1. RACE, INCOME, AND OPERATIVE TIME Jeffrey H. Silber, M.D., Ph.D. Paul R. Rosenbaum, Ph.D. Xuemei Zhang, M.S. Orit Even-Shoshan, M.S. The Center for Outcomes Research, The Children’s Hospital of Philadelphia The Department of Pediatrics, Anesthesiology and Critical Care Medicine, PENN The Department of Statistics, The Wharton School, PENN The Leonard Davis Institute of Health Economics

2. Introduction Operative time is a common measure of surgical quality –Longer procedures are associated with higher infection rates –Longer procedures are associated with physicians-in-training

3. Measuring Operative Time Until now, studies analyzing operative time in the Medicare population have been limited to single (or very few) institutions. Operative time is usually defined as: –Surgical Time: Incision to closure –Anesthesia Time: Induction to Recovery Room

4. Measuring Operative Time in Medicare Patients In 1994, billing for Anesthetist and anesthesiologist services changed to a “by the minute” system Anesthetist bills (anesthesiologists, nurse anesthetists) from Medicare have never been utilized to examine procedure time on a large scale Race and Income have not been studied with respect to procedure time

5. Goals of this Talk To examine the accuracy of using Anesthesia Time Units from Medicare bills to estimate operative time To examine models that predict procedure length based on: –Patient comorbidities –Race –Income To explore the relationship between race and operative time at individual hospitals To discuss the implications of disparities in operative time

6. Data Medicare Claims on the 20 most common General Surgical procedures and the 20 most common Orthopedic procedures in Pennsylvania in 1995 and 1996, N = 77,638 Chart Abstractions on a subset of 1931 Pennsylvania General Surgical and Orthopedic patients as part of the Surgical Outcomes Study

7. The Anesthesia Claim The Anesthesia Claim consists of two parts: –Base Units –Time Units Time units are in 15 minute intervals. The first digit of the time unit is a decimal tenths digit –For example: “25” for units = 15 x 25/10 minutes or 37.5 minutes We chose the single longest anesthesia bill associated with the same day as the principle procedure

8. Time Abstraction We defined four specific times for abstraction on 1931 charts in the SOS study: –Start induction –Start incision –Closure –To recovery room or ICU (if going directly to ICU)

9. Bill Time - Chart Time. N = 1931 patients from the Surgical Outcomes Study Shapiro-Wilk Test P < 0.0001

10. Chart Time as a Function of Claim Time, N = 1931 VariablesInt.SlopePR2R2 Median Absolute Residual (minute) P (Wald) I:Unadjusted m-Estimation -1.210.97.0001.895.49N/A II:Comorbidities, Procedures and Hospitals 2.470.98.0001.895.37<.0001

11. The independent variable is anesthesia claim minutes, and the dependent variable is anesthesia chart minutes. N = 1931,  = 0.94.

12. ProcedureN25 th %ileMedian75 TH %ile Abd-Perineal Rect Resect422210260320 Anterior Rectal Resection685165251255 Left Hemicolectomy1307155195242 Part Lg Bowel Excis Nec507150191251 Sigmoidectomy2922140176221 Lg Bowel Stoma Closure326116164221 Part Sm Bowel Resection1253120155209 Right Hemicolectomy34350120155195 Unilat Thyroid Lobectomy370120135176 Cholecystectomy-Open3883105135176 Peritoneal Adhesiolysis126894125173 Estimated Anesthesia Time (Minutes) for Each General Surgical Principle Procedure These times include principle procedures that were also accompanied with other secondary procedures billed on the same day.

13. ProcedureN25 th %ileMedian75 TH %ile Abd-Perineal Rect Resect84206240285 Anterior Rectal Resection222146176218 Left Hemicolectomy262143180221 Part Lg Bowel Excis Nec77131158206 Sigmoidectomy678125155195 Lg Bowel Stoma Closure159101125180 Part Sm Bowel Resection112105131170 Right Hemicolectomy940110135170 Unilat Thyroid Lobectomy286108135167 Cholecystectomy-Open97890116146 Peritoneal Adhesiolysis31680101125 Estimated Anesthesia Time (minutes) for Each General Surgical Principle Procedure (when only one procedure performed) These times only include principle procedures that did not have other secondary procedures billed on the same day.

