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The impact of an acute care surgery model on general surgery service productivity
Perioperative Care and Operating Room Management 12 (2018) 26–30
Contents lists available at ScienceDirect
Perioperative Care and Operating Room Management journal homepage: www.elsevier.com/locate/pcorm
The impact of an acute care surgery model on general surgery service productivity☆
T
⁎
Adam N. Painea,b, , Bradley L. Krompfb, Edward C. Borrazzoa,b, Thomas P. Aherna, Ajai K. Malhotraa,b, Mitchell C. Norotskya,b, Mitchell H. Tsaic a
Department of Surgery, The University of Vermont Larner College of Medicine, Burlington, VT, United States Department of Surgery, The University of Vermont Medical Center, Burlington, VT, United States c Department of Anesthesiology, Department of Surgery (by courtesy), Department of Orthopaedics and Rehabilitation (by courtesy), and The University of Vermont Larner College of Medicine, Burlington, VT, United States b
A R T I C LE I N FO
A B S T R A C T
Keywords: Acute Care Surgery Emergency General Surgery General Surgery Work Relative Value Units Productivity
Background: The Acute Care Surgery (ACS) model has been widely adopted by hospitals across the United States, with ACS services managing emergency general surgery (EGS) patients previously treated by general surgery (GS) services. We evaluated the operational and financial impact of an ACS service model on general surgeons at an academic medical center. Methods: Using WiseOR® (Palo Alto, CA), we compared surgical case volumes for the GS service two years before (October, 2013–September, 2015) and two years after (October, 2015–September, 2017) implementation of an ACS service at the University of Vermont Medical Center. From financial reports, we obtained monthly wRVUs, clinical FTEs, net patient revenue, and payer mix for the GS service and compared the two years before and after ACS model implementation. Results: There was a significant reduction in the average number of cases performed by the GS service following ACS service implementation (monthly mean ± SD, 139.1 ± 16.0 vs. 116.7 ± 14.0, p < 0.001). The normalhours caseload remained stable, while a significant decrease in after-hours cases accounted for the reduction in overall volume. Despite the reduction in operative volume, the decrease in mean monthly wRVU/FTE for the GS service when comparing the pre- and post-ACS periods did not reach statistical significance (614.9 ± 82.9 vs. 576.3 ± 62.1, p = 0.08). There was a significant increase in average monthly clinic-derived wRVU/FTE for the GS service (106.3 ± 13.5 vs. 120.5 ± 16.4, p = 0.007). Conclusions: Shifting EGS patient management from the GS to ACS service did not negatively impact the productivity of the GS service.
1. Introduction The Acute Care Surgery (ACS) model has been widely adopted by health care organizations across the United States.1 Although substantial institutional variation exists with ACS model organization, the implementation of an ACS service line generally involves a paradigm shift with the ACS service managing emergency general surgery (EGS) patients previously treated by general surgery (GS) services.2,3 Numerous studies have examined the effects of ACS models on patient
outcomes, namely in the appendicitis and cholecystitis populations.4–8 There is a trend toward more rapid evaluation and treatment with an ACS model, compared with traditional on-call GS models.9 There are fewer reports about the effects of ACS model implementation on departmental finances and, more specifically, on GS service line productivity. Since EGS patients frequently represent a significant portion of a general surgeon's practice, there is clear cause for apprehension and investigation.10 Miller et al. demonstrated that the GS service experienced a significant decrease in work Relative
Abbreviations: ACS, acute care surgery; EGS, emergency general surgery; GS, general surgery; FTE, full-time equivalent; wRVU, work relative value unit; TCC, trauma-critical care; OR, operating room; SICU, surgical intensive care unit; CPT, current procedural terminology; UVMMC, University of Vermont Medical Center ☆ Presented at the New England Surgical Society, 2017 Annual Meeting, Bretton Woods, NH, September, 2017. ⁎ Corresponding author at: Department of Surgery, The University of Vermont Medical Center, 111 Colchester Ave, Burlington, VT 05401, United States. E-mail addresses: [email protected] (A.N. Paine), [email protected] (B.L. Krompf), [email protected] (E.C. Borrazzo), [email protected] (T.P. Ahern), [email protected] (A.K. Malhotra), [email protected] (M.C. Norotsky), [email protected] (M.H. Tsai). https://doi.org/10.1016/j.pcorm.2018.09.001 Received 22 January 2018; Received in revised form 27 April 2018; Accepted 23 September 2018 Available online 24 September 2018 2405-6030/ © 2018 Elsevier Inc. All rights reserved.
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Fig. 1. General Surgery (GS) service line mean monthly case volume two years before and two years after implementation of the Acute Care Surgery (ACS) service line which subsequently managed all emergency general surgery (EGS) patients.15 Error bars represent standard error. Asterisk (*) denotes statistical significance by Student's t with significance set at p < 0.05.
