Hearing loss (HL) is under-diagnosed in the United States, referral to audiology specialists is underutilized, and relatively few individuals with HL use hearing aids. The goal of this research is to explore the feasibility of using automated electronic tools to improve the quality of hearing health care provided to patients with mild to moderate HL. The study is unique in that it focuses on detection and referral at the primary care level. Previous research has shown that many individuals with HL live with it for more than ten years and do not receive treatment until the HL has progressed to the moderate-to-severe levels, with resulting significant adverse sequalae. Most primary care physicians (PCP) do not currently screen for HL. This is due to several reasons including a poor understanding of HL and the high complexity of primary care that makes management of less-recognized chronic conditions difficult. Preliminary research suggests that hearing aid use improves following establishment of systems to improve detection of HL and referral by PCP, so improving the identification and referral of these patients has great potential for decreasing morbidity. Nevertheless, important questions remain in this arena. Specifically, (1) To what extent can emerging innovative health care delivery methodologies developed for primary care settings be used to universally increase HL screening and detection rates among patients most likely to experience it? (2) To what extent can this improve the referral rate to audiology specialists? (3) Are patients referred for HL testing actually having it done? In this study, we will employ use of tools that have been used for more visible chronic conditions such as diabetes - electronic clinical management tools, targeted educational interventions, and a team-based approach with audiologists - to determine whether these methods can also increase PCP evaluation for less visible but common chronic conditions such as hearing loss. In particular, we will assess whether these help PCPs better assess and make early identification of HL, and refer such patients when appropriate to audiology specialists. The results will also provide community- based data to inform future studies of health care delivery for patients with HL as well as care for other under-recognized chronic conditions.
NIH ExPorter
NIH ExPorter