Nearly 1.5 billion people globally have some decline in hearing ability throughout their lifetime. Many causes for hearing loss are preventable, such as that from exposure to noise and chemicals. According to the World Health Organization, nearly 50% of individuals 12–25 years old are at risk of hearing loss due to recreational noise exposure. In the occupational setting, an estimated 16% of disabling hearing loss is related to occupational noise exposure, highest in developing countries. Ototoxicity is another cause of acquired hearing loss. Audiologic assessment is essential for monitoring hearing health and for the diagnosis and management of hearing loss and related disorders (e.g., tinnitus). However, 44% of the world's population is considered rural and, consequently, lacks access to quality hearing healthcare. Therefore, serving individuals living in rural and under-resourced areas requires creative solutions. Conducting hearing assessments via telehealth is one such solution. Telehealth can be used in a variety of contexts, including noise and ototoxic exposure monitoring, field testing in rural and low-resource settings, and evaluating auditory outcomes in large-scale clinical trials. This overview summarizes current telehealth applications and practices for the audiometric assessment, identification, and monitoring of hearing loss.

More than 1.5 billion people globally have some decline in their hearing, and 430 million experience disabling hearing loss (World Health Organization, 2021). The impact of hearing loss can have far-reaching effects, including on language development and educational attainment for children, psychosocial outcomes and quality of life, and vocational opportunities throughout the lifespan (Jung and Bhattacharyya, 2012; Emmett and Francis, 2015; Lemke and Scherpiet, 2015; Tomblin , 2015; Russ , 2018; Thiyagarajan , 2019).

It is estimated that nearly 60% of childhood hearing loss is preventable and can be mitigated through early detection and intervention (World Health Organization, 2021). Across the lifespan, potentially preventable causes of acquired hearing loss include ear infections, exposure to noise, and exposure to chemicals. According to the World Health Organization, nearly 50% of individuals 12–25 years of age are at risk of hearing loss due to exposure to unsafe levels of sounds in recreational settings (World Health Organization, 2021). In the occupational setting, an estimated 16% of disabling hearing loss is related to occupational noise exposure, highest in developing countries (Nelson , 2005). For veterans of the United States military service, noise-induced hearing loss and tinnitus continue to be the most prevalent service-connected disability (Yong and Wang, 2015).

Damage to the cochlea from ototoxic drugs is another preventable cause of acquired hearing loss. The reported prevalence of ototoxicity in patients who received ototoxic medications ranges from 4% to 91% with outcomes varying by type and dose of agent (Landier, 2016). Overall use of ototoxic medications is on the rise and is more prevalent among older adults and those with more severe hearing loss (Joo , 2018). Furthermore, robust evidence confirms synergistic effects between ototoxic medications and noise exposure with greater risk for hearing loss from combined exposure (Campo , 2013).

Prospective assessment and monitoring of hearing health is essential for early detection and intervention of hearing damage from noise exposure and ototoxicity. Timely monitoring of hearing outcomes can slow or mitigate hearing damage and may aid in potential alterations to therapy or environment to avoid averse downstream consequences of hearing loss (Fausti , 2005). The comprehensive audiometric assessment is an important component of hearing loss monitoring programs; however, globally, barriers exist that limit the capacity to conduct traditional face-to-face assessments.

Barriers to the provision of conventional in-person hearing services include shortages of hearing specialists and lack of resources, such as sound treated rooms. These challenges are exacerbated by the disproportionate prevalence of potentially preventable hearing loss in rural and low-resource settings. Nearly 44% of the world's population lives in rural areas (World Bank, 2020). The World Health Organization estimates that 93% of low-income and 76% of lower-middle-income countries have fewer than 1 audiologist per 1 × 106 people (World Health Organization, 2021). Even in high income countries, such as the United States, nearly 20% of the population is considered rural (Ratcliffe , 2016), yet audiologists are concentrated in urban areas where household incomes are higher (Coco , 2018; Planey, 2019). The global shortage and maldistribution of hearing specialists has been previously documented (Windmill and Freeman, 2013; Coco , 2018; Planey, 2019). Studies have shown that barriers in access to audiology providers result in delays in diagnosis and treatment (Bush , 2014; Bush , 2015; Bush , 2017). Additionally, Windmill and Freeman (2013) conducted an analysis of audiologist supply and demand in the United States and found that even with conservative estimates, the projected supply of audiologists will not meet demand. This strain is expected to worsen with the growing aging population in the United States.

The use of telehealth applications in audiology is one strategy to extend the reach of hearing healthcare services globally. Telehealth in audiology (or teleaudiology) services are generally provided using peripherals interfaced with computer technology (Swanepoel and Hall, 2010; Krumm, 2016b). Teleaudiology service delivery began in the 1990s, but projects were mostly funded by grants or government programs, limiting advancement and integration into the clinical setting (Bashshur , 2000; Krumm, 2016b). However, emerging technology and the impact of the global pandemic on healthcare have brought renewed acceptance for the use of teleaudiology for the delivery of hearing healthcare services (Kim , 2021; Muñoz , 2021; Palmer, 2021; D'Onofrio and Zeng, 2022). With increased dissemination and implementation of telehealth addressing the challenge of provider shortages, it is possible rural and underserved areas could have improved access to hearing services in their local communities.

In addition to being used to extend hearing healthcare services, teleaudiology can also be used in clinical trials. To prevent hearing loss caused by both noise and chemical exposure, investigations are under way to develop otoprotective and restorative therapies that aim to preserve and repair hair cell function (Crowson , 2017; Youm and Li, 2018; Schilder , 2019). Clinical trials in hearing restoration, such as FX-322 (McLean , 2021), are essential to the advancement of technologies that protect and restore hearing. While clinical trials are vital to the development of these technologies, participation in clinical trials at large is low (Unger , 2021) and often not inclusive of rural, diverse, and/or low-income populations (Unger , 2016; Mudaranthakam , 2022). Decentralized clinical trials (DCTs) are trials executed virtually through telehealth and mobile technologies. The importance of DCTs has become apparent during the COVID-19 pandemic, where traditional clinical trials, dependent on research facilities, experienced disruptions and increasing barriers (Van Norman, 2021). Not only can DCTs facilitate studies outside the traditional clinical research setting, they can extend the reach of recruitment into underserved populations, improve retention, and obtain more real-time, real-world monitoring of participant data (Apostolaros , 2020). Telehealth tools in DCTs can include wearable technology, home visits, direct-to-patient virtual visits, and delivery of study drugs and/or materials directly to a patient (Van Norman, 2021). For studies with auditory measures, this can include the comprehensive assessment of hearing thresholds, speech-in-noise testing, or remote monitoring of hearing. As increasingly more DCTs are established and become more accepted, the ability to measure auditory outcomes in these types of trial designs will be crucial. Existing teleaudiology solutions can be used to support the collection of auditory measures in DCTs.

In this special issue on clinical and investigational tools for measuring auditory outcomes and monitoring hearing loss from noise exposure, we will provide a summary of current telehealth applications in audiology using expert opinion. We will specifically highlight opportunities for utilization in clinical trials assessing the efficacy of pharmaceutical interventions for hearing loss and evaluation and monitoring of hearing loss from noise and other relevant etiologies, such as ototoxic exposure. In this overview, we will introduce telehealth tools for the comprehensive hearing assessment, including service delivery models, methods of data exchange, diagnostic applications, emerging technology, and telehealth considerations.

