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Automated Audiometry

Number: 0870



Policy

Aetna considers automated audiometry that is either self-administered or administrated by non-audiologists experimental and investigational because its effectiveness has not been adequately validated to be equivalent to audiometry performed by an audiologist.

Background

A limited number of studies have compared computer-assisted audiometry that is self-administered or administered by non-audiologists to audiometry administered by an audiologist. 

Mahomed et al (2013) conducted a meta-analysis of studies reporting within-subject comparisons of manual and automated threshold audiometry.  The authors found overall average differences between manual and automated air conduction audiometry to be comparable with test-retest differences for manual and automated audiometry.  The authors found, however, limited data on automated audiometry in children and difficult-to-test populations, automated bone conduction audiometry, and data on the performance of automated audiometry in different types and degrees of hearing loss.

The American Speeh-Language Hearing Association (2013) recommends that hearing screening be conducted under the supervision of an audiologist holding the ASHA Certificate of Clinical Competence (CCC).

In a prospective diagnostic study, Foulad et al (2103) determined the feasibility of an Apple iOS-based automated hearing testing application and compared its accuracy with conventional audiometry.  An iOS-based software application was developed to perform automated pure-tone hearing testing on the iPhone, iPod touch, and iPad.  To assess for device variations and compatibility, preliminary work was performed to compare the standardized sound output (dB) of various Apple device and headset combinations.  A total of 42 subjects underwent automated iOS-based hearing testing in a sound booth, automated iOS-based hearing testing in a quiet room, and conventional manual audiometry.  The maximum difference in sound intensity between various Apple device and headset combinations was 4 dB.  On average, 96 % (95 % confidence interval [CI]: 91 % to 100 %) of the threshold values obtained using the automated test in a sound booth were within 10 dB of the corresponding threshold values obtained using conventional audiometry.  When the automated test was performed in a quiet room, 94 % (95 % CI: 87 % to 100 %) of the threshold values were within 10 dB of the threshold values obtained using conventional audiometry.  Under standardized testing conditions, 90 % of the subjects preferred iOS-based audiometry as opposed to conventional audiometry.  The authors concluded that Apple iOS-based devices provided a platform for automated air conduction audiometry without requiring extra equipment and yielded hearing test results that approach those of conventional audiometry.  This was a feasibility study; its findings need to be validated by well-designed studies.

Khoza-Shangase and Kassner (2013) determined the accuracy of UHear™, a downloadable audiometer on to an iPod Touch©, when compared with conventional audiometry.  Participants were primary school students.  A total number of 86 participants (172 ears) were included.  Of these 86 participants, 44 were females and 42 were males; with the age ranging from 8 years to 10 years (mean age of 9.0 years).  Each participant underwent 2 audiological screening evaluations; one by means of conventional audiometry and the other by means of UHear™.  Otoscopy and tympanometry was performed on each participant to determine status of their outer and middle ear before each participant undergoing pure tone air conduction screening by means of conventional audiometer and UHear™.  The lowest audible hearing thresholds from each participant were obtained at conventional frequencies.  Using the paired t-test, it was determined that there was a significant statistical difference between hearing screening thresholds obtained from conventional audiometry and UHear™.  The screening thresholds obtained from UHear™ were significantly elevated (worse) in comparison to conventional audiometry.  The difference in thresholds may be attributed to differences in transducers used, ambient noise levels and lack of calibration of UHear™.  The authors concluded that the UHear™ is not as accurate as conventional audiometry in determining hearing thresholds during screening of school-aged children.  Moreover, they stated that caution needs to be exercised when using such measures and research evidence needs to be established before they can be endorsed and used with the general public.

In a Cochrane review, Barker et al (2014) stated that acquired adult-onset hearing loss is a common long-term condition for which the most common intervention is hearing aid fitting. However, up to 40 % of people fitted with a hearing aid either fail to use it or may not gain optimal benefit from it. These investigators evaluated the long-term effectiveness of interventions to promote the use of hearing aids in adults with acquired hearing loss fitted with at least 1 hearing aid. The authors concluded that there is some low to very low quality evidence to support the use of self-management support and complex interventions combining self-management support and delivery system design in adult auditory rehabilitation. However, effect sizes were small and the range of interventions that had been tested was relatively limited.

