Overview of medical errors and adverse events

Safety is a global concept that encompasses efficiency, security of care, reactivity of caregivers, and satisfaction of patients and relatives. Patient safety has emerged as a major target for healthcare improvement. Quality assurance is a complex task, and patients in the intensive care unit (ICU) are more likely than other hospitalized patients to experience medical errors, due to the complexity of their conditions, need for urgent interventions, and considerable workload fluctuation. Medication errors are the most common medical errors and can induce adverse events. Two approaches are available for evaluating and improving quality-of-care: the room-for-improvement model, in which problems are identified, plans are made to resolve them, and the results of the plans are measured; and the monitoring model, in which quality indicators are defined as relevant to potential problems and then monitored periodically. Indicators that reflect structures, processes, or outcomes have been developed by medical societies. Surveillance of these indicators is organized at the hospital or national level. Using a combination of methods improves the results. Errors are caused by combinations of human factors and system factors, and information must be obtained on how people make errors in the ICU environment. Preventive strategies are more likely to be effective if they rely on a system-based approach, in which organizational flaws are remedied, rather than a human-based approach of encouraging people not to make errors. The development of a safety culture in the ICU is crucial to effective prevention and should occur before the evaluation of safety programs, which are more likely to be effective when they involve bundles of measures

Mild hypoglycemia is strongly associated with increased intensive care unit length of stay

Background: Hypoglycemia is associated with increased mortality in critically ill patients. The impact of hypoglycemia on resource utilization has not been investigated. The objective of this investigation was to evaluate the association of hypoglycemia, defined as a blood glucose concentration (BG) <70 mg/dL, and intensive care unit (ICU) length of stay (LOS) in three different cohorts of critically ill patients. Methods: This is a retrospective investigation of prospectively collected data, including patients from two large observational cohorts: 3,263 patients admitted to Stamford Hospital (ST) and 2,063 patients admitted to three institutions in The Netherlands (NL) as well as 914 patients from the GLUCONTROL trial (GL), a multicenter prospective randomized controlled trial of intensive insulin therapy. Results: Patients with hypoglycemia were more likely to be diabetic, had higher APACHE II scores, and higher mortality than did patients without hypoglycemia. Patients with hypoglycemia had longer ICU LOS (median [interquartile range]) in ST (3.0 [1.4-7.1] vs. 1.2 [0.8-2.3] days, P <0.0001), NL (5.2 [2.6-10.3] vs. 2.0 [1.3-3.2] days, P <0.0001), and GL (9 [5-17] vs. 5 [3-9] days, P <0.0001). For the entire cohort of 6,240 patients ICU LOS was 1.8 (1.03.3) days for those without hypoglycemia and 3.0 (1.5-6.7) days for those with a single episode of hypoglycemia (P <0.0001). This was a consistent finding even when patients were stratified by severity of illness or survivor status. There was a strong positive correlation between the number of episodes of hypoglycemia and ICU LOS among all three cohorts. Conclusions: This multicenter international investigation demonstrated that hypoglycemia was consistently associated with significantly higher ICU LOS in heterogeneous cohorts of critically ill patients, independently of severity of illness and survivor status. More effective methods to prevent hypoglycemia in these patients may positively impact their cost of car

The role of insulin therapy and glucose normalisation in patients with acute coronary syndrome

Patients with acute myocardial infarction (AMI) and diabetes mellitus, as well as patients admitted with elevated blood glucose without known diabetes, have impaired outcome. Therefore intensive glucose-lowering therapy with insulin (IGL) has been proposed in diabetic or hyperglycaemic patients and has been shown to improve survival and reduce incidence of adverse events. The current manuscript provides an overview of randomised controlled trials investigating the effect of IGL. Furthermore, systematic glucose–insulin–potassium infusion (GIK) has been studied to improve outcome after AMI. In spite of positive findings in some early studies, GIK did not show any beneficial effects in recent clinical trials and thus this concept has been abandoned. While IGL targeted to achieve normoglycaemia improves outcome in patients with AMI, achievement of glucose regulation is difficult and carries the risk of hypoglycaemia. More research is needed to determine the optimal glucose target levels in AMI and to investigate whether computerised glucose protocols and continuous glucose sensors can improve safety and efficacy of IGL

