“Wellness” has become a new mantra for healthcare organizations. Medicare Advantage programs are vaunting their support for “wellness,” and you see wellness campaigns at pharmacies, employers, and elsewhere. Particularly pertinent to the Healthcare IT Today blog, wellness is a goal promised by many digital apps.
Do these programs give us what we seek? That is the question asked by payers, clinicians, and all of us who are considering the use of wearables and digital apps. Even though downloading a wellness app or signing up for an online program isn’t fraught with the same risks as choosing a medication or invasive medical treatment, we all want some assurance that the intervention works.
This article begins a series that looks at useful measures of health and how the companies that promote wellness programs demonstrate their success. We’ll see measurements of objective outcomes, patient-reported outcomes, and what payers look for when they can’t get direct evidence of improvements in wellness.
You’ll note, as we survey the wellness solutions and measurements used, that the leading organizations in this space are payers, not clinicians. I’m sure that doctors and nurse practitioners truly care for the overall happiness and wellbeing of their patients. But the institutions aren’t set up to make that a priority. Sara Shanti, a partner specializing in health care at law firm Sheppard Mullin, points out that by setting up various incentives that observers broadly group under the term “value-based care,” the payers are a driving force in the wellness movement.
Research, correlations, and measures
An article examines the clinical literature for about 20 different measures of wellness, and distinguishes wellness from related concepts: absence of disease, wellbeing, and quality of life. Jim Wallace, CEO of DecisionRx, points out that physicians are not usually equipped to collect measures of wellness, nor does the typical electronic health record (EHR) have fields to store them.
Clinical effects are established by various forms of research: clinical trials, longitudinal studies such as the historic Framingham Heart Study, and so on. Demonstrable correlations take a long time, and validation of results usually requires multiple studies.
To watch the process in action, although the bad effects of tobacco were long known, a clear clinical link to health wasn’t established until about 1953. The dangers of second-hand smoke became known only much later and contributed to overcoming tobacco companies’ resistance to smoking bans.
Alcohol has even a more muddled clinical history. Until recently, some experts claimed that a drink a day could improve health. Only this year did the World Health Organization announce that any level of alcohol consumption is harmful. (My PCP told me starkly, “Alcohol is a toxin.”)
The degree to which pseudo-science can take over the wellness space is illustrated by the credence that the public gave to a marketing campaign to encourage 10,000 steps a day. (Although the number was arbitrarily chosen, one article called it a good goal.) We want to avoid wellness fads.
Another typical, but questionable, use of data comes from a study by the company dacadoo. It’s nice to see that “users who have a connected wearable device average a 30% higher activity rate than users without wearables” and that “the retention level of these users after 12 months was shown to be 36% higher than users without wearables.” But do these statistics justify dacadoo’s claim that “the use of wearable devices is strongly encouraged for our clients looking to boost engagement of their platforms powered by dacadoo technology”? Can dacadoo go further to show that a 30% increase in activity means better health?
Depending on how the dacadoo platform is used, that might not be their problem to solve. All they need to prove to digital companies who use the dacadoo platform is that engagement can be improved. Whether engagement leads to health is up to the client company to prove—and as we’ll see in this series, the proof may vary widely depending on the company’s clients.
Categories of Measures
Clinicians, payers, and regulators tend to look at two different types of measures: outcomes and process indicators. Both are actually proxies for health.
An outcome is a medical change: Did the A1C of a person with diabetes go down? Did an obese person lose weight? Are vital signs looking good? Research has shown such measures to correlate with both life expectancy and quality of life.
Outcome measures are meaningful on an actuarial level, of course: not tied to individual patients on a one-to-one basis. In other words, we probably all know someone with terribly elevated blood pressure who lived a long and happy life. But your odds of feeling good are much better if you pay attention to the measures.
And as pointed out by Shanti, patient data may tell you a problem exists but not how to fix it. OK, so your blood pressure is high. Do you need medication, a dietary change, or just less stress?
A process indicator answers questions such as: Did you get to your doctor’s visit? Did you get colonoscopy or mammogram recommended by the experts? Process indicators are much easier to measure and to achieve than outcomes. But again, research has established enough of a link to health that payers are satisfied with process indicators.
Process indicators are the basis of the Medicare’s Star ratings, probably the most important measures clinicians pay attention to. Medicare has wisely refrained from making a clinician responsible for outcomes.
As mentioned by Erica Kraus, a partner specializing in value-based care at Sheppard Mullin, the actions of a single clinical institution in the U.S. healthcare system can have a tenuous relationship to outcomes. (This is why some Accountable Care Organizations have trouble achieving their value-based goals.) Patients with chronic conditions may come for a time-limited course of treatment and then go off, no longer subject to regular supervision by the physician. Furthermore, a patient could do everything right, improve their health, and experience an unexpected health event, from contracting an infection to getting hit by a bus.
Kraus also says that it can be hard for payers and providers to agree on measures in their value-based contracts.
Karl Ulfers, co-founder and vice president of growth at DUOS, praised the Star ratings as great examples of healthcare measures, saying that they were chosen well to be meaningful, includes incentives, and are clearly defined so that clinicians could aim for compliance without confusion.
Kraus also praised CMS’s efforts to provide incentives for value-based care, including its tabulation of Star ratings. She says, “The efforts by CMS to incorporate and reward achievement on value measures, such as Star ratings, are seeing dividends.” More and more institutions are using data to improve coordination and quality of care and financial incentives have improved. More subltly, “safe harbors” and exceptions in the regulations are allowing clinicians to receive benefits for value-based care without risk of being penalized for violations of laws such as the Anti-Kickback Statute and the Stark Law.
Shanti mentioned a plethora of other things that companies might measure, both for the individual’s benefit and to assess progress toward commercial goals. Medication adherence, for instance, might be measured to show conformance to a treatment plan, support eligibility in a program, or meet the requirements of a court order. Safety and quality metrics (such as infection rates), incidence of diseases such as COVID-19 in the population, the success of a prophylactic measure or treatment, and the popularity of a service might be measured. Other applications of measurements mentioned by Shanti are patient surveys on Yelp or Google, and gamification statistics that reflect patient engagement in their treatment plan.
Jake Sattelmair, executive vice president and general manager at Wellframe, a HealthEdge company, distinguishes between short-term and long-term impacts. A typical short-term impact is a process indicator such as whether your intervention helped them get to a visit. Long-term impacts include healthier patient actions, self-reported quality of life, and reductions in total cost of care.
Christiana Voelker, healthcare industry lead at Avanade, says that personal goals such as being able to attend a family event or abstaining from alcohol are subject to measurement, just like more objective goals. We can also demonstrate productive behaviors such as using a tablet to check one’s health plan can lead to better outcomes.
Now that we’ve surveyed broadly the types of measures used to indicate wellness, the next article in this series goes deeper, looking at specific measures adopted by several organizations.
