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Peer-reviewedCC BY-NCHealth affairs scholar

9-1-1, what is your emergency? Human-centered artificial intelligence, language access and health policy.

  • Esmeralda Melgoza1
  • Diego Xavier Torres1
  • Elaine Hsiang1
  • Rohan E Shah2
  • Eli Carrillo1
  • Kenneth Miller1
  • Jennifer A Newberry1
  • Arturo Vargas Bustamante3
  1. 1Department of Emergency Medicine, Stanford University, Palo Alto, CA 94304, United States.
  2. 2Bellarmine College Preparatory, San Jose, CA 95126, United States.
  3. 3Department of Health Policy and Management, UCLA, Los Angeles, CA 90095, United States.
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Abstract

Introduction

Emergency medical dispatch (EMD) is a critical yet understudied entry point into the US healthcare system. Given the increasing adoption of artificial intelligence (AI) in healthcare, we examine 9-1-1 telecommunicators' perspectives on AI integration in EMD.Methods

We conducted a qualitative analysis of open-ended responses from a cross-sectional electronic survey of 9-1-1 telecommunicators who primarily manage emergency medical calls at three 9-1-1 call centers in California between February and April 2026.Results

Eight themes emerged from the study: (1) 9-1-1 telecommunicators generally viewed human-centered AI as a tool to supplement, rather than replace human expertise; (2) the importance of maintaining human connection and empathy; (3) concerns related to liability, accountability, and data security; (4) the need to differentiate between emergency and non-emergency calls; (5) 9-1-1 caller location identification; (6) 9-1-1 caller language identification; 7) delays in connecting with interpreters; and (8) AI performance under "less-than-ideal" conditions.Policy implications

These findings highlight the importance of human-centered, equity-focused approaches to AI integration in EMD, including proactive policy development, implementation, and evaluation.

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Cite

BibTeXRIS
BibTeX
@article{melgoza2026what,
  title = {{9-1-1, what is your emergency? Human-centered artificial intelligence, language access and health policy.}},
  author = {Esmeralda Melgoza and Diego Xavier Torres and Elaine Hsiang and Rohan E Shah and Eli Carrillo and Kenneth Miller and Jennifer A Newberry and Arturo Vargas Bustamante},
  journal = {Health affairs scholar},
  year = {2026},
  month = sep,
  doi = {10.1093/haschl/qxag262},
  url = {https://europepmc.org/article/MED/42948637},
  note = {CC BY-NC},
}
RIS
TY  - JOUR
TI  - 9-1-1, what is your emergency? Human-centered artificial intelligence, language access and health policy.
AU  - Esmeralda Melgoza
AU  - Diego Xavier Torres
AU  - Elaine Hsiang
AU  - Rohan E Shah
AU  - Eli Carrillo
AU  - Kenneth Miller
AU  - Jennifer A Newberry
AU  - Arturo Vargas Bustamante
PY  - 2026
DA  - 2026/09/25
JO  - Health affairs scholar
DO  - 10.1093/haschl/qxag262
UR  - https://europepmc.org/article/MED/42948637
AB  - Introduction  Emergency medical dispatch (EMD) is a critical yet understudied entry point into the US healthcare system. Given the increasing adoption of artificial intelligence (AI) in healthcare, we examine 9-1-1 telecommunicators' perspectives on AI integration in EMD.Methods  We conducted a qualitative analysis of open-ended responses from a cross-sectional electronic survey of 9-1-1 telecommunicators who primarily manage emergency medical calls at three 9-1-1 call centers in California between February and April 2026.Results  Eight themes emerged from the study: (1) 9-1-1 telecommunicators generally viewed human-centered AI as a tool to supplement, rather than replace human expertise; (2) the importance of maintaining human connection and empathy; (3) concerns related to liability, accountability, and data security; (4) the need to differentiate between emergency and non-emergency calls; (5) 9-1-1 caller location identification; (6) 9-1-1 caller language identification; 7) delays in connecting with interpreters; and (8) AI performance under "less-than-ideal" conditions.Policy implications  These findings highlight the importance of human-centered, equity-focused approaches to AI integration in EMD, including proactive policy development, implementation, and evaluation.
SN  - 2976-5390
ER  -