Basal-bolus insulin protocols enter the computer age

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.

InsulinAPP application protocol for the inpatient management of type 2 diabetes on a hospitalist-managed ward: a retrospective study

Introduction

We assessed metrics related to inpatient glycemic control using InsulinAPP, an application available for free in Brazil, on the hospitalist-managed ward of our hospital.

Subjects and methods

We performed a retrospective study of patients with type 2 diabetes (T2D) admitted from November 2018 to October 2019. InsulinAPP recommends NPH and regular insulins three times a day, in bolus-correction or basal-bolus schemes. Parameters that included BG within range of 70-180 mg/dL, insulin treatment regimen and frequency of hypoglycemia were evaluated.

Results

A total of 147 T2D individuals (23% medicine and 77% surgery) were included (mean age 62.3 ± 12.7 years, HbA1c: 8.3 ± 3.0%). The initial insulin regimen was 50% bolus-correction, 47% basal-bolus and 3% with sliding scale insulin. During hospitalization, 71% patients required a bolus-basal regimen. In the first 10 days of the protocol, 71% BG measurements were between 70-180 mg/dL and 26% patients experienced one or more episodes of hypoglycemia < 70 mg/dL, and 5% with BG < 54 mg/dL.

Conclusion

The results of this retrospective study indicate the InsulinAPP application using human insulin formulations was effective and safe for the management of hyperglycemia on a hospitalist-managed ward, with more than 70% BG measurements within the therapeutic range and a low rate of hypoglycemia.

Qualitative Evaluation of the Barriers and Facilitators Influencing the Use of an Electronic Basal Bolus Insulin Therapy Protocol to Improve the Care of Adult Inpatients With Diabetes

OBJECTIVES

A qualitative evaluation of the perceived impact of a new evidence-informed electronic basal bolus insulin therapy order set on clinical workflow and practice, and exploration of potential barriers and facilitators to electronic basal bolus insulin order set uptake and use in acute care facilities for various acute care team members.

METHODS

We conducted 9 semistructured focus groups with multidisciplinary nursing staff (n=22), resident trainees (n=24) and attending physicians (n=23) involved in the delivery of inpatient diabetes care at 3 adult acute care facilities. The domains of inquiry included impact on workload, perceived impact on patient care and discipline-specific barriers and facilitators to use, including care-providers' needs, comfort and competencies, contributions from the clinical environment and efficacy of communication. The interviews were transcribed and analyzed using a content analysis approach.

RESULTS

Several major themes emerged from the focus group discussions, including impact of education, information technology/user interface, workflow, organizational issues and practices, and perceived outcomes. Barriers and facilitators were identified relating to each theme.

CONCLUSIONS

The outcomes highlight the complex interplay between educational, organizational and technical themes and the significance of employing a systemic approach to support the implementation of electronic inpatient glycemic-management protocols within complex social organizations.

Knowledge Translation to Optimize Adult Inpatient Glycemic Management With Basal Bolus Insulin Therapy and Improve Patient Outcomes

OBJECTIVES

To develop and evaluate a Basal Bolus Insulin Therapy (BBIT) Knowledge Translation toolkit to address barriers to adoption of established best practice with BBIT in the care of adult inpatients.

METHODS

This study was conducted in 2 phases and focused on the hospitalist provider group across 4 acute care facilities in Calgary. Phase 1 involved a qualitative evaluation of provider and site specific barriers and facilitators, which were mapped to validated interventions using behaviour change theory. This informed the co-development and optimization of the BBIT Knowledge Translation toolkit, with each tool targeting a specific barrier to improved diabetes care practice, including BBIT ordering. In Phase 2, the BBIT Knowledge Translation toolkit was implemented and evaluated, focusing on BBIT ordering frequency, as well as secondary outcomes of hyperglycemia (patient-days with BG >14.0 mmol/L), hypoglycemia (patient-days with BG <4.0 mmol/L), and acute length of stay.

RESULTS

Implementation of the BBIT Knowledge Translation toolkit resulted in a significant 13% absolute increase in BBIT ordering. Hyperglycemic patient-days were significantly reduced, with no increase in hypoglycemia. There was a significant, absolute 14% reduction in length of stay.

CONCLUSIONS

The implementation of an evidence-informed, multifaceted BBIT Knowledge Translation toolkit effectively reduced a deeply entrenched in-patient diabetes care gap. The resulting sustained practice change improved patient clinical and system resource utilization outcomes. This systemic approach to implementation will guide further scale and spread of glycemic optimization initiatives.

