David R. Sinclair

Can postoperative nausea and vomiting be predicted

BackgroundRetrospective [1] studies fail to identify predictors of postoperative nausea and vomiting (PONV). The authors prospectively studied 17,638 consecutive outpatients who had surgery to identify these predictors.MethodsData on medical conditions, anesthesia, surgery, and PONV were collected i

What Is the Driving Performance of Ambulatory Surgical Patients after General Anesthesia

Background:Ambulatory surgical patients are advised to refrain from driving for 24 h postoperatively. However, currently there is no strong evidence to show that driving skills and alertness have resumed in patients by 24 h after general anesthesia. The purpose of this study was to determine whether impaired driver alertness had been restored to normal by 2 and 24 h after general anesthesia in patients who underwent ambulatory surgery. Methods:Twenty patients who underwent left knee arthroscopic surgery were studied. Their driving simulation performance, electroencephalographically verified parameters of sleepiness, subjective assessment of sleepiness, fatigue, alertness, and pain were measured preoperatively and 2 and 24 h postoperatively. The same measurements were performed in a matched control group of 20 healthy individuals. Results:Preoperatively, patients had significantly higher attention lapses and lower alertness levels versus normal controls. Significantly impaired driving skills and alertness, including longer reaction time, higher occurrence of attention lapses, and microsleep intrusions, were found 2 h postoperatively versus preoperatively. No significantly differences were found in any driving performance parameters or electroencephalographically verified parameters 24 h postoperatively versus preoperatively. Conclusions:Patients showed lower alertness levels and impaired driving skills preoperatively and 2 h postoperatively. Based on driving simulation performance and subjective assessments, patients are safe to drive 24 h after general anesthesia.

General anesthesia does not impair simulator driving skills in volunteers in the immediate recovery period: a pilot study

PurposeThe current recommendations to refrain from driving for 24 hr after general anesthesia (GA) lack evidence. Our objective was to measure impairment of driving performance at various time intervals after anesthesia using driving impairment at different blood alcohol concentrations (BAC) as a gold standard for comparison.MethodsInstitutional Review Board approval was obtained. Acrossover design, within subject comparison was used. Twelve volunteers were randomized to three treatments: GA, alcohol, and no drug. Psychomotor recovery was assessed by Digit Symbol Substitution Test (DSST) and Trieger Dot Test (TDT). On the anesthetic day, GA was induced with propofol 2.5 mgℐg−1 and fentanyl l μg·kg−1 and maintained with N2O-O2 50:50 and approximately one minimum alveolar concentration of desflurane by spontaneous ventilation for 30 min. Driving simulator test runs occurred at two, three, four, and 24 hr postanesthesia. On the alcohol treatment day, a vodka and orange juice beverage was administered to reach the legal limit for BAC in the province of Ontario, Canada (BAC 0.08%). On the control day, no drug was given. Driving simulator test runs corresponded to the same time of day as the postanesthetic test runs. Two-way analysis of variance for dependent samples (ANOVA) was performed using the SAS program. P values of less than 0.05 were considered significant.ResultsThere was no significant difference in postanesthetic driving skills at two, three, and four hours postanesthesia, and the corresponding control sessions. There was no significant difference among the three sessions with respect to pen and paper tests of psychomotor performance. Performance during the alcohol session differed significantly from that during the control and postanesthetic sessions.ConclusionCertain driving skills return by two hours after one half hour of GA of propofol, desflurane, and fentanyl in a group of young volunteers.RésuméObjectifLa recommandation courante restreignant la conduite pendant 24 h après une anesthésie générale (AG) manque de preuve. Notre objectif était de mesurer l’altération des habiletés de conduite à différents intervalles de temps après l’anesthésie en utilisant la détérioration de la conduite selon divers taux d’alcoolémie comme référence.MéthodeNous avons obtenu l’approbation du Comité d’examen de l’établissement. Un devis croisé avec comparaison intra-sujets a été utilisé. Douze volontaires ont reçu trois traitements au hasard: AG, alcool et absence de médicament. La récupération psychomotrice a été évaluée par le test de substitution de codes (TSC) et le Trieger Dot Test (TDT). Le jour de l’anesthésie, l’AG a été induite avec 2,5 mg·kg−1 de propofol et I μ·kg−1 de fentanyl et maintenue avec un mélange à 50 % de N2O-O2 et environ une CAM de desflurane par ventilation spontanée pendant 30 min. La série de tests de simulation de conduite a eu lieu deux, trois, quatre et 24 h après l’anesthésie. Le jour où on a donné l’alcool, une boisson faite de vodka et de jus d’orange a permis d’atteindre le taux d’alcoolémie limite accepté en Ontario, Canada (0,08 %). Le jour témoin, aucun médicament n’a été administré. La série de tests de simulation de conduite s’est faite aux mêmes intervalles de temps que la série réalisée le jour de l’anesthésie. Une analyse de variance à deux facteurs pour variables dépendantes (ANOVA) a été réalisée avec l’usage du programme SAS. Les valeurs de P de moins de 0,05 ont été considérées significatives.RésultatsII n’y a pas eu de différence significative entre les habiletés postanesthésiques testées à deux, trois et quatre heures après l’anesthésie et pendant les sessions témoins correspondantes. II n’y a pas eu de différence significative entre les trois sessions quant à la performance psychomotrice aux tests d’écriture. La performance pendant la session sous alcool a présenté une différence significative par rapport aux deux autres sessions.

