Farnoosh Haji-Sheikhi, Maren S Fragala, Lance A Bare, Charles M Rowland, Steven E Goldberg
{"title":"用可变健康指标预测未来医疗费用。","authors":"Farnoosh Haji-Sheikhi, Maren S Fragala, Lance A Bare, Charles M Rowland, Steven E Goldberg","doi":"10.2147/CEOR.S406525","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Discussion: </strong>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.</p>","PeriodicalId":47313,"journal":{"name":"ClinicoEconomics and Outcomes Research","volume":"15 ","pages":"525-534"},"PeriodicalIF":2.1000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/41/12/ceor-15-525.PMC10319160.pdf","citationCount":"0","resultStr":"{\"title\":\"Prediction of Future Medical Costs by Modifiable Measures of Health.\",\"authors\":\"Farnoosh Haji-Sheikhi, Maren S Fragala, Lance A Bare, Charles M Rowland, Steven E Goldberg\",\"doi\":\"10.2147/CEOR.S406525\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Discussion: </strong>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.</p>\",\"PeriodicalId\":47313,\"journal\":{\"name\":\"ClinicoEconomics and Outcomes Research\",\"volume\":\"15 \",\"pages\":\"525-534\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/41/12/ceor-15-525.PMC10319160.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ClinicoEconomics and Outcomes Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2147/CEOR.S406525\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ClinicoEconomics and Outcomes Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2147/CEOR.S406525","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
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 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.