- Email: [email protected]
Using an at-risk salary model to improve throughput in academic medical center operating rooms
Journal of Clinical Anesthesia (2016) 34, 416–419
Original Contribution
Using an at-risk salary model to improve throughput in academic medical center operating rooms☆,☆☆ Rachel M. Kacmar MD a,⁎, Brian M. Davidson MD b,1 , Matthew Victor MD a,2 , Ken Bullard BS a,3 , Jose Melendez MD a,4 a
Department of Anesthesiology, University of Colorado School of Medicine, 12401 E. 17th Ave, Mailstop B113, Aurora, CO 80045 Department of Anesthesiology, St Mary's Medical Center, 2635 N 7th St, Grand Junction, CO 81501
b
Received 12 August 2015; accepted 17 May 2016
Keywords: Operating room efficiency; Incentive; Performance metric; At-risk salary model
Abstract Study objective: The objective was to analyze if an at-risk salary model for faculty anesthesiologists could improve on-time first case starts (FCSs) and case turnovers (TOs) in an academic hospital inpatient operating room (IOR) and ambulatory surgery center (ASC). Organizational goals were 65% and 70% on-time FCS and case TO times for IOR and ASC, respectively. Design: This was a retrospective study. Setting: Surgical cases performed at both the IORs and the ASCs at a large academic medical center were included. Interventions: We converted 5% to 7% (academic rank dependent) of anesthesiologist salary from guaranteed to an at-risk salary model. Salary was earned back on a case-by-case basis by starting cases on time or by documenting a valid reason for case delay in the anesthesia record. On-time first case and goal TO times were determined using American Association of Clinical Directors standard definitions. Measurements: Data were reviewed for 1 year prior to implementation of the at-risk salary model and for 1 year after the implementation. Monthly average on-time FCS and TO times were compared between the preimplementation and postimplementation time frames. Data were analyzed using analysis of variance for repeated measures. Main Results: After the implementation of the at-risk salary model, the organization experienced a 33% and 86% improvement in on-time FCSs (Pb .01) in the inpatient and ambulatory operating rooms, respectively. A 41% (IOR) and 44% (ASC) improvement in timely case TOs (Pb .01) was also seen. Conclusions: Anesthesiologists can drive efficiency in an operating room setting. By incentivizing on-time FCS and timely case TO with an at-risk salary model for faculty anesthesiologists, we were able to demonstrate a sustained significant improvement for these metrics. In both an inpatient and an ambulatory setting, operating room efficiency may be best served by aligning provider financial incentives with desired outcome metrics. © 2016 Elsevier Inc. All rights reserved.
☆
Disclosures/Conflict of Interest: None. This work was previously presented in part at the 2010 American Society of Anesthesiologist's Annual Meeting. ⁎ Corresponding author. Tel.: +1 720 848 6726. E-mail addresses: [email protected] (R.M. Kacmar), [email protected] (B.M. Davidson), [email protected] (M. Victor), [email protected] (K. Bullard), [email protected] (J. Melendez). 1 Tel.: +1,970,298 7077. 2 Tel.: +1,720,848 6726. 3 Tel.: +1,720,848 6747. 4 Tel.: +1,720,848 6752. ☆☆
http://dx.doi.org/10.1016/j.jclinane.2016.05.028 0952-8180/© 2016 Elsevier Inc. All rights reserved.
At-Risk Salary Model for Anesthesiologists
1. Introduction The operating room (OR) revenue is a key component of the financial success of a hospital. It is also one of the costliest portions for the institution. In addition, surgeon and patient satisfaction are inexorably tied to OR success through increased surgical volumes. Surgeon satisfaction is highly dependent on ease of throughput. Hence, OR efficiency is a priority for health systems [1,2]. Medical executive committees and C-suites equate operational OR efficiency with first case starts, turnovers (TOs), and room utilization. If routine delays occur, the entire OR staff is affected [3,4], and patient and surgeon satisfaction will suffer [5]. Numerous publications describe attempts to improve OR efficiency via reduction in TO time (TOT) and increases in first case on-time (OT) starts via process improvements such as Six Sigma, team training, and systematic design [1,2,4,6–8]. Little is known about whether simple individual financial incentive, as opposed to broad OR reorganization, or changes in case scheduling, could lead to improved OR efficiency. The objective of our study was to analyze whether creating an at-risk salary model (ARSM) for faculty anesthesiologists could improve the percentage of OT first case starts and case TOs in an academic hospital inpatient operating room (IOR) and ambulatory surgery center (ASC).
