Insulin Order Sets Research Articles

Evaluation of a Standardized Obstetrics Insulin Drip Protocol and Order Set

Objective The prevalence of pregnancies affected by diabetes is increasing, with the Centers for Disease Control and Prevention reporting that 1–2% of pregnant women have type 1 or type 2 diabetes and up to 10% of pregnancies are affected by gestational diabetes as of 2018. Maternal glycemic management is directly related to fetal and neonatal outcomes, and aberrant maternal hyperglycemia has known negative outcomes. Although most of glycemic management centers on outpatient treatment, evidence exists to support the use of intravenous insulin drips during inpatient admissions. This study aimed to evaluate an intravenous insulin protocol specific to the obstetric (OB) population. Research Design and Methods This was a single-center retrospective pre-/post- cohort study of OB patients with diabetes admitted to an academic medical center. Groups were differentiated based on admission date and protocol implementation with a 6-month washout period. Included patients received an intravenous insulin drip around either antenatal corticosteroid administration or during labor and delivery. Those who were within 7 days of receiving a diabetic ketoacidosis diagnosis or who were admitted to an intensive care unit were excluded. Results Fifty-nine patients received 69 distinct insulin drip orders. Twelve drips were included in the group admitted before initiation of the insulin drop protocol (pre-group) and 57 in the group admitted after the protocol went into effect (post-group). Time spent within the goal glucose range while on an insulin drip in the pre-group was 1.63% compared with 39.30% in the post-group (P <0.001). Glucose levels <70 mg/dL was 0.00% in the pre-group compared with 3.23% in the post-group (P = 0.045). There were no differences in severe hypoglycemia (glucose <50 mg/dL), hyperglycemia (glucose >110 mg/dL), or neonatal outcomes. Conclusion Implementation of a nursing-driven, obstetrics-specific intravenous insulin drip protocol significantly improved maternal glycemic management within a goal glucose range of 70–110 mg/dL during antenatal corticosteroid administration and labor and delivery.

The impact of the implementation of computerized insulin order sets for the control of hyperglycemia in hospitalized cardiac patients.

Glycemic control is crucial in managing hospitalized patients with type II diabetes (T2DM), and it presents as a clinical challenge in the cardiac population. Therefore, we aimed to evaluate the impact of computerized insulin order sets in T2DM hospitalized cardiac patients. A quasi-experimental, pre- and post-study design. We included T2DM patients who were hospitalized for at least 3 days. Patients undergoing cardiac surgery were excluded. The primary endpoint was the mean difference in random blood glucose level (BGL) before and after the implementation of insulin order sets. While the secondary endpoints were to compare the median differences in fasting BGLs and the number of hyperglycemic and hypoglycemic episodes during the first 7 days. The study consisted of three phases: pre-implementation, intervention and post-phase. In the intervention phase, insulin order sets were integrated into the electronic prescribing system, and education was provided to the cardiology department. The post-phase included the patient's post-implementations. A total of 194 patients were enrolled during the study period. The mean random BGL was 11.17 mmol/L, 95% CI, 10.6-11.7 in the pre-phase and 9.5 mmol/L, 95% CI, 9-1 -9.9 mmol/L in the post-phase (P < 0.001). The median fasting BGL was 9.2 mmol/L (7.4-11.8, IQR) in the pre-phase and 8.5 mmol/L (6.6-10.3, IQR) in the post-phase (P = 0.027). The number of hypoglycemic episodes was 24 in pre-phase and 33 in post-phase (P = 0.13). The use of computerized insulin order sets was associated with potential improvements in random and fasting glycemic control without increasing the risk of hyperglycemia or hypoglycemia.

