Mobile Health School Screening and Telemedicine Referral to Improve Access to Specialty Care in Rural Alaska: Integrating Mixed Methods Data to Contextualize Trial Outcomes.

OBJECTIVES: To understand factors associated with outcomes in a cluster-randomized controlled trial that evaluated a telemedicine specialty referral intervention for school hearing screenings in 15 rural Alaskan communities. DESIGN: Hearing Norton Sound was a mixed methods cluster-randomized controlled trial that compared a telemedicine specialty referral pathway (intervention) to a standard primary care referral pathway (control) for school hearing screenings. As a mixed methods trial, both quantitative and qualitative data were collected, analyzed, and integrated. Main trial results are published elsewhere, but integration of community-specific quantitative outcomes and qualitative results have not yet been reported. The constant comparative method was used to analyze qualitative data from semistructured interviews with six stakeholder groups across all 15 communities. Descriptive statistics were used to describe community-specific proportions of follow-up in both trial years. Qualitative and quantitative results were integrated to reveal relationships between contextual factors and follow-up outcomes across communities. RESULTS: The Hearing Norton Sound trial enrolled 1481 children from October 2017 to March 2019, with a total of 790 children requiring referral. Of the children who referred in the telemedicine specialty referral pathway communities (intervention), 68.5% received follow-up (268/391), compared to 32.1% (128/399) in primary care referral communities (control)(previously reported). When broken down by community, the mean proportion receiving follow-up was 75.26% (SD 22.5) and 37.9% (SD 11.4) for the telemedicine specialty referral communities and primary care referral communities, respectively. For qualitative data collection, semistructured interviews were conducted with 101 individuals between December 2018 and August 2019. Six stakeholder groups participated: elders (n = 14), parents (n = 25), children (n = 11), teachers/school staff (n = 18), principals (n = 6), and healthcare providers/clinic staff (n = 27). Six overall factors related to the outcomes of the telemedicine specialty referral pathway emerged during analysis: clinic capacity, personnel ownership and engagement, scheduling, telemedicine equipment/processes, communication, and awareness of the need for follow-up. We integrated these factors with the community-specific follow-up percentages and found associations for four of the six qualitative factors: clinic capacity, personnel ownership and engagement, communication, and awareness. An association was not seen for scheduling and telemedicine equipment/processes, which had variable relationships with the follow-up outcome. CONCLUSIONS: The Hearing Norton Sound trial demonstrated that a telemedicine specialty referral pathway can close the gap on children lost to follow up after school hearing screening. As a whole, the intervention profoundly increased the proportion of children receiving follow-up, but there was variability in outcomes within and between communities. To understand this variability, we analyzed community-specific intervention outcomes alongside community member feedback on factors related to the intervention. We identified four key factors that contributed to the success of the intervention. Attention to these factors will be essential to successful adaptation and implementation of this telemedicine specialty referral intervention and other similar interventions in future work in rural Alaska and beyond.

Prevalence of Childhood Hearing Loss in Rural Alaska.

OBJECTIVES: Childhood hearing loss has well-known lifelong consequences. Certain rural populations are at higher risk for infection-related hearing loss. For Alaska Native children, historical data on hearing loss prevalence suggest a higher burden of infection-related hearing loss, but updated prevalence data are urgently needed in this high-risk population. DESIGN: Hearing data were collected as part of two school-based cluster-randomized trials in 15 communities in rural northwest Alaska over two academic years (2017-2019). All enrolled children from preschool to 12th grade were eligible. Pure-tone thresholds were obtained using standard audiometry and conditioned play when indicated. The analysis included the first available audiometric assessment for each child (n = 1634 participants, 3 to 21 years), except for the high-frequency analysis, which was limited to year 2 when higher frequencies were collected. Multiple imputation was used to quantify the prevalence of hearing loss in younger children, where missing data were more frequent due to the need for behavioral responses. Hearing loss in either ear was evaluated using both the former World Health Organization (WHO) definition (pure-tone average [PTA] > 25 dB) and the new WHO definition (PTA ≥ 20 dB), which was published after the study. Analyses with the new definition were limited to children 7 years and older due to incomplete data obtained on younger children at lower thresholds. RESULTS: The overall prevalence of hearing loss (PTA > 25 dB; 0.5, 1, 2, 4 kHz) was 10.5% (95% confidence interval [CI], 8.9 to 12.1). Hearing loss was predominately mild (PTA >25 to 40 dB; 8.9%, 95% CI, 7.4 to 10.5). The prevalence of unilateral hearing loss was 7.7% (95% CI, 6.3 to 9.0). Conductive hearing loss (air-bone gap of ≥ 10 dB) was the most common hearing loss type (9.1%, 95% CI, 7.6 to 10.7). Stratified by age, hearing loss (PTA >25 dB) was more common in children 3 to 6 years (14.9%, 95% CI, 11.4 to 18.5) compared to children 7 years and older (8.7%, 95% CI, 7.1 to 10.4). In children 7 years and older, the new WHO definition increased the prevalence of hearing loss to 23.4% (95% CI, 21.0 to 25.8) compared to the former definition (8.7%, 95% CI, 7.1 to 10.4). Middle ear disease prevalence was 17.6% (95% CI, 15.7 to 19.4) and was higher in younger children (23.6%, 95% CI, 19.7 to 27.6) compared to older children (15.2%, 95% CI, 13.2 to 17.3). High-frequency hearing loss (4, 6, 8kHz) was present in 20.5% (95% CI, 18.4 to 22.7 [PTA >25 dB]) of all children and 22.8% (95% CI, 20.3 to 25.3 [PTA >25 dB]) and 29.7% (95% CI, 27.0 to 32.4 [PTA ≥ 20 dB]) of children 7 years and older (limited to year 2). CONCLUSIONS: This analysis represents the first prevalence study on childhood hearing loss in Alaska in over 60 years and is the largest cohort with hearing data ever collected in rural Alaska. Our results highlight that hearing loss continues to be common in rural Alaska Native children, with middle ear disease more prevalent in younger children and high-frequency hearing loss more prevalent with increasing age. Prevention efforts may benefit from managing hearing loss type by age. Lastly, continued research is needed on the impact of the new WHO definition of hearing loss on field studies.