2. Materials and methods 2.1. OR organization The University of Colorado Hospital is a large academic medical center with more than 30 anesthetizing locations. A medical direction model is used where each faculty attending anesthesiologist supervises 2 rooms staffed by resident anesthesiologists or 2 to 4 rooms staffed by certified resident nurse anesthetists (CRNAs) or anesthesia assistants. There are 2 distinct anesthetizing locations: the IORs and an ASC connected to the main hospital. The IOR includes electrophysiology and interventional radiology and the ASC included the gastrointestinal suites. In each setting, anesthesia providers are responsible for transporting patients from the preoperative setting to the OR. Transport cannot occur until all of the following elements occur: perioperative nursing intake, both surgical and anesthesia history and physical and consents, surgical site mark, and OR nurse check. All first cases (IOR and ASC) start at 7:30 AM (8:30 AM Mondays) and target room TOTs are 30 minutes for the IOR and 20 minutes for ASC ORs. OT first case and goal TOTs were determined using American Association of Clinical Directors standard definitions.
2.2. At-risk salary model We converted 5% to 7% (academic rank dependent) of faculty anesthesiologist salary from guaranteed to an ARSM.
417 Salary could be earned back on a case-by-case basis by starting OR cases OT or by documenting a valid reason for a case delay in the anesthesia electronic health record. Valid reasons for delay included all delays not related to anesthesia care or evaluation (Table 1). Faculty at-risk salary incentive was further calculated to $13 for each OT first case and TO, or valid delay reason, in the ASC and $20 for each OT first case start and TO, or valid delay reason, in the IOR. The ARSM incentive is distributed monthly as part of each faculty member's overall incentive pay. The ARSM was initiated in January 2009.
2.3. Goals for OR efficiency Our organizational goals were 65% average OT IOR first case OT start and TO and 70% for similar metrics in the ASC ORs. OT start was defined as “the patient in the room” at or before the scheduled start time. On-time TO was defined as “patient out of the room” to “next patient in the room” within the specified 20 (ASC) or 30 (IOR) minutes. All anesthesia providers received daily e-mails detailing individual performance on meeting OT first case starts and timely case TOs.
2.4. Data collection and analysis The percentages of OT first case starts and TOTs are reported daily to all anesthesia providers at the University of Colorado. These data were collected and averaged monthly for 12 months
Table 1 Valid nonanesthesia delay codes for late case starts and/or delayed case turnovers Delay category
Specific delay reason
Patient/family related delay
Patient arrived late Family, religion, etc Last case ended early PACU hold Scheduled start time Laboratory tests delayed Insurance hold Transport delay Epic (EMR) Notes, consent, marking not complete Surgeon unavailable (notes, consent, marking complete) Complex patient without preprocedural services evaluation Surgeon running 2 rooms Preoperative prep (IV, meds, etc) not complete Late bathroom needs OR not ready for patient
System delay
Surgical team delay
Perioperative nursing delay
PACU = postanesthesia recovery unit; EMR = electronic medical record; IV = intravenous; OR = operating room.
418 prior to implementation of the ARSM (January–December 2008) and for 12 months after the implementation (January-December 2009). Cases that were not scheduled (emergency, urgent, addon) or that occurred on weekends and/or holidays were not included in the analysis. Monthly average OT first case starts and TOTs were compared between the preimplementation and postimplementation time frames for both the IOR and the ASC. Data were analyzed using analysis of variance for repeated measures. Pb .01 was considered significant.