1047-P: Evaluating Discharge Prescription Errors and the Clinical Impacts in Patients with Insulin-Treated Diabetes Mellitus in a Community Hospital

Introduction: Transitioning patients with insulin treated diabetes (ITDM) at time of hospital discharge is identified as a source of error in how information for home management is provided that can contribute to significant adverse health outcomes. To address this, we conducted a quality improvement project investigating the safety of current discharge procedures in our hospital and the impact on glycemic control at 3 months and diabetes related readmissions at 3 and 6 months. Methods: We retrospectively analyzed discharge prescription errors in patients with ITDM in a community hospital between January 2020 and December 2021. Errors were defined as being discharged on the wrong form of insulin (pen vs vial), and/or not being provided appropriate insulin administration devices (i.e., pen needles or syringes). Data was collected by reviewing discharge summaries, discharge medication reconciliations and pharmacy records. Results: Among 75 patients with ITDM (62 (82%) T2DM, 12 (16%) T1DM, 1 (1%) ketosis-prone DM), errors were noted in 73 (97%) patients. 46 (63%) were discharged on wrong form of insulin and 67 (91%) were discharged without appropriate insulin administration devices. Among those 73 patients, 19 (26%) patients had an increase in HbA1c at 3 months (8.7 vs 10.03, p=0.001); 5 (25%) and 8 (24%) had 30-day and 90-day diabetes-related hospital readmissions, respectively. In 2 patients with appropriate discharge, there were no 30-day or 90-day hospital readmissions. Conclusion: Prescription errors in patients with ITDM at discharge are common and potentially remediable and lead to hospital readmissions and poor glycemic control. These results demonstrate the need for increased awareness among providers through adoption of standardized discharge insulin order sets in EMR system including the form of insulin, insulin administration devices and supplies as well as for early post-discharge follow up with endocrinology. Disclosure A.N.Keskinkilic: None. M.T.Korytkowski: None. S.Mon: None.

Increasing Frequency of Hemoglobin A1c Measurements in Hospitalized Patients With Diabetes: A Quality Improvement Project Using Lean Six Sigma.

The American Diabetes Association (ADA) recommends measuring A1c in all inpatients with diabetes if not performed in the prior three months. Our objective was to determine the impact of utilizing Lean Six Sigma to increase the frequency of A1c measurements in hospitalized patients. We evaluated inpatients with diabetes mellitus consecutively admitted in a community hospital between January 2016 and June 2021, excluding those who had an A1c in the electronic health record (EHR) in the previous three months. Lean Six Sigma was utilized to define the extent of the problem and devise solutions. The intervention bundle delivered between November 2017 and February 2018 included (1) provider education on the utility of A1c, (2) more rapid turnaround of A1c results, and (3) an EHR glucose-management tab and insulin order set that included A1c. Hospital encounter and patient-level data were extracted from the EHR via bulk query. Frequency of A1c measurement was compared before (January 2016-November 2017) and after the intervention (March 2018-June 2021) using χ2 analysis. Demographics did not differ preintervention versus postintervention (mean age [range]: 70.9 [18-104] years, sex: 52.2% male, race: 57.0% white). A1c measurements significantly increased following implementation of the intervention bundle (61.2% vs 74.5%, P < .001). This level was sustained for more than two years following the initial intervention. Patients seen by the diabetes consult service (40.4% vs 51.7%, P < 0.001) and length of stay (mean: 135 hours vs 149 hours, P < 0.001) both increased postintervention. We demonstrate a novel approach in improving A1c in hospitalized patients. Lean Six Sigma may represent a valuable methodology for community hospitals to improve inpatient diabetes care.

PSUN219 Increasing Frequency of Hemoglobin A1c (Hba1c) Measurements in Hospitalized Patients With Diabetes: A Quality Improvement Project Using Lean Six Sigma

