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Empirical Analysis of the Effect Residents Have on Treatment Times in an Emergency Department David Anderson, John Silberholz, Bruce Golden, Mike Harrington,

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Presentation on theme: "Empirical Analysis of the Effect Residents Have on Treatment Times in an Emergency Department David Anderson, John Silberholz, Bruce Golden, Mike Harrington,"— Presentation transcript:

1 Empirical Analysis of the Effect Residents Have on Treatment Times in an Emergency Department David Anderson, John Silberholz, Bruce Golden, Mike Harrington, Jon Mark Hirshon POMS Annual Meeting, Denver 2013

2 Overview Broad Healthcare Landscape -Health Care Reform Bill, 2010 -Americans spent $2.3 trillion on health care in 2007 -Hospitals are one of the least efficient sectors University of Maryland Medical Center (UMMC) UMMCUMMC ED 700 beds 1,182 doctors 742 residents 55 beds 20% admission rate 46,000 patients/year 2

3 Residency Model Medical School Four years Classes, clinical rotations Residency First year: Internship, general medicine Next 3-7 years: Specialty Designed for teaching Attending Physician Private practice or hospital 3

4 Research Question What effects do residents have on the efficiency of the emergency department? - Longer or shorter patient treatment times? Residents are in the hospital to learn, but also treat patients One conjecture is that the teaching of residents takes time away from patient care and negatively impacts efficiency 4

5 Inconclusive Literature Medicare reimbursement rates consider the direct and indirect costs of training residents (Rosko, 1996) It has been argued that Medicare reimbursement rates overcompensate for the costs of training residents (Anderson & Lave, 1986; Custer & Wilke, 1991; Rogowski & Newhouse, 1992; Welch, 1987). Presence of residents increases faculty staffing requirements - attending physicians are required to spend time supervising and instructing the residents (DeBehnke, 2001) Teaching and treatment can occur simultaneously, meaning that residents can help to improve throughput (Knickman et al. 1992) 5

6 Observational Studies Residents Slow Down Treament: – Harvey et al. (2008) – New Zealand resident strike – Salazar et al. (2001) – Resident strike in the US – Lammers et al. (2003) – pre-post addition of residents Residents Help: – Theokary et al. (2011) – Residents increase treatment quality – Blake and Carter (1996) – When residents treat patients they help – Eappen et al. (2004) – Addition of anesthesiology residents – Offner et al. (2003) – Addition of trauma residents – Dowd et al. (2005) – As residents gain experience they increase efficiency 6

7 Resident Seminars Residents absent every Wednesday morning for a seminar No replacement workers hired Wednesday mornings provide a representative sample of all emergency department activity – Wide range of arrival rates – All types of patients and severities – Congestion levels vary as well 7

8 Advantages Over Previous Studies Short-term absence of residents – No operational changes No changes in staffing Quick turnover: easy to measure impact 8

9 Data Data was provided on 7395 patients Information on severity score, number of lab and radiology tests needed, arrival time, treatment time, congestion of the waiting room, and whether or not the patient was admitted to the hospital was given for each patient Resident presence was determined based on the time the patient was first treated 9

10 Arrival Rates 10

11 Regression Analysis Regressed treatment time on patient and treatment characteristics: Resident absence increases treatment times by almost 8% (exp.075 =.08) VariableCoefficientStd. Errort-valuep-value (Intercept)5.0020.020247.475<.001 NoRes0.0750.0342.2420.025 Line0.0100.0025.455<.001 Admit0.0880.0155.819<.001 NumLab0.0320.00135.847<.001 Labs0.3350.01818.716<.001 NumRad0.0570.00413.509<.001 Rad0.1480.0169.376<.001 Weekend-0.0440.013-3.311<.001 Sev1-0.1480.096-1.5440.123 sev20.0480.0172.7300.006 sev30.0310.0152.0800.038 sev4-0.1780.032-5.511<.001 sev5-0.5430.090-6.001<.001 (Adjusted R2 =.5355, N = 7935) 11

12 High Severity vs Low Severity Residents might play different roles when treating different types of patients Ran regressions on high and low severity patients separately Residents have a strong effect on lowering treatment times when treating high severity patients, but no noticeable effect when treating low severity patients 12

13 High Severity Results VariableCoefficientStd. Errort-valuep-value (Intercept) 5.0270.020245.581<.001 NoRes 0.0730.0342.1380.033 Line 0.0090.0024.784<.001 Admit 0.0900.0155.955<.001 Numlab 0.0320.00135.832<.001 Labs 0.3160.01817.242<.001 Numrad 0.0560.00413.331<.001 Rad 0.1430.0168.881<.001 Weekend -0.0550.014-4.010<.001 sev1 -0.1460.095-1.5280.126 sev2 0.0490.0172.8280.005 sev3 0.0290.0151.9870.047 (Adjusted R2 =.5133, N = 7549) 13

14 Low Severity Results VariableCoefficientStd. Errort-valuep-value (Intercept)4.2340.10440.558<.001 NoRes0.1100.1890.5810.562 Line0.0410.0113.711<.001 Admit0.0100.1270.0810.935 Numlab0.0350.0074.899<.001 Labs0.5530.0876.324<.001 Numrad0.1330.0373.610<.001 Rad0.1440.0931.5590.120 Weekend0.1350.0622.1830.030 sev40.2810.0992.8340.005 (Adjusted R2 =.5737, N = 341) 14

15 Morning Patients One possible source of endogeneity is that residents are only absent for patients treated in the morning We restrict the data to only those patients who began treatment between 7 am and 1 pm (the time of the seminars on Wednesday) Our results still hold 15

16 Morning Results VariableCoefficientStd. Errort-valuep-value (Intercept)4.6300.05584.908<.001 NoRes0.0680.0342.0080.045 Line0.0230.0063.792<.001 Admit0.1460.0314.669<.001 Numlab0.0300.00215.628<.001 Labs0.3280.0388.750<.001 Numrad0.0540.0095.901<.001 Rad0.1880.0335.763<.001 High0.3450.0546.359<.001 (Adjusted R 2 =.5712, N = 1768) 16

17 Survival Analysis Instead of measuring treatment times, we can measure discharge rate We compare discharge rate on Wednesday mornings to the discharge rate on other weekdays A higher discharge rate would imply that residents help to increase throughput 17

18 Survival Analysis Results VariableCoefficientStandard Error zPr(>|z|) Numlab0.00370.00550.66800.5044 Numrad-0.03580.0254-1.40900.1587 NoRes-0.25050.0860-2.91400.0036 Sev10.64030.45401.41000.1585 Sev2-0.04470.1023-0.43700.6622 Sev3-0.11400.0836-1.36400.1725 Sev4-0.03200.1932-0.16600.8685 Sev50.63170.58641.07700.2814 Line0.03270.01043.13100.0017 Labs-0.61330.1067-5.74900.0000 Rad-0.21980.0905-2.42900.0152 18

19 Different Patient Populations 19 Residents have a bigger impact on more severe populations

20 Conclusion Contrary to our original intuition, we have shown that residents speed up the treatment of patients in the emergency department This effect is especially strong when treating high severity patients We recommend that when possible, residents treat high severity patients 20

21 Future Work Quantify effect of each additional healthcare worker and compare nurses and nurse practitioners to residents Model doctor decisions explicitly, show how they move through ED Identify bottlenecks in the system Include data gathered in person to help model doctor movement 21

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