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

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

Remote Monitoring and Consultation of Inpatient Populations with Diabetes.

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

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

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

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

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