Heat Flux Sensing for Machine-Learning-Based Personal Thermal Comfort Modeling.

In recent years, physiological features have gained more attention in developing models of personal thermal comfort for improved and accurate adaptive operation of Human-In-The-Loop (HITL) Heating, Ventilation, and Air-Conditioning (HVAC) systems. Pursuing the identification of effective physiological sensing systems for enhancing flexibility of human-centered and distributed control, using machine learning algorithms, we have investigated how heat flux sensing could improve personal thermal comfort inference under transient ambient conditions. We have explored the variations of heat exchange rates of facial and wrist skin. These areas are often exposed in indoor environments and contribute to the thermoregulation mechanism through skin heat exchange, which we have coupled with variations of skin and ambient temperatures for inference of personal thermal preferences. Adopting an experimental and data analysis methodology, we have evaluated the modeling of personal thermal preference of 18 human subjects for well-known classifiers using different scenarios of learning. The experimental measurements have revealed the differences in personal thermal preferences and how they are reflected in physiological variables. Further, we have shown that heat exchange rates have high potential in improving the performance of personal inference models even compared to the use of skin temperature.

Cognitive Preference and Clinical Experience: The Relationship Between Student Nurse Anesthetists' and Certified Registered Nurse Anesthetists' Thinking Styles.

This study examined the relationship between cognitive preference and clinical experience in student registered nurse anesthetists (SRNAs) and certified registered nurse anesthetists (CRNAs). Survey data was collected from enrolled SRNAs and practicing CRNAs via an email link distributive through a network sampling technique. Participants completed the Rational Experiential Inventory (REI-40), which assesses individuals' preference, ability, and engagement with rational and experiential cognitive styles. Data analysis revealed that SRNAs and CRNAs have the ability and engagement preference for rational decision-making. Furthermore, there was no statistical significance in years of clinical experience to cognitive preference, nor was there a statistically significant difference between SRNA and CRNA REI-40 Inventory results. Based on these findings, the dominant cognitive preference is rational cognition and experiential thinking preference remains constant with increased experience. This knowledge contributes to our understanding of CRNAs' decision-making related to cognitive processes and provides insight into SRNA clinical education and CRNA continuing development.

Overview of Preoperative Risk Analysis: American Society of Anesthesiology Physical Status Classification and the Surgical Risk Calculator.

The certified registered nurse anesthetist has a vital role and critical position to provide safe and effective anesthesia and to speak on behalf of the patient when they cannot speak for themselves. Paramount to this process is analyzing risk factors related to the patient's physical status, the specific surgical procedure, and the method of anesthesia delivery. The American Society of Anesthesiology Physical Status Classification is a foundation in preoperative patient assessment. This preoperative assessment tool is used for assessing patient's functional reserve and risk for anesthesia. The American College of Surgeons National Surgical Quality Improvement Program developed the Surgical Risk Calculator. This preoperative assessment tool uses 21 preoperative risk factors to predict 13 perioperative complications and is proving to be a reliable indicator for predicting patient risk. Anesthetic techniques such as multimodal analgesia and enhanced recovery after surgery have demonstrated a significant impact on patient outcomes. There are potential improvements and opportunities for anesthesia providers to collaborate and improve patient risk analysis.

Biological validation of a novel process and product for quantitating western blots.

Protein normalization of western blots has relied upon housekeeping proteins which exhibit signal saturation and varied cellular expression level variations. These issues can produce spurious results leading to erroneous conclusions. A superior method to protein normalization using housekeeping proteins is Total Protein Normalization, a method now recognized as the gold standard for quantitative westerns. Total Protein Normalization requires that all proteins on a membrane be stained or labeled uniformly, imaged, and then analyzed for total protein. It is important that such a normalization process not interfere with typical immunodetection methods, fits within existing western workflows, and exhibits a linear relationship of signal intensity to protein load under all experimental conditions. Here we report that we developed a new reagent enabling Total Protein Normalization, and we demonstrate its superior protein normalization capabilities through analysis of target proteins in different cell backgrounds. These data illustrate how housekeeping proteins exhibit signal saturation, yield erroneous normalization data, and display sample-to-sample variations averaging 48.2 % overall. Signal intensities obtained using our new method show a linear relationship to protein sample load, thus providing accurate protein normalization with an overall average variation of 7.7 %.