There are four predominant telehealth models or modes of delivery used in hearing healthcare: synchronous, asynchronous, hybrid, and self-test or self-administered technology (Swanepoel and Hall, 2010; Krumm, 2016b; Krumm, 2020). The models are described below, and advantages and disadvantages of each are reviewed. Readers are also referred to other work, such as Krumm (2016b), for more specifics on model considerations in teleaudiology.

1. Synchronous models

Synchronous telehealth includes a “real-time” audio and video connection between the provider and individual receiving healthcare services (Fig. 1). It typically involves a high-quality video exchange and/or real-time data transmission using remote controlled access. Many audiology services can be done using synchronous telehealth, including screening and diagnostic hearing assessment, otoacoustic emissions, auditory brainstem response testing, video otoscopy, tympanometry, hearing aid/cochlear implant programming, and aural rehabilitation (Krumm, 2016b).

FIG. 1.

(Color online) Real-time/synchronous telehealth model.

FIG. 1.

(Color online) Real-time/synchronous telehealth model.

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a. Advantages of synchronous applications.

The most compelling advantage of synchronous teleaudiology service is that it can mirror in-person services, and it is simple. These systems provide the experience most similar to a face-to-face clinical visit and allow the provider more control of services provided. In this scenario, the provider can see the patient and monitor patient behavior and responses in real time (Yulzari , 2018). The same is true in research, where the live interactive video paradigm allows the researcher to monitor participant response validity.

b. Disadvantages of synchronous applications.

Synchronous systems require the provider or researcher and patient/participant to meet at the same time, which can be cumbersome. A trained facilitator may also be required at the patient site and adds cost to the paradigm, which is not always reimbursable. Synchronous models are limited by the need for adequate Internet bandwidth at both the provider/researcher and patient/participant locations. Prior work suggests a minimum Internet or network bandwidth of 100–200 kilobits/s is required for successful real time exchange (Lancaster , 2008; Monica , 2017). The bandwidth for live video should be capable of producing high-quality interactive video without the loss of video packets (data) or remote computing information obtained from the patient or research participant. Optimal bandwidth video speed in most cases is 30 frames/s (Krumm, 2016b; Krumm, 2020). Bandwidth allocation should be coordinated through IT personnel to have desired synchronous services. In addition, synchronous teleaudiology services should be piloted to ensure sufficient bandwidth for service delivery.

2. Asynchronous models

Asynchronous, or store-and-forward, telehealth includes acquiring and storing data at the patient site and transmitting it to the hearing healthcare provider at a regional site for review and consultation (Fig. 2). With asynchronous telehealth, images or data are typically stored on a cloud platform or sent via secure email. Within audiology, asynchronous telehealth has been used for video otoscopy, tympanometry, otoacoustic emissions (OAEs), automated hearing testing, hearing aid programming, and aural rehabilitation (Kokesh , 2010; Swanepoel and Hall, 2010; Jacobs , 2012; Biagio , 2013; Botasso , 2015; Dille , 2015; Krumm, 2016b; Brungart , 2018). Furthermore, investigators have found that services provided asynchronously achieve outcomes equal to those of in-person services (e.g., Patricoski , 2003; Kokesh , 2008; Lancaster , 2008; Lundberg , 2017; Moberly , 2018; Konrad-Martin , 2021).

FIG. 2.

(Color online) Asynchronous/store-and-forward telehealth model.

FIG. 2.

(Color online) Asynchronous/store-and-forward telehealth model.

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a. Advantages of asynchronous applications.

Asynchronous applications have the advantage of being delivered to geographical locations where Internet or network bandwidths are limited. Providers and researchers will most likely find limited bandwidth in developing countries, rural areas, or simply locations in which connectivity is poor. Using asynchronous applications, patient data can be transmitted via mobile phone, satellite, fax, or telephone (Hofstetter , 2010; Watson , 2012; Brennan-Jones , 2016; Krumm, 2020). Typically, a facilitator is on-site to assist with patient data collection and transmission. However, another advantage of asynchronous service delivery is that, in some cases, data services can be collected by the patient/participant themselves (self-test) and transmitted to a provider/investigator in a different location.

Another advantage of asynchronous telehealth applications is that many audiology peripherals can be used asynchronously and transmitted using simple solutions like attachments in email. An example is tympanometry, where the tympanogram result can be printed and scanned into a computer and sent via email to the examiner (Lancaster , 2008) or obtained by a screen capture and sent as an attachment. Likewise, video files from video otoscopy can be saved and sent as an email attachment (Kokesh , 2008; Kokesh , 2010).

b. Disadvantages of asynchronous applications.

Potential disadvantages of asynchronous models include the lack of direct interaction between provider/researcher and patient/participant and the inherent delays in receiving the provider's recommendations compared to real-time exchange (Williams , 2001). In the absence of real-time communication, facilitator training may be particularly important (Coco , 2021), including how to observe behavioral responses and how to respond to questions. Data integrity may become compromised from factors such as background noise in the environment or poor acquisition. However, these issues can be ameliorated in a variety of ways. For example, feedback can be automated (Eksteen , 2019), and response reliability to test stimuli can be assessed using computer algorithms built into the audiometric software (Mahomed-Asmail , 2016). In addition, ambient noise levels can be measured continuously (Swanepoel , 2015; Brennan-Jones , 2016).

3. Hybrid models

Hybrid telehealth, as the name indicates, is a combination of both synchronous and asynchronous models of data transmission and technology (Fig. 3). It allows the flexibility to provide a variety of services needed at the time. An example is asynchronous capture and review of video otoscopic images, tympanometry, and OAE results, combined with synchronous (real-time) case history, hearing assessment, and counseling to maximize Internet bandwidth and resource efficiency. In each of these models (synchronous, asynchronous, and hybrid), a trained facilitator or technician is often needed at the patient site to assist with hands-on duties, such as situating headphones on the patient for testing (Coco , 2020). Hybrid teleaudiology models can also be a combination of in-person and telehealth visits (Arnold , 2022).

FIG. 3.

(Color online) Example of a hybrid telehealth model.

FIG. 3.

(Color online) Example of a hybrid telehealth model.

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a. Advantages of hybrid applications.

A hybrid teleaudiology paradigm incorporates both synchronous and asynchronous applications and offers the most flexibility. In addition, hybrid services appear most beneficial when a full complement of audiology services is provided. However, few hybrid teleaudiology services have been described in practice (Dennis , 2012; Dworsack-Dodge, 2013; Ratanjee-Vanmali , 2020). An example of a hybrid application was employed in a school screening of elementary aged children in rural Utah (Lancaster , 2008), where pure tone screening and video otoscopy were conducted synchronously and tympanometry asynchronously. Outcomes yielded results comparable to those obtained face to face.

b. Disadvantages of hybrid applications.

There are limited additional disadvantages to the hybrid telehealth models, since it provides the greatest flexibility, but it typically does require audiologists and facilitators to be comfortable with a diverse array of technology necessary for data collection and exchange.

