Do Pain Medicine Fellowship Programs Provide Education in Practice Management? A Survey of Pain Medicine Fellowship Programs.

BACKGROUND: We hypothesized that there is a gap between expectations and actual training in practice management for pain medicine fellows. Our impression is that many fellowships rely on residency training to provide exposure to business education. Unfortunately, pain management and anesthesiology business education are very different, as the practice settings are largely office- versus hospital-based, respectively. OBJECTIVE: Because it is unclear whether pain management fellowships are providing practice management education and, if they do, whether the topics covered match the expectations of their fellows, we surveyed pain medicine program directors and fellows regarding their expectations and training in business management. STUDY DESIGN: A survey. SETTING: Academic pain medicine fellowship programs. METHODS: After an exemption was obtained from the University of Texas Medical Branch Institutional Review Board (#13-030), an email survey was sent to members of the Association of Pain Program Directors to be forwarded to their fellows. Directors were contacted 3 times to maximize the response rate. The anonymous survey for fellows contained 21 questions (questions are shown in the results). RESULTS: Fifty-nine of 84 program directors responded and forwarded the survey to their fellows. Sixty fellows responded, with 56 answering the survey questions. LIMITATIONS: The responder rate is a limitation, although similar rates have been reported in similar studies. CONCLUSIONS: The majority of pain medicine fellows receive some practice management training, mainly on billing documentation and preauthorization processes, while most do not receive business education (e.g., human resources, contracts, accounting/financial reports). More than 70% of fellows reported that they receive more business education from industry than from their fellowships, a result that may raise concerns about the independence of our future physicians from the industry. Our findings support the need for enhanced and structured business education during pain fellowship. KEY WORDS: Business education, practice management, fellowship training, curriculum development, knowledge gaps, private practice.

The prevalence and characteristics of incentive plans for clinical productivity among academic anesthesiology programs.

Performance-based compensation is encouraged in medical schools to improve faculty productivity. Medical specialties other than anesthesiology have used financial incentives for clinical work. The goal of this study was to determine the prevalence and the types of clinical incentive plans among academic anesthesiology departments. We performed an electronic survey of the members of the Society of Academic Anesthesiology Chairs and the Association of Anesthesiology Program Directors in the spring of 2003. The survey included questions about departmental size, presence of a clinical incentive plan, characteristics of existing incentive plans, primary quantifiers of productivity, and factors used to modify productivity measurements. An incentive plan was considered to be present if the department measured clinical productivity and varied compensation according to the measurements. The plans were grouped by the primary measure used into the following categories: None, Charges, Time, Shift, Late/Call (only late rooms and call), and Other. Eighty-eight (64%) of 138 programs responded to the survey, and 5 were excluded for incomplete data. Of the responding programs, 29% had no system, 30% used a Late/Call system, 20% used a Shift system, 11% used a Charges system, 6% used a Time system, and 3% fit in the Other category. Larger groups (>40 faculty members) had a significantly more frequent prevalence of incentive plans compared with smaller groups (<20 faculty members). Incentives were paid monthly or quarterly in 85% of the groups. In 90% of groups, incentive payments accounted for <25% of total compensation. Adjustments for operating room schedule supervisors, personally performed cases, day surgery preoperative clinics, pain-management services, and critical care services were included in less than half of the programs that reported incentive plans. Call and late room compensation was based on varied formulas. Sixty-nine percent of academic anesthesiology departments did not vary compensation according to clinical activity during regular hours. Most did vary payments on the basis of call and/or late rooms worked. Larger departments were more likely to use clinical incentive plans.

Influence of the type of anesthesia provider on costs of labor analgesia to the Texas Medicaid program.