3. Results 3.1. Inpatient ORs In the 12 months prior to the implementation of the ARSM for faculty anesthesiologists, 49% of IOR first start cases were OT compared with 65% of first start cases post-ASRM (33% improvement, Pb .01). The percentage of OT case TOs in the IOR improved by 41% after implementation of the ARSM (39% compared with 55%, Pb .01). Average TOT was not significantly different between the 2 periods (36:48 pre-ARSM vs 36:20 post-ARSM).
3.2. ASC operating rooms There was an 85% improvement in OT first case starts in the ASC ORs after implementation of the ARSM (39% vs 72%, Pb .01). OT case TOs improved by 44% post-ARSM (52% vs 75%, Pb .01). Average TOT improved by nearly 2 minutes (20:32 vs 18:46) after implementation of the ARSM (Fig. 1).
4. Discussion We demonstrated that by creating a financial incentive in the form of a partial ARSM for faculty attending anesthesiologists at a large academic medical center, we could improve both OT first case starts and OT case TOs. Many groups have
Fig. 1 Percent of on-time first case starts and on-time case turnovers before and after implementation of at-risk salary model. ARSM = at-risk salary model; IOR = inpatient operating rooms; ASC = ambulatory surgery center; FCS = first case start; TO = turnover.
R.M. Kacmar et al. previously attempted to show increased OR efficiency through improved organization, improving TOTs and even parallel processing wherein surgeons prepare patients in the preoperative area [5]. A recent study utilized a small biweekly financial incentive plan for members of the perioperative team (OR nurses, surgical scrub technicians, anesthesia technicians, CRNAs) to improve the percent of case turnaround times less than 60 minutes as well as the percent of OT first case starts [9]. However, that study site had only 8 ORs and cares for primarily trauma patients, so results may not be widely applicable to other academic centers and large hospital systems. Increased OR geometry creates systematic issues for block time scheduling and utilization, and patient throughput, and the increased number of anesthesia, nursing, and surgical providers creates challenges in cohesive team performance. We believe that we are the first to utilize a simple monetary incentive to motivate anesthesiology faculty to significantly increase OR efficiency in a large academic center. In addition to the financial enticement, daily reports of anesthesiologist efficiency are distributed to the entire anesthesiology department in a summary e-mail with performance stratified by individual provider. Thus, faculty members are able to gauge their performance against their peers as well as conduct self-review on a longitudinal scale. A similar profiling has previously been shown to contribute to improved anesthesiologist performance in efficiency metrics [10]. For the purposes of this study, we did not include analysis of potential impact of the daily e-mails on OT first case starts and TOs. OR time is estimated to cost $10 to $30 per minute [1], and depending on surgical procedure, OR costs can account for nearly 40% of the overall hospital cost for an inpatient surgical patient [11]. Simply asking staff to work harder is insufficient motivation to improve efficiency. When delays occur, the OR schedule is necessarily shifted, which often leads to increased anesthesia and nursing staff utilization after normal working hours. In many cases, this adds cost, not only in terms of OR time usage but also in staffing compensation where most academic anesthesiology departments provide incentive pay for call or off-hour work [3]. In addition, surgical block time is impeded upon by the preceding cases, leading to both surgeon and patient dissatisfaction. Our incentive ARSM relied only on faculty anesthesia provider motivation and did not include the surgical or nursing teams. Certain delay reasons place blame on other care providers; however, our system does not allow for penalties depending on the cause for delay. In addition, the nature of the implementation prevented objection by other groups as only anesthesiologists were involved. Some authors have brought up nursing leadership concerns that attempts to improve TOTs and encouraging early patient entry into the OR could negatively impact patient safety [2]. As long as there is adequate anesthesia staff to attend the patient during induction and intubation, patient safety should be ensured. When cases start and are turned over OT, there is potential to perform additional procedures over the course of a day or week, and in some cases even open surgical block time [5,12,13]. Surgeons may have an improved perception of TOT when they see the anesthesia team actively working to ready the patient for surgery [14].