Value Units (wRVU) upon initiation of an ACS service at their institution. This decrease in clinical workload did not translate to a reduction in revenue, most likely due to a favorable change in payer mix.11 In contrast, Barnes et al. demonstrated that the wRVUs of the GS service increased following implementation of an ACS service at their institution.12 To date, the lack of a universally accepted productivity measure among surgical services in the literature impedes the generalizability of these studies. Undoubtedly, dollar reimbursement is a focus at the institutional level, though there are many local factors influencing this value. As such, the same service line performing the same volume and mix of cases at different hospitals could lead to disparate collections. Work RVUs are frequently used to negate such institutional variation, though, importantly, they do not account for changes in workforce over time. A less frequently used value in the surgical literature is the ratio of wRVUs to Full Time Equivalent (FTE) surgeons on the service line at any given time (wRVU/FTE), which accounts for institutional and workforce variation.13,14 In order to sustain the clinical benefits of the ACS model, it is imperative to develop generalizable financial frameworks for further analyses. In previous work at our institution, we demonstrated that following implementation of an ACS service in October, 2015, the GS service line had a significant drop in after-hours caseload while maintaining a stable normal-hours caseload.15 In an effort to generalize and promulgate the financial implications of an ACS service model, we sought to use the wRVU/FTE ratio to quantify the financial impact on the GS service of transferring EGS patient management to the ACS service.
covered the majority of the general surgery call. Occasionally, in the pre-ACS era, two additional surgeons—one in private practice and one UVMMC surgical oncologist—took general surgery call (less than four days per month on average). We excluded their data from these analyses. Using WiseOR (Palo Alto, CA), we extracted monthly surgical cases for the GS service two years before (October, 2013 – September, 2015) and after (October, 2015–September, 2017) the implementation of the ACS service. We compared the mean monthly case volumes during normal-hours (07:00–17:30 on weekdays) and after-hours (17:30–07:00 on weekdays and all weekend cases). From financial reports, we obtained monthly wRVUs, clinical FTEs, net patient revenue, and payer mix for the GS service during the four-year study period. We then compared the wRVU/FTE ratios, net patient revenue, and payer mix for the GS service two years before and after implementation of the ACS service. Microsoft Excel (Redmond, WA) was used for database entry and STATA v. 15.0 (Stata Corporation, College Station, TX) was used for statistical analysis. We described trends in monthly wRVU/FTE by plotting kernel-smoothed points from the raw data and fitting a firstdegree polynomial function to the smoothed data. We also plotted the month over month difference in wRVU/FTE (example calculation: monthly data point = October 2014 wRVU/FTE ratio – September 2014 wRVU/FTE ratio). Student's t test was used to compare differences in continuous variables between time periods, and Chi-Squared tests were used to evaluate the distribution of categorical variables. All statistical tests were two-sided, with a type I error rate of 5%.
2. Methods
There was a statistically significant decrease in the total number of cases performed by the GS service following implementation of the ACS service (monthly mean ± standard deviation, 139.1 ± 16.0 vs. 116.7 ± 14.0, p < 0.001, Fig. 1). The number of cases occurring afterhours decreased significantly (37.1 ± 7.7 vs. 16.6 ± 5.0, p < 0.001) while normal-hours case volumes remained stable over the study period (102.0 ± 14.4 vs. 100.1 ± 11.4, p = 0.64). These findings remained constant when normalized to monthly clinical FTE. The decrease in average monthly wRVU/FTE for the GS service, when comparing the pre- and post-ACS periods, did not reach statistical significance (614.9 ± 82.9 vs. 576.3 ± 62.1, p = 0.08, Fig. 2). The trend plot in Fig. 3 A shows no discernable downtrend following ACS service initiation. Fig. 3B demonstrates month over month analysis of the wRVU/FTE ratio, showing a random difference pattern centered on zero—again signifying no appreciable decrease in GS productivity following ACS implementation. The GS had a significant increase in the
3. Results
The University of Vermont Medical Center (UVMMC), a 562-bed, Level-1 trauma center, implemented an ACS service in October, 2015. The organization of the ACS service and the specifics of its implementation are described in our previous work.15 In brief, the ACS service took over the Trauma-Critical Care (TCC) service, previously comprised of four surgeons taking rotating trauma call and covering the surgical intensive care unit (SICU). With the creation of the new service, the Department of Surgery hired a new division chief and two additional surgeons in the first 12 months. Beginning in October, 2015 the ACS service covered all EGS, trauma, and the SICU. Prior to October, 2015 all EGS patients were covered by general surgeons not belonging to the TCC service. Seven board-certified surgeons, (including one fellowship-trained minimally invasive surgeon, two fellowship-trained bariatric surgeons, and three fellowship-trained colorectal surgeons) 27
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clinical FTE of the GS service was 5.6 over the 24 months pre-ACS and 5.5 over the 24 months post-ACS. The GS service generated 81411 wRVUs the two years before ACS implementation and 76242 wRVUs the two years following ACS implementation (monthly average 3392 ± 446.1 wRVU pre-ACS, 3176.8 ± 328.8 wRVU post-ACS, p = 0.10). The GS service had a 6.5% decrease in net patient revenue comparing the two years before and after ACS implementation. When net patient revenue was analyzed on a monthly basis this decrease did not reach statistical significance (p = 0.06). The payer mix for the GS and TCC-ACS services in the two years before and after ACS model implementation can be seen in Table 1. Both services had statistically significant changes in their payer mix when comparing the pre- to postACS periods (p < 0.001 for both services). 4. Discussion
Fig. 2. Mean monthly wRVU/FTE for the general surgery (GS) service two years before and two years after implementation of the acute care surgery (ACS) service. Error bars represent standard error. There was no statistically significant change between the two study periods, p = 0. 08.