Abstract Background Studies have shown the predictive value of hemoglobin A1c (HbA1c) on inpatient glycemic control, and its value for discharge planning. There is little data on HbA1c testing adherence to American Diabetes Association (ADA) guidelines among inpatient providers, and anecdotal evidence suggests that most inpatient providers do not have a standardized approach to HbA1c measurement. The Lean Six Sigma method is a management system that originated in the automobile industry and has become widely used in healthcare to improve the efficiency of processes. The objective of this study was to determine the impact utilizing Lean Six Sigma methodology to increase frequency of HbA1c measurements among hospitalized patients with a known history of diabetes, in line with ADA guidelines. Methods This was a quality improvement study performed in a 240-bed community hospital, evaluating inpatients (≥16 years) consecutively admitted with a diagnosis of diabetes (ICD-10 code E8-E13 and O24) between January 2016-June 2021. Patients were excluded if they had a HbA1c in the health system electronic health record (EHR) in the prior 3 months. The Lean Six Sigma approach was utilized to define the problem and implement solutions. The intervention bundle delivered between November 2017 and February 2018 included 1) provider and nursing education on the utility of HbA1c in patient care, 2) change in laboratory protocols for more rapid turnaround of HbA1c, 3) modifications to the EHR including a glucose management tab and insulin order set that included HbA1c. Hospital encounter and patient-level data were extracted from the EHR via bulk query. Demographic characteristics were calculated. Frequency of HbA1c lab sent while inpatient was compared pre- (Jan 2016-Nov 2017) and post-intervention (March 2018-June 2021) using chi-square analysis. Results 17,869 patients were included (7,332 pre- and 10,537 post-intervention). Demographics did not differ between pre and post intervention periods (mean age [range]: 78.1 [16-106] years, sex: 52.3% male, race: 52.1% White, 25.1% Black). Only 53.5% of patients who met criteria had a HbA1c measured during hospitalization before intervention. This frequency increased to 70.2% postintervention. The improvement in the frequency of HbA1c measurement was sustained more than two years following the initial interventions and continued to improve over time. Conclusion This novel approach was successful in improving adherence to guideline-based measurement of HbA1c in hospitalized patients. This is the first quality improvement project in a community hospital utilizing the Lean Six Sigma process for this purpose and may represent a valuable methodology for community hospitals to improve inpatient diabetes care. Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m.

Surgical universal euglycemic attainment during recovery (SUGAR) initiative: Sweet results through quality improvement (286)

<b>Objectives:</b> Perioperative hyperglycemia is associated with adverse postoperative outcomes. Lack of standardization leads to inconsistent detection and management of patients with diabetes during the perioperative period. Our objective was to improve perioperative glycemic control among patients with Type II diabetes mellitus undergoing open gynecologic surgery through a quality improvement initiative. <b>Methods:</b> We assembled a multidisciplinary team and implemented standardized screening guidelines, including obtaining a preoperative hemoglobin A1C in all patients before surgery. Algorithms were developed for patients with diabetes, and those at high risk were referred to Endocrinology to optimize glucose control in the preoperative period. We also standardized the intraoperative and postoperative management by increasing the frequency of intraoperative glucose monitoring and developing weight-based postoperative insulin order sets with basal, prandial, and correctional insulin. Outcomes were compared between a baseline (BL) group (February 2015-August 2017) and a post-implementation (PI) group (February 2018-April 2021). Summary statistics were used to describe the clinical and demographic characteristics. BL and PI groups were compared using the Chi-square test, Fisher's exact test, t-test, or Wilcoxon rank-sum test. A linear mixed effect model was constructed based on hours since initial preop measurement, time period measurement took place, and group (BL vs PI). <b>Results:</b> There were 81 patients in the BL group and 119 in the PI group. The BL and PI groups were similar in age, race, and indication for surgery (benign vs malignant). The PI group had lower median BMI (PI 32.7kg/m2 vs BL 35.3mg/m2; p=0.02), higher median Charlson Comorbidity Index (PI 4 vs BL 3; p=0.004), and surgical time (PI 258 minutes vs BL 197 minutes; p=0.009). The rate of obtaining a hemoglobin A1c prior to surgery increased from BL 14.8% to PI 89.0% (p<0.001). The rate of intraoperative glucose monitoring also increased from BL 50.6% to PI 76.5% (p<0.001). The linear mixed-effects model found PI estimated average glucose values decreased by 8.13mg/dL compared to BL levels (p=0.046). The percentage of postoperative glucose values that were at goal (<180mg/ dL) improved from BL 83% to PI 86% (p=0.008). There were no episodes of hypoglycemia or other safety events associated with the postoperative insulin order sets. <b>Conclusions:</b> The SUGAR initiative successfully increased compliance with preoperative screening for diabetes as well as improved perioperative monitoring and management of hyperglycemia. The impact of this initiative on glycemic control is evident not only by the improvement in average glucose values across all time periods but also by the percentage of glucose values that are at goal. This protocol safely improved perioperative glycemic control among patients with diabetes undergoing open gynecologic surgery.

