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ECONOMICS AND HEALTH SYSTEMS RESEARCH

The Cost Effectiveness of Anesthesia Workforce Models: A Simulation Approach Using Decision-Analysis Modeling

University of Rochester School of Medicine, Rochester, New York

Address correspondence and reprint requests to Laurent G. Glance, MD, Department of Anesthesiology, University of Rochester Medical Center, 601 Elmwood Ave., Box 604, Rochester, NY 14642.

	Abstract

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The objective of this study was to evaluate the incremental cost effectiveness of anesthesia workforce staffing scenarios, as a function of skill mix, by using the technique of decision analysis. A decision tree model was constructed to compare the incremental cost effectiveness of alternative delivery systems for anesthesia care from the perspective of the payer. Five different staffing scenarios, ranging from physician-intensive to nurse-intensive, were modeled. In the nurse-intensive model, low- and intermediate-risk patients were cared for by solo certified registered nurse anesthetists (CRNAs) and high-risk patients were cared for by physicians. In the physician-intensive model, physicians anesthetized all patients. In the first-, second-, and third-team models, all high-risk patients were cared for by physicians working alone, and all intermediate-risk patients were cared for using an anesthesia care team approach with a ratio of one physician to two CRNAs. The low-risk patients were managed by using an anesthesia care team approach with physician to CRNA ratios of 1:2, 1:4, and 1:8 in the first-, second-, and third-team models, respectively. The findings of this decision-analysis model suggest that physician-only anesthesia is not cost effective. However, the third-team model is cost effective when compared with the nurse-intensive model.

Implications: An anesthesia care-team approach with a physician to certified registered nurse anesthetist (CRNA) ratio of 1:2 is the preferred staffing scenario for intermediate-risk patients. Although medical direction of CRNAs caring for low-risk patients is cost-effective, the small improvement in outcome resulting from increasing the physician to CRNA ratio from 1:8 to 1:4 may not be justified by the added cost.

	Introduction

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Market forces and legislative mandates are increasingly shaping the healthcare landscape. Anesthesia costs, which are estimated to be between 3% and 5% of the total health care expenditures (1), are the subject of scrutiny by both third-party payers and the government. Personnel accounts for most of this cost. The magnitude of the salary differential between certified nurse anesthetists (CRNAs) and anesthesiologists (2) is perceived by some as an opportunity for achieving cost savings through changes in the provider mix (3). The elimination of the federal requirement for supervision of CRNAs, recently proposed by the Health Care Financing Administration (4), would allow the substitution of lower-cost CRNAs for anesthesiologists. This proposal is supported by the American Association of Nurse Anesthetists and is strongly opposed by the American Society of Anesthesiologists. In other specialties, the number of nonphysician clinicians (NPCs) has increased. Similarly, changes in state regulations to expand the scope of practice and independence of NPCs may allow them to replace, rather than complement, their physician counterparts in certain settings (5).

The impressive safety record of the anesthesiology specialty was recently cited in a Health Policy Report in the New England Journal of Medicine as an example to be emulated by the health care community in its search to improve quality (6). Therefore, any proposal to alter the current provider mix of physicians and nonphysicians in anesthesia to achieve cost reductions should consider the potential adverse effects of such a change on anesthesia outcomes. There are no outcome studies which definitively support the superiority of physician versus nonphysician anesthesia providers to help guide such an effort. Nevertheless, many anesthesiologists support the principle that the "skill mix of the provider influences the quality of service" (7). In contrast, the American Association of Nurse Anesthetists has used the lack of outcome studies to support the exploration of "alternative delivery systems for anesthesia care" (8) that use proportionately greater numbers of CRNAs to reduce overall labor costs. Unfortunately, it may not be possible to devise adequately powered studies to examine the effect of provider mix on anesthesia outcome. This lack of outcome data, coupled with the economics of increasing numbers of physicians and CRNAs, and the mounting pressure to decrease costs have generated some extreme positions within both communities of providers.

