Estimated Therapy Costs and Downstream Cost Consequences of iBASIS-Video Interaction to Promote Positive Parenting Intervention vs Usual Care Among Children Displaying Early Behavioral Signs of Autism in Australia.

Importance: The growing global prevalence of autism spectrum disorder (ASD) is associated with increasing costs for support services. Ascertaining the effects of a successful preemptive intervention for infants showing early behavioral signs of autism on human services budgets is highly policy relevant. Objective: To estimate the net cost impact of the iBASIS-Video Interaction to Promote Positive Parenting (iBASIS-VIPP) intervention on the Australian government. Design, Setting, and Participants: Infants (aged 12 months) showing early behavioral indicators of autism were recruited through community settings into the multicenter Australian iBASIS-VIPP randomized clinical trial (RCT), a 5- to 6-month preemptive parent-mediated intervention, between June 9, 2016, and March 30, 2018, and were followed up for 18 months to age 3 years. This economic evaluation, including cost analysis (intervention and cost consequences) and cost-effectiveness analyses of iBASIS-VIPP compared with usual care (treatment as usual [TAU]), modeled outcomes observed at age 3 through to 12 years (13th birthday) and was conducted from April 1, 2021, to January 30, 2023. Data analysis was conducted from July 1, 2021, to January 29, 2023. Exposures: iBASIS-VIPP intervention. Main Outcomes and Measures: To project the diagnostic trajectory and associated disability support costs drawing on the Australian National Disability Insurance Scheme (NDIS), the main outcome was the differential treatment cost of iBASIS-VIPP plus TAU vs TAU and disability-related government costs modeled to age 12 years, using a clinical diagnosis of ASD and developmental delay (with autism traits) at 3 years. Costs were calculated in Australian dollars and converted to US dollars. Economic performance was measured through the following: (1) differential net present value (NPV) cost (iBASIS-VIPP less TAU), (2) investment return (dollars saved for each dollar invested, taking a third-party payer perspective), (3) break-even age when treatment cost was offset by downstream cost savings, and (4) cost-effectiveness in terms of the differential treatment cost per differential ASD diagnosis at age 3 years. Alternate values of key parameters were modeled in 1-way and probabilistic sensitivity analysis, the latter identifying the likelihood of an NPV cost savings. Results: Of the 103 infants enrolled in the iBASIS-VIPP RCT, 70 (68.0%) were boys. Follow-up data at age 3 years were available for 89 children who received TAU (44 [49.4%]) or iBASIS-VIPP (45 [50.6%]) and were included in this analysis. The estimated mean differential treatment cost was A $5131 (US $3607) per child for iBASIS-VIPP less TAU. The best estimate of NPV cost savings was A $10 695 (US $7519) per child (discounted at 3% per annum). For each dollar invested in treatment, a savings of A $3.08 (US $3.08) was estimated; the break-even cost occurred at age 5.3 years (approximately 4 years after intervention delivery). The mean differential treatment cost per lower incident case of ASD was A $37 181 (US $26 138). We estimated that there was an 88.9% chance that iBASIS-VIPP would deliver a cost savings for the NDIS, the dominant third-party payer. Conclusions and Relevance: The results of this study suggest that iBASIS-VIPP represents a likely good-value societal investment for supporting neurodivergent children. The estimated net cost savings were considered conservative, as they covered only third-party payer costs incurred by the NDIS and outcomes were modeled to just age 12 years. These findings further suggest that preemptive interventions may be a feasible, effective, and efficient new clinical pathway for ASD, reducing disability and the costs of support services. Long-term follow-up of children receiving preemptive intervention is needed to confirm the modeled results.

Factors Influencing Postoperative Experiences in Adult Cochlear Implant Recipients: A Multistakeholder Perspective.

OBJECTIVE: To explore factors influencing postoperative experiences of adult cochlear implant (CI) recipients, determine the impact of each factor, and conceptualize recipients' postoperative journey. STUDY DESIGN: Participatory mixed methods; concept mapping. SETTING: Tertiary care (private and public). PATIENTS: Ninety-three participated in the brainstorming activity. Eighty-nine completed the sorting tasks (96% retention rate): CI recipients (n = 44), significant others (n = 13), CI audiologists (n = 14) and surgeons (n = 5), CI clinics' administration staff (n = 5) and managers (n = 3), and CI manufactures' clinical support staff (n = 5). INTERVENTIONS: Rehabilitative (CIs). MAIN OUTCOME MEASURES: Statements were generated and rated by participants. Similarity of grouping of the statements informed the matrices used for cluster analysis to form concepts. RESULTS: Eighty-seven unique statements described the factors influencing adapting to, use, and maintenance of CIs after implantation. These were grouped, and five concepts were identified: financial considerations, complications, device usability and durability, device programming and adaptation, and patient motivation and supports. Although statements within the concepts financial considerations and complications were negatively rated, statements within the concepts device programming and adaptation, and patient motivation and supports were mostly rated as having positive influence in patients' postoperative journey. The concept device usability and durability contained both negatively and positively rated statements. CONCLUSIONS: Postoperative experience of adult CI recipients is a multifaceted journey with several challenges to address to improve services. Although support from and connection with family and clinicians, and simplicity of using a CI device facilitated the experience, medical and surgical complications, durability, and cost of maintaining the device challenged the postoperative experience.