At-Risk Salary Model for Anesthesiologists Our study is not without limitations. We only used the ARSM for faculty attending anesthesiologists and did not have additional incentive for the CRNAs, anesthesia assistants, and residents that often have more control on when the patient enters the OR. In addition, we did not examine the other potential contributing factors for improvement and/or delays in case starts and case TOs featured by other authors. In some cases, the length of time between cases is out of the control of the OR staff, such as when an insurance hold occurs. We also used the definitions of “case start” and “turnover” that are based on when patients enter and exit the OR. Some authors may define such times based on when the patient is ready for surgery or when the surgical procedure is completed [15]. The timing of this study was also shortly prior to significant growth throughout the department of anesthesiology, and the impact of this growth is still under investigation. The incentive described within this article is only the first in a plan for stepwise implementation of efficiency performance incentives for anesthesiology faculty at our institution. In conclusion, we have shown that an ARSM for faculty anesthesiologists at an academic medical center can lead to significant improvement in OT first case starts and OT case TOs in both inpatient and ambulatory settings. In the future, assessing the ability of such a system to have a sustained impact on all anesthesia provider performances and overall OR staff satisfaction and utilization will be important to determine if this is a feasible long-term solution.
References [1] Sandberg WS, Daily B, Egan M, et al. Deliberate perioperative systems design improves operating room throughput. Anesthesiology 2005; 103(2):406-18.
419 [2] Kodali BS, Kim D, Bleday R, Flanagan H, Urman RD. Successful strategies for the reduction of operating room turnover times in a tertiary care academic medical center. J Surg Res 2014;187(2):403-11. [3] Abouleish AE, Dexter F, Whitten CW, Zavaleta JR, Prough DS. Quantifying net staffing costs due to longer-than-average surgical case durations. Anesthesiology 2004;100(2):403-12. [4] Harders M, Malangoni MA, Weight S, Sidhu T. Improving operating room efficiency through process redesign. Surgery 2006;140(4):509-14 [discussion 514–506]. [5] Friedman DM, Sokal SM, Chang Y, Berger DL. Increasing operating room efficiency through parallel processing. Ann Surg 2006;243(1): 10-4. [6] Cima RR, Brown MJ, Hebl JR, et al. Use of lean and six sigma methodology to improve operating room efficiency in a high-volume tertiary-care academic medical center. J Am Coll Surg 2011;213(1): 83-92 [discussion 93–84]. [7] Armour Forse R, Bramble JD, McQuillan R. Team training can improve operating room performance. Surgery 2011;150(4):771-8. [8] Adams R, Warner P, Hubbard B, Goulding T. Decreasing turnaround time between general surgery cases: a six sigma initiative. J Nurs Adm 2004;34(3):140-8. [9] Scalea TM, Carco D, Reece M, Fouche YL, Pollak AN, Nagarkatti SS. Effect of a novel financial incentive program on operating room efficiency. JAMA Surg 2014;149(9):920-4. [10] St Jacques PJ, Patel N, Higgins MS. Improving anesthesiologist performance through profiling and incentives. J Clin Anesth 2004; 16(7):523-8. [11] Macario A, Vitez TS, Dunn B, McDonald T. Where are the costs in perioperative care? Analysis of hospital costs and charges for inpatient surgical care. Anesthesiology 1995;83(6):1138-44. [12] Avery DM III, Matullo KS. The efficiency of a dedicated staff on operating room turnover time in hand surgery. J Hand Surg Am 2014; 39(1):108-10. [13] Olmstead J, Coxon P, Falcone D, Ignas L, Foss P. World-class OR turnaround times: secrets uncovered. AORN J 2007;85(5):942-5 [947–949]. [14] Masursky D, Dexter F, Isaacson SA, Nussmeier NA. Surgeons' and anesthesiologists' perceptions of turnover times. Anesth Analg 2011; 112(2):440-4. [15] Mazzei WJ. Operating room start times and turnover times in a university hospital. J Clin Anesth 1994;6(5):405-8.