Capital budgeting decisions using the discounted cash flow method

To the Editor, The return on investment (ROI) method is commonly quoted in the analysis of capital investments affecting the practice of anesthesiology, such as the Anesthesia Information Management System (AIMS), handheld computer technology, and the Preoperative Evaluation Clinic. The ROI method is easy to compute and understand (Table 1). However, it measures risk rather than investment returns. The ROI method is biased against long-term projects and is based on an arbitrary, short-term cut-off date that ignores the investment’s performance after the cut-off point and disregards the possibility of growing cash flows after that point. For example, one cannot disregard the cost reductions and cost savings of an AIMS resulting from reductions in anesthetic-related drug costs and increases in hospital reimbursement occurring beyond a cut-off period. Expressing these future cash flows in terms of their value today is known as the discounted cash flow (DCF) method. The DCF method is superior to the ROI method for analyzing capital investment decisions because it incorporates the time value of money. The DCF method estimates the value of an investment’s projected future cash flows as if the cash flows were available today. It includes two main methods of discounting future cash flow. The discounted payback period rule includes the time value of money; however, like the ROI method, it is limited by an arbitrary short-term cut-off period that is biased against long-term investments. The net present value (NPV) method includes the time value of money and is a superior method for long-term projects, such as those commonly encountered in the practice of anesthesiology. The NPV method is a measure of financial value and one approach to assessing the profitability of a proposed investment. The calculation of NPV can result in one of three possible scenarios (Table 1). First, a NPV that is greater than zero adds monetary value to the organization. The capital budgeting process can be viewed as a search for investments with a positive NPV. From a financial standpoint, these projects should be undertaken because they add value. Second, a NPV that is less than zero would represent a loss of value to the organization if the investment were undertaken. From a financial standpoint, the investment should not be made. Third, a NPV that is equal to zero represents an indifference towards the project and the need to consider other non-monetary factors before proceeding with the investment. The NPV should not be used to the exclusion of other variables that influence capital investment decisions simply because it is superior to the ROI method. In clinical practice, many non-economic factors take precedence over capital investment calculations, including medical evidence, quality and safety, governmental regulations, incentives, penalties, and compliance requirements. Despite the NPV of the proposed investment, the improvement in a hospital’s welfare may exceed the expenditure on the project. In addition, the annual operating cash flow estimates that are based on D. R. Sinclair, MD (&) University of Miami, Miami, FL, USA e-mail: dsinclair@med.miami.edu Table 1 Summary of formulas and calculations

The impact of anesthesia providers on major morbidity following screening colonoscopies

Background and aims Few studies evaluate the impact of anesthesia providers during procedures, such as colonoscopy, on low-risk patients. The objective of this study was to compare the effect of anesthesia providers on several outcome variables, including major morbidity, following screening colonoscopies. Methods A propensity-matched cohort study of 14,006 patients who enrolled with a national insurer offering health maintenance organization (HMO), preferred provider organization (PPO), and Medicare Advantage plans for a screening colonoscopy between July 1, 2005 and June 30, 2007 were studied. Records were evaluated for completion of the colonoscopy, new cancer diagnosis (colon, anal, rectal) within 6 months of the colonoscopy, new primary diagnosis of myocardial infarction (MI), new primary diagnosis of stroke, hospital admission within 7 days of the colonoscopy, and adherence to guidelines for use of anesthesia providers. Results The presence of an anesthesia provider did not affect major morbidity or the percent of completed exams. Overall morbidity within 7 days was very low. When an anesthesia provider was present, a nonsignificant trend toward greater cancer detection within 6 months of the procedure was observed. Adherence to national guidelines regarding the use of anesthesia providers for low-risk patients was poor. Conclusion A difference in outcome associated with the presence or absence of an anesthesia provider during screening colonoscopy in terms of MI, stroke, or hospital admission within 7 days of the procedure was not observed. Adherence to published guidelines for the use of anesthesia providers is low. The incidence of completed exams was unaffected by the presence of an anesthesia provider. However, a nonstatistically significant trend toward increased cancer detection requires further study.