What Influences Decision-Making for Cochlear Implantation in Adults? Exploring Barriers and Drivers From a Multistakeholder Perspective.

OBJECTIVES: To explore the factors influencing the uptake of cochlear implants in adults, determine the impact of each factor, and to conceptualize the journey to implantation from a multistakeholder perspective. DESIGN: Concept mapping was used to integrate input from multiple stakeholders, each with their own experience and expertise. This mixed participatory method collects qualitative and quantitative data collection and enables further quantitative analysis. There were two participant cohorts: clients (cochlear implant recipients, candidates, and family members) and professionals (cochlear implant audiologists, ear, nose, and throat surgeons, administration staff, managers. and manufacturer representatives). A total of 93 people participated in the study: client cohort (n = 60, M age = 66.60 years) and professional cohort (n = 33, M age = 45.24 years). Participants brainstormed statements in response to the question "What influences people's decision to get/not get a cochlear implant?" They subsequently grouped the statements and named each group. They rated each statement as to its impact on the decision and prioritized the need for each to be changed/improved using a five-point Likert scale. Multidimensional scaling was used to produce a visual representation of the ideas and their relationship in the form of concepts. Further analysis was conducted to determine the differences between the cohorts, subcohorts, and concepts. RESULTS: One hundred ten unique statements were generated and grouped into six concepts which either directly affected the client or their environment. These concepts were: external influences (awareness and attitude of non-implant professionals about uptake, cost, logistics, the referral pathway, public awareness); uncertainties, beliefs, and fears (fears, negative effect of word of mouth, unsuccessful previous ear surgery, cosmetics of the device, misunderstanding of how a cochlear implant functions, eligibility for an implant and outcomes after implantation); health problems (mental and physical health); hearing difficulties (social, emotional, and communication impacts of hearing loss, severity of hearing loss, benefit from and experience with hearing aids); implant professionals (implant team's attitude, knowledge and relationship with clients, quality of overall service); and goals and support (clients 'hearing desires and goals, motivation, positive impact of word of mouth, family support, having a cochlear implant mentor. The six concepts fell into two overarching domains: the client-driven domain with four concepts and the external domain with two concepts. The mean rating of concepts in terms of impact on a client's decision to get an implant ranged from 2.24 (external influences, the main barrier) to 4.45 (goals and support, the main driver). Ratings significantly differed between the client and professional cohorts. CONCLUSIONS: This study increases our understanding of the factors, which influence a client's decision choose a cochlear implant as a hearing treatment. It also provides new information on the influence of the other stakeholders on the client journey. The magnitude of the generated statements in the client-driven domain highlights the pivotal role of individualized care in clinical settings in influencing a client's decision and the need for the professionals to understand a client's needs and expectations. A client's persistent hearing difficulties, goals, and support network were identified as drivers to the uptake of cochlear implants. However, the barriers identified highlight the need for a collaborative multi- and interdisciplinary approach to raise awareness in and educate non-implant hearing professionals about the cochlear implant process, as well as providing information to empower clients to make educated decisions and consider a cochlear implant as a hearing management option.

Predicting sequential bilateral cochlear implantation performance in postlingually deafened adults; A retrospective cohort study.

OBJECTIVE: To identify which preoperative patient characteristics influence sequential bilateral cochlear implantation performance and to create a statistical model that predicts benefit. DESIGN: Multicentre retrospective cohort study. SETTING: All patients were operated in four academic teaching hospitals in Perth, Australia, and followed up by audiologists of the Ear Science Institute Australia. PARTICIPANTS: A total of 92 postlingually deafened adult patients who had undergone sequential cochlear implantations between 19 June 1990 and 14 March 2016 were included. Patients were excluded if the 12-month follow-up consonant-nucleus-consonant (CNC) phoneme score was missing. MAIN OUTCOME MEASURE: The effect of 18 preoperative factors on the CNC phoneme score in quiet (at 65 dB SPL) with the second cochlear implant (CI2) one year after implantation. RESULTS: Two factors were positively correlated to speech understanding with CI2: Wearing a hearing aid (HA) before receiving CI2 (r = 0.46, P = 0.00) and the maximum CNC phoneme score with the first CI (CI1) (r = 0.21, P = 0.05). Two factors were negatively correlated: the length of hearing loss before CI2 in the second implanted ear (r = -0.25, P = 0.02) and preoperative pure tone average (PTA) (0.5, 1, 2 kHz) before CI2 in the second implanted ear (r = -0.27, P = 0.01). The following model could be created: predicted CNC phoneme score with CI2 (%) = 16 + (44 * HA use before CI2 (yes)) - (0.22 * length of hearing loss before CI2 (years)) + (0.23 * CNC phoneme score with CI1 (%)). Because the effect of HA use before implantation played such a major role, we also created a model after exclusion of the HA factor: Predicted CNC phoneme score with CI2 (%) = 82 - (0.17 * length of hearing loss before CI2 (years)) - (0.27 * PTA in second implanted ear before CI2 (0.5, 1, 2 kHz)) + (0.20 * CNC phoneme score with CI1 (%)). CONCLUSION: Advanced age or a long interval between implantations does not necessarily lead to poor CI2 results. Patients who are successful HA users before CI2, who have a low PTA before CI2, a high CNC phoneme score with CI1 and a limited length of hearing loss before CI2, are likely to be successful CI2 recipients.