A Hybrid Deep Learning Approach to Identify Preventable Childhood Hearing Loss.

OBJECTIVE: Childhood hearing loss has well-known, lifelong consequences. Infection-related hearing loss disproportionately affects underserved communities yet can be prevented with early identification and treatment. This study evaluates the utility of machine learning in automating tympanogram classifications of the middle ear to facilitate layperson-guided tympanometry in resource-constrained communities. DESIGN: Diagnostic performance of a hybrid deep learning model for classifying narrow-band tympanometry tracings was evaluated. Using 10-fold cross-validation, a machine learning model was trained and evaluated on 4810 pairs of tympanometry tracings acquired by an audiologist and layperson. The model was trained to classify tracings into types A (normal), B (effusion or perforation), and C (retraction), with the audiologist interpretation serving as reference standard. Tympanometry data were collected from 1635 children from October 10, 2017, to March 28, 2019, from two previous cluster-randomized hearing screening trials (NCT03309553, NCT03662256). Participants were school-aged children from an underserved population in rural Alaska with a high prevalence of infection-related hearing loss. Two-level classification performance statistics were calculated by treating type A as pass and types B and C as refer. RESULTS: For layperson-acquired data, the machine-learning model achieved a sensitivity of 95.2% (93.3, 97.1), specificity of 92.3% (91.5, 93.1), and area under curve of 0.968 (0.955, 0.978). The model's sensitivity was greater than that of the tympanometer's built-in classifier [79.2% (75.5, 82.8)] and a decision tree based on clinically recommended normative values [56.9% (52.4, 61.3)]. For audiologist-acquired data, the model achieved a higher AUC of 0.987 (0.980, 0.993), had an equivalent sensitivity of 95.2 (93.3, 97.1), and a higher specificity of 97.7 (97.3, 98.2). CONCLUSIONS: Machine learning can detect middle ear disease with comparable performance to an audiologist using tympanograms acquired either by an audiologist or a layperson. Automated classification enables the use of layperson-guided tympanometry in hearing screening programs in rural and underserved communities, where early detection of treatable pathology in children is crucial to prevent the lifelong adverse effects of childhood hearing loss.

Potential Clinical and Economic Outcomes of Over-the-Counter Hearing Aids in the US.

Importance: Over-the-counter (OTC) hearing aids are now available in the US; however, their clinical and economic outcomes are unknown. Objective: To project the clinical and economic outcomes of traditional hearing aid provision compared with OTC hearing aid provision. Design, Setting, and Participants: This cost-effectiveness analysis used a previously validated decision model of hearing loss (HL) to simulate US adults aged 40 years and older across their lifetime in US primary care offices who experienced yearly probabilities of acquiring HL (0.1%-10.4%), worsening of their HL, and traditional hearing aid uptake (0.5%-8.1%/y at a fixed uptake cost of $3690) and utility benefits (0.11 additional utils/y). For OTC hearing aid provision, persons with perceived mild to moderate HL experienced increased OTC hearing aid uptake (1%-16%/y) based on estimates of time to first HL diagnosis. In the base case, OTC hearing aid utility benefits ranged from 0.05 to 0.11 additional utils/y (45%-100% of traditional hearing aids), and costs were $200 to $1400 (5%-38% of traditional hearing aids). Distributions were assigned to parameters to conduct probabilistic uncertainty analysis. Intervention: Provision of OTC hearing aids, at increased uptake rates, across a range of effectiveness and costs. Main Outcomes and Measures: Lifetime undiscounted and discounted (3%/y) costs and quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs). Results: Traditional hearing aid provision resulted in 18.162 QALYs, compared with 18.162 to 18.186 for OTC hearing aids varying with OTC hearing aid utility benefit (45%-100% that of traditional hearing aids). Provision of OTC hearing aids was associated with greater lifetime discounted costs by $70 to $200 along with OTC device cost ($200-$1000/pair; 5%-38% traditional hearing aid cost) due to increased hearing aid uptake. Provision of OTC hearing aids was considered cost-effective (ICER<$100 000/QALY) if the OTC utility benefit was 0.06 or greater (55% of the traditional hearing aid effectiveness). In probabilistic uncertainty analysis, OTC hearing aid provision was cost-effective in 53% of simulations. Conclusions and Relevance: In this cost-effectiveness analysis, provision of OTC hearing aids was associated with greater uptake of hearing intervention and was cost-effective over a range of prices so long as OTC hearing aids were greater than 55% as beneficial to patient quality of life as traditional hearing aids.

Telemedicine Referral to Improve Access to Specialty Care for Preschool Children in Rural Alaska: A Cluster-Randomized Controlled Trial.

