A Consensus Statement for Continuous Glucose Monitoring Metrics for Inpatient Clinical Trials.

Diabetes Technology Society organized an expert consensus panel to develop metrics for research in the use of continuous glucose monitors (CGMs) in a hospital setting. The experts met virtually in small groups both before and after an April 13, 2023 virtual meeting of the entire panel. The goal of the panel was to develop consensus definitions in anticipation of greater use of CGMs in hospital settings in the future. Establishment of consensus definitions of inpatient analytical metrics will be easier to compare outcomes between studies. Panelists defined terms related to 10 dimensions of measurements related to the use of CGMs including (1) hospital hypoglycemia, (2) hospital hyperglycemia, (3) hospital time in range, (4) hospital glycemic variability, (5) hospital glycemia risk index, (6) accuracy of CGM devices and reference methods for CGMs in the hospital, (7) meaningful time blocks for hospital glycemic goals, (8) hospital CGM data sufficiency, (9) using CGM data for insulin dosing, and (10) miscellaneous factors. The panelists voted on 51 proposed recommendations. Based on the panel vote, 51 recommendations were classified as either strong (43) or mild (8). Additional research is needed on CGM performance in the hospital. This consensus report is intended to support that type of research intended to improve outcomes for hospitalized people with diabetes.

Barriers to Implementation of Teleretinal Diabetic Retinopathy Screening Programs Across the University of California.

Aim: To describe barriers to implementation of diabetic retinopathy (DR) teleretinal screening programs and artificial intelligence (AI) integration at the University of California (UC). Methods: Institutional representatives from UC Los Angeles, San Diego, San Francisco, Irvine, and Davis were surveyed for the year of their program's initiation, active status at the time of survey (December 2021), number of primary care clinics involved, screening image quality, types of eye providers, image interpretation turnaround time, and billing codes used. Representatives were asked to rate perceptions toward barriers to teleretinal DR screening and AI implementation using a 5-point Likert scale. Results: Four UC campuses had active DR teleretinal screening programs at the time of survey and screened between 246 and 2,123 patients at 1-6 clinics per campus. Sites reported variation between poor-quality photos (<5% to 15%) and average image interpretation time (1-5 days). Patient education, resource availability, and infrastructural support were identified as barriers to DR teleretinal screening. Cost and integration into existing technology infrastructures were identified as barriers to AI integration in DR screening. Conclusions: Despite the potential to increase access to care, there remain several barriers to widespread implementation of DR teleretinal screening. More research is needed to develop best practices to overcome these barriers.

Glucometrics: Where Are We Now?

PURPOSE OF REVIEW: Inpatient glucose data analysis, or glucometrics, has developed alongside the growing emphasis on glycemic control in the hospital. Shortcomings in the initial capabilities for glucometrics have pushed advancements in defining meaningful units of measurement and methods for capturing glucose data. This review addresses the growth in glucometrics and ends with its promising new state. RECENT FINDINGS: Standardization, allowing for benchmarking and purposeful comparison, has been a goal of the field. The National Quality Foundation glycemic measures and recently enacted Center for Medicare and Medicaid Services (CMS) electronic quality measures for hypo- and hyperglycemia have allowed for improved integration and consistency. Prior systems have culminated in an upcoming measure from the Center for Disease Control and Prevention's National Healthcare Safety Network. It is poised to create a new gold standard for glucometrics by expanding and refining the CMS metrics, which should empower both local improvement and benchmarking as the program matures.

Accuracy and Glycemic Efficacy of Continuous Glucose Monitors in Critically Ill COVID-19 Patients: A Retrospective Study.

