Management of Individuals With Diabetes at High Risk for Hypoglycemia: An Endocrine Society Clinical Practice Guideline.

CONTEXT: Hypoglycemia in people with diabetes is common, especially in those taking medications such as insulin and sulfonylureas (SU) that place them at higher risk. Hypoglycemia is associated with distress in those with diabetes and their families, medication nonadherence, and disruption of life and work, and it leads to costly emergency department visits and hospitalizations, morbidity, and mortality. OBJECTIVE: To review and update the diabetes-specific parts of the 2009 Evaluation and Management of Adult Hypoglycemic Disorders: Endocrine Society Clinical Practice Guideline and to address developing issues surrounding hypoglycemia in both adults and children living with diabetes. The overriding objectives are to reduce and prevent hypoglycemia. METHODS: A multidisciplinary panel of clinician experts, together with a patient representative, and methodologists with expertise in evidence synthesis and guideline development, identified and prioritized 10 clinical questions related to hypoglycemia in people living with diabetes. Systematic reviews were conducted to address all the questions. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess the certainty of evidence and make recommendations. RESULTS: The panel agreed on 10 questions specific to hypoglycemia risk and prevention in people with diabetes for which 10 recommendations were made. The guideline includes conditional recommendations for use of real-time continuous glucose monitoring (CGM) and algorithm-driven insulin pumps in people with type 1 diabetes (T1D), use of CGM for outpatients with type 2 diabetes at high risk for hypoglycemia, use of long-acting and rapid-acting insulin analogs, and initiation of and continuation of CGM for select inpatient populations at high risk for hypoglycemia. Strong recommendations were made for structured diabetes education programs for those at high risk for hypoglycemia, use of glucagon preparations that do not require reconstitution vs those that do for managing severe outpatient hypoglycemia for adults and children, use of real-time CGM for individuals with T1D receiving multiple daily injections, and the use of inpatient glycemic management programs leveraging electronic health record data to reduce the risk of hypoglycemia. CONCLUSION: The recommendations are based on the consideration of critical outcomes as well as implementation factors such as feasibility and values and preferences of people with diabetes. These recommendations can be used to inform clinical practice and health care system improvement for this important complication for people living with diabetes.

Automated Self-Adjusting Subcutaneous Insulin Algorithm for Patients NPO or on TPN or Enteral Feedings.

BACKGROUND: Perioperative diabetes patients are often treated with sliding-scale insulin, despite a lack of evidence to support therapeutic effectiveness. We introduced an automated subcutaneous insulin algorithm (SQIA) to improve glycemic control in these patients while maintaining the simplicity of a q4 hour adjustable sliding-scale insulin order set. METHODS: In this pilot study, we implemented a fully programmed, self-adjusting SQIA as part of a structured order set in the electronic medical record for adult patients who are nil per os, or on continuous enteral tube feedings or total parenteral nutrition. The nurse only enters the current glucose in the Medication Administration Record, and then the calculated dose is shown. The new dose is based on previous dose, and current and previous glucoses. The SQIA titrates the glucose to 120-180 mg/dL. For this pilot, this order set was utilized for complex perioperative oncologic patients. RESULTS: The median duration on the SQIA was 58 hours. Glucoses at titration initiation were highest at 206 ± 63 mg/dL, and came down to 156 ± 29 mg/dL by 72 hours. The majority of measured glucoses (66.8%, n = 647) were maintained between 80 and 180 mg/dL. There were no glucoses lower than 60 mg/dL, and only 0.3% (n = 3) were below 70 mg/dL. There was a low rate of errors (1%). CONCLUSIONS: A simple automated SQIA can be used to titrate insulin to meet the changing metabolic requirements of individuals perioperatively and maintain glucose within the target range for these hospitalized patients.

Decreasing Hypoglycemia following Insulin Administration for Inpatient Hyperkalemia.