Since its inception over a decade ago, the ACS model of EGS patient management has led to clinical and operational workflow improvements. However, there is a lack of comprehensive evidence demonstrating the financial sustainability of the ACS model. More specifically, there is a paucity of generalizable studies analyzing the financial impact of shifting the EGS patient population from GS service lines to ACS surgeons. With surgical care alone representing an estimated 6% of
average monthly wRVU/FTE generated in the outpatient clinic setting when comparing the two years before and after ACS implementation (106.3 ± 13.5 vs. 120. 16.4, p = 0.007, Fig. 4). The average monthly
Fig. 3. (A) Monthly wRVU/FTE ratio for the general surgery (GS) service plotted from October, 2013 – September, 2017. Dots show original data points. Trend curve was fit using local kernel smoothing followed by fitting a first-degree polynomial. The vertical dashed line denotes start of the acute care surgery (ACS) service in October, 2015. (B) Month over month difference in wRVU/FTE for the GS service plotted from September, 2013–September 2017 (example calculation: monthly data point = October 2014 wRVU/FTE ratio – September 2014 wRVU/FTE ratio). The vertical dashed line denotes start of the acute care surgery (ACS) service in October, 2015.
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Fig. 4. Mean monthly clinic derived wRVU/FTE for the general surgery (GS) service two years before and two years after implementation of the acute care surgery (ACS) service. Error bars represent standard error. Asterisk (*) denotes statistical significance, p = 0.007.
subspecialty care would represent a service to the community while undoubtedly increasing surgeon satisfaction, and thus requires continued investigation. Another contributing factor is the effect of officederived wRVUs. Our results demonstrate that the GS service had more productive clinics in the post-ACS period, likely due in part to less interruption by unscheduled EGS activity. From a physician wellness perspective, reducing after-hours caseload likely reduces the incidence of surgeon burnout, an unfortunate epidemic plaguing most specialties.18 There is clear evidence demonstrating a tipping point where increasing workload leads to undesirable patient outcomes.19 Unsurprisingly, there is a negative correlation between physician burnout and institutional revenue.20,21 Our findings suggest that the substantial after-hours caseload handled by the general surgeons before ACS service implementation did not positively contribute to productivity. Forthcoming work will elucidate this presumed effect on surgeon well-being. The wRVU/FTE ratio is an effective and generalizable method for analyzing service line productivity. It is important to highlight that these data are largely unaffected by variations in institutional payer mix and reimbursement rates. Dollar collections, directly influenced by both of these factors, are difficult to generalize across institutions. Compared to collections, wRVU/FTE ratios may be less impactful within an institution; however, they can be used to effectively communicate analyses nationally. A limitation of any longitudinal analysis of wRVU data is the possibility that the wRVUs earned per Current Procedural Terminology (CPT) code can change. When such changes do occur, they are uniformly applied across the country and can be highlighted and/or adjusted for in analysis if felt to significantly impact findings. The wRVUs earned per CPT did not change significantly for the majority of procedures performed by the GS service during the study period. The only significant change in wRVU earned per CPT identified was for a laparoscopic sleeve gastrectomy (CPT 43775). For the first 27 months of our study period the Centers for Medicare and Medicaid Services (CMS) designated this CPT to be contractor priced and thus reimbursement was negotiated on a local level by Medicare contractors. For the last 21 months of the post-ACS period it was assigned 20.38 wRVUs by CMS at the national level. As such, there was a discrepancy in the wRVUs earned per laparoscopic sleeve gastrectomy performed by our surgeons between the first 27 and last 21 months of the study period. The numbers reported herein reflect the actual wRVUs earned by the surgeon at the time the CPT was billed for. Despite a lack of generalizability, dollar collections cannot be ignored. It is important to acknowledge that a 6.5% decrease in net patient revenue, though not statistically significant, may be considered meaningful by administrators and lead to institutional changes. As revenue is dependent on payer mix, one must address any changes in
Table 1 Payer mix as a percent of patient encounters before and after implementation of the ACS service model for the (A) General Surgery (GS) service and (B) the Trauma Critical Care (TCC) service which subsequently became the Acute Care Surgery (ACS) service. By the Chi-squared test of independence, both services experienced statistically significant payer mix changes from the pre- to postACS period (p < 0.001 for both services). A. GeneralSurgeryService Insurance type Medicare Medicaid Commercial insurance Self-Pay Other
Pre-ACS 25.5% 12.9% 57.2% 1.7% 2.7%
Post-ACS 24.9% 15.2% 57.0% 1.3% 1.7%
Difference -0.7% +2.3% -0.1% -0.4% -1.0%
B. Trauma CriticalCare –CuteCareSurgeryService Insurance type
Pre-ACS
Post-ACS
Difference
Medicare Medicaid Commercial insurance Self-Pay Other
27.4% 13.4% 40.2% 4.0% 15.0%
32.7% 14.9% 36.3% 3.9% 12.1%
+5.3% +1.5% -3.8% -0.1% -2.9%
United States gross domestic product, it is prudent to develop and analyze service models with fiduciary frameworks.16 Herein, we demonstrate a generalizable method for analyzing the financial impact of an ACS model on a GS service line that previously managed EGS patients. In this study, the GS service maintained a wRVU/FTE ratio consistent with its pre-ACS level despite a significant decrease in afterhours case volume. The concern that general surgeons’ productivity would be threatened by the loss of EGS patients is not supported by our findings.10,17 Our results suggest that our GS service line was able to increase the number of wRVUs generated during normal-hours to compensate for lost after-hours productivity. In other words, the general surgeons were actually more productive during normal hours in the post-ACS period. The reduction in after-hours workload would seemingly reduce the total clinical productivity for the GS service. However, several factors may attenuate these losses. One possible contributing explanation is a change in case mix that focused more on the individual surgeon's subspecialty, with an attendant increase in wRVU/case ratio. For example, comparing the pre- and post- ACS periods, the GS service had a 92% reduction in the number of laparoscopic appendectomies performed, and a 39% increase in the number of laparoscopic sleeve gastrectomies performed. The possibility of increasing access to local 29
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payer mix when performing such analyses. The study period herein corresponded to major national and state level insurance reform including the expansion of Medicaid in the state of Vermont as part of the Affordable Care Act. With these simultaneous extraneous factors on payer mix it is difficult to make any definitive conclusions about the effect shifting EGS patients to the ACS service had on the GS service payer mix as previous studies have quantified.11 Given the widespread adoption of the ACS model, studies evaluating clinical outcomes, cost-effectiveness, and the impact on hospital finances must continue.1 In today's climate of unsustainable health care costs, the need to include economic analyses of such paradigm changes cannot be overemphasized. Our results build on a growing foundation of evidence supporting the transition of EGS patient management from traditional on-call GS services to an ACS model.
