The CPT1A Arctic variant: perspectives of community members and providers in two Alaska tribal health settings

Newborn screening in Alaska includes screening for carnitine palmitoyltransferase 1A (CPT1A) deficiency. The CPT1A Arctic variant is a variant highly prevalent among Indigenous peoples in the Arctic. In this study, we sought to elicit Alaska Native (AN) community member and AN-serving healthcare providers' knowledge and perspectives on the CPT1A Arctic variant. Focus groups with community members and healthcare providers were held in two regions of Alaska between October 2018 and January 2019. Thematic analysis was used to identify recurring constructs. Knowledge and understanding about the CPT1A Arctic variant and its health impact varied, and participants were interested in learning more about it. Additional education for healthcare professionals was recommended to improve providers' ability to communicate with family caregivers about the Arctic variant. Engagement with AN community members identified opportunities to improve educational outreach via multiple modalities for providers and caregivers on the Arctic variant, which could help to increase culturally relevant guidance and avoid stigmatization, undue worry, and unnecessary intervention. Education and guidance on the care of infants and children homozygous for the CPT1A Arctic variant could improve care and reduce negative psychosocial effects.

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.

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.

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.

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.

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.

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.

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 (ρ_Spearman = 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.

Telehealth solutions for assessing auditory outcomes related to noise and ototoxic exposures in clinic and research

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.

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.

Early Patient-Centered Outcomes Research Experience With the Use of Telehealth to Address Disparities: Scoping Review

BACKGROUND

Health systems and providers across America are increasingly employing telehealth technologies to better serve medically underserved low-income, minority, and rural populations at the highest risk for health disparities. The Patient-Centered Outcomes Research Institute (PCORI) has invested US $386 million in comparative effectiveness research in telehealth, yet little is known about the key early lessons garnered from this research regarding the best practices in using telehealth to address disparities.

OBJECTIVE

This paper describes preliminary lessons from the body of research using study findings and case studies drawn from PCORI seminal patient-centered outcomes research (PCOR) initiatives. The primary purpose was to identify common barriers and facilitators to implementing telehealth technologies in populations at risk for disparities.

METHODS

A systematic scoping review of telehealth studies addressing disparities was performed. It was guided by the Arksey and O'Malley Scoping Review Framework and focused on PCORI's active portfolio of telehealth studies and key PCOR identified by study investigators. We drew on this broad literature using illustrative examples from early PCOR experience and published literature to assess barriers and facilitators to implementing telehealth in populations at risk for disparities, using the active implementation framework to extract data. Major themes regarding how telehealth interventions can overcome barriers to telehealth adoption and implementation were identified through this review using an iterative Delphi process to achieve consensus among the PCORI investigators participating in the study.

RESULTS

PCORI has funded 89 comparative effectiveness studies in telehealth, of which 41 assessed the use of telehealth to improve outcomes for populations at risk for health disparities. These 41 studies employed various overlapping modalities including mobile devices (29/41, 71%), web-based interventions (30/41, 73%), real-time videoconferencing (15/41, 37%), remote patient monitoring (8/41, 20%), and store-and-forward (ie, asynchronous electronic transmission) interventions (4/41, 10%). The studies targeted one or more of PCORI's priority populations, including racial and ethnic minorities (31/41, 41%), people living in rural areas, and those with low income/low socioeconomic status, low health literacy, or disabilities. Major themes identified across these studies included the importance of patient-centered design, cultural tailoring of telehealth solutions, delivering telehealth through trusted intermediaries, partnering with payers to expand telehealth reimbursement, and ensuring confidential sharing of private information.

CONCLUSIONS

Early PCOR evidence suggests that the most effective health system- and provider-level telehealth implementation solutions to address disparities employ patient-centered and culturally tailored telehealth solutions whose development is actively guided by the patients themselves to meet the needs of specific communities and populations. Further, this evidence shows that the best practices in telehealth implementation include delivery of telehealth through trusted intermediaries, close partnership with payers to facilitate reimbursement and sustainability, and safeguards to ensure patient-guided confidential sharing of personal health information.

Hearing Norton Sound: community involvement in the design of a mixed methods community randomized trial in 15 Alaska Native communities

Community involvement is important in good research practice. We led a community-based study to improve early detection and treatment of childhood hearing loss in rural Alaska. This study evaluated a cell phone-based hearing screening process and compared a new telemedicine specialty referral pathway to the standard primary care referral pathway. The study included community involvement, engagement, and participation from the very beginning to inform how to best design the trial. We obtained insight and feedback from community members through involvement of a core stakeholder team and through community engagement and participation in focus groups and community events. Feedback received through community involvement and participation influenced the design of the trial at key decision points. Community member guidance shaped the research question, the outcomes to be measured, and the procedures for completing the project, such as participant recruitment. This study offers an example of community involvement, engagement and participation that could be mirrored in future research to maintain the interests of participating communities. Background Effective systems for early identification and treatment of childhood hearing loss are essential in rural Alaska, where data indicate a high prevalence of childhood ear infections and hearing loss. However, loss to follow-up from school hearing screening programs is pervasive. The Hearing Norton Sound study was a mixed methods community randomized controlled trial that was developed to address this gap. The study engaged community members and participants in the design of the trial, including involvement of stakeholders as collaborators. Methods Community engagement and participation in research design occurred through focus groups and through the integration of stakeholders into the study team. Representation was cross-sectoral, involving individuals from multiple levels of the school and health system, as well as community members from each of the 15 communities. Feedback obtained between April 2017 and August 2017 informed the final design of the randomized trial, which began enrollment of children in October 2017 and concluded in March 2019. Results Stakeholder involvement and community participation shaped the design of specific trial elements (research question; comparators; outcomes and measures; telemedicine protocols; and recruitment and retention). Community involvement was strengthened by the use of multiple modalities of involvement and by the positionality of lead stakeholders on the study team. Conclusions This study highlights the effectiveness of multifaceted stakeholder involvement and participation in the design of health research conducted within Alaska Native communities. It offers an example of involvement and reporting that could be mirrored in future research in order to protect and further the interests of the participating community. Trial registration ClinicalTrials.gov, NCT03309553 , First registered 10/9/2017.

