Improving anesthesiologist performance through profiling and incentives

doi:10.1016/j.jclinane.2004.03.003

Journal of Clinical Anesthesia

Volume 16, Issue 7, November 2004, Pages 523-528

https://doi.org/10.1016/j.jclinane.2004.03.003 Get rights and content

Abstract

Study objective

To determine the influence of profiling and incentives on anesthesiologist behavior in relation to several key indicators of performance.

Design

Prospective collection and analysis of operational data before and after implementation of a physician profiling, reporting, and incentive program.

Setting

University hospital.

Measurements

An intervention consisting of two components was studied with the intent of stimulating a high level of performance in relation to a peer group. The first component, a monthly report of physician performance via an individualized performance report, was provided to each physician for each of 6 months. The second component consisted of a financial incentive. For each month in the study, physicians were eligible to receive a variable financial incentive of between $0 and $500 per month depending on individual performance based scoring in relation to each other. Physician performance was tracked in five areas: 1) percentage of first cases of the day in the room at or before the scheduled in-room time, 2) percentage of cases with an anesthesia prep time less than a target, 3) percentage of cases delayed due to waiting for an anesthesiology patient evaluation, 4) percentage of cases delayed during the anesthesiology controlled time, and, 5) percentage of cases delayed due to waiting for the anesthesiology attending. Results were reported to each physician on a monthly basis, by e-mail distribution, of an individualized perioperative efficiency summary report. A monthly financial incentive was awarded to the top performing physicians in the form of a credit to the physician's personal CME/expense account. Also, all physicians received a rank order list of their performance on each indicator at the end of each month.

Main results

31 anesthesiologists, comprising the multispecialty division, and covering all services with the exception of obstetrics, pediatrics, and cardiothoracic anesthesia were tracked for 6 months. Compared to the first month, the percent of first cases of the day in the room at or before the scheduled start time and the percent of cases with an anesthesiology prep time less than target increased significantly (19 ± 4.6%, vs. 61 ± 6.5%, 95% CI, p < 0.001; and 57 ± 5.3%, vs. 73 ± 5.1%, 95% CI, p < 0 .001) during the sixth month. The mean number of cases per physician with a delay during anesthesiology controlled time decreased (14.9 ± 2.9 vs. 3.3 ± 1, p < 0.001), no change occurred in the number of cases with a delay due to waiting for an anesthesiology patient evaluation or number of cases delayed due to waiting for the anesthesiology attending in the sixth month compared with the first month.

Conclusion

Tracking and rewarding physician performance with monthly profiling and a financial incentive given to the best in a peer group improves anesthesiologist performance in several key areas.

Introduction

In most health care institutions, the operating room (OR) represents the largest source of both hospital revenue and costs.1 Operating room utilization and efficiency have been extensively studied.2, 3 Investigations have demonstrated the use of patient scheduling to maximize OR block time utilization,4 staff scheduling to minimize labor costs,5 materials systems analysis to decrease supply costs,6, 7 and individualized anesthetic techniques to speed patient throughput. 8, 9

The process of patient care is dependent on the coordinated efforts of a large number of care providers. It has been shown that surgeons, even within a single specialty, exhibit a wide variation in profitability depending on their practice patterns.10 Other providers may present significant variation in the motivation and ability to deliver efficient medical care, which may account for a significant portion of the wide range of profitability exhibited by health care institutions. Maximizing the productivity of individuals on the day of surgery is critical to perioperative process improvement and the goal of maximizing profit in the operating suite.

Overdyk et al.11 identified several indicators, such as first case of the day in-room time, anesthesia preparatory time, and anesthesiologist availability delays that are controllable by individual anesthesiolgists. Vitez and Macario12 have shown that identifying and setting performance standards can improve timely first-case starts and turnaround times. However, providing a financial reward and a peer group comparison to an individual anesthesiologist to incentivize performance improvement in this setting has not been studied to date. We hypothesized that providing both publicly posted, comparative timeliness-related performance data and a financial incentive to reward anesthesiologist efficiency would lead to performance improvement in the OR as measured by several key indicators.

Section snippets

Materials and methods

With Vanderbilt University Medical Center Institutional Review Board approval for the study, we collected performance data for 31 anesthesiologists providing care for 6618 surgical cases completed at Vanderbilt University Hospital, an academic tertiary-care hospital located in Nashville, Tennessee, between September 1, 2002 and February 28, 2003. The data of six anesthesiologists were excluded from analysis because these physicians were not present in the study group during both the first and

Results

A total of 31 anesthesiologists were tracked during the study period. Full-time equivalency ranged from one to five clinical OR days per week (20% to 100%). A total of 1261 cases were recorded in the initial period, and 1439 cases were recorded after the intervention. Mean age, inpatient percent, and ASA group did not vary between groups, whereas mean case time was significantly longer in the post-interventional group (Table 2).

