In a changing healthcare landscape, uncertainties about data analytic capabilities loom large in the minds of patient care organization leaders. The industry is in the early days of an information revolution, and the question is not whether healthcare organizations should respond to the population health management trend, but instead how they are going to do so.
For providers and health plans alike, strengthening one’s population health management capabilities for the new healthcare is not an easy task, says Alex White, managing director the Corporate Finance/Restructuring practice at the West Palm Beach, Fla.-based FTI Consulting, an organization that focuses on strategic, operational, financial, and capital needs of businesses.
White, who has more than 12 years of experience in commercial due diligence, mergers and acquisitions strategy, growth strategy, and brand planning and innovation, recently sat down with HCI Assistant Editor Rajiv Leventhal to discuss the changing landscape of healthcare data analysis and population health management, the latest trends, and strategies for health plans and providers to take to achieve success in this arena. Below are excerpts of that interview.
In this changing landscape, what are some trends you are finding in the population health management arena?
Regarding the payer side, the national payers have invested heavily in analytics—and that has put a lot of pressure on the regional “Blues” to make sure they are keeping up. The broad trend—the catalyst of this—is pressure from employers, many of whom are getting more sophisticated themselves in terms of having analytics capabilities in health. They are hiring people with informatics backgrounds, or with a good level of experience in data analytics. That pressure is what they are pushing onto their payers; they expect them to not just say that a disease or wellness program is getting a return on investment (ROI), but they also want to be able to quantify it and get to a granular level very quickly. The major national payers have responded to that, and the Blues are now under pressure to do the same. The trend coming from that is that people are going outside to vendors or self investing in enterprise data warehouses that will allow them to pull claims data with clinical data (that they have access to) with pharmaceutical data, and put that in a single data repository that the entire organization can mine. That is becoming important.
Another associated trend is the emphasis on managing care across the care continuum. In order to do that, you will need to have access to a longitudinal view of a member’s experience over time. So being able to trace diabetics, for example, is key—Is the patient getting care frequently enough to be able to keep track of the impact on his or her sight? People are trying to pull that data and then form longitudinal views of customers across the care continuum.
The third area to highlight is that both payers and providers see this middle ground on population health management as being an area where neither has all of the skills necessarily. This means that people are trying to develop capabilities for themselves that they didn’t have previously. So for example, providers being able to develop the ability to analyze a risk pool of patients is obviously a new thing—they are stepping into payer territory. Similarly, on the payer side, you have them getting into a greater degree of hands-on management of the patient experience than they would have done in the typical disease management program. In a way, it is a race to take on this middle ground of really caring about keeping someone well as opposed to treating them when they get sick. And that’s really how our health system should work. Both sides are moving towards taking on risk for populations that become the area where value will be created.
What are some strategic tips you would give to health systems as they move forward with population health management?
Taking a step back, many small providers haven’t even started to think about where the next generation of population health management, which is driven by analytics, will be going. But I think the answer is different for different types of providers. If you take a community hospital network who hasn’t thought about it to date, the simplest thing for them to do would be to begin to focus on areas that will directly impact them in the short term. An obvious one would be readmissions, where you already have an additional incentive from the Centers for Medicare & Medicaid Services (CMS) from a reimbursement perspective if you are able to identify individuals who might be at risk for readmissions. Short term, there are tactical things like that that can immediately impact the bottom line for a provider.
Longer- term, and for the more sophisticated and larger providers, there is a range of uses of analytics for the uses of population health management that will position them well down the line. For example, if a provider wants to take on risk for a population as a whole, they may want to have the ability to get ahead of the game in terms of using analytics for actuarial analysis on that population they are taking risk for. Or if they want to start taking perspective bundled payments for knee and hip surgeries, it may advantage them to be able to trace physicians within their organization that are providing those services with greater or lesser complications. There is a real spectrum of what the appropriate strategy should be, and it varies by size, sophistication, and reimbursement environment from a commercial payer perspective that the provider is dealing with.
If the goal is to deliver information-powered care, you will need more access to patients’ health statuses. How can that be acquired when patients are not within the doctor’s office’s walls?
The answer is that in 10 or 20 years time, most of us expect that there will be a flood if information outside the office that is facilitated by technology. It’s already happening, with technology such as Bluetooth-enabled pill bottles. So if I open the bottle in the morning, the bottle will actually say I have taken the drug. And if not, I will get an alert on my iPhone telling me I am not compliant with that drug. There is data with things like that, and there is also data from monitoring devices in the inpatient setting, as well as data in an intensive care unit (ICU). We are still in the early stages of really adopting these things because a lot of providers don’t have the ability to cope with that data, analyze it, act accordingly on it, and drive change from it, and equally, payers are just trying to get with grips to analyze claims data, let alone real-time streaming data from devices. This could be the next wave that we’ll see.
How are physicians taking to this movement?
It depends on the organization you are in. If you are in an accountable care organization (ACO), you will likely be required or it will be strongly suggested that you build analytics into your practice. So if a provider is entered into a patient-centered medical home (PCMH) agreement, they will likely have a dashboard that will help them identify gaps in care and manage their outreach to patients appropriately, and that would be part of the norm of doing business. At the next level, you have physicians who are employed by a hospital, and the hospital network wants to move to a greater user of analytics. In that situation, there may be some back and forth between physicians and the hospital, but ultimately the hospital is likely to have a greater degree of influence. And the far extreme is that you have physicians who are still conducting much of the work on a fee-for-service basis, so those people might be resistant to a new technology that they think can compromise the quality of care they provide their patients.
What are the main challenges organizations are facing when it comes to population health management?
Many of the challenges are centered around the mechanics and practicalities of the shift to embedding informatics more in the organization. The single biggest mistake is dipping your toe in the water as opposed to making a real commitment to informatics. The official first step for getting analytics capability is building an enterprise data warehouse, in which you have a single source of truth. A common mistake is trying to take shortcuts around that by maybe pulling part of the data or pulling data only for certain populations, but not stepping back and saying, “This is the way we’re going to go, so let’s do it properly one time.”
The second part is appropriate governance of that data. This can be done in several ways, but you do need a clear governance structure. One organization we worked with decided to create an executive level role where there was a head of informatics responsible for managing and organizing the data, and ensuring it could be used for different departments in the organization. Whatever the model, there needs to be a clear understanding from the start in terms of whose job is it to make sure the data warehouse is built according to specification that will best be appropriate for uses around the organization.
Strategically, as you get into data analytics, you get into more information that could lead to potential conflicts, or at least tradeoffs that you will need to make. You need to think before you gather information— why are you doing it and how will it be used? Often, organizations aren’t clear about what their strategic objectives are. Think about that before you get a large team of people getting intimate details about the data, since you don’t want to waste a lot of time. It is important to remember that because the environment is changing so rapidly, you will need to adapt the plan as you go forward—flexibility is crucial.