A Mobile Computerized Decision Support System to Prevent Hypoglycemia in Hospitalized Patients With Type 2 Diabetes Mellitus

BACKGROUND

Diabetes management requires complex and interdisciplinary cooperation of health care professionals (HCPs). To support this complex process, IT-support is recommended by clinical guidelines. The aim of this article is to report on results from a clinical feasibility study testing the prototype of a mobile, tablet-based client-server system for computerized decision and workflow support (GlucoTab®) and to discuss its impact on hypoglycemia prevention.

METHODS

The system was tested in a monocentric, open, noncontrolled intervention study in 30 patients with type 2 diabetes mellitus (T2DM). The system supports HCPs in performing a basal-bolus insulin therapy. Diabetes therapy, adverse events, software errors and user feedback were documented. Safety, efficacy and user acceptance of the system were investigated.

RESULTS

Only 1.3% of blood glucose (BG) measurements were <70 mg/dl and only 2.6% were >300 mg/dl. The availability of the system (97.3%) and the rate of treatment activities documented with the system (>93.5%) were high. Only few suggestions from the system were overruled by the users (>95.7% adherence). Evaluation of the 3 anonymous questionnaires showed that confidence in the system increased over time. The majority of users believed that treatment errors could be prevented by using this system.

CONCLUSIONS

Data from our feasibility study show a significant reduction of hypoglycemia by implementing a computerized system for workflow and decision support for diabetes management, compared to a paper-based process. The system was well accepted by HCPs, which is shown in the user acceptance analysis and that users adhered to the insulin dose suggestions made by the system.

USE OF A COMPUTER-GUIDED GLUCOSE MANAGEMENT SYSTEM TO IMPROVE GLYCEMIC CONTROL AND ADDRESS NATIONAL QUALITY MEASURES: A 7-YEAR, RETROSPECTIVE OBSERVATIONAL STUDY AT A TERTIARY CARE TEACHING HOSPITAL

OBJECTIVE

Inpatient hyperglycemia, hypoglycemia, and glucose variability are associated with increased mortality. The use of an electronic glucose management system (eGMS) to guide intravenous (IV) insulin infusion has been found to significantly improve blood glucose (BG) control. This retrospective observational study evaluated the 7-year (January 2009-December 2015) impact of the EndoTool^® eGMS in intensive and intermediate units at Vidant Medical Center, a 900-bed tertiary teaching hospital.

METHODS

Patients assigned to eGMS had indications for IV insulin infusion, including uncontrolled diabetes, stress hyperglycemia, and/or postoperative BG levels >140 mg/dL. This study evaluated time required to achieve BG control (<180 mg/dL; <140 mg/dL for cardiovascular surgery patients); hypoglycemia incidence (<70 and <40 mg/dL); glucose variability (assessed by SD and coefficient of variation percentage [CV%]); excursions (BG levels >180 mg/dL after control attained); and the impact of eGMS on hospital-acquired condition (HAC)-8 rates.

RESULTS

Data were available for all treated patients (492,078 BG readings from 16,850 patients). With eGMS, BG levels were brought to target within 1.5 to 2.3 hours (4.5 to 4.8 hours for cardiovascular patients). Minimal hypoglycemia was observed (BG values <70 mg/dL, 0.93%; <40 mg/dL, 0.03%), and analysis of variance of BG values <70 mg/dL showed significant reductions over time in hypoglycemia frequency, from 1.04% in 2009 to 0.46% in 2015 (P<.0001). The CV% per patient visit was 26.5 (±12.9)%, and 4% of patients experienced glucose excursions (defined as BG levels >180 mg/dL once control was attained). HAC-8 rates were reduced from 0.083 per 1,000 patients (2008) to 0.032 per 1,000 patients (2011).

CONCLUSION

The use of eGMS resulted in rapid, effective control of inpatient BG levels, including significantly reduced hypoglycemia rates.

ABBREVIATIONS

BG = blood glucose CMS = Centers for Medicare and Medicaid Services CV = coefficient of variation CV% = coefficient of variation percentage eGMS = electronic glucose management system GV = glycemic variability HAC = Hospital-Acquired Condition ICU = intensive care unit IU = intermediate unit IV = intravenous LOS = length of stay VMC = Vidant Medical Center.

Reduction of Insulin Related Preventable Severe Hypoglycemic Events in Hospitalized Children

OBJECTIVE

Insulin is a commonly used, high-risk medication in the inpatient setting. Incorrect insulin administration can lead to preventable hypoglycemic events, which are a significant morbidity in inpatient diabetes care. The goal of this intervention was to decrease preventable insulin-related hypoglycemic events in an inpatient setting in a tertiary care pediatric hospital.

METHODS

Methods included the institution of several interventions such as nursing and physician education, electronic medical record order sets, electronic communication note templates, and the development of new care guidelines.

