Abstract: Out-of-Pocket Financial Burden for Middle-Aged Adults: Impact of Distinct Patterns of Multi-Morbidity and Health Insurance (Society for Social Work and Research 22nd Annual Conference - Achieving Equal Opportunity, Equity, and Justice)

226P Out-of-Pocket Financial Burden for Middle-Aged Adults: Impact of Distinct Patterns of Multi-Morbidity and Health Insurance

Schedule:
Friday, January 12, 2018
Marquis BR Salon 6 (ML 2) (Marriott Marquis Washington DC)
* noted as presenting author
Eunsun Kwon, PhD, Research Associate, Seoul National University, Seoul, Korea, Republic of (South)
Bo Rin Kim, PhD, Assistant Professor, University of New Hampshire, Durham, Durham, NH
Sojung Park, PhD, Assistant Professor, Washington University in Saint Louis, Saint Louis, MO
Na Youn Lee, PhD, Assistant Professor, University of Mississippi, University, MS
Songhee Kim, MSW, MSW Student, Washington University in Saint Louis, Saint Louis, MO
Background/Purpose: Multimorbid and comorbid chronic diseases are increasingly placing a financial burden on individuals and health care services. Despite the prevalence of comorbid conditions among middle-aged adults, relatively few studies have addressed the need to understand patterns of disease combinations/clusters and associated financial burden on medical out-of-pocket costs. The patterns of multi-morbidity may differ by income levels as people with multiple chronic conditions tend to be from lower income groups. In addition, the association between financial burden and multi-morbidity patterns may vary by type of health insurance. This study aimed to identify the pattern of co-occurrence of common chronic diseases in middle-aged Americans, and also to explore whether and how the patterns identified are associated with out-of-pocket financial burden, taking into account their income and health insurance. 

Methods: Data came from seven waves of the Health and Retirement Study (HRS, 2002-2014). We restricted our sample to middle-aged adults between age 51 and 64, and separated them into two income groups (low income adults living below 200% of the federal poverty (Observations=1,926; N=806); moderate to high income adults above 200% of FPL (Observations=12,008; N=4,266). This study focused on the most common serious chronic diseases: high blood pressure (HBP), Diabetes, cancer, lung disease, heart disease, stroke, psychiatric problems, and arthritis. A latent class analysis was used to identify different combinations of chronic diseases. Then, a discrete-time survival analysis of the timing of first experience of financial burden that occurred between 2004 and 2014.  

Results:For low income adults, latent class analysis revealed a three-group comorbidity structure: (1) Multi-morbid with Diabetes (HBP, Diabetes, Heart disease, Psychiatric problem, and Arthritis); (2) Multi-morbid with Lung disease (HBP + Lung disease, Heart disease, Psychiatric problem, and Arthritis); and (3) Relatively healthy (HBP and Arthritis). For moderate to high income adults, the following three clusters were found: (1) Multi-morbid (HBP, Heart disease, psychiatric problem, and Arthritis); (2) Diabetes (HBP, Diabetes, and Arthritis); (3) Relatively healthy (Arthritis only). Results from the discrete-time survival analyses showed that low income adults in the Multi-morbid with Diabetes group had a higher risk of experiencing financial burden compared with relatively healthy group. When health insurance taken account into, the group who had only private insurance tended to experience burden. For moderate to high income adults, compared with relatively healthy group, those in Multi-morbid group with only private insurance faced a higher odd of having burden.      

Conclusions and Implications:The results confirmed that HBP and arthritis, the two leading chronic diseases, are dominant in major comorbid pairs and multimorbid combinations among middle-aged Americans. Regardless of income level, people with private insurance were not in a secure position if they were with multiple chronic conditions.  Identifying common chronic clusters may improve understanding of these effects on financial burden and enable policymakers and clinicians to work towards simplifying the care process, and saving patients’ burdens.