Background: Professional recommendations to patients concerning hearing instrument (HI) technology levels are not currently evidence-based. Pre-fitting parameters have not been proven to be the primary indicators for optimal patient outcome with different HI technology levels. This results in subjective decision-making as regards the technology level recommendation made by professionals.
Purpose: The objective of this study is to gain insight into the decision-making criteria utilized by professionals when recommending HI technology levels to hearing-impaired patients.
Research design: A set of patient variables (and their respective levels) was identified by professionals as determinant for their recommendation of HIs. An experimental design was developed and 21 representative patient cases were generated. The design was based on a contrastive vignette technique according to which different types of vignettes (patient cases) were randomly presented to respondents in an online survey. Based on these patient cases, professionals were asked in the survey to make a treatment recommendation.
Study sample: The online survey was sent to approximately 3,500 professionals from the US, Germany, France, and Italy. The professionals were randomly selected from the databases of Oticon sales companies. The manufacturer sponsoring the survey remained anonymous and was only revealed after completing the survey, if requested by the respondent. The response rate was 20.5%.
Data collection and analysis: Data comprised of respondent descriptions and patient case recommendations that were collected from the online survey. A binary logit modeling approach was used to identify the variables that discriminate between the respondents' recommendations of HI technology levels.
Results: The results show that HI technology levels are recommended by professionals based on their perception of the patient's activity level in life, the level of HI usage for experienced users, their age, and their speech discrimination score. Surprisingly, the patient's lifestyle as perceived by the hearing care professional, followed by speech discrimination, were the strongest factors in explaining treatment recommendation. An active patient with poor speech discrimination had a 17% chance of being recommended the highest technology level HI. For a very active patient with good speech discrimination, the probability increases to 68%.
Conclusions: The discrepancies in HI technology level recommendations are not justified by academic research or evidence of optimal patient outcome with a different HI technology level. The paradigm of lifestyle as the significant variable identified in this study is apparently deeply anchored in the mindset of the professional despite the lack of supporting evidence. These results call for a shift in the professional's technology level recommendation practice, from nonevidence-based to a proven practice that can maximize patient outcome.
American Academy of Audiology.