Original Contribution
Using an at-risk salary model to improve throughput in academic medical center operating rooms☆,☆☆ Rachel M. Kacmar MD a,⁎, Brian M. Davidson MD b,1 , Matthew Victor MD a,2 , Ken Bullard BS a,3 , Jose Melendez MD a,4 a
Department of Anesthesiology, University of Colorado School of Medicine, 12401 E. 17th Ave, Mailstop B113, Aurora, CO 80045 Department of Anesthesiology, St Mary's Medical Center, 2635 N 7th St, Grand Junction, CO 81501
b
Received 12 August 2015; accepted 17 May 2016
Keywords: Operating room efficiency; Incentive; Performance metric; At-risk salary model
Abstract Study objective: The objective was to analyze if an at-risk salary model for faculty anesthesiologists could improve on-time first case starts (FCSs) and case turnovers (TOs) in an academic hospital inpatient operating room (IOR) and ambulatory surgery center (ASC). Organizational goals were 65% and 70% on-time FCS and case TO times for IOR and ASC, respectively. Design: This was a retrospective study. Setting: Surgical cases performed at both the IORs and the ASCs at a large academic medical center were included. Interventions: We converted 5% to 7% (academic rank dependent) of anesthesiologist salary from guaranteed to an at-risk salary model. Salary was earned back on a case-by-case basis by starting cases on time or by documenting a valid reason for case delay in the anesthesia record. On-time first case and goal TO times were determined using American Association of Clinical Directors standard definitions. Measurements: Data were reviewed for 1 year prior to implementation of the at-risk salary model and for 1 year after the implementation. Monthly average on-time FCS and TO times were compared between the preimplementation and postimplementation time frames. Data were analyzed using analysis of variance for repeated measures. Main Results: After the implementation of the at-risk salary model, the organization experienced a 33% and 86% improvement in on-time FCSs (Pb .01) in the inpatient and ambulatory operating rooms, respectively. A 41% (IOR) and 44% (ASC) improvement in timely case TOs (Pb .01) was also seen. Conclusions: Anesthesiologists can drive efficiency in an operating room setting. By incentivizing on-time FCS and timely case TO with an at-risk salary model for faculty anesthesiologists, we were able to demonstrate a sustained significant improvement for these metrics. In both an inpatient and an ambulatory setting, operating room efficiency may be best served by aligning provider financial incentives with desired outcome metrics. © 2016 Elsevier Inc. All rights reserved.
☆
Disclosures/Conflict of Interest: None. This work was previously presented in part at the 2010 American Society of Anesthesiologist's Annual Meeting. ⁎ Corresponding author. Tel.: +1 720 848 6726. E-mail addresses: [email protected] (R.M. Kacmar), [email protected] (B.M. Davidson), [email protected] (M. Victor), [email protected] (K. Bullard), [email protected] (J. Melendez). 1 Tel.: +1,970,298 7077. 2 Tel.: +1,720,848 6726. 3 Tel.: +1,720,848 6747. 4 Tel.: +1,720,848 6752. ☆☆
http://dx.doi.org/10.1016/j.jclinane.2016.05.028 0952-8180/© 2016 Elsevier Inc. All rights reserved.
At-Risk Salary Model for Anesthesiologists
1. Introduction The operating room (OR) revenue is a key component of the financial success of a hospital. It is also one of the costliest portions for the institution. In addition, surgeon and patient satisfaction are inexorably tied to OR success through increased surgical volumes. Surgeon satisfaction is highly dependent on ease of throughput. Hence, OR efficiency is a priority for health systems [1,2]. Medical executive committees and C-suites equate operational OR efficiency with first case starts, turnovers (TOs), and room utilization. If routine delays occur, the entire OR staff is affected [3,4], and patient and surgeon satisfaction will suffer [5]. Numerous publications describe attempts to improve OR efficiency via reduction in TO time (TOT) and increases in first case on-time (OT) starts via process improvements such as Six Sigma, team training, and systematic design [1,2,4,6–8]. Little is known about whether simple individual financial incentive, as opposed to broad OR reorganization, or changes in case scheduling, could lead to improved OR efficiency. The objective of our study was to analyze whether creating an at-risk salary model (ARSM) for faculty anesthesiologists could improve the percentage of OT first case starts and case TOs in an academic hospital inpatient operating room (IOR) and ambulatory surgery center (ASC).
