Implementation of App-Based Diabetes Medication Management: Outpatient and Perioperative Clinical Decision Support.

PURPOSE OF REVIEW: Outpatient and perioperative therapeutic decision making for patients with diabetes involves increasingly complex medical-decision making due to rapid advances in knowledge and treatment modalities. We sought to review mobile decision support tools available to clinicians for this essential and increasingly difficult task, and to highlight the development and implementation of novel mobile applications for these purposes. RECENT FINDINGS: We found 211 mobile applications related to diabetes from the search, but only five were found to provide clinical decision support for outpatient diabetes management and none for perioperative decision support. We found a dearth of tools for clinicians to navigate these tasks. We highlight key aspects for effective development of future diabetes decision support. These include just-in-time availability, respect for the five rights of clinical decision support, and integration with clinical workflows including the electronic medical record.

A multifaceted quality improvement project improves intraoperative redosing of surgical antimicrobial prophylaxis during pediatric surgery.

BACKGROUND: Accurate intraoperative antibiotic redosing contributes to prevention of surgical site infections in pediatric patients. Ensuring compliance with evolving national guidelines of weight-based, intraoperative redosing of antibiotics is challenging to pediatric anesthesiologists. AIMS: Our primary aim was to increase compliance of antibiotic redoses at the appropriate time and appropriate weight-based dose to 70%. Secondary aims included a subset analysis of time compliance and dose compliance individually, and compliance based on order entry method of the first dose (verbal or electronic). METHODS: At a freestanding, academic pediatric hospital, we reviewed surgical cases between May 1, 2014, and October 31, 2017 requiring antibiotic redoses. After an institutional change in cefazolin dosing in May 2015, phased interventions to improve compliance included electronic countermeasures to display previous and next dose timing, an alert 5 minutes prior to next dose, and weight-based dose recommendation (September 2015). Physical countermeasures include badge cards, posting of guidelines, and updates to housestaff manual (September 2015). Statistical process control charts were used to assess overall antibiotic redose compliance, time compliance, and dose compliance. The chi-square test was used to analyze group differences. RESULTS: A total of 3015 antibiotic redoses were administered during 2341 operative cases between May 1, 2014, and October 31, 2017. Mean monthly compliance with redosing was 4.3% (May 2014-April 2015) and 73% (November 2015-October 2017) (P < 0.001). Dose-only compliance increased from 76% to 89% (P < 0.001), and time-only compliance increased from 4.9% to 82% (P < 0.001). After implementation of countermeasures, electronic order entry compared with verbal order was associated with higher dose compliance, 90% vs 86% (P = 0.015). CONCLUSION: This quality improvement project, utilizing electronic and physical interventions, was effective in improving overall prophylactic antibiotic redosing compliance in accordance with institutional redosing guidelines.

Feasibility and indicator outcomes using computerized clinical decision support in pediatric traumatic brain injury anesthesia care.

BACKGROUND: Traumatic brain injury anesthesia care is complex. The use of clinical decision support to improve pediatric trauma care has not been examined. AIMS: The aim of this study was to examine feasibility, reliability, and key performance indicators for traumatic brain injury anesthesia care using clinical decision support. METHODS: Clinical decision support was activated for patients under 19 years undergoing craniotomy for suspected traumatic brain injury. Anesthesia providers were prompted to adhere to process measures via on-screen alerts and notified in real time of abnormal monitor data or laboratory results (unwanted key performance indicator events). Process measures pertained to arterial line placement and blood gas draws, neuromuscular blockade, hypotension, anemia, coagulopathy, hyperglycemia, and intracranial hypertension. Unwanted key performance indicators were: hypotension, hypoxia, hypocarbia, hypercarbia, hypothermia, hyperthermia, anesthetic agent overdose; hypoxemia, coagulopathy, anemia, and hyperglycemia. Anesthesia records, vital signs, and alert logs were reviewed for 39 anesthetic cases (19 without clinical decision support and 20 with clinical decision support). RESULTS: Data from 35 patients aged 11 months to 17 years and 77% males were examined. Clinical decision support reliably identified 39/46 eligible anesthetic cases, with 85% sensitivity and 100% specificity, and was highly sensitive, detecting 89% of monitor key performance indicator events and 100% of reported lab key performance indicator events. There were no false positive alerts. Median event duration was lower in the "with clinical decision support" group for 4/7 key performance indicators. Second insult duration was lower for duration of hypocarbia (by 44%), hypotension (29%), hypothermia (12%), and hyperthermia (15%). CONCLUSION: Use of clinical decision support in pediatric traumatic brain injury anesthesia care is feasible, reliable, and may have the potential to improve key performance indicator outcomes. This observational study suggests the possibility of clinical decision support as a strategy to reduce second insults and improve traumatic brain injury guideline adherence during pediatric anesthesia care.

Development and Feasibility of a Real-Time Clinical Decision Support System for Traumatic Brain Injury Anesthesia Care.

BACKGROUND: Real-time clinical decision support (CDS) integrated with anesthesia information management systems (AIMS) can generate point of care reminders to improve quality of care. OBJECTIVE: To develop, implement and evaluate a real-time clinical decision support system for anesthetic management of pediatric traumatic brain injury (TBI) patients undergoing urgent neurosurgery. METHODS: We iteratively developed a CDS system for pediatric TBI patients undergoing urgent neurosurgery. The system automatically detects eligible cases and evidence-based key performance indicators (KPIs). Unwanted clinical events trigger and display real-time messages on the AIMS computer screen. Main outcomes were feasibility of detecting eligible cases and KPIs, and user acceptance. RESULTS: The CDS system was triggered in 22 out of 28 (79%) patients. The sensitivity of detecting continuously sampled KPIs reached 93.8%. For intermittently sampled KPIs, sensitivity and specificity reached 90.9% and 100%, respectively. 88% of providers reported that CDS helped with TBI anesthesia care. CONCLUSIONS: CDS implementation is feasible and acceptable with a high rate of case capture and appropriate generation of alert and guidance messages for TBI anesthesia care.

Simulating ventilation distribution in heterogenous lung injury using a binary tree data structure.

To determine the impact of mechanical heterogeneity on the distribution of regional flows and pressures in the injured lung, we developed an anatomic model of the canine lung comprised of an asymmetric branching airway network, which can be stored as binary tree data structure. The entire tree can be traversed using a recursive flow divider algorithm, allowing for efficient computation of acinar flow and pressure distributions in a mechanically heterogeneous lung. These distributions were found to be highly dependent on ventilation frequency and the heterogeneity of tissue elastances, reflecting the preferential distribution of ventilation to areas of lower regional impedance.