Delayed emergencies: The composition and magnitude of non-respiratory emergency department visits during the COVID-19 pandemic.

IMPORTANCE: COVID-19 has been associated with excess mortality among patients not diagnosed with COVID-19, suggesting disruption of acute health care provision may play a role. OBJECTIVE: To determine the degree of declines in emergency department (ED) visits attributable to COVID-19 and determine whether these declines were concentrated among patients with fewer comorbidities and lower severity visits. DESIGN: We conducted a differences-in-differences analysis of all commercial health insurance claims for ED visits in the first 20 weeks of 2018, 2019, and 2020. The intervention period began March 9 (week 11) of 2020, following state stay-at-home orders. SETTING: We analyzed claims from Blue Cross Blue Shield of Louisiana (BCBSLA), located in a state with an early US COVID-19 outbreak. Visit and patient risk was assessed through comorbidities previously described as increasing the risk of COVID-19 decompensation, the hospital location's COVID-19 outbreak status, and the Ambulatory Care Sensitive Condition algorithm. PARTICIPANTS: The study population comprised all ED visits from all BCBSLA members, whether admitted or discharged. There were 332,917 ED visits over the study period. The study population spanned member demographics including sex, age, and geography. Uninsured adults were not included due to data limitations. EXPOSURES: The COVID-19 outbreak beginning March 9, 2020 in Louisiana. MAIN OUTCOMES AND MEASURES: The main outcome of interest for this analysis is the difference (percent change) in all ED visits, categorized as either respiratory or non-respiratory, from week 1-20 in 2019 and week 1-10 in 2020, compared to week 11-20 in 2020. RESULTS: In this differences-in-differences study using data from a commercial health insurer, we found that non-respiratory ED visits declined by 39%, whereas respiratory visits did not experience a significant decline. Visits that were potentially deferrable or from lower risk patient populations showed greater declines, but even high-risk patients and non-avoidable visits experienced large declines in non-respiratory ED visits. Non-respiratory ED visits declined by only 18% in areas experiencing COVID outbreak. CONCLUSIONS AND RELEVANCE: COVID-19 has resulted in significant avoidance of ED care, comprising a mix of deferrable and high severity care. Hospital and public health pronouncements should emphasize appropriate care seeking.

Non-Invasive Blood Perfusion Measurements Using a Combined Temperature and Heat Flux Surface Probe.

Non-invasive blood perfusion measurement systems have been developed and tested in a phantom tissue and an animal model. The probes use a small sensor with a laminated flat thermocouple to measure the heat transfer and temperature response to an arbitrary thermal event (convective or conductive) imposed on the tissue surface. Blood perfusion and thermal contact resistance are estimated by comparing heat flux data with a mathematical model of the tissue. The perfusion probes were evaluated for repeatability and sensitivity using both a phantom tissue test stand and exposed rat liver tests. Perfusion in the phantom tissue tests was varied by controlling the flow of water into the phantom tissue test section, and the perfusion in the exposed liver tests was varied by temporarily occluding blood flow through the portal vein. The phantom tissue tests indicated that the probes can be used to detect small changes in perfusion (0.005 ml/ml/s). The probes qualitatively tracked the changes in the perfusion of the liver model due to occlusion of the portal vein.

Quality and the Health System: Becoming a High Reliability Organization.

Since the publication of "To Err is Human" in 1999, substantial efforts have been made within the health care industry to improve quality and patient safety. Although improvements have been made, recent estimates continue to indicate the need for a marked change in approach. In this article, the authors discuss the concepts and characteristics of high reliability organizations, safety culture, and clinical microsystems. The health care delivery system must move beyond current quality and patient safety approaches and fully engage in these new concepts to transform health care system performance.

Modeling assisted evaluation of direct electricity generation from waste heat of wastewater via a thermoelectric generator.

