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Prediction of Future Medical Costs by Modifiable Measures of Health

INTRODUCTION: Strategies to mitigate rising health-care costs are a priority for patients, employers, and health insurers. Yet gaps currently exist in whether health risk assessment can forecast medical claims costs. This study examined the ability of a health quotient (HQ) based on modifiable risk...

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Autores principales: Haji-Sheikhi, Farnoosh, Fragala, Maren S, Bare, Lance A, Rowland, Charles M, Goldberg, Steven E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10319160/
https://www.ncbi.nlm.nih.gov/pubmed/37408662
http://dx.doi.org/10.2147/CEOR.S406525
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author Haji-Sheikhi, Farnoosh
Fragala, Maren S
Bare, Lance A
Rowland, Charles M
Goldberg, Steven E
author_facet Haji-Sheikhi, Farnoosh
Fragala, Maren S
Bare, Lance A
Rowland, Charles M
Goldberg, Steven E
author_sort Haji-Sheikhi, Farnoosh
collection PubMed
description INTRODUCTION: Strategies to mitigate rising health-care costs are a priority for patients, employers, and health insurers. Yet gaps currently exist in whether health risk assessment can forecast medical claims costs. This study examined the ability of a health quotient (HQ) based on modifiable risk factors, age, sex, and chronic conditions to predict future medical claims spending. METHODS: The study included 18,695 employees and adult dependents who participated in health assessments and were enrolled in an employer-sponsored health plan. Linear mixed effect models stratified by chronic conditions and adjusted for age and sex were utilized to evaluate the relationship between the health quotient (score of 0–100) and future medical claims spending. RESULTS: Lower baseline health quotient was associated with higher medical claims cost over 2 years of follow up. For participants with chronic condition(s), costs were $3628 higher for those with a low health quotient (<73; N = 2673) compared to those with high health quotient (>85; N = 1045), after adjustment for age and sex (P value = 0.004). Each one-unit increase in health quotient was associated with a decrease of $154 (95% CI: 87.4, 220.3) in average yearly medical claims costs during follow up. DISCUSSION: This study used a large employee population with 2 years of follow-up data, which provides insights that are applicable to other large employers. Results of this analysis contribute to our ability to predict health-care costs using modifiable aspects of health, objective laboratory testing and chronic condition status.
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spelling pubmed-103191602023-07-05 Prediction of Future Medical Costs by Modifiable Measures of Health Haji-Sheikhi, Farnoosh Fragala, Maren S Bare, Lance A Rowland, Charles M Goldberg, Steven E Clinicoecon Outcomes Res Original Research INTRODUCTION: Strategies to mitigate rising health-care costs are a priority for patients, employers, and health insurers. Yet gaps currently exist in whether health risk assessment can forecast medical claims costs. This study examined the ability of a health quotient (HQ) based on modifiable risk factors, age, sex, and chronic conditions to predict future medical claims spending. METHODS: The study included 18,695 employees and adult dependents who participated in health assessments and were enrolled in an employer-sponsored health plan. Linear mixed effect models stratified by chronic conditions and adjusted for age and sex were utilized to evaluate the relationship between the health quotient (score of 0–100) and future medical claims spending. RESULTS: Lower baseline health quotient was associated with higher medical claims cost over 2 years of follow up. For participants with chronic condition(s), costs were $3628 higher for those with a low health quotient (<73; N = 2673) compared to those with high health quotient (>85; N = 1045), after adjustment for age and sex (P value = 0.004). Each one-unit increase in health quotient was associated with a decrease of $154 (95% CI: 87.4, 220.3) in average yearly medical claims costs during follow up. DISCUSSION: This study used a large employee population with 2 years of follow-up data, which provides insights that are applicable to other large employers. Results of this analysis contribute to our ability to predict health-care costs using modifiable aspects of health, objective laboratory testing and chronic condition status. Dove 2023-06-30 /pmc/articles/PMC10319160/ /pubmed/37408662 http://dx.doi.org/10.2147/CEOR.S406525 Text en © 2023 Haji-Sheikhi et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Haji-Sheikhi, Farnoosh
Fragala, Maren S
Bare, Lance A
Rowland, Charles M
Goldberg, Steven E
Prediction of Future Medical Costs by Modifiable Measures of Health
title Prediction of Future Medical Costs by Modifiable Measures of Health
title_full Prediction of Future Medical Costs by Modifiable Measures of Health
title_fullStr Prediction of Future Medical Costs by Modifiable Measures of Health
title_full_unstemmed Prediction of Future Medical Costs by Modifiable Measures of Health
title_short Prediction of Future Medical Costs by Modifiable Measures of Health
title_sort prediction of future medical costs by modifiable measures of health
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10319160/
https://www.ncbi.nlm.nih.gov/pubmed/37408662
http://dx.doi.org/10.2147/CEOR.S406525
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