1887
Volume 2021, Issue 1
  • ISSN: 1999-7086
  • EISSN: 1999-7094

Abstract

The time to initial physician contact or time for medical doctor (tMD) is one of the crucial key performance indicators for the emergency department (ED). The “tMD” helps in improving medical care, administrative benefits, and operational changes. The main aim of this study was to assess the effects of different operational changes on tMD. The study was a prospectively designed analysis for one year. Data were collected via the study center's electronic records. The study was divided into three operational events (increase in number of consultants, change of shift timings, and increase in consultants covering a shift) in comparison with the baseline (prestudy) period. Data were then downloaded and imported into the statistical software package Stata for a detailed analysis. The study commenced on July 1, 2016, with a 52-week period and 418,899 patient encounters. The coefficient for tMD slope improvement as compared with baseline with confidence interval (CI) and value was: Phase 1: −2.5 [CI: −4.1 to −0.97 ( = 0.002)]; Phase 2: −1.6 [CI: −2.8 to −0.37 ( = 0.031)]; and Phase 3: −2.4 [CI: −3.4 to −1.4 ( < 0.001)]. The study phases showed a significant improvement over the baseline study period. The study results indicate that different types of interventions (e.g.,., changing shift times, increasing total hours of MD coverage throughout the day) had demonstrated different apparent effects in this study's ED. Further work in this study's ED should aim to continue to reduce absolute tMD and decrease variation by homogenizing dispersion as much as possible across the 24 hours of a day. ED has no control over the concentration or spread of visitors over the period of the day. The data were useful for guiding operations planning both during the study period and thereafter, as operations continue to focus on optimizing tMD.

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2021-06-24
2024-04-20
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References

  1. Xi W, Dalal V. Impact of Family Medicine Resident Physicians on Emergency Department Wait Times and Patients Leaving Without Being Seen. CJEM. 2015:1–9.
    [Google Scholar]
  2. Lucas J, Batt RJ, Soremekun OA. Setting wait times to achieve targeted left-without-being-seen rates. The American journal of emergency medicine. 2014; 32:(4):342–5.
    [Google Scholar]
  3. Shaikh SB, Jerrard DA, Witting MD, Winters ME, Brodeur MN. How long are patients willing to wait in the emergency department before leaving without being seen? The western journal of emergency medicine. 2012; 13:(6):463–7.
    [Google Scholar]
  4. Welch S, Dalto J. Improving door-to-physician times in 2 community hospital emergency departments. American journal of medical quality: the official journal of the American College of Medical Quality. 2011; 26:(2):138–44.
    [Google Scholar]
  5. Preyde M, Crawford K, Mullins L. Patients’ satisfaction and wait times at Guelph General Hospital Emergency Department before and after implementation of a process improvement project. CJEM. 2012; 14:(3):157–68.
    [Google Scholar]
  6. Fernandes CM, McLeod S, Krause J, Shah A, Jewell J, Smith B, et al. Reliability of the Canadian Triage and Acuity Scale: interrater and intrarater agreement from a community and an academic emergency department. CJEM. 2013; 15:(4):227–32.
    [Google Scholar]
  7. Schwab RA, DelSorbo SM, Cunningham MR, Craven K, Watson WA. Using statistical process control to demonstrate the effect of operational interventions on quality indicators in the emergency department. Journal for healthcare quality: official publication of the National Association for Healthcare Quality. 1999; 21:(4):38–41.
    [Google Scholar]
  8. Pathan SA, Bhutta ZA, Moinudheen J, Jenkins D, Silva AD, Sharma Y, et al. Marginal analysis in assessing factors contributing time to physician in the Emergency Department using operations data. Qatar Med J. 2016; 2016:(2):18.
    [Google Scholar]
  9. Qualls M, Pallin DJ, Schuur JD. Parametric versus nonparametric statistical tests: the length of stay example. Acad Emerg Med. 2010; 17:(10):1113–21.
    [Google Scholar]
  10. Pielsticker S, Whelan L, Arthur AO, Thomas S. Identifying Patient Door-to-Room Goals to Minimize Left-Without-Being-Seen Rates. The western journal of emergency medicine. 2015; 16:(5):611–8.
    [Google Scholar]
  11. Rousseeux PJ, Croux C. Alternatives to the median absolute deviation. J American Statistical Assoc. 1993; 88:(424):1273–83.
    [Google Scholar]
  12. Leys C, Ley C, Klein O, Bernard P, Licata L. Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median. J Experimental Social Psych. 2013; 49:(4):764–8.
    [Google Scholar]
  13. Cox NJ. Stata tip 68: Week assumptions. Stata Journal. 2010; 10:(4):682–5.
    [Google Scholar]
  14. Mitchell MN. Interpreting and visualizing regression models using Stata. 1 ed. College Station TX: Stata Press; 2012.
    [Google Scholar]
  15. Whelan L, Burns B, Brantley M, Haas T, Arthur AO, Thomas SH. Mathematical Modeling of the Impact of Hospital Occupancy: When Do Dwindling Hospital Beds Cause ED Gridlock? Advances in Emergency Medicine. 2014; 2014:5:.
    [Google Scholar]
  16. Eitel DR, Rudkin SE, Malvehy MA, Killeen JP, Pines JM. Improving service quality by understanding emergency department flow: a White Paper and position statement prepared for the American Academy of Emergency Medicine. The Journal of emergency medicine. 2010; 38:(1):70–9.
    [Google Scholar]
  17. McClelland MS, Jones K, Siegel B, Pines JM. A field test of time-based emergency department quality measures. Ann Emerg Med. 2012; 59:(1):1–10e2.
    [Google Scholar]
  18. Milsten A, Klein J, Liu Q, Vibhakar N, Linder L. Retrospective Analysis of Quality Improvement Throughput Measures at a High-Volume Community Emergency Department. Journal for healthcare quality: official publication of the National Association for Healthcare Quality. 2013.
    [Google Scholar]
  19. Pines JM, Prabhu A, Hilton JA, Hollander JE, Datner EM. The effect of emergency department crowding on length of stay and medication treatment times in discharged patients with acute asthma. Acad Emerg Med. 2010; 17:(8):834–9.
    [Google Scholar]
  20. Sayah A, Rogers L, Devarajan K, Kingsley-Rocker L, Lobon LF. Minimizing ED Waiting Times and Improving Patient Flow and Experience of Care. Emergency medicine international. 2014;2014:981472.
    [Google Scholar]
  21. Pathan S, Bhutta Z, Moinudheen J, Jenkins D, Farook S, Qureshi I, et al. Partial replacement of board-certified specialist-grade physicians with emergency medicine trainees in a busy Emergency Department: Lack of adverse effect on time-to-physician. J Emerg Med Trauma Acute Care. 2017; 2017:(7).
    [Google Scholar]
  22. Bair AE, Song WT, Chen YC, Morris BA. The impact of inpatient boarding on ED efficiency: a discrete-event simulation study. Journal of medical systems. 2010; 34:(5):919–29.
    [Google Scholar]
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