BACKGROUND: Acute hyperkalemia (serum potassium ≥ 5.1 mEq/L) is often treated with a bolus of IV insulin. This treatment may result in iatrogenic hypoglycemia (glucose < 70 mg/dl). OBJECTIVES: The aims of this study were to accurately determine the frequency of iatrogenic hypoglycemia following insulin treatment for hyperkalemia, and to develop an electronic health record (EHR) orderset to decrease the risk for iatrogenic hypoglycemia. DESIGN: This study was an observational, prospective study. SETTING: The setting for this study was a university hospital. PATIENTS: All nonobstetric adult inpatients in all acute and intensive care units were eligible. INTERVENTION: Implementation of a hyperkalemia orderset (Orderset 1.1) with glucose checks before and then one, two, four, and six hours after regular intravenous insulin administration. Based on the results from Orderset 1.1, Orderset 1.2 was developed and introduced to include weight-based dosing of insulin options, alerts identifying patients at higher risk of hypoglycemia, and tools to guide decision-making based on the preinsulin blood glucose level. MEASUREMENTS: Patient demographics, weight, diabetes history, potassium level, renal function, and glucose levels were recorded before, and then glucose levels were measured again at one, two, four, and six hours after insulin was administered. RESULTS: The iatrogenic hypoglycemia rate identified with mandatory glucose checks in Orderset 1.1 was 21%; 92% of these occurred within three hours posttreatment. Risk factors for hypoglycemia included decreased renal function (serum creatinine >2.5 mg/dl), a high dose of insulin (>0.14 units/kg), and re-treatment with blood glucose < 140 mg/dl. After the introduction of Orderset 1.2, the rate of iatrogenic hypoglycemia decreased to 10%. CONCLUSIONS: The use of an EHR orderset for treating hyperkalemia may reduce the risk of iatrogenic hypoglycemia in patients receiving insulin while still adequately lowering their potassium.

A Survey of Opioid Medication Stewardship Practices at Academic Medical Centers.

Purpose: The results of a survey of academic medical centers assessing the presence and description of opioid stewardship activities. Methods: Academic medical centers within the Vizient University Health System Consortium Pharmacy Network were asked to complete a survey related to opioid stewardship activities. The survey consisted of 30 questions aimed at identifying current opioid stewardship practices among hospitals and health systems. Results: There were 27 respondents to the survey. Only 42.3% of respondents have opioid stewardship activities in place. Opioid stewardship practices are primarily linked to either formal consult services or the role of a clinical pharmacy specialist. Very few institutions have opioid stewardship embedded into the daily practice of clinical pharmacists. Just over half of respondents have pharmacists as part of a pain consult team. Principle roles of pharmacists on consult teams include provider education, patient education, and optimization of therapy outside of a collaborative practice or prescribing role. Over half of the respondents participating in stewardship maintain a pharmacist's role in monitoring surgery and postoperative opioid prescribing. The majority of respondents have opioid medication policies in place to address range orders, smart pump programming of opioids, limits on meperidine use, and cumulative limits on acetaminophen dosing. Conclusion: There are limited examples of pharmacy services related to opioid stewardship. The authors believe this is a pharmacy practice model that will evolve with the national attention to the opioid epidemic and new Joint Commission Standards.

Development and Implementation of a Subcutaneous Insulin Pen Label Bar Code Scanning Protocol to Prevent Wrong-Patient Insulin Pen Errors.

PROBLEM DEFINITION: Insulin, a high-alert medication, is regularly prescribed in the inpatient setting for hyperglycemia and diabetes mellitus. Although convenient, insulin pens carry a risk of blood-borne pathogens if the same pen is used on multiple patients. At the University of California, San Francisco (UCSF), a new nursing protocol for insulin pen administration was developed to ensure that insulin was quickly available and to identify and move to eliminate wrong-patient insulin pen errors. This protocol involved unit-based automated dispensing machines and an electronic health record (EHR)-integrated patient-specific bar code label work flow. APPROACH: After piloting on three hospital units, this new patient-specific bar code label process was expanded hospitalwide. "Print Label For Insulin Pen" and "Scan Insulin Pen" buttons were programmed into the EHR to enable nurses to print patient-specific bar code labels. In addition, a "wrong-patient pen alert" was activated to prevent wrong-pen insulin pen administration. OUTCOMES: For the 162,075 inpatient insulin pen administrations during the study period (April 2017-March 2018), monthly errors (rates) ranged from 13 (0.12%) to 36 (0.23%). In total, 296 near-miss events (0.18% of all insulin pen administrations) were observed and prevented. CONCLUSION: Insulin pen work flow and EHR changes implemented at UCSF enable subcutaneous insulin to remain a time-critical medication and ensure patient safety. The wide adoption of EHRs offers an opportunity to integrate patient safety improvements directly into the electronic medication administration record systems to maximize patient safety.

Remote Monitoring and Consultation of Inpatient Populations with Diabetes.