A matrix model for valuing anesthesia service with the resource-based relative value system

Background The purpose of this study was to propose a new crosswalk using the resource-based relative value system (RBRVS) that preserves the time unit component of the anesthesia service and disaggregates anesthesia billing into component parts (preoperative evaluation, intraoperative management, and postoperative evaluation). The study was designed as an observational chart and billing data review of current and proposed payments, in the setting of a preoperative holing area, intraoperative suite, and post anesthesia care unit. In total, 1,195 charts of American Society of Anesthesiology (ASA) physical status 1 through 5 patients were reviewed. No direct patient interventions were undertaken. Results Spearman correlations between the proposed RBRVS billing matrix payments and the current ASA relative value guide methodology payments were strong (r=0.94–0.96, P<0.001 for training, test, and overall). The proposed RBRVS-based billing matrix yielded payments that were 3.0%±1.34% less than would have been expected from commercial insurers, using standard rates for commercial ASA relative value units and RBRVS relative value units. Compared with current Medicare reimbursement under the ASA relative value guide, reimbursement would almost double when converting to an RBRVS billing model. The greatest increases in Medicare reimbursement between the current system and proposed billing model occurred as anesthetic management complexity increased. Conclusion The new crosswalk correlates with existing evaluation and management and intensive care medicine codes in an essentially revenue neutral manner when applied to the market-based rates of commercial insurers. The new system more highly values delivery of care to more complex patients undergoing more complex surgery and better represents the true value of anesthetic case management.

Gaining acceptance for anesthesia information management systems among anesthesiologists

To the Editor, I read with interest the recent review article by Stabile and Cooper that identifies the lack of clinician involvement in the implementation, planning, design, and installation of anesthesia information management systems (AIMS) as a barrier to the adoption of health information technology. Many challenges are associated with the implementation of new AIMS in the perioperative setting, including the perception that workload will increase or autonomy will decrease. Even if AIMS use were mandated and early acceptance occur, the negative consequences of resistance may surface over the long term if the information system were viewed as prone to error or slow. Medical directors and anesthesiology department chiefs must actively manage the change process and gain physician acceptance for the new information system. Failure to gain acceptance of the AIMS may result in the unsuccessful launch of the system and huge financial losses. The Technology Acceptance Model, the most widely accepted method of adopting information technology, focuses on interventions taken by managers to change employees’ attitudes toward information technology. The model identifies two main factors that influence an individual’s intention to use information technology, namely, the extent to which the user believes that the information technology will enhance their job performance (perceived usefulness) and require little effort (perceived ease of use). Perceived usefulness is determined by social influence and system characteristics, and perceived ease of use is determined by facilitating factors, individual differences, and system characteristics. Social influence variables include the opinions about use of information technology from people who are important to the user (subjective norm) and the extent to which the user’s standing among their peers will be maintained or raised (image). System characteristics are defined by the degree to which the user thinks the information technology is important to their work (job relevance), effective (output quality), able to deliver results that are easy to observe and share (result demonstrability), enjoyable (perceived enjoyment), and matches their desired level of effort (objective usability). Facilitating factors refer to the user’s belief that the organization supports the information technology and has committed resources to maintain its operation (perception of external control). Individual differences are defined by the degree to which the user believes in their computer skills (computer self-efficacy), is apprehensive about using a computer (computer anxiety), and is motivated to use new technology (computer playfulness). Managers should take well-defined steps to target the determinants of perceived usefulness and perceived ease of use in order to improve the adoption of AIMS and influence acceptance of information systems among anesthesiologists.

