Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

A randomized controlled trial evaluating the effects of nurse-led triage of 911 calls

A Publisher Correction to this article was published on 27 June 2024

This article has been updated


To better connect non-emergent 911 callers to appropriate care, Washington, DC, routed low-acuity callers to nurses. Nurses could provide non-emergent transportation to a health centre, recommend self-care or return callers to the traditional 911 system. Over about one year, 6,053 callers were randomized (1:1) to receive a business-as-usual response (ncontrol = 3,023) or further triage (ntreatment = 3,030). We report on seven of nine outcomes, which were pre-registered ( The proportion of calls resulting in an ambulance dispatch dropped from 97% to 56% (β = −1.216 (−1.324, −1.108), P < 0.001), and those resulting in an ambulance transport dropped from 73% to 45% (β = −3.376 (−3.615, −3.137), P < 0.001). Among those callers who were Medicaid beneficiaries, within 24 hours, the proportion of calls resulting in an emergency department visit for issues classified as non-emergent or primary care physician (PCP) treatable dropped from 29.5% to 25.1% (β = −0.230 (−0.391, −0.069), P < 0.001), and the proportion resulting in the caller visiting a PCP rose from 2.5% to 8.2% (β = 1.252 (0.889, 1.615), P < 0.001). Over the longer time span of six months, we failed to detect evidence of impacts on emergency department visits, PCP visits or Medicaid expenditures. From a safety perspective, 13 callers randomized to treatment were eventually diagnosed with a time-sensitive illness, all of whom were quickly triaged to an ambulance response. These short-term effects suggest that nurse-led triage of non-emergent calls can safely connect callers to more appropriate, timely care.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: CONSORT diagram.
Fig. 2: Percentages of the control and treatment groups receiving ambulance dispatch and transport.
Fig. 3: Percentages of the control and treatment groups visiting an ED or PCP.

Similar content being viewed by others

Data availability

The data analysed in this paper were provided by DC’s FEMS, Office of the Chief Technology Officer and DHCF and contain protected health information. To protect privacy, we cannot publicly post individual-level data. Qualified researchers and relevant approvals including ethical approval can request access to the de-identified data about this trial from the corresponding author. A formal contract will be signed, and an independent data protection agency should oversee the sharing process to ensure the safety of the data.

Code availability

All code used to produce this analysis is publicly available at

Change history


  1. 9-1-1 Statistics (National Emergency Number Association, 2020).

  2. Sporer, K. A. 911 patient redirection. Prehosp. Disaster Med. 32, 589–592 (2017).

    Article  PubMed  Google Scholar 

  3. Reducing Emergency Department Overuse: A $38 Billion Opportunity (New England Health Institute, 2011).

  4. Bruijns, S. R. et al. Effect of introduction of nurse triage on waiting times in a South African emergency department. Emerg. Med. J. 25, 395–397 (2008).

    Article  CAS  PubMed  Google Scholar 

  5. Mills, J. et al. Effectiveness of nurse triage in the emergency department of an urban county hospital. J. Am. Coll. Emerg. Physicians 5, 877–882 (1976).

    Article  CAS  Google Scholar 

  6. A Model for Better Community Healthcare: How One EMS System Achieved the Triple Aim from a Federal Health Care Innovation Award Grant (REMSA, 2017).

  7. Gardett, I. et al. 911 emergency communication nurse triage reduces EMS patient costs and directs patients to high-satisfaction alternative point of care. Ann. Emerg. Dispatch Response 3, 8–13 (2015).

    Google Scholar 

  8. Møller, T. P. et al. Why and when citizens call for emergency help: an observational study of 211,193 medical emergency calls. Scand. J. Trauma Resusc. Emerg. Med. 23, 88 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Zinger, N. D., Blomberg, S. N., Lippert, F., Krafft, T. & Christensen, H. C. Impact of integrating out-of-hours services into Emergency Medical Services Copenhagen: a descriptive study of transformational years. Int. J. Emerg. Med. 15, 40 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Eastwood, K. et al. A novel approach for managing the growing demand for ambulance services by low-acuity patients. Aust. Health Rev. 40, 378–384 (2015).

    Article  Google Scholar 

  11. District of Columbia Fire and Emergency Medical Services Integrated Healthcare Collaborative, Final Report (District of Columbia Fire & Emergency Medical Services, 2017).

  12. Berchick, E. R. et al. Health Insurance Coverage in the United States: 2018 (US Department of Commerce, 2019).

  13. DeLeire, T. in Health and Labor Markets (eds. Tatsiramos, K. & Polachek, S. W.) 155–194 (Emerald, 2019).

  14. Finkelstein, A. N. et al. Effect of Medicaid coverage on ED use—further evidence from Oregon’s experiment. N. Engl. J. Med. 375, 1505–1507 (2016).

    Article  PubMed  Google Scholar 

  15. Lavetti, K. J. et al. How Do Low-Income Enrollees in the Affordable Care Act Marketplaces Respond to Cost-Sharing? Technical Report No. 26430 (National Bureau of Economic Research, 2019).