There is no question that the pressure to reduce anesthesia costs will continue as part of the overall effort to control rising medical expenditures. Currently, payments for anesthesia services are based on time and base units; these are a function of the complexity and duration of the surgical procedure. Efforts to control anesthesia costs by third-party payers have focused primarily on reducing the cost per unit. Changing the proportion of physician to nonphysician anesthesia providers could also result in a lower overall cost from the payer’s perspective. However, current Medicare rules mandate an anesthesia provider-mix neutral approach to billing. Specifically, total anesthesia reimbursement is the same whether a patient is anesthetized by a CRNA working alone, a physician working alone, or an anesthesia care team (ACT). Outside of the Medicare fee structure, there is no consistent reimbursement formula for CRNAs. In the future, policy-makers may attempt to achieve further cost reductions by mandating lower reimbursement levels for and proportionately greater use of CRNAs.

Changing the proportion of physician to nonphysician anesthesia providers, with modifications of the current fee schedule, could achieve a lower cost from the payer’s perspective. However, the use of unsupervised or minimally supervised CRNAs may also result in worse patient outcomes. Therefore, any effort to shift care to a delivery system that emphasizes the increased use of CRNAs must be accompanied by an analysis that balances the resultant cost savings against the potential for increases in adverse outcomes.

The purpose of this study was to examine the cost effectiveness (C/E) of anesthesia workforce models in the context of a "provider-sensitive" fee structure by using decision-analysis modeling. In this analysis, it was assumed that anesthesiologists working alone result in better patient outcomes than CRNAs working either alone or with minimal medical direction. If this is correct, then should only physicians be giving anesthesia? Alternatively, are physicians working alone too expensive despite their improved outcomes? This simulation assessed the incremental C/E of various anesthesia care delivery systems ranging from physician-intensive to nurse-intensive. The purpose of this study was to determine the level (if any) at which increasing physician participation in the work force model was no longer cost effective. Such a finding may help guide the debate regarding the optimal staffing mix of physicians and CRNAs delivering anesthesia care. Moreover, such an approach allows this discussion to be framed in economic terms and reaches beyond the visceral response espoused by many practitioners.

	Methods

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Overview
A decision-analysis model was constructed to evaluate the incremental C/E of anesthesia staffing scenarios by using different ratios of physician to nonphysician anesthesia providers. The model was based on limited outcome data from the literature as well as demographic and cost data based on a cohort of approximately 25,000 patients at a major university teaching hospital. In the absence of outcome studies comparing mortality as a function of anesthesia provider, baseline assumptions were developed by using the available literature. Sensitivity analysis was used to explore the effect of varying these baseline assumptions.

The Model
Staffing Scenarios. Five different staffing scenarios were modeled, based on the Abt Corporation study (9), ranging from a physician-intensive to nurse-intensive practice settings. The staffing scenarios examined were:

1. Physician-intensive model: only physicians administer anesthesia.

2. First-team model: physicians anesthetize all high-risk patients; intermediate and low-risk patients are anesthetized by an ACT with a physician to CRNA ratio of 1:2.

3. Second-team model: physicians anesthetize all high-risk patients; intermediate-risk patients are anesthetized by an ACT with a physician to CRNA ratio of 1:2; and low-risk patients are anesthetized by an ACT with a physician to CRNA ratio of 1:4.

4. Third-team model: physicians anesthetize all high-risk patients; intermediate-risk patient are anesthetized by an ACT with a physician to CRNA ratio of 1:2; and low-risk patients are anesthetized by an ACT with a physician to CRNA ratio of 1:8.

5. Nurse-intensive model: physicians anesthetize all high-risk patients; intermediate and low-risk patients are anesthetized by CRNAs who are not supervised by an anesthesiologist.

Surgical procedures were divided into three categories—high, intermediate, and low-risk–adapted from the risk stratification scheme developed by the American College of Cardiology/American Heart Association (10).

1. High—emergent major operations; aortic and major vascular; cardiac

2. Intermediate—intraperitoneal; intrathoracic; orthopedic; prostate

3. Low—endoscopic procedures; superficial procedures

The Decision Tree. A multistate decision-tree model (Figure 1) simulating the C/E of five hypothetical staffing scenarios was written by using DATA 3.5 (Treeage Software, Williamstown, MA) decision-analysis software. DATA provides a structured methodology that permits quantitative analysis of "what if" scenarios using decision trees.