OBJECTIVES: Preschool programs provide essential preventive services, such as hearing screening, but in rural regions, limited access to specialists and loss to follow-up compound rural health disparities. We conducted a parallel-arm cluster-randomized controlled trial to evaluate telemedicine specialty referral for preschool hearing screening. The goal of this trial was to improve timely identification and treatment of early childhood infection-related hearing loss, a preventable condition with lifelong implications. We hypothesized that telemedicine specialty referral would improve time to follow-up and the number of children receiving follow-up compared with the standard primary care referral. DESIGN: We conducted a cluster-randomized controlled trial in K-12 schools in 15 communities over two academic years. Community randomization occurred within four strata using location and school size. In the second academic year (2018-2019), an ancillary trial was performed in the 14 communities that had preschools to compare telemedicine specialty referral (intervention) to standard primary care referral (comparison) for preschool hearing screening. Randomization of communities from the main trial was used for this ancillary trial. All children enrolled in preschool were eligible. Masking was not possible because of timing in the second year of the main trial, but referral assignment was not openly disclosed. Study team members and school staff were masked throughout data collection, and statisticians were blinded to allocation during analysis. Preschool screening occurred once, and children who were referred for possible hearing loss or ear disease were monitored for follow-up for 9 months from the screening date. The primary outcome was time to ear/hearing-related follow-up from the date of screening. The secondary outcome was any ear/hearing follow-up from screening to 9 months. Analyses were conducted using an intention-to-treat approach. RESULTS: A total of 153 children were screened between September 2018 and March 2019. Of the 14 communities, 8 were assigned to the telemedicine specialty referral pathway (90 children), and 6 to the standard primary care referral pathway (63 children). Seventy-one children (46.4%) were referred for follow-up: 39 (43.3%) in the telemedicine specialty referral communities and 32 (50.8%) in the standard primary care referral communities. Of children referred, 30 (76.9%) children in telemedicine specialty referral communities and 16 (50.0%) children in standard primary care referral communities received follow-up within 9 months (Risk Ratio = 1.57; 95% confidence interval [CI], 1.22 to 2.01). Among children who received follow-up, median time to follow-up was 28 days (interquartile range [IQR]: 15 to 71) in telemedicine specialty referral communities compared with 85 days (IQR: 26 to 129) in standard primary care referral communities. Mean time to follow-up for all referred children was 4.5 (event time ratio = 4.5; 95% CI, 1.8 to 11.4; p = 0.045) times faster in telemedicine specialty referral communities compared with standard primary care referral communities in the 9-month follow-up time frame. CONCLUSIONS: Telemedicine specialty referral significantly improved follow-up and reduced time to follow-up after preschool hearing screening in rural Alaska. Telemedicine referrals could extend to other preventive school-based services to improve access to specialty care for rural preschool children.

Changing the Paradigm for School Hearing Screening Globally: Evaluation of Screening Protocols From Two Randomized Trials in Rural Alaska.

OBJECTIVES: Diagnostic accuracy was evaluated for various screening tools, including mobile health (mHealth) pure-tone screening, tympanometry, distortion product otoacoustic emissions (DPOAE), and inclusion of high frequencies to determine the most accurate screening protocol for identifying children with hearing loss in rural Alaska where the prevalence of middle ear disease is high. DESIGN: Hearing screening data were collected as part of two cluster randomized trials conducted in 15 communities in rural northwest Alaska. All children enrolled in school from preschool to 12th grade were eligible. Analysis was limited to data collected 2018 to 2019 (n = 1449), when both trials were running and measurement of high frequencies were included in the protocols. Analyses included estimates of diagnostic accuracy for each screening tool, as well as exploring performance by age and grade. Multiple imputation was used to assess diagnostic accuracy in younger children, where missing data were more prevalent due to requirements for conditioned responses. The audiometric reference standard included otoscopy, tympanometry, and high frequencies to ensure detection of infection-related and noise-induced hearing loss. RESULTS: Both the mHealth pure-tone screen and DPOAE screen performed better when tympanometry was added to the protocol (increase in sensitivity of 19.9%, 95% Confidence Interval (CI): 15.9 to 24.1 for mHealth screen, 17.9%, 95% CI: 14.0 to 21.8 for high-frequency mHealth screen, and 10.4%, 95% CI: 7.5 to 13.9 for DPOAE). The addition of 6 kHz to the mHealth pure-tone screen provided an 8.7 percentage point improvement in sensitivity (95% CI: 6.5 to 11.3). Completeness of data for both the reference standard and the mHealth screening tool differed substantially by age, due to difficulty with behavioral testing in young children. By age 7, children were able to complete behavioral testing, and data indicated that high-frequency mHealth pure-tone screen with tympanometry was the superior tool for children 7 years and older. For children 3 to 6 years of age, DPOAE plus tympanometry performed the best, both for complete data and multiply imputed data, which better approximates accuracy for children with missing data. CONCLUSIONS: This study directly evaluated pure-tone, DPOAE, and tympanometry tools as part of school hearing screening in rural Alaskan children (3 to 18+ years). Results from this study indicate that tympanometry is a key component in the hearing screening protocol, particularly in environments with higher prevalence of infection-related hearing loss. DPOAE is the preferred hearing screening tool when evaluating children younger than 7 years of age (below 2nd grade in the United States) due to the frequency of missing data with behavioral testing in this age group. For children 7 years and older, the addition of high frequencies to pure-tone screening increased the accuracy of screening, likely due to improved identification of hearing loss from noise exposure. The lack of a consistent reference standard in the literature makes comparing across studies challenging. In our study with a reference standard inclusive of otoscopy, tympanometry, and high frequencies, less than ideal sensitivities were found even for the most sensitive screening protocols, suggesting more investigation is necessary to ensure screening programs are appropriately identifying noise- and infection-related hearing loss in rural, low-resource settings.

