130 Impact of Low-Dose High-Frequency in situ Simulation on Inpatient Diabetes Management: A Pilot Study

Even in the presence of established institutional guidelines, failure of compliance by the clinical teams plays an important role in the control of diabetes. The identified gaps include contextual and biomedical knowledge, attitudes, clinical inertia, confidence and familiarity with existing hospital resources and guidelines with regards to hospital diabetes care We wanted to demonstrate the efficacy of low-dose high-frequency The exercise was a 15-minute session, delivered during working hours to individual nurses. This consisted of a 5-minute scenario, involving a standardized patient followed by a 10-minute debrief. Modified Diamond-model debrief with an advocacy-inquiry model was used by the debriefer, a trained fellow in simulation, and overseen by an expert. The scripted scenario involved a patient with Diabetic Ketoacidosis (DKA), with learning outcomes of recognizing DKA, managing the patient and adhering to the institutional guidelines including management of hypoglycaemia. The scenario was individualized based on the roles of the participants. Pre- and post-questionnaires were given to the participants. The simulation was repeated twice in the second week and once in the third week.This mixed-method study was conducted in a UK teaching hospital, in a ward designated for patients with diabetes, as a part of a quality improvement programme. In the first week, patients with diabetes, admitted for DKA, were chosen and their blood sugar recordings, dysglycaemic episodes and adherence to guidelines were noted. Every week data were collected as in the first week. GNU pspp 1.0.1 [version 3] free software was used. The confidence scores were given as mean and standard deviation with confidence interval (CI) of 98.75%. A p-value of <0.0125 was considered significant based on the number of data points.The Dysglycemic episodes and protocol adherence from medical recordsConsidering the T2 (increased recognition of diabetic emergencies and adherence to protocol) and T3 (improved patient outcomes) outcomes, the methodology was recommended as a modality of training the nursing staff involved in inpatient care of patients with diabetes. Future programmes including multi-disciplinary teams, to explore teamwork and communication, are planned.

Practical implementation of remote continuous glucose monitoring in hospitalized patients with diabetes

Disclaimer In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose Inpatient diabetes management involves frequent assessment of glucose levels for treatment decisions. Here we describe a program for inpatient real-time continuous glucose monitoring (rtCGM) at a community hospital and the accuracy of rtCGM-based glucose estimates. Methods Adult inpatients with preexisting diabetes managed with intensive insulin therapy and a diagnosis of coronavirus disease 2019 (COVID-19) were monitored via rtCGM for safety. An rtCGM system transmitted glucose concentration and trending information at 5-minute intervals to nearby smartphones, which relayed the data to a centralized monitoring station. Hypoglycemia alerts were triggered by rtCGM values of ≤85 mg/dL, but rtCGM data were otherwise not used in management decisions; insulin dosing adjustments were based on blood glucose values measured via blood sampling. Accuracy was evaluated retrospectively by comparing rtCGM values to contemporaneous point-of-care (POC) blood glucose values. Results A total of 238 pairs of rtCGM and POC data points from 10 patients showed an overall mean absolute relative difference (MARD) of 10.3%. Clarke error grid analysis showed 99.2% of points in the clinically acceptable range, and surveillance error grid analysis showed 89.1% of points in the lowest risk category. It was determined that for 25% of the rtCGM values, discordances in rtCGM and POC values would likely have resulted in different insulin doses. Insulin dose recommendations based on rtCGM values differed by 1 to 3 units from POC-based recommendations. Conclusion rtCGM for inpatient diabetes monitoring is feasible. Evaluation of individual rtCGM-POC paired values suggested that using rtCGM data for management decisions poses minimal risks to patients. Further studies to establish the safety and cost implications of using rtCGM data for inpatient diabetes management decisions are warranted.

