Impact of Project ECHO on Patient and Community Health Outcomes: A Scoping Review
Bibliographic record
Abstract
PURPOSE: Project Extension for Community Healthcare Outcomes (ECHO) is a hub-and-spoke tele-education model that aims to increase health care providers' access to evidence-based guidelines and enhance their capacity to care for complex patients in rural, remote, and underserved communities. The purpose of this scoping review was to examine evidence of the impact of Project ECHO programs on patient and community health outcomes. METHOD: The authors used Arksey and O'Malley's framework and subsequent revisions proposed by Levac and colleagues to guide their review. They searched MEDLINE, EMBASE, CINAHL Plus, and Web of Science for English-language, peer-reviewed articles published between January 2003 and June 2020. Included studies focused on Project ECHO programs and reported either patient or community health outcomes. The authors used a standardized data extraction form to document bibliographical information and study characteristics, including health outcome level(s), as articulated by Moore's evaluation framework for continuing medical education. RESULTS: Of the 597 search results, the authors identified 15 studies describing Project ECHO programs. These programs were implemented in the United States and Australia and facilitated education sessions with health care providers caring for adult patients living with 1 of 7 medical conditions. Included study findings suggest Project ECHO programs significantly changed patient-level outcomes (n = 15) and to a lesser extent changed community-level outcomes (n = 1). Changes in care were observed at the individual patient level, at the practice level, and in objective clinical measures, including sustained virologic response and HbA1c. CONCLUSIONS: This review identified emerging evidence of the effectiveness of Project ECHO as a tele-education model that improves patient health outcomes and has the potential to positively impact community health. The small number of included studies suggests that additional evidence of patient- and community-level impact is required to support the continued adoption and implementation of this model.
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 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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".