University of South Carolina University of California, Davis JUST A MINUTE:  The Effect of Emergency Department Wait Time on the Cost of Care Lindsey Woodworth University of South Carolina James F. Holmes University of California, Davis

BACKGROUND Wait times in U.S. emergency departments (EDs) are long In 2013, over 17% of ED patients waited more than one hour to reach the physician Long ED wait times are associated with adverse clinical outcomes (e.g., Fee et al. 2007) If patients’ conditions deteriorate with time, then longer ED wait times could exacerbate treatment costs Fee, C., Weber, E. J., Maak, C. A., & Bacchetti, P. (2007). Effect of emergency department crowding on time to antibiotics in patients admitted with community-acquired pneumonia. Annals of Emergency Medicine, 50(5), 501-509. Sun, B. C., Hsia, R. Y., Weiss, R. E., Zingmond, D., Liang, L. J., Han, W., ... & Asch, S. M. (2013). Effect of emergency department crowding on outcomes of admitted patients. Annals of Emergency Medicine, 61(6), 605-611.

BACKGROUND Annual U.S. healthcare expenditures exceed $3T Highest estimates suggest ~10% of total healthcare expenditures exhausted in emergency care (Lee, Schuur & Zingk 2013) The policy complication is that reducing healthcare expenditures generally compromises patients’ outcomes Maybe targeting timeliness of care could both reduce costs and improve patients’ outcomes…

QUESTION What is the causal effect of emergency department (ED) wait time on the total cost to care for a patient?

Costi = β0 + β1Waiti + β2X’ + εi QUESTION Empirical Challenge: Costi = β0 + β1Waiti + β2X’ + εi Acuity captured by εi and correlated with Waiti In OLS models, β1 is persistently negative

AMBULANCE

TRIAGE STATIONS

TRIAGE STATIONS 1 5

TRIAGE WAITING STATIONS ROOM 1 5

TRIAGE WAITING STATIONS ROOM 2 4 1 5

TRIAGE WAITING STATIONS ROOM PHYSICIAN 2 4 1 5

TRIAGE WAITING STATIONS ROOM PHYSICIAN 2 4 1 5

TRIAGE WAITING STATIONS ROOM PHYSICIAN 2 4 5

TRIAGE WAITING STATIONS ROOM PHYSICIAN 2 4 5 3

TRIAGE WAITING STATIONS ROOM PHYSICIAN 2 4 5 3

TRIAGE WAITING STATIONS ROOM PHYSICIAN 3 2 4 5

 

TRIAGING A one level change in a patient’s triage level can have a big effect on their wait time How exact are triage level assignments? Patients are perpetually bumped back as long as other patients arrive with lower levels

TRIAGING

TRIAGING NOTES: There is room for inter-nurse variation in triaging Two triage nurses are always working concurrently Patients’ acuities overlap between nurses Triage nurses only assign triage levels 1 – And a one level change can have a huge impact on wait time

IDENTIFICATION Instrumental variables, using the stringency of a patient’s triage nurse as the instrument for their wait time.   Assumptions: Triage nurse stringency affects patients’ wait times The stringency a patient is exposed to is effectively random Exposure to a stringent triage nurse moves patients’ wait times monotonically

DATA Medical Records Presented at large urban academic medical center’s ED, July ‘08 – April ‘13 (ages 18-89) Time stamps Triage nurse ID Triage level Demographics Billing Records Reflecting all utilization throughout the course of patient’s stay in the health system Aggregate charges‡ Aggregate payments Final diagnosis ‡ Multiplied by hospital’s cost-to- charge ratio

DATA Mean Wait Time 1hr 23min Total Charge $39,754 Total Payment Descriptive Statistics DATA Descriptive Statistics   Mean Wait Time 1hr 23min Total Charge $39,754 Total Payment $6,334 Total Cost* $6,395 Male 50.4% Age 45.3 years Triage Assignment: Level 1 17.8% Level 2 30.4% Level 3 36.5% Level 4 14.6% Level 5 0.7% N=187,149

