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Calculating the return on investment of mobile healthcare

Nancy E Oriol*, Paul J Cote, Anthony P Vavasis, Jennifer Bennet, Darien DeLorenzo, Philip Blanc and Isaac Kohane

BMC Medicine 2009, 7:27  doi:10.1186/1741-7015-7-27

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Revised ED avoidance estimate for use in ROI algorithm

Nancy Oriol   (2013-03-19 10:27)  Harvard Medical School

Upon revisiting our source for estimating emergency department visits avoided (Peter Cunningham's July 2006 Health Affairs article "What Accounts for Differences in Use of Hospital Emergency Departments Across US Communities?") we noted that we had incorrectly interpreted its Exhibit 4 as additive data as opposed to discreet categorical data. The national mid-point between High-ED-use and Low-ED-use communities for uninsured and medicaid populations as a proportion of all outpatient visits is 22%. Therefore the value for ED visits avoided in the ROI algorithm should be revised to 22% from 44% with a concomindent change in ROI from 36:1 to 33:1. We have revised the algorithm on our publicly available materials.

Competing interests



Misquoted adherence estimate

Nancy Oriol   (2011-06-08 17:14)  Harvard Medical School, The Family Van email

On page 8, the authors incorrectly state that: "NCPP estimations assume a 30% non-compliance with treatment". In fact, as stated in their methods (Priorities among effective clinical preventive services: results of a systematic review and analysis. Am J Prev Med 2006, 31(1):52-61) , NCPP specifically addresses patient adherence in its calculation of effectiveness of each intervention as follows: "Effectiveness = (percent who would accept the preventive service once offered) X (sensitivity of screening or assessment) X (adherence with follow-up treatment or advice to change behavior) X (effectiveness of prevention, treatment, or behavior change)". For example, in calculating the effectiveness of brief counseling services such as smoking cessation, NCPP projected patient adherence to be less than 1%

Competing interests



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