2. Santry HP, Madore JC, Collins CE, et al. Variations in the implementation of acute care surgery: results from a national survey of university-affiliated hospitals. J Trauma Acute Care Surg. 2015;78:60–78. 3. Santry HP, Pringle PL, Collins CE, Kiefe CI. A qualitative analysis of acute care surgery in the United States: it's more than just “a competent surgeon with a sharp knife and a willing attitude. Surgery. 2014;155:809–825. 4. Earley AS, Pryor JP, Kim PK, et al. An acute care surgery model improves outcomes in patients with appendicitis. Ann Surg Lippincott,. 2006;244:498–504. 5. Ekeh AP, Monson B, Wozniak CJ, et al. Management of acute appendicitis by an acute care surgery service: is operative intervention timely? J. Am Coll Surg. 2008;207:43–48. 6. Gandy RC, Truskett PG, Wong SW, et al. Outcomes of appendicectomy in an acute care surgery model. Med J Aust. 2010;193:281–284. 7. Cubas RF, Gómez NR, Rodriguez S, et al. Outcomes in the management of appendicitis and cholecystitis in the setting of a new acute care surgery service model: impact on timing and cost. J Am Coll Surg. 2012;215:715–721. 8. Britt RC, Bouchard C, Weireter LJ, Britt LD. Impact of acute care surgery on biliary disease. J Am Coll Surg. 2010;210:595–599. 9. Nagaraja V, Eslick GD, Cox MR. The acute surgical unit model verses the traditional “on call” model: a systematic review and meta-analysis. World J Surg. 2014;38:1381–1387. 10. Jurkovich GJ, Rozycki GS. Acute care surgery: real or imagined threat to the general surgeon. Am J Surg. 2010;199:862–863. 11. Miller PR, Wildman EA, Chang MC, Meredith JW. Acute care surgery: impact on practice and economics of elective surgeons. J Am Coll Surg. 2012;214:531–535. 12. Barnes SL, Cooper CJ, Coughenour JP, et al. Impact of acute care surgery to departmental productivity. J Trauma Inj Infect Crit Caress. 2011;71:1027–1034. 13. Wai PY, O'Hern T, Andersen DO, et al. Impact of business infrastructure on financial metrics in departments of surgery. Surgery. 2012;152:729–737. 14. Lu Y, Arenson RL. The academic radiologist's clinical productivity. Acad Radiol. 2005;12:1211–1223. 15. Paine AN, Andritsos DA, Fitzgerald JR, Norotsky MC, Malhotra AK, Tsai M. The operational impact of an acute care surgical service on operating room metrics. Perioper Care Oper Room Manag. 2017;8:38–41. 16. Muñoz E, Muñoz W, Wise L. National and surgical health care expenditures, 2005–2025. Ann Surg. 2010;251:195–200. 17. Malangoni MA. Acute care surgery: the general surgeon's perspective. Surgery. 2007;141:324–326. 18. Ariely D, Lanier WL. Disturbing trends in physician burnout and satisfaction with work-life balance. Mayo Clin Proc. 2015;90:1593–1596. 19. Kc DS, Terwiesch C. Impact of workload on service time and patient safety: an econometric analysis of hospital operations. Manage Sci Informs. 2009;55:1486–1498. 20. Muller IR, Eldakar-Hein ST, Ames E, Rosen LD, Urman RD, Tsai M. Potential association between physician burnout rates and operating margins: specialty-specific analysis. J Med Pract Manag. 2017;32(4):233–238 PMID: 29969540. 21. Dewa CS, Jacobs P, Thanh NX, Loong D. An estimate of the cost of burnout on early retirement and reduction in clinical hours of practicing physicians in Canada. BMC Health Serv Res BioMed Central. 2014;14:254.
Author contribution Study conception and design: Tsai, Malhotra, Norotsky, Borrazzo, Paine. Acquisition of data: Tsai, Paine, Krompf. Analysis and interpretation of data: Tsai, Ahern, Paine, Krompf. Drafting of manuscript: Tsai, Paine, Krompf. Critical revision: Tsai, Paine, Krompf, Borrazzo, Ahern, Norotsky. Declarations of interest None. Funding disclosure Author TPA was supported by a grant from the National Institute of General Medical Sciences at the National Institutes of Health (P20 GM103644). References 1. Collins CE, Pringle PL, Santry HP. Innovation or rebranding, acute care surgery diffusion will continue. J Surg Res. 2015;197:354–362.
