A survey and clinical evaluation of hearing aid data-logging: a valued but underutilized hearing aid fitting tool

ABSTRACT Objectives: Data-logging is a feature in hearing aids with little empirical evidence as to its use and relationship to outcomes in adults. Two studies were undertaken to evaluate data-logging use. Methods: Study 1: a 27-question web-based survey was developed in consultation with hearing aid manufacturers and distributors, and sent to 358 members of the New Zealand Audiological Society (NZAS). Study 2: data-logging results and hearing aid features from 44 clients were related to the Modified Abbreviated Profile of Hearing Aid Benefit (MAPHAB). Results: Study 1 had 108 respondents to the survey (30% response rate); 88% of audiologists found data-logging to be a useful clinical tool in the overall hearing aid fitting process and 94% found it to be a useful tool in participant counselling. Most audiologists reported data-logging use in the first follow-up appointment and often (but not always) in subsequent appointments. Study 2 found data-logging agreed with self-reported patterns of use. The participants found significant benefit in hearing aids according to the MAPHAB, but data-logging results provided little insight into MAPHAB outcomes. Participants used hearing aids for over 8 h per day, with aids in ‘speech-in-quiet’ modes 67% of the time. Clients fitted to the NAL-NL2 prescription had greater benefit than those fitted to NAL-NL1. The trial audiologists seldom used data-logging to assist fitting. Conclusions: Audiologists self-reported that data-logging was a useful clinical tool for assisting in the hearing aid fitting process, however in practice audiologists did not appear to be using many of the data-logging features.

[1]  Robyn M. Cox,et al.  The Abbreviated Profile of Hearing Aid Benefit , 1995, Ear and hearing.

[2]  H. Dillon,et al.  Client Oriented Scale of Improvement (COSI) and its relationship to several other measures of benefit and satisfaction provided by hearing aids. , 1997, Journal of the American Academy of Audiology.

[3]  Suzanne C. Purdy,et al.  Investigation of the Profile of Hearing Aid Performance in Experienced Hearing Aid Users , 1998, Ear and hearing.

[4]  R M Cox,et al.  Measuring Satisfaction with Amplification in Daily Life: the SADL scale. , 1999, Ear and hearing.

[5]  S. Purdy,et al.  Technology, expectations, and adjustment to hearing loss: predictors of hearing aid outcome. , 2001, Journal of the American Academy of Audiology.

[6]  G Keidser,et al.  NAL-NL1 procedure for fitting nonlinear hearing aids: characteristics and comparisons with other procedures. , 2001, Journal of the American Academy of Audiology.

[7]  Norbert Dillier,et al.  Sound Classification in Hearing Aids Inspired by Auditory Scene Analysis , 2005, EURASIP J. Adv. Signal Process..

[8]  H. Gustav Mueller Data logging: Itʼs popular, but how can this feature be used to help patients? , 2007 .

[9]  G. Keidser,et al.  The NAL-NL2 Prescription Procedure , 2011, Audiology research.

[10]  G. Searchfield,et al.  Occupational stress amongst audiologists: Compassion satisfaction, compassion fatigue, and burnout , 2012, International journal of audiology.

[11]  Ryan W McCreery Data logging and hearing aid use: Focus on the forest, not the trees , 2013 .

[12]  M. P. Moeller,et al.  Predictors of hearing aid use time in children with mild-to-severe hearing loss. , 2013, Language, speech, and hearing services in schools.

[13]  A. Karni,et al.  Better together: reduced compliance after sequential versus simultaneous bilateral hearing aids fitting. , 2014, American journal of audiology.

[14]  Graham Naylor,et al.  Patterns of hearing aid usage predict hearing aid use amount (data logged and self-reported) and overreport. , 2014, Journal of the American Academy of Audiology.

[15]  M. P. Moeller,et al.  Trends and Predictors of Longitudinal Hearing Aid Use for Children Who Are Hard of Hearing , 2015, Ear and hearing.