4. Self-testing models

A fourth, emerging telehealth model is the use of self-directed or self-administered technology (Fig. 4). Although the concept of self-testing audiometry dates back to Békésy audiometry in the mid-1900s (Jerger, 1962), the more recent advancement in technology, particularly Mobile health (mHealth) solutions, has propelled the increased popularity of this model. As is suggested by the terminology, the patient is testing themselves without assistance or perhaps with only an on-site facilitator. The most common methods for self-testing include pure tone screening and speech-in-noise tasks that are either accessed via a cellphone or wired landline telephone (Williams-Sanchez , 2014), a personal computer with an Internet browser and calibrated earphones (Margolis , 2016), and a smartphone with calibrated headphones (De Sousa , 2018; De Sousa , 2020). Self-testing is advantageous for conducting population-based hearing screening but requires careful consideration for calibration of screening tools, equipment used, ambient noise levels, and training provided (Masalski and Kręcicki, 2013; Al-Abri , 2016; Mosley , 2019).

FIG. 4.

(Color online) Self-administered hearing screening/testing.

FIG. 4.

(Color online) Self-administered hearing screening/testing.

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a. Advantages of self-testing applications.

This paradigm has all the advantages of asynchronous models, which enable testing to occur anytime and anyplace the self-testing application is available. Self-test applications may be used online using the Internet and accessed by a microcomputer or smart phone (Masalski and Kręcicki, 2013; Sandström , 2020). Self-testing using speech-in-noise is frequently used for hearing screening purposes online or via telephone (Watson , 2012; Smits , 2013; Williams-Sanchez , 2014; Koole , 2016). Investigators have also developed self-testing diagnostic systems, which will be reviewed later (Swanepoel and Biagio, 2011; Dille , 2015; Brungart , 2018). Self-testing has the potential of reaching large populations of people in the most remote locations (Koole , 2016; Krumm, 2020; Sandström , 2020). Not only can self-testing extend the reach of audiology screening and services; it also creates an opportunity to share electronic health (eHealth) information, simulations of hearing loss, and referral sources for consumers.

b. Disadvantages of self-testing applications.

The challenges with self-testing/screening are similar to those found with asynchronous audiology paradigms, where there is less direct provider/patient interaction and there can be a higher risk of compromised data collection. One solution available to reduce concerns for data quality, particularly for automated hearing testing, is algorithms for measuring response reliability, such as Qualind™ used in the GSI Automated Method for Testing Auditory Sensitivity (AMTAS) (Margolis , 2007). Other challenges for self-testing potentially include Internet infrastructure at home, cost, access gaps, and digital health literacy (Garg , 2020; Raj Westwood, 2021).

Telehealth allows two sites to connect from different locations. Communication and data exchange can occur using one of three primary types of models: clinic-to-satellite clinic, direct-to-patient, or eHealth/mHealth.

In a clinic-to-satellite clinic exchange, the consulting provider is located at a regional center and the individual receiving healthcare services is at a satellite clinic, typically with a facilitator present. This is also known as the hub-and-spoke model. One example is Williams (2020), who set up a model where audiologists are located at a centralized hub site (in this case, a university clinic in the United States) and connected with patients at distant spoke or satellite sites in rural areas across the state. Spoke sites have testing equipment specific to the audiology services or procedures, such as auditory brainstem response (ABR), OAE, tympanometry, and video otoscopy, as well as a computer and a web camera, while the hub location, where the provider is located, typically requires a web camera and computer.

The direct-to-patient exchange involves an individual undergoing hearing healthcare services from within their own home, instead of at a traditional clinic or formal healthcare setting. Brungart (2018) reviewed portable tablet-based automated auditory assessment tools used in ototoxicity monitoring programs. They found several devices that use automated protocols designed for self-testing from within the patient's own home. One example is the Ototoxicity Identification Device (OtoID) system, a portable audiometer with high frequency test functionality (0.5–20 kHz) designed for either manual use by an audiologist or automated for direct-to-patient exchange (Jacobs , 2012; Dille , 2015; Konrad-Martin , 2021). There are also several hybrid models that incorporate a direct-to-patient component and have demonstrated feasibility, such as a recent pilot study by Arnold (2022). The authors evaluated smartphone-based virtual visits following in-person delivery of a hearing intervention and found improved performance and no significant difference in patience satisfaction between in-person and virtual visits (Arnold , 2022).

eHealth, or the use of modern communication technology to transmit health information, is becoming more prevalent as individuals receive information regarding their health through patient portals. eHealth also includes the use of virtual check-in through secure messaging technologies (Krumm, 2016b). mHealth is another way to transmit information and involves the use of mobile phones, tablets, or other wireless technology. In hearing healthcare, mHealth is commonly used to conduct video otoscopy and hearing screenings, and it is also being incorporated into diagnostic hearing assessments (Krumm, 2016b). One major benefit of mHealth data transmission is that mobile-based platforms are portable, layperson-friendly, and cloud-based. Potential drawbacks include concerns about patient safety, privacy, and security (D'Onofrio and Zeng, 2022), as well as a lack of standards for application (app) quality (Irace , 2021). In van Wyk (2019), community health workers were trained to administer smartphone-based hearing screenings in their community using a validated smartphone app [HearScreen by hearX (Pretoria, South Africa)]. In this community-based mHealth hearing screening program, data were instantly uploaded from the smartphone app to a secure cloud-based server, allowing for community-based data capture and off-site management.

The comprehensive audiometric assessment is central to evaluation and monitoring of ototoxic and noise exposure, as well as when considering auditory outcomes in clinical trials. Research has documented the validity of telehealth applications in nearly all aspects of the comprehensive audiometric assessment. Table I provides a summary of the primary elements in the audiometric evaluation, the telehealth models, types of information exchange, and key references for each.

TABLE I.

Summary of the primary components in the audiometric evaluation and the possible telehealth models, types of information exchange, and key references for each.

