By: Scott Kraft
The entities that fund health care services – primarily federal and state governments and private insurance companies – are increasingly looking for new ways to take health care expenditures to quality results.
They’re demanding that the providers of health care services know more about their patient populations, be more proactive at managing health conditions and avoid providing repetitive, needless services.
New entities such as Accountable Care Organizations (ACOs) and new Shared Savings Programs are pushing the notion of population health management – the idea that a whole group of patients can be managed at the best cost to the best outcome – and holding health providers responsible for delivering.
Excuses such as patients not being invested in their own health aren’t being accepted either.
It will take new technology really influence the results, and the reality that many physician practices are starting to realize is that electronic health record (EHR) systems, while adept at helping to create documentation and manage individual patient encounters, aren’t always as effective at producing timely data on entire subsets of patient populations.
Population health management technology is centered on three key areas. First, helping the provider community to keep closer tabs on patient populations and engage with their most at-risk patients to help drive better compliance.
Second, giving the patients new tools and technology – much of it web-based – to help them better track their own health through metrics and data.
Finally, connecting the patient-centered data and efforts to the health providers in a way that doesn’t overwhelm the provider with useless data, but gives physicians and entire health care teams access to critical data quickly.
One example of a company driving rapid advances in population health management on the provider side is Ft. Lauderdale-based SRG Technology. The company’s population health management tool, TopCare, can be configured by health care providers to collect and sort data based on the entity’s own goals when it comes to managing a patient population.
As a result, if a physician group is looking to achieve a certain objective for a patient population, such as diabetics, the population health management tool will pull in patient data from multiple places – the electronic health record system, a practice management system, laboratory results or data – and push the patient toward the right solution based on the intensity of the intervention needed.
Not every patient needs an interaction with a physician, for example. A patient who needs guidance on screening services could be directed to a nurse or even a member of the front office staff to reach out and make contact.
Patients who need more aggressive interventions will be assured of getting more time with the physician, because the system is set up to better manage the flow of data to ensure those patients don’t fall off of the radar screen.
The physician practice is better equipped to avoid the scenario where the most compliant, engaged patients are coming into the office too much, but the practice’s patient population isn’t optimally managed because some patients have fallen through the cracks.
Patient engagement is key
As important as the physician piece is, getting tools into the hands of patients that better position them to successfully achieve their goals is a critical part of success.
That’s where companies such as Get Real Health come in. The Rockville, Md.-based company is focused on getting the right tools into the hands of patients to encourage them to better manage their own day-to-day health, then get the patient produced data into the hands of physicians and other providers to drive better interventions.
Patient engagement is the key to population health management – if you can’t reach the patients, efforts are going to be useless, believes Robin Wiener, president and founding partner of Get Real Health.
The company’s patient engagement platform, InstantPHR, was recently ranked as the best patient engagement tool in the market by Chilmark Research.
Wiener relays how the company uses analytics, in one example, to get a large group of diabetics age 35-50 into an electronic management program that includes phone reminders and alerts.
Patients are able to input data as well. No phone calls are needed, but the patients can be better managed based on the data they’re providing, rather than just being given information and not seeing results.
In one patient cohort, Get Real Health started with patients with an average A1C reading that was more than 10 – about seven is average – and glucose levels in the 190 range, a sign of very poorly managed patients who didn’t really understand diabetes, Wiener says.
The patients were given glucometers that fed results directly into the company’s patient portal and directly to the doctors, with the critical readings and information highlighted for the provider, Wiener adds.
There are really two success stories here. First, getting that higher level of patient engagement and response. Second, the patients were producing a lot more data, which helped them to get an intervention before they reached a health crisis and also created a more meaningful data set to work with then just having the patient show up in the office two to three times a year.
Patients were also given contextual information about their results. Patients with high blood sugar would get content about the health implications of high blood sugar readings, while patients with low blood sugar might get an alert to drink some orange juice or about what could happen if their blood sugar continued to drop.
The engaged patient will be a key step in meaningful use stage 3, and giving patients simple alerts and reminders via phone are a fast, easy way to engage, Wiener says, noting that the patients in the program saw their A1C levels return to normal ranges and have generally stayed in that range.
While electronic health record systems are doing a better job of slicing and dicing data then they used to, it is still very hard for them to produce the data in such a way that the provider knows what to do with it, Wiener says.