  16. Taubman, S. L. et al. Medicaid increases emergency-department use: evidence from Oregon’s health insurance experiment. Science 343, 263–268 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Datta, S. & Mullainathan, S. Behavioral design: a new approach to development policy. Rev. Income Wealth 60, 7–35 (2014).

    Article  Google Scholar 

  18. Rose, A. J. et al. Primary care visit regularity and patient outcomes: an observational study. J. Gen. Intern. Med. 34, 82–89 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Daniels, O. District triage line continues to trim non-emergency calls from 911. Washington Post 20 November (2023).

  20. Python Language Reference, v.3.8.6 (Python Software Foundation, 2020).

  21. R: a language and environment for statistical computing (R Foundation for Statistical Computing, 2021).

  22. Briggs, J. K. Telephone Triage Protocols for Nurses (Wolters Kluwer Health, 2020).

  23. Finkelstein, A. et al. Health care hotspotting—a randomized, controlled trial. N. Engl. J. Med. 382, 152–162 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Billings, J. et al. Emergency Room Use: The New York Story (Commonwealth Fund, 2000).

Download references


This work would not be possible without the support of M. Bowser (mayor), K. Donahue (city administrator), R. Young (former city administrator), S. Quinney (director of The Lab @ DC), G. M. Dean (retired fire chief), FEMS, the Office of Unified Communications, the DHCF, the FQHCs, the DC Primary Care Association, the Department of Health and the Office of the Deputy Mayor for Public Safety and Justice. We thank the following for their time and assistance in making this evaluation possible: M. Baisley, A. Beaton, V. Bishop, D. Braman, R. Breslin, S. Brown, I. Bucksell, J. Coombs, D. Corcoran, T. Curtis, O. Dedner, J. Doleac, N. Donnelly, J. Duff, T. Dutta, L. Edmonson, B. Egar, K. Gan, H. Gil, A. Grady, J. Greenberg, K. Holmes, E. Holve, A.-T. Huang, A. Huberts, T. Kavaleri, D. Kornfield, E. Koshkin, B. Kreiswirth, B. Krucoff, K. Liebowitz, M. MacCarthy, K. Minnich, A. Mauro, L. Nesbitt, C. Nguyen, C. Nwaete, P. Oandasan, K.Y. Oh, J. Reed, M. Reed, S. Roque, C. Scholsberg, N. Smith, D. Stanescu, P. Testa, T. Thangalvadi, W. Turnage, J. Wedeles, D. Weinroth, J. Weissfeld, O. Whittaker, M. Williamson, S. Willig and J. Wobbleton. We especially thank M. A. Bates, N. Choudhry and B. Özler for reviewing the pre-analysis plan and M. Welch for her substantive and project management contributions during the review process. The intervention as a whole was funded by general appropriations from the District of Columbia. R.P.H., as the medical director of DC FEMS, was also funded through DC appropriations. C.H., K.H.W., R.T.M. and D.Y. were funded through the Laura and John Arnold Foundation (now Arnold Ventures). R.A.J. was funded through the ABF/JPB Foundation Access to Justice Scholars programme for time supporting the work. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations



Conceptualization: C.H., R.P.H., R.T.M., K.H.W. and D.Y. Methodology: C.H., R.T.M., K.H.W. and D.Y. Visualization: R.A.J. and K.H.W. Coding and analysis—original analysis: R.A.J. and K.H.W. Coding and analysis—review and supplemental: R.A.J., R.T.M. and K.H.W. Project administration: C.H. and R.P.H. Supervision: C.H. and R.T.M. Writing—original draft: C.H., R.A.J. and K.H.W. Writing—review and editing: C.H., R.P.H., R.A.J., R.T.M., K.H.W. and D.Y.

Corresponding author

Correspondence to Kevin H. Wilson.

Ethics declarations

Competing interests

R.P.H. was during the commission of this study the medical director of DC FEMS and draws a salary from the District of Columbia. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Human Behaviour thanks Stefan Morreel and Armann Ingolfsson for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Overall counts of treated and control group callers aggregated to the monthly level.

The figure shows the raw counts of treatment and control group callers for each of the eleven months in the study period. We see a sharp rise after the triage line was expanded to 24 hours per day.

Extended Data Fig. 2 Balance plot: treatment and control group (Medicaid beneficiary sample).

The figure shows the standardized mean difference for each attribute between the treatment and control group, which helps us compare variables on different scales (for example, years versus percentages).

Extended Data Fig. 3 Detailed outcomes of the safety analysis.

The flow chart shows a low incidence of safety events.

Extended Data Table 1 Treatment effects on ambulance use by month
Extended Data Table 2 Breakdown of identifiers by ambulance status
Extended Data Table 3 Treatment and control group characteristics: Medicaid sample
Extended Data Table 4 Exact rates and proportions: Emergency department and primary care physician visits

Supplementary information

Supplementary Information

Four sections of supplementary discussion: safety analysis results, matching to Medicaid beneficiaries, departures from the pre-analysis plan and key sections of code.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wilson, K.H., Johnson, R.A., Hatzimasoura, C. et al. A randomized controlled trial evaluating the effects of nurse-led triage of 911 calls. Nat Hum Behav (2024).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI:


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing