Effectiveness of a web-based socio-geriatric pre-consultation tool for older adults in primary care: A randomized controlled trial (Preprint)
Bibliographic record
Abstract
BACKGROUND Pre-consultation tools have been proposed as a solution to support primary care providers in effectively managing the growing number of older adults. Despite older adults making up 25% of primary care consultations, few tools are specifically adapted for them, and most only assess their physical health. The Evaluation SOcio-GERiatrique (ESOGER) tool, a short web-based pre-consultation questionnaire of older adults' physical, mental, cognitive, and social support needs, administered by phone, may provide an effective means of supporting providers in improving patient outcomes in the primary care setting. OBJECTIVE To evaluate the effectiveness of the ESOGER tool in improving health-related quality of life and unplanned health service use for older adults in the primary care context. METHODS A multi-center, individually-randomized parallel-group controlled trial was conducted at four university affiliated interprofessional primary care clinics in Quebec, Canada. Participants were randomized 1 to 1 to either the intervention or standard care group. The intervention group was administered the ESOGER tool by phone by clinic staff (total of 12 clinic staff across sites) at least one day prior to their consultation with their health provider. The ESOGER tool generated a report for the provider to view at the time of consultation. Although clinics were not blinded to group assignment, patients were blinded unless the tool was mentioned during consultation with the health provider. The primary outcome of interest was self-reported health-related quality of life (HRQoL) as measured by the EuroQol 5D (EQ-5D). Secondary outcomes were self-reported unplanned visits to their family doctor, visits to the emergency department (ED) and hospitalizations within the last three months. Data were collected at baseline and 3 months. An intention-to-treat (ITT) analysis was carried out for the study outcomes. The primary outcome was analysed using beta regression. Secondary outcomes were analysed using logistic regression. Inverse probability of censoring weighting was used to impute missing data due to censoring. RESULTS Of the 452 eligible to participate, 111 were lost to follow up, for a total sample size of 341 (75.4%) participants. No significant differences in the EQ-5D were observed between the intervention and the standard care group (OR = 1.0, 95%CI [0.5, 2.0]) or the secondary outcomes. CONCLUSIONS ESOGER, a pre-consultation tool in the primary care setting for older adults, did not have an effect on health-related quality of life or unplanned health service use when compared to standard care. The non-significant results of the ESOGER tool could be due to a ceiling effect, a limited follow-up duration, or lack of resources for the implementation of the ESOGER tool. Given the potential of pre-consultation tools to support the management of older adults, further research should explore the conditions under which these tools can lead to positive patient outcomes. CLINICALTRIAL ClinicalTrials.gov NCT05102890
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".