BACKGROUND: Continuous glucose monitoring (CGM) is approved for insulin dosing decisions in the ambulatory setting, but not currently for inpatients. CGM has the capacity to reduce patient-provider contact in inpatients with coronavirus disease 2019 (COVID-19), thus potentially reducing in hospital virus transmission. However, there are sparse data on the accuracy and efficacy of CGM to titrate insulin doses in inpatients. METHODS: Under an emergency use protocol, CGM (Dexcom G6) was used alongside standard point-of-care (POC) glucose measurements in patients critically ill from complications of COVID-19 requiring intravenous (IV) insulin. Glycemic control during IV insulin therapy was retrospectively assessed comparing periods with and without adjunctive CGM use. Accuracy metrics were computed and Clarke Error Grid analysis performed comparing CGM glucose values with POC measurements. RESULTS: Twenty-four critically ill patients who met criteria for emergency use of CGM resulted in 47 333 CGM and 5677 POC glucose values. During IV insulin therapy, individuals' glycemic control improved when CGM was used (mean difference -30.7 mg/dL). Among 2194 matched CGM: POC glucose pairs, a high degree of concordance was observed with a mean absolute relative difference of 14.8% and 99.5% of CGM: POC pairs falling in Zones A and B of the Clarke Error Grid. CONCLUSIONS: Continuous glucose monitoring use in critically ill COVID-19 patients improved glycemic control during IV insulin therapy. Continuous glucose monitoring glucose data were highly concordant with POC glucose during IV insulin therapy in critically ill patients suggesting that CGM could substitute for POC measurements in inpatients thus reducing patient-provider contact and mitigating infection transmission.

Electronic Health Record-Based Decision-Making Support in Inpatient Diabetes Management.

PURPOSE OF REVIEW: This review discusses ways in which the electronic health record (EHR) can offer clinical decision support (CDS) tools for management of inpatient diabetes and hyperglycemia. RECENT FINDINGS: The use of electronic order sets can help providers order comprehensive basal bolus insulin regimens that are consistent with current guidelines. Order sets have been shown to reduce insulin errors and hypoglycemia rates. They can also help set glycemic targets, give hemoglobin A1C reminders, guide weight-based dosing, and match insulin regimen to nutritional profile. Glycemic management dashboards allow multiple variables affecting blood glucose to be shown in a single view, which allows for efficient evaluation of glucose trends and adjustment of insulin regimen. With the use glycemic management dashboards, active surveillance and remote management also become feasible. Hypoglycemia prevention and management are another part of inpatient diabetes management that is enhanced by EHR CDS tools. Furthermore, diagnosis and management of diabetic ketoacidosis and hyperglycemia hyperosmolar state are improved with the aid of EHR CDS tools. The use of EHR CDS tools helps improve the care of patients with diabetes and hyperglycemia in the inpatient hospital setting.

Hospital care: improving outcomes in type 1 diabetes.

PURPOSE OF REVIEW: Caring for patients with type 1 diabetes (T1D) in the hospital presents unique challenges. This review provides an update on significant issues relevant to the inpatient management of T1D. Topics include trends in diabetic ketoacidosis (DKA), hypoglycemia, and adapting ambulatory technologies for inpatient use. RECENT FINDINGS: Rates of DKA in the United States are rising. Although socioeconomic status, health insurance coverage, and hemoglobin A1c are persistently associated with DKA in individuals with T1D, newer risk factors have also emerged. These include the off-label use of sodium-glucose cotransporter inhibitor medications, immune checkpoint inhibitor-induced diabetes, and infection with severe acute respiratory syndrome coronavirus 2. Hypoglycemia is common among hospitalized patients with T1D. Use of validated hypoglycemia risk prediction models and multidisciplinary care initiatives can reduce the risk of inpatient hypoglycemia. Finally, continuous glucose monitoring is being adapted for use in the hospital setting and has shown promise during the coronavirus disease 2019 (COVID-19) pandemic. SUMMARY: Evidence-based treatment algorithms, risk prediction calculators, multidisciplinary interventions, and wearable technology hold promise for improved outcomes in hospitalized patients with T1D.

Insulin Infusion Computer Calculator Programmed Directly Into Electronic Health Record Medication Administration Record.