14. ProcedureN25 th %ileMedian75 TH %ile Lumbar/Lum-sac Fus Post273236299380 Other Cervical Fus Ant152182240343 Revise Hip Replacement971180234311 Spinal Canal Explor3166138180240 Revise Knee Replacement1110143180230 Excision Intervert Disc2565131165221 Total Hip Replacement6215140165197 Total Knee Replacement12718131150180 Open Red-Int Fix Hum690107142191 Partial Hip Replacement4735105129155 Shoulder Arthroplasty909105124158 Estimated Anesthesia Time (Minutes) for Each Orthopedic Principle Procedure These times include principle procedures that were also accompanied with other secondary procedures billed on the same day.

15. ProcedureN25 th %ileMedian75 TH %ile Lumbar/Lum-sac Fus Post41200240294 Other Cervical Fus Ant30155195245 Revise Hip Replacement639180225300 Spinal Canal Explor1478131170218 Revise Knee Replacement792140179227 Excision Intervert Disc1529122155196 Total Hip Replacement4770140165195 Total Knee Replacement10551131150180 Open Red-Int Fix Hum459101131170 Partial Hip Replacement4102105125150 Shoulder Arthroplasty129101131176 Estimated Anesthesia Time (minutes) for Each Orthopedic Principle Procedure (when only one procedure performed) These times only include principle procedures that did not have other secondary procedures billed on the same day.

16. Estimating Anesthesia Time (Y = Mins. from bill) ParameterMinutesP-value Multiple procedures18.3.0001 Admit from ER.10.90 Transfer In6.6.0003 Hx Coagulopathy5.0.0001 Hx Diabetes2.5.0001 Hx Paraplegia4.7.0004 Black Race Vs White5.2.0001 Severity Score 11.5.04 Severity Score 2.40.59 Severity Score 3 & 42.2.03 Severity Score 0RefN/A N=77,638 patients, controlling for 39 (=n-1) surgical procedures and 182 (=n-1) hospitals and 34 patient covariates of which 8 are displayed above. The model was fit using m-estimation, rank R 2 of 40%.

17. WL (n = 9,324) BM (n = 513) WM (n = 25,060) BH (n = 547) WH (n = 27,473) BL (n = 2002)29 (<.0001) 15 (<.0001)30 (<.0001) 15 (<.0001) 27 (<.0001) WL (n = 9,324)----14 <.0001) 1 (<.0001) -14 (<.0001) -2 (<.0001) BM (n = 513) ---14 (<.0001) 0 (.8939) 12 (<.0001) WM (n = 25,060) ----15 (<.0001)-3 (<.0001) BH (n = 547) ---12 (<.0001) Race, Income, and Procedure Time

18. WL (n = 9,324) BM (n = 513) WM (n = 25,060) BH (n = 547) WH (n = 27,473) BL (n = 2002) BL adjusted by 183 hosp. 29 (<.0001) 9 (<.0001) 15 (<.0001) 3 (0.159) 30 (<.0001) 7 (<.0001) 15 (<.0001) 8 (<.0001) 27 (<.0001) 8 (<.0001) WL (n = 9,324) WL adjusted by 183 hosp. ----14 <.0001) -4 (.036) 1 (<.0001) 0 (.578) -14 (<.0001) -5 (.486) -2 (<.0001) 1 (.069) BM (n = 513) BM adjusted by 183 hosp. ---14 (<.0001) 4 (.036) 0 (.8939) 5 (.052) 12 (<.0001) 4 (.014) WM (n = 25,060) WM adjusted by 183 hosp. ----15 (<.0001) 1 (.570) -3 (<.0001) 1 (.126) BH (n = 547) BH adjusted by 183 hosp. ---12 (<.0001) 0 (.848) Race, Income, and Procedure Time

