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Open Access Highly Accessed Research article

The ACTIVE cognitive training trial and predicted medical expenditures

Fredric D Wolinsky12*, Henry W Mahncke3, Mark Kosinski4, Frederick W Unverzagt5, David M Smith5, Richard N Jones6, Anne Stoddard7 and Sharon L Tennstedt7

Author Affiliations

1 Health Services Research, Iowa City Veterans Affairs Medical Center, Iowa City, Iowa, USA

2 College of Public Health, University of Iowa, 200 Hawkins Drive, E205 General Hospital, Iowa City, Iowa 52242, USA

3 Posit Science Corporation, San Francisco, CA, USA

4 QualityMetric, Inc., Providence, RI, USA

5 School of Medicine, Indiana University, Indianapolis, IN, USA

6 Institute for Aging Research, Hebrew Senior-Life, Boston, MA, USA

7 Aging Studies, New England Research Institutes, Watertown, MA, USA

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BMC Health Services Research 2009, 9:109  doi:10.1186/1472-6963-9-109

Published: 29 June 2009

Abstract

Background

Health care expenditures for older adults are disproportionately high and increasing at both the individual and population levels. We evaluated the effects of the three cognitive training interventions (memory, reasoning, or speed of processing) in the ACTIVE study on changes in predicted medical care expenditures.

Methods

ACTIVE was a multisite randomized controlled trial of older adults (≥ 65). Five-year follow-up data were available for 1,804 of the 2,802 participants. Propensity score weighting was used to adjust for potential attrition bias. Changes in predicted annualmedical expenditures were calculated at the first and fifth annual follow-up assessments using a new method for translating functional status scores. Multiple linear regression methods were used in this cost-offset analysis.

Results

At one and five years post-training, annual predicted expenditures declinedby $223 (p = .024) and $128 (p = .309), respectively, in the speed of processing treatment group, but there were no statistically significant changes in the memory or reasoning treatment groups compared to the no-contact control group at either period. Statistical adjustment for age, race, education, MMSE scores, ADL and IADL performance scores, EPT scores, chronic condition counts, and the SF-36 PCS and MCS scores at baseline did not alter the one-year ($244; p = .012) or five-year ($143; p = .250) expenditure declines in the speed of processing treatment group.

Conclusion

The speed of processing intervention significantly reduced subsequent annual predicted medical care expenditures at the one-year post-baseline comparison, but annual savings were no longer statistically significant at the five-year post-baseline comparison.