Diabetic Ketoacidosis (DKA) Insulin Infusion Protocol Update Using Evidence-Based Practice: A Quality Improvement Project

Diabetic Ketoacidosis is a life-threatening side effect to Diabetes Mellitus. Standards of treatment and recommendations are made by the American Diabetes Association. The project was to evaluate and provide the latest evidence-based practice to update the hospital policy for the treatment of DKA in the Intensive Care Unit and Emergency Department. Retrospective chart reviews were conducted to review the number of patients admitted with diabetic ketoacidosis and treated on the DKA Insulin Infusion Protocol before and after the update. Rapid correction of blood glucose levels proved to be an issue at this facility both before and after the updates were made to the DKA Insulin Infusion Protocol. The data supports the need for change in protocol, staff development in the use of the protocol and the need for change in the emergency department as well as the intensive care unit

Use of a Subcutaneous Insulin Computerized GlucoStabilizer™ Program on Glycemic Control in the Intensive Care Setting: A Retrospective Data Analysis.

Background: Despite guidelines that recommend strongly against Sliding Scale Insulin (SSI) it continues to be the most commonly insulin regimen used in hospitals to treat hyperglycemia. In addition to being reactionary to a glucose that has already increased, SSI offers practical challenges in the randomness of the doses of insulin prescribed and often a disconnect with glucose testing that should be occurring in congruence to the insulin dosing. While many clinical trials have shown improved glycemic control in critical care patients receiving intravenous insulin; few studies have demonstrated the efficacy of subcutaneous (SQ) insulin in this setting. In this study, we have evaluated the safety and efficacy of SQ insulin administration utilizing a computerized program, the Clarian GlucoStabilizer™ Subcutaneous Program (CGS-SQ) in the intensive care unit (ICU). This program is designed to overcome some of the most common barriers of SQ insulin delivery, those of dose calculation and timing. Methods: A computerized SQ insulin delivery program -The Clarian GlucoStabilizer™ Subcutaneous Program (CGS-SQ)- was made available to ICU practitioners, facilitating standardized calculation of insulin doses and incorporating reminder alarms for blood glucose (BG) testing. This program used three defaults Insulin Sensitivity Factors (ISF) and Insulin to Carbohydrate Ratios (CR) to calculate insulin doses. Additionally, there is an option for practitioner determined ISF and ICR. Patients, aged ≥ 18 years, initiated on the CGS-SQ and admitted to the (ICU) were eligible for inclusion in this retrospective evaluation. Patients were divided into four groups based on initial insulin sensitivity factor (ISF) and carbohydrate ratio (CR). Three of the groups used a default ISF and CR; ISF 60, CR 15; ISF 30, CR 10 and ISF 15, CR 8. These groups were compared with those where the practitioner specified an individualized ISF and CR, referred to as PDS (practitioner defined setting). Primary endpoints included: mean glucose, time to target glucose, hyperglycemic and hypoglycemic events. Results: In the 1,384 patients identified, patients initiated with a predefined setting had lower mean glucose compared to patients with PDS (ISF 60, CR 15: 135 mg/dL vs. ISF 30, CR 10: 140 mg/dL vs. ISF 15, CR 8: 134 mg/dL vs. PDS: 143 mg/dL; p \u3c 0.0001). Patients in the default settings had shorter time to target glucose and decreased incidence of hyperglycemia and hypoglycemia. Conclusions: Using a system of computerized prompts with standardization of insulin dose calculation, SQ insulin can be effectively used in the treatment of ICU patients to target BG of 100-150 mg/dL with minimal risk of hypoglycemia

Doctor of Philosophy

dissertationThe task of comparing and evaluating the performance of different computer-based clinical protocols is difficult and expensive to accomplish. This dissertation explores methods to compare and evaluate computer-based insulin infusion protocols based on an in silico analytical framework iteratively developed for this study, using data from the intensive care unit (ICU). In Methods for Aim 1, we used a pairwise comparative technique to evaluate two computer-based insulin infusion protocols. Our result showed that the pairwise method can rapidly identify a promising computer-based clinical protocol but with limitations. In Methods for Aim 2, we used a ranking strategy to evaluate six computer-based insulin infusion protocols. The ranking method enabled us to overcome a key limitation in Methods for Aim 1, making it possible to compare multiple computer-based clinical protocols simultaneously. In Methods for Aim 3, we developed a more comprehensive in silico method based on multiple-criteria decision analysis that included user-defined performance evaluation criteria examining different facets of the computer-based insulin infusion protocols. The in silico method appears to be an efficient way for identifying promising computer-based clinical protocols suitable for clinical evaluation. We discuss the advantages and disadvantages for each of the presented methods. We also discuss future research work and the generalizability of the framework to other potential clinical areas

Patient Monitoring Systems

book chapterBiomedical Informatic

Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock: 2016.