PURPOSE OF REVIEW: Inpatient hyperglycemia is common and is linked to increased morbidity and mortality. We review current and innovative ways diabetes specialists consult in the management of inpatient diabetes. RECENT FINDINGS: With electronic medical records (EMRs), remote monitoring and intervention may improve the management of inpatient hyperglycemia. Automated reports allow monitoring of glucose levels and allow diabetes teams to intervene through formal or remote consultation. Following a 2-year transition of our complex paper-based insulin order sets to be EMR based, we leveraged this change by developing new daily glycemic reports and a virtual glucose management service (vGMS). Based on a daily report identifying patients with two or more glucoses over 225 mg/dl and/or a glucose <70 mg/dl in the past 24 h, a vGMS note with management recommendations was placed in the chart. Following the introduction of the vGMS, the proportion of hyperglycemic patients decreased 39% from a baseline of 6.5 per 100 patient-days to 4.0 per 100 patient-days The hypoglycemia proportion decreased by 36%. Ninety-nine percent of surveyed medical and surgical residents said the vGMS was both important and helpful.

Association Between a Virtual Glucose Management Service and Glycemic Control in Hospitalized Adult Patients: An Observational Study.

BACKGROUND: Inpatient hyperglycemia is common and is linked to adverse patient outcomes. New methods to improve glycemic control are needed. OBJECTIVE: To determine whether a virtual glucose management service (vGMS) is associated with improved inpatient glycemic control. DESIGN: Cross-sectional analyses of three 12-month periods (pre-vGMS, transition, and vGMS) between 1 June 2012 and 31 May 2015. SETTING: 3 University of California, San Francisco, hospitals. PATIENTS: All nonobstetric adult inpatients who underwent point-of-care glucose testing. INTERVENTION: Hospitalized adult patients with 2 or more glucose values of 12.5 mmol/L or greater (≥225 mg/dL) (hyperglycemic) and/or a glucose level less than 3.9 mmol/L (<70 mg/dL) (hypoglycemic) in the previous 24 hours were identified using a daily glucose report. Based on review of the insulin/glucose chart in the electronic medical record, recommendations for insulin changes were entered in a vGMS note, which could be seen by all clinicians. MEASUREMENTS: Proportion of patient-days classified as hyperglycemic, hypoglycemic, and at-goal (all measurements ≥3.9 and ≤10 mmol/L [≥70 and ≤180 mg/dL] during the pre-vGMS, transition, and vGMS periods). RESULTS: The proportion of hyperglycemic patients decreased by 39%, from 6.6 per 100 patient-days in the pre-vGMS period to 4.0 per 100 patient-days in the vGMS period (difference, -2.5 [95% CI, -2.7 to -2.4]). The hypoglycemic proportion in the vGMS period was 36% lower than in the pre-vGMS period (difference, -0.28 [CI, -0.35 to -0.22]). Forty severe hypoglycemic events (<2.2 mmol/L [<40 mg/dL]) occurred during the pre-vGMS period compared with 15 during the vGMS period. LIMITATION: Information was not collected on patients' concurrent illnesses and treatment or physicians' responses to the vGMS notes. CONCLUSION: Implementation of the vGMS was associated with decreases in hyperglycemia and hypoglycemia. PRIMARY FUNDING SOURCE: National Institutes of Health, the Wilsey Family Foundation, and the UCSF Clinical & Translational Science Institute.

A detailed description of the implementation of inpatient insulin orders with a commercial electronic health record system.

In the setting of Meaningful Use laws and professional society guidelines, hospitals are rapidly implementing electronic glycemic management order sets. There are a number of best practices established in the literature for glycemic management protocols and programs. We believe that this is the first published account of the detailed steps to be taken to design, implement, and optimize glycemic management protocols in a commercial computerized provider order entry (CPOE) system. Prior to CPOE implementation, our hospital already had a mature glycemic management program. To transition to CPOE, we underwent the following 4 steps: (1) preparation and requirements gathering, (2) design and build, (3) implementation and dissemination, and (4) optimization. These steps required more than 2 years of coordinated work between physicians, nurses, pharmacists, and programmers. With the move to CPOE, our complex glycemic management order sets were successfully implemented without any significant interruptions in care. With feedback from users, we have continued to refine the order sets, and this remains an ongoing process. Successful implementation of glycemic management protocols in CPOE is dependent on broad stakeholder input and buy-in. When using a commercial CPOE system, there may be limitations of the system, necessitating workarounds. There should be an upfront plan to apply resources for continuous process improvement and optimization after implementation.