The impact of reduction of testing at a Preoperative Evaluation Clinic for elective cases: Value added without adverse outcomes.

STUDY OBJECTIVE: Protocol changes at Vanderbilt have been adopted with the intention of reducing unnecessary preoperative testing. We sought to evaluate their success and association with clinical decisions. DESIGN: Retrospective Observational Study SETTING: Vanderbilt's Preoperative Evaluation Clinic MEASUREMENTS: We reviewed and identified a key interval of change on clinical workup protocols which led to a reduction in preoperative testing. We queried Data Warehouse for preoperative chemistry tests, complete blood counts, coagulation blood draws, electrocardiograms, and chest x-rays done before and after these intervals. Chi-square, univariate and mixed effect multivariable regressions were performed to determine the significance of testing reduction and tendency of readmission rates and length-of-stay; Welch's t-test with Freeman-Tukey transformation was conducted to identify the differences in case cancellation rates. MAIN RESULTS: We analyzed 56,425 anesthetic cases and there was a statistically significant downward trend in all preoperative testing performed: electrocardiograms (61.90% to 31.66% [OR 0.151; 95% CI 0.144 to 0.159]), coagulation blood draws (37.57% to 29.74% [OR 0.392; 95% CI 0.370 to 0.416]), basic metabolic panels (70.64% to 51.29% [OR 0.294; 95% CI 0.280 to 0.309]), blood cell counts (71.38% to 51.42% [OR 0.264; 95% CI 0.251 to 0.277]) and chest x-rays (11.80% to 6.04% [OR 0.417; 95% CI 0.384 to 0.452], to 3.13% [OR 0.473; 95% CI 0.431 to 0.519]) after protocol changed. The changes didn't induce a significant increase in case cancellations, length-of-stay, readmission or most DOS testing; except for BMPs (0.28% to 0.66% [OR 1.307; 95% CI 1.104 to 1.549]). CONCLUSIONS: A net reduction in preoperative testing was seen at our institution from 2012 to 2015 due to anesthesia protocol changes intended to limit routine ordering of labs and imaging. While there was a significant increase in DOS testing for BMPs, these increases were not enough to offset the decrease in testing observed preoperatively.

A retrospective evaluation of the risk of bias in perioperative temperature metrics.

The prevention and treatment of hypothermia is an important part of routine anesthesia care. Avoidance of perioperative hypothermia was introduced as a quality metric in 2010. We sought to assess the integrity of the perioperative hypothermia metric in routine care at a single large center. Perioperative temperatures from all anesthetics of at least 60 min duration between January 2012 and 2017 were eligible for inclusion in analysis. Temperatures were displayed graphically, assessed for normality, and analyzed using paired comparisons. Automatically-recorded temperatures were obtained from several monitoring sites. Provider-entered temperatures were non-normally distributed, exhibiting peaks at temperatures at multiples of 0.5 °C. Automatically-acquired temperatures, on the other hand, were more normally distributed, demonstrating smoother curves without peaks at multiples of 0.5 °C. Automatically-acquired median temperature was highest, 36.8 °C (SD = 0.8 °C), followed by the three manually acquired temperatures (nurse-documented postoperative temperature, 36.5 °C [SD = 0.6 °C]; intraoperative manual temperature, 36.5 °C [SD = 0.6 °C]; provider-documented postoperative temperature, 36.1 °C [SD = 0.6 °C]). Provider-entered temperatures exhibit values that are unlikely to represent a normal probability distribution around a central physiologic value. Manually-entered perioperative temperatures appear to cluster around salient anchoring values, either deliberately, or as an unintended result driven by cognitive bias. Automatically-acquired temperatures may be superior for quality metric purposes.

Nursing attitudes towards continuous capnographic monitoring of floor patients.