BACKGROUND: The Texas Medicaid Program (Medicaid) defines billable time for labor analgesia as face-to-face time; therefore, anesthesia providers determine billed time. The authors' goal was to determine the influence of anesthesia providers on labor analgesia costs billed to Medicaid. METHODS: Under the Freedom of Information Act, Medicaid provided data on claims paid for 6 months in 2001 for labor analgesia administered during the course of a vaginal delivery. Claims were either time based (codes 00946 or 00955) or a flat fee (codes 26311 or 26319). Using modifiers, the authors grouped time-based claims as either anesthesiologist group or certified registered nurse anesthetist (CRNA) group. The cost to Medicaid was based on the 2001 fee schedule. The conversion factor was 18.21 USD per American Society of Anesthesiologists unit. The flat-fee reimbursement was 152.50 USD. CRNA services were paid at 85% of the fee schedule. Average time per time claim, percent of providers with more than 4 h of billed time, and cost per claim were determined for each group. Providers with more than 120 claims (> 20 claims/month) were considered high-volume. RESULTS: The database included 21,378 claims (anesthesiologist group: 12,698 claims from 219 providers; CRNA group: 8,680 claims from 117 providers). For time-based claims, the average time per case was significantly higher in the CRNA group (146 min) than in the anesthesiologist group (105 min). The CRNA group cost to Medicaid (225.11 USD) was 19% more per claim than the anesthesiologist group (189.26 USD). The difference in cost per claim was greater among high-volume providers--213.10 USD for the CRNA group versus 168.76 USD for the anesthesiologist group. If a flat-fee program were instituted using the average cost per claim for all groups (203.81 USD), the Texas Medicaid program would save more than 500,000 USD annually. CONCLUSIONS: The costs of labor analgesia billed to Texas Medicaid were 19% to 26% less per patient when provided by anesthesiologists than by CRNAs, despite lower per-unit reimbursement of CRNAs.

Increasing the value of time reduces the lost economic opportunity of caring for surgeries of longer-than-average times.

UNLABELLED: Anesthesiology groups that provide care for surgical procedures of longer-than-average duration are economically disadvantaged by both increased staffing costs and reduced revenue. Under the current billing system, anesthesia time is valued the same regardless of the total case duration. In this study, we evaluated the effect on four academic anesthesiology departments of two hypothetical scenarios by changing the anesthesia care billing system to make more valuable either 1) all time units or 2) just second-hour and subsequent time units. From the four departments, case-specific data (anesthesia Current Procedural Terminology code and minutes of care) were collected for all anesthesia cases billed for 1 yr. Basic units were determined from the American Society of Anesthesiologists (ASA) relative value guide. The average time for each case was defined as the average anesthesia time for that specific Current Procedural Terminology code, as published by the Center for Medicare and Medicaid Services (CMS). The actual total ASA units per hour (tASA/h) was determined by adding all the basic units and time units and dividing by hours of anesthesia care (minutes of anesthesia care divided by 60). We then calculated a hypothetical CMS tASA/h for each group by substituting the CMS average time for each anesthesia procedure time for the actual time reported by each group and using 15-min time units. For each group, the Actual (Act) tASA/h and CMS tASA/h were calculated for both options-changing the interval for all time units or only for second and subsequent hours. Intervals were 15, 12, 10, 7, 6, or 5 min. When changing all time units, Act tASA/h and CMS tASA/h were never equal for all groups. The two productivity measures became approximately equal if only time units after the first hour were changed to 6- to 7-min intervals. When changes were applied only to the Act tASA/h (with CMS tASA/h remaining at 15-min intervals), at the 12-min interval either option resulted in a similar or higher Act tASA/h than CMS tASA/h. Both options increase the value of time and help compensate for the lost economic opportunity of longer-than-average surgical durations. IMPLICATIONS: Longer-than-average surgical durations result in less potential revenue per hour under current billing methodology. This study quantifies the increase in billing productivity when the value of time is increased, when evaluating the billing productivity of four academic anesthesiology groups.

Quantifying net staffing costs due to longer-than-average surgical case durations.

BACKGROUND: Anesthesiology departments incur staffing costs that are not covered by revenue because the operating room (OR) time allocation and case scheduling are not done to maximize OR efficiency and because surgical durations are longer than average. The purpose of this article is to demonstrate a method to quantify net anesthesia staffing costs due to longer-than-average surgical durations and evaluate the factors that influence staffing costs. METHODS: Data collected from two anesthesiology departments in academic hospitals for 1 yr included date of surgery, time that patients entered the OR, time that patients exited the OR, surgical service, and the Current Procedural Terminology code for the primary surgical procedure. Anesthesia care performed outside the main surgical suite and services not billed with American Society of Anesthesiologists units were excluded. National average surgical durations were determined from the Current Procedural Terminology code from the Centers for Medicare and Medicaid Services' database. Actual surgical durations were then used to determine staffing solutions to maximize OR efficiency; national average surgical durations were then used to determine a second solution. The difference in staffing costs between these two staffing solutions represented the staffing costs attributable to longer surgical durations. Costs were converted to dollar amounts using compensation values reported in a national compensation survey. The differences in revenue were determined by applying conversion factors to the differences in surgical durations. The annual net cost attributable to longer surgical durations equaled the staffing costs minus the revenue produced by longer durations. Net staffing costs were estimated for two hospitals using median staffing compensation and median payer mix. Net staffing costs were then recalculated by varying the parameters (conversion factors, limits on differences between actual and average surgical duration, levels of compensation, surgical service size of OR allocation). RESULTS: Using the median compensation of staff and an average conversion factor, the net annual staffing costs attributable to longer surgical durations were $672,100 for the first hospital. However, if staff members were highly compensated and the payer mix was unfavorable, the net staffing costs were $1,688,000. Reducing the difference between actual and average duration resulted in lower staffing costs. Net staffing costs were less in a second hospital studied that had many low-volume surgical services. CONCLUSIONS: Longer-than-average surgical durations can increase net staffing costs for anesthesiology groups. The increase is dependent on factors such as staffing compensation and payer mix.