Figure 1 shows that the percentage of first cases of the day

Discussion

The most significant performance improvement occurred in the category of first cases of the day entering the OR at or before their scheduled start time, with a 42% increase over the study period. These results compare similarly to results reported in 1998 by Vitez and Macario,12 in which institution of performance standards was found to decrease anesthesiology-related delays to timely first-case starts from 36% to 9%. However, our study included not just anesthesiology-related delays, but all

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Cited by (26)

Systems analysis of neurosurgical first-case delays identifies opportunities to optimize operating room efficiency
2022, Perioperative Care and Operating Room Management
Citation Excerpt :
Given the primary results of our study, future directions could include a quality improvement (QI) project to address first-case delays associated with patient preparation, medically complex patients, or patient bottlenecks.41 Based on previously published studies, an intervention could employ several strategies, including staff education, enhanced team communication, financial incentives, optimized systems-based protocols, “golden patient” selection (i.e. selecting medically fit first-case patients with an uncomplicated surgical plan), collaboration between management and OR staff in process improvement, or the Lean and Six Sigma methods.10,21,38,42–45 While the causes and magnitude of first-case delays in this study cannot be generalized to other neurosurgical practices, a generalizable takeaway that could be recapitulated at other institutions is our multimodal approach for diagnosing the causes of delays.
Operating room (OR) efficiency is a key target for optimizing healthcare delivery and value-based care. First-case delays are a common marker of OR efficiency. Our multidisciplinary team investigated the neurosurgical first-case delays at a large academic medical center.
We assessed all neurosurgical first-cases at the Massachusetts General Hospital between 7/1/18 and 7/1/19. We defined a delayed first-case as actual start (patient entering the OR) ≥ 15 minutes from the scheduled start time. We analyzed timestamp data in the electronic medical record (EMR) and used published methods to estimate costs associated with first-case delays. We also conducted direct process mapping and qualitative analyses of first-case delays.
Of 1063 neurosurgical first-cases, 283 were delayed (27%). The median delay was 25 minutes (IQR: 18 – 35 minutes). The total delay was 9432 minutes (157.2 hours) over one year, and the estimated costs associated with these delays ranged from $25,843.68 to $238,252.32. There was a significant difference between the American Society of Anesthesia (ASA) Physical Classification scores of delayed first-cases vs. non-delayed first-cases (p = 0.03). Late arrival to the hospital contributed to delayed first-case starts (p < 0.01). Qualitative analysis identified patient preparation as the most common cause of delayed first-cases and venous and arterial lines as the most common causes of patient preparation-related delays. Direct process mapping identified system-level inefficiencies unaccounted by timestamp or qualitative analysis.
First-case delays are multifactorial and can impact healthcare delivery and costs. This study demonstrates the potential of a multimodal approach that includes objective EMR data, an OR cost estimation, direct observation, and qualitative analysis in pinpointing perioperative inefficiency.
Time Is Money: Can Punctuality Decrease Operating Room Cost?
2020, Journal of the American College of Surgeons
Citation Excerpt :
In April 2017, the Division of Perioperative Services at our tertiary-care medical center launched a multifaceted FCOTS improvement initiative. Based on best practices3,4,10-13 and investigation of institutional pre-intervention workflow, the policy comprised 3 main components: defining FCOTS and stakeholder education regarding its importance; assignment of a discrete, standardized process for preoperative workflow known as “swim-lanes” (eFig. 1); and daily reporting of FCOTS rates and sources of failure to hospital leadership and surgical, anesthesiology, and nursing stakeholders. All physicians, nurses, and ancillary staff working within perioperative areas received role-directed education on this initiative in the months preceding roll-out.
Inefficient operating room (OR) use wastes resources. Studies have suggested “first case on-time starts” (FCOTS) reduce OR “idle time,” yet no direct association between FCOTS and markers of OR efficiency, like “last case on-time end” (LCOTE) or overtime costs, have been reported. We performed this study to evaluate factors associated with FCOTS, LCOTE, and OR overtime costs.
In April 2017, our medical center launched an FCOTS improvement initiative. Prospectively collected data concerning cases performed in the 6-month pre- (October 2016 to March 2017) and post-intervention (October 2017 to March 2018) periods were retrospectively analyzed. Elective, nontraumatic cases performed by orthopaedics, gynecology, urology, minimally invasive surgery, or colorectal surgery were eligible. Univariate and multivariable analyses were used to evaluate 3 outcomes of interest: the association between FCOTS and LCOTE (primary), the change in FCOTS rates after intervention implementation (secondary), and estimated overtime cost savings associated with FCOTS (secondary).
