Return on Investment for Digital Health Technology
Updated: Sep 23
A Credible ROI Is Built Before the Formula
Return on investment is often presented as a simple equation: subtract cost from benefit, divide by cost, and express the result as a percentage or multiple. The arithmetic is easy. The difficult work is deciding whose return is being measured, which benefits can be counted, what evidence supports the inputs, and whether the technology actually caused the result.
For digital health companies, the formula is the final step of a value strategy. A credible ROI begins with a defined buyer, population, problem, and pathway of change.
Value is larger than financial return
ROI is a financial metric from a single perspective. Value can include clinical outcomes, quality of life, experience, equity, access, staff satisfaction, caregiver burden, and strategic differentiation. Some of those benefits can be monetized, but others should remain visible without being forced into dollars.
This distinction prevents two common errors. The first is treating every positive outcome as a financial saving. The second is ignoring important nonfinancial benefits because they do not enter the equation.
A payer may benefit when hospitalizations decline, while a hospital may lose revenue. A provider may save staff time while a patient spends more time in appointments. An employer may value retention even when the health plan sees no immediate medical-cost change. Each stakeholder experiences a different balance of costs and benefits.
One ROI calculation should therefore use one perspective. If several stakeholders matter, build separate analyses and then explain the broader value story around them.
Define the problem before estimating the return
A solution can't create more economic value than the problem contains. The first task is to estimate the size of the addressable burden for the target population.
That requires specificity. How many members are eligible? What event or cost is occurring? How often does it happen? What is the unit cost? Which portion is preventable? How many members can the program reach? How effective is the intervention under realistic conditions?
The best demonstrations quantify both the size of the problem and the portion the solution can change. A large disease burden does not guarantee a large ROI if engagement is low or the product affects only a small component. A smaller, high-risk population can generate a stronger return if the intervention is well targeted and the avoidable cost is substantial.
This logic also guides market selection. Different payers have different prevalence, utilization, benefit designs, quality goals, employer customers, and cost structures. An ROI established in one regional population may need to be recalculated for a national plan or another line of business.
Count what is measurable, monetizable, and attributable
The webinar offers a useful standard for financial inputs, explaining that a benefit should be measurable, monetizable, and directly attributable to the technology.
Measurable means a reliable data source can detect the change. Monetizable means the change can be converted into a financial amount from the chosen perspective. Attributable means the analysis can reasonably connect the change to the intervention rather than to unrelated care, regression to the mean, or another program.
A reduction in hospital admissions may satisfy all three if claims data, a sound comparison, and unit-cost estimates are available. Improved confidence may be important but difficult to monetize. Better adherence could be measurable yet require a credible link to downstream events before it becomes a financial benefit.
Benefits that do not pass all three tests should not be discarded. They belong in the broader value narrative, clearly separated from the ROI calculation. This protects credibility while preserving the complete case.
The inputs deserve more scrutiny than the output
Most ROI work is input development. Companies may need literature reviews, claims analyses, pilot studies, clinical data, customer records, or actuarial estimates to determine baseline cost and expected change.
Every input should have a source and range. Prevalence may vary by market. Unit costs differ by contract. Engagement will not match a controlled study automatically. Clinical effectiveness can decline when the program moves into routine operations.
Sensitivity analysis reveals which assumptions control the result. A base case can use the most supportable estimates, while conservative and optimistic cases show how the return changes. If a small reduction in engagement turns the ROI negative, the commercial risk should be visible before launch.
The payer will often replace the vendor’s assumptions with its own. A transparent model invites that process. A black-box calculator creates suspicion, especially when it produces an unusually high return.
Choose the metric that answers the buyer’s question
ROI is not the only financial measure. A benefit-cost ratio compares total benefits with total costs. Payback period shows how long it takes to recover the initial investment. Savings per member or per engaged participant may be easier to compare with pricing. Budget impact can show the near-term cash requirement even when long-term ROI is favorable.
The appropriate metric depends on the decision. A health system evaluating a capital investment may care about payback period. A health plan comparing programs may focus on per-member economics and total budget impact. An investor may examine how customer ROI supports pricing, retention, and market size.
Healthcare also lacks one universal threshold for an acceptable return. An ROI near zero can still represent strong value when the program materially improves health, experience, equity, or clinician workload without increasing total cost. Interpretation should explain why the result matters to the specific buyer.
Design pilots to reduce the buyer’s risk
Evidence from a published study or another customer can open the conversation. Payers often want to validate the result in their own population because utilization, demographics, benefit design, and delivery systems differ.
A pilot should be built around the uncertainties that block a larger decision. It may test whether the company can recruit the intended population, achieve sufficient engagement, integrate data, change an intermediate outcome, or reproduce expected utilization effects.
Success criteria should be agreed before launch. The plan should define the eligible cohort, comparison, measurement period, claims runout, attribution rules, and decision that follows.
A pilot without a scale decision can become a prolonged demonstration that consumes resources without advancing the partnership.
Robustness matters more than the most favorable point estimate. A payer gains confidence when the model remains positive under conservative assumptions and when the company is transparent about limitations.
Use ROI to improve the product, not only the pitch
An ROI model can identify where the product creates and loses value. If implementation cost dominates, the roadmap may prioritize faster integration. If return depends on a narrow high-risk segment, eligibility and screening may become product capabilities. If engagement drives most of the result, communications and retention deserve the same attention as clinical features.
The model can also inform price. A defensible price reflects the value available to the buyer, the evidence supporting capture, competitive alternatives, and the risk allocated through the contract. ROI does not dictate price, but it shows the economic room in which pricing must operate.
The final business case should be simple enough to explain and detailed enough to audit. It should show the target population, problem size, mechanism of change, measurable benefits, program cost, assumptions, sensitivity, and nonfinancial value.
The formula is the smallest part of that story. Credibility comes from the decisions made before the numbers are placed into it.
About the Speakers
Craig Solid, PhD
Founder of Solid Research Group
Craig is a health economist who helps healthcare companies demonstrate clinical, economic, and operational value. He brings more than 20 years of research and data-analysis experience and has authored dozens of peer-reviewed publications and books on healthcare ROI and implementation. Connect with Craig on LinkedIn.
Demi Radeva, MSc
Founder and Chief Strategist at Akros Advisory
Demi has more than a decade of experience across Medicaid, Medicare, and Commercial health plans, including leadership roles at UnitedHealthcare and Optum. She now advises HealthTech companies on reimbursement, payer strategy, market access, and commercialization. Connect with Demi on LinkedIn.
Comments