The thermal energy represents a significant portion of energy potential in municipal wastewater and may be recovered as electricity by a thermoelectric generator (TEG). Converting heat to all-purpose electricity by TEG has been demonstrated with large heat gradients, but its application in waste heat recovery from wastewater has not been well evaluated. Herein, a bench-scale Bi2Te3-based waste heat recovery system was employed to generate electricity from a low temperature gradient through a combination of experiments and mathematical modeling. With an external resistance of 7.8â€¯Ω and a water (hot side) flow rate of 75 mL min-1, a maximum normalized energy recovery of 4.5 × 10-4 kWh m-3 was achieved under a 2.8 °C temperature gradient (ΔT). Model simulation indicated a boost in both power output and energy conversion efficiency from 0.76 mW and 0.13% at ΔT = 2.8 °C to 61.83 mW and 1.15% at ΔT = 25 °C. Based on the data of two-year water/air temperature obtained from the Christiansburg Wastewater Treatment Plant, an estimated energy generation of 1094 to 70,986 kWh could be expected annually with a saving of $163 to $6076. Those results have revealed a potential for TEG-centered direct electricity generation from low-grade heat towards enhanced resource recovery from wastewater and encouraged further exploration of this approach.

Applied Use of Safety Event Occurrence Control Charts of Harm and Non-Harm Events: A Case Study.

Most hospitals use occurrence reporting systems that facilitate identifying serious events that lead to root cause investigations. Thus, the events catalyze improvement efforts to mitigate patient harm. A serious limitation is that only a few of the occurrences are investigated. A challenge is leveraging the data to generate knowledge. The goal is to present a methodology to supplement these incident assessment efforts. The framework affords an enhanced understanding of patient safety through the use of control charts to monitor non-harm and harm incidents simultaneously. This approach can identify harm and non-harm reporting rates and also can facilitate monitoring occurrence trends. This method also can expedite identifying changes in workflow, processes, or safety culture. Although unable to identify root causes, this approach can identify changes in near real time. This approach also supports evaluating safety or policy interventions that may not be observable in annual safety climate surveys.

The Development of a Thin-Filmed Noninvasive Tissue Perfusion Sensor to Quantify Capillary Pressure Occlusion of Explanted Organs.

A new thin-filmed perfusion sensor was developed using a heat flux gauge, thin-film thermocouple, and a heating element. This sensor, termed "CHFT+," is an enhancement of the previously established combined heat flux-temperature (CHFT) sensor technology predominately used to quantify the severity of burns [1]. The CHFT+ sensor was uniquely designed to measure tissue perfusion on explanted organs destined for transplantation, but could be functionalized and used in a wide variety of other biomedical applications. Exploiting the thin and semiflexible nature of the new CHFT+ sensor assembly, perfusion measurements can be made from the underside of the organ-providing a quantitative indirect measure of capillary pressure occlusion. Results from a live tissue test demonstrated, for the first time, the effects of pressure occlusion on an explanted porcine kidney. CHFT+ sensors were placed on top of and underneath 18 kidneys to measure and compare perfusion at perfusate temperatures of 5 and 20 °C. The data collected show a greater perfusion on the topside than the underside of the specimen for the length of the experiment. This indicates that the pressure occlusion is truly affecting the perfusion, and, thus, the overall preservation of explanted organs. Moreover, the results demonstrate the effect of preservation temperature on the tissue vasculature. Focusing on the topside perfusion only, the 20 °C perfusion was greater than the 5 °C perfusion, likely due to the vasoconstrictive response at the lower perfusion temperatures.

The Human Factors Analysis Classification System (HFACS) applied to health care.

In spite of efforts to improve patient safety since the 1999 report, To Error Is Human, recent studies have shown limited progress toward preventing serious error. Most hospitals use root cause analysis as a method of serious event investigation. The authors postulate that this method suffers from 4 problems: (a) the use of root cause analysis is neither standardized nor reliable between organizations, (b) hospitals focus on "who" did "what" rather than on "why" the error occurred, (c) the identified causes are often too nonspecific to develop actionable correction plans, and (d) a standardized nomenclature does not exist to allow analysis of recurring errors across the organization. This article describes the modification of the Human Factors Analysis Classification System based on James Reason's theory of error causation for use in health care. This method resolves the 4 deficiencies noted above. The authors' experience investigating 105 serious events over 2 years is described.

Estimation of hand hygiene opportunities on an adult medical ward using 24-hour camera surveillance: validation of the HOW2 Benchmark Study.