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Contents lists available at ScienceDirect
Perioperative Care and Operating Room Management journal homepage: www.elsevier.com/locate/pcorm
The impact of an acute care surgery model on general surgery service productivity☆
T
⁎
Adam N. Painea,b, , Bradley L. Krompfb, Edward C. Borrazzoa,b, Thomas P. Aherna, Ajai K. Malhotraa,b, Mitchell C. Norotskya,b, Mitchell H. Tsaic a
Department of Surgery, The University of Vermont Larner College of Medicine, Burlington, VT, United States Department of Surgery, The University of Vermont Medical Center, Burlington, VT, United States c Department of Anesthesiology, Department of Surgery (by courtesy), Department of Orthopaedics and Rehabilitation (by courtesy), and The University of Vermont Larner College of Medicine, Burlington, VT, United States b
A R T I C LE I N FO
A B S T R A C T
Keywords: Acute Care Surgery Emergency General Surgery General Surgery Work Relative Value Units Productivity
Background: The Acute Care Surgery (ACS) model has been widely adopted by hospitals across the United States, with ACS services managing emergency general surgery (EGS) patients previously treated by general surgery (GS) services. We evaluated the operational and financial impact of an ACS service model on general surgeons at an academic medical center. Methods: Using WiseOR® (Palo Alto, CA), we compared surgical case volumes for the GS service two years before (October, 2013–September, 2015) and two years after (October, 2015–September, 2017) implementation of an ACS service at the University of Vermont Medical Center. From financial reports, we obtained monthly wRVUs, clinical FTEs, net patient revenue, and payer mix for the GS service and compared the two years before and after ACS model implementation. Results: There was a significant reduction in the average number of cases performed by the GS service following ACS service implementation (monthly mean ± SD, 139.1 ± 16.0 vs. 116.7 ± 14.0, p < 0.001). The normalhours caseload remained stable, while a significant decrease in after-hours cases accounted for the reduction in overall volume. Despite the reduction in operative volume, the decrease in mean monthly wRVU/FTE for the GS service when comparing the pre- and post-ACS periods did not reach statistical significance (614.9 ± 82.9 vs. 576.3 ± 62.1, p = 0.08). There was a significant increase in average monthly clinic-derived wRVU/FTE for the GS service (106.3 ± 13.5 vs. 120.5 ± 16.4, p = 0.007). Conclusions: Shifting EGS patient management from the GS to ACS service did not negatively impact the productivity of the GS service.
1. Introduction The Acute Care Surgery (ACS) model has been widely adopted by health care organizations across the United States.1 Although substantial institutional variation exists with ACS model organization, the implementation of an ACS service line generally involves a paradigm shift with the ACS service managing emergency general surgery (EGS) patients previously treated by general surgery (GS) services.2,3 Numerous studies have examined the effects of ACS models on patient
outcomes, namely in the appendicitis and cholecystitis populations.4–8 There is a trend toward more rapid evaluation and treatment with an ACS model, compared with traditional on-call GS models.9 There are fewer reports about the effects of ACS model implementation on departmental finances and, more specifically, on GS service line productivity. Since EGS patients frequently represent a significant portion of a general surgeon's practice, there is clear cause for apprehension and investigation.10 Miller et al. demonstrated that the GS service experienced a significant decrease in work Relative
Abbreviations: ACS, acute care surgery; EGS, emergency general surgery; GS, general surgery; FTE, full-time equivalent; wRVU, work relative value unit; TCC, trauma-critical care; OR, operating room; SICU, surgical intensive care unit; CPT, current procedural terminology; UVMMC, University of Vermont Medical Center ☆ Presented at the New England Surgical Society, 2017 Annual Meeting, Bretton Woods, NH, September, 2017. ⁎ Corresponding author at: Department of Surgery, The University of Vermont Medical Center, 111 Colchester Ave, Burlington, VT 05401, United States. E-mail addresses: [email protected] (A.N. Paine), [email protected] (B.L. Krompf), [email protected] (E.C. Borrazzo), [email protected] (T.P. Ahern), [email protected] (A.K. Malhotra), [email protected] (M.C. Norotsky), [email protected] (M.H. Tsai). https://doi.org/10.1016/j.pcorm.2018.09.001 Received 22 January 2018; Received in revised form 27 April 2018; Accepted 23 September 2018 Available online 24 September 2018 2405-6030/ © 2018 Elsevier Inc. All rights reserved.
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Fig. 1. General Surgery (GS) service line mean monthly case volume two years before and two years after implementation of the Acute Care Surgery (ACS) service line which subsequently managed all emergency general surgery (EGS) patients.15 Error bars represent standard error. Asterisk (*) denotes statistical significance by Student's t with significance set at p < 0.05.
