A102 INTERDISCIPLINARY TELEHEALTH REFERRAL PATHWAY AND CONSULTATIONS TO IMPROVE OUTCOMES AMONG CANADIAN OLDER ADULTS WITH LIVER CIRRHOSIS
Bibliographic record
Abstract
Abstract Background Telehealth and telemedicine have become indispensable healthcare delivery tools during the COVID-19 pandemic. Older individuals with cirrhosis have complex medical needs that are currently unmet due to the growing disease burden and decreased access to care. Delivering timely specialist care virtually to older adults with cirrhosis will likely be beneficial and acceptable to such patients; however, this has not yet been prospectively evaluated. Purpose The primary goal is to pilot the delivery of dual specialist care from a hepatologist and geriatrician, delivered virtually, for older adults living with liver cirrhosis who are at high risk of geriatric syndromes (age >/= 65 with frailty, undifferentiated cognitive impairment from dementia or hepatic encephalopathy, recurrent falls, risk factors for polypharmacy and moderate to severe malnutrition). Care is delivered using a dedicated hepatology-geriatric referral pathway. Primary objectives include evaluating the impact of this approach on emergency care and inpatient utilization, along with patient attitude and satisfaction to the virtual interdisciplinary care delivery model. Method This pilot quality improvement study was conducted in Halifax, Nova Scotia. Ethics approval was obtained from the Nova Scotia Health Research Ethics Board and the University of Alberta Research Ethics Board. Fifty to one hundred participants (age 65 years or older with at least one geriatric syndrome; diagnosis of liver cirrhosis by liver elastography or liver biopsy, or Fibrosis-4 Index for Liver Fibrosis greater than three and having radiological features of cirrhosis and/or portal hypertension) were recruited between September 2022 to December 2022 at the time of their hepatology consultation. After consent and screening, each patient underwent a telehealth appointment by zoom with a geriatrician within four weeks of their initial hepatology assessment. Follow-up by telephone using a standardized survey regarding ease of access and quality of their telehealth experience then occurred at 3-4 weeks, 3 months and 6 months for emergency room visits and hospital admission status. Result(s) Pending Conclusion(s) Pending Please acknowledge all funding agencies by checking the applicable boxes below Other Please indicate your source of funding; Pfizer Canada Disclosure of Interest J. Zhu Grant / Research support from: Pfizer Canada, F. Carr Grant / Research support from: Pfizer Canada, P. Tian: None Declared, M. McLeod: None Declared, M. MacFarlane: None Declared, S. De Coutere: None Declared, M. Sun: None Declared, K. Peltekian: None Declared
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".