View larger version (36K): [in this window] [in a new window]   Figure 1. Decision tree model. Square = the choice of one of five staffing scenarios, circle enclosing M = Markov node, ACT 1:2 = anesthesia care team (ACT) with one physician supervising two certified registered nurse anesthetists (CRNAs), ACT 1:4 = ACT with one physician supervising four CRNAs; ACT 1:8 = ACT with one physician supervising eight CRNAs.

View larger version (14K): [in this window] [in a new window]   Figure 2. The nurse-intensive subtree. Circle enclosing M = Markov node, CRNA = certified registered nurse anesthetist.

C/E. The measure of utility used in this analysis was YLS. Although quality adjusted life-years are a more commonly used measure of utility (12), there is no data on anesthesia related morbidity as a function of provider mix to derive this measure of effect. An annual discount rate of 5% was used to discount future YLS (13). This analysis was based on the perspective of the payer. Because it was assumed that drug and material costs would be independent of provider mix, only labor costs were included in the model. Costs were a function of the following factors: number of anesthesia units, type of insurance coverage, dollar charge per unit, and provider mix. All costs were calculated using 1998 US dollars.

In comparing two strategies, one is considered dominated if it is more expensive but of equal or lesser effectiveness than another strategy. Alternatively, if one strategy is both more effective and more expensive, the incremental C/E can be derived as the ratio of the difference in cost over the difference in effectiveness (14). Interventions whose incremental C/E is less than $50,000 per quality adjusted life-year are considered to be within the range of currently accepted medical therapies (15).

Data and Assumptions
Events leading to anesthesia-related mortality can be grouped into two broad categories and described by using the terms primary and secondary mortality rate. The first includes simple errors in judgment, lack of vigilance, drug overdose, failure to intubate/ventilate, and inadequate monitoring. Also included are adverse events which are "accidental" in nature, such as anaphylaxis, aspiration, bronchospasm, and hypotension (16), in which "failure-to-rescue" by the anesthesia provider leads to patient death. In all these cases, patient death is directly linked to anesthetic care. The mortality rate directly attributable to anesthesia was assumed to be 1 in 185,000 based on the Confidential Inquiry into Perioperative Death (CEPOD) (17). The primary mortality rate was assumed to vary according to risk category.

The secondary mortality rate is a function of the interaction between patient and procedure-related factors and the quality of anesthesia care. In such cases, anesthesia contributes to but is not solely responsible for patient outcome. The secondary mortality rate, based on the CEPOD study, was assumed to be 7.4 in 10,000 in the overall population and to vary according to risk category. Although the CEPOD study was based on physician-only anesthesia, outcome data in this inquiry were extended to other provider mixes by incorporating "provider mix adjustment factors" (see below).

There are no randomized, controlled trials evaluating patient outcome as a function of provider mix. Bechtoldt (18) conducted a retrospective review of two million anesthetics administered between 1969 to 1976 in North Carolina; the incidence of anesthesia-related deaths as a function of provider was similar across the range of provider mix. The major limitation of this study was that no attempt was made to adjust for case-mix. However, it is likely that physicians were involved in the care of the sicker patients and those having more complex surgeries. A prospective study from the Stanford Center for Health Care Research reported on 8593 patients (19). This study suggested a trend toward lower-risk adjusted mortality rates for physician-only and ACT environments as compared with unsupervised CRNAs. In a more recent study, using logistic regression modeling to analyze a data set of 5972 patients undergoing cholecystectomy and transurethral prostatomy, Silber et al. (20) demonstrated that the proportion of board-certified anesthesiologists is inversely related to the "failure to rescue" from adverse events. The relative risk of "failure-to-rescue" was 2.5 times higher in hospitals in which 0%–33% of anesthesiologists were board-certified as compared with hospitals in which 66%–99% of the anesthesiologists were board-certified. Because increases in the anesthesia-related mortality rate will result from "failure to rescue," nonboard certified anesthesiologists were assumed to have a 2.5 times higher anesthesia-related mortality rates than board-certified anesthesiologists. In our study, it was assumed that a CRNA working alone would have twice the mortality of a nonboard certified anesthesiologist. All anesthesiologists in the model were assumed to be board-certified. CRNAs working alone were assumed to have a 5 times higher mortality rate than that of solo anesthesiologists or of ACTs with physician to CRNA ratios of 1:2 or 1:4 (based on the assumption that unsupervised CRNAs were twice as likely to have "failure to rescue" than nonboard certified anesthesiologists). ACTs with a ratio of 1 physician to 8 CRNAs were assumed to have 2.5 times the mortality of solo anesthesiologists because of the nominal nature of physician supervision. The assumption that ACTs with a physician to CRNA ratio of 1:2 or 1:4 have outcomes equivalent to physicians working alone was based on the premise that the advantage of physician-only anesthesia was offset by the presence of ‘two sets of eyes’ in an ACT.