Use of operating room information system data to predict the impact of reducing turnover times on staffing costs.

UNLABELLED: Potential benefits to reducing turnover times are both quantitative (e.g., complete more cases and reduce staffing costs) and qualitative (e.g., improve professional satisfaction). Analyses have shown the quantitative arguments to be unsound except for reducing staffing costs. We describe a methodology by which each surgical suite can use its own numbers to calculate its individual potential reduction in staffing costs from reducing its turnover times. Calculations estimate optimal allocated operating room (OR) time (based on maximizing OR efficiency) before and after reducing the maximum and average turnover times. At four academic tertiary hospitals, reductions in average turnover times of 3 to 9 min would result in 0.8% to 1.8% reductions in staffing cost. Reductions in average turnover times of 10 to 19 min would result in 2.5% to 4.0% reductions in staffing costs. These reductions in staffing cost are achieved predominantly by reducing allocated OR time, not by reducing the hours that staff work late. Heads of anesthesiology groups often serve on OR committees that are fixated on turnover times. Rather than having to argue based on scientific studies, this methodology provides the ability to show the specific quantitative effects (small decreases in staffing costs and allocated OR time) of reducing turnover time using a surgical suite's own data. IMPLICATIONS: Many anesthesiologists work at hospitals where surgeons and/or operating room (OR) committees focus repeatedly on turnover time reduction. We developed a methodology by which the reductions in staffing cost as a result of turnover time reduction can be calculated for each facility using its own data. Staffing cost reductions are generally very small and would be achieved predominantly by reducing allocated OR time to the surgeons.

Problem-based learning in a managed care seminar for all new residents at an academic medical center.

One of the most important challenges in resident education is to train residents how to function in relation to managed care companies and systems so as to enhance the quality, accessibility, and efficiency of health care. Since 1996, The University of Texas Medical Branch in Galveston has presented an annual half-day seminar on managed care to new residents. The format involves training sessions and didactic presentations aimed at small groups (led by faculty physicians and nonphysicians from throughout the medical and managed care establishments). Problem-based learning sessions conducted in these groups focus on topics such as the organization of managed care systems, access, network, admit versus observation, inpatient status, denials, avoidable hospital days, concurrent reviews, gatekeepers, referrals, behavioral health, disease management programs, and financial considerations. Pretests and posttests are given to those participating to gauge the effectiveness of the program. In addition, participants complete evaluation forms that can be used by program coordinators to assess resident satisfaction with the learning format and to determine what improvements can be made in the process. For the 1999 and 2000 seminars, posttest results were significantly higher than pretest results for the new residents who participated in the seminar. Each year, seminar evaluations show that the small-group format is well received. We conclude that the small-group learning format is effective and enjoyable for the residents and their leaders. The format necessitates the training of 30 group leaders to increase their knowledge of managed care systems.

Labor costs incurred by anesthesiology groups because of operating rooms not being allocated and cases not being scheduled to maximize operating room efficiency.