We analyzed 12,073 cases (6,095 pre- vs 5,978 post-intervention) performed over 2,631 OR days (1,401 pre vs 1,230 post). The FCOTS rate increased after intervention (76.1% vs 86.6%, p < 0.001), with post-intervention cases twice as likely to start on time (adjusted odds ratio [aOR] 2.07; 95% CI 1.73 to 2.46, p < 0.001). Additionally, starting on time was associated with a higher likelihood of LCOTE (aOR 1.76; 95% CI 1.38 to 2.24, p < 0.001) and 21.8 fewer overtime minutes (95% CI 13.7 to 29.8, p < 0.001) per OR day. Post-intervention estimated savings of $87,954 in direct OR costs over 6 months were associated with the FCOTS initiative.
The FCOTS initiative was associated with higher frequency of FCOTS, which was independently associated with LCOTE. This achieved an estimated 6-month cost savings of more than $80,000 in direct OR expenditures.
Using an at-risk salary model to improve throughput in academic medical center operating rooms
2016, Journal of Clinical Anesthesia
Citation Excerpt :
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.
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.
This was a retrospective study.
Surgical cases performed at both the IORs and the ASCs at a large academic medical center were included.
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.
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.
After the implementation of the at-risk salary model, the organization experienced a 33% and 86% improvement in on-time FCSs (P< .01) in the inpatient and ambulatory operating rooms, respectively. A 41% (IOR) and 44% (ASC) improvement in timely case TOs (P< .01) was also seen.
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.
The effectiveness of payment for performance in health care: A meta-analysis and exploration of variation in outcomes
2016, Health Policy
Citation Excerpt :
All 96 studies could be included in the logistic regression and 37 reported sufficient data to be included in the meta-analysis and meta-regression (see Supplementary files S12 and S13). Fig. 2 shows a forest plot of the 37 studies [23–59] included in the meta-analysis, stratified by evaluation design (RCT = 6, quasi-experimental = 11, and no control groups/before and after studies = 20). Fig. 3 shows them by domain of performances (processes or outcomes).
Pay for performance (P4P) incentive schemes are increasingly used world-wide to improve health system performance but results of evaluations vary considerably. A systematic analysis of this variation in the effects of P4P schemes is needed.
Evaluations of P4P schemes from any country were identified by searching for and updating systematic reviews of P4P schemes in health care in four bibliographic databases. Outcomes using different measures of effect were converted into standardized effect sizes (standardized mean difference, SMD) and each study was categorized as to whether or not it found a positive effect. Subgroup analysis, meta-regression and multilevel logistic regression were used to investigate factors explaining heterogeneity. Random-effects models were used because they take into account heterogeneity likely to be due to differences between studies rather than just chance. Sensitivity analysis was used to test the effect of different assumptions.
96 primary studies were identified; 37 were included in the meta-analysis and meta-regression and all 96 in the logistic regression. The proportion of observed variation in study results that can be explained by true heterogeneity (I²) was 99.9%. Estimates of effect of P4P schemes were lower in evaluations using randomized controlled trials (SMD = 0.08; 95% CI: 0.01–0.15) compared to no controls (0.15; 95% CI: 0.09–0.21), and lower for those measuring outcomes (e.g., smoking cessation) (SMD = 0.0; 95% CI: −0.01 to 0.01) compared to process measures (e.g., giving cessation advice) (0.18; 95% CI: 0.06–0.31).
Adjusting for other design features and the evaluation method, the odds of showing a positive effect was three times higher for schemes with larger incentives (>5% of salary/usual budget) (OR = 3.38; 95% CI: 1.07–10.64). There were non-statistically significant increases in the odds of success if the incentive is paid to individuals (as opposed to groups) (OR = 2.0; 95% CI: 0.62–6.56) and if there is a lower perceived risk of not earning the incentive (OR = 2.9; 95% CI: 0.78–10.83). Schemes evaluated using less rigorous designs were 24 times more likely to have positive estimates of effect than those using randomized controlled trials (OR = 24; 95% CI: 6.3–92.8).
Estimates of the effectiveness of incentive schemes on health outcomes are probably inflated due to poorly designed evaluations and a focus on process measures rather than health outcomes. Larger incentives and reducing the perceived risk of non-payment may increase the effect of these schemes on provider behavior.
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Numerous studies have considered opportunity costs of operating time
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^*: Director of Anesthesiology Informatics

^†: Director of Perioperative Informatics and Computing Group

^‡: Interim Chair, Department of Anesthesiology

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Original contributionImproving anesthesiologist performance through profiling and incentives

Abstract

Study objective

Design

Setting

Measurements

Main results

Conclusion

Introduction

Section snippets

Materials and methods

Results

Discussion

J Clin Anesth

Surg Clin North Am

J Clin Anesth

Where are the costs in perioperative care? Analysis of hospital costs and charges for inpatient surgical care

Anesthesiology

An operating room scheduling strategy to maximize the use of operating room block time: computer simulation of patient scheduling and survey of patients' preferences for surgical waiting time

Anesth Analg

A statistical analysis of weekday operating room anesthesia group staffing costs at nine independently managed surgical suites

Anesth Analg

Original contribution
Improving anesthesiologist performance through profiling and incentives