Psychophysical Map Stability in Bilateral Sequential Cochlear Implantation: Comparing Current Audiology Methods to a New Statistical Definition.

OBJECTIVES: The purpose of this study was to establish a statistical definition for stability in cochlear implant maps. Once defined, this study aimed to compare the duration taken to achieve a stable map in first and second implants in patients who underwent sequential bilateral cochlear implantation. This article also sought to evaluate a number of factors that potentially affect map stability. DESIGN: A retrospective cohort study of 33 patients with sensorineural hearing loss who received sequential bilateral cochlear implantation (Cochlear, Sydney, Australia), performed by the senior author. Psychophysical parameters of hearing threshold scores, comfort scores, and the dynamic range were measured for the apical, medial, and basal portions of the cochlear implant electrode at a range of intervals postimplantation. Stability was defined statistically as a less than 10% difference in threshold, comfort, and dynamic range scores over three consecutive mapping sessions. A senior cochlear implant audiologist, blinded to implant order and the statistical results, separately analyzed these psychophysical map parameters using current assessment methods. First and second implants were compared for duration to achieve stability, age, gender, the duration of deafness, etiology of deafness, time between the insertion of the first and second implant, and the presence or absence of preoperative hearing aids were evaluated and its relationship to stability. Statistical analysis included performing a two-tailed Student's t tests and least squares regression analysis, with a statistical significance set at p ≤ 0.05. RESULTS: There was a significant positive correlation between the devised statistical definition and the current audiology methods for assessing stability, with a Pearson correlation coefficient r = 0.36 and a least squares regression slope (b) of 0.41, df(58), 95% confidence interval 0.07 to 0.55 (p = 0.004). The average duration from device switch on to stability in the first implant was 87 days using current audiology methods and 81 days using the statistical definition, with no statistically significant difference between assessment methods (p = 0.2). The duration to achieve stability in the second implant was 51 days using current audiology methods and 60 days using the statistical method, and again no difference between the two assessment methods (p = 0.13). There was a significant reduction in the time to achieve stability in second implants for both audiology and statistical methods (p < 0.001 and p = 0.02, respectively). There was a difference in duration to achieve stability based on electrode array region, with basal portions taking longer to stabilize than apical in the first implant (p = 0.02) and both apical and medial segments in second implants (p = 0.004 and p = 0.01, respectively). No factors that were evaluated in this study, including gender, age, etiology of deafness, duration of deafness, time between implant insertion, and the preoperative hearing aid status, were correlated with stability duration in either stability assessment method. CONCLUSIONS: Our statistical definition can accurately predict cochlear implant map stability when compared with current audiology practices. Cochlear implants that are implanted second tend to stabilize sooner than the first, which has a significant impact on counseling before a second implant. No factors evaluated affected the duration required to achieve stability in this study.

Clinical validation of the AMTAS automated audiometer.

OBJECTIVE: To validate the air- and bone-conduction AMTAS automated audiometry system. DESIGN: Prospective study. Test-retest reliability was determined by assessing adults with AMTAS air- and bone-conduction audiometry. Accuracy was determined by comparing AMTAS and manual audiometry conducted on adults. AMTAS testing was conducted in a quiet room and manual audiometry in a sound booth. STUDY SAMPLE: Ten participants for test-retest reliability tests and 44 participants to determine accuracy were included. Participants had varying degrees of hearing loss. RESULTS: For test-retest reliability the overall difference in air-conduction hearing thresholds (n = 119) was 0.5 dB. The spread of differences (standard deviation of absolute differences) was 4.9 dB. For bone-conduction thresholds (n = 99) the overall difference was - 0.2 dB, and the spread of differences 4.5 dB. For accuracy the overall difference in air-conduction hearing thresholds (n = 509) between the two techniques was 0.1 dB. The spread of differences was 6.4 dB. For bone-conduction thresholds (n = 295) the overall difference was 0 dB, and the spread of differences 7.7 dB. CONCLUSIONS: Variations between air- and bone-conduction audiometry for automated and manual audiometry were within normally accepted limits for audiometry. However, AMTAS thresholds were elevated but not significantly different compared to other contemporary studies that included an automated audiometer.