827-P: Pioneering a Novel Inpatient Diabetes Consult Service in the COVID Era

Hospitalized patients often do not reach the ADA-recommended glucose targets, which in turn increases complications, costs, length of stay, and readmission rate. The ADA supports the availability of trained specialists and teams to improve outcomes. Partly in response to the SARS CoV-2 pandemic, we instituted an inpatient “virtual care” initiative by electronic medical record (EMR) review. The ProActive Glucose Advice Team (pGAT) utilizes specialist expertise, automated computerized detection of hyperglycemia, and feedback to the primary service. The pGAT team members consist of an endocrinologist, a nurse diabetes care and education specialist, and a clinical dietician. The team reviewed a computer-generated report of inpatients with either 2 or more blood glucose values ≥180 mg/dl within the last 24 hours, and/or a hemoglobin A1c (A1c) ≥8%. We proposed to enter a brief, structured “pGAT Note” in the EMR, followed by a “gentle reminder” note the next day, including advice for a formal diabetes education and an endocrinology consultation. This proactive approach to the management of hyperglycemia would provide a summary review of the patient’s glucose state, determine the level of patient’s self-care skills, and steps to improve inpatient glycemic control. For preliminary data during the first 4-month phase after implementation of the pGAT initiative, we examined individualized discharge management and timely outpatient follow-up with endocrinology. Of 37 patients (28 males, 9 females; average age 60.4 years), 34 were treated with intensive insulin therapy with multiple daily insulin injections, 31 were seen in f/u within 2 weeks of discharge, and 25 were begun on Continuous Glucose Monitoring. The average A1c fell from an inpatient value of 11.6% to 8.4% measured between 2-4 months later. During the next pGAT phase, we intend to study inpatient therapy parameters, notably appropriate use of computerized insulin order sets, titration of basal insulin, and prandial-correction bolus insulin use. Disclosure A. A. Rizvi: None. A. O. Rich: None. R. Eldridge: None.

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

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. 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. 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%). 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.

Implementation of Glycemic Management to Reduce Surgical Site Infections in Spinal Fusion Patients

<h3>Background</h3> The 2017 Centers for Disease Control and Prevention Guideline for the Prevention of Surgical Site Infection classified the implementation of peri-operative glycemic control as a strong recommendation with high to moderate-quality evidence. We describe implementation and lessons learned of a glycemic management (GM) protocol for spinal fusion (SF) patients. <h3>Methods</h3> A multidisciplinary team was engaged to create a GM protocol. Non-diabetic (ND) SF patients were selected to pilot implementation measures. The protocol was implemented in two stages. Stage 1 consisted of a whole blood glucose (WBG) in the preoperative holding area (PREOP) and a WBG upon arrival in the post-anesthesia care unit (PACU). Stage 2 extended the GM protocol to include WBG every six hours for at least 24 hours after PACU WBG. Non-diabetic insulin order sets were developed for results ≥180 mg/dl. <h3>Results</h3> During Stage 1, 1% of ND SF patients experienced hyperglycemia (defined as ≥140 mg/dl) in PREOP, in contrast 43% were hyperglycemic upon arrival to PACU. During Stage 2, the percentage of ND patients having two consecutive glucose results ≥140 mg/dl or one ≥180 mg/dl decreased steadily. Most SF patients experienced hyperglycemia on postoperative day (POD) 1. Postoperative steroid use was identified as a factor contributing to hyperglycemia. The percentage of hyperglycemic patients increased with increase in total Decadron dose. Elimination of postoperative steroid usage supported GM efforts. Complex SF SSI (deep and organ space) decreased 40% from the same time period in prior year. <h3>Conclusions</h3> Most ND SF patients experienced hyperglycemia on POD 1. Postoperative steroid use was identified as a contributor to hyperglycemia. GM implementation allowed identification and control of hyperglycemia, decreasing the number of complex SF SSI observed.