Community Perspectives on Hearing Loss in Rural Alaska.

OBJECTIVES: The aim of this study is to present an explanatory model of hearing loss in the Bering Strait region of Alaska in order to contextualize the results of a cluster randomized trial and propose implications for regional hearing-related health care. DESIGN: To promote ecological validity, or the generalizability of trial findings to real world experiences, qualitative methods (focus groups and interviews) were used within a mixed methods cluster randomized trial evaluating school hearing screening and follow-up processes in 15 communities in the Bering Strait region of Alaska. Focus groups were held between April and August 2017, and semistructured interviews were conducted between December 2018 and August 2019. Convenience sampling was used for six of the 11 focus groups to capture broad community feedback. Purposive sampling was used for the remaining five focus groups and for all interviews to capture a variety of experiences with hearing loss. Audio recordings of focus groups and interviews were transcribed, and both notes and transcripts were deidentified. All notes and transcripts were included in the analysis. The constant comparative method was used to develop a codebook by iteratively moving between transcripts and preliminary themes. Researchers then used this codebook to code data from all focus groups and interviews using qualitative analysis software (NVIVO 12, QSR International) and conducted thematic analyses to distill the findings presented in this article. RESULTS: Participants in focus groups (n = 116) and interviews (n = 101) shared perspectives in three domains: etiology, impact, and treatment of hearing loss. Regarding etiology, participants emphasized noise-induced hearing loss but also discussed infection-related hearing loss and various causes of ear infections. Participants described the impact of hearing loss on subsistence activities, while also detailing social, academic, and economic consequences. Participants described burdensome treatment pathways that are repetitive and often travel and time intensive. Communication breakdowns within these pathways were also described. Some participants spoke positively of increased access via onsite hearing health care services in "field clinics" as well as via telemedicine services. Others described weaknesses in these processes (infrequent field clinics and communication delays in telemedicine care pathways). Participants also described home remedies and stigma surrounding the treatment for hearing loss. CONCLUSIONS: Patient-centered health care requires an understanding of context. Explanatory models of illness are context-specific ways in which patients and their networks perceive and describe the experience of an illness or disability. In this study, we documented explanatory models of hearing loss to foster ecological validity and better understand the relevance of research findings to real-life hearing-related experiences. These findings suggest several areas that should be addressed in future implementation of hearing health care interventions elsewhere in rural Alaska, including management of repetitious treatments, awareness of infection-mediated hearing loss, mistrust, and communication breakdowns. For hearing-related health care in this region, these findings suggest localized recommendations for approaches for prevention and treatment. For community-based hearing research, this study offers an example of how qualitative methods can be used to generate ecologically valid (i.e., contextually grounded) findings.

Hearing-related quality of life in children and adolescents in rural Alaska.

Objective: This study evaluated the Hearing Environments and Reflection on Quality of Life (HEAR-QL) questionnaire in rural Alaska, including an addendum crafted through community feedback to reflect the local context. The objectives were to assess whether HEAR-QL score was inversely correlated with hearing loss and middle ear disease in an Alaska Native population. Methods: The HEAR-QL questionnaires for children and adolescents were administered as part of a cluster randomized trial in rural Alaska from 2017 to 2019. Enrolled students completed an audiometric evaluation and HEAR-QL questionnaire on the same day. A cross-sectional evaluation of questionnaire data was utilized. Results: A total of 733 children (ages 7-12 years) and 440 adolescents (ages ≥13 years) completed the questionnaire. Median HEAR-QL scores were similar among children with and without hearing loss (Kruskal-Wallis, p = .39); however, adolescent HEAR-QL scores significantly decreased with increasing hearing loss (p < .001). Median HEAR-QL scores were significantly lower in both children (p = .02) and adolescents (p < .001) with middle ear disease compared with those without. In both children and adolescents, the addendum scores were strongly correlated with total HEAR-QL score (ρSpearman = 0.72 and 0.69, respectively). Conclusions: The expected negative association between hearing loss and HEAR-QL score was observed in adolescents. However, there was significant variability that could not be explained by hearing loss, and further investigation is warranted. The expected negative association was not observed in children. HEAR-QL scores were associated with middle ear disease in both children and adolescents, making it potentially valuable in populations where the prevalence of ear infections is high. Level of Evidence: Level 2 Clinicaltrials.gov registration numbers: NCT03309553.

The Impact of Hearing Loss and Its Treatment on Health-Related Quality of Life Utility: a Systematic Review with Meta-analysis.