OBJECTIVE: To provide an update to "Surviving Sepsis Campaign Guidelines for Management of Sepsis and Septic Shock: 2012." DESIGN: A consensus committee of 55 international experts representing 25 international organizations was convened. Nominal groups were assembled at key international meetings (for those committee members attending the conference). A formal conflict-of-interest (COI) policy was developed at the onset of the process and enforced throughout. A stand-alone meeting was held for all panel members in December 2015. Teleconferences and electronic-based discussion among subgroups and among the entire committee served as an integral part of the development. METHODS: The panel consisted of five sections: hemodynamics, infection, adjunctive therapies, metabolic, and ventilation. Population, intervention, comparison, and outcomes (PICO) questions were reviewed and updated as needed, and evidence profiles were generated. Each subgroup generated a list of questions, searched for best available evidence, and then followed the principles of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system to assess the quality of evidence from high to very low, and to formulate recommendations as strong or weak, or best practice statement when applicable. RESULTS: The Surviving Sepsis Guideline panel provided 93 statements on early management and resuscitation of patients with sepsis or septic shock. Overall, 32 were strong recommendations, 39 were weak recommendations, and 18 were best-practice statements. No recommendation was provided for four questions. CONCLUSIONS: Substantial agreement exists among a large cohort of international experts regarding many strong recommendations for the best care of patients with sepsis. Although a significant number of aspects of care have relatively weak support, evidence-based recommendations regarding the acute management of sepsis and septic shock are the foundation of improved outcomes for these critically ill patients with high mortality