23-OR: EHR-Based Blood Glucose Alerts Improve Inpatient Glycemic Control at a Large Academic Medical Center

Hospital blood glucose (BG) management is a challenge. We implemented an electronic health record (EHR)-based system at our 1541-bed academic medical center (AMC), alerting when a patient (pt) experiences significant hyperglycemia (hyper; 2 BGs ≥300 mg/dL over 48 hours) or hypoglycemia (hypo; &amp;lt;70 mg/dL). These Excursion Event Alerts (EEAs) fired to the clinician entering orders and provided links to insulin order sets and consult requests. The EEAs were launched on 14 non-ICU wards in mid-2019. We compared BG control during the 3 months prior to launch vs. the most recent 3 months. The control group consisted of 12 non-EEA wards. Our 1° outcome was the Quality Hyperglycemia Score-2 (QHS2), previously developed to assess/compare the overall BG quality on individual wards. QHS2 (scale, 0-100) incorporates 5 elements of BG management, crediting overall control as well as the minimization of significant fluctuations. After the intervention, there was a substantial 13.8% improvement in mean QHS2 (+9.36, p=0.029), comprised of more pt-days in target (+4.3%, p=0.024) and a trend for less pt-days with severe hyper (-2%, p=0.09), with no change in hypoglycemia. In contrast, there was no change in QHS2 on control wards. We conclude that a glycemic alert system was associated with improved BG control at our large AMC, suggesting that a simple EHR-based intervention can favorably impact hospital diabetes management. Disclosure L.B. Bak: None. T.M. Fandel: None. J.E. Bozzo: None. M.L. DeWitt: None. P. Chen: None. R.A. Pando: None. L. Ferro: None. R. Kaplan: None. K.C. Hendrickson: None. S.B. Amport: None. L. Sussman: None. S.E. Inzucchi: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Lexicon Pharmaceuticals, Inc., Novo Nordisk A/S, Sanofi. Consultant; Self; Abbott, Merck &amp; Co., Inc., vTv Therapeutics.

Impact of Structured Insulin Order Sets on Inpatient Hypoglycemia and Glycemic Control

Objective: In hospitalized patients, glycemic excursions outside recommended glycemic targets have been associated with increased morbidity and mortality. Despite recommendations to avoid use of correctional insulin alone for managing hyperglycemia, this approach remains common. We performed a quality improvement project aimed at both reducing hypoglycemic events and promoting increased use of basal insulin by updating our insulin order sets to reflect clinical practice guideline recommendations. Methods: Brooke Army Medical Center correctional insulin order sets were modified to reflect higher treatment thresholds and targets, and a basal insulin order was added with a recommended weight-based starting dose. Pre- and postintervention analyses were performed. Patients were included if they were prescribed subcutaneous insulin during their hospital stay. The following outcomes were measured: (1) glucose levels, and (2) prescriptions for basal insulin. Results: A significant reduction in hypoglycemia events was noted following the intervention (glucose <70 mg/dL: 9.2% pre-intervention vs. 8.8% postintervention; glucose <55 mg/dL: 4.2% pre-intervention vs. 2.2% postintervention). When excluding patients that were ordered correctional insulin alone but did not receive a dose, an increase in basal insulin use was seen (50% pre-intervention vs. 61% postintervention). Rates and severity of hyperglycemia (glucose >180 mg/dL) remained unchanged. Conclusion: The alteration in insulin order set parameters resulted in a significant reduction in hypoglycemia without significant increases in hyperglycemia. Although basal insulin use increased, optimal dosing recommendations were not often utilized. Further interventions are necessary to reduce hyperglycemia. Abbreviations: CPOE = computerized provider order entry; EMR = electronic medical record; HbA1c = hemoglobin A1c; LOS = length of stay; QI = quality improvement; SSI = sliding scale insulin.

2260-PUB: Inpatient Diabetes Patient Brochure: What You Need to Know while You Are in the Hospital

Hospitalized patients with diabetes, whether previously on insulin or not, are generally treated with insulin. This change from outpatient medication, the type of insulin, and insulin regimen may be significantly different from what the patient is familiar with and may result in confusion, discomfort or even confrontation about the treatment plan. To ease the transition from outpatient to inpatient, we developed a “Brochure for Patients with Diabetes: What you need to know while you are in the hospital” to help make the patient feel more comfortable about the glycemic care they receive and improve patient satisfaction. The specific items covered in the brochure are: 1) Why the management of your diabetes may be quite different from what you usually do at home; 2) Goals for blood sugars (why different from home: fighting infections, avoiding hypoglycemia); 3) How we manage your blood sugar levels; 4) Blood sugar checks (how often); 5) Diet (restrictions, meals on demand); 6) Discharge planning; 7) Common questions such as use of own meter, reasons for different insulins, pumps, and CGM. The brochure is printed for the patient with the first time any insulin order set is ordered. The brochure is available in Spanish, Chinese and Russian. Evaluation: We audited brochure distribution to determine percentage of patients who received the brochure and developed a survey to determine the patient’s understanding of the brochure. Results: Audit results: After upgrades to the order sets so brochure would be printed, 100% of 50 charts had printed brochures. The survey: was hand delivered to 40 consecutive patients on insulin. 32 of the patients had ≧90% correct responses. The remaining 8 averaged 60% correct response. Conclusion: We successfully produced a brochure that explains inpatient diabetes management to newly admitted patients. Whether the patients who had decreased understanding may have been too ill to completely understand the brochure and possible changes in patient satisfaction remain to be explored. Disclosure R.J. Rushakoff: None. H.W. MacMaster: None.