BACKGROUND: Computerized insulin infusion protocols have demonstrated higher staff satisfaction, better compliance with protocols, and increased time with glucose in range compared to paper protocols. At University of California San Diego Health (UCSDH), we implemented an insulin infusion computer calculator (IICC) and transitioned it from a web-based platform directly into the electronic medication administration record (eMAR) of our primary electronic health record (EHR). METHODS: This is a retrospective analysis of 6306 adult patients at UCSDH receiving intravenous (IV) insulin infusion from March 7, 2013 to May 30, 2019. We created three periods of the study-(1) the pre-eMAR integration period; (2) the eMAR integration period; and (3) the post-eMAR integration period-and looked at the percentage of readings within goal range (90-150 mg/dL for intensive care unit [ICU], 90-180 mg/dL for non-ICU) in patients with and without hyperglycemic emergencies. As our safety endpoints, we elected to look at incidence of blood glucose (BG) readings <70 mg/dL, <54 mg/dL, and <40 mg/dL. RESULTS: Pre-eMAR 69.8% of readings were in the 90-150 mg/dL range compared to 70.2% post-eMAR (P = .03) and 82.7% of readings were in the 90-180 mg/dL range pre-eMAR versus 82.9% (P = .09) post-eMAR in patients without hyperglycemic emergencies. Rates of hypoglycemia with BG <70 mg/dL were 0.43%, <54 mg/dL were 0.07%, and <40 mg/dL were 0.01% of readings pre- and post-eMAR. CONCLUSIONS: At UCSDH, our IICC has shown to be safe and effective in a wide variety of clinical situations and we were able to successfully transition it from a web-based platform directly into the eMAR of our primary EHR.

Review of Intravenous and Subcutaneous Electronic Glucose Management Systems for Inpatient Glycemic Control.

PURPOSE OF REVIEW: The goal of this review is to summarize current literature on electronic glucose management systems (eGMS) and discuss their benefits and disadvantages in the inpatient setting. RECENT FINDINGS: We review different versions of commercially available eGMS: Glucommander™ (Glytec, Greenville, SC), EndoToolR (MD Scientific LLC, Charlotte, NC), GlucoStabilizer™ (Medical Decision Network, Charlottesville, VA), GlucoCare™ (Pronia Medical Systems, KY), and discuss advantages such as reducing rates of hypoglycemia, hyperglycemia, and glycemic variability. In addition, eCGMs offer a uniform standard of care and may improve workflows across institutions as well reduce barriers. Despite ample literature on intravenous (IV) versions of eGMS, there is little published research on subcutaneous (SQ) insulin guidance. Although use of eGMS requires extensive training and institution-wide adoption, time spent on diabetes management is better facilitated by their use.

Hospital Diabetes Meeting 2020.

Patients with diabetes may experience adverse outcomes related to their glycemic control when hospitalized. Continuous glucose monitoring systems, insulin-dosing software, enhancements to the electronic health record, and other medical technologies are now available to improve hospital care. Because of these developments, new approaches are needed to incorporate evolving treatments into routine care. With the goal of educating healthcare professionals on the most recent practices and research for managing diabetes in the hospital, Diabetes Technology Society hosted the Virtual Hospital Diabetes Meeting on April 24-25, 2020. Because of the coronavirus disease 2019 (COVID-19) pandemic, the meeting was restructured to be held virtually during the national lockdown to ensure the safety of the participants and allow them to remain at their posts treating COVID-19 patients. The meeting focused on (1) inpatient management and perioperative care, (2) diabetic ketoacidosis and hyperglycemic hyperosmolar state, (3) computer-guided insulin dosing, (4) Coronavirus Disease 2019 and diabetes, (5) technology, (6) hypoglycemia, (7) data and cybersecurity, (8) special situations, (9) glucometrics and insulinometrics, and (10) quality and safety. This meeting report contains summaries of each of the ten sessions. A virtual poster session will be presented within two months of the meeting.