2. Materials and methods 2.1. OR organization The University of Colorado Hospital is a large academic medical center with more than 30 anesthetizing locations. A medical direction model is used where each faculty attending anesthesiologist supervises 2 rooms staffed by resident anesthesiologists or 2 to 4 rooms staffed by certified resident nurse anesthetists (CRNAs) or anesthesia assistants. There are 2 distinct anesthetizing locations: the IORs and an ASC connected to the main hospital. The IOR includes electrophysiology and interventional radiology and the ASC included the gastrointestinal suites. In each setting, anesthesia providers are responsible for transporting patients from the preoperative setting to the OR. Transport cannot occur until all of the following elements occur: perioperative nursing intake, both surgical and anesthesia history and physical and consents, surgical site mark, and OR nurse check. All first cases (IOR and ASC) start at 7:30 AM (8:30 AM Mondays) and target room TOTs are 30 minutes for the IOR and 20 minutes for ASC ORs. OT first case and goal TOTs were determined using American Association of Clinical Directors standard definitions.
2.2. At-risk salary model We converted 5% to 7% (academic rank dependent) of faculty anesthesiologist salary from guaranteed to an ARSM.
417 Salary could be earned back on a case-by-case basis by starting OR cases OT or by documenting a valid reason for a case delay in the anesthesia electronic health record. Valid reasons for delay included all delays not related to anesthesia care or evaluation (Table 1). Faculty at-risk salary incentive was further calculated to $13 for each OT first case and TO, or valid delay reason, in the ASC and $20 for each OT first case start and TO, or valid delay reason, in the IOR. The ARSM incentive is distributed monthly as part of each faculty member's overall incentive pay. The ARSM was initiated in January 2009.
2.3. Goals for OR efficiency Our organizational goals were 65% average OT IOR first case OT start and TO and 70% for similar metrics in the ASC ORs. OT start was defined as “the patient in the room” at or before the scheduled start time. On-time TO was defined as “patient out of the room” to “next patient in the room” within the specified 20 (ASC) or 30 (IOR) minutes. All anesthesia providers received daily e-mails detailing individual performance on meeting OT first case starts and timely case TOs.
2.4. Data collection and analysis The percentages of OT first case starts and TOTs are reported daily to all anesthesia providers at the University of Colorado. These data were collected and averaged monthly for 12 months
Table 1 Valid nonanesthesia delay codes for late case starts and/or delayed case turnovers Delay category
Specific delay reason
Patient/family related delay
Patient arrived late Family, religion, etc Last case ended early PACU hold Scheduled start time Laboratory tests delayed Insurance hold Transport delay Epic (EMR) Notes, consent, marking not complete Surgeon unavailable (notes, consent, marking complete) Complex patient without preprocedural services evaluation Surgeon running 2 rooms Preoperative prep (IV, meds, etc) not complete Late bathroom needs OR not ready for patient
System delay
Surgical team delay
Perioperative nursing delay
PACU = postanesthesia recovery unit; EMR = electronic medical record; IV = intravenous; OR = operating room.
418 prior to implementation of the ARSM (January–December 2008) and for 12 months after the implementation (January-December 2009). Cases that were not scheduled (emergency, urgent, addon) or that occurred on weekends and/or holidays were not included in the analysis. Monthly average OT first case starts and TOTs were compared between the preimplementation and postimplementation time frames for both the IOR and the ASC. Data were analyzed using analysis of variance for repeated measures. Pb .01 was considered significant.