DATA Balance in Mean Patient Characteristics Stringent=1   Stringent=1 (Treatment Group) Stringent=0 (Control Group) Share Male 50.5% 50.3% Mean Age* 45.0 years 46.1 years Final Diagnosis: Chest pain, unspecified (ICD-9: 786.50) 3.4% 3.3% Headache (ICD-9: 784.0) 1.7% Abdominal pain, other specified site (ICD-9: 789.09)* 1.6% 1.4% Urinary tract infection, site not specified (ICD-9: 599.0) 1.5% Unspecified septicemia (ICD-9: 038.9)* 1.3% N=134,884 N=52,265 * Denotes statistically significant difference in means

ESTIMATION  

ESTIMATION 2SLS identifies LATE (estimates apply to patients at thresholds) To capture effect heterogeneity, stratify sample by neighboring triage levels L1 L2 L3 L4 L5

ESTIMATION 2SLS identifies LATE (estimates apply to patients at thresholds) To capture effect heterogeneity, stratify sample by neighboring triage levels To ensure monotonicity, restrict to times without upfront care L1 L2 L3 L4 L5

First-Stage Estimates   Wait Time (hours) A. Level 1 & 2 Patients (n=89,789) Stringent Nurse 0.0612 *** (0.0128) F-Stat: 55.77 Mean Wait: 59min B. Level 2 & 3 Patients (n=124,700) 0.1450 (0.0150) F-Stat: 80.59 Mean Wait: 1hr 38min C. Level 3 & 4 Patients† (n=17,433) 0.0642 * (0.0376) F-Stat: 17.17 Mean Wait: 1hr 54min D. Level 4 & 5 Patients (n=28,520) 0.0287 (0.0299) F-Stat: 28.49 Mean Wait: 1hr 21min † Omits 6am-9:59pm arrivals (so Level 4 patients are never susceptible to upfront care).

X 2SLS Estimates ln(Cost) A. Level 1 & 2 Patients (n=89,789)   ln(Cost) A. Level 1 & 2 Patients (n=89,789) Wait Time in Hours 0.3045 (0.1444) ** [0.1795] * Mean Cost: $10,822 B. Level 2 & 3 Patients (n=124,700) 0.2135 (0.0527) *** [0.0714] Mean Cost: $5,315 C. Level 3 & 4 Patients† (n=17,433) 0.1446 (0.2884) [0.3107] Mean Cost: $2,560 D. Level 4 & 5 Patients (n=28,520) X Mean Cost: $819 † Omits 6am-9:59pm arrivals. (SE unclustered) [SE clustered by “shift”]

ROBUSTNESS CHECKS Sensitivity to controls Descriptive Statistics ROBUSTNESS CHECKS Sensitivity to controls Sensitivity to different measure of “cost” (i.e., payment)

EXTERNAL VALIDITY 30% 21% L1 L2 L3 L4 L5

EXTERNAL VALIDITY 30% 21% L1 L2 L3 L4 L5

EXTERNAL VALIDITY Calculate back-of-the-envelope approximations for cost-savings from reducing wait times in EDs with different distributions of patient acuity If reduce each patient’s wait time 1/2 hour… Costs ~7% ↓ in the average U.S. ED Costs ~10% ↓ in our relatively high-acuity ED ■8(−(0.30/2) $𝟏𝟓,𝟐𝟐𝟓 〖𝑆ℎ𝑎𝑟𝑒〗_1−(0.21/2) $𝟖,𝟐𝟑𝟗 〖𝑆ℎ𝑎𝑟𝑒〗_2@)/■8(@$𝟏𝟓,𝟐𝟐𝟓 〖𝑆ℎ𝑎𝑟𝑒〗_1+$𝟖,𝟐𝟑𝟗 〖𝑆ℎ𝑎𝑟𝑒〗_2+$𝟐,𝟖𝟖𝟑 〖𝑆ℎ𝑎𝑟𝑒〗_3+$𝟖𝟑𝟖 〖𝑆ℎ𝑎𝑟𝑒〗_4+$𝟒𝟎𝟒 〖𝑆ℎ𝑎𝑟𝑒〗_5 ) The higher an ED’s share of high-acuity patients, the greater the opportunity for cost-savings Starting from a mean wait time of ~1/2 hour for Level 1 patients