Service delivery mode Type of information exchange Key references
Synchronous (real-time) Asynchronous (store-and-forward)
Video otoscopy   
Remote provider views images of the tympanic membrane and ear canal in real time using videoconferencing and remote desktop share applications.  A non-specialist facilitator obtains photos and/or recordings (videos) of the tympanic membrane and ear canal and sends videos/images off-site to a clinician for review and diagnosis.  Clinic-to-satellite; direct-to-patient; mHealth  Crump and Driscoll (1996); Stern (1998); Whitten and Cook (1999); Holtel and Burgess (2002); Eikelboom (2002); Patricoski (2003); Eikelboom (2005); Lancaster (2008); Kokesh (2008); Lundberg (2008); Ciccia (2011); Biagio (2013); Lundberg (2017); Soares (2019); Erkkola-Anttinen (2019); Alenezi (2021)  
Tympanometry   
Remote provider connects with patient site via videoconferencing, and a trained facilitator conducts tympanometry screenings in real-time.  A trained facilitator located at the patient site conducts tympanometry screenings. Results are sent to an off-site clinician for review.  Clinic-to-satellite  Lancaster (2008); Hofstetter (2010); Ciccia (2011); Kleindienst (2014)  
Audiometry   
Provider remotely controls a computer-based audiometer to conduct testing in real time and communicates with patient via videoconferencing.  Automated or screening protocols are used to conduct hearing assessments at the patient site. Results are sent to an off-site clinician for review.  Clinic-to-satellite; direct-to-patient; mHealth; self-test  Givens and Elangovan (2003); Swanepoel and Biagio (2011); Eikelboom (2013); Brennan-Jones (2016); van Tonder (2017); Sandström (2020); Konrad-Martin (2021)  
Speech testing   
The patient is in a quiet environment and is tested using pre-recorded calibrated test materials. The clinician connects from off-site via videoconferencing.  Automated, self-administered speech-in-noise tests can be accessed via tablets or cell phones. Results can be shared with providers or used for self-monitoring.  Clinic-to-satellite; direct-to-patient; mHealth; self-test  Ribera (2005); Potgieter (2016); Smits (2013); De Sousa (2020); Venail (2021)  
OAEs   
OAE screenings can be done remotely via interactive real-time audio and video exchange and screenshare.  Trained facilitators conduct screenings at the patient site. Results are sent to an off-site clinician for review.  Clinic-to-satellite; direct-to-patient; mHealth  Krumm (2007); Ciccia (2011); Monica (2017); Ameyaw (2019)  
Service delivery mode Type of information exchange Key references
Synchronous (real-time) Asynchronous (store-and-forward)
Video otoscopy   
Remote provider views images of the tympanic membrane and ear canal in real time using videoconferencing and remote desktop share applications.  A non-specialist facilitator obtains photos and/or recordings (videos) of the tympanic membrane and ear canal and sends videos/images off-site to a clinician for review and diagnosis.  Clinic-to-satellite; direct-to-patient; mHealth  Crump and Driscoll (1996); Stern (1998); Whitten and Cook (1999); Holtel and Burgess (2002); Eikelboom (2002); Patricoski (2003); Eikelboom (2005); Lancaster (2008); Kokesh (2008); Lundberg (2008); Ciccia (2011); Biagio (2013); Lundberg (2017); Soares (2019); Erkkola-Anttinen (2019); Alenezi (2021)  
Tympanometry   
Remote provider connects with patient site via videoconferencing, and a trained facilitator conducts tympanometry screenings in real-time.  A trained facilitator located at the patient site conducts tympanometry screenings. Results are sent to an off-site clinician for review.  Clinic-to-satellite  Lancaster (2008); Hofstetter (2010); Ciccia (2011); Kleindienst (2014)  
Audiometry   
Provider remotely controls a computer-based audiometer to conduct testing in real time and communicates with patient via videoconferencing.  Automated or screening protocols are used to conduct hearing assessments at the patient site. Results are sent to an off-site clinician for review.  Clinic-to-satellite; direct-to-patient; mHealth; self-test  Givens and Elangovan (2003); Swanepoel and Biagio (2011); Eikelboom (2013); Brennan-Jones (2016); van Tonder (2017); Sandström (2020); Konrad-Martin (2021)  
Speech testing   
The patient is in a quiet environment and is tested using pre-recorded calibrated test materials. The clinician connects from off-site via videoconferencing.  Automated, self-administered speech-in-noise tests can be accessed via tablets or cell phones. Results can be shared with providers or used for self-monitoring.  Clinic-to-satellite; direct-to-patient; mHealth; self-test  Ribera (2005); Potgieter (2016); Smits (2013); De Sousa (2020); Venail (2021)  
OAEs   
OAE screenings can be done remotely via interactive real-time audio and video exchange and screenshare.  Trained facilitators conduct screenings at the patient site. Results are sent to an off-site clinician for review.  Clinic-to-satellite; direct-to-patient; mHealth  Krumm (2007); Ciccia (2011); Monica (2017); Ameyaw (2019)  

Video otoscopy involves the use of an otoscopic device with a camera attached to the end. Video otoscopy is used to capture and store still images and videos of the external auditory canal and tympanic membrane. Video otoscopy is a natural fit for telehealth service delivery, and research has shown that remote otologic assessment and diagnosis using video otoscopic images are comparable to traditional in-person otoscopy. Video otoscopy via telehealth has been well-validated in both synchronous (Crump and Driscoll, 1996; Stern , 1998; Whitten and Cook, 1999; Holtel and Burgess, 2002; Lancaster , 2008; Ciccia , 2011; Alenezi , 2021) and asynchronous (Stern , 1998; Eikelboom , 2002; Holtel and Burgess, 2002; Patricoski , 2003; Eikelboom , 2005; Kokesh , 2008; Lancaster , 2008; Lundberg , 2008; Biagio , 2013; Lundberg , 2017) telehealth models.

There are numerous types of video otoscopes, including large imaging and illumination platforms, handheld digital otoscopes, and mHealth otoscopes used in conjunction with a smartphone. Video otoscopic images can be viewed on the unit itself, via a wired USB or wireless connection (Bluetooth) to a laptop or desktop computer, or on a smartphone or tablet screen. Video otoscopes can be dedicated (single purpose) or have multiple exam cameras or lenses to support a variety of rigid and flexible scopes. They can be powered by battery, personal computer (PC), or smartphone. Video otoscopes can be easily added to a laptop driving other technology, or they can come bundled in a package cart system.

Because video otoscopes allow capturing and recording of images, video otoscopy can provide an enhanced view of the tympanic membrane in contrast to traditional otoscopes. However, clinical image quality is an important component of how successfully video otoscopy can be performed, and this factor can vary widely. Clinical image quality includes factors such as device field of view and depth of view, resolution and clarity, color accuracy, and image light quality. As technology improves, more video otoscope options are becoming available at lower costs with improved image quality. Soares (2019) found that low-cost ($25.99–$49.99), smartphone-based video otoscopes yielded high-quality images for otologic examination. These low-cost mHealth video otoscopes are often marketed to parents of children with suspected ear infection and are layperson-friendly and relatively easy to operate. Early evidence suggests that parents can accurately perform video otoscopy for diagnosis of otitis media (Erkkola-Anttinen , 2019).

Video otoscopy can also be performed well by facilitators. Lundberg (2017) showed good diagnostic accuracy of video otoscopy by a trained healthcare facilitator compared to traditional face-to-face otoscopy by a physician. The increasing accessibility of video otoscope technology, with regard to both cost and usability, may help support telehealth adoption and implementation in audiology.

In recent years, there has also been significant development of automated diagnosis of ear disease using deep learning machine models (Myburgh , 2016; Myburgh , 2018; Cha , 2019; Livingstone and Chau, 2020; Esposito , 2021; Wu , 2021; Zeng , 2021). Thousands of images of tympanic membranes with various types of ear diseases have been used to train machine learning models to automatically classify with relatively high accuracy (80%–97%) (Myburgh , 2016; Myburgh , 2018; Cha , 2019; Livingstone and Chau, 2020; Zeng , 2021). Machine learning algorithms can facilitate early detection and management of ear disease where access to skilled specialists, such as audiologists and otolaryngologists, is limited.

Tympanometry, an assessment of middle ear function, is another procedure in the audiological comprehensive examination that can be accomplished via telehealth. Tympanometry has been validated using both synchronous and asynchronous telehealth models (Lancaster , 2008; Ciccia , 2011). Lancaster (2008) conducted screenings in an elementary school setting where tympanometry was asynchronously collected, and results were scanned and emailed to an audiologist for review and interpretation. Alternatively, Ciccia (2011) used synchronous video and remote desktop applications to view and/or control tympanometry collected at another location in real time.

Tympanometry via store-and-forward telehealth is also used as part of clinical care in rural Alaska, where the prevalence of otitis media is high. In rural Alaska, the Alaska Federal Health Care Access Network (AFHCAN) system is used regularly to capture still otoscopic images and tympanometry using the asynchronous telehealth model to manage middle ear disease remotely. Otolaryngologists were comfortable using tympanometry combined with video otoscopy to diagnosis and treat otitis media (Kleindienst, 2014), and using this asynchronous model reduced wait time on ENT specialty care by more than 3 months (Hofstetter , 2010). A hybrid model is also used for collection of audiometric data, including tympanometry for difficult to test patients, complex otologic cases, and training. In this model, the trained facilitator would be with the patient collecting the data with the audiologist on real-time video, watching and providing guidance on test acquisition.