Value Units (wRVU) upon initiation of an ACS service at their institution. This decrease in clinical workload did not translate to a reduction in revenue, most likely due to a favorable change in payer mix.11 In contrast, Barnes et al. demonstrated that the wRVUs of the GS service increased following implementation of an ACS service at their institution.12 To date, the lack of a universally accepted productivity measure among surgical services in the literature impedes the generalizability of these studies. Undoubtedly, dollar reimbursement is a focus at the institutional level, though there are many local factors influencing this value. As such, the same service line performing the same volume and mix of cases at different hospitals could lead to disparate collections. Work RVUs are frequently used to negate such institutional variation, though, importantly, they do not account for changes in workforce over time. A less frequently used value in the surgical literature is the ratio of wRVUs to Full Time Equivalent (FTE) surgeons on the service line at any given time (wRVU/FTE), which accounts for institutional and workforce variation.13,14 In order to sustain the clinical benefits of the ACS model, it is imperative to develop generalizable financial frameworks for further analyses. In previous work at our institution, we demonstrated that following implementation of an ACS service in October, 2015, the GS service line had a significant drop in after-hours caseload while maintaining a stable normal-hours caseload.15 In an effort to generalize and promulgate the financial implications of an ACS service model, we sought to use the wRVU/FTE ratio to quantify the financial impact on the GS service of transferring EGS patient management to the ACS service.
covered the majority of the general surgery call. Occasionally, in the pre-ACS era, two additional surgeons—one in private practice and one UVMMC surgical oncologist—took general surgery call (less than four days per month on average). We excluded their data from these analyses. Using WiseOR (Palo Alto, CA), we extracted monthly surgical cases for the GS service two years before (October, 2013 – September, 2015) and after (October, 2015–September, 2017) the implementation of the ACS service. We compared the mean monthly case volumes during normal-hours (07:00–17:30 on weekdays) and after-hours (17:30–07:00 on weekdays and all weekend cases). From financial reports, we obtained monthly wRVUs, clinical FTEs, net patient revenue, and payer mix for the GS service during the four-year study period. We then compared the wRVU/FTE ratios, net patient revenue, and payer mix for the GS service two years before and after implementation of the ACS service. Microsoft Excel (Redmond, WA) was used for database entry and STATA v. 15.0 (Stata Corporation, College Station, TX) was used for statistical analysis. We described trends in monthly wRVU/FTE by plotting kernel-smoothed points from the raw data and fitting a firstdegree polynomial function to the smoothed data. We also plotted the month over month difference in wRVU/FTE (example calculation: monthly data point = October 2014 wRVU/FTE ratio – September 2014 wRVU/FTE ratio). Student's t test was used to compare differences in continuous variables between time periods, and Chi-Squared tests were used to evaluate the distribution of categorical variables. All statistical tests were two-sided, with a type I error rate of 5%.
2. Methods
There was a statistically significant decrease in the total number of cases performed by the GS service following implementation of the ACS service (monthly mean ± standard deviation, 139.1 ± 16.0 vs. 116.7 ± 14.0, p < 0.001, Fig. 1). The number of cases occurring afterhours decreased significantly (37.1 ± 7.7 vs. 16.6 ± 5.0, p < 0.001) while normal-hours case volumes remained stable over the study period (102.0 ± 14.4 vs. 100.1 ± 11.4, p = 0.64). These findings remained constant when normalized to monthly clinical FTE. The decrease in average monthly wRVU/FTE for the GS service, when comparing the pre- and post-ACS periods, did not reach statistical significance (614.9 ± 82.9 vs. 576.3 ± 62.1, p = 0.08, Fig. 2). The trend plot in Fig. 3 A shows no discernable downtrend following ACS service initiation. Fig. 3B demonstrates month over month analysis of the wRVU/FTE ratio, showing a random difference pattern centered on zero—again signifying no appreciable decrease in GS productivity following ACS implementation. The GS had a significant increase in the
3. Results
The University of Vermont Medical Center (UVMMC), a 562-bed, Level-1 trauma center, implemented an ACS service in October, 2015. The organization of the ACS service and the specifics of its implementation are described in our previous work.15 In brief, the ACS service took over the Trauma-Critical Care (TCC) service, previously comprised of four surgeons taking rotating trauma call and covering the surgical intensive care unit (SICU). With the creation of the new service, the Department of Surgery hired a new division chief and two additional surgeons in the first 12 months. Beginning in October, 2015 the ACS service covered all EGS, trauma, and the SICU. Prior to October, 2015 all EGS patients were covered by general surgeons not belonging to the TCC service. Seven board-certified surgeons, (including one fellowship-trained minimally invasive surgeon, two fellowship-trained bariatric surgeons, and three fellowship-trained colorectal surgeons) 27
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clinical FTE of the GS service was 5.6 over the 24 months pre-ACS and 5.5 over the 24 months post-ACS. The GS service generated 81411 wRVUs the two years before ACS implementation and 76242 wRVUs the two years following ACS implementation (monthly average 3392 ± 446.1 wRVU pre-ACS, 3176.8 ± 328.8 wRVU post-ACS, p = 0.10). The GS service had a 6.5% decrease in net patient revenue comparing the two years before and after ACS implementation. When net patient revenue was analyzed on a monthly basis this decrease did not reach statistical significance (p = 0.06). The payer mix for the GS and TCC-ACS services in the two years before and after ACS model implementation can be seen in Table 1. Both services had statistically significant changes in their payer mix when comparing the pre- to postACS periods (p < 0.001 for both services). 4. Discussion
Fig. 2. Mean monthly wRVU/FTE for the general surgery (GS) service two years before and two years after implementation of the acute care surgery (ACS) service. Error bars represent standard error. There was no statistically significant change between the two study periods, p = 0. 08.