In a 2-phase correlational study, Convery et al (2015) evaluated the reliability and validity of an automatic audiometry algorithm that is fully implemented in a wearable hearing aid, to determine to what extent reliability and validity are affected when the procedure is self-directed by the user, and to investigate contributors to a successful outcome. A total of 60 adults with mild-to-moderately severe hearing loss participated in both studies: 20 in Study 1 and 40 in Study 2; 27 participants in Study 2 attended with a partner. Participants in both phases were selected for inclusion if their thresholds were within the output limitations of the test device. In both phases, participants performed automatic audiometry through a receiver-in-canal, behind-the-ear hearing aid coupled to an open dome. In Study 1, the experimenter directed the task. In Study 2, participants followed a set of written, illustrated instructions to perform automatic audiometry independently of the experimenter, with optional assistance from a lay partner. Standardized measures of hearing aid self-efficacy, locus of control, cognitive function, health literacy, and manual dexterity were administered. Statistical analysis examined the repeatability of automatic audiometry; the match between automatically and manually measured thresholds; and contributors to successful, independent completion of the automatic audiometry procedure. When the procedure was directed by an audiologist, automatic audiometry yielded reliable and valid thresholds. Reliability and validity were negatively affected when the procedure was self-directed by the user, but the results were still clinically acceptable: test-retest correspondence was 10 dB or lower in 97 % of cases, and 91 % of automatic thresholds were within 10 dB of their manual counterparts. However, only 58 % of participants were able to achieve a complete audiogram in both ears. Cognitive function significantly influenced accurate and independent performance of the automatic audiometry procedure; accuracy was further affected by locus of control and level of education. Several characteristics of the automatic audiometry algorithm played an additional role in the outcome. The authors concluded that average transducer- and coupling-specific correction factors are sufficient for a self-directed in-situ audiometry procedure to yield clinically reliable and valid hearing thresholds. Before implementation in a self-fitting hearing aid, however, the algorithm and test instructions should be refined in an effort to increase the proportion of users who are able to achieve complete audiometric results. They stated that further evaluation of the procedure, particularly among populations likely to form the primary audience of a self-fitting hearing aid, should be undertaken.

CPT Codes / HCPCS Codes / ICD-10 Codes
Information in the [brackets] below has been added for clarification purposes.   Codes requiring a 7th character are represented by "+":
ICD-10 codes will become effective as of October 1, 2015:
CPT codes not covered for indications listed in the CPB:
0208T Pure tone audiometry (threshold), automated; air only [without an audiologist]
0209T     air and bone [without an audiologist]


The above policy is based on the following references:
    1. Mahomed F, Swanepoel DW, Eikelboom RH, Soer M. Validity of automated threshold audiometry: A systematic review and meta-analysis. Ear Hear. 2013;34(6):745-752.
    2. Yu J, Ostevik A, Hodgetts B, Ho A. Automated hearing tests: Applying the otogram to patients who are difficult to test. J Otolaryngol Head Neck Surg. 2011;40(5):376-383.
    3. Swanepoel de W, Mngemane S, Molemong S, et al. Hearing assessment-reliability, accuracy, and efficiency of automated audiometry. Telemed J E Health. 2010;16(5):557-563.
    4. Margolis RH, Glasberg BR, Creeke S, Moore BC. AMTAS: Automated method for testing auditory sensitivity: Validation studies. Int J Audiol. 2010;49(3):185-194.
    5. Ho AT, Hildreth AJ, Lindsey L. Computer-assisted audiometry versus manual audiometry. Otol Neurotol. 2009;30(7):876-883.
    6. American Speech-Language-Hearing Association (ASHA). Hearing screening and testing. Information for the Public. Rockville, MD: ASHA; 2013.
    7. Foulad A, Bui P, Djalilian H. Automated audiometry using apple iOS-based application technology. Otolaryngol Head Neck Surg. 2013;149(5):700-706.
    8. Khoza-Shangase K, Kassner L. Automated screening audiometry in the digital age: Exploring Uhear™ and its use in a resource-stricken developing country. Int J Technol Assess Health Care. 2013;29(1):42-47.
    9. Barker F, Mackenzie E, Elliott L, et al. Interventions to improve hearing aid use in adult auditory rehabilitation. Cochrane Database Syst Rev. 2014;7:CD010342
    10. Convery E, Keidser G, Seeto M, et al. Factors affecting reliability and validity of self-directed automatic in situ audiometry: Implications for self-fitting hearing AIDS. J Am Acad Audiol. 2015;26(1):5-18.


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