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Quality of Life Research

Gepubliceerd in:

23-06-2022

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

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

Gepubliceerd in: Quality of Life Research | Uitgave 11/2022

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.

vorige artikel Changes in older people’s quality of life in the COVID-19 era: a population-based study in Finland

volgende artikel Cancer-related fatigue mediates the relationships between physical fitness and attendance and quality of life after participation in a clinical exercise program for survivors of cancer

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%.”.

Secretary’s Advisory Committee for Healthy People 2030. (2018). Issue briefs to inform development and implementation of Healthy People 2030. https://www.healthypeople.gov/sites/default/files/HP2030_Committee-Combined-Issue%20Briefs_2019-508c_0.pdf

World Health Organization. (2021). Constitution. https://www.who.int/about/who-we-are/constitution

Evans, R. G., & Stoddart, G. L. (1990). Producing health, consuming health care. Social Science & Medicine, 31(12), 1347–1363. https://doi.org/10.1016/0277-9536(90)90074-3CrossRef

National Research Council. (2013). Subjective well-being: Measuring happiness, suffering, and other dimensions of experience. The National Academies Press. https://doi.org/10.17226/18548

Boscardin, C. K., Gonzales, R., Bradley, K. L., & Raven, M. C. (2015). Predicting cost of care using self-reported health status data. BMC Health Services Research, 15(406), 1–8. https://doi.org/10.1186/s12913-015-1063-1CrossRef

Perrin, N. A., Stiefel, M., Mosen, D. M., Bauck, A., Shuster, E., & Dirks, E. M. (2011). Self-reported health and functional status information improves prediction of inpatient admissions and costs. The American Journal of Managed Care, 17(12), e472–e478.PubMed

DeSalvo, K. B., Fan, V. S., McDonell, M. B., & Fihn, S. D. (2005). Predicting mortality and healthcare utilization with a single question. Health Services Research, 40(4), 1234–1246. https://doi.org/10.1111/j.1475-6773.2005.00404.xCrossRefPubMedPubMedCentral

Cotiviti. (2021). Medical intelligence: Gain insights into every facet of healthcare utilization. https://www.cotiviti.com/solutions/quality-and-performance/medical-intelligence

Harrison, P. L., Pope, J. E., Coberley, C. R., & Rula, E. Y. (2012). Evaluation of the relationship between individual well-being and future health care utilization and cost. Population Health Management, 15(6), 325–330. https://doi.org/10.1089/pop.2011.0089CrossRefPubMed

10.

Riley, C., Roy, B., Herrin, J., Spatz, E. S., Arora, A., Kell, K. P., Rula, E. Y., & Krumholz, H. M. (2018). Association of the overall well-being of a population with health care spending for people 65 years of age or older. Journal of the American Medical Association Network Open, 1(5), e182136. https://doi.org/10.1001/jamanetworkopen.2018.2136CrossRef

11.

Sidney, J. A., Jones, A., Coberley, C., Pope, J. E., & Wells, A. (2017). The well-being valuation model: a method for monetizing the nonmarket good of individual well-being. Health Services and Outcomes Research Methodology, 17, 84–100.CrossRef

12.

Kim, E. S., Park, N., Sun, J. K., Smith, J., & Peterson, C. (2014). Life satisfaction and frequency of doctor visits. Psychosomatic Medicine, 76(1), 86–93. https://doi.org/10.1097/PSY.0000000000000024CrossRefPubMed

13.

Blumenthal, K. J., Chang, Y., Ferris, T. G., Spirt, J. C., Vogeli, C., Wagle, N., & Metlay, J. P. (2017). Using a self-reported global health measure to identify patients at high risk for future healthcare utilization. Journal of General Internal Medicine, 32, 877–882. https://doi.org/10.1007/s11606-017-4041-yCrossRefPubMedPubMedCentral

14.

Sears, L. E., Shi, Y., Coberley, C. R., & Pope, J. E. (2013). Overall well-being as a predictor of health care, productivity, and retention outcomes in a large employer. Population Health Management, 16(6), 397–405. https://doi.org/10.1089/pop.2012.0114CrossRefPubMedPubMedCentral

15.

Stiefel, M. C., Gordon, N. P., Wilson-Anumudu, F. J., & Arsen, E. L. (2019). Sociodemographic determinants of health and well-being among adults residing in the combined Kaiser Permanente regions. The Permanente Journal, 23, 18–091. https://doi.org/10.7812/TPP/18-091CrossRefPubMedCentral

16.