BACKGROUND: Hearing loss significantly impacts health-related quality of life (QoL), yet the effects of current treatments on QoL utility remain uncertain. Our objective was to describe the impact of untreated and treated hearing loss on QoL utility to inform hearing healthcare policy. METHODS: We searched databases for articles published through 02/01/2021. Two independent reviewers screened for articles that reported elicitation of general QoL utility values for untreated and treated hearing loss health states. We extracted data and quality indicators from 62 studies that met the inclusion criteria. RESULTS: Included studies predominately used observational pre/post designs (61%), evaluated unilateral cochlear implantation (65%), administered the Health Utilities Index 3 (HUI3; 71%), and were conducted in Europe and North America (84%). In general, treatment of hearing loss improved post-treatment QoL utility when measured by most methods except the Euro-QoL 5 dimension (EQ-5D). In meta-analysis, hearing aids for adult mild-to-moderate hearing loss compared to no treatment significantly improved HUI3-estimated QoL utility (3 studies; mean change=0.11; 95% confidence interval (CI): 0.07 to 0.14) but did not impact EQ-5D-estimated QoL (3 studies; mean change=0.0; 95% CI: -0.03 to 0.04). Cochlear implants improved adult QoL utility 1-year post-implantation when measured by the HUI3 (7 studies; mean change=0.17; 95% CI: 0.11 to 0.23); however, pediatric VAS-estimated QoL utility was non-significant (4 studies; mean change=0.12; 95% CI: -0.02 to 0.25). The quality of included studies was limited by failure to report missingness of data and low survey response rates. Our study was limited by heterogeneous study populations and designs. FINDINGS: Treatment of hearing loss significantly improves QoL utility, and the HUI3 and VAS were most sensitive to improvements in hearing. Improved access to hearing healthcare should be prioritized. SYSTEMATIC REVIEW REGISTRATION: PROSPERO: CRD42021253314.

Environmental Factors for Hearing Loss and Middle Ear Disease in Alaska Native Children and Adolescents: A Cross-Sectional Analysis from a Cluster Randomized Trial.

OBJECTIVES: Infection-related childhood hearing loss is one of the few preventable chronic health conditions that can affect a child's lifelong trajectory. This study sought to quantify relationships between infection-mediated hearing loss and middle ear disease and environmental factors, such as exposure to wood smoke, cigarette smoke, household crowding, and lack of access to plumbed (running) water, in a northwest region of rural Alaska. DESIGN: This study is a cross-sectional analysis to estimate environmental factors of infection-related hearing loss in children aged 3 to 21 years. School hearing screenings were performed as part of two cluster randomized trials in rural Alaska over two academic years (2017-2018 and 2018-2019). The first available screening for each child was used for this analysis. Sociodemographic questionnaires were completed by parents/guardians upon entry into the study. Multivariable regression was performed to estimate prevalence differences and prevalence ratios (PR). A priori knowledge about the prevalence of middle ear disease and the difficulty inherent in obtaining objective hearing loss data in younger children led to analysis of children by age (3 to 6 years versus 7 years and older) and a separate multiple imputation sensitivity analysis for pure-tone average (PTA)-based infection-related hearing loss measures. RESULTS: A total of 1634 children participated. Hearing loss was present in 11.1% of children sampled based on otoacoustic emission as the primary indicator of hearing loss and was not associated with exposure to cigarette smoke (PR = 1.07; 95% confidence interval [CI], 0.48 to 2.38), use of a wood-burning stove (PR = 0.85; 95% CI, 0.55 to 1.32), number of persons living in the household (PR = 1.06; 95% CI, 0.97 to 1.16), or lack of access to running water (PR = 1.38; 95% CI, 0.80 to 2.39). Using PTA as a secondary indicator of hearing loss also showed no association with environmental factors. Middle ear disease was present in 17.4% of children. There was a higher prevalence of middle ear disease in homes without running water versus those with access to running water (PR = 1.53; 95% CI, 1.03 to 2.27). There was little evidence to support any cumulative effects of environmental factors. Heterogeneity of effect models by age found sample prevalence of hearing loss higher for children aged 3 to 6 years (12.2%; 95% CI, 9.3 to 15.7) compared to children 7 years and older (10.6%; 95% CI, 8.9 to 2.6), as well as for sample prevalence of middle ear disease (22.7%; 95% CI, 18.9 to 26.9 and 15.3%; 95% CI, 13.3 to 17.5, respectively). CONCLUSIONS: Lack of access to running water in the home was associated with increased prevalence of middle ear disease in this rural, Alaska Native population, particularly among younger children (aged 3 to 6 years). There was little evidence in this study that cigarette smoke, wood-burning stoves, and greater numbers of persons in the household were associated with infection-mediated hearing loss or middle ear disease. Future research with larger sample sizes and more sensitive measures of environmental exposure is necessary to further evaluate these relationships. Children who live in homes without access to running water may benefit from earlier and more frequent hearing health visits.

Model-Projected Cost-Effectiveness of Adult Hearing Screening in the USA.

BACKGROUND: While 60% of older adults have hearing loss (HL), the majority have never had their hearing tested. OBJECTIVE: We sought to estimate long-term clinical and economic effects of alternative adult hearing screening schedules in the USA. DESIGN: Model-based cost-effectiveness analysis simulating Current Detection (CD) and linkage of persons with HL to hearing healthcare, compared to alternative screening schedules varying by age at first screen (45 to 75 years) and screening frequency (every 1 or 5 years). Simulated persons experience yearly age- and sex-specific probabilities of acquiring HL, and subsequent hearing aid uptake (0.5-8%/year) and discontinuation (13-4%). Quality-adjusted life-years (QALYs) were estimated according to hearing level and treatment status. Costs from a health system perspective include screening ($30-120; 2020 USD), HL diagnosis ($300), and hearing aid devices ($3690 year 1, $910/subsequent year). Data sources were published estimates from NHANES and clinical trials of adult hearing screening. PARTICIPANTS: Forty-year-old persons in US primary care across their lifetime. INTERVENTION: Alternative screening schedules that increase baseline probabilities of hearing aid uptake (base-case 1.62-fold; range 1.05-2.25-fold). MAIN MEASURES: Lifetime undiscounted and discounted (3%/year) costs and QALYs and incremental cost-effectiveness ratios (ICERs). KEY RESULTS: CD resulted in 1.20 average person-years of hearing aid use compared to 1.27-1.68 with the screening schedules. Lifetime total per-person undiscounted costs were $3300 for CD and ranged from $3630 for 5-yearly screening beginning at age 75 to $6490 for yearly screening beginning at age 45. In cost-effectiveness analysis, yearly screening beginning at ages 75, 65, and 55 years had ICERs of $39,100/QALY, $48,900/QALY, and $96,900/QALY, respectively. Results were most sensitive to variations in hearing aid utility benefit and screening effectiveness. LIMITATION: Input uncertainty around screening effectiveness. CONCLUSIONS: We project that yearly hearing screening beginning at age 55+ is cost-effective by US standards.

