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

BackgroundGlucose 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.MethodsAll 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.ResultsData 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.ConclusionThere 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 changes.

[1]  Anthony Delaney,et al.  Tight glycemic control in critically ill adults. , 2008, JAMA.

[2]  Ameen Abu-Hanna,et al.  A systematic review on quality indicators for tight glycaemic control in critically ill patients: need for an unambiguous indicator reference subset , 2008, Critical care.

[3]  Renda Soylemez Wiener,et al.  Ill Adults: A Meta-analysis Benefits and Risks of Tight Glucose Control in Critically , 2010 .

[4]  G. Van den Berghe.  First do no harm ... hypoglycemia or hyperglycemia? , 2006, Critical care medicine.

[5]  Rinaldo Bellomo,et al.  The impact of early hypoglycemia and blood glucose variability on outcome in critical illness , 2009, Critical care.

[6]  Rinaldo Bellomo,et al.  Variability of Blood Glucose Concentration and Short-term Mortality in Critically Ill Patients , 2006, Anesthesiology.

[7]  Malgorzata E. Wilinska,et al.  Tight glycaemic control by an automated algorithm with time-variant sampling in medical ICU patients , 2008, Intensive Care Medicine.

[8]  H. Outin,et al.  Failure to achieve glycemic control despite intensive insulin therapy in a medical ICU: incidence and influence on ICU mortality , 2007, Intensive Care Medicine.

[9]  Raymond G. Carey,et al.  How Do You Know That Your Care Is Improving? Part I: Basic Concepts in Statistical Thinking , 2002 .

[10]  J Geoffrey Chase,et al.  Is there more to glycaemic control than meets the eye? , 2007, Critical care.

[11]  G. Van den Berghe,et al.  Intensive insulin therapy in the medical ICU. , 2006, The New England journal of medicine.

[12]  Deborah J. Cook,et al.  Intensive insulin therapy and mortality among critically ill patients: a meta-analysis including NICE-SUGAR study data , 2009, Canadian Medical Association Journal.

[13]  J. Donado,et al.  Strict glycaemic control in patients hospitalised in a mixed medical and surgical intensive care unit: a randomised clinical trial , 2008, Critical care.

[14]  James Stephen Krinsley,et al.  Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients. , 2003, Mayo Clinic proceedings.

[15]  Benjamin M. Adams,et al.  Advanced Topics in Statistical Process Control : The Power of Shewhart's Charts , 1995 .

[16]  H. Gerstein,et al.  Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview , 2000, The Lancet.

[17]  P. Marik,et al.  Stress-hyperglycemia, insulin and immunomodulation in sepsis , 2004, Intensive Care Medicine.

[18]  Ameen Abu-Hanna,et al.  Tight glycemic control and computerized decision-support systems: a systematic review , 2009, Intensive Care Medicine.

[19]  M Schetz,et al.  Intensive insulin therapy in critically ill patients. , 2001, The New England journal of medicine.

[20]  Yingxing Wu,et al.  Effect of hyperglycemia and continuous intravenous insulin infusions on outcomes of cardiac surgical procedures: the Portland Diabetic Project. , 2004, Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists.

[21]  N. Khardori.  Intensive Insulin Therapy and Pentastarch Resuscitation in Severe Sepsis , 2008 .

[22]  P. Spronk,et al.  Intensive Insulin Therapy in Intensive Care: An Example of the Struggle to Implement Evidence-Based Medicine , 2006, PLoS medicine.

[23]  Dominic S. Lee,et al.  Implementation and evaluation of the SPRINT protocol for tight glycaemic control in critically ill patients: a clinical practice change , 2008, Critical care.

[24]  Mathijs Vogelzang,et al.  Design and implementation of GRIP: a computerized glucose control system at a surgical intensive care unit , 2005, BMC Medical Informatics Decis. Mak..

[25]  Stephane Heritier,et al.  Intensive versus conventional glucose control in critically ill patients. , 2009, The New England journal of medicine.

[26]  J. Krinsley,et al.  Glycemic variability: A strong independent predictor of mortality in critically ill patients* , 2008, Critical care medicine.

[27]  D. Bruns,et al.  Tight glucose control in critically ill adults. , 2008, JAMA.

[28]  E. de Jonge,et al.  Evaluation of short-term consequences of hypoglycemia in an intensive care unit* , 2006, Critical care medicine.

[29]  B. Bistrian,et al.  Intensive insulin therapy in critically ill patients. , 2002, The New England journal of medicine.

[30]  M A Mohammed,et al.  Plotting basic control charts: tutorial notes for healthcare practitioners , 2008, Quality & Safety in Health Care.

[31]  G. Van den Berghe,et al.  Metabolic, endocrine, and immune effects of stress hyperglycemia in a rabbit model of prolonged critical illness. , 2003, Endocrinology.

[32]  Roman Hovorka,et al.  Multicentric, randomized, controlled trial to evaluate blood glucose control by the model predictive control algorithm versus routine glucose management protocols in intensive care unit patients. , 2006, Diabetes care.

[33]  Paul Taylor,et al.  Research Paper: Use of a Computerized Guideline for Glucose Regulation in the Intensive Care Unit Improved Both Guideline Adherence and Glucose Regulation , 2004, J. Am. Medical Informatics Assoc..

[34]  M. Levy,et al.  Surviving Sepsis Campaign: International guidelines for management of severe sepsis and septic shock: 2008 , 2007, Intensive Care Medicine.

[35]  Margaret M Parker,et al.  Surviving Sepsis Campaign guidelines for management of severe sepsis and septic shock , 2004, Critical care medicine.

[36]  Raymond G. Carey,et al.  Improving Healthcare with Control Charts: Basic and Advanced SPC Methods and Case Studies , 2002 .

[37]  Thomas Lotz,et al.  A simple insulin-nutrition protocol for tight glycemic control in critical illness: development and protocol comparison. , 2006, Diabetes technology & therapeutics.

[38]  Johan Groeneveld,et al.  A prospective randomised multi-centre controlled trial on tight glucose control by intensive insulin therapy in adult intensive care units: the Glucontrol study , 2009, Intensive Care Medicine.