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The American Journal of Managed Care February 2019
The American Journal of Managed Care February 2019
CLINICAL
Haley Bush, MSPH; James Paik, PhD; Pegah Golabi, MD; Leyla de Avila, BA; Carey Escheik, BS; and Zobair M. Younossi, MD, MPH
COMMENTARY
Jackson Williams, JD
EDITORIAL
A. Mark Fendrick, MD; and Darrell George, BA
From The Editorial Board
Sachin H. Jain, MD, MBA
POLICY
Nirosha Mahendraratnam, PhD; Corinna Sorenson, PhD, MHSA, MPH; Elizabeth Richardson, MSc; Gregory W. Daniel, PhD, MPH, RPh; Lisabeth Buelt, MPH; Kimberly Westrich, MA; Jingyuan Qian, MPP; Hilary Campbell, PharmD, JD; Mark McClellan, MD, PhD; and Robert W. Dubois, MD, PhD
Seth A. Seabury, PhD; J. Samantha Dougherty, PhD; and Jeff Sullivan, MS
TRENDS FROM THE FIELD
Anna D. Sinaiko, PhD, MPP; Shehnaz Alidina, SD, MPH; and Ateev Mehrotra, MD, MPH
WEB EXCLUSIVE
Rebecca A. Gourevitch, MS; Ateev Mehrotra, MD, MPH; Grace Galvin, MPH; Avery C. Plough, BA; and Neel T. Shah, MD, MPP
Cheryl L. Damberg, PhD; Marissa Silverman, MSPH; Lane Burgette, PhD; Mary E. Vaiana, PhD; and M. Susan Ridgely, JD
Currently Reading
Validating a Method to Assess Disease Burden From Insurance Claims
Thomas E. Kottke, MD, MSPH; Jason M. Gallagher, MBA; Marcia Lowry, MS; Pawan D. Patel, MD; Sachin Rauri, MS; Juliana O. Tillema, MPA; Jeanette Y. Ziegenfuss, PhD; Nicolaas P. Pronk, PhD, MA; and Susan M. Knudson, MA
Felix Sebastian Wicke, Dr Med; Anastasiya Glushan, BSc; Ingrid Schubert, Dr Rer Soc; Ingrid Köster, Dipl-Stat; Robert Lübeck, Dr Med; Marc Hammer, MPH; Martin Beyer, MSocSc; and Kateryna Karimova, MSc
Jesús Antonio Álvarez, PhD, MD; Rubén Francisco Flores, PhD; Jaime Álvarez Grau, PhD; and Jesús Matarranz, PhD
Validating a Method to Assess Disease Burden From Insurance Claims
Thomas E. Kottke, MD, MSPH; Jason M. Gallagher, MBA; Marcia Lowry, MS; Pawan D. Patel, MD; Sachin Rauri, MS; Juliana O. Tillema, MPA; Jeanette Y. Ziegenfuss, PhD; Nicolaas P. Pronk, PhD, MA; and Susan M. Knudson, MA
When we weighted health insurance claims with a disease burden score, we were able to generate valid estimates of disability-adjusted life-years.
ABSTRACT
Objectives: To validate a method that estimates disease burden as disability-adjusted life-years (DALYs) from insurance claims and death records for the purpose of identifying the conditions that place the greatest burden of disease on an insured population.
Study Design: Comparison of the DALYs generated from death records and insurance claims with functional status and health status reported by individuals who were insured with one of HealthPartners’ commercial products and completed a health assessment in 2011, 2012, or 2013.
Methods: We calculated values of Spearman’s ρ, the rank-order coefficient of correlation, for the correlation of DALYs with self-reported function and self-reported health. We did the same for the number of medical conditions per member and the cost of claims per member.
Results: The Spearman’s ρ values for the correlation of DALYs with function were –0.241, –0.238, and –0.229 in 2011, 2012, and 2013, respectively (all P <.0001). The respective Spearman’s ρ values for the correlation of DALYs with health were –0.197, –0.189, and –0.192 (all P <.0001). These Spearman’s ρ values were similar in magnitude to those for the correlation of the number of medical conditions per member with function (–0.212, –0.213, and –0.205) and health (–0.199, –0.196, and –0.198) over the 3 years. The Spearman’s ρ values for the correlation of DALYs with function and health were greater than or equal to those for the correlation of cost of claims per member with function (–0.144, –0.193, and –0.186) and greater than those for the cost of claims per member with health (–0.126, –0.150, and –0.151).
Conclusions: Health plans can use DALYs calculated from their own health insurance claims and death records as a valid and inexpensive method to identify the conditions that place the greatest burden of poor function and ill health on their insured populations.
Am J Manag Care. 2019;25(2):e39-e44Takeaway Points
Based on the correlation of disability-adjusted life-years (DALYs) with self-reported function and self-reported health, we conclude that our method of estimating DALYs by combining mortality data with insurance claims weighted by a condition burden score is valid.
Insurance claims tell the organization which conditions its members are experiencing, but they also present a problem: Insurance claims are agnostic about the burden that the associated conditions place on an individual’s health and function. It is therefore necessary to assign a weight to each claim that reflects the disease burden. We used the Global Burden of Disease (GBD) as our source of condition weights.9
To document whether and the extent to which our method of calculating DALYs is a valid measure of disease burden, as well as the extent to which it provides information that is not available with measures that are more straightforward, we asked the following questions: (1) Are the correlations between DALYs and function and health of the same magnitude as an accepted measure of risk: the number of disease conditions associated with an individual?10,11 (2) Do the correlations between DALYs and function and health provide information that differs from that of 2 simpler indicators: the number of members who have a particular condition and the healthcare costs associated with a condition? (3) Is simply calculating the function losses or the health losses associated with a disease or condition as useful as our method of calculating DALYs?