Since its inception over a decade ago, the ACS model of EGS patient management has led to clinical and operational workflow improvements. However, there is a lack of comprehensive evidence demonstrating the financial sustainability of the ACS model. More specifically, there is a paucity of generalizable studies analyzing the financial impact of shifting the EGS patient population from GS service lines to ACS surgeons. With surgical care alone representing an estimated 6% of
average monthly wRVU/FTE generated in the outpatient clinic setting when comparing the two years before and after ACS implementation (106.3 ± 13.5 vs. 120. 16.4, p = 0.007, Fig. 4). The average monthly
Fig. 3. (A) Monthly wRVU/FTE ratio for the general surgery (GS) service plotted from October, 2013 – September, 2017. Dots show original data points. Trend curve was fit using local kernel smoothing followed by fitting a first-degree polynomial. The vertical dashed line denotes start of the acute care surgery (ACS) service in October, 2015. (B) Month over month difference in wRVU/FTE for the GS service plotted from September, 2013–September 2017 (example calculation: monthly data point = October 2014 wRVU/FTE ratio – September 2014 wRVU/FTE ratio). The vertical dashed line denotes start of the acute care surgery (ACS) service in October, 2015.
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Fig. 4. Mean monthly clinic derived wRVU/FTE for the general surgery (GS) service two years before and two years after implementation of the acute care surgery (ACS) service. Error bars represent standard error. Asterisk (*) denotes statistical significance, p = 0.007.
subspecialty care would represent a service to the community while undoubtedly increasing surgeon satisfaction, and thus requires continued investigation. Another contributing factor is the effect of officederived wRVUs. Our results demonstrate that the GS service had more productive clinics in the post-ACS period, likely due in part to less interruption by unscheduled EGS activity. From a physician wellness perspective, reducing after-hours caseload likely reduces the incidence of surgeon burnout, an unfortunate epidemic plaguing most specialties.18 There is clear evidence demonstrating a tipping point where increasing workload leads to undesirable patient outcomes.19 Unsurprisingly, there is a negative correlation between physician burnout and institutional revenue.20,21 Our findings suggest that the substantial after-hours caseload handled by the general surgeons before ACS service implementation did not positively contribute to productivity. Forthcoming work will elucidate this presumed effect on surgeon well-being. The wRVU/FTE ratio is an effective and generalizable method for analyzing service line productivity. It is important to highlight that these data are largely unaffected by variations in institutional payer mix and reimbursement rates. Dollar collections, directly influenced by both of these factors, are difficult to generalize across institutions. Compared to collections, wRVU/FTE ratios may be less impactful within an institution; however, they can be used to effectively communicate analyses nationally. A limitation of any longitudinal analysis of wRVU data is the possibility that the wRVUs earned per Current Procedural Terminology (CPT) code can change. When such changes do occur, they are uniformly applied across the country and can be highlighted and/or adjusted for in analysis if felt to significantly impact findings. The wRVUs earned per CPT did not change significantly for the majority of procedures performed by the GS service during the study period. The only significant change in wRVU earned per CPT identified was for a laparoscopic sleeve gastrectomy (CPT 43775). For the first 27 months of our study period the Centers for Medicare and Medicaid Services (CMS) designated this CPT to be contractor priced and thus reimbursement was negotiated on a local level by Medicare contractors. For the last 21 months of the post-ACS period it was assigned 20.38 wRVUs by CMS at the national level. As such, there was a discrepancy in the wRVUs earned per laparoscopic sleeve gastrectomy performed by our surgeons between the first 27 and last 21 months of the study period. The numbers reported herein reflect the actual wRVUs earned by the surgeon at the time the CPT was billed for. Despite a lack of generalizability, dollar collections cannot be ignored. It is important to acknowledge that a 6.5% decrease in net patient revenue, though not statistically significant, may be considered meaningful by administrators and lead to institutional changes. As revenue is dependent on payer mix, one must address any changes in
Table 1 Payer mix as a percent of patient encounters before and after implementation of the ACS service model for the (A) General Surgery (GS) service and (B) the Trauma Critical Care (TCC) service which subsequently became the Acute Care Surgery (ACS) service. By the Chi-squared test of independence, both services experienced statistically significant payer mix changes from the pre- to postACS period (p < 0.001 for both services). A. GeneralSurgeryService Insurance type Medicare Medicaid Commercial insurance Self-Pay Other
Pre-ACS 25.5% 12.9% 57.2% 1.7% 2.7%
Post-ACS 24.9% 15.2% 57.0% 1.3% 1.7%
Difference -0.7% +2.3% -0.1% -0.4% -1.0%
B. Trauma CriticalCare –CuteCareSurgeryService Insurance type
Pre-ACS
Post-ACS
Difference
Medicare Medicaid Commercial insurance Self-Pay Other
27.4% 13.4% 40.2% 4.0% 15.0%
32.7% 14.9% 36.3% 3.9% 12.1%
+5.3% +1.5% -3.8% -0.1% -2.9%
United States gross domestic product, it is prudent to develop and analyze service models with fiduciary frameworks.16 Herein, we demonstrate a generalizable method for analyzing the financial impact of an ACS model on a GS service line that previously managed EGS patients. In this study, the GS service maintained a wRVU/FTE ratio consistent with its pre-ACS level despite a significant decrease in afterhours case volume. The concern that general surgeons’ productivity would be threatened by the loss of EGS patients is not supported by our findings.10,17 Our results suggest that our GS service line was able to increase the number of wRVUs generated during normal-hours to compensate for lost after-hours productivity. In other words, the general surgeons were actually more productive during normal hours in the post-ACS period. The reduction in after-hours workload would seemingly reduce the total clinical productivity for the GS service. However, several factors may attenuate these losses. One possible contributing explanation is a change in case mix that focused more on the individual surgeon's subspecialty, with an attendant increase in wRVU/case ratio. For example, comparing the pre- and post- ACS periods, the GS service had a 92% reduction in the number of laparoscopic appendectomies performed, and a 39% increase in the number of laparoscopic sleeve gastrectomies performed. The possibility of increasing access to local 29
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payer mix when performing such analyses. The study period herein corresponded to major national and state level insurance reform including the expansion of Medicaid in the state of Vermont as part of the Affordable Care Act. With these simultaneous extraneous factors on payer mix it is difficult to make any definitive conclusions about the effect shifting EGS patients to the ACS service had on the GS service payer mix as previous studies have quantified.11 Given the widespread adoption of the ACS model, studies evaluating clinical outcomes, cost-effectiveness, and the impact on hospital finances must continue.1 In today's climate of unsustainable health care costs, the need to include economic analyses of such paradigm changes cannot be overemphasized. Our results build on a growing foundation of evidence supporting the transition of EGS patient management from traditional on-call GS services to an ACS model.