Technology advancement in tympanometry for telehealth is limited. To date, there are no known mHealth applications available for tympanometry. However, a recent study by Chan (2019) evaluated acoustic reflectometry using the microphone and speaker of a smartphone with a paper funnel to detect middle ear fluid and found results similar to commercial equipment. Further work is needed in this area, and work is currently under way to address gaps in hearing healthcare using mHealth applications for tympanometry (NIH RePORTER NIH Grant No. R21DC020134).

Pure tone testing is another measure in the audiologic test battery that is well-validated for telehealth service delivery. Evidence has been generated for diagnostic hearing testing (Givens , 2003; Givens and Elangovan, 2003; Krumm , 2007; Swanepoel and Biagio, 2011; Meinke , 2017) and screening hearing (Lancaster , 2008; Mahomed-Asmail , 2016; Skarzyński , 2016; Yousuf Hussein , 2016; Yousuf Hussein , 2018; Dawood , 2021) via telehealth.

Telehealth-delivered manual diagnostic hearing testing is predominantly done using a real-time synchronous telehealth model with an audiometer located at the patient site and the audiologist using remote desktop applications to control the audiometer and measure thresholds. Both air and bone conduction testing have been validated, although less evidence is available for bone conduction (Swanepoel and Biagio, 2011; Maclennan-Smith , 2013; Swanepoel , 2013). However, the development of technological advances with several audiometric systems has made bone conduction testing via telehealth a possibility, both for manual and automated testing. These audiometric systems include KUDUwave, Creare Wireless Automated Hearing Test (WAHTS), GSI AMTAS, and SHOEBOX and are discussed in greater detail in Sec. V A.

Automated audiometric testing could be used to identify or monitor noise-induced and ototoxic hearing loss. Research has documented the validity and reliability of automated audiometry for both air and bone conduction thresholds (Eikelboom , 2013; Serpanos , 2021). Mahomed (2013) conducted a systematic review and meta-analysis on the test-retest reliability and accuracy of automated audiometry. Among the included studies, results showed that the overall differences between manual and automated air conduction thresholds were only 0.4 dB [6.1 standard deviation (SD)], and test-retest differences were insignificant at 1.3 dB (6.1 SD) and 0.3 dB (6.9 SD). Studies have also shown that bone conduction automated audiometry is reliable (Shojaeemend and Ayatollahi, 2018). Furthermore, solutions exist to better understand the reliability of the self-test audiogram results, such as quality indicators, or Qualind™, which provides a categorical predicted accuracy (good, fair, poor) based on factors such as age and gender, false alarm rate, and response time (Margolis , 2007). When frequent monitoring of hearing is required, such as that of patients with noise or ototoxic exposures or participants receiving restorative therapy in a clinical trial, automated testing may provide a solution for measuring hearing often without increasing the burden on the individual or healthcare institution.

Hearing screening using telehealth applications has been done using both asynchronous and synchronous telehealth models. In the asynchronous models, hearing screening is conducted by a trained facilitator or community screener on-site with the patient and then uploaded or sent to the provider or partnering health organization (Skarzyński , 2016; Yousuf Hussein , 2018). Synchronous models have been employed with the audiologist using real-time video to provide supervision and guidance of screening, as well as conduct the hearing screening using remote control technology (Lancaster , 2008; Ciccia , 2011).

Speech testing, as part of the audiometric test battery (e.g., speech reception/detection threshold, speech discrimination, and speech-in-noise testing), is currently available in several telehealth systems used today for audiology, but limited empirical evidence exists. Ribera (2005) evaluated patients' results from the Hearing in Noise Test (HINT) using synchronous telehealth and found results were comparable to in-person testing. The digits-in-noise (DIN) test is an automated, self-administered speech-in-noise screening assessment using digit triplets in steady-state speech noise. The DIN test is accessed as a smartphone or tablet-based app, and its feasibility and validity have been documented across several studies (Smits , 2013; Koole , 2016; Potgieter , 2016; De Sousa , 2020).

The feasibility and validity of word recognition has also been evaluated via a smartphone app and compared to presentation using a computer and compact disc (CD) player (van Zyl , 2018). Regardless of hardware used (smartphone, computer, CD player), there was no significant effect on the frequency content of the recorded word lists and there was good inter-list reliability. Some of the previously mentioned telehealth equipment incorporates speech testing (e.g., the KUDUwave and SHOEBOX audiometers).

Investigators have also validated speech testing via telehealth for hearing aid and cochlear implant programming. Evidence suggests speech testing using telehealth solutions in the field is similar to that in the sound booth (Goehring , 2012; Hughes , 2012; Schepers , 2019; Luryi , 2020), as well as remotely versus face-to-face (Venail , 2021). However, it should be noted that one study found poorer speech perception in the remote location likely due to the lack of a sound booth (Hughes , 2012).

The use of OAEs in telehealth is well-validated and has primarily been used via synchronous models (Krumm , 2007; Krumm , 2008; Ciccia , 2011; Monica , 2017; Ameyaw , 2019). It is worth noting that most studies have been conducted in young school-aged children or newborns and predominantly using DPOAEs. However, there are also applications in ototoxic exposure and noise monitoring (Khoza-Shangase and Moroe, 2020).

There is limited evidence to date on telehealth solutions in audiology relating to noise-induced hearing loss and the measurement of harmful noise levels. A recent scoping review (Khoza-Shangase and Moroe, 2020) offers some insight into current telehealth applications in audiology for noise measurements. Overall, the authors found that literature on hearing conservation programs was lacking on an international basis and suggested that telehealth applications may be particularly effective in areas that have limited resources to provide effective hearing conservation programs.

One key area in which telehealth and mHealth may be applied to monitoring noise exposure is with the emergence of smartphone technology (McLennon , 2019). Several apps are available today at minimal or no cost and essentially transform the microphone of the cell phone into a sound level meter (SLM). App technology has the potential to provide individuals and employers with mHealth information concerning harmful levels of noise in a variety of environments, including work, home, and recreational activities.

However, not all smartphone SLM apps are created equal. Research on the accuracy of SLM apps has shown that a small number of apps are accurate to within ±2 dB and therefore could be used for some (non-regulatory) occupational noise measurements, and a number of apps lack the precision necessary for precise noise measurements (Kardous and Shaw, 2014; Nast , 2014; McLennon , 2019). According to Kardous and Shaw (2014), the most accurate smart phones for sound level measurement were those on iOS (iPhone operating system).

As smartphone technology continues to improve, the gap between smartphone applications and SLMs is narrowing. In a follow-up study, Kardous and Shaw (2016) published data concerning four iOS SLM apps using external microphones that produced consistently accurate noise level measurements within 1 dB of the reference. Similarly, McLennon (2019) evaluated ten iOS and Android smartphones and found subtle differences between them, although Android apps underreported sound levels at the higher levels (90 dBA).

