

Harvard University photo
Friday, July 10, 2009
ROI algorithm calculates value of mobile health care
By Jim Schakenbach, Special to Mass High Tech
Millions of dollars and countless studies have been used to demonstrate the value of our traditional health care system. But what about nontraditional methods of providing health care and prevention services? How do we judge those programs, how well do they work, and are they worth funding?
These were the questions that drove Nancy Oriol and a team of health care professionals to create a unique return-on-investment calculator designed to measure the value of nontraditional, prevention-based health care services. Oriol, who is dean of students at the Harvard Medical School and an obstetric anesthesiologist at Beth Israel Deaconess Medical Center, is co-founder of the 17-year-old Family Van mobile health clinic in Boston. While mobile clinic staffers could talk anecdotally about how their programs have profoundly affected the lives of disenfranchised people, they had no hard data to prove how nontraditional programs could provide effective services for hard-to-reach populations and show how much money those services save.
“There’s a whole segment of society that doesn’t use mainstream health care — they go to the nontraditional portals. These are people who, one way or another, are medically disenfranchised,” said Oriol. “There are about 2,000 mobile clinics across the country, each seeing about 2,000 people. That’s 4 million people being served by nontraditional systems.”
To prove the effectiveness of a mobile health program such as the Family Van, Oriol and her team developed an algorithm to calculate the ROI of a typical mobile clinic based on published data that quantifies the value of traditional prevention practices and the value of preventing unnecessary emergency department visits.
“Real data from real emergency room visits showed that an unnecessary emergency room visit cost the system $900,” said Oriol. “There are real costs associated with unnecessary emergency department visits that are often avoided through mobile health clinics.”
Tom Hubbard, program director for the Cambridge-based New England Health Care Institute, agrees. “There are any number of calculators designed to show ROI for traditional employee health programs, but none for services such as this. There’s a real payback for taking these services directly to people who don’t have access to preventive mainstream services.” According to Hubbard, the data generated by Oriol’s calculator is providing “a hard, empirical case to help demonstrate value.”
So what does Oriol envision as the future for her nontraditional health care ROI calculator?
“We see expanding the lines of the algorithm so that it is applicable for many different settings. We need to make our algorithm more sophisticated so that it can be used effectively for other types of mobile programs,” she said.
For example, Oriol states that while a mobile clinic 500 miles from an emergency room won’t likely prevent an ER visit, its success will be measured by some other benchmark requiring another, different line in the algorithm.
By revising the ROI calculator algorithm so that it can be used in a wide variety of operational settings, Oriol sees it becoming an effective tool for establishing the value of this sector of the health care system, for fundraising, and for helping these nontraditional programs track and analyze the important work they do. “The beauty of this concept is that it is multidimensional.”
Jim Schakenbach is a freelance writer in Jefferson.







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