Page 1 - DeterminingtheROIfromRemotePatientMonitoringAPrimer

Determining the ROI from Remote Patient Monitoring: A Primer

Remote patient monitoring (RPM) refers to a variety of high tech and high touch patient care
approaches that do not require a face-to-face visit. RPM solutions promote better health at lower
costs because they enable more frequent health status monitoring and feedback, make home
the central place of care, serve as an early warning system of deteriorating health, enable early
intervention, and, as a result, typically reduce emergency room visits and hospitalizations.

Before investing in an RPM program, organizations naturally seek to understand their potential
return on investment (ROI). This document is intended to serve as a brief guide to the factors that
should be considered in such an analysis. This is presented through the hypothetical example of an
organization seeking to create a care management program for individuals with congestive heart
failure (CHF) who will be engaged for at least six months, if not longer.

Key Factors Detailed

The essence of an ROI model is that of a beneit-cost test. The following example examines beneits
to costs on a PPPY basis (per patient, per year). Organizations may also want to calculate ROI
based on their total expected patient volume/enrollment.

Beneits. The beneit of an RPM-based program will be a function of the projected reduction of the
average cost of a given population. For this example, we assume that the organization applies the
selection algorithm to a data set and draws a population with an average projected cost of $20,000
per year. Based on a literature search, the organization decides that a 20 percent gross reduction in
annual costs is feasible. The gross per-patient savings – or beneit – is thus $4,000 per year.

Costs.The two key categories of cost are labor costs and technology.

Labor costs are a function of the costs of paying staff and their caseloads.

Staff costs will differ in different areas and between different organizations based on multiple factors
ROI Brief
such as level of credential, relative area labor costs (such as New York City vs. Poughkeepsie), and
whether a workforce is unionized. This later factor may also have an impact on caseloads.

Caseloads will be a function of the acuity level of a managed population, and worklow, which in turn
will be heavily inluenced by the RPM intervention being used. Stafing requirements can be treated
as ixed project-based overhead or as a variable cost.

For the purposes of our example, the organization implementing the hypothetical program is in
the Midwest, where area costs are at about the national average – and the average fully loaded
staff cost is $100,000. Furthermore, the organization’s selection algorithm is tied to identifying
patients who have had at least two hospitalizations in the previous year. Given the nature of the CHF
population and technology selected, our example assumes that a care manager can support 200
individuals (which achieves the desired cost reduction). The average labor cost per patient thus is
$50 per month, or $600 per year. Implementing an RPM program often necessitates the creation
of new job functions or roles that may not have existed before. ROI models may incorporate new
Fall labor costs that are incurred for this reason.
2 01 1 Center for Technology and Aging
Afiliated with the Public Health Institute
Supported by a grant from The SCAN Foundation