INTRODUCTION: Nurses' perceptions of the utility of capnography monitoring are inconsistent in previous studies. We sought to outline the limitations of a uniform education effort in bringing about consistent views of capnography among nurses. METHODS: A survey was administered to 22 nurses in three subacute care floors participating in a pragmatic clinical trial employing capnography monitoring in a large, urban tertiary care hospital. A 5-point Likert scale was used to assess the value and acceptance nurses ascribed to the practice. Means and SD were calculated for each response. RESULTS: Survey results indicated inconsistency in the valuation of capnography, coupled with varying degrees of acceptance of its use. The mean for the level of perceived impact of capnography use on patient safety was 3.86, yet the perceived risk of removing capnography was represented by a mean of 2.57. The levels of urgency attached to apnoea alarms (mean 3.57, SD 1.57) were lower than those for alarms for oxygen saturation violations (mean 3.67, SD 1.32). The necessity for pulse oximetry monitoring was perceived as much higher than that for capnography monitoring (mean 1.76, SD 1.34), where '1' represented pulse oximetry as more necessary and '5' represented capnography as more necessary. CONCLUSIONS: Nursing acceptance of capnography monitoring is a difficult endpoint to achieve. There is a need for better accounting for the external and internal influences on nurse perceptions and values to have greater success with the implementation of similar monitoring.

Sources of Variation in Anesthetic Drug Costs.

BACKGROUND: Increasing attention has been focused on health care expenditures, which include anesthetic-related drug costs. Using data from 2 large academic medical centers, we sought to identify significant contributors to anesthetic drug cost variation. METHODS: Using anesthesia information management systems, we calculated volatile and intravenous drug costs for 8 types of inpatient surgical procedures performed from July 1, 2009, to December 31, 2011. For each case, we determined patient age, American Society of Anesthesiologists (ASA) physical status, gender, institution, case duration, in-room provider, and attending anesthesiologist. These variables were then entered into 2 fixed-effects linear regression models, both with logarithmically transformed case cost as the outcome variable. The first model included duration, attending anesthesiologist, patient age, ASA physical status, and patient gender as independent variables. The second model included case type, institution, patient age, ASA physical status, and patient gender as independent variables. When all variables were entered into 1 model, redundancy analyses showed that case type was highly correlated (R = 0.92) with the other variables in the model. More specifically, a model that included case type was no better at predicting cost than a model without the variable, as long as that model contained the combination of attending anesthesiologist and case duration. Therefore, because we were interested in determining the effect both variables had on cost, 2 models were created instead of 1. The average change in cost resulting from each variable compared to the average cost of the reference category was calculated by first exponentiating the ß coefficient and subtracting 1 to get the percent difference in cost. We then multiplied that value by the mean cost of the associated reference group. RESULTS: A total of 5504 records were identified, of which 4856 were analyzed. The median anesthetic drug cost was $38.45 (25th percentile = $23.23, 75th percentile = $63.82). The majority of the variation was not described by our models-35.2% was explained in the model containing case duration, and 32.3% was explained in the model containing case type. However, the largest sources of variation our models identified were attending anesthesiologist, case type, and procedure duration. With all else held constant, the average change in cost between attending anesthesiologists ranged from a cost decrease of $41.25 to a cost increase of $95.67 (10th percentile = -$19.96, 90th percentile = +$20.20) when compared to the provider with the median value for mean cost per case. The average change in cost between institutions was significant but minor ($5.73). CONCLUSIONS: The majority of the variation was not described by the models, possibly indicating high per-case random variation. The largest sources of variation identified by our models included attending anesthesiologist, procedure type, and case duration. The difference in cost between institutions was statistically significant but was minor. While many prior studies have found significant savings resulting from cost-reducing interventions, our findings suggest that because the overall cost of anesthetic drugs was small, the savings resulting from interventions focused on the clinical practice of attending anesthesiologists may be negligible, especially in institutions where access to more expensive drugs is already limited. Thus, cost-saving efforts may be better focused elsewhere.

Clinical Data Visualization: The Current State and Future Needs.