Computer-assisted glucose control in critically ill patients

Objective: Intensive insulin therapy is associated with the risk of hypoglycemia and increased costs of material and personnel. We therefore evaluated the safety and efficiency of a computer-assisted glucose control protocol in a large population of critically ill patients. Design and setting: Observational cohort study in three intensive care units (32 beds) in a 1,300-bed university teaching hospital. Patients: All 2,800 patients admitted to the surgical, neurosurgical, and cardiothoracic units; the study period started at each ICU after implementation of Glucose Regulation for Intensive Care Patients (GRIP), a freely available computer-assisted glucose control protocol. Measurements and results: We analysed compliance in relation to recommended insulin pump rates and glucose measurement frequency. Patients were on GRIP-ordered pump rates 97% of time. Median measurement time was 5 min late (IQR 20 min early to 34 min late). Hypoglycemia was uncommon (7% of patients for mild hypoglycemia, <3.5 mmol/l; 0.86% for severe hypoglycemia, <2.2 mmol/l). Our predefined target range (4.0 - 7.5 mmol/l) was reached after a median of 5.6h (IQR 0.2 - 11.8) and maintained for 89% (70 - 100%) of the remaining stay at the ICU. The number of measurements needed was 5.9 (4.8 - 7.3) per patient per day. In-hospital mortality was 10.1%. Conclusions: Our computer-assisted glucose control protocol provides safe and efficient glucose regulation in routine intensive care practice. A low rate of hypoglycemic episodes was achieved with a considerably lower number of glucose measurements than used in most other schemes

Implementing glucose control in intensive care: a multicenter trial using statistical process control

Glucose control (GC) with insulin decreases morbidity and mortality of critically ill patients. In this study we investigated GC performance over time during implementation of GC strategies within three intensive care units (ICUs) and in routine clinical practice. All adult critically ill patients who stayed for >24 h between 1999 and 2007 were included. Effects of implementing local GC guidelines and guideline revisions on effectiveness/efficiency-related indicators, safety-related indicators, and protocol-related indicators were measured. Data of 17,111 patient admissions were evaluated, with 714,141 available blood glucose levels (BGL) measurements. Mean BGL, time to reach target, hyperglycemia index, sampling frequency, percentage of hyperglycemia events, and in-range measurements statistically changed after introducing GC in all ICUs. The introduction of simple rules on GC had the largest effect. Subsequent changes in the protocol had a smaller effect than the introduction of the protocol itself. As soon as the protocol was introduced, in all ICUs the percentage of hypoglycemia events increased. Various revisions were implemented to reduce hypoglycemia events, but levels never returned to those from pre-implementation. More intensive implementation strategies including the use of a decision support system resulted in better control of the process. There are various strategies to achieve GC in routine clinical practice but with variable success. All of them were associated with an increase in hypoglycemia events, but GC was never stopped. Instead, these events have been accepted and managed. Statistical process control is a useful tool for monitoring phenomena over time and captures within-institution change

International recommendations for glucose control in adult non diabetic critically ill patients

The purpose of this research is to provide recommendations for the management of glycemic control in critically ill patients.Comparative StudyJournal ArticleResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishedPour la Société Française d'Anesthésie-Réanimation (SFAR); Société de Réanimation de langue Française (SRLF) and the Experts grou

Control of hyperglycaemia in paediatric intensive care (CHiP): study protocol.

BACKGROUND: There is increasing evidence that tight blood glucose (BG) control improves outcomes in critically ill adults. Children show similar hyperglycaemic responses to surgery or critical illness. However it is not known whether tight control will benefit children given maturational differences and different disease spectrum. METHODS/DESIGN: The study is an randomised open trial with two parallel groups to assess whether, for children undergoing intensive care in the UK aged <or= 16 years who are ventilated, have an arterial line in-situ and are receiving vasoactive support following injury, major surgery or in association with critical illness in whom it is anticipated such treatment will be required to continue for at least 12 hours, tight control will increase the numbers of days alive and free of mechanical ventilation at 30 days, and lead to improvement in a range of complications associated with intensive care treatment and be cost effective. Children in the tight control group will receive insulin by intravenous infusion titrated to maintain BG between 4 and 7.0 mmol/l. Children in the control group will be treated according to a standard current approach to BG management. Children will be followed up to determine vital status and healthcare resources usage between discharge and 12 months post-randomisation. Information regarding overall health status, global neurological outcome, attention and behavioural status will be sought from a subgroup with traumatic brain injury (TBI). A difference of 2 days in the number of ventilator-free days within the first 30 days post-randomisation is considered clinically important. Conservatively assuming a standard deviation of a week across both trial arms, a type I error of 1% (2-sided test), and allowing for non-compliance, a total sample size of 1000 patients would have 90% power to detect this difference. To detect effect differences between cardiac and non-cardiac patients, a target sample size of 1500 is required. An economic evaluation will assess whether the costs of achieving tight BG control are justified by subsequent reductions in hospitalisation costs. DISCUSSION: The relevance of tight glycaemic control in this population needs to be assessed formally before being accepted into standard practice