Prescribing cellular phones to patients helps emergency physicians and staff provide care
Bibliographic record
Abstract
Background: Emergency Department (ED) patients experiencing disadvantage (e.g., homelessness, addictions) can have limited access to cellular phones. This barrier can affect access to follow-up health care, connecting with community resources, and communicating with friends and family. PHONE-CONNECT is an intervention providing free cellular phones and prepaid plans to patients who do not have them. This intervention allows ED-based health care workers, such as social workers, nurses and physicians, to facilitate follow-up care with patients in their transition from hospital to community. Objective: To explore how the intervention affects health care workers in the emergency department, including those facilitating implementation. Methods: We used valid and reliable implementation science outcome measures - Acceptability, Appropriateness, and Feasibility of Intervention Measures - informed by a Realist Evaluation approach to explore how, why, and for whom the intervention works best. Staff trained in data collection deployed anonymous in-person and online surveys across 3 academic ED's in Toronto, Ontario. Respondents were registered nurses, medical doctors, social workers, and peer-based staff. Survey questions focused on implementation, and perceived impact of the intervention. Questions were scored on a 5-point Likert scale ranging from Completely disagree [1] to Completely Agree [5]. Data were analyzed using descriptive statistics and aggregate scores were calculated in Microsoft Excel. Results: 142 survey responses were collected between August and September 2022. Respondents agree that the intervention is acceptable (84.5%), appropriate (83.9%), and feasible (80.4%). A subset of 46 respondents facilitating the intervention reported that it improves their ability to meet the health (92.9%) and social needs of patients (91.4%); facilitate follow-up care (91.9%) and disposition planning while in the ED (88.1%); and improves the quality of care provided (90.5%). Distributing phones was reported to be worth the cumulative time and effort (91.7%), and was felt to reduce experiences of moral distress (82.4%) and burnout (69%). Conclusion: PHONE-CONNECT is feasible, acceptable, and appropriate in the ED. It empowers physicians and health care workers to provide high quality care, while reducing moral distress and burnout. Novel ED-based interventions are efficacious ways to bridge gaps in care experienced by patients in their transition from hospital to community. Though challenging with this population, future work exploring patient experiences will help optimize outcomes and further streamline the process of phone delivery and utilization.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".