BACKGROUND: We previously published a formula to estimate the number of hand hygiene opportunities (HHOs) per patient-day using the World Health Organization's "Five Moments for Hand Hygiene" methodology (HOW2 Benchmark Study). HHOs can be used as a denominator for calculating hand hygiene compliance rates when product utilization data are available. This study validates the previously derived HHO estimate using 24-hour video surveillance of health care worker hand hygiene activity. METHODS: The validation study utilized 24-hour video surveillance recordings of 26 patients' hospital stays to measure the actual number of HHOs per patient-day on a medicine ward in a large teaching hospital. Statistical methods were used to compare these results to those obtained by episodic observation of patient activity in the original derivation study. RESULTS: Total hours of data collection were 81.3 and 1,510.8, resulting in 1,740 and 4,522 HHOs in the derivation and validation studies, respectively. Comparisons of the mean and median HHOs per 24-hour period did not differ significantly. HHOs were 71.6 (95% confidence interval: 64.9-78.3) and 73.9 (95% confidence interval: 69.1-84.1), respectively. CONCLUSION: This study validates the HOW2 Benchmark Study and confirms that expected numbers of HHOs can be estimated from the unit's patient census and patient-to-nurse ratio. These data can be used as denominators in calculations of hand hygiene compliance rates from electronic monitoring using the "Five Moments for Hand Hygiene" methodology.

The Surgical Safety Checklist and Teamwork Coaching Tools: a study of inter-rater reliability.

OBJECTIVE: To assess the inter-rater reliability (IRR) of two novel observation tools for measuring surgical safety checklist performance and teamwork. SUMMARY BACKGROUND: Data surgical safety checklists can promote adherence to standards of care and improve teamwork in the operating room. Their use has been associated with reductions in mortality and other postoperative complications. However, checklist effectiveness depends on how well they are performed. METHODS: Authors from the Safe Surgery 2015 initiative developed a pair of novel observation tools through literature review, expert consultation and end-user testing. In one South Carolina hospital participating in the initiative, two observers jointly attended 50 surgical cases and independently rated surgical teams using both tools. We used descriptive statistics to measure checklist performance and teamwork at the hospital. We assessed IRR by measuring percent agreement, Cohen's κ, and weighted κ scores. RESULTS: The overall percent agreement and κ between the two observers was 93% and 0.74 (95% CI 0.66 to 0.79), respectively, for the Checklist Coaching Tool and 86% and 0.84 (95% CI 0.77 to 0.90) for the Surgical Teamwork Tool. Percent agreement for individual sections of both tools was 79% or higher. Additionally, κ scores for six of eight sections on the Checklist Coaching Tool and for two of five domains on the Surgical Teamwork Tool achieved the desired 0.7 threshold. However, teamwork scores were high and variation was limited. There were no significant changes in the percent agreement or κ scores between the first 10 and last 10 cases observed. CONCLUSIONS: Both tools demonstrated substantial IRR and required limited training to use. These instruments may be used to observe checklist performance and teamwork in the operating room. However, further refinement and calibration of observer expectations, particularly in rating teamwork, could improve the utility of the tools.

Hospital hand hygiene opportunities: where and when (HOW2)? The HOW2 Benchmark Study.

BACKGROUND: Measurement and monitoring of health care workers' hand hygiene compliance (i.e., actions/opportunities) is a key component of strategies to eliminate hospital-acquired infections. Little data exist on the expected number of hand hygiene opportunities (HHOs) in various hospital settings, however. The purpose of this study was to estimate HHOs in 2 types of hospitals--large teaching and small community--and 3 different clinical areas-medical-surgical intensive care units, general medical wards, and emergency departments. METHODS: HHO data were collected through direct observations using the World Health Organization's monitoring methodology. Estimates of HHOs were developed for 12-hour AM/PM shifts and 24-hour time frames. RESULTS: During 436.7 hours of observation, 6,640 HHOs were identified. Estimates of HHOs ranged from 30 to 179 per patient-day on inpatient wards and from 1.84 to 5.03 per bed-hour in emergency departments. Significant differences in HHOs were found between the 2 hospital types and among the 3 clinical areas. CONCLUSION: This study is the first to use the World Health Organization's data collection methodology to estimate HHOs in general medical wards and emergency departments. These data can be used as denominator estimates to calculate hand hygiene compliance rates when product utilization data are available.