UNLABELLED: Determination of operating room (OR) block allocation and case scheduling is often not based on maximizing OR efficiency, but rather on tradition and surgeon convenience. As a result, anesthesiology groups often incur additional labor costs. When negotiating financial support, heads of anesthesiology departments are often challenged to justify the subsidy necessary to offset these additional labor costs. In this study, we describe a method for calculating a statistically sound estimate of the excess labor costs incurred by an anesthesiology group because of inefficient OR allocation and case scheduling. OR information system and anesthesia staffing data for 1 yr were obtained from two university hospitals. Optimal OR allocation for each surgical service was determined by maximizing the efficiency of use of the OR staff. Hourly costs were converted to dollar amounts by using the nationwide median compensation for academic and private-practice anesthesia providers. Differences between actual costs and the optimal OR allocation were determined. For Hospital A, estimated annual excess labor costs were $1.6 million (95% confidence interval, $1.5-$1.7 million) and $2.0 million ($1.89-$2.05 million) when academic and private-practice compensation, respectively, was calculated. For Hospital B, excess labor costs were $1.0 million ($1.08-$1.17 million) and $1.4 million ($1.32-1.43 million) for academic and private-practice compensation, respectively. This study demonstrates a methodology for an anesthesiology group to estimate its excess labor costs. The group can then use these estimates when negotiating for subsidies with its hospital, medical school, or multispecialty medical group. IMPLICATIONS: We describe a new application for a previously reported statistical method to calculate operating room (OR) allocations to maximize OR efficiency. When optimal OR allocations and case scheduling are not implemented, the resulting increase in labor costs can be used in negotiations as a statistically sound estimate for the increased labor cost to the anesthesiology department.

Inclusion of turnover time does not influence identification of surgical services that over- and underutilize allocated block time.

UNLABELLED: Allocation of operating room (OR) block time is an ongoing challenge for OR managers. In this study, we sought to determine whether inclusion or exclusion of turnover time in comparisons of block utilization would identify different surgical services as under- or overused. For a 13-mo period, we evaluated data extracted from the OR information system of a large academic medical center. During that time period, 15 surgical services performed 12,245 surgical procedures. Allocated block hours, number of first cases performed, total number of cases, and average case durations were determined. The average turnover time for each service was determined by a manual, case-by-case review of data from 1 mo. Raw utilization (RU; case durations only) and adjusted utilization (AU; case duration plus turnover time) were calculated for each service. Turnover time was credited to the service performing surgery after room turnover. Case du-ration was limited to surgeries performed during resource hours. Two indices of utilization (i.e., the usage rate of the service divided by the overall use of all ORs in the suite) were used to compare services: the RU or AU Index (RUI or AUI). Outliers were services with indices that were >1.15 or <0.85. The RUI identified three services as underutilizers and one service as an overutilizer. Using the AUI, the same outliers were identified, and no new services were identified. Examining the changes in index (between AUI and RUI), the percentage of to-follow cases highly correlated with changes in index (r(2) = 0.60); the average turnover time did not (r(2) = 0.002). Inclusion of turnover time did not change the services that were identified as under- and overutilizer. IMPLICATIONS: Turnover time is difficult to determine from existing operating room information systems. This study determined the use of block time with and without turnover time for each surgical service in a large academic hospital. Turnover time did not change identification of surgical services that over- (one service) or underused (three services) allocated block time.

Comparing clinical productivity of anesthesiology groups.

BACKGROUND: Intergroup comparisons of clinical productivity are important for strategic planning and evaluation of clinical and business operations. However, in a preliminary study, comparisons of two anesthesiology groups using "per full-time equivalent" measurements were confounded by different concurrencies or staffing ratios, whereas measurements based on "per operating room (OR) site," "per case," and "billed American Society of Anesthesiologists (ASA) units per hour of care" permitted meaningful comparisons despite differing concurrencies. The purpose of this study was to determine whether these measurements would allow for meaningful comparisons when applied to multiple groups. METHODS: Annual totals of total ASA units (tASA), 15-min time units, and the number of cases billed, as well as the average number of daily anesthetizing sites (OR sites) staffed and the average number of anesthesiologists required to the staff sites, were collected from each group that participated. All anesthesia care billed with ASA units was included, except for obstetric care. Any clinical service not billed using ASA units was excluded. Productivity measurements (concurrency, tASA/OR site, hours billed per OR site per day, hours billed per case, tASA billed per hour of anesthesia care, and base units per case) were calculated. Median and range for all groups and for private-practice and academic groups were determined. RESULTS: Eleven private-practice and nine academic groups from 12 states participated in the study. Productivity measurements that are influenced by duration of surgery (hours billed per case, tASA billed per hour of anesthesia care) differed significantly between groups, with private-practice groups having shorter duration than academic groups (median hours billed per case, 1.5 2.6, respectively). Although tASA/OR site measurements were similar in private-practice and academic groups, academic groups worked significantly longer hours billed per OR site per day (median, 6.0 h 7.8, respectively) to achieve the same level of tASA/OR site. Hourly billing productivity (tASA billed per hour of anesthesia care) correlated highly with surgical duration (hours billed per case). CONCLUSION: This study demonstrates a method of comparing departmental clinical productivity between anesthesiology groups. Private-practice groups provided care for cases of shorter duration than academic groups. This difference was evident in several productivity measurements.