2. Santry HP, Madore JC, Collins CE, et al. Variations in the implementation of acute care surgery: results from a national survey of university-affiliated hospitals. J Trauma Acute Care Surg. 2015;78:60–78. 3. Santry HP, Pringle PL, Collins CE, Kiefe CI. A qualitative analysis of acute care surgery in the United States: it's more than just “a competent surgeon with a sharp knife and a willing attitude. Surgery. 2014;155:809–825. 4. Earley AS, Pryor JP, Kim PK, et al. An acute care surgery model improves outcomes in patients with appendicitis. Ann Surg Lippincott,. 2006;244:498–504. 5. Ekeh AP, Monson B, Wozniak CJ, et al. Management of acute appendicitis by an acute care surgery service: is operative intervention timely? J. Am Coll Surg. 2008;207:43–48. 6. Gandy RC, Truskett PG, Wong SW, et al. Outcomes of appendicectomy in an acute care surgery model. Med J Aust. 2010;193:281–284. 7. Cubas RF, Gómez NR, Rodriguez S, et al. Outcomes in the management of appendicitis and cholecystitis in the setting of a new acute care surgery service model: impact on timing and cost. J Am Coll Surg. 2012;215:715–721. 8. Britt RC, Bouchard C, Weireter LJ, Britt LD. Impact of acute care surgery on biliary disease. J Am Coll Surg. 2010;210:595–599. 9. Nagaraja V, Eslick GD, Cox MR. The acute surgical unit model verses the traditional “on call” model: a systematic review and meta-analysis. World J Surg. 2014;38:1381–1387. 10. Jurkovich GJ, Rozycki GS. Acute care surgery: real or imagined threat to the general surgeon. Am J Surg. 2010;199:862–863. 11. Miller PR, Wildman EA, Chang MC, Meredith JW. Acute care surgery: impact on practice and economics of elective surgeons. J Am Coll Surg. 2012;214:531–535. 12. Barnes SL, Cooper CJ, Coughenour JP, et al. Impact of acute care surgery to departmental productivity. J Trauma Inj Infect Crit Caress. 2011;71:1027–1034. 13. Wai PY, O'Hern T, Andersen DO, et al. Impact of business infrastructure on financial metrics in departments of surgery. Surgery. 2012;152:729–737. 14. Lu Y, Arenson RL. The academic radiologist's clinical productivity. Acad Radiol. 2005;12:1211–1223. 15. Paine AN, Andritsos DA, Fitzgerald JR, Norotsky MC, Malhotra AK, Tsai M. The operational impact of an acute care surgical service on operating room metrics. Perioper Care Oper Room Manag. 2017;8:38–41. 16. Muñoz E, Muñoz W, Wise L. National and surgical health care expenditures, 2005–2025. Ann Surg. 2010;251:195–200. 17. Malangoni MA. Acute care surgery: the general surgeon's perspective. Surgery. 2007;141:324–326. 18. Ariely D, Lanier WL. Disturbing trends in physician burnout and satisfaction with work-life balance. Mayo Clin Proc. 2015;90:1593–1596. 19. Kc DS, Terwiesch C. Impact of workload on service time and patient safety: an econometric analysis of hospital operations. Manage Sci Informs. 2009;55:1486–1498. 20. Muller IR, Eldakar-Hein ST, Ames E, Rosen LD, Urman RD, Tsai M. Potential association between physician burnout rates and operating margins: specialty-specific analysis. J Med Pract Manag. 2017;32(4):233–238 PMID: 29969540. 21. Dewa CS, Jacobs P, Thanh NX, Loong D. An estimate of the cost of burnout on early retirement and reduction in clinical hours of practicing physicians in Canada. BMC Health Serv Res BioMed Central. 2014;14:254.
Author contribution Study conception and design: Tsai, Malhotra, Norotsky, Borrazzo, Paine. Acquisition of data: Tsai, Paine, Krompf. Analysis and interpretation of data: Tsai, Ahern, Paine, Krompf. Drafting of manuscript: Tsai, Paine, Krompf. Critical revision: Tsai, Paine, Krompf, Borrazzo, Ahern, Norotsky. Declarations of interest None. Funding disclosure Author TPA was supported by a grant from the National Institute of General Medical Sciences at the National Institutes of Health (P20 GM103644). References 1. Collins CE, Pringle PL, Santry HP. Innovation or rebranding, acute care surgery diffusion will continue. J Surg Res. 2015;197:354–362.
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