As the leaders of patient care organizations move forward into the post-implementation phase around electronic health records (EHRs), they face a welter of challenges. Facing intensifying and accelerating policy, payment, business, operational, and clinical practice challenges, they are realizing that what has been called “EHR optimization” is really a very broad set of challenges around interoperability, information systems optimization, and IT strategy, organized around the need for patient care systems to become remarkably more efficient, cost-effective, and demonstrative of improved patient outcomes, and more clinician end-user-friendly, all with the ultimate aim of organization performance improvement.
One person who has spent a great deal of time helping healthcare IT leaders work through these issues is Rob Barras, a national partner, consulting, at The Advisory Board Company (Washington, D.C.), and responsible for leading pursuits on electronic health record (EHR) planning, optimization, implementation and go-live solutions. He is a 27-year veteran of health care IT, and has worked for years as a consultant, as well as at vendor company organizations. Recently, the Philadelphia-based Barras spoke with Editor-in-Chief Mark Hagland about the challenges around EHR optimization in the current policy and operational landscape of U.S. healthcare. Below are excerpts from that interview.
Looking at the present moment in evolution of the U.S. healthcare system, what is the landscape like right now for EHR optimization, from your perspective?
When I speak to audiences of Advisory Board Company member organizations, I’ve been sharing with them a summary presentation that focuses on five key challenges that healthcare IT leaders are facing in the next five years, broadly speaking. The first of the five, and the foremost among them, is the need for healthcare IT leaders to create value from the EHR investments that their organizations have made over the last few years. That sounds easy, and it’s something that everyone talks about; but prioritization becomes the real value. CIOs say, I’m being asked to do more with less, and how do I do that? And I say, prioritize—make sure you’re adding value to the organization. And the ones doing better are doing more with less; so that’s number one.
The next four key challenges easily fall under that first one. The second would be leveraging IT to enable value-based care—and that means pursuing things around risk identification and capture. In that context, healthcare IT leaders need to look at the HCC (hierarchical condition categories) model, as articulated by CMS [the federal Centers for Medicare and Medicaid Services] to determine the complexity of a patient population. Two years ago, I would have said that 80 percent of CIOs, or really anyone—COOs, CFOs—had very little concept of HCC and risk-adjusted reimbursement; but that proportion has flipped now. And you’re starting to see the vendors get more involved in that work. But it’s very complex, and risky if you’re not documenting appropriately. But over the next five years, we’ll make progress in that important area.
The third key challenge is a set of challenges around interoperability. Looking at where we’ve been in healthcare and where we need to get to, it really is unbelievable that we’ve still got such a low proportion of interoperability; but progress is happening. The fourth key challenge is the ever-changing provider landscape. The acceleration of mergers and acquisitions reinforces care variation and increases cost. So we’re going to have to manage that and help standardize and decrease costs. And the fifth key challenge would be creating value from data. I sometimes hesitate to use the word “analytics,” because it’s over-used. Really, “analytics” just means making use of the data that is there or might be there. We need to move towards predictive analytics for risk assessment and management of populations.
From what we’re hearing from CIOs, CMIOs, and healthcare IT leaders across the country, healthcare IT leaders are getting stuck trying to put analytics solutions on top of EHRs, with regard to interoperability and ease of use.
I absolutely agree. And in that context, I recommend to everyone that they begin with data governance. Who are the operational stakeholders for each piece of data? How do we identify terms? How do we standardize terms internally? Length of stay may mean different things in different service areas. So you’ll need to develop a data dictionary. Go through that governance process first, and develop what we call an analytics roadmap. So now, let’s create that roadmap of what the requirements are in each area—everything from what dashboards we need in each clinical area, to what the dashboards are that are needed to manage specific at-risk populations. And ask, is my EHR vendor going to provide everything I need to manage all of this, or do I need another tool? And the thing is, there’s so much noise out there at HIMSS [the annual HIMSS Conference, sponsored by the Chicago-based Healthcare Information and Management Systems Society], and everywhere.
What CIOs and other healthcare IT leaders are telling us is that they’re having to do a lot of customization, in order to make their analytics solutions work for them.
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