Costs
Cost data and patient demographics (Table 1) were based on a data set of 24,970 patients (age > 12 yr) receiving anesthesia between February 1997 and April 1999 at Strong Memorial Hospital (University of Rochester School of Medicine and Dentistry). As previously described, patients were divided into three risk categories and then further grouped according to insurance coverage. The cost per anesthesia unit was assumed to be $34, $17, $5, and $34 for Blue Cross/Blue Shield, Medicare, Medicaid, and "other," respectively. The anesthesia cost was calculated by multiplying the mean number of units by the cost per unit (e.g., the cost of a patient undergoing a low-risk procedure with Blue Cross/Blue Shield coverage was obtained by multiplying 14.0 by $34). Physicians working alone were assumed to bill the full rate. The cost conversion factor for CRNAs working alone was assumed to be 0.65 based on a survey estimating the market costs of physician and CRNA services (21). Anesthesia costs for patients cared for by ACTs with a physician to CRNA ratio of 1:2 (ACT 1:2) were assumed to be the same as for a solo anesthesiologist. It was also assumed that in ACTs with physician to CRNA ratios of 1:4 and 1:8, the physician portion of the cost would decline proportionately at higher levels of supervision. For example, in the ACT with a physician to CRNA ratio of 1:4, the CRNA portion of the cost for a given patient was 50%, and the physician portion was 25% of the cost of an anesthesiologist working alone. The total cost of the ACT with a physician to CRNA ratio of 1:4 was assumed to be equal to 75% of the cost of an anesthesiologist working alone. Reimbursement ratios for physicians were chosen so that total physician compensation remained constant, whether an anesthesiologist was working alone or supervising 2, 4, or 8 CRNAs. Table 2 summarizes the estimates used in the baseline analysis, as well as the ranges of values used for sensitivity analysis.

	Results

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View larger version (15K): [in this window] [in a new window]   Figure 3. Power analysis for a prospective, randomized, controlled trial comparing secondary mortality rates of intermediate-risk patients cared in nurse-intensive versus physician-intensive models.

View larger version (15K): [in this window] [in a new window]   Figure 4. Power analysis for a prospective, randomized, controlled trial comparing primary mortality rate of intermediate-risk patients cared in nurse-intensive versus physician-intensive models.

	Discussion

Top Abstract Introduction Methods Results Discussion References

The effect of varying the model assumptions on the incremental C/E of the anesthesia staffing scenarios was explored by using sensitivity analysis. The results are sensitive to the secondary mortality rate—deaths in which anesthesia contributed to but was not solely responsible for the death of the patient. Medical direction of CRNAs for intermediate- and low-risk patients was cost effective over the entire range of the sensitivity analysis. However, an ACT with a physician to CRNA ratio of 1:4 was the preferred strategy for low-risk patients only if the secondary mortality rate was greater than 4.6 in 10,000; if the secondary mortality rate was <4.6 in 10,000, then the optimal staff mix for low-risk patients was an ACT with a physician to CRNA ratio of 1:8. The results of the analysis were not sensitive to changes in the primary mortality rate—deaths for which anesthesia was solely responsible.

One of the fundamental assumptions underlying this decision analysis is that physician supervision leads to outcomes superior to those achieved by CRNAs working either alone or under nominal supervision. This assumption was incorporated into the model by using an outcome adjustment factor. The third-team model was cost effective over the entire range of the sensitivity analysis for this variable. However, the second-team model was not cost effective unless the secondary mortality rates of patients cared for by ACTs with a physician to CRNA ratio of 1:8 was at least twice that of patients cared for by ACTs with a physician to CRNA ratio of 1:4.