The growing volume of clinical data in modern medical practice creates difficulties for clinicians when attempting to come to a full understanding of each patient's overall health status. Many different approaches to computer-based visualizations have been taken in an attempt to alleviate this burden; however, no single approach has been widely adopted. As a step towards optimization and standardization of data visualization in healthcare, this paper presents a diverse set of approaches to visualization for multiple organ systems. To do so we summarize best practices in design and evaluation while proposing usability testing methodology. We then review and illustrate the goals of various clinical data visualization techniques.

Combined effects of EPS and HRT enhanced biofouling on a submerged and hybrid PAC-MF membrane bioreactor.

The goal of this study was to quantify and demonstrate the dynamic effects of hydraulic retention time (HRT), organic carbon and various components of extracellular polymeric substances (EPS) produced by microorganisms on the performance of submersed hollow-fiber microfiltration (MF) membrane in a hybrid powdered activated carbon (PAC)-MF membrane bioreactor (MBR). The reactors were operated continuously for 45 days to treat surface (river) water before and after pretreatment using a biofiltration unit. The real-time levels of organic carbon and the major components of EPS including five different carbohydrates (D(+) glucose and D(+) mannose, D(+) galactose, N-acetyl-D-galactosamine and D-galactose, oligosaccharides and L(-) fucose), proteins, and polysaccharides were quantified in the influent water, foulants, and in the bulk phases of different reactors. The presence of PAC extended the filtration cycle and enhanced the organic carbon adsorption and removal more than two fold. Biological filtration improved the filtrate quality and decreased membrane fouling. However, HRT influenced the length of the filtration cycle and had less effect on organic carbon and EPS component removal and/or biodegradation. The abundance of carbohydrates in the foulants on MF surfaces was more than 40 times higher than in the bulk phase, which demonstrates that the accumulation of carbohydrates on membrane surfaces contributed to the increase in transmembrane pressure significantly and PAC was not a potential adsorbent of carbohydrates. The abundance of N-acetyl-d-galactosamine and d-galactose was the highest in the foulants on membranes receiving biofilter-treated river water. Most of the biological fouling compounds were produced inside the reactors due to biodegradation. PAC inside the reactor enhanced the biodegradation of polysaccharides up to 97% and that of proteins by more than 95%. This real-time extensive and novel study demonstrates that the PAC-MF hybrid MBR is a sustainable technology for treating river water.

Characterization and effect of biofouling on polyamide reverse osmosis and nanofiltration membrane surfaces.

Biofouling is a major reason for flux decline in the performance of membrane-based water and wastewater treatment plants. Initial biochemical characterization of biofilm formation potential and biofouling on two commercially available membrane surfaces from FilmTec Corporation were investigated without filtration in laboratory rotating disc reactor systems. These surfaces were polyamide aromatic thin-film reverse osmosis (RO) (BW30) and semi-aromatic nanofiltration (NF270) membranes. Membrane swatches were fixed on removable coupons and exposed to water with indigenous microorganisms supplemented with 1.5 mg l(-1) organic carbon under continuous flow. After biofilms formed, the membrane swatches were removed for analyses. Staining and epifluorescence microscopy revealed more cells on the RO than on the NF surface. Based on image analyses of 5-µm thick cryo-sections, the accumulation of hydrated biofoulants on the RO and NF surfaces exceeded 0.74 and 0.64 µm day(-1), respectively. As determined by contact angle the biofoulants increased the hydrophobicity up to 30° for RO and 4° for NF surfaces. The initial difference between virgin RO and NO hydrophobicities was ∼5°, which increased up to 25° after biofoulant formation. The initial roughness of RO and NF virgin surfaces (75.3 nm and 8.2 nm, respectively) increased to 48 nm and 39 nm after fouling. A wide range of changes of the chemical element mass percentages on membrane surfaces was observed with X-ray photoelectron spectroscopy. The initial chemical signature on the NF surface was better restored after cleaning than the RO membrane. All the data suggest that the semi-aromatic NF surface was more biofilm resistant than the aromatic RO surface. The morphology of the biofilm and the location of active and dead cell zones could be related to the membrane surface properties and general biofouling accumulation was associated with changes in the surface chemistry of the membranes, suggesting the validity of the combination of these novel approaches for initial assessment of membrane performance.