There is still work to be done to conform to the International Electrotechnical Commission (IEC) and the American National Standards Institute (ANSI) standards, but data do show promise. The National Institute for Occupational Safety and Health (NIOSH) released an iOS-based SLM (National Institute for Occupational Safety and Health, 2022) that, when used with a properly calibrated external microphone, mostly met the type 2 requirements of the IEC 61 672/ANSI S1.4 standard: Sound Level Meters—Part 3: Periodic Tests (Celestina , 2018). The NIOSH app can provide various kinds of sound measurements, including equivalent continuous sound pressure level (LAeq) and time-weighted average (TWA), maximum and peak levels, and noise dose and projected dose in either NIOSH or OSHA standards and is accurate within ± 2 dB. This app can also measure in A, C, or Z weightings.

The NIOSH app is consumer-oriented and provides instructions to layperson users in how to conduct noise measurements as well as properly select a hearing protection device (HPD), and it includes information about the prevention of hearing loss. It also supports sound measurements using the internal mic of the iPhone for individuals who do not have an external mic, which produces only slightly less accurate measurements than with an external mic. The NIOSH app has received recent attention by researchers (Crossley , 2021) who evaluated nine noise measurement apps and found the NIOSH SLM app to be the most accurate. Consequently, this app can be used to inform consumers and workers alike about the effects of noise in their work and recreational environments (Crossley , 2021).

Other emerging direct-to-patient models that address individuals' noise exposure risk include a Windows-based operating system developed by NIOSH, which allows individuals to check the attenuation of their HPDs (Paraventi, 2019). This system is called Well-Fit and allows for quick fit-testing for hearing protection (National Institute for Occupational Safety and Health, 2015). It is now distributed as FitCheck Solo (Michael & Associates, 2015). NIOSH has also created a simple web-interfaced program that allows any user to check the fit of their hearing protection by playing two sound files with and without HPDs to determine if the fit is correct (National Institute for Occupational Safety and Health, 2012). The program is free and accessible via the Internet; therefore, it may be helpful to workers and other consumers who are interested in evaluating whether their HPD is providing at least 15 dB of attenuation. These technologies aim to address one of the significant causes for the lack of HPD effectiveness—poorly fitting HPDs (Byrne , 2017).

Additional HPD attenuation check fit programs include but are not limited to the Honeywell Safety Products (Charlotte, NC) VeriPRO, 3 M E-A-Rfit Dual-Ear Validation System, INTEGRAfit for Apple iPad by Workplace INTEGRA, and SonoPass by Sonomax. Data obtained in these systems can be utilized in a variety of ways for healthcare using asynchronous telehealth models, which could include training for effective HPD fittings, HPD deterioration over time, and monitoring for when significant hearing threshold shifts are observed.

Ototoxicity monitoring programs (OMPs) aim to reduce the effects of ototoxic and vestibulotoxic drugs when possible and to plan for interventions if cochlear and vestibular systems become affected. Ototoxic and vestibulotoxic drugs include aminoglycoside antibiotics, platinum-based chemotherapy (including cisplatin and carboplatin), loop diuretics, non-steroidal anti-inflammatory drugs (NSAIDS), and chemotherapeutic agents, such as cisplatin, with NSAIDs (Campbell and Le Prell, 2018; Konrad-Martin , 2018). These drugs are administered for a variety of diseases, including cancer, cystic fibrosis, tuberculosis, sepsis, and other life-threatening disease (Konrad-Martin , 2018).

Ideally, OMPs include a battery of tests to assess the effects of ototoxic and vestibulotoxic drugs (Brungart , 2018; Campbell and Le Prell, 2018; Konrad-Martin , 2018), which typically incorporate high frequency pure tone testing, speech perception and speech-in-noise testing, DPOAEs, auditory brainstem response (for patients unable to respond), tinnitus inventories, and balance inventories. However, OMPs are often employed inconsistently or with non-standard monitoring practices (Konrad-Martin , 2018). Furthermore, the audiological portion of ototoxic monitoring is often limited by the lack of trained professionals and sound treated rooms. The same is true in clinical trials evaluating hearing restoration and otoprotection (Le Prell, 2021). Advances in telehealth service delivery and remote testing technology have allowed researchers and clinicians to address these challenges for patients receiving ototoxic medications. One example is the OtoID system, mentioned previously (Jacobs , 2012; Dille , 2013; Dille , 2015; Konrad-Martin , 2021). The OtoID system is a mobile high frequency audiometer that enables patients taking ototoxic medications to complete self-administered hearing testing. Data are then asynchronously transmitted to the audiologist to monitor for changes in high frequency hearing loss. A more recent version of the OtoID system incorporates an SMS text format for transmission of results to providers, demonstrating increased efficiency in ototoxic management with time savings realized for both provides and patients (e.g., faster, easier access to results with fewer trips to the clinic location when change in hearing is not indicated). The OtoID system also incorporates speech-in-noise tests, DPOAEs, patient questionnaires, and active noise monitoring to ensure valid responses in noisy environments (Dille , 2015). Finally, a recent randomized trial (Konrad-Martin , 2021) found that the OtoID system, using an automated protocol during infusion treatments, improved OMP adherence compared to traditional in-clinic monitoring (83.3% and 4.5%, respectively). This study demonstrates that the use of teleaudiology techniques may in some cases be more advantageous than traditional in-person visits.

Technology advancement has resulted in more systems that can be used in OMPs to enable time-efficient monitoring (Brungart , 2018). The Creare Wireless Audiometer (WAHTS) is an audiometer built into supra-aural headphones controlled wirelessly by an Android tablet using Bluetooth (Meinke , 2017). The Creare system is operated by an open-source program called TabSINT designed to provide customized inventories and diagnostic tests for OMP applications. The KUDUwave audiometer is yet another example of a computer-driven, headset-encased audiometer. The KUDUwave can be configured for high frequency pure tone testing up to 20 kHz (Peerbhay , 2022). Patients can conduct self-testing with audiometric data sent via store and forward to an audiologist for interpretation. The SHOEBOX audiometer is a tablet-based (Apple iPad) audiometer that has been used in OMPs. One example is a study (Vijayasingam , 2020) that used a combination of self-administered web-based pure tone testing, pure tone testing with extended high frequencies (up to 12.5 kHz) using the SHOEBOX audiometer, and validation questionnaires to screen and monitor for hearing loss in adults with cystic fibrosis, often treated with aminoglycosides resulting in ototoxicity.

The ability to monitor high frequency hearing loss is also now available using smartphone technology. There are several apps available for this purpose, and details can be found in a comprehensive scoping review (Peerbhay , 2022). Initial validation studies for high frequency threshold testing via a smartphone have been conducted (Bornman , 2019), and results have been found accurate (up to 16 kHz) when used with RadioEar DD450 audiometric headphones and a digital audio converter (V3 DAC). There are also several smartphone apps that do not directly measure high frequency hearing but could be incorporated into OMPs. Examples include a collaborative app by Apple and Unitron (Commack, NY), which resulted in the uHear (Al-Abri , 2016) self-testing software. This app includes speech-in-noise testing that may be beneficial for use with individuals who require OMPs, if properly validated. OtoCalc (Hollander , 2020) is another app designed to help audiologists manage patients with ototoxicity more effectively. Consumer-facing apps have the potential to play a significant role in helping identify and monitor the negative effects of ototoxic or vestibulotoxic medications, particularly for patients in underserved areas, yet as this area grows, there is a need to evaluate their effectiveness. While the growth in mobile and consumer-facing technology is promising for addressing challenges in ototoxic monitoring, these solutions can vary in OMP paradigms, such as type of stimuli used. Standardization in OMP practices should be incorporated into developing teleaudiology practices and emerging technology.