3. Results 3.1. Inpatient ORs In the 12 months prior to the implementation of the ARSM for faculty anesthesiologists, 49% of IOR first start cases were OT compared with 65% of first start cases post-ASRM (33% improvement, Pb .01). The percentage of OT case TOs in the IOR improved by 41% after implementation of the ARSM (39% compared with 55%, Pb .01). Average TOT was not significantly different between the 2 periods (36:48 pre-ARSM vs 36:20 post-ARSM).
3.2. ASC operating rooms There was an 85% improvement in OT first case starts in the ASC ORs after implementation of the ARSM (39% vs 72%, Pb .01). OT case TOs improved by 44% post-ARSM (52% vs 75%, Pb .01). Average TOT improved by nearly 2 minutes (20:32 vs 18:46) after implementation of the ARSM (Fig. 1).
4. Discussion We demonstrated that by creating a financial incentive in the form of a partial ARSM for faculty attending anesthesiologists at a large academic medical center, we could improve both OT first case starts and OT case TOs. Many groups have
Fig. 1 Percent of on-time first case starts and on-time case turnovers before and after implementation of at-risk salary model. ARSM = at-risk salary model; IOR = inpatient operating rooms; ASC = ambulatory surgery center; FCS = first case start; TO = turnover.
R.M. Kacmar et al. previously attempted to show increased OR efficiency through improved organization, improving TOTs and even parallel processing wherein surgeons prepare patients in the preoperative area [5]. A recent study utilized a small biweekly financial incentive plan for members of the perioperative team (OR nurses, surgical scrub technicians, anesthesia technicians, CRNAs) to improve the percent of case turnaround times less than 60 minutes as well as the percent of OT first case starts [9]. However, that study site had only 8 ORs and cares for primarily trauma patients, so results may not be widely applicable to other academic centers and large hospital systems. Increased OR geometry creates systematic issues for block time scheduling and utilization, and patient throughput, and the increased number of anesthesia, nursing, and surgical providers creates challenges in cohesive team performance. We believe that we are the first to utilize a simple monetary incentive to motivate anesthesiology faculty to significantly increase OR efficiency in a large academic center. In addition to the financial enticement, daily reports of anesthesiologist efficiency are distributed to the entire anesthesiology department in a summary e-mail with performance stratified by individual provider. Thus, faculty members are able to gauge their performance against their peers as well as conduct self-review on a longitudinal scale. A similar profiling has previously been shown to contribute to improved anesthesiologist performance in efficiency metrics [10]. For the purposes of this study, we did not include analysis of potential impact of the daily e-mails on OT first case starts and TOs. OR time is estimated to cost $10 to $30 per minute [1], and depending on surgical procedure, OR costs can account for nearly 40% of the overall hospital cost for an inpatient surgical patient [11]. Simply asking staff to work harder is insufficient motivation to improve efficiency. When delays occur, the OR schedule is necessarily shifted, which often leads to increased anesthesia and nursing staff utilization after normal working hours. In many cases, this adds cost, not only in terms of OR time usage but also in staffing compensation where most academic anesthesiology departments provide incentive pay for call or off-hour work [3]. In addition, surgical block time is impeded upon by the preceding cases, leading to both surgeon and patient dissatisfaction. Our incentive ARSM relied only on faculty anesthesia provider motivation and did not include the surgical or nursing teams. Certain delay reasons place blame on other care providers; however, our system does not allow for penalties depending on the cause for delay. In addition, the nature of the implementation prevented objection by other groups as only anesthesiologists were involved. Some authors have brought up nursing leadership concerns that attempts to improve TOTs and encouraging early patient entry into the OR could negatively impact patient safety [2]. As long as there is adequate anesthesia staff to attend the patient during induction and intubation, patient safety should be ensured. When cases start and are turned over OT, there is potential to perform additional procedures over the course of a day or week, and in some cases even open surgical block time [5,12,13]. Surgeons may have an improved perception of TOT when they see the anesthesia team actively working to ready the patient for surgery [14].