How Low Can You Go? Reducing Rates of Hypoglycemia in the Non-critical Care Hospital Setting.

PURPOSE OF REVIEW: The purpose of this review is to discuss strategies to reduce rates of hypoglycemia in the non-critical care setting. RECENT FINDINGS: Strategies to reduce hypoglycemia rates should focus on the most common causes of iatrogenic hypoglycemia. Creating a standardized insulin order set with built-in clinical decision support can help reduce rates of hypoglycemia. Coordination of blood glucose monitoring, meal tray delivery, and insulin administration is an important and challenging task. Protocols and processes should be in place to deal with interruptions in nutrition to minimize risk of hypoglycemia. A glucose management page that has all the pertinent information summarized in one page allows for active surveillance and quick identification of patients who may be at risk of hypoglycemia. Finally, education of prescribers, nurses, food and nutrition services, and patients is important so that every member of the healthcare team can work together to prevent hypoglycemia. By implementing strategies to reduce hypoglycemia, we hope to lower rates of adverse events and improve quality of care while also reducing hospital costs. Future research should focus on the impact of an overall reduction in hypoglycemia to determine whether the expected benefits are achieved.

IMPROVING GLYCEMIC CONTROL SAFELY IN CRITICAL CARE PATIENTS: A COLLABORATIVE SYSTEMS APPROACH IN NINE HOSPITALS.

OBJECTIVE: Safely improve glycemic control in the critical care units of nine hospitals. METHODS: Critical care adult inpatients from nine hospitals with ≥4 point-of-care blood glucose (BG) readings over ≥2 days were targeted by collaborative improvement efforts to reduce hyper- and hypoglycemia. Balanced glucometric goals for each hospital were set targeting improvement from baseline or goals deemed desirable from Society of Hospital Medicine (SHM) benchmarking data. Collaborative interventions included standardized insulin infusion protocols, hypoglycemia prevention bundles, audit and feedback, education, and measure-vention (coupling measurement of patients "off protocol" with concurrent interventions to correct suboptimal care). RESULTS: All sites improved glycemic control. Six reached prespecified levels of improvement of the day-weighted mean BG. The day-weighted mean BG for the cohort decreased by 7.7 mg/dL (95% confidence interval [CI], 7.0 mg/dL to 8.4 mg/dL) to 151.3 mg/dL. Six of nine sites showed improvement in the percent intensive care unit (ICU) days with severe hyperglycemia (any BG >299 mg/dL). ICU severe hyperglycemic days declined from 8.6 to 7.2% for the cohort (relative risk, 0.84; 95% CI, 0.80 to 0.88). Patient days with any BG <70 mg/dL were reduced by 0.4% (95% CI, 0.06% to 0.6%), from 4.5 to 4.1%, for a small but statistically significant reduction in hypoglycemia. Seven of nine sites showed improvement. CONCLUSION: Multihospital improvements in ICU glycemic control, severe hyperglycemia, and hypoglycemia are feasible. Balanced goals for glycemic control and hypoglycemia in the ICU using SHM benchmarks and metrics enhanced successful improvement efforts with good staff acceptance and sustainability. ABBREVIATIONS: BG = blood glucose CMI = case-mix index CY = calendar year DKA = diabetic ketoacidosis EMR = electronic medical record GBMF = Gordon and Betty Moore Foundation ICU = intensive care unit IIP = insulin infusion protocol SHM = Society of z Hospital Medicine.

Impact of a hypoglycemia reduction bundle and a systems approach to inpatient glycemic management.

