G2TT
来源类型Report
规范类型报告
DOIhttps://doi.org/10.7249/RR2934
来源IDRR-2934-ASPEC
Evaluation of Technology-Enabled Collaborative Learning and Capacity Building Models: Materials for a Report to Congress
Shira H. Fischer; Adam J. Rose; Ryan K. McBain; Laura J. Faherty; Jessica L. Sousa; Monique Martineau
发表日期2019-03-06
出版年2019
页码202
语种英语
结论

Empirical evidence for the effects of ECHO and ECHO-like models (EELM) on patient and provider outcomes remains modest

  • Based on a literature review and a technical expert panel, the quality of evidence for the effectiveness of EELM is rated as "low" or "very low" based on generally accepted systems of measurement. However, it is important to note that many models of care delivery are supported only by low-quality evidence.
  • In the areas that researchers have measured, EELM mostly show positive effects.
  • The intention of EELM is to increase access to specialty care by educating generalist health providers, particularly those in locales with limited access such as rural and remote areas. However, there is a need for targeted funding to evaluate EELM effectively.
摘要

Across the United States and internationally, multiple health care sites have embraced technology-enabled collaborative learning and capacity-building models. Such models use technology to connect generalist providers, often located in remote areas, with specialist teams that help train these providers to deliver care for patients with conditions that they might not feel adequately prepared to handle but are nevertheless within their scope of practice. The first implementation of this model, Project ECHO (Extension for Community Healthcare Outcomes), launched in 2003 in New Mexico. Project ECHO began with a focus on supporting the management of patients with hepatitis C virus (HCV) in rural regions of the state. This model has since been adapted to many different sites within the United States and other countries, and these models now address a wide range of medical conditions and other issues that providers face. This report documents what is known about ECHO and ECHO-like models (EELM). Generally speaking, the quality of evidence for the effectiveness of EELM could use improvement, but EELM mostly show positive effects in the small but growing body of research of EELM, which thus far measures more provider outcomes than patient outcomes.

目录
  • Chapter One

    Introduction

  • Chapter Two

    EELM in Context: History, Promise, and Challenges

  • Chapter Three

    Methods

  • Chapter Four

    Findings: Inventory

  • Chapter Five

    Findings: Evidence Review

  • Chapter Six

    Findings of Technical Expert Panel: Evaluation Options

  • Chapter Seven

    Example Evaluation Study Designs

  • Chapter Eight

    Implications and Conclusions

  • Appendix A

    Search Technique for Inventory

  • Appendix B

    Search Technique for Evidence Review

  • Appendix C

    Studies Used in Evidence Review

  • Appendix D

    Studies Considered as Examples of EELM Evaluations

  • Appendix E

    Case Studies: Technology-Based Health Care Collaborative Learning & Capacity- Building Models

  • Appendix F

    Inventory

主题Community-Based Health Care ; Cost-Effectiveness in Health Care ; Evidence Based Health Practice ; Health Care Access ; Health Care Quality Measurement ; Health Care Services Capacity ; Telemedicine
URLhttps://www.rand.org/pubs/research_reports/RR2934.html
来源智库RAND Corporation (United States)
引用统计
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/523752
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Shira H. Fischer,Adam J. Rose,Ryan K. McBain,et al. Evaluation of Technology-Enabled Collaborative Learning and Capacity Building Models: Materials for a Report to Congress. 2019.
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