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Health Trajectories of Older Americans and Medical Expenses: Evidence from the Health and Retirement Study Data Over the 18 Year Period

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Abstract

This study investigates the long-term relationship between individuals’ health state changes over time and burdens due to out-of-pocket medical expenses (OOP) in later years. We kept track of 5540 individuals’ health trajectories and their accumulated OOP using the HRS data from 1992 to 2010. American adults between 50 and 70 years old spend on average $27,000 on OOP, and have five common health trajectory patterns (Multi-Morbidity, Co-Morbidity, Mild Disease, Late Event, and No Disease). However, their OOPs differed substantially depending on the pattern of health trajectory. The most costly pattern of Multi-Morbidity needed $18,823 more than the least costly No Disease pattern. Older adults with the most costly pattern spent most of OOP on either prescription drugs or doctor/dental visits. Additionally, we found that the OOP burden of prescription medications was substantially relieved by the Medicare Part D implementation. These findings have several important implications for individuals, financial educators, and policy makers.

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Notes

  1. Sequence analysis has been developed and applied in many different social science fields such as psychology, economics, and political science to identify the typical patterns of life course trajectories (Aassve et al. 2007; Anyadike-Danes and McVicar 2010; Blair-Loy 1999; Halpin and Chan 1998; Martin et al. 2008; McVicar and Anyadike-Danes 2002; Pollock 2007; Pollock et al. 2002; Salmela-Aro et al. 2011).

  2. Again, we note the accumulated OOP for the four categories is for the period from 1996 to 2010.

  3. Medicare Part D, which began on January 1, 2006, gives the Medicare-eligible population of seniors’ access to a subsidized market for non-mandatory standardized prescription drug coverage through contracts sponsored by private insurance firms (Heiss et al. 2013).

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  1. University of Kentucky, 315 Funkhouser Building, Lexington, KY, 40506, USA

    Serah Shin & Hyungsoo Kim

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  1. Serah Shin
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Correspondence to Serah Shin.

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Appendix

Appendix

See Tables 8, 9, 10, 11 and 12.

Table 8 Logistic regression for calculating inverse probability weights
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Table 9 Comparison of characteristics of sample and descriptive statistics
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Table 10 Sensitivity tests to check potential biases: sensitivity tests for total OOP
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Table 11 Sensitivity tests to check potential biases: regression results applying both inverse probability weight and Ln transformation
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Table 12 Simulations results ($) based on Tables 5, 6 and 7
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Shin, S., Kim, H. Health Trajectories of Older Americans and Medical Expenses: Evidence from the Health and Retirement Study Data Over the 18 Year Period. J Fam Econ Iss 39, 19–33 (2018). https://doi.org/10.1007/s10834-017-9542-7

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