At-Risk Salary Model for Anesthesiologists Our study is not without limitations. We only used the ARSM for faculty attending anesthesiologists and did not have additional incentive for the CRNAs, anesthesia assistants, and residents that often have more control on when the patient enters the OR. In addition, we did not examine the other potential contributing factors for improvement and/or delays in case starts and case TOs featured by other authors. In some cases, the length of time between cases is out of the control of the OR staff, such as when an insurance hold occurs. We also used the definitions of “case start” and “turnover” that are based on when patients enter and exit the OR. Some authors may define such times based on when the patient is ready for surgery or when the surgical procedure is completed [15]. The timing of this study was also shortly prior to significant growth throughout the department of anesthesiology, and the impact of this growth is still under investigation. The incentive described within this article is only the first in a plan for stepwise implementation of efficiency performance incentives for anesthesiology faculty at our institution. In conclusion, we have shown that an ARSM for faculty anesthesiologists at an academic medical center can lead to significant improvement in OT first case starts and OT case TOs in both inpatient and ambulatory settings. In the future, assessing the ability of such a system to have a sustained impact on all anesthesia provider performances and overall OR staff satisfaction and utilization will be important to determine if this is a feasible long-term solution.
References [1] Sandberg WS, Daily B, Egan M, et al. Deliberate perioperative systems design improves operating room throughput. Anesthesiology 2005; 103(2):406-18.
419 [2] Kodali BS, Kim D, Bleday R, Flanagan H, Urman RD. Successful strategies for the reduction of operating room turnover times in a tertiary care academic medical center. J Surg Res 2014;187(2):403-11. [3] Abouleish AE, Dexter F, Whitten CW, Zavaleta JR, Prough DS. Quantifying net staffing costs due to longer-than-average surgical case durations. Anesthesiology 2004;100(2):403-12. [4] Harders M, Malangoni MA, Weight S, Sidhu T. Improving operating room efficiency through process redesign. Surgery 2006;140(4):509-14 [discussion 514–506]. [5] Friedman DM, Sokal SM, Chang Y, Berger DL. Increasing operating room efficiency through parallel processing. Ann Surg 2006;243(1): 10-4. [6] Cima RR, Brown MJ, Hebl JR, et al. Use of lean and six sigma methodology to improve operating room efficiency in a high-volume tertiary-care academic medical center. J Am Coll Surg 2011;213(1): 83-92 [discussion 93–84]. [7] Armour Forse R, Bramble JD, McQuillan R. Team training can improve operating room performance. Surgery 2011;150(4):771-8. [8] Adams R, Warner P, Hubbard B, Goulding T. Decreasing turnaround time between general surgery cases: a six sigma initiative. J Nurs Adm 2004;34(3):140-8. [9] Scalea TM, Carco D, Reece M, Fouche YL, Pollak AN, Nagarkatti SS. Effect of a novel financial incentive program on operating room efficiency. JAMA Surg 2014;149(9):920-4. [10] St Jacques PJ, Patel N, Higgins MS. Improving anesthesiologist performance through profiling and incentives. J Clin Anesth 2004; 16(7):523-8. [11] Macario A, Vitez TS, Dunn B, McDonald T. Where are the costs in perioperative care? Analysis of hospital costs and charges for inpatient surgical care. Anesthesiology 1995;83(6):1138-44. [12] Avery DM III, Matullo KS. The efficiency of a dedicated staff on operating room turnover time in hand surgery. J Hand Surg Am 2014; 39(1):108-10. [13] Olmstead J, Coxon P, Falcone D, Ignas L, Foss P. World-class OR turnaround times: secrets uncovered. AORN J 2007;85(5):942-5 [947–949]. [14] Masursky D, Dexter F, Isaacson SA, Nussmeier NA. Surgeons' and anesthesiologists' perceptions of turnover times. Anesth Analg 2011; 112(2):440-4. [15] Mazzei WJ. Operating room start times and turnover times in a university hospital. J Clin Anesth 1994;6(5):405-8.