2380-PUB: Factors Associated with Successful Implementation of an Inpatient Glycemic Management Program to Improve Glucose Control for Patients Needing Subcutaneous Insulin

Deployment and maturation of computerized medical records has improved insight into the unintended variability of glucose management in hyperglycemic inpatients. We used expert panels and extensive field testing to design a Glycemic Management Program to simultaneously reduce mean glucose levels and the frequency of hypoglycemic events. Factors observed as contributing to glucose control variation included over-use of sliding scale insulin; inconsistencies in timing, type and dose of insulin; and the alignment of blood glucose testing with meal tray delivery. We designed our Glycemic Management Program to address these factors with four distinct components: 1) Change management via targeted education; 2) Standardization of the ordering process for nutrition, blood glucose monitoring frequency, and a single subcutaneous insulin order set with decision support; 3) Standardization of workflow, including the timing and coordination of glucose testing and meal tray delivery; and 4) Patient specific, customized ongoing insulin dosing recommendations through FDA-approved decision support software. We implemented our Glycemic Management Program pilot in a 325 bed community hospital in the southeastern United States. Since its launch, 2277 patients have been managed on the program. By six months post-implementation, the rate of severe hypoglycemia (&amp;lt;54mg/dL) decreased 32.2% and basal-bolus insulin usage increased 135%. Average daily glucose values decreased without increasing the rate of hypoglycemia. Decreases were observed in overall length of stay (79%), complication rate (25.3%) and ICU length of stay (60%). A comprehensive program that incorporates decision support with attention to workflow, provider engagement, and education can result in improved glucose management in an inpatient setting. Feedback has led to programmatic changes to maximize positive outcomes and ensure sustainability. Disclosure R. Freeman: None. W.E. Gay: None. T.L. Garthwaite: Advisory Panel; Self; Ondine Biomedical. L. Hollis: None. J. McCannon (Bush): None. C. Spencer-Smith: None. E.E. Samuelson: None. P. Mehta: None.

Surgical Universal euGlycemic Attainment during Recovery (SUGAR) Initiative.

252 Background: Surgical site infections (SSI) are infections of the surgical incision or organ space within 30 days of surgery and are associated with increased morbidity, mortality and healthcare expenditures. Diabetic patients undergoing laparotomy are at high risk. Prior studies have shown SSI reduction by avoiding hyperglycemia. The aim of our Quality Improvement (QI) initiative is to reduce the SSI rate among diabetic patients undergoing laparotomy by 40% within 2 years compared to the baseline (2/2015-8/2017) rate of 16%. Methods: We formed a multi-disciplinary QI team including physicians, nurses and advanced care providers from Gynecologic Oncology, Pharmacy, Nutrition, Endocrinology, Internal Medicine and Anesthesiology. The intervention began 2/2018 in our main center and 5 satellite sites including: screening gynecologic cancer patients undergoing laparotomy with hemoglobin A1C, intra-operative glucose monitoring with goal of &lt; 180mg/dL, creation and use of a standardized basal-bolus insulin order set for post-operative care, and endocrine and nutritional consultation. The following variables were assessed: age, race, ethnicity, BMI, cancer type, comorbidities, smoking status, surgical procedure, receipt of antibiotic prophylaxis, hemoglobin A1C, post-operative glucose values, intervention compliance, intra-operative complications, post-operative complications including SSI, hospital readmissions, reoperation and mortality. Results: Since 2/2018, 39 gynecologic cancer patients have undergone laparotomy. Overall compliance with HgA1c screening is 64% (25/39), which has improved from 42% in 2/2018 to 70% in 3/2018 and 83% in 4/2018. Causes of non-compliance included unplanned conversion to laparotomy and need for additional education. Five of 39 (13%) patients were diabetic, including one newly diagnosed through this initiative. The post-intervention diabetic SSI rate is 0% (0/5) with all post-intervention glucose values &lt; 180mg/dL. There have been no safety adverse events resulting in patient harm. Conclusions: Implementing a QI initiative to standardize management of diabetic patients undergoing surgery is both safe and feasible. Effectiveness data will continue to be collected.