OBJECTIVE: Uncontrolled hyperglycemia and iatrogenic hypoglycemia represent common and frequently preventable quality and safety issues. We sought to demonstrate the effectiveness of a hypoglycemia reduction bundle, proactive surveillance of glycemic outliers, and an interdisciplinary data-driven approach to glycemic management. POPULATION: all hospitalized adult non-intensive care unit (non-ICU) patients with hyperglycemia and/or a diagnosis of diabetes admitted to our 550-bed academic center across 5 calendar years (CYs). INTERVENTIONS: hypoglycemia reduction bundle targeting most common remediable contributors to iatrogenic hypoglycemia; clinical decision support in standardized order sets and glucose management pages; measure-vention (daily measurement of glycemic outliers with concurrent intervention by the inpatient diabetes team); educational programs. MEASURES AND ANALYSIS: Pearson chi-square value with relative risks (RRs) and 95% confidence intervals (CIs) were calculated to compare glycemic control, hypoglycemia, and hypoglycemia management parameters across the baseline time period (TP1, CY 2009-2010), transitional (TP2, CY 2011-2012), and mature postintervention phase (TP3, CY 2013). Hypoglycemia defined as blood glucose <70 mg/dL, severe hypoglycemia as <40 mg/dL, and severe hyperglycemia >299 mg/dL. RESULTS: A total of 22,990 non-ICU patients, representing 94,900 patient-days of observation were included over the 5-year study. The RR TP3:TP1 for glycemic excursions was reduced significantly: hypoglycemic stay, 0.71 (95% CI, 0.65 to 0.79); severe hypoglycemic stay, 0.44 (95% CI, 0.34 to 0.58); recurrent hypoglycemic day during stay, 0.78 (95% CI, 0.64 to 0.94); severe hypoglycemic day, 0.48 (95% CI, 0.37 to 0.62); severe hyperglycemic day (>299 mg/dL), 0.76 (95% CI, 0.73 to 0.80). CONCLUSION: Hyperglycemia and hypoglycemia event rates were both improved, with the most marked effect on severe hypoglycemic events. Most of these interventions should be portable to other hospitals.

Design and implementation of a web-based reporting and benchmarking center for inpatient glucometrics.

Insulin is a top source of adverse drug events in the hospital, and glycemic control is a focus of improvement efforts across the country. Yet, the majority of hospitals have no data to gauge their performance on glycemic control, hypoglycemia rates, or hypoglycemic management. Current tools to outsource glucometrics reports are limited in availability or function. Society of Hospital Medicine (SHM) faculty designed and implemented a web-based data and reporting center that calculates glucometrics on blood glucose data files securely uploaded by users. Unit labels, care type (critical care, non-critical care), and unit type (eg, medical, surgical, mixed, pediatrics) are defined on upload allowing for robust, flexible reporting. Reports for any date range, care type, unit type, or any combination of units are available on demand for review or downloading into a variety of file formats. Four reports with supporting graphics depict glycemic control, hypoglycemia, and hypoglycemia management by patient day or patient stay. Benchmarking and performance ranking reports are generated periodically for all hospitals in the database. In all, 76 hospitals have uploaded at least 12 months of data for non-critical care areas and 67 sites have uploaded critical care data. Critical care benchmarking reveals wide variability in performance. Some hospitals achieve top quartile performance in both glycemic control and hypoglycemia parameters. This new web-based glucometrics data and reporting tool allows hospitals to track their performance with a flexible reporting system, and provides them with external benchmarking. Tools like this help to establish standardized glucometrics and performance standards.

Best Practices for Interdisciplinary Care Management by Hospital Glycemic Teams: Results of a Society of Hospital Medicine Survey Among 19 U.S. Hospitals.