CONCLUSION There is concern that long ED wait times might exacerbate costs It is difficult to identify the effect of ED wait time on costs because patients are seen in order of acuity We exploit the quasi-random assignment of patients to triage nurses (who differ in stringency) to identify causal effects Average ED: 1-3% patients L1 (2%) 20-30% patients L2 (25%) 30-40% patients L3 (40%) 20-35% patients L4-5 (30% L4, 3% L5) Our ED: 17.8% patients L1 30.4% patients L2 36.5% patients L3 14.6% patients L4 0.7% patients L5

CONCLUSION Evidence that long ED wait times exacerbate costs, with effect intensification as acuity heightens From a policy perspective, minimizing wait times could potentially both improve patients’ health and lower healthcare expenditures Our results reiterate the importance of triaging; EDs could focus on precise triaging as a first step for cost-minimization Average ED: 1-3% patients L1 (2%) 20-30% patients L2 (25%) 30-40% patients L3 (40%) 20-35% patients L4-5 (30% L4, 3% L5) Our ED: 17.8% patients L1 30.4% patients L2 36.5% patients L3 14.6% patients L4 0.7% patients L5

Thank You Average ED: 1-3% patients L1 (2%) 20-30% patients L2 (25%) 20-35% patients L4-5 (30% L4, 3% L5) Our ED: 17.8% patients L1 30.4% patients L2 36.5% patients L3 14.6% patients L4 0.7% patients L5

Descriptive Statistics

Sensitivity to Controls ln(Cost) A. Level 1 & 2 Patients (n=89,789)   ln(Cost) A. Level 1 & 2 Patients (n=89,789) M A I N S P E C I F I C A T I O N Wait Time in Hours 0.3078 0.1856 0.2806 0.2347 0.4040 (0.1681) * (0.1680) (0.1513) (0.1593) (0.1575) *** [0.2000] [0.2279] [0.2086] [0.1950] [0.1972] ** Mean Cost: $10,822 B. Level 2 & 3 Patients (n=124,700) 0.1925 0.3224 0.3860 0.1804 0.2404 (0.0579) (0.0573) (0.0640) (0.0475) (0.0516) [0.0740] [0.0879] [0.0983] [0.0642] [0.0691] Mean Cost: $5,315 C. Level 3 & 4 Patients† (n=17,433) 0.1884 0.0539 0.3364 0.0027 0.0824 (0.3306) (0.2149) (0.4426) (0.1608) (0.2596) [0.3560] [0.2366] [0.5040] [0.1702] [0.2741] Mean Cost: $2,560 Controls: Time of Presentation ü Clinical Characteristics Payer Replace $0 with $0.01 (affects ~1%) No Yes <1% of sample has $0 charges. † Omits 6am-9:59pm arrivals. (SE unclustered) [SE clustered by “shift”]

X Alternative Measure of “Cost” (i.e., Payment) First-Stage 2SLS   First-Stage 2SLS Stringent → Wait Wait → ln(Payment) A. Level 1 & 2 Patients (n=71,516) 0.0492 *** 0.3020 (0.0137) (0.2420) F-Stat: 19.13 [0.2728] Mean Wait: 59min Mean Payment: $11,367 B. Level 2 & 3 Patients (n=91,496) 0.1304 0.1407 (0.0170) (0.0773) * F-Stat: 24.72 [0.0884] Mean Wait: 1hr 38min Mean Payment: $4,722 C. Level 3 & 4 Patients† (n=11,440) 0.0366 X (0.0452) F-Stat: 6.01 Mean Wait: 1hr 54min Mean Payment: $1,847 D. Level 4 & 5 Patients (n=16,598) 0.0085 (0.0384) F-Stat: 8.13 Mean Wait: 1hr 21min Mean Payment: $484 † Omits 6am-9:59pm arrivals. (SE unclustered) [SE clustered by “shift”]