Impact of Audit and Feedback on Timing Variation in the Point of Care Glucose Collection-Insulin Administration Workflow: A Quality Improvement Study

BACKGROUND: Multiple roles contribute to the point of care glucose collection and insulin administration workflow. Diabetes care associations and safety advocates provide recommendations since the time-action profile of prandial insulin requires knowledge and performance to deliver insulin safely. PROBLEM: Variation of practice in relation to the time that point of care glucose was collected and meal and insulin administration assessments were completed failed to meet parameters. PURPOSE: A quality improvement project aimed to test the effect audit and feedback has on rapid acting insulin administration and point of care glucose collection practice at meals. METHOD: Audit and feedback, a knowledge transfer-behavior change intervention, was tested to determine its effectiveness as a technique to translate evidence to practice. Audit and feedback cycles informed nurses of the goals, performance measures, and gaps to improve practice. A pre-test post-test study design was used. Point of care glucose and rapid acting insulin data was retrospectively audited from electronic medical records of a medical-surgical unit. RESULTS: Post-intervention performance measures indicated the intervention was not effective. Variation persisted after the intervention. While the frequency of outcomes measures did not improve, the quality improvement process revealed information to inform clinical improvements for future quality improvement. CONCLUSION: Audit and feedback as an intervention for knowledge transfer and behavior change remains a questionable intervention for translating evidence to practice. More evidence is needed of when and how audit and feedback will be most effective must be understood

LABRAD : Vol 46, Issue 4 - October 2021

Role of Barcoding in a Clinical Laboratory to Reduce Pre-Analytical Errors Congenital Dyserythropoietic Anemia: The Morphological Diagnosis Digital Imaging in Hematology: A New Beginning Metabolomics: Identification of Fatty Acid Oxidation (FAO) Disorders Next-Generation Sequencing for HLA Genotyping Urine Metabolomics to identify Organic Academia Next-Generation Sequencing (NGS) of Solid Tumor Importance of using Genomic Tool in Microbial Identification Radiology Practice in 21st Century: Role of Artificial Intelligence Case Quiz Best of the Recent Past Polaroidhttps://ecommons.aku.edu/labrad/1036/thumbnail.jp

Clinical decision support systems in the care of hospitalised patients with diabetes

This thesis explored the role of health informatics (decision support systems) in caring for hospitalised patients with diabetes through a systematic review and by analysing data from University Hospital Birmingham, UK. Findings from the thesis: 1) highlight the potential role of computerised physician order entry system in improving guideline based anti-diabetic medication prescription in particular insulin prescription, and their effectiveness in contributing to better glycaemic control; 2) quantify the occurrence of missed discharge diagnostic codes for diabetes using electronic prescription data and suggests 60% of this could be potentially reduced using an algorithm that could be introduced as part of the information system; 3) found that hypoglycaemia and foot disease in hospitalised diabetes patients were independently associated with higher in-hospital mortality rates and longer length of stay; 4) quantify the hypoglycaemia rates in non-diabetic patients and proposes one method of establishing a surveillance system to identify non diabetic hypoglycaemic patients; and 5) introduces a prediction model that may be useful to identify patients with diabetes at risk of poor clinical outcomes during their hospital stay

The scientific impact of the Structural Genomics Consortium: a protein family and ligand-centered approach to medically-relevant human proteins

As many of the structural genomics centers have ended their first phase of operation, it is a good point to evaluate the scientific impact of this endeavour. The Structural Genomics Consortium (SGC), operating from three centers across the Atlantic, investigates human proteins involved in disease processes and proteins from Plasmodium falciparum and related organisms. We present here some of the scientific output of the Oxford node of the SGC, where the target areas include protein kinases, phosphatases, oxidoreductases and other metabolic enzymes, as well as signal transduction proteins. The SGC has aimed to achieve extensive coverage of human gene families with a focus on protein–ligand interactions. The methods employed for effective protein expression, crystallization and structure determination by X-ray crystallography are summarized. In addition to the cumulative impact of accelerated delivery of protein structures, we demonstrate how family coverage, generic screening methodology, and the availability of abundant purified protein samples, allow a level of discovery that is difficult to achieve otherwise. The contribution of NMR to structure determination and protein characterization is discussed. To make this information available to a wide scientific audience, a new tool for disseminating annotated structural information was created that also represents an interactive platform allowing for a continuous update of the annotation by the scientific community

Modeling and control to improve blood glucose concentration for people with diabetes

