MedCity Influencers, Health IT, Patient Engagement

Defining digital health ROI: 5 elements that might actually make sense

Every stakeholder has a different definition of what patient engagement or behavior change is and the value that it brings to their organization.

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In our line of work we see countless value propositions that digital health companies strive to (or claim to) deliver.

Maybe we’ve had one too many summertime margaritas, but lately this value proposition barrage has got us thinking: It seems that there is something missing in the digital health value chain.

Clinically and commercially validated digital health interventions are supposed to be paving the way towards success and bringing return on investment to the health stakeholder. This is what we’re all trying to do, right? The question is though: what exactly is the ROI that digital health promises to bring?

There are a lot of grey areas when it comes to digital health ROI quantification. Is it qualitative and health outcome improvements that matter? How do you take something this multi-dimensional, quantify it in a metric and then somehow attribute fiscal value to that? Is it an objective improvement in medication adherence? For whom? The least adherent? The highest “value” patients?

In our day-to-day life we define value as:

1) an immediate improvement in revenues for healthcare stakeholder and/or

2) demonstrable, repeatable, significant, short and long-term cost savings.

By the way, it is way easier to sell #1 than #2, which is why true systemic digital health care innovation is a challenge to commercialize. The short-term gains are not always apparent in the cost-savings equation and not everyone has the patience (or fortitude) to view longitudinal outcomes as valuable.

In digital health, the basic concepts of ROI are disguised in ambiguous terms like: patient activation, behavior change, and value-based pricing. Excuse the expression, but WTF do any of those mean? We’re trying to sell people on catchy sounding, but ultimately undefined, value propositions.

We are in the medication adherence business (we think so anyways) and we can say firsthand that every stakeholder has a different definition of what patient engagement or behavior change is AND the value that it brings to their organization. This variability means that we can’t use these terms in our everyday discussions about the ROI of digital health.

I would like to suggest that while these terms aren’t perfect, they can accurately reflect the value of digital health interventions. With a little definition and a lot of objective data, we can show healthcare stakeholders how the many domains of digital health can add value.

Engagement Assurance: What is it about digital health that can ensure people’s engagement with their health? Can this engagement be quantified? Does this engagement capture a stakeholder’s attention (it should) and, in parallel, does the engagement have a demonstrable longitudinal health or cost outcome? Keep in mind that the end user (patient) and payer (stakeholder) often differ in their perception of value from health engagement. Powerful digital health interventions do a good job of providing high value engagement for both groups.

Behavior change: How can one objectively quantify behavior change? What actual value does that demonstrate to the stakeholder? In our industry, adherence behavior change means different things to different people. For pharma, it means more scripts filled and more predictable revenue. For payers/providers, behavior change = reduction in per member per month costs, lower healthcare utilization, lower readmission rates and a proxy for the health of their accountable care models. We can measure behavior change but can we agree on a way to translate it into a quantifiable dollar value?

Patient Centricity (or more correctly, integrative efficacy): Features and functionality that we use to make sure technology fits a person’s needs (an individual end-user, a patient). These are the cool shiny things that allows us to affect points 1 and 2. But as we know from other industries, it’s not always the shiniest or trendiest solutions that win. I believe that it is not patient centricity that determines digital health success but integrative efficacy. How does a solution fit into clinical workflow? Can it be designed to be objectively measurable, enabling independent verification? Does it improve disease management at each level of the healthcare system (patient, provider, payer). Does an integrated approach have trickle down effects that generate value throughout the chain of care?

Population health management enablement: To me, this a long phrase to describe one word: scalability. How does the digital health solution complement the tools, business logic and the decision support systems already in place? Can a bit saved at each step multiply the value down the line? Does the data generated though the intervention enable big data approaches to risk flagging, proactive actions and improved analytics that ease the strain on the system?

Innovation: Everyone loves innovating. It’s been the bread and butter for my organization for years now. The question is: does the innovation produce value? How might the outside the box approach change established business models and processes? Does innovation solve a problem that might not be high value or worse create a solution to a non-existent problem? How does the innovation change the competitive landscape for stakeholders? Can you translate the amount of innovation into a concrete value for your organization?

So what does this all mean to the stakeholder? Hopefully, it is defined early in the design/deployment process. Hopefully, ROI is based on some form of targeting of a success metric, the appropriate population, a value threshold and measuring the difference being made. We implore you, healthcare stakeholders, define value, define ROI, and, above all, define their measurement. Then, once you’ve understood how digital health can add value to your organization take that definition, lead with it and then let the digital health community do its job and deliver.

Bill Simpson, PhD

Bill Simpson, PhD

This post was written by Amos Adler and co-authored with Bill Simpson. Bill Simpson began academic life as an undergraduate researcher, completing his B.Sc in Psychology at McMaster in 2007.  Following a three-year stint as a research assistant, he returned to McMaster in 2010 to pursue his Ph.D in Neuroscience.  In 2011, while working on his graduate thesis (examining the biology of postpartum depression) he started a small consulting company specializing in data analytics.  Four years and a doctorate later he is now Director of Data Science at MEMOTEXT while also holding the position of Senior Research Associate at the MACANXIETY Research Centre.  To date, he has 17 publications spanning topics from psychometric properties of rating scales to the use of internet based screening tools in mental health. His current research focuses big data analytic strategies, the “actioning” of health data and the use of technology to improve patient outcomes.  

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