The Circle of Care for Older Adults With Hearing Loss and Comorbidities: A Case Study of a Geriatric Audiology Clinic
Bibliographic record
Abstract
Purpose Older adults seeking audiologic rehabilitation often present with medical comorbidities, yet these realities of practice are poorly understood. Study aims were to examine (a) the frequency of identification of selected comorbidities in clients of a geriatric audiology clinic, (b) the influence of comorbidities on audiology practice, and (c) the effect of comorbidities on rehabilitation outcomes. Method The records of 135 clients ( M age = 86 years) were examined. Information about comorbidities came from audiology charts (physical paper files) and hospital electronic health records (EHRs). Data about rehabilitation recommendations and outcomes came from the charts. Focus groups with audiologists probed their views of how comorbidities influenced their practice. Results The frequency of identification was 68% for visual, 50% for cognitive, and 42% for manual dexterity issues; 84% had more than one comorbidity. Also noted were hypertension (43%), falls (33%), diabetes (13%), and depression (16%). Integrating information from the audiology chart and EHR provided a more complete understanding of comorbidities. Information about hearing in the EHR included logs of outpatient audiology visits (75% of 135 cases), audiologists' care notes for inpatients and long-term care residents (25%), and entries by other health professionals (60%). Modifications to audiology practice were common and varied depending on comorbidity. High rates of success were achieved regardless of comorbidities. Conclusions In this clinic, successful outcomes were achieved by modifying audiology practice for clients with comorbidities. Increased interprofessional communication among clinicians in the circle of care could improve care planning and outcomes for older adults with hearing loss.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".