Estimated Monetary Value of Future Research Clarifying Uncertainties Around the Optimal Adult Hearing Screening Schedule.

Importance: Adult hearing screening is not routinely performed, and most individuals with hearing loss (HL) have never had their hearing tested as adults. Objective: To project the monetary value of future research clarifying uncertainties around the optimal adult hearing screening schedule. Design, Setting, and Participants: In this economic evaluation, a validated decision model of HL (DeciBHAL-US: Decision model of the Burden of Hearing loss Across the Lifespan) was used to simulate current detection and treatment of HL vs hearing screening schedules. Key model inputs included HL incidence (0.06%-10.42%/y), hearing aid uptake (0.54%-8.14%/y), screening effectiveness (1.62 × hearing aid uptake), utility benefits of hearing aids (+0.11), and hearing aid device costs ($3690). Distributions to model parameters for probabilistic uncertainty analysis were assigned. The expected value of perfect information (EVPI) and expected value of partial perfect information (EVPPI) using a willingness to pay of $100 000 per quality-adjusted life-year (QALY) was estimated. The EVPI and EVPPI estimate the upper bound of the dollar value of future research. This study was based on 40-year-old persons over their remaining lifetimes in a US primary care setting. Exposures: Screening schedules beginning at ages 45, 55, 65, and 75 years, and frequencies of every 1 or 5 years. Main Outcomes and Measures: The main outcomes were QALYs and costs (2020 US dollars) from a health system perspective. Results: The average incremental cost-effectiveness ratio for yearly screening beginning at ages 55 to 75 years ranged from $39 200 to $80 200/QALY. Yearly screening beginning at age 55 years was the optimal screening schedule in 38% of probabilistic uncertainty analysis simulations. The population EVPI, or value of reducing all uncertainty, was $8.2 to $12.6 billion varying with willingness to pay and the EVPPI, or value of reducing all screening effectiveness uncertainty, was $2.4 billion. Conclusions and Relevance: In this economic evaluation of US adult hearing screening, large uncertainty around the optimal adult hearing screening schedule was identified. Future research on hearing screening has a high potential value so is likely justified.

The prevalence of Post-Ebola Syndrome hearing loss, Sierra Leone.

BACKGROUND: Globally, hearing loss is the second leading cause of disability, affecting approximately 18.7% of the world's population. However, the burden of hearing loss is unequally distributed, with the majority of affected individuals located in Asia or Sub-Saharan Africa. Following the 2014 West African Ebola Outbreak, disease survivors began to describe hearing loss as part of the constellation of symptoms known as Post-Ebola Syndrome. The goal of this study was to more fully characterize hearing loss among Ebola Virus Disease (EVD) survivors. METHODOLOGY AND PRINCIPAL FINDINGS: EVD survivors and their household contacts were recruited (n = 1,12) from Eastern Sierra Leone. Each individual completed a symptom questionnaire, physical exam, and a two-step audiometry process measuring both air and bone conduction thresholds. In comparison to contacts, EVD survivors were more likely to have complaints or abnormal findings affecting every organ system. A significantly greater percentage of EVD survivors were found to have hearing loss in comparison to contacts (23% vs. 9%, p < 0.001). Additionally, survivors were more likely to have bilateral hearing loss of a mixed etiology. Logistic regression revealed that the presence of any symptoms of middle or inner ear (p < 0.001), eye (p = 0.005), psychiatric (p = 0.019), and nervous system (p = 0.037) increased the odds of developing hearing loss. CONCLUSIONS AND SIGNIFICANCE: This study is the first to use an objective and standardized measurement to report hearing loss among EVD survivors in a clinically meaningful manner. In this study it was found that greater than 1/5th of EVD survivors develop hearing loss. The association between hearing impairment and symptoms affecting the eye and nervous system may indicate a similar mechanism of pathogenesis, which should be investigated further. Due to the quality of life and socioeconomic detriments associated with untreated hearing loss, a greater emphasis must be placed on understanding and mitigating hearing loss following survival to aid in economic recovery following infectious disease epidemics.

Expanding Clinical Trials Designs to Extend Equitable Hearing Care.

Clinical trials are critically important to translate scientific innovations into clinical practice. Hearing healthcare depends on this translational approach to improve outcomes and quality of life. Across the spectrum of healthcare, there is a lack of diverse participation in clinical trials, a failure to recruit and retain underrepresented and underserved populations, and an absence of rigorous dissemination and implementation of novel research to broader populations. The field of hearing healthcare research would benefit from expanding the types and designs of clinical trials that extend hearing healthcare and novel interventions to diverse populations, as well as emphasizing trials that evaluate factors influencing how that care can be delivered effectively. This article explores the following: (1) the role, value, and design types of clinical trials (randomized controlled, cluster randomized, stepped wedge, and mixed methods) to address health equity; (2) the importance of integrating community and stakeholder involvement; and (3) dissemination and implementation frameworks and designs for clinical trials (hybrid trial designs). By adopting a broader range of clinical trial designs, hearing healthcare researchers may be able to extend scientific discoveries to a more diverse population.