Discounted cash flow of anesthesia information management systems

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Should automated information management systems be leased

To the Editor: Anesthesia information management systems (AIMS) improve staff scheduling, medical decision-making support, and quality improvement monitoring [1]. Information management systems facilitate benchmarking and monitoring of quality and performance improvement, and they are an essential component of the data-driven quality improvement process [2]. Decisions to upgrade existing information systems, or even switching to a new provider, are often delayed due to the high costs associated with the process. As the importance of achieving and maintaining competitive advantage using AIMS are weighed against the high capital expenditure of a purchase, leasing software and hardware may be amore convenient, flexible, and attractive option to operating room medical directors and health system administrators. Leasing, as opposed to borrowing or buying, has several advantages, including increased tax shields, reduced restrictive covenants, and lower transaction costs [3]. Leases may beless costly than purchases, allowing for conservation of working capital while preserving the credit and debt capacity of the organization. Reduced risk of obsolescence and concern for capital equipment disposal at the end of the assets life are additional benefits of leasing. Leases are classified as operating or capital. Operating lease agreements may offer advantages to the hospital (lessee) regarding the AIMS. Typically, operating leases are written for a shorter period than the expected life of the asset, and the hospital may have the right to cancel the lease before the expiration of the agreement. In addition, the information management company (lessor) provides for maintenance of the AIMS. In contrast, capital leases cannot be cancelled before the end of the agreement. According to these agreements, if cancellation were allowed, the information management company would not recover the full cost of the AIMS, as rental payments are based on the full price of the asset minus its residual value. Although uncertainty may exist as to a standard way of evaluating the lease versus purchase decision, comparing the cost streams on the basis of the present value of cash flows is a simple method [4]. The benefit of leasing is determined by comparing the net present value (NPV) of purchasing to the NPV of leasing, known as the net advantage of leasing (NAL). Leases should be analyzed as projects according to their NPV, known as the NAL [3]. The NAL is the most popular method for analyzing a lease, representing the total monetary saving resulting from leasing an asset. For an asset to be leased, the NPV of the lease must be positive and greater than the NPV of owning the asset. Calculations should include estimates of three main variables, namely depreciation, maintenance costs, and the average life expectancy of the AIMS. Detailed tax implications of leases are beyond the scope of this analysis. The present value (PV) of annual cash flows is calculated using the formula:

Inventory management and the safety stock of disposable airway devices

To the Editor, Management of the difficult airway is one of the most challenging situations encountered by an anesthesiologist. Airway devices are commonly used to facilitate tracheal intubation in patients with a known difficult airway or one that is suspected or unrecognized. Current single-use, disposable airway devices include the Clarus Video Scope disposable sheath (Clarus Medical, Minneapolis, MN, USA), the Airtraq (King Systems, Noblesville, IN, USA), the King LTS-D (King Systems, Noblesville, IN, USA), the LMA-Fastrach (LMA North America, Inc, San Diego, CA, USA), the Pentax AWS (Pentax Medical, Montvale, NJ, USA), and Portex Stylets (Smiths Medical, Rockland, MA, USA). The availability of a specific airway device in an emergency situation depends on a wellcoordinated inventory supply chain of intermediate business transactions between suppliers, manufacturers, distributors, warehouses, and hospitals. Airway devices in the hospital inventory are associated with carrying and shortage costs. Carrying costs can range from 20-40% of the inventory value per year and are associated with the storage, tracking, insurance, and opportunity costs of the items. Shortage costs include restocking and ordering costs, and maintaining safety reserves. The basic goal of inventory management is cost minimization. However, efforts to minimize costs may lead to inadequate availability of airway devices to satisfy clinical demand. Hospitals typically reorder airway devices at a predetermined reorder point that incorporates the time lag between reordering and arrival of the device (lead time). The economic order quantity formula determines the number of devices to reorder to minimize total inventory costs. However, this formula assumes that inventory is reordered when reduced to zero. In order to minimize the risk of a stockout and depletion of the airway device inventory, a safety stock level should remain available in the inventory. The safety stock level of a particular brand of disposable single-use airway device optimizes the balance between maintaining minimal inventory while meeting clinical needs during the time that inventory is being replenished. Safety stock level is calculated based on airway device demand during the lead time and the desired level of service, which corresponds to the percentage of time that the airway device will be available to meet clinical demand (Table 1). Although a service level of 95% is common in the retail and manufacturing sectors, service level should approximate 100% when calculating the safety stock level for the emergency airway device. Many of the mathematical tasks in the safety stock equation involve simple arithmetic. The more advanced functions, such as inverse of normal cumulative distribution and standard deviation, are easy to perform with the Microsoft Office Excel spreadsheet application. Consider the example in the Table 1. An anesthesia department used a disposable airway device ‘‘X’’ seven times per day over the previous two-month lead time. The desired service level is 99.9%. In order to meet clinical needs without the risk of a shortage and achieve minimal inventory levels, three airway devices ‘‘X’’ should be available in inventory while waiting for new supplies to arrive. This approach, however, assumes a constant lead time. Other approaches to the safety stock calculation using advanced mathematics and tables are indicated when the D. R. Sinclair, MD (&) University of Miami, Miami, FL, USA e-mail: dsinclair@med.miami.edu