The findings of this analysis are relatively insensitive to the proportion of both high-risk patients and of patients covered by Medicare. The model is also relatively robust when changes are made in reimbursement levels. The third-team model is cost effective, as compared with the nurse-intensive model, over the entire range of the reimbursement level. The second-team model is cost effective, compared with the third-team model, when the reimbursement level was between the range of 50% and 160% of current levels.

The most significant limitation of this model is the absence of reliable data on anesthesia outcomes as a function of skill mix to use as the basis for the decision analysis. Nonetheless, there is consensus within the physician community that patient outcomes are better when anesthesiologists either directly administer or closely supervise anesthesia care (7,22–25). This position is based on the premise that anesthesiology is the practice of medicine and, therefore, requires a specialized skill set and knowledge base acquired only through medical training. The corollary to this position is that nonphysician anesthesia care providers can only produce optimal outcomes in the context of medical direction by an anesthesiologist. The evidence supporting this position consists mainly of expert opinion and poorly controlled studies. Unfortunately, the sample size necessary to conduct a randomized, controlled trial to answer this question is very large. In conducting a sensitivity analysis on the effect of varying the outcome adjustment factor for the secondary mortality rate, it was assumed CRNAs working independently would have at least 2.5 times the secondary mortality rate of physicians or of CRNAs under medical direction (physician to CRNA ratio 1:2 or 1:4). Power analysis demonstrates (P < 0.05 and power = 80%) that the number of patients necessary for such a study is approximately 18,000. To demonstrate smaller differences in outcomes would require an even greater number of patients. Additionally, there is the problem of defining under what set of conditions anesthesia "contributes" to mortality. If such a study is instead limited to examining only the primary mortality rate, the number of patients necessary would be greater than 2,000,000. It is therefore unlikely that such studies will be performed in the future. Alternatively, logistic regression modeling could be used to examine the relative risk of mortality as a function of provider mix after adjusting for severity of disease and procedure risk. However, even if a sufficiently large database were available for such an analysis, it may not be possible to completely eliminate the possibility of selection bias.

A second weakness in this model is that it limits outcomes to live/die and does not address significant morbidity resulting from anesthesia. Including anesthesia-related morbidity would have greatly increased the level of complexity of the model and the level of uncertainty of the model variables. Such an approach, although more comprehensive, might have resulted in more questionable conclusions. Finally, a structural weakness of the model is that it fails to account for situations in which the number of low-risk patients receiving anesthesia simultaneously is insufficient to allow for a 1:8 level of supervision.

Given the inherent limitations of this model, what inferences can be drawn based on its findings? First, a physician-intensive model, in which intermediate- and low-risk patients are anesthetized by anesthesiologists working alone, may not be cost effective. Second, an anesthesia care team approach with a physician to CRNA ratio of 1:2 appears to be cost-effective for intermediate-risk patients when compared with staffing models in which CRNAs work independently. Finally, medical direction of CRNAs caring for low-risk patients is also cost effective when the CRNA to physician ratio is 1:8.

C/E analysis provides an ideal framework for the discussion of the relative merits of alternative staffing scenarios in anesthesia. It seems intuitive, the lack of outcome studies notwithstanding, that using more highly trained physicians versus NPCs will result in improved outcomes. But, is the increased cost justified by the improvement in outcomes? It would appear, based on the results presented here, that the answer is that the most cost-effective staffing scenario involves a mix of physicians and NPCs.

The findings of this study argue in favor of a staffing model that combines both physician and ACT approaches. However, they do not support CRNAs working independent of medical direction by an anesthesiologist. They support direct physician involvement in the care of higher-risk patients and more of a supervisory role in the care of lower-risk patients. The value of this study is that it presents an economic framework for the analysis of anesthesia staffing scenarios. The findings of this analysis, however, must be qualified by the lack of outcome data.

	References

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Anesthesia & Analgesia® is published for the International Anesthesia Research Society® by Lippincott Williams & Wilkins with the assistance of Stanford University Libraries' HighWire Press®. Copyright 2006 by the International Anesthesia Research Society. Online ISSN: 1526-7598   Print ISSN: 0003-2999