Objective. The Society for Hospital Medicine (SHM) conducted a survey of U.S. hospital systems to determine how nonphysician providers (NPPs) are utilized in interdisciplinary glucose management teams. Methods. An online survey grouped 50 questions into broad categories related to team functions. Queries addressed strategies that had proven successful, as well as challenges encountered. Fifty surveys were electronically distributed with an invitation to respond. A subset of seven respondents identified as having active glycemic committees that met at least every other month also participated in an in-depth telephone interview conducted by an SHM Glycemic Advisory Panel physician and NPP to obtain further details. The survey and interviews were conducted from May to July 2012. Results. Nineteen hospital/hospital system teams completed the survey (38% response rate). Most of the teams (52%) had existed for 1-5 years and served 90-100% of noncritical care, medical critical care, and surgical units. All of the glycemic control teams were supported by the use of protocols for insulin infusion, basal-bolus subcutaneous insulin orders, and hypoglycemia management. However, > 20% did not have protocols for discontinuation of oral hypoglycemic agents on admission or for transition from intravenous to subcutaneous insulin infusion. About 30% lacked protocols assessing A1C during the admission or providing guidance for insulin pump management. One-third reported that glycemic triggers led to preauthorized consultation or assumption of care for hyperglycemia. Institutional knowledge assessment programs were common for nurses (85%); intermediate for pharmacists, nutritionists, residents, and students (40-45%); and uncommon for fellows (25%) and attending physicians (20%). Many institutions were not monitoring appropriate use of insulin, oral agents, or insulin protocol utilization. Although the majority of teams had a process in place for post-discharge referrals and specific written instructions were provided, only one-fourth were supported with written protocols to standardize medication, education, equipment, and follow-up instructions. Conclusion. Inpatient glycemic control teams with NPPs often function in environments without a full set of measurement, education, standardization, transition, and order tools. Executive hospital leaders, community partners, and the glycemic control teams themselves need to address these deficiencies to optimize team effectiveness.

Saxagliptin: the evidence for its place in the treatment of type 2 diabetes mellitus.

INTRODUCTION: The worldwide prevalence of type 2 diabetes mellitus (T2DM) is high, and the chronically poor metabolic control that can result from T2DM is associated with a high risk for microvascular and macrovascular complications. Because of the progressive pathophysiology of T2DM, oral antidiabetic agents often fail to provide sustained glycemic control, indicating the need for new therapies. Saxagliptin (Onglyza™; Bristol-Myers Squibb Company, Princeton, NJ, USA; AstraZeneca Pharmaceuticals LP, Wilmington, DE, USA) is an oral dipeptidyl peptidase-4 inhibitor, recently approved for the treatment of T2DM. EVIDENCE REVIEW: Saxagliptin significantly improves glycemic control vs placebo, as demonstrated by decreasing glycated hemoglobin, fasting plasma glucose, and postprandial plasma glucose levels when used as monotherapy; in initial combination with metformin; and as add-on therapy with metformin, sulfonylurea (SU), or thiazolidinedione (TZD). Saxagliptin also significantly improves ß-cell function, is weight neutral, has a low risk for hypoglycemia, and has been shown to have cardiovascular safety. PLACE IN THERAPY: The clinical profile for saxagliptin indicates that it is useful as an adjunct to diet and exercise as first-line monotherapy and in combination with metformin; or as add-on treatment for patients who cannot achieve glycemic control with a combination of diet and lifestyle changes and metformin, SU, or TZD.

Pharmacotherapy of hyperglycemia.

Type 2 diabetes mellitus (T2DM) is a chronic, progressive disorder that affects more than 230 million people worldwide and is expected to affect 366 million by 2030. Both the prevalence of T2DM and the cost of its long term complications has driven the focus and emphasis on treatments aimed at reducing hyperglycemia and controlling hypertension and dyslipidemia. In the last 5 years new glucose lowering drugs acting on novel pathways have been developed, licensed and launched. These drugs include the glucagon-like peptide (GLP-1) agonists, exenatide, and dipeptidyl peptidase (DPP-IV) inhibitors such as sitagliptin and saxagliptin. This review describes current approaches to T2DM treatment, focusing on newer agents which tend to be associated with less hypoglycemia and possible weight loss, and addresses the potential roles of novel oral pharmacologic agents in the late-stages of development that might provide new options for the management of this disease.