The Endocrine Hospitalist: Enhancing the Quality of Diabetes Care

The endocrine hospitalist and inpatient diabetes management team increases access to endocrinology consultations and improves glycemic control and quality metrics such as length of stay and hospital readmission. Enhanced glycemic care is needed in both academic and community hospital settings. Endocrine fellowship programs should implement endocrine hospitalist rotations with emphasis on training endocrine fellows to deliver fast-paced inpatient endocrine care. Entrepreneurship, innovation, and a “start-up” culture within the field of Endocrinology should be encouraged and supported by healthcare systems.

Effects of a Dedicated Inpatient Diabetes Management Service on Glycemic Control in a Community Hospital Setting

Background: Community hospitals account for over 84% of all hospitals and over 94% of hospital admissions in the United States. In academic settings, implementation of an Inpatient Diabetes Management Service (IDMS) model of care has been shown to reduce rates of hyper- and hypoglycemia, hospital length of stay (LOS), and associated hospital costs. However, few studies to date have evaluated the implementation of a dedicated IDMS in a community hospital setting. Methods: This retrospective study examined the effects of changing the model of inpatient diabetes consultations from a local, private endocrine practice to a full-time endocrine hospitalist on glycemic control, LOS, and 30-day readmission rates in a 267-bed community hospital. Results: Overall diabetes patient days for the hospital were similar pre- and post-intervention (20,191 vs 20,262); however, the volume of patients seen by IDMS increased significantly after changing models. Rates of hyperglycemia decreased both among patients seen by IDMS (53.8% to 42.5%, P < .0001) and those not consulted on by IDMS (33.2% to 29.9%; P < .0001). When examined over time, rates of hypoglycemia steadily decreased in the 24 months after dedicated IDMS initiation ( P = .02); no such time effect was seen prior to IDMS ( P = .34). LOS and 30DRR were not significantly different between IDMS models. Conclusions: Implementation of an endocrine hospitalist-based IDMS at a community hospital was associated with significantly decreased hyperglycemia, while avoiding concurrent increases in hypoglycemia. Further studies are needed to investigate whether these effects are associated with improvements in clinical outcomes, patient or staff satisfaction scores, or total cost of care.

Electronic Diabetes Management System Replaces Paper Insulin Chart: Improved Quality in Diabetes Inpatient Care Processes Due to Digitalization

Background: GlucoTab, an electronic diabetes management system (eDMS), supports healthcare professionals (HCPs) in inpatient blood glucose (BG) management at point-of-care and was implemented for the first time under routine conditions in a regional hospital to replace the paper insulin chart. Method: To investigate quality of the eDMS for inpatients with type 2 diabetes mellitus a monocentric retrospective before-after evaluation was conducted. We compared documentation possibilities by assessing a blank paper chart vs the eDMS user interface. Further quality aspects were compared by assessing filled-in paper charts ( n = 106) vs filled-in eDMS documentation ( n = 241). HCPs ( n = 59) were interviewed regarding eDMS satisfaction. Results: The eDMS represented an improvement of documentation possibilities by offering a more structured and comprehensive user interface compared to the blank paper chart. The number of good diabetes days averaged to a median value of four days in both groups (paper chart: 4.38 [0-7] vs eDMS: 4.38 [0-7] days). Median daily BG was 170 (117-297) mg/dL vs 168 (86-286) mg/dL and median fasting BG was 152 (95-285) mg/dL vs 145 (69-333) mg/dL, and 0.1% vs 0.4% BG values <54 mg/dL were documented. Diabetes documentation quality improved when using eDMS, for example, documentation of ordered BG measurement frequency (1% vs 100%) and ordered BG targets (0% vs 100%). HCPs stated that by using eDMS errors could be prevented (74%), and digital support of work processes was completed (77%). Time saving was noted by 8 out of 11 HCPs and estimated at 10-15 minutes per patient day by two HCPs. Conclusions: The eDMS completely replaced the paper chart, showed comparable glycemic control, was positively accepted by HCPs, and is suitable for inpatient diabetes management.