Population Health and Patient Engagement: A Reckoning Is Coming

Population health and patient engagement should be best friends. To draw conclusions for population health, you need a lot of data, and patient engagement that is, patients interacting digitally with treatment plans and healthcare providers, generates a ton of data. Population health tries to analyze the general to get to the specific and identify patients at risk. Patient engagement starts with the specific patient, and with enough data recorded by those patients, can find general trends.

With patient engagement, the information is real-time. With population health it is backwards-looking. Population health has the richness of the medical teams notes and diagnosis but it is missing the patient perspective. Patient-generated data will have diagnosis if it’s part of a treatment plan prescribed by a physician, but it won’t have the full notes. A blurring of the boundaries between population health and patient engagement presents a way forward to greater insights about both individuals and groups, and can make population health actionable at the individual patient level by providing personalized instructions (with or without care managers).

However, to get to this desired end-state, we need to clear some obstacles, first of which is the idea that patient engagement generates too much data for physicians.

Yes, an individual physician does not want to see or review each data point that a true patient engagement solution generates. However, this information can be extremely interesting to the patient, especially when looking for trends to help self-manage a chronic condition so it is worth enabling patients to collect it. For example, looking at whether certain foods trigger arthritis, or whether certain activities trigger headaches. However, to draw conclusions like this, you must record a lot of data points and in real-time, and this makes physicians nervous. They have enough to do, and not enough time to do it in, so this data cannot add to that workload.

As well, patient-generated data is messy, which can be intimidating, especially in an industry that is looking for deviations from norms. The challenge with patient-generated data is that it can uncover that the long-tail is actually longer than previously thought, that there are sub-groups within previously thought to be homogeneous groups of patients with a similar condition. In the long run, this will result in medical breakthroughs and personalized medicine. In the short run this can be difficult to deal with in the current systems.

the long-tail is actually longer than previously thought

Does that mean that we shouldn’t collect patient-generated data? Not at all. Helping patients track their experiences is a great first step to self-management. Knowing whether they are following a treatment plan, and what their experiences are with that treatment plan can help healthcare systems determine the impact of their instructions outside the clinic.

Although physicians don’t want all this data, healthcare organizations both providers and payers, should want it. Other industries would kill for this type of data. Data scientists and population health managers at health systems should be clamoring for this valuable patient-generated data.

Patient-generated data is usually collected in real-time so it may be more representative of the actual current population. The benefit of real-time collection is that further exploration of the actual patient experience is possible and can be used to prevent issues from escalating. With backwards looking data whatever was going to happen has happened, so you can only use it to impact new groups of patients not current groups.Patient-Generated Data

Finally, patient-generated data is less likely to be siloed, like clinical data often is, because the patient experience is broad and often messy and crosses clinical department thresholds (or more simply, patients are usually treated for more than one issue at a time.) Being relatively new to market, patient-engagement systems are built on modern and interoperable technology which also makes accessing data for analysis easier.

So where will we end up? To our team at Wellpepper, it seems inevitable that influencing and understanding patient experience outside the clinic. If you are making decisions for an individual patient with only a few clinical touch points, this is a very thin slice, often with a specific clinician’s specialty lenses on the actual situation. While healthcare systems are currently dipping their toes in the water on collecting and analyzing this data, if they don’t embrace the whole patient, patients will vote with their feet and pocket books towards organizations that are data and technology driven.

Posted in: Adherence, big data, Healthcare Technology, Healthcare transformation, Interoperability, M-health, patient engagement, population health

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