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1.
Acad Emerg Med ; 27(2): 139-147, 2020 02.
Article in English | MEDLINE | ID: mdl-31733003

ABSTRACT

OBJECTIVES: More than 2 million patients present to a U.S. emergency department (ED) annually and leave without being seen (LWBS) due to delays in initiating care. We evaluated whether tele-intake at the time of presentation would reduce LWBS rates and ED throughput measures. METHODS: We conducted a before-and-after study at an urban community hospital. The intervention was use of a tele-intake physician to triage patients from 11 am to 6 pm, 7 days per week. Tele-intake providers performed a triage history and physical examination, documented findings, and initiated orders in the medical record. We assessed the impact of this program using the domains of the National Quality Forum framework evaluating access, provider experience, and effectiveness of care. The main outcome was 24-hour LWBS rate. Secondary outcomes were overall door to provider and door to disposition times, left without treatment complete (LWTC), left against medical advice (AMA), left without treatment (LWOT), and physician experience. We compared the 6-month tele-intake period to the same period from the prior year (October 1 to April 1, 2017 vs. 2016). Additionally, we conducted a survey of our physicians to assess their experience with the program. RESULTS: Total ED volume was similar in the before and after periods (19,892 patients vs. 19,646 patients). The 24-hour LWBS rate was reduced from 2.30% (95% confidence interval [CI] = 2.0% to 2.5%) to 1.69% (95% CI = 1.51% to 1.87%; p < 0.001). Overall door to provider time decreased (median = 19 [interquartile range {IQR} = 9 to 38] minutes vs. 16.2 [IQR = 7.8 to 34.3] minutes; p < 0.001), but ED length of stay for all patients (defined as door in to door out time for all patients) minimally increased (median = 184 [IQR = 100 to 292] minutes vs. 184.3 [IQR = 104.4 to 300] minutes; p < 0.001). There was an increase in door to discharge times (median = 146 [IQR = 83 to 231] minutes vs. 148 [IQR = 88.2 to 233.6] minutes; p < 0.001) and door to admit times (median = 330 [IQR = 253 to 432] minutes vs. 357.6 [IQR = 260.3 to 514.5] minutes; p < 0.001). We saw an increase in LWTC (0.59% [95% CI = 0.49% to 0.70%] vs. 1.1% [95% CI = 0.9% to 1.2%]; p < 0.001), but no change in AMA (1.4% [95% CI = 1.2% to 1.6%] vs. 1.6% [95% CI = 1.4% to 1.78%]; p = 0.21) or LWOT (4.3% [95% CI = 4.1% to 4.6%] vs. 4.4% [95% CI = 4.1% to 4.7%]; p = 0.7). Tele-intake providers thought tele-intake added value (12/15, 80%) and allowed them to effectively address medical problems (14/15, 95%), but only (10/15, 67%) thought that it was as good as in-person triage. Of the receiving physicians, most agreed with statements that tele-intake did not interfere with care (19/22, 86%), helped complement care (19/21, 90%), and gave the patient a better experience (19/22, 86%). CONCLUSIONS: Remote tele-intake provided in an urban community hospital ED reduced LWBS and time to provider but increased LWTC rates and had no impact on LWOT.


Subject(s)
Emergency Service, Hospital/organization & administration , Telemedicine/methods , Triage/methods , Adult , Benchmarking , Female , Humans , Length of Stay/statistics & numerical data , Male , Middle Aged , Patient Dropouts/statistics & numerical data , Time Factors , Treatment Refusal/statistics & numerical data
2.
J Emerg Med ; 47(4): 479-85, 2014 Oct.
Article in English | MEDLINE | ID: mdl-24656983

ABSTRACT

BACKGROUND: Self-reported pain scales are commonly used in emergency departments (EDs). The 11-point (0-10) numerical rating scale is a commonly used scale for adults visiting EDs in the United States. Despite their widespread use, little is known about whether distribution of pain scores has remained consistent over time. OBJECTIVES: The objective of this study is to determine if there were upwards or downwards (monotonic) trends in pain scores over time at a single hospital. METHODS: Retrospective chart review for the years 2003-2011. All pain scores for May 1(st) and 2(nd) of those years were collected. Multinomial logistic regression was used to model the probability of a patient rating their pain in each of 11 categories (scores 0 to 10) as a function of the calendar year. Additional analysis was carried out with pain scores grouped into four categories. RESULTS: Data were collected from 2934 patient charts. Pain scores were recorded in 2136 charts, and 1637 of these pain scores were above zero (i.e., 1-10). The pain score distribution differed significantly over time (p = 0.001); however, there was no monotonic (single-direction) trend. CONCLUSION: Although there were significant shifts in pain scores over time, there is not a significant monotonic trend. At this hospital, there was no "inflation" or "deflation" in pain scores over time. Shifts in distribution, even when not in a single direction, may be important for researchers examining pain scores in the ED.


Subject(s)
Emergency Service, Hospital/statistics & numerical data , Pain Measurement/standards , Adolescent , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , Female , Humans , Infant , Logistic Models , Male , Middle Aged , Pain Measurement/statistics & numerical data , Pain Measurement/trends , Retrospective Studies , Self Report , Time Factors , United States , Young Adult
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