Hearing care across the life course provided in the community

Untreated hearing loss is recognized as a growing global health priority because of its prevalence and harmful effects on health and well-being. Until recently, little progress had been made in expanding hearing care beyond traditional clinic-based models to incorporate public health approaches that increase accessibility to and affordability of hearing care. As demonstrated in numerous countries and for many health conditions, sharing health-care tasks with community health workers (CHWs) offers advantages as a complementary approach to expand health-service delivery and improve public health. This paper explores the possibilities of task shifting to provide hearing care across the life course by reviewing several ongoing projects in a variety of settings – Bangladesh, India, South Africa and the United States of America. The selected programmes train CHWs to provide a range of hearing-care services, from childhood hearing screening to management of age-related hearing loss. We discuss lessons learnt from these examples to inform best practices for task shifting within community-delivered hearing care. Preliminary evidence supports the feasibility, acceptability and effectiveness of hearing care delivered by CHWs in these varied settings. To make further progress, community-delivered hearing care must build on established models of CHWs and ensure adequate training and supervision, delineation of the scope of practice, supportive local and national legislation, incorporation of appropriate technology and analysis of programme costs and cost–effectiveness. In view of the growing evidence, community-delivered hearing care may now be a way forward to improve hearing health equity.

Hearing Norton Sound: mixed methods protocol of a community randomised trial to address childhood hearing loss in rural Alaska

INTRODUCTION

Childhood hearing loss has implications for school achievement, economic outcomes and quality of life. This study will engage rural Alaska communities in research to improve the school hearing screening and referral process, partnering with stakeholders to develop a locally derived, evidence-based solution to improve timely identification and treatment of childhood hearing loss.

METHODS AND ANALYSIS

Mixed methods community randomised trial in 15 communities in the Norton Sound region of northwest Alaska. Data collection will span from April 2017 until February 2020. Qualitative and mixed methods components are described in this protocol and the community randomised trial in the companion protocol. Focus groups and community events will be held leading up to the randomised trial to obtain community perspectives on childhood hearing loss in Alaska and elicit community input during trial protocol refinement (exploratory sequential stage). Stakeholder groups, including parents, children, teachers, school administrators and community health aides, will participate, along with community leaders, tribal leaders and community members. The randomised trial will be combined with qualitative, semi-structured interviews to elicit stakeholder perspectives on the intervention (explanatory sequential stage). The five stakeholder groups described above will participate in interviews. The study will conclude with additional focus groups and community events to discuss results and provide community insight for future implementation. Concluding focus groups will include policymakers, healthcare administrators, and tribal and community leaders in addition to the stakeholder groups. Informed consent and child assent will be required. Recordings will be transcribed and deidentified, with only stakeholder group recorded. Analyses will include categorical coding as well as narrative and thematic analysis.

ETHICS AND DISSEMINATION

The Hearing Norton Sound study has been approved by the Institutional Review Boards of Alaska Area, Norton Sound, and Duke University, with trial registration on clinicaltrials.gov. Study results will be distributed with equal emphasis on scientific and community dissemination.

TRIAL REGISTRATION NUMBER

NCT03309553; Results.

Hearing Norton Sound: a community randomised trial protocol to address childhood hearing loss in rural Alaska

INTRODUCTION

The population in rural Alaska experiences a disproprionately high burden of infection-mediated hearing loss. While the state mandates school hearing screening, many children with hearing loss are not identified or are lost to follow-up before ever receiving treatment. A robust, tribally owned healthcare system exists in Alaska, but children with hearing loss must first be identified and referred for existing infrastructure to be used. This trial will evaluate a new school hearing screening and referral process in rural Alaska, with the goal of improving timely identification and treatment of childhood hearing loss.

METHODS AND ANALYSIS

Comparative effectiveness community randomised trial testing digital innovations to improve school hearing screening and referral in 15 communities in the Norton Sound region of northwest Alaska, with data collection from October 2017 to February 2020. All children (K-12) attending school in Bering Strait School District with parental informed consent and child assent will be eligible (target recruitment n=1500). Participating children will undergo both the current school hearing screen and new mobile health (mHealth) screen, with screening test validity evaluated against an audiometric assessment. Communities will be cluster randomised to continue the current primary care referral process or receive telemedicine referral for follow-up diagnosis and treatment. The primary outcome will be time to International Statistical Classification of Diseases, 10th Revision, ear/hearing diagnosis from screening date, measured in days. Secondary outcomes will include: sensitivity and specificity of current school and mHealth screening protocols measured against a benchmark audiometric assessment (air and bone conduction audiometry, tympanometry and digital otoscopy); hearing loss prevalence; hearing-related quality of life; and school performance (AIMSweb). Intention-to-treat analysis will be used.

ETHICS AND DISSEMINATION

This study has been approved by the Institutional Review Boards of Alaska Area, Norton Sound and Duke University and is registered on clinicaltrials.gov. Results will be distributed with equal emphasis on scientific and community dissemination.

TRIAL REGISTRATION NUMBER

NCT03309553; Pre-results.