To the extent that the answer to the first question is yes, we consider our method of calculating DALYs to be valid. To the extent that the answer to the second question is yes, we conclude that our method adds value, and if the answer to the third question is no, we consider that calculating DALYs from insurance claims is useful.
METHODS
The HealthPartners institutional review board (IRB) agreed that this analysis is quality improvement, not research, and is thus not subject to IRB review.
Data Source for Member-Reported Function and Health
Self-report is considered a valid way to measure both the average health and the average function of a population.12,13 It is used as such in both Europe14 and the United States.15 Each year, members insured through HealthPartners’ commercial (non–government-sponsored) programs are offered the opportunity to complete a health assessment. One question on the assessment relates to the respondent’s difficulty in doing daily work because of physical function, 1 relates to the extent to which emotional problems interfere with the respondent’s ability to do their daily work, and 1 asks the respondent to describe their health. For each question, the respondent has 5 choices, ranging from “none” to “I could not do my daily work” for physical function, “not at all” to “extremely” for emotional problems, and “poor” to “excellent” for health. We used these 3 questions in the analyses we report here. We excluded data from any member whose name appeared on one of our health plan, research, or related do-not-contact lists. Overall, this applied to 0.2% of our membership.
Objectives: To validate a method that estimates disease burden as disability-adjusted life-years (DALYs) from insurance claims and death records for the purpose of identifying the conditions that place the greatest burden of disease on an insured population.
Study Design: Comparison of the DALYs generated from death records and insurance claims with functional status and health status reported by individuals who were insured with one of HealthPartners’ commercial products and completed a health assessment in 2011, 2012, or 2013.
Methods: We calculated values of Spearman’s ρ, the rank-order coefficient of correlation, for the correlation of DALYs with self-reported function and self-reported health. We did the same for the number of medical conditions per member and the cost of claims per member.
Results: The Spearman’s ρ values for the correlation of DALYs with function were –0.241, –0.238, and –0.229 in 2011, 2012, and 2013, respectively (all P <.0001). The respective Spearman’s ρ values for the correlation of DALYs with health were –0.197, –0.189, and –0.192 (all P <.0001). These Spearman’s ρ values were similar in magnitude to those for the correlation of the number of medical conditions per member with function (–0.212, –0.213, and –0.205) and health (–0.199, –0.196, and –0.198) over the 3 years. The Spearman’s ρ values for the correlation of DALYs with function and health were greater than or equal to those for the correlation of cost of claims per member with function (–0.144, –0.193, and –0.186) and greater than those for the cost of claims per member with health (–0.126, –0.150, and –0.151).
Conclusions: Health plans can use DALYs calculated from their own health insurance claims and death records as a valid and inexpensive method to identify the conditions that place the greatest burden of poor function and ill health on their insured populations.
Am J Manag Care. 2019;25(2):e39-e44Takeaway Points
Based on the correlation of disability-adjusted life-years (DALYs) with self-reported function and self-reported health, we conclude that our method of estimating DALYs by combining mortality data with insurance claims weighted by a condition burden score is valid.
- Important differences are revealed when population burden from a condition is defined by DALYs rather than by the number of individuals with the condition or the cost of the condition to the health plan.
- The magnitude of these correlations with self-reported function and health is greater than that of cost of claims.
- Unlike assessing disease burden by counting the number of conditions per individual, calculating the DALYs attributable to conditions identifies opportunities to improve population health by addressing particularly burdensome conditions.
Insurance claims tell the organization which conditions its members are experiencing, but they also present a problem: Insurance claims are agnostic about the burden that the associated conditions place on an individual’s health and function. It is therefore necessary to assign a weight to each claim that reflects the disease burden. We used the Global Burden of Disease (GBD) as our source of condition weights.9
To document whether and the extent to which our method of calculating DALYs is a valid measure of disease burden, as well as the extent to which it provides information that is not available with measures that are more straightforward, we asked the following questions: (1) Are the correlations between DALYs and function and health of the same magnitude as an accepted measure of risk: the number of disease conditions associated with an individual?10,11 (2) Do the correlations between DALYs and function and health provide information that differs from that of 2 simpler indicators: the number of members who have a particular condition and the healthcare costs associated with a condition? (3) Is simply calculating the function losses or the health losses associated with a disease or condition as useful as our method of calculating DALYs?
To the extent that the answer to the first question is yes, we consider our method of calculating DALYs to be valid. To the extent that the answer to the second question is yes, we conclude that our method adds value, and if the answer to the third question is no, we consider that calculating DALYs from insurance claims is useful.
METHODS
The HealthPartners institutional review board (IRB) agreed that this analysis is quality improvement, not research, and is thus not subject to IRB review.
Data Source for Member-Reported Function and Health
Self-report is considered a valid way to measure both the average health and the average function of a population.12,13 It is used as such in both Europe14 and the United States.15 Each year, members insured through HealthPartners’ commercial (non–government-sponsored) programs are offered the opportunity to complete a health assessment. One question on the assessment relates to the respondent’s difficulty in doing daily work because of physical function, 1 relates to the extent to which emotional problems interfere with the respondent’s ability to do their daily work, and 1 asks the respondent to describe their health. For each question, the respondent has 5 choices, ranging from “none” to “I could not do my daily work” for physical function, “not at all” to “extremely” for emotional problems, and “poor” to “excellent” for health. We used these 3 questions in the analyses we report here. We excluded data from any member whose name appeared on one of our health plan, research, or related do-not-contact lists. Overall, this applied to 0.2% of our membership.
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