Stiefel, M. C., McNeely, E., Riley, C. L., Roy, B., Straszewski, T., & VanderWeele, T. J. (2020). Well-Being Assessment (Adult - 24 items). 100 Million Healthier Lives, convened by the Institute for Healthcare Improvement. http://www.ihi.org/100MLives

17.

Cantril, H. (1965). The pattern of human concerns. Rutgers University Press.

18.

Gallup, Inc. (2021). Understanding how Gallup uses the Cantril Scale. https://news.gallup.com/poll/122453/understanding-gallup-uses-cantril-scale.aspx

19.

Porter, N. M., & Garman, E. T. (1992). Money as part of a measure of financial well-being. American Behavioral Scientist, 35(6), 820–826. https://doi.org/10.1177/0002764292035006016CrossRef

20.

Centers for Disease Control and Prevention. (2016). Behavioral Risk Factor Surveillance System 2017 Questionnaire, 2017. https://www.cdc.gov/brfss/questionnaires/pdf-ques/2017_BRFSS_Pub_Ques_508_tagged.pdf

21.

Diener, E., Wirtz, D., Tov, W., Kim-Prieto, C., Choi, D., Oishi, S., & Biswas-Diener, R. (2010). New well-being measures: Short scales to assess flourishing and positive and negative feelings. Social Indicators Research, 97(2), 143–156. https://doi.org/10.1007/s11205-009-9493-yCrossRef

22.

Centers for Disease Control and Prevention. (2018). CDC HRQOL–14 ‘Healthy Days Measure,’ 2018. https://www.cdc.gov/hrqol/hrqol14_measure.htm#1

23.

Steptoe, A., Deaton, A., & Stone, A. A. (2015). Subjective wellbeing, health, and ageing. Lancet, 385(9968), 640–648. https://doi.org/10.1016/S0140-6736(13)61489-0CrossRefPubMed

24.

Kim, E. S., Hagan, K. A., Grodstein, F., DeMeo, D. L., De Vivo, I., & Kubzansky, L. D. (2017). Optimism and cause-specific mortality: A prospective cohort study. American Journal of Epidemiology, 185(1), 21–29. https://doi.org/10.1093/aje/kww182CrossRefPubMed

25.

SAS Institute Inc. (2021). SAS Studio. https://www.sas.com/en_hk/software/studio.html

26.

Bednar, W. (2017). Building actuarial cost models from health care claims data for strategic decision-making. Health Watch. (83)

27.

Winkelman R, Mehmud S. (2007) A comparative analysis of claims-based tools for health risk assessment. Society of Actuaries. 1–70.

28.

Ryan, R. M., & Deci, E. L. (2001). On happiness and human potentials: A review of research on hedonic and eudaimonic well-being. In S. Fiske (Ed), Annual Review of Psychology (Vol 52, pp. 141–166). Annual Reviews, Inc. https://doi.org/10.1146/annurev.psych.52.1.141

29.

VanderWeele, T. J., Trudel-Fitzgerald, C., Allin, P., Farrelly, C., Fletcher, G., Frederick, D. E., Hall, J., Helliwell, J. F., Kim, E. S., Lauinger, W. A., Lee, M. T., Lyubomirsky, S., Margolis, S., McNeely, E., Messer, N., Tay, L., Viswanath, V., Węziak-Białowolska, D., & Kubzansky, L. D. (2020). Current recommendations on the selection of measures for well-being. Preventive Medicine, 133, 106004.CrossRef

30.

Boehm, J. K., & Kubzansky, L. D. (2012). The heart’s content: The association between positive psychological well-being and cardiovascular health. Psychological Bulletin, 138(4), 655–691. https://doi.org/10.1037/a0027448CrossRefPubMed

Titel: Testing the added value of self-reported health and well-being in understanding healthcare utilization and costs
Auteurs: Tasha Straszewski
Colleen A. Ross
Carley Riley
Brita Roy
Matthew C. Stiefel
Publicatiedatum: 23-06-2022
Uitgeverij: Springer International Publishing
Gepubliceerd in: Quality of Life Research / Uitgave 11/2022
Print ISSN: 0962-9343
Elektronisch 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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