Telehealth as a Means of Enabling Health Equity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The goal of this paper is to provide a consensus review on telehealth delivery prior to and during the COVID-19 pandemic to develop a set of recommendations for designing telehealth services and tools that contribute to system resilience and equitable health. METHODS: The IMIA-Telehealth Working Group (WG) members conducted a two-step approach to understand the role of telehealth in enabling global health equity. We first conducted a consensus review on the topic followed by a modified Delphi process to respond to four questions related to the role telehealth can play in developing a resilient and equitable health system. RESULTS: Fifteen WG members from eight countries participated in the Delphi process to share their views. The experts agreed that while telehealth services before and during COVID-19 pandemic have enhanced the delivery of and access to healthcare services, they were also concerned that global telehealth delivery has not been equal for everyone. The group came to a consensus that health system concepts including technology, financing, access to medical supplies and equipment, and governance capacity can all impact the delivery of telehealth services. CONCLUSION: Telehealth played a significant role in delivering healthcare services during the pandemic. However, telehealth delivery has also led to unintended consequences (UICs) including inequity issues and an increase in the digital divide. Telehealth practitioners, professionals and system designers therefore need to purposely design for equity as part of achieving broader health system goals.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it