Measurement of the thermal conductivity of carbon nanotube--tissue phantom composites with the hot wire probe method.

Developing combinatorial treatments involving laser irradiation and nanoparticles require an understanding of the effect of nanoparticle inclusion on tissue thermal properties, such as thermal conductivity. This information will permit a more accurate prediction of temperature distribution and tumor response following therapy, as well as provide additional information to aid in the selection of the appropriate type and concentration of nanoparticles. This study measured the thermal conductivity of tissue representative phantoms containing varying types and concentrations of carbon nanotubes (CNTs). Multi-walled carbon nanotubes (MWNTs, length of 900-1200 nm and diameter of 40-60 nm), single-walled carbon nanotubes (SWNTs, length of 900-1200 nm and diameter <2 nm), and a novel embodiment of SWNTs referred to as single-walled carbon nanohorns (SWNHs, length of 25-50 nm and diameter of 3-5 nm) of varying concentrations (0.1, 0.5, and 1.0 mg/mL) were uniformly dispersed in sodium alginate tissue representative phantoms. The thermal conductivity of phantoms containing CNTs was measured using a hot wire probe method. Increasing CNT concentration from 0 to 1.0 mg/mL caused the thermal conductivity of phantoms containing SWNTs, SWNHs, and MWNTs to increase by 24, 30, and 66%, respectively. For identical CNT concentrations, phantoms containing MWNTs possessed the highest thermal conductivity.

A phantom tissue system for the calibration of perfusion measurements.

A convenient method for testing and calibrating surface perfusion sensors has been developed. A phantom tissue model is used to simulate the nondirectional blood flow of tissue perfusion. A computational fluid dynamics (CFD) model was constructed in Fluent(R) to design the phantom tissue and validate the experimental results. The phantom perfusion system was used with a perfusion sensor based on clearance of thermal energy. A heat flux gage measures the heat flux response of tissue when a thermal event (convective cooling) is applied. The blood perfusion and contact resistance are estimated by a parameter estimation code. From the experimental and analytical results, it was concluded that the probe displayed good measurement repeatability and sensitivity. The experimental perfusion measurements in the tissue were in good agreement with those of the CFD models and demonstrated the value of the phantom tissue system.

Noninvasive blood perfusion measurements of an isolated rat liver and an anesthetized rat kidney.

A simple, cost effective, and noninvasive blood perfusion system is tested in animal models. The system uses a small sensor to measure the heat transfer response to a thermal event (convective cooling) imposed on the tissue surface. Heat flux data are compared with a mathematical model of the tissue to estimate both blood perfusion and thermal contact resistance between the tissue and the probe. The perfusion system was evaluated for repeatability and sensitivity using isolated rat liver and exposed rat kidney tests. Perfusion in the isolated liver tests was varied by controlling the flow of the perfusate into the liver, and the perfusion in the exposed kidney tests was varied by temporarily occluding blood flow through the renal artery and vein. The perfusion estimated by the convective perfusion probe was in good agreement with that of the metered flow of the perfusate into the liver model. The liver tests indicated that the probe can be used to detect small changes in perfusion (0.005 ml/ml/s). The probe qualitatively tracked the changes in the perfusion in the kidney model due to occlusion of the renal artery and vein.

Removal of sodium and potassium adducts using a matrix additive during matrix-associated laser desorption/ionization time-of-flight mass spectrometric analysis of peptides.

Monovalent cations often associate with peptides and proteins under mass spectrometry (MS) conditions, resulting in a discernable, but often misleading, adduct cluster pattern. These adduct cluster peaks reduce the signal intensity of specific peptide species by splitting the ion population into multiple mass peaks, suppressing the ionization of neighboring low-abundance peaks, and interfering with identification of post-translational modifications. Further, monovalent contaminants tend to form a distribution of matrix cluster peaks in matrix-associated laser desorption/ionization time-of-flight (MALDI-TOF) spectra causing interference and suppression in the mass range below 1400 Da. The most common method for reduction or elimination of adduct clusters is solid-phase extraction via a pipette tip or spin column, which often leads to loss of low-abundance peptide components. In this study we describe the use of a commercially available surfactant blend that markedly reduces the adduction of monovalent cations during peptide analysis by MALDI-TOFMS.