RESULTS

After the institution of multiple interventions, the rate of preventable hypoglycemic events decreased from 1.4 preventable events per 100 insulin days to 0.4 preventable events per 100 insulin days.

CONCLUSIONS

Through the use of a multi-interventional approach with oversight of a multidisciplinary insulin safety committee, a sustained decreased rate of severe preventable hypoglycemic events in hospitalized pediatric patients receiving insulin was achieved.

Sliding Scale Insulin vs Basal-Bolus Insulin Therapy in Long-Term Care: A 21-Day Randomized Controlled Trial Comparing Efficacy, Safety and Feasibility

INTRODUCTION

Sliding scale insulin (SSI) therapy remains a common means of insulin therapy in long-term care (LTC) for the management of type 2 diabetes mellitus, despite current recommendations not supportive of the form of therapy today. Lack of randomized trial data on the efficacy and safety of basal-bolus insulin (B-BI) therapy in nursing home residents may have precluded this form of insulin administration in the LTC setting. Our study is a comparison of the efficacy of SSI (control) and B-BI (intervention) therapies during a 21-day intervention trial in older nursing home residents.

METHODS

Fourteen LTC facilities in the US participated; 110 residents with type 2 diabetes volunteered to participate; 35 failed inclusion criteria, 75 signed informed written consent, and 11 were discharged to home/hospital or withdrew consent; data from 64 participants are reported. Recent fasting blood glucose (FBG), hemoglobin A1c, and chemistries were obtained. Four glucose readings (prior to breakfast, lunch, dinner, and bedtime), oral antiglycemic drug, and insulin doses and changes, and all adverse events/serious adverse events, both those related to glucose control [hypoglycemic (<70 mg/dL) and hyperglycemic (>200 mg/dL) episodes] and those unrelated, were recorded daily. Patients were randomized to either remain on SSI or be shifted to the B-BI group.

RESULTS

Nursing home residents 80 ± 8 (standard deviation) years, 66% female participated; Control and Intervention participants had similar age, gender, race distributions, comorbidity, and 3-day average pretrial FBG levels (all P > .05). At study end, B-BI volunteers had significantly lower 3-day average FBG levels vs pretrial (P = .0231) while SSI participants had no change in 3-day average FBG (P > .05). During the trial, participants from both groups had similar rates of hypoglycemia, hyperglycemia, other adverse events, and hospitalizations (serious adverse events) unrelated to glucose control (all P > .05).

CONCLUSIONS

B-BI therapy produced significantly lower average FBG levels after 21 days compared with SSI therapy; both groups had similar rates of hypo- and hyperglycemia. Switching to B-BI therapy is feasible, safe, and effective in the LTC setting.

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.

Glucose control in non-critically ill inpatients with diabetes: towards closed-loop

Inpatient glycaemic control remains an important issue due to the increasing number of patients with diabetes admitted to hospital. Morbidity and mortality in hospital are associated with poor glucose control, and cost of hospitalization is higher compared to non-diabetes patients. Guidelines for inpatient glycaemic control in the non-critical care setting have been published. Current recommendations include basal-bolus insulin therapy, regular glucose monitoring, as well as enhancing healthcare provider's role and knowledge. In spite of growing focus, implementation in practice is limited, mainly due to increasing workload burden on staff and fear of hypoglycaemia. Advances in healthcare technology may contribute to an improvement of inpatient diabetes care. Integration of glucose measurements with healthcare records and computerized glycaemic control protocols are currently being used in some institutions. Recent interests in continuous glucose monitoring have led to studies assessing its utilization in inpatients. Automation of glucose monitoring and insulin delivery may provide a safe and efficacious tool for hospital staff to manage inpatient hyperglycaemia, whilst reducing staff workload. This review summarizes the evidence on current approaches to managing inpatient glycaemic control; its utility and limitations. We conclude by discussing the evidence from feasibility studies to date, on the potential use of closed loop in the non-critical care setting and its implication for future studies.

Discovery of an intravenous hepatoselective glucokinase activator for the treatment of inpatient hyperglycemia

Glucokinase (hexokinase IV) continues to be a compelling target for the treatment of type 2 diabetes given the wealth of supporting human genetics data and numerous reports of robust clinical glucose lowering in patients treated with small molecule allosteric activators. Recent work has demonstrated the ability of hepatoselective activators to deliver glucose lowering efficacy with minimal risk of hypoglycemia. While orally administered agents require a considerable degree of passive permeability to promote suitable exposures, there is no such restriction on intravenously delivered drugs. Therefore, minimization of membrane diffusion in the context of an intravenously agent should ensure optimal hepatic targeting and therapeutic index. This work details the identification a hepatoselective GKA exhibiting the aforementioned properties.