Diabetes mellitus is a chronical condition that features either the lack of insulin or increased insulin resistance. It is a disorder in the human metabolic system. To combat insufficiency of insulin released by pancreas, a closed-loop control system, also known as artificial pancreas (AP) in this application, have been created to mimic the functionality of a human pancreas. An AP is used to regulate blood glucose concentration (BGC) by managing the release of insulin. Therefore, an algorithm, which can administer insulin to reduce the variation of BGC and minimize the occurrences of hyper-/ hypoglycemia episodes, is the key component of an AP. The objective of the dissertation is to develop an optimal algorithm to better control BGC for people with diabetes. For people with Type 2 diabetes, prevention or treatment of diabetes mellitus can typically be done via a change of lifestyle and weight management. A virtual sensing system that does not require many manual inputs from patients can ease the burden for people with Type 2 diabetes. This dissertation covers the development of a monitoring system for Type 2 diabetes. To achieve the goal of tighter control of BGC for people with Type 1 diabetes, dynamic modeling methodology for capturing the cause-and-effect relationship between manipulated variable (i.e. insulin) and controlled variable (i.e. BGC) has been developed. Theoretically, this dissertation has established that physiologically based nonlinear parameterized wiener models being superior to nonlinear autoregressive moving average with exogenous inputs (NARMAX) models in capturing dynamic relationships in processes with correlated inputs. Based on these results, wiener models have been applied in the modeling of BGC for real subjects with Type 1 diabetes under free-living conditions. With promising results shown in wiener models, an extended physiologically based model (i.e. semi-coupled model) has been developed from wiener structure, which enables the development of a phenomenologically sound feedforward control law. The feedforward control law based on wiener models has been tested in simulated continuous-stirred-tank reactor (CSTR) that demonstrates tight control of controlled variables. Further simulation runs with a CSTR also shows feedforward predictive control (FFPC) can provide tighter control over model predictive control (MPC). Lastly, for the special application of BGC control for people with Type 1 diabetes, FFPC demonstrates tighter control than MPC under simulation environment. To account for unmeasured disturbances and inaccurate models for manipulated variable in real life scenarios, feedback predictive control (FBPC) is developed and proven to be a more effective control algorithm under both CSTR and diabetes simulation environment, which can establish the foundation for tightening BGC in real subject clinical studies

Access to Personal Transportation for People with Disabilities with Autonomous Vehicles

The objective of this paper was to explore the potential of emerging technology of autonomous vehicles in accessible transportation and incorporate these findings a standardized transportation solution that readily accommodates future travelers with disabilities based on careful study on current trends in accessible transportation and interviews and surveys that were conducted as a part of this effort. The suggested solution and design principles associated with it took in account, the popular opinions of people with disabilities as well as various experts in the field of accessible transportation. The presented solution is based on emerging technology that is being actively pursued by the automotive industry and research institutions and seriously being considered through current and pending state legislation as a viable product in the near future. This paper explores the legal, technical and safety obstacles that lay in the path to making this a reality

Fibroblast Growth Factor 21 is a Novel Protein Sensor in Pregnancy

The twenty-first century has experienced a shift in cause of death worldwide from communicable diseases to noncommunicable diseases. Interestingly, many of these implicated chronic diseases, such as cancer, diabetes, and cardiovascular disease, have been shown to be programmed in the womb. As first posited by the Barker Hypothesis, adverse exposures in utero can increase an individual’s risk for chronic disease later in life. Therefore, pregnancy is an opportune time for intervention to improve the health of future generations. Studies of exposures known to negatively impact infant health, e.g. states of overnutrition (obesity, diabetes, excess gestational weight gain) and undernutrition (starvation, protein restriction), are critical to reveal the mechanisms of and identify markers for developmental programming. Numerous endocrine signals including insulin, leptin, and adiponectin have been extensively investigated during pregnancy with aberrant effects on offspring growth and metabolic function. A novel endocrine hormone, fibroblast growth factor 21 (FGF21), which has been recently implicated as a signal for protein restriction, has not yet been studied for a potential role in developmental programming of future disease. Therefore, we aimed to investigate the role of FGF21 in pregnancy. We hypothesized FGF21 may be a nutrient sensor and a signal for fetal nutrient insufficiency during pregnancy. In studies of healthy, pregnant women, we found FGF21 was acutely regulated by maternal macronutrient balance. We then found in both mice and human studies that FGF21 is elevated in response to low maternal protein intake in pregnancy. We also showed elevated maternal FGF21 correlated with decreased infant size in the first year of life, an outcome commonly associated with reduced maternal protein intake in pregnancy. Finally, we used the Protein Leverage Hypothesis to directly test whether FGF21 is indeed a protein sensor in pregnancy and found that FGF21 is required for the hyperphagic response to low protein intake in pregnancy. In summary, these studies support the hypothesis that FGF21 is a protein sensor in pregnancy. Further studies in large clinical populations including fetal growth restriction are needed to discern whether FGF21 could be used as a marker for fetal nutrient insufficiency in the public health setting

Tackling dysfunction of mitochondrial bioenergetics in the brain

Oxidative phosphorylation (OxPhos) is the basic function of mitochondria, although the landscape of mitochondrial functions is continuously growing to include more aspects of cellular homeostasis. Thanks to the application of -omics technologies to the study of the OxPhos system, novel features emerge from the cataloging of novel proteins as mitochondrial thus adding details to the mitochondrial proteome and defining novel metabolic cellular interrelations, especially in the human brain. We focussed on the diversity of bioenergetics demand and different aspects of mitochondrial structure, functions, and dysfunction in the brain. Definition such as ‘mitoexome’, ‘mitoproteome’ and ‘mitointeractome’ have entered the field of ‘mitochondrial medicine’. In this context, we reviewed several genetic defects that hamper the last step of aerobic metabolism, mostly involving the nervous tissue as one of the most prominent energy-dependent tissues and, as consequence, as a primary target of mitochondrial dysfunction. The dual genetic origin of the OxPhos complexes is one of the reasons for the complexity of the genotype-phenotype correlation when facing human diseases associated with mitochondrial defects. Such complexity clinically manifests with extremely heterogeneous symptoms, ranging from organ-specific to multisystemic dysfunction with different clinical courses. Finally, we briefly discuss the future directions of the multi-omics study of human brain disorders

Aerospace Medicine and Biology, a continuing bibliography with indexes

This bibliography lists 197 reports, articles and other documents introduced into the NASA scientific and technical information system in November 1984