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Quality of Life Research

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23-06-2022

Testing the added value of self-reported health and well-being in understanding healthcare utilization and costs

Authors: Tasha Straszewski, Colleen A. Ross, Carley Riley, Brita Roy, Matthew C. Stiefel

Published in: Quality of Life Research | Issue 11/2022

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Abstract

Purpose

We investigated the relationship between measures of self-reported health and well-being and concurrent and prospective healthcare utilization and costs to assess the added value of these self-reported measures in understanding utilization and cost.

Methods

Kaiser Permanente members (N = 6752) completed a 9-item survey measuring life evaluation, financial situation, social support, meaning and purpose, physical health, and mental health. Responses were linked to medical record information during the period 12 months before and after the survey.

Results

Correlations between health and well-being measures and healthcare utilization and cost variables were generally weak, with stronger correlations for future life evaluation and selected health measures (ρ = .20–.33, ps < .001). Better overall life evaluation had a significant but weak association with lower total cost and hospital days in the following year after controlling for age, sex, and race/ethnicity (p < .001). Full multivariate models, adjusting for age, sex, race/ethnicity, prior utilization, and relative risk models, showed weak associations between health and well-being measures and following year total healthcare cost and utilization, though the associations were relatively stronger for the health variables than the well-being variables.

Conclusion

Overall, the health and well-being variables added little to no predictive utility for future utilization and cost beyond prior utilization and cost and the inclusion of predictive models based on clinical information.

Perceptions of well-being may be associated with factors beyond healthcare utilization. When information about prior use is unavailable, self-reported health items have some predictive utility.

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After we merged the HWBS responses with the EMR data (n = 7935), we excluded 1183 members who did not have at least 12 months of KP enrollment before and after the survey, resulting in our sample size of 6752. We decided not to use listwise deletion for missing data to keep the data as complete as possible. As such, the sample sizes reported for each of the analyses may have some slight variations. The average percentage of missing data across the variables was .42%, with a range of 0.00 to 4.10%.”.

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Title: Testing the added value of self-reported health and well-being in understanding healthcare utilization and costs
Authors: Tasha Straszewski
Colleen A. Ross
Carley Riley
Brita Roy
Matthew C. Stiefel
Publication date: 23-06-2022
Publisher: Springer International Publishing
Published in: Quality of Life Research / Issue 11/2022
Print ISSN: 0962-9343
Electronic ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-022-03168-1

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Abstract

Purpose

Methods

Results

Conclusion

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