In a recent whitepaper from consulting firm KPMG LLP—a Delaware limited liability partnership and the U.S. member firm of the KPMG network—senior executives at the firm looked at several clinical information system optimization strategies that patient care organizations could put in place to enhance clinical outcomes.
The authors of the Dec. 2015 paper, “Eliminating the Disconnect: Strategies That Bridge EHR Systems and Outcomes,” argued that “As population health management, improved outcomes and reduced costs become more entwined with reimbursement under value-based healthcare, effective use of clinical systems will be essential. These efforts require care coordination beyond hospital walls, which necessitates tools and processes that allow the seamless collection, sharing, analysis, and clinical use of data across facilities and locations. Optimizing EHRs [electronic health records] and other clinical systems represents an undeniably cost-effective and prudent approach to achieving these objectives.”
Indeed, the paper pointed out many of the core issues that physicians nationwide have been grappling with when it comes to EHRs: poor usability, time-consuming data entry, limited interoperability, and interference with the patient/provider relationship. Michael A. Beaty, principal at KPMG Advisory, and co-contributor of the whitepaper, works with hospitals all over the country that are trying to upgrade their EHR systems and bring them into the more modern era of healthcare. Beaty, based in Atlanta, recently spoke with Healthcare Informatics about his research, why so many physicians are dissatisfied with EHRs, and what it will take for the industry to move past the EHR adoption stage and into the optimization stage. Below are excerpts of that discussion.
We all know that the government has invested significant dollars into EHR implementation, but many providers have not gotten far past the adoption stage of the technology. What is your take on why this is?
There are technical limitations, there are regulatory limitations, and there are people limitations—all of which, combined, have put us into the situation we are in today, and we really have a long ways to go. There is quite a dense vendor landscape today in health IT; at HIMSS you saw the wide variety of choices that healthcare provider buyers—the CIOs, CMIOs, and CFOs—have available to them. When you contrast that to other functional areas like finance and human resources, you have a much smaller suite of products to choose from. So in the EHR world, there are hundreds of choices you can choose from to enable your organization with [one]. On the vendor side, there has been less innovation in the last couple of years and more of a focus on getting volume to remain viable.
Also, there is the heavy burden of dealing with regulatory demands via meaningful use (MU). So you have significant market competition which creates pressure in pricing and talent issues in terms of development of talent, as well as a heavy regulatory burden that has in effect driven the product roadmap for many of these vendors. Meaningful use as created a situation in which a vendor may have a very unique and differentiating capability in its product, but if it didn't map to MU Stages 1 and 2 over the last few years, it’s not a viable choice for any of the buyers.
When you look at future functionality requirements, such as the ability to do complex care coordination or manage populations, while some people are headed down that path, lots of health systems aren’t. Some need it and desire it, while a significant amount of others just aren’t there right now.
You also mentioned the limitations of the feds and the end users as reasons for the lack of EHR optimization across the industry. Can you expand on that?
The federal government funded the meaningful use program to incentivize health systems to invest in technology. That is a massive optimization strategy form the feds, and a lot of health systems really did take advantage of those incentives to bring their platforms up to the state-of-the-art in the EHR world. But those federal guidelines did not appropriately address—nor did they intend to address—physician usability, clinician satisfaction with the systems, redundancy of data entry, or time required to document certain things. That will come in the next generation, but in the MU-version of these platforms, while that was a great opportunity to upgrade the overall technology platforms for health systems, that upgrade path was not driven by the true end user, which is the clinician.
Michael A. Beaty
What do you define as true clinical information system optimization?
It’s a broad topic that involves thinking through the most optimal, or best-in-KLAS end-to-end processes for a certain clinical area. It’s about the people, the process, the technology, and the information flowing through those environments. We use the ED as a good example in discussions with our clients, as many run their own EDs. The goals of an ED are effective triage, throughput, and discharge into the acute, so how do those processes happen from a patient safety perspective, efficiency perspective, and a patient experience perspective? You cannot clinically transform without all of those aspects—the process, the people, the technology, and the information flowing through.
Where we see a huge opportunity right now, now that meaningful use is somewhat done in terms of doing the heavy lifting, is focusing on the technology layer to refine how EHRs are configured, built, and deployed. Now you can look at how they are interoperating with other platforms, and how systems are extracting and using data to impact the process workflow. Now is the time to do that in a strategic way as health systems have matured their existing EHR deployment, understand their shortcomings, and now have the desire and opportunity to take those platforms to the next level to help manage that clinical transformation initiative.
What are the biggest EHR complaints you hear about in addition to lack of interoperability and documentation challenges?
Those are the two big ones. There is probably not a health system out there that isn’t trying to figure out the integration strategy between platforms. Some systems are deciding between an all-Epic or all-Cerner strategy as opposed to an integrated strategy where they do have to make these systems share data in a seamless way. There is a lot of complexity there because some of these systems just don’t have open architecture.
Regarding documentation, for years, we have had quite a bit of success in the clinical documentation improvement space, and with technology like natural language processing coming along, the opportunities around documentation—doing it in a more sophisticated way and getting analytics out of it—are more present now. Having to spend too much time in the chart is a common complaint we hear, and that is a factor of the way systems were designed to meet meaningful use.
What are your thoughts on the recent Health Affairs article that found doctors spend 785 physician and staff hours per physician annually—equaling $15.4 billion—to track and report quality measures?
I wasn’t surprised by this. Those were some big numbers, and you can argue those numbers one way or the other. To me, the more important takeaway is that it’s a significant lift, even for the most efficient health systems, to document and report on quality measures. We do need more information out of these health systems to equally and appropriately evaluate how they are doing from a quality perspective, but I think the ability to abstract the data needed, do the reporting itself, and maintain integrity around that process is a huge burden in some cases, but also a real opportunity for improvement as technology gets more sophisticated.
We see an opportunity for systems to enhance their control over their clinical data. If you think about what people are contemplating using that quality measure data for, using it as a benchmark for payment in some scenarios for example, the level of rigor and control around the underlying data will be very high. Just like you see controls in place for publicly reported financial information, I think you will have a similar situation here where systems are expected to have strong control frameworks around their clinical quality data. Some are addressing this, but most are not thinking about it in this way, and are still thinking about the tactical process to do the reporting itself.
When will EHRs be able to effectively support population health and care management?
That’s a really good question. I wish I had a precise answer. Right now the industry is defining for itself what optimization truly means and entails, and some people’s point of view is more grand and ambitious than others’. I think you have to look at what will drive that optimization. Clearly, the regulatory agenda will continue to drive how people invest in their technology platforms. In some states, like New York, there are big Medicaid transformations going on. That program is really incentivizing and enforcing providers to think about how they use their technology to manage their populations at risk.
There will be cost pressures as well, as the total cost of ownership on these platforms is very high. As deployments stabilize, CIOs and CTOs will look at ways to make them more affordable to manage over time, and that will drive some innovation in terms of cloud-based providers and third-party host providers. There will also be significant demand from the users, both clinicians and patients in terms of how they interact with these systems. Their voices will drive innovation as fast as anything. People are fed up, and they want more access and more portability of their data. Is this happening in the next year? No, but we will see substantial improvements in five years, and it might take 10 years to feel like EHR platforms are truly helpful in facilitating this process, driving patient safety, driving clinician satisfaction, and making healthcare more interconnected.