows that 20 percent of provider respondents already are affiliated with a PCM and 70 percent more are receptive to the idea—especially when health plans offer financial incentives to participate.
To make PCMH successful, it’s imperative that we break down the traditional information silos. We can begin to contain double-digit premium increases and align costs with quality of care only when primary care physicians, specialists, hospitals, health plans, and patients all have access to each other’s data. Aggregating, analyzing, reconciling, and intelligently distributing that information will be critical to support optimally coordinated care in the PCMH paradigm.
Workflow integration also will be a key to success. To prevent mass confusion at the provider level, the myriad data sources must be presented in a consistent and uniform manner to be utilized most effectively. Large-scale multi-payer platforms integrated into practice workflows already exist and can be leveraged to support rapid deployment of PCMH. On a related note, data to support coordinated care must be accessible across all form factors (like portals, smart phones, and tablets) in accordance with user preferences.
When we combine the administrative and financial data collected by health plans with the clinical data collected by providers, we have the power to establish continuity, promote positive outcomes, and support value-based reimbursement. From there, we naturally will reduce costs and improve patient satisfaction.
Clearly, if we want to move forward with quality care, we must enable a much richer data exchange between providers and health plans. We have in our midst the opportunity to rapidly achieve superior clinical outcomes and better health of populations—and to bend the cost curve. The time to do it is now. This is our last best chance.
S. Michael Ross, MD, MHA is chief medical officer of NaviNet of Boston, MA.
Ivo Told Me Not To Do It
By Dana Sellers
I’ve known Encore’s founder, Ivo Nelson, since the 1980s. I’ve found out over the years that he’s almost always right. In fact, I thought he was outright wrong once, but it turned out I was mistaken. So when Ivo tells me to do something, I generally listen. But every once in a while, like a horse with the bit in its teeth, I just have to go my own way out of pure stubbornness.
The other day I told Ivo I wanted to write an article about how fantasy football is like modern day healthcare. Without even a second to think about it, he told me not to do it. Normally, I’d follow his advice, but somehow I haven’t been able to get the idea out of my head. So, against Ivo’s better judgment, here goes…
In the old days of football, I really only cared about my team. I’d watch that one game, and then I’d turn off the TV. I knew who my players were, and they didn’t really change week to week. The rules were simple, and the scoring was clearly understood.
Then my sons needed one more person to complete their college fantasy league and they voted me in. Yes, me — Mom. And all of a sudden, the world of football changed. No longer was football something that was contained within the boundaries of a single game. It suddenly became something that was far more about strategy outside the walls—about finding and aligning with the very best. I had to plan, prepare and strategize. I found myself watching football in a whole new way.
Data was key. In fact, I found that I needed real-time data — on performance, on injuries, on projections. Lots and lots of data. I signed up for Sunday Ticket and StatTracker. I used all the filters and views on Yahoo! to make game day decisions, trades, and plan my next move. I downloaded all the fantasy apps for iPhone. I needed data all the time, wherever I was.
I also found that the scoring rules had become a lot more complicated and were a moving target. I’m in two leagues now, and what works in one doesn’t necessarily work in the other. The same touchdown that could help me win in one league could put me out of competition in my other league. I’ll watch a game hoping that my Cowboys will win, but that one particular player will do all the scoring because any other result will cost me precious fantasy points.
Here comes the hard part that Ivo thought I couldn’t pull off. So how is this like today’s healthcare?
I think there are a lot of similarities. In healthcare today, it’s not enough to think within our walls and turn off the TV any more. We have to be watching what’s going on across the industry, strategizing and planning and thinking about how to align with the best and brightest to accomplish what has to be done.
And data is key. We’re all going to need lots and lots of data—about performance, about quality, about projections. We’re going to need to be able to slice and dice it and look at the data in whole new ways. We’ll want it accessible for the end-user/stakeholder so that when we need it, we can get to it, wherever and whenever we want it. Our stakeholders aren’t going to want to submit a query and wait for a stale report to come back. They’re going to want the data NOW, just like they have for their fantasy football team. Why should they settle for less in their real-world job?
Finally, scoring is the hardest part. In fantasy football, if you lose, only your pride is hurt. (Personally, my teams aren’t doing so well right now, but I’m going to make some changes and see what happens next week.) But in healthcare, the score can mean survival as a healthcare organization. And we don’t just live in two leagues, we have two different scoring systems emerging right now—fee-for-service and pay-for-performance. If you optimize for one, you can hurt yourself in the other if you’re not careful. Get really good at reducing readmissions and you may see your revenue drop. Survival today means managing a shifting reimbursement world, understanding how government and payer “scoring” is changing in an almost real-time way, and being able to change and adapt in a nimble manner.
In the past, you only needed to take care of yourself and pay attention to your own hospital and your own local NFL team. Simpler times. Then along came reform, consumerism, and fantasy football. Now you have to take a more global, whole league view. Watch national trends, watch the future of government intervention, reimbursement trends, offensive and defensive schemes, and manage a diverse roster. ACOs, ICD-10, MU, VBP, and comparative effectiveness … 32 QBs, 120 or so RBs and WRs.