Previous investigations have documented the synergistic effects between ototoxic agents and excessive noise levels (Pouryaghoub , 2007; Steyger, 2008; Durrant , 2009; Wang , 2017; Morata , 2021). Teleaudiology applications may offer monitoring capabilities for individuals to identify and then mitigate the harmful effects of noise and ototoxicity and their synergistic effects. The OTO ID system previously described in this paper appears to be one approach that could be used to monitor synergistic effects of noise and ototoxic agents. In addition, questionnaires or other forms of eHealth might be used to identify and monitor individuals who are high risk for hearing loss cause by synergistic effects. For example, a recently published article describes a questionnaire that assesses an individual's exposure to noise to identify possible synergistic effects (Griest-Hines , 2021). These measures are naturally set up for asynchronous or eHealth technology exchange, along with phone or email follow-up, which are still used in monitoring programs (Brungart , 2018; Ferrua , 2020).

Another solution for measuring synergistic effects may be the use of body worn sensors, also known as “wearables” or “hearables” when placed in the ear (Krumm, 2016a; Themann , 2019). Monitoring an individual's noise exposure is not a new concept as dosimeters are well-established in hearing conservation programs. However, limited literature exists on the use of wearables or hearables to detect harmful levels of environmental noise (Themann , 2019; Fischer , 2022). There are a few phone apps and wearables, developed in the last decade, that can measure noise levels (Leaffer , 2019; Themann , 2019; Crossley , 2021). Also, Davis (2019) describe a wearable with integrated hearing protection and recording system for dosimetry that can measure on-body and in-ear noise exposure levels, particularly for impulse noise from firearms.

Body worn sensors can be used to monitor hazardous chemicals, oxygen levels, toxicity, falls, and heart functioning (Duregger , 2015; Shen and Naeim, 2017; Ueberham and Schlink, 2018; Colozza , 2019; Leaffer , 2019; Ramezani , 2019; Phan, 2021), and an individual can be fit with multiple sensors. In a recent publication, investigators described a multipurpose wearable system capable of measuring both air particles for toxic agents and hazardous environmental noise levels, simultaneously (Leaffer , 2019). Researchers have gone as far as to speculate that wearables could, through geolocation of an individual, route individuals away from hazardous noise levels (Kepplinger , 2017), and it is possible that this could apply to toxic agents as well.

When selecting equipment for performing audiometric assessment via telehealth, there are several key elements to take into consideration. Audiological tools that are, or can be, controlled by a computer (PC-enabled) and are often easily configurable for telehealth applications (Krumm, 2016b). Peripherals that are portable and either use mobile smartphone technology or can be controlled by Bluetooth are also well-suited for telehealth applications. For example, using remote controlled desktop applications and a Bluetooth or PC-interfaced otoscope, tympanometer, OAE unit, and audiometer at the patient site, a provider can complete a full examination with assistance from a trained facilitator (Coco , 2020; Coco , 2021; Thai-Van , 2021). Depending on the needs of the program and the setting, technology solutions can be balanced based on portability, automation, internet bandwidth, personnel, and clinical needs (Bashshur , 2000; Krumm, 2016b).

Currently on the market, there are several audiology technology systems designed for mobile and/or telehealth applications that allow hearing tests to be collected outside of a sound booth. Examples include the PC-controlled KUDUwave audiometer by Emoyo, the iPad-based SHOEBOX audiometer, the hearTest application by hearX, a smartphone-based audiometer for Android devices, and the WAHTS tablet-based audiometer by Creare, Inc. These systems vary in their design and functionality, including the software and hardware. Nearly all these systems have screening, automated, and diagnostic testing capabilities with layperson-friendly design. An important consideration when choosing a telehealth system is to identify equipment that is user-friendly according to the end-user, whether that is a facilitator at a patient remote site or a patient during self-testing.

A telehealth cart system is another option (Bush and Sprang, 2019). Rather than use separate equipment that is especially designed for telehealth, a cart system is a single unit that integrates equipment for comprehensive audiometry services. For example, the Department of Veterans' Affairs uses a cart system for teleaudiology (Dennis , 2012; Dworsack-Dodge, 2013) that includes a video otoscope, PC-based audiometer, tympanometer, and hearing aid fitting system with real ear verification equipment that allows for hybrid telehealth service delivery. The telehealth cart is located at the patient site, and the hands-on aspects are managed by a trained facilitator. An audiologist connects remotely (via videoconferencing) from a separate site. The benefit of a cart system is that it integrates hardware and software in one unit, which can increase efficiency, although it can be costly; a comprehensive hearing telehealth cart can cost more than $20,000.

Cart-based telehealth systems are also used to provide remote care, including hearing services. In rural Alaska, geographical distance, population sparsity, and physician and specialist provider shortages challenged traditional healthcare service delivery and prompted one of the largest telehealth endeavors in the world, the AFHCAN (University of Alaska Statewide Health Programs, 2004). The result of this effort is a well-established comprehensive statewide telehealth network integrated into clinical practice. The AFHCAN system contains peripherals for several healthcare specialties. As it relates to audiologic care, this cart is equipped to provide video otoscopy, immittance, automated audiometry, and otoacoustic emissions screening. The AFHCAN system is predominantly used for asynchronous exchange of clinical data, where audiological information is collected, stored, and then sent to the audiologist for review. Cart-based systems, such as those mentioned, could be established in satellite or remote facilities to extend clinical services and provide exposure monitoring more easily. In research, cart-based telehealth systems could support enrollment for DCTs.

Extending the reach of audiological assessment and management often means providing services where audiometric sound treated rooms are not available. To obtain accurate thresholds outside of a sound booth, it is important to minimize ambient noise and to ensure that background noise does not impact the test signal. Excessive ambient noise is likely among the greatest threats to the validity of hearing testing in telehealth service delivery (Goehring , 2012; Monica , 2017; Ramkumar, 2020). To minimize the influence of noise, many tablet-based and wireless audiometry systems collect real-time noise measurements using a SLM or via ear level measurements to ensure valid testing (e.g., KUDUwave, hearTest, SHOEBOX). This is done by enabling re-testing of thresholds if ambient noise is too loud or alerting the tester to manually pause testing and adjust background noise. To address the issue of testing outside of a sound booth, audiological systems incorporate passive attenuation, such as thick supra-aural foam earcups and deeply inserted ear tips (e.g., Creare WAHTS and KUDUwave), and/or passive monitoring of ambient noise levels that notify or limit testing until the environment is suitable (Swanepoel , 2010; Swanepoel and Biagio, 2011; Swanepoel , 2014; Shojaeemend and Ayatollahi, 2018). Less widely used is active noise suppression, also known as noise-cancellation, although emerging research shows this strategy can yield valid thresholds in the presence of noise (Saliba , 2017). Several studies have validated aspects of manual and automated pure tone testing in a natural environment (e.g., a clinic waiting room or a school classroom) and found similar results when compared to testing in a sound booth (Swanepoel and Biagio, 2011; Meinke , 2017; Bastianelli , 2019; Serpanos , 2021). For example, the KUDUwave 5000 was shown to obtain 92% of thresholds within ±5 dB for participants with normal hearing in 40 dBA of background noise (Storey , 2014).

