Hearing Loss and Older Adults’ Perceptions of Access to Care
- 417 Downloads
We investigated whether hard-of-hearing older adults were more likely to report difficulties and delays in accessing care and decreased satisfaction with healthcare access than those without hearing loss. The Wisconsin Longitudinal Study (2003–2006 wave, N = 6,524) surveyed respondents regarding hearing, difficulties/delays in accessing care, satisfaction with healthcare access, socio-demographics, chronic conditions, self-rated health, depression, and length of relationship with provider/site. We used multivariate regression to compare access difficulties/delays and satisfaction by respondents’ hearing status (hard-of-hearing or not). Hard-of-hearing individuals comprised 18% of the sample. Compared to those not hard-of-hearing, hard-of-hearing individuals were significantly more likely to be older, male and separated/divorced. They had a higher mean number of chronic conditions, including atherosclerotic vascular disease, diabetes and depression. After adjustment for potential confounders, hard-of-hearing individuals were more likely to report difficulties in accessing healthcare (Odds Ratio 1.85; 95% Confidence Interval 1.19–2.88). Satisfaction with healthcare access was similar in both groups. Our findings suggest healthcare access difficulties will be heightened for more of the population because of the increasing prevalence of hearing loss. The prevalence of hearing loss in this data is low and our findings from a telephone survey likely underestimate the magnitude of access difficulties experienced by hard-of-hearing older adults. Further research which incorporates accessible surveys is needed. In the meantime, clinicians should pay particular attention to assessing barriers in healthcare access for hard-of-hearing individuals. Resources should be made available to proactively address these issues for those who are hard-of-hearing and to educate providers about the specific needs of this population.
KeywordsHearing loss Healthcare access Older adults Presbycusis
We acknowledge that this project was supported by the Community-Academic Partnerships core of the University of Wisconsin Institute for Clinical and Translational Research (UW ICTR) funded through an NIH Clinical and Translational Science Award (CTSA), grant number 1 UL1 RR025011. In addition, Nancy Pandhi is supported by a National Institute on Aging Mentored Clinical Scientist Research Career Development Award, grant number l K08 AG029527. Steven Barnett is supported by grant K08 HS15700 from the Agency for Healthcare Research and Quality (AHRQ). This research uses data from the Wisconsin Longitudinal Study (WLS) of the University of Wisconsin-Madison. Since 1991, the WLS has been supported principally by the National Institute on Aging (R01 AG09775, R01 AG033285), with additional support from the Vilas Estate Trust, the National Science Foundation, the Spencer Foundation, and the Graduate School of the University of Wisconsin-Madison. A public use file of data from the Wisconsin Longitudinal Study is available from the Wisconsin Longitudinal Study, University of Wisconsin-Madison, 1180 Observatory Drive, Madison, Wisconsin, 53706 and at http://www.ssc.wisc.edu/wlsresearch/data/. The opinions expressed herein are those of the authors.
- 1.Collins, J. G. (1997). Prevalence of selected chronic conditions: United States, 1990–1992. Vital Health Statistics, 10(194), 1–89.Google Scholar
- 2.Pleis, J. R., & Lethbridge-Cejku, M. (2006). Summary health statistics for U.S. adults: National Health Interview Survey, 2005. Vital Health Statistics, 10(10), 1–153.Google Scholar
- 25.Hauser, R. M., & Willis, R. J. (2004). Survey design and methodology in the Health and Retirement Study and the Wisconsin Longitudinal Study. In L. J. Waite (Ed.), Aging, health and public policy: Demographic and economic perspectives (pp. 209–235). New York: Population Council.Google Scholar
- 27.Davies, A. R., & Ware, J. E. (1991) GHAA’s consumer satisfaction survey and user’s manual (2nd Ed.). Washington, DC: Group Health Association of America.Google Scholar
- 28.WWMAI Rural Health Research Center. ZIP Code RUCA approximation methodology [Internet]. Accessed December 21, 2010, at http://depts.washington.edu/uwruca/index.php.
- 40.Stata Statistical Software [computer program]. (2007). Version 10. College Station, TX: StataCorp LP.Google Scholar
- 41.Huber, P. J. (1967). The behavior of maximum likelihood estimates under non-standard conditions. Paper presented at: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Berkeley and Los Angeles, CA.Google Scholar
- 43.Rogers, W. H. (1993). SG17: regression standard errors in clustered samples. Stata Technical Bulletin, 13, 19–23.Google Scholar
- 48.Cleary, P. D., Edgman-Levitan, S., McMullen, W., & Delbanco, T. L. (1992). The relationship between reported problems and patient summary evaluations of hospital care. QRB Quality Review of Bulletin, 18, 53–59.Google Scholar
- 52.Parsons, J., Baum, S., & Johnson, T. (2000). Inclusion of disabled populations in social surveys: Review and recommendations. Chicago: University of Illinois.Google Scholar
- 53.Kirchner, C. (1998). Improving research by assuring access. Footnotes, 26, 7.Google Scholar