Validation of the Decision model of the Burden of Hearing loss Across the Lifespan (DeciBHAL) in Chile, India, and Nigeria.

Background: There is no published decision model for informing hearing health care resource allocation across the lifespan in low- and middle-income countries. We sought to validate the Decision model of the Burden of Hearing loss Across the Lifespan International (DeciBHAL-I) in Chile, India, and Nigeria. Methods: DeciBHAL-I simulates bilateral sensorineural hearing loss (SNHL) and conductive hearing loss (CHL) acquisition, SNHL progression, and hearing loss treatment. To inform model inputs, we identified setting-specific estimates including SNHL prevalence from the Global Burden of Disease (GBD) studies, acute otitis media (AOM) incidence and prevalence of otitis-media related CHL from a systematic review, and setting-specific pediatric and adult hearing aid use prevalence. We considered a coefficient of variance root mean square error (CV-RMSE) of ≤15% to indicate good model fit. Findings: The model-estimated prevalence of bilateral SNHL closely matched GBD estimates, (CV-RMSEs: 3.2-7.4%). Age-specific AOM incidences from DeciBHAL-I also achieved good fit (CV-RMSEs=5.0-7.5%). Model-projected chronic suppurative otitis media prevalence (1.5% in Chile, 4.9% in India, and 3.4% in Nigeria) was consistent with setting-specific estimates, and the incidence of otitis media-related CHL was calibrated to attain adequate model fit. DeciBHAL-projected adult hearing aid use in Chile (3.2-19.7% ages 65-85 years) was within the 95% confidence intervals of published estimates. Adult hearing aid prevalence from the model in India was 1.4-2.3%, and 1.1-1.3% in Nigeria, consistent with literature-based and expert estimates. Interpretation: DeciBHAL-I reasonably simulates hearing loss natural history, detection, and treatment in Chile, India, and Nigeria. Future cost-effectiveness analyses might use DeciBHAL-I to inform global hearing health policy. Funding: National Institutes of Health (3UL1-TR002553-03S3 and F30 DC019846).

Mobile health school screening and telemedicine referral to improve access to specialty care in rural Alaska: a cluster- randomised controlled trial.

BACKGROUND: School-based programmes, including hearing screening, provide essential preventive services for rural children. However, minimal evidence on screening methodologies, loss to follow-up, and scarcity of specialists for subsequent care compound rural health disparities. We hypothesised telemedicine specialty referral would improve time to follow-up for school hearing screening compared with standard primary care referral. METHODS: In this cluster-randomised controlled trial conducted in 15 rural Alaskan communities, USA, we randomised communities to telemedicine specialty referral (intervention) or standard primary care referral (control) for school hearing screening. All children (K-12; aged 4-21 years) enrolled in Bering Straight School District were eligible. Community randomisation occurred within four strata using location and school size. Participants were masked to group allocation until screening day, and assessors were masked throughout data collection. Screening occurred annually, and children who screened positive for possible hearing loss or ear disease were monitored for 9 months from the screening date for follow-up. Primary outcome was the time to follow-up after a positive hearing screen; analysis was by intention to treat. The trial was registered with ClinicalTrials.gov, NCT03309553. FINDINGS: We recruited participants between Oct 10, 2017, and March 28, 2019. 15 communities were randomised: eight (750 children) to telemedicine referral and seven (731 children) to primary care referral. 790 (53·3%) of 1481 children screened positive in at least one study year: 391 (52∤1%) in the telemedicine referral communities and 399 (50∤4%) in the primary care referral communities. Of children referred, 268 (68·5%) in the telemedicine referral communities and 128 (32·1%) in primary care referral communities received follow-up within 9 months. Among children who received follow-up, mean time to follow-up was 41·5 days (SD 55·7) in the telemedicine referral communities and 92·0 days (75·8) in the primary care referral communities (adjusted event-time ratio 17·6 [95% CI 6·8-45·3] for all referred children). There were no adverse events. INTERPRETATION: Telemedicine specialty referral significantly improved the time to follow-up after hearing screening in Alaska. Telemedicine might apply to other preventive school-based services to improve access to specialty care for rural children. FUNDING: Patient-Centered Outcomes Research Institute.

Development and validation of DeciBHAL-US: A novel microsimulation model of hearing loss across the lifespan in the United States.

BACKGROUND: Hearing loss affects over 50% of people in the US across their lifespan and there is a lack of decision modeling frameworks to inform optimal hearing healthcare delivery. Our objective was to develop and validate a microsimulation model of hearing loss across the lifespan in the US. METHODS: We collaborated with the Lancet Commission on Hearing Loss to outline model structure, identify input data sources, and calibrate/validate DeciBHAL-US (Decision model of the Burden of Hearing loss Across the Lifespan). We populated the model with literature-based estimates and validated the conceptual model with key informants. We validated key model endpoints to the published literature, including: 1) natural history of sensorineural hearing loss (SNHL), 2) natural history of conductive hearing loss (CHL), and 3) the hearing loss cascade of care. We reported the coefficient of variance root mean square error (CV-RMSE), considering values ≤15% to indicate adequate fit. FINDINGS: For SNHL prevalence, the CV-RMSE for model projected male and female age-specific prevalence compared to sex-adjusted National Health and Nutrition Examination Survey (NHANES) data was 4.9 and 5.7%, respectively. Incorporating literature-based age-related decline in SNHL, we validated mean four-frequency average hearing loss in the better ear (dB) among all persons to longitudinal data (CV-RMSE=11.3%). We validated the age-stratified prevalence of CHL to adjusted NHANES data (CV-RMSE=10.9%). We incorporated age- and severity-stratified time to first hearing aid (HA) use data and HA discontinuation data (adjusted for time-period of use) and validated to NHANES estimates on the prevalence of adult HA use (CV-RMSE=10.3%). INTERPRETATION: Our results indicate adequate model fit to internal and external validation data. Future incorporation of cost and severity-stratified utility data will allow for cost-effectiveness analysis of US hearing healthcare interventions across the lifespan. Further research might expand the modeling framework to international settings. FUNDING: This study was funded by the National Institute on Deafness and Other Communication Disorders and the National Institute on Aging (3UL1-TR002553-03S3 and F30 DC019846).