Computerized advice on drug dosage to improve prescribing practice

International audienceComputerized advice on drug dosage to improve prescribing practice (Review) 1 Copyright © 2013 The Cochrane Collaboration. Published by JohnWiley & Sons, Ltd. Data collection and analysis Two review authors independently extracted data and assessed study quality.We grouped the results from the included studies by drug used and the effect aimed at for aminoglycoside antibiotics, amitriptyline, anaesthetics, insulin, anticoagulants, ovarian stimulation, anti-rejection drugs and theophylline. We combined the effect sizes to give an overall effect for each subgroup of studies, using a random-effects model. We further grouped studies by type of outcome when appropriate (i.e. no evidence of heterogeneity). Main results Forty-six comparisons (from 42 trials) were included (as compared with 26 comparisons in the last update) including a wide range of drugs in inpatient and outpatient settings. All were randomized controlled trials except two studies. Interventions usually targeted doctors, although some studies attempted to influence prescriptions by pharmacists and nurses. Drugs evaluated were anticoagulants, insulin, aminoglycoside antibiotics, theophylline, anti-rejection drugs, anaesthetic agents, antidepressants and gonadotropins. Although all studies used reliable outcome measures, their quality was generally low. This update found similar results to the previous update and managed to identify specific therapeutic areas where the computerized advice on drug dosage was beneficial compared with routine care: 1. it increased target peak serum concentrations (standardized mean difference (SMD) 0.79, 95% CI 0.46 to 1.13) and the proportion of people with plasma drug concentrations within the therapeutic range after two days (pooled risk ratio (RR) 4.44, 95% CI 1.94 to 10.13) for aminoglycoside antibiotics; 2. it led to a physiological parameter more often within the desired range for oral anticoagulants (SMD for percentage of time spent in target international normalized ratio +0.19, 95% CI 0.06 to 0.33) and insulin (SMD for percentage of time in target glucose range: +1.27, 95% CI 0.56 to 1.98); 3. it decreased the time to achieve stabilization for oral anticoagulants (SMD -0.56, 95% CI -1.07 to -0.04); 4. it decreased the thromboembolism events (rate ratio 0.68, 95% CI 0.49 to 0.94) and tended to decrease bleeding events for anticoagulants although the difference was not significant (rate ratio 0.81, 95%CI 0.60 to 1.08). It tended to decrease unwanted effects for aminoglycoside antibiotics (nephrotoxicity: RR 0.67, 95% CI 0.42 to 1.06) and anti-rejection drugs (cytomegalovirus infections: RR 0.90, 95% CI 0.58 to 1.40); 5. it tended to reduce the length of time spent in the hospital although the difference was not significant (SMD -0.15, 95% CI -0.33 to 0.02) and to achieve comparable or better cost-effectiveness ratios than usual care; 6. there was no evidence of differences in mortality or other clinical adverse events for insulin (hypoglycaemia), anaesthetic agents, antirejection drugs and antidepressants. For all outcomes, statistical heterogeneity quantified by I2 statistics was moderate to high. Authors’ conclusions This review update suggests that computerized advice for drug dosage has some benefits: it increases the serum concentrations for aminoglycoside antibiotics and improves the proportion of people for which the plasma drug is within the therapeutic range for aminoglycoside antibiotics. It leads to a physiological parameter more often within the desired range for oral anticoagulants and insulin. It decreases the time to achieve stabilization for oral anticoagulants. It tends to decrease unwanted effects for aminoglycoside antibiotics and anti-rejection drugs, and it significantly decreases thromboembolism events for anticoagulants. It tends to reduce the length of hospital stay compared with routine care while comparable or better cost-effectiveness ratios were achieved. However, there was no evidence that decision support had an effect on mortality or other clinical adverse events for insulin (hypoglycaemia), anaesthetic agents, anti-rejection drugs and antidepressants. In addition, there was no evidence to suggest that some decision support technical features (such as its integration into a computer physician order entry system) or aspects of organization of care (such as the setting) could optimize the effect of computerized advice. Taking into account the high risk of bias of, and high heterogeneity between, studies, these results must be interpreted with caution. P L A I N L A N G U A G E S U M M A R Y Computerized advice on drug dosage to improve prescribing practice (Review) 2 Copyright © 2013 The Cochrane Collaboration. Published by JohnWiley & Sons, Ltd. Computerized advice on drug dosage to improve prescribing practice Background Physicians and other healthcare professionals often prescribe drugs that will only work at certain concentrations. These drugs are said to have a narrow therapeutic window. This means that if the concentration of the drug is too high or too low, they may cause serious side effects or not provide the benefits they should. For example, blood thinners (anticoagulants) are prescribed to thin the blood to prevent clots. If the concentration is too high, people may experience excessive bleeding and even death. In contrast, if the concentration is too low, a clot could form and cause a stroke. For these types of drugs, it is important that the correct amount of the drug be prescribed. Calculating and prescribing the correct amount can be complicated and time-consuming for healthcare professionals. Sometimes determining the correct dose can take a long time since healthcare professionals may not want to prescribe high doses of the drugs initially because they make mistakes in calculations. Several computer systems have been designed to do these calculations and assist healthcare professionals in prescribing these types of drugs. Study characteristics We sought clinical trial evidence from scientific databases to evaluate the effectiveness of these computer systems. The evidence is current to January 2012. We found data from 42 trials (40 randomized controlled trials (trials that allocate people at random to receive one of a number of drugs or procedures) and two non-randomized controlled trials). Key results Computerized advice for drug dosage can benefit people taking certain drugs compared with empiric dosing (where a dose is chosen based on a doctor’s observations and experience)without computer assistance.When using the computer system, healthcare professionals prescribed appropriately higher doses of the drugs initially for aminoglycoside antibiotics and the correct drug dose was reached more quickly for oral anticoagulants. It significantly decreased thromboembolism (blood clotting) events for anticoagulants and tended to reduce unwanted effects for aminoglycoside antibiotics and anti-rejection drugs (although not an important difference). It tended to reduce the length of hospital stay compared with routine care with comparable or better cost-effectiveness. There was no evidence of effects on death or clinical side events for insulin (low blood sugar (hypoglycaemia)), anaesthetic agents, anti-rejection drugs (drugs taken to prevent rejection of a transplanted organ) and antidepressants. Quality of evidence The quality of the studies was low so these results must be interpreted with caution