There is so much information to absorb and so much going on month to month in healthcare and week to week in FFL. Take your eye off of any of it and you can get crushed. Miss a nuance in a new regulation or payer contract or that a team made a scheme or roster change and you can be devastated. So stay alert, and keep your eye on the ball….
Oh, and by the way, Ivo—my “Fightin’ Frogs” are gonna crush your “Guiness Stouts” on Sunday.
Dana Sellers is president and CEO of Encore Health Resources of Houston, TX.
As hospitals make significant investments in EMRs — along with related updates to hospital billing, materials management, costing, and quality systems — they typically find that the promised analytics and reporting are not adequate. To tie together data from these disparate systems and even to optimize access to data within an integrated system, a Business Intelligence (BI) strategy is needed.
A typical BI strategy encompasses data governance; data staging and warehousing; tools for query, reporting, and dashboards; and a staffing model to build the initial framework and expand the architecture to serve the changing needs of the business.
For many organizations, this additional investment is hard to justify considering the outlays already made in their core systems. While working on one strategy recently, I was asked, “If we make this investment, how can we measure the direct return on investment (ROI)? What is the actual ROI of an investment in BI?”
To help the client answer these questions, I reached out to a dozen organizations, all of which have BI programs of some degree of maturity, and asked the very same questions. The responses I got were different and enlightening. I found that successful sites had a common theme: BI value is based on the use of the system to analyze data from various clinical and administrative systems and the willingness of the organization to act upon the findings to make changes that ultimately improve productivity and efficiency.
While these organizations varied in size, EMR maturity, and technology, I found commonalities in their responses.
A Cost of Doing Business
Many of the respondents stated that there wasn’t a planned ROI. They saw the investment in BI as a cost of doing business and considered BI as a necessary investment for which the value would be proven using the results from the analytics. Thus they did not establish clear financial goals beforehand. Instead, they identified gaps in their data environment that a BI strategy would address and chartered projects to suit.
Empower the Analysts (Plus a Little Insurance)
A smaller group of the participating organizations had a slightly clearer idea of what they’re trying to achieve with their BI investment: empowering their data and business analysts. In these cases, the organizations have fairly seasoned analysts who are clamoring for better tools to continue their roles as data analyzers.
This approach drives to more standardization of data and allows for replication of the current mysterious data manipulations of these trusted analysts. In addition, replacing the desktop database with an IT-maintained warehouse and a heavily macro-filled spreadsheet with a set of summary tables and dashboards provides a measure of insurance that the knowledge and analytics would be securely in place should the analyst decide to move on or could be used by others within the organization.
Targeted and Tactical
A core group of respondents challenged the premise of BI ROI by saying that BI has NO value to the organization in and of itself unless the project is matched to strategic initiatives. Their BI projects, interestingly enough, were often much smaller than the “insurance” or “build it and they will come” initiatives.
In all of these cases, there was a level of BI infrastructure required to make this all work, but the level of direct investment required was, in most cases, far less than a full soup-to-nuts data warehousing initiative. The ROI realized was the result of targeted, limited scope initiatives with only just enough infrastructure to deliver these results.
Although there were a few cases where it appeared that investments were being made to get BI in the door without truly understanding the solution on offer, those that had embarked on their BI strategies with a solid set of requirements and strong governance will be well served by their investment. There are complex questions that these organizations simply would not be able to answer without the data aggregation and query toolsets that an investment in BI brings.
But direct calculation of a return on investment can be difficult. For the “build it and they will come” group, they have made it clear they’re willing to let the ROI be determined through later projects. What the third group of respondents showed was that if you’re looking for ROI, you need a clear definition of scope and the organizational ability to respond to findings. It is possible to get an amazing ROI from a project with one smart analyst, some extract files, and an Access database. But it’s up to the organization to take that information and act on it, and it’s up to IT to build a support structure to ensure that that information continues to be available.
To design and implement a Business Intelligence initiative that delivers a positive ROI, start out with a limited scope and strong organizational support for acting on the findings. Select a single study area, get clinical support, and assign the most experienced analysts (second model) with support for data extracts as needed. Once you have proven value to the organization, look for ways to expand. Work to productionize the extracts and move the database off of the analyst’s desktop, so the value you get from that first study area is preserved and re-useable. Work on back-loading additional data as needed to expand the study area.
Find a second and third related organizational problem that could be piggybacked on the dataset you’re using and find an organizational sponsor who will take the action needed based on the BI data findings. If possible, expand the existing structures to contain the data needed for the new studies, but don’t create a tortured data model. Don’t be afraid to create another targeted data mart as needed.
In parallel with this first initiative, start building strong BI governance in the organization. Ensure that analysts across the organization are meeting regularly to discuss and document data standards and that wheel-reinvention is minimized. This can be a matrixed group rather than a formal reporting organization, but participation needs to be mandatory. The lead for this analyst group should be invited to executive-level steering meetings to listen for areas of frustration and concern with data and be able to both represent the work that is being done and bring the concerns back to the analyst team for action.
Through targeted initiatives, experienced analysts, and strong governance, BI projects will have a tangible ROI.
Jim B-Reay is a principal with Aspen Advisors of Pittsburgh, PA.