Brian Clay

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. METHODS 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.

Indication-Based Ordering: A New Paradigm for Glycemic Control in Hospitalized Inpatients

Background: Inpatient glycemic control is a constant challenge. Institutional insulin management protocols and structured order sets are commonly advocated but poorly studied. Effective and validated methods to integrate algorithmic protocol guidance into the insulin ordering process are needed. Methods: We introduced a basic structured set of computerized insulin orders (Version 1), and later introduced a paper insulin management protocol, to assist users with the order set. Metrics were devised to assess the impact of the protocol on insulin use, glycemic control, and hypoglycemia using pharmacy data and point of care glucose tests. When incremental improvement was seen (as described in the results), Version 2 of the insulin orders was created to further streamline the process. Results: The percentage of regimens containing basal insulin improved with Version 1. The percentage of patient days with hypoglycemia improved from 3.68% at baseline to 2.59% with Version 1 plus the paper insulin management protocol, representing a relative risk for hypoglycemic day of 0.70 [confidence interval (CI) 0.62, 0.80]. The relative risk of an uncontrolled (mean glucose over 180 mg/dl) patient stay was reduced to 0.84 (CI 0.77, 0.91) with Version 1 and was reduced further to 0.73 (CI 0.66, 0.81) with the paper protocol. Version 2 used clinician-entered patient parameters to guide protocol-based insulin ordering and simultaneously improved the flexibility and ease of ordering over Version 1. Conclusion: Patient parameter and protocol-based clinical decision support, added to computerized provider order entry, has a track record of improving glycemic control indices. This justifies the incorporation of these algorithms into online order management.

Integrated precision medicine: the role of electronic health records in delivering personalized treatment

Precision Medicine involves the delivery of a targeted, personalized treatment for a given patient. By harnessing the power of electronic health records (EHRs), we are increasingly able to practice precision medicine to improve patient outcomes. In this article, we introduce the scientific community at large to important building blocks for personalized treatment, such as terminology standards that are the foundation of the EHR and allow for exchange of health information across systems. We briefly review different types of clinical decision support (CDS) and present the current state of CDS, which is already improving the care patients receive with genetic profile‐based tailored recommendations regarding diagnostic and treatment plans. We also report on limitations of current systems, which are slowly beginning to integrate new genomic data into patient records but still present many challenges. Finally, we discuss future directions and how the EHR can evolve to increase the capacity of the healthcare system in delivering Precision Medicine at the point of care. WIREs Syst Biol Med 2017, 9:e1378. doi: 10.1002/wsbm.1378

Transfusing Wisely: Clinical Decision Support Improves Blood Transfusion Practices

BACKGROUND The cost and risks of red blood cell (RBC) transfusions, along with evidence of overuse, suggest that improving transfusion practices is a key opportunity for health systems to improve both the quality and value of patient care. Previous work, which included a BestPractice Advisory (BPA), was adapted in a quality improvement project designed to reduce both exposure to unnecessary blood products and costs. METHODS A prospective, pre-post study was conducted at an academic medical center with a diverse patient population. All noninfant inpatients without gastrointestinal bleeding who were not within 12 hours of surgical procedures were included. The interventions were education, a BPA, and other enhancements to the computerized provider order entry system. RESULTS The percentage of multiunit (≥ 2 units) RBC transfusions decreased from 59.9% to 41.7% during the intervention period and to 19.7% postintervention (p < 0.0001). The percentage of inpatient RBC transfusion units administered for hemoglobin (Hb) ≥ 7 g/dL declined from 72.3% to 57.8% during the intervention period and to 38.0% for the postintervention period (p < 0.0001). The overall rate of inpatient RBC transfusion (units administered per 1,000 patient-days without exclusions) decreased from 89.8 to 78.1 during the intervention period and to 72.7 during the postintervention period (p <0.0001). The estimated annual cost savings was

Using an online quiz-based reinforcement system to teach healthcare quality and patient safety and care transitions at the University of California

1,050,750. CONCLUSION The interventions reduced multiunit transfusions (by 67.1%) and transfusions for Hb ≥ 7 g/dL (by 47.4%). The improvement in the overall transfusion rate (19.0%) was less marked, limited by better baseline performance relative to other centers.

Electronic Health Records Quantify Previously Existing Phenomenon-Physicians Spend Hours Coordinating Care.

Quality issue Implementing quality improvement (QI) education during clinical training is challenging due to time constraints and inadequate faculty development in these areas. Initial assessment Quiz-based reinforcement systems show promise in fostering active engagement, collaboration, healthy competition and real-time formative feedback, although further research on their effectiveness is required. Choice of solution An online quiz-based reinforcement system to increase resident and faculty knowledge in QI, patient safety and care transitions. Implementation Experts in QI and educational assessment at the 5 University of California medical campuses developed a course comprised of 3 quizzes on Introduction to QI, Patient Safety and Care Transitions. Each quiz contained 20 questions and utilized an online educational quiz-based reinforcement system that leveraged spaced learning. Evaluation Approximately 500 learners completed the course (completion rate 66-86%). Knowledge acquisition scores for all quizzes increased after completion: Introduction to QI (35-73%), Patient Safety (58-95%), and Care Transitions (66-90%). Learners reported that the quiz-based system was an effective teaching modality and preferred this type of education to classroom-based lectures. Suggestions for improvement included reducing frequency of presentation of questions and utilizing more questions that test learners on application of knowledge instead of knowledge acquisition. Lessons learned A multi-campus online quiz-based reinforcement system to train residents in QI, patient safety and care transitions was feasible, acceptable, and increased knowledge. The course may be best utilized to supplement classroom-based and experiential curricula, along with increased attention to optimizing frequency of presentation of questions and enhancing application skills.

Results of a medication reconciliation survey from the 2006 Society of Hospital Medicine national meeting

Fourth, blood pressure was measured in different seasons (44.6% in winter and summer vs 55.4% in spring and autumn) which made the blood pressure incomparable between participants. Fifth, it is unclear why the strength of untreated hypertension vs treated hypertension on risk of CVD mortality decreased with age increasing. The risk ratio was about 4 for participants ages 35 to 59 years, while the risk ratio was approximately 2 for participants ages 70 to 74 years. Does it mean that untreated hypertension in middle-age adults is more harmful than that in older adults? Finally, we felt that the third age group in Figure 3 might be wrong and that it should be “70-74” rather than “70-79.”