19. Hospital No. Black No. WhiteTeaching Type Excess Mins. (b-w)P-Value 1153352Major3.3.449 2147322V Major7.0.115 3130326V Major0.8.870 4125108V Major12.2.039 51181319Major14.3.001 6112437Major12.1.011 711243Major-4.6.562 81111006Not Teaching4.0.366 910971V Major6.9.308 10107505Major9.3.050 11105178V Major15.9.004 121001007V Major-5.1.274 Adjusted Differences Between Black and White Procedure Times in Pennsylvania Hospitals With the Largest Black Populations The overall Wald test for equality was 0.029, suggesting there is variability in disparity across hospitals. General Surgical and Orthopedic Procedures

20. Policy Implications

21. Why might there be a disparity in operative time inside a hospital? Reasons consistent with fairness –Unobserved severity –Admission from ER –Emergency Surgery Reasons based on injustice –Different Surgeon/Physician-in-Training for less empowered –Risk of Litigation –Racism (Conscious or Unconscious)

22. Why do we care about 15 minutes?

23. Identifying the Provider: Who is holding the retractor? In teaching hospitals it is not always clear from the chart or the claim who is performing surgery. Is the resident doing the dissection or holding the retractor? Differential times between the resident and the attending may help in identifying the two providers.

24. For a typical procedure like Colectomy, which was described in Khuri et al. (Annals Surgery 2001), we can estimate the relative speed of the resident and attending, assuming the hospital location does not influence this time. VA Location NComplexit y % of Cases by Residents Hours of Surgery Mean Time Combined Teaching8,0383.0093.643.173.085 Non- Teach 1,2012.951.422.54 From this table we can solve for the time a resident takes to perform the colectomy (T R ) and the time an attending takes to perform the surgery (T A ). We have two equations and two unknowns: (0.9346)T R + (0.0636)T A = 3.17 (0.0142)T R + (0.9808)T A = 2.52 Solving, we get T A = 2.523 and T R = 3.213 hours. This is very close to those in table 8 above, as almost all the surgery in the teaching hospital was with residents and almost all the surgery in the non-teaching hospital was with attendings.

25. T B = T R * P B,R + T A * P B,A T W = T R * P W,R + T A * P W,A Or, since P B,R + P B,A = 1and P W,R + P W,A = 1, we can write: T B = T R * P B,R + T A * (1 - P B,R ) and T W = T R * P W,R + T A * (1 - P W,R ). Hence, T B -T W = P B,R * [T R - T A ] - P W,R *[T R - T A ] and: [T B - T W ]/[T R -T A ] = P B,R - P W,R Or: [T B - T W ]/ [P W,R ][T R -T A ] = [P B,R / P W,R ]-1 and finally: 1+ {[T B - T W ] / {[P W,R ][T R -T A ]}} = [P B,R / P W,R ] The Relative Risk of Getting a Resident in Black Versus White Patients

26. From Regression Data From External Data or Matching Studies

27. Assuming: T R -T A = 30 mins T B – T W = 15 mins

28. Advantages of using Procedure Time as a Measure of Disparity Bills available for literally all procedures performed in the OR for Medicare patients Procedure length is highly dependent on the surgeon, not patient compliance Procedure length is less dependent on the past history of the patient—insensitive to unobserved severity Time is not game-able, especially since it has not been used to measure disparity in the past

29. Conclusions Procedure time can be well estimated with Medicare claims data Procedure time is a function of race and income and the specific hospital, after adjustment for other patient factors There is a significant procedure length racial disparity inside of hospitals Mechanisms for this procedure length disparity need to be better understood

30. Acknowledgements This work was funded through a grant from the Leonard Davis Institute of Health Economics at PENN and supported in part from AHRQ Grant Number HS-09460

31. The End

32. Additional Slides for Potential Questions

33. Sometimes ALWAYS TEACHINGNON-TEACHING N=96 Surgeons N=480 Patients

34. Sometimes ALWAYS TEACHINGNON-TEACHING P = 0.214 P = 0.002 P = 0.393 P = 0.657 P = 0.0001 103 minutes 106 minutes 109 minutes 121 minutes