{"id":143,"date":"2020-10-20T19:19:57","date_gmt":"2020-10-20T19:19:57","guid":{"rendered":"https:\/\/wellai.health\/blog\/?p=143"},"modified":"2022-01-03T00:45:57","modified_gmt":"2022-01-03T00:45:57","slug":"how-would-you-save-with-wellais-chronic-disease-management","status":"publish","type":"post","link":"https:\/\/wellai.health\/blog\/how-would-you-save-with-wellais-chronic-disease-management\/","title":{"rendered":"How would you save with WellAI\u2019s chronic disease management?"},"content":{"rendered":"

WellAI\u2019s Health Cost Savings Calculator \u2013 Health Risk Assessment (HRA), Wellness Program and Chronic Disease Management<\/strong><\/p>\n

This is part 4 of the series on the WellAI\u2019s health cost savings calculator for CEOs, CFOs and heads of HR.\u00a0 Today we will very briefly explain how cost savings from HRA ((Health Risk Assessment), wellness plans and chronic disease management programs for companies of various sizes are calculated.<\/p>\n

To implement an analysis of the effectiveness of a health promotion (wellness) program, employees need to be grouped into a treatment sample (e.g. \u201cat high risk\u201d) and a control sample (e.g. \u201cnot at high risk\u201d).\u00a0 This is usually done via an HRA survey.<\/p>\n

Once the HRA survey done, given all assumptions outlined in part 2 of these blog series, we start with the most up-to-date and the most comprehensive mega-analysis study currently available in the literature \u2013 namely, a June 2020 study by Goetzel et al in the American Journal of Health Promotion that reached out to 439,689 employees from 11 companies of various sizes.\u00a0 Supplementary exhibit A1 of the paper provides us with a multivariate regression model of an annual total health care spending.\u00a0 As the paper suggests, we only use statistically significant independent variables (whose p-value < 0.05) to evaluate the share of health costs.\u00a0 These most significant variables are availability of high health risk, employee age demographics, gender distribution, percent of salaried employees, and percent of employees using a High Deductible Health Plan (HDHP).\u00a0 When we apply this model, we find that all these variables contribute roughly 22% to total health costs.\u00a0 By applying the assumed program participation rate of 30.8%, we find that potential health cost savings associated with a wellness program that is focused on chronic disease management is 6.9% (= 22% x 30.8%).<\/p>\n

We can do similar exercise for a large employer (employee size of roughly more than 10,000) and for a small employer (employee size of roughly less than 2,000).<\/p>\n

Characteristics of a large employer we obtain from a May 2011 study by Kowlessar et al in the Journal of Occupational and Environmental Medicine.\u00a0 Once we input those characteristics into a multivariate regression model from the June 2020 study described above, we find that potential health cost savings associated with a wellness program with a focus on chronic disease management for a large employer is 9.1%.<\/p>\n

Similarly, characteristics of a small employer we obtain from a May 2014 study by Goetzel et al in the Journal of Occupational and Environmental Medicine.\u00a0 Once we input those characteristics into a multivariate regression model from the June 2020 study described above, we find that potential health cost savings associated with a wellness program with a focus on chronic disease management for a small employer is 7.2%.<\/p>\n

The WellAI app is now available for free on your smartphone.\u00a0 Please use the following links to schedule a 1-on-1 demo<\/strong>:<\/p>\n