Middle Cranial Fossa Approach: The Incudomalleolar Joint as a Reliable Landmark

Abstract Introduction The middle cranial fossa approach is performed by fewer neurotologists owing to a reduced number of indications. Consistent landmarks are mandatory to guide the surgeon in a narrow field. Objectives We have evaluated the incus and malleus head and the incudomalleal joint (IMJ) as a key landmark for identifying the superior semicircular canal (SSC) and to get oriented along the floor of the middle cranial fossa. Methods A combination of 20 temporal bone dissections and CT imaging were utilized to test and describe these landmarks. Results The blue line of the SSC is consistently identified along the prolongation of a virtual line through the IMJ and the angulation toward the root of zygoma. The mean distance from the zygoma toward the IMJ ranged from 1.60 to 1.90cm. Once the IMJ was identified, the blue line of the SSC was consistently found along the virtual line through the IMJ within 5 to 9mm. Conclusions The IMJ is a safe and consistent anatomical marker in the surgical approach to the middle cranial fossa floor. Opening the tegmen 1.5 to 2cm medial to the root of the zygoma and identifying the joint allows to trace a virtual line toward the SSC within 5 to 9mm. Knowledge of the close relationship between the direction of the IMJ and the superior canal can be used in all transtemporal approaches, thus orienting the surgeon in a rather narrow field with limited retraction of the dura and brain.

Middle Cranial Fossa Approach: The Incudomalleolar Joint as a Reliable Landmark.

Introduction The middle cranial fossa approach is performed by fewer neurotologists owing to a reduced number of indications. Consistent landmarks are mandatory to guide the surgeon in a narrow field. Objectives We have evaluated the incus and malleus head and the incudomalleal joint (IMJ) as a key landmark for identifying the superior semicircular canal (SSC) and to get oriented along the floor of the middle cranial fossa. Methods A combination of 20 temporal bone dissections and CT imaging were utilized to test and describe these landmarks. Results The blue line of the SSC is consistently identified along the prolongation of a virtual line through the IMJ and the angulation toward the root of zygoma. The mean distance from the zygoma toward the IMJ ranged from 1.60 to 1.90cm. Once the IMJ was identified, the blue line of the SSC was consistently found along the virtual line through the IMJ within 5 to 9mm. Conclusions The IMJ is a safe and consistent anatomical marker in the surgical approach to the middle cranial fossa floor. Opening the tegmen 1.5 to 2cm medial to the root of the zygoma and identifying the joint allows to trace a virtual line toward the SSC within 5 to 9mm. Knowledge of the close relationship between the direction of the IMJ and the superior canal can be used in all transtemporal approaches, thus orienting the surgeon in a rather narrow field with limited retraction of the dura and brain.

Evidence gaps in economic analyses of hearing healthcare: A systematic review.

BACKGROUND: Hearing loss is a common and costly medical condition. This systematic review sought to identify evidence gaps in published model-based economic analyses addressing hearing loss to inform model development for an ongoing Lancet Commission. METHODS: We searched the published literature through 14 June 2020 and our inclusion criteria included decision model-based cost-effectiveness analyses that addressed diagnosis, treatment, or prevention of hearing loss. Two investigators screened articles for inclusion at the title, abstract, and full-text levels. Data were abstracted and the studies were assessed for the qualities of model structure, data assumptions, and reporting using a previously published quality scale. FINDINGS: Of 1437 articles identified by our search, 117 unique studies met the inclusion criteria. Most of these model-based analyses were set in high-income countries (n = 96, 82%). The evaluated interventions were hearing screening (n = 35, 30%), cochlear implantation (n = 34, 29%), hearing aid use (n = 28, 24%), vaccination (n = 22, 19%), and other interventions (n = 29, 25%); some studies included multiple interventions. Eighty-six studies reported the main outcome in quality-adjusted or disability-adjusted life-years, 24 of which derived their own utility values. The majority of the studies used decision tree (n = 72, 62%) or Markov (n = 41, 35%) models. Forty-one studies (35%) incorporated indirect economic effects. The median quality rating was 92/100 (IQR:72-100). INTERPRETATION: The review identified a large body of literature exploring the economic efficiency of hearing healthcare interventions. However, gaps in evidence remain in evaluation of hearing healthcare in low- and middle-income countries, as well as in investigating interventions across the lifespan. Additionally, considerable uncertainty remains around productivity benefits of hearing healthcare interventions as well as utility values for hearing-assisted health states. Future economic evaluations could address these limitations. FUNDING: NCATS 3UL1-TR002553-03S3.