Impact of Geriatric Hotlines on Health Care Pathways and Health Status in Patients Aged 75 Years and Older: Protocol for a French Multicenter Observational Study (Preprint)
Bibliographic record
Abstract
BACKGROUND In France, emergency departments (EDs) are the fastest and most common means for general practitioners (GPs) to cope with the complex issues presented by elderly patients with multiple conditions. EDs are overburdened, and studies show that being treated in EDs can have a damaging effect on the health of elderly patients. Outpatient care or planned hospitalizations are possible solutions if appropriate geriatric medical advice is provided. In 2013, France’s regional health authorities proposed creating direct telephone helplines, “geriatric hotlines,” staffed by geriatric specialists to encourage interactions between GP clinics and hospitals. These hotlines are designed to improve health care pathways and the health status of the elderly. OBJECTIVE This study aims to describe the health care pathways and health status of patients aged 75 years and older hospitalized in short-stay geriatric wards following referral from a geriatric hotline. METHODS The study will be conducted over 24 months in seven French university hospital centers. It will include all patients aged 75 and older, living in their own homes or nursing homes, who are admitted to short-stay geriatric wards following hotline consultation. Two questionnaires will be filled out by medical staff at specific time points: (1) after conducting the telephone consultation and (2) on admitting the patient to a short-stay geriatric medical care. The primary endpoint will be mean hospitalization duration. The secondary endpoints will be intrahospital mortality rate, the characteristics of patients admitted via the hotline, and the types of questions asked and responses given via the hotline. RESULTS The study was funded by the National School for Social Security Loire department (École Nationale Supérieure de Sécurité Sociale) and the Conference for funders of prevention of autonomy loss for the elderly of the Loire department in November 2017. Institutional review board approval was obtained in April 2018. Data collection started in May 2018; the planned end date for data collection is May 2020. Data analysis will take place in the summer of 2020, and the first results are expected to be published in late 2020. CONCLUSIONS The results will reveal whether geriatric hotlines provide the most effective management of elderly patients, as indicated by shorter mean hospitalization durations. Shorter hospital durations could lead to a reduced risk of complications—geriatric syndromes—and the domino chain of geriatric conditions that follow. We will also describe different geriatric hotlines from different cities and compare how they function to improve the health care of the elderly and pave the way toward new advances, especially in the organization of the care path. CLINICALTRIAL ClinicalTrials.gov NCT03959475; https://clinicaltrials.gov/ct2/show/NCT03959475 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/15423
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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 | 0.020 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".