ANSI specifies maximum permissible noise levels in an audiometric test room (ANSI 3.1, 1999) and specifications for the performance of audiometric devices (ANSI 3.6, 2018), and the International Standards Organization (ISO 8253:1, 2010) specifies standards for audiometric testing internationally. Emerging technology also requires either CE certification for equipment used in the European Union or registration with the Food and Drug Administration (FDA) for use in the United States. To date, there is no separate ANSI standard for the performance of tablet-based audiometers. The SHOEBOX audiometer meets electroacoustic requirements for audiometric equipment in ANSI 3.6 and ANSI 3.1 for testing outside of a booth (Thompson , 2015; Rourke , 2016). SHOEBOX is also registered as a class II device by the FDA and Health Canada (SHOEBOX, 2022), which has implications for its use in clinic with respect to reimbursement. The KUDUwave audiometer is ANSI 3.6 and OSHA compliant, is FDA-approved as a type II screening and diagnostic audiometer, and is ISO 13485 and CE certified (KUDUwave, 2022). hearTest by hearX is CE and FDA compliant and meets IEC 60645-1 (pure tone testing).

Technology that incorporates techniques to attenuate, monitor, and/or suppress ambient noise is essential. This is particularly necessary as the definition of hearing loss as classified by the World Health Organization (WHO) is now a pure tone average of 20 dB hearing level (HL) or greater at 500, 1000, 2000, and 4000 Hz in the better ear (World Health Organization, 2021). This new WHO definition of mild hearing loss places greater emphasis on the need for accurate testing outside of a sound booth, where ambient noise could play a critical factor in obtaining valid hearing thresholds. Technology that uses both passive and active ambient noise management to achieve ANSI-standard testing in the field will be required for telehealth applications for assessment and monitoring of hearing to be successful.

A facilitator is a person at the patient site who is responsible for hands-on aspects of teleaudiology service delivery, such as placing the headphones on the patient and managing local technology. A recent scoping review (Coco , 2020) on teleaudiology patient-site facilitators identified that, across 82 included studies, there were 57 total distinct tasks that fell under facilitators' purview. Responsibilities varied depending on the audiology procedures provided. For example, in auditory brainstem response testing, the facilitator prepared the infant's skin for testing (Ramkumar , 2019). Facilitators were also responsible for general duties such as obtaining the client's consent (Crowell , 2011). Despite the range of tasks the facilitator is potentially responsible for, their training is not thoroughly described in much of the literature. In response to a need for a standardized training for facilitators, Coco (2021) developed and evaluated a multi-level training series that prepared community health workers to serve as patient-site facilitators in teleaudiology hearing aid service delivery. Future work may lead to greater availability of facilitator trainings, which may be particularly helpful for audiologists who, due to lack of experience, do not feel equipped to develop and carry out trainings themselves.

In teleaudiology-delivered ototoxicity and noise monitoring programs, as well as in large-scale clinical trials, a patient-site facilitator's duties may include ensuring data quality in assessments, calibrating equipment, and helping with data transfer. They may also help with recruiting and play a crucial role in patient/participant engagement. Facilitators' specific roles, responsibilities, and training needs may become more evident as work in this area increases.

Comprehensive audiometric assessments are often a crucial facet of noise and ototoxic exposure monitoring programs, as well as in research programs. However, numerous barriers, such as a global shortage of ear and hearing care professionals and lack of sound booths in rural areas, have limited the reach of these services, particularly when service delivery and data collection are limited to traditional face-to-face care. Telehealth provides an opportunity to increase access. In this special issue on clinical and investigational tools for measuring auditory outcomes, we present a summary of teleaudiology solutions, particularly for utilization in large (decentralized) clinical trials and for evaluation and monitoring of hearing loss from noise and ototoxic exposures.

There is well-documented evidence that telehealth is a valid approach for conducting comprehensive audiometric assessments. Studies have demonstrated that the use of telehealth in the provision of hearing healthcare services is comparable to face-to-face services under ideal conditions. However, as discussed in this article, telehealth typically involves testing outside of a sound booth, which can introduce challenges to obtaining a valid comprehensive assessment. Fortunately, advances in telehealth equipment are beginning to ameliorate many of the challenges (e.g., ambient noise) that arise when using telehealth to conduct a comprehensive audiometric assessment.

While the reliability and validity of telehealth in audiology is well-documented, there is less evidence to suggest there is widespread implementation into everyday clinic and research settings. Despite the potential advantages of telehealth during the recent Coronavirus (COVID-19) pandemic, there was mixed evidence on adoption of teleaudiology practices. Saunders and Roughley (2021) found that teleaudiology increased from 30% to 98%, while others found far less adoption of teleaudiology during COVID-19 (Parmar , 2022). Furthermore, many audiologists planned to return to face-to-face care when COVID-19 restrictions lifted (Saunders and Roughley, 2021). Barriers still exist, including adapting existing clinical and research infrastructure to a remote setup and obtaining appropriate training.

Implementation research can help improve the dissemination and adoption of teleaudiology in diverse, rural, and under-resourced areas and help scale clinical trials (Douglas , 2022). Future implementation-focused research in this area may involve identifying barriers and facilitators to adopting teleaudiology—including at patient/participant, provider, and organizational levels—and adapting evidence-based protocols based on the needs of a particular setting or population served. To achieve broader dissemination of evidence-based telehealth strategies, and thus achieve greater public health impact, telehealth research is needed in real-world settings and in collaboration with a range of stakeholders.

This invited paper provided an overview of telehealth applications for measuring auditory outcomes in clinical and research settings. A potential limitation is that the summary of work presented was not a systematic review, but rather a narrative overview based on authors' expertise and experience. With emerging technology and increased availability of telehealth solutions, there will likely be a need for formal systematic and scoping reviews of the technology, implementation, and use cases. This may be particularly true for the rapidly emerging field of telehealth in the identification and management of noise- or ototoxic exposure-induced hearing loss and related sequala (e.g., tinnitus), as well as implications of telehealth use in large-scale clinical trials.

The potential for telehealth applications in clinical and investigational assessments is significant. Telehealth applications in audiology do not need to be limited to audiometric evaluation and rehabilitation. We envision a world in which future potential telehealth applications in noise exposure monitoring include “hearable” technology used to monitor the environment and inform an individual when they have reached their “noise dose” for the day. For patients receiving ototoxic medications, we imagine a buffet of options to help monitor the effects of medication on their health, including hearables for continuous user-controlled hearing monitoring, combined with a smart watch to monitor blood oxygen levels, and other peripherals for important health metrics. For auditory outcomes in clinical trials, we see self-test and mobile cart-based technology as solutions for the collection of high-fidelity data in the hardest to reach places, without the need for sound treated rooms or in-person audiologists. Teleaudiology technology available today can be used to support investigators interested in establishing DCTs inclusive of auditory outcomes, such as studies evaluating the efficacy of pharmaceutical interventions for hearing loss.

It is an exciting time for telehealth applications for audiology. With renewed interest in the integration of telehealth solutions into clinical practice and the research setting and the rapid advancement of technology, the profession of audiology is well-positioned to extend clinical services into underserved regions, as well as support future research and scientific innovation.

The authors would like to thank the United States Department of Defense Hearing Center for Excellence for the invitation to submit this overview as part of the special issue “Noise-induced Hearing Disorders: Clinical and Investigational Tools.” The authors have no conflicts of interest to declare. The content of this paper does not represent the views of the United States government or the Department of Veteran Affairs.

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