Implementation of a Standardized Admission Hyperglycemia Insulin Order Set in a Veterans Hospital

Implementation of a Standardized Admission Hyperglycemia Insulin Order Set in a Veterans Hospital

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.

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. 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. 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. 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.

Improving Insulin Administration Through Redesigning Processes of Care: A Multidisciplinary Team Approach.

This article describes a quality improvement project using a multidisciplinary team approach to improve the rate of errors of omission of preprandial subcutaneous coverage insulin orders. A Diabetic Management Work Group was created to evaluate the system processes that affect success and failure of timely administration and documentation of preprandial coverage insulin, commonly referred to as sliding scale coverage. Data before and after the project were collected to evaluate the effectiveness of a process change through the bar code medication administration system, in which preprandial coverage insulin order sets were changed to eliminate errors of omission and improve documentation. A review of 833 random blood glucose measurements with corresponding short- or rapid-acting insulin coverage orders was conducted. A mean error of omission rate of 23.4% was identified with respect to coverage insulin that was clinically indicated by provider-ordered insulin set but not administered or documented in the electronic medication record. After process redesign and implementation, 951 blood glucose measurements with corresponding insulin coverage orders were randomly reviewed, and a mean of 10.7% of omission rate for coverage insulin administration was identified. This represented a decrease in omission of coverage insulin by 54% compared with preprocess improvement. Decreased errors of omission as well as improved administration and documentation of coverage insulin were demonstrated by this multimodal process change. Scheduled standardized order sets, extensive nursing staff education, and enhanced efficiency of the existing process led to improved outcomes.

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

The purpose of this review is to discuss strategies to reduce rates of hypoglycemia in the non-critical care setting. 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.

Remote Monitoring and Consultation of Inpatient Populations with Diabetes

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. 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 225mg/dl and/or a glucose <70mg/dl in the past 24h, 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.

Computerized Insulin Order Sets and Glycemic Control in Hospitalized Patients

BackgroundThe purpose of this study was to evaluate the impact of computerized provider order entry subcutaneous insulin order sets on inpatient glycemic control and ordering behavior. MethodsThis was an interrupted time series study of non-intensive care patients at an urban teaching hospital. The primary outcome was proportion of capillary blood glucose in optimal range (4.0-10.0 mmol/L [72-180 mg/dL]) during the 6 months before and after a change to a computerized provider order entry-integrated insulin order set. Secondary outcomes included other measures of glycemia (hyperglycemia [>13.9mmol/L (250 mg/dL)], hypoglycemia [<4.0 mmol/L (72 mg/dL)], severe hypoglycemia [<2.2 mmol/L (40 mg/dL)]) and ordering behavior (use of basal-bolus-correctional insulin regimens). Comparisons of sensitivity-based versus generic correctional scale were also conducted. ResultsA total of 63,393 measurements were obtained from June 2011 to June 2012. Order set usage was limited (51.5%). The weekly proportion of capillary blood glucose within the optimal range was not significantly different after the switch to computerized provider order entry order sets (pre-period: 64.9% vs post-period: 65.3%, P = .996). There were no differences in the proportions of moderate or severe hyperglycemia (pre-period: 10.9% vs post-period: 12.0%, P = .061) and hypoglycemia (pre-period: 1.9% vs post-period: 1.6%, P = .144). However, an increased proportion within the optimal range was seen in those with an order set featuring a sensitivity-based correctional scale versus orders without (65.3% vs 55.0%, P <.001). Increased basal-bolus-correctional ordering was observed after protocol implementation (20.3% vs 23.6%, P <.0001). ConclusionsWith low institutional uptake, computerized insulin order sets did not improve inpatient glycemic control.