Herasevich, Vitaly

Abstract Objective Despite increased use of electronic health records (EHRs), the clinical impact of system downtime is unknown. Materials and Methods This retrospective matched cohort study evaluated the impact of EHR downtime episodes lasting more than 60 minutes over a 6-year study period. Patients age 18 years or older who underwent surgical procedures at least 60 minutes in duration with an inpatient stay exceeding 24 hours within the study period were eligible for inclusion. Out of 4115 patients exposed to 1 of 176 EHR downtime episodes, 4103 patients were matched to an unexposed cohort in a 1:1 ratio. Multivariable regression analysis, as well as trend analysis for effect of duration of downtime on outcomes, was performed. Results Downtime-exposed patients had operating room duration 1.1 times longer (p < .001) and postoperative length of stay 1.04 times longer (p = .007) compared to unexposed patients. The 30-day mortality rates were similar between these groups (odds ratio 1.26, p > .05). In trend analysis, there was no association between duration of downtime with respect to evaluated outcomes, postoperative length of stay, and 30-day mortality. Conclusion EHR downtime had no impact on 30-day mortality. Potential associations for increased postoperative length of stay and duration of time spent in the operating room were observed among downtime-exposed patients. No trend effect was observed with respect to duration of downtime and postoperative length of stay and 30-day mortality rates.

Background Electronic Health Record (EHR)-based sepsis alert systems have failed to demonstrate improvements in clinically meaningful endpoints. However, the effect of implementation barriers on the success of new sepsis alert systems is rarely explored. Objective To test the hypothesis time to severe sepsis alert acknowledgement by critical care clinicians in the ICU setting would be reduced using an EHR-based alert acknowledgement system compared to a text paging-based system. Study Design In one arm of this simulation study, real alerts for patients in the medical ICU were delivered to critical care clinicians through the EHR. In the other arm, simulated alerts were delivered through text paging. The primary outcome was time to alert acknowledgement. The secondary outcomes were a structured, mixed quantitative/qualitative survey and informal group interview. Results The alert acknowledgement rate from the severe sepsis alert system was 3% ( N = 148) and 51% ( N = 156) from simulated severe sepsis alerts through traditional text paging. Time to alert acknowledgement from the severe sepsis alert system was median 274 min ( N = 5) and median 2 min ( N = 80) from text paging. The response rate from the EHR-based alert system was insufficient to compare primary measures. However, secondary measures revealed important barriers. Conclusion Alert fatigue, interruption, human error, and information overload are barriers to alert and simulation studies in the ICU setting.

Objectives: Sarcopenia is associated with a poor prognosis in the ICU. The purpose of this study was to describe a simple sarcopenia index using routinely available renal biomarkers and evaluate its association with muscle mass and patient outcomes. Design: A retrospective cohort study. Setting: A tertiary-care medical center. Patients: High-risk adult ICU patients from October 2008 to December 2010. Interventions: The gold standard for muscle mass was quantified with the paraspinal muscle surface area at the L4 vertebrae in the subset of individuals with an abdominal CT scan. Using Pearson’s correlation coefficient, serum creatinine-to-serum cystatin C ratio was found to be the best performer in the estimation of muscle mass. The relationship between sarcopenia index and hospital and 90-day mortality, and the length of mechanical ventilation was evaluated. Measurements and Main Results: Out of 226 enrolled patients, 123 (54%) were female, and 198 (87%) were white. Median (interquartile range) age, body mass index, and body surface area were 68 (57–77) years, 28 (24–34) kg/m2, and 1.9 (1.7–2.2) m2, respectively. The mean (± sd) Acute Physiology and Chronic Health Evaluation III was 70 (± 22). ICU, hospital, and 90-day mortality rates were 5%, 12%, and 20%, respectively. The correlation (r) between sarcopenia index and muscle mass was 0.62 and coefficient of determination (r 2) was 0.27 (p < 0.0001). After adjustment for Acute Physiology and Chronic Health Evaluation III, body surface area, and age, sarcopenia index was independently predictive of both hospital (p = 0.001) and 90-day mortality (p < 0.0001). Among the 131 patients on mechanical ventilator, the duration of mechanical ventilation was significantly lower on those with higher sarcopenia index (–1 d for each 10 unit of sarcopenia index [95% CI, –1.4 to –0.2; p = 0.006]). Conclusions: The sarcopenia index is a fair measure for muscle mass estimation among ICU patients and can modestly predict hospital and 90-day mortality among patients who do not have acute kidney injury at the time of measurement.

Hyperglycemia control is associated with improved outcomes in patients undergoing cardiac surgery. The Surgical Care Improvement Project metric (SCIP-inf-4) was introduced as a performance measure in surgical patients and included hyperglycemia control. Compliance with the SCIP-inf-4 metric remains suboptimal. A novel real-time decision support tool (DST) with guaranteed feedback that is based on the existing electronic medical record system was developed at a tertiary academic center. Implementation of the DST increased the compliance rate with the SCIP-inf-4 from 87.3% to 96.5%. Changes in tested clinical outcomes were not observed with improved metric compliance. This new framework can serve as a backbone for development of quality control processes for other metrics. Further and, ideally, multicenter studies are required to test if implementation of electronic DSTs will translate into improved resource utilization and outcomes for patients.

Introduction Acute respiratory failure (ARF) often presents and progresses outside of the intensive care unit. However, recognition and treatment of acute critical illness is often delayed with inconsistent adherence to evidence-based care known to decrease the duration of mechanical ventilation (MV) and complications of critical illness. The goal of this trial is to determine whether the implementation of an electronic medical record-based early alert for progressive respiratory failure coupled with a checklist to promote early compliance to best practice in respiratory failure can improve the outcomes of patients at risk for prolonged respiratory failure and death. Methods and analysis A pragmatic stepped-wedged cluster clinical trial involving 6 hospitals is planned. The study will include adult hospitalised patients identified as high risk for MV >48 hours or death because they were mechanically ventilated outside of the operating room or they were identified as high risk for ARF on the Accurate Prediction of PROlonged VEntilation (APPROVE) score. Patients with advanced directives limiting intubation will be excluded. The intervention will consist of (1) automated identification and notification of clinician of high-risk patients by APPROVE or by invasive MV and (2) checklist of evidence-based practices in ARF (Prevention of Organ Failure Checklist—PROOFCheck). APPROVE and PROOFCheck will be developed in the pretrial period. Primary outcome is hospital mortality. Secondary outcomes include length of stay, ventilator and organ failure-free days and 6-month and 12-month mortality. Predefined subgroup analysis of patients with limitation of aggressive care after study entry is planned. Generalised estimating equations will be used to compare patients in the intervention phase with the control phase, adjusting for clustering within hospitals and time. Ethics and dissemination The study was approved by the institutional review boards. Results will be published in peer-reviewed journals and presented at international meetings. Trial registration number NCT02488174.

Objective: In this systematic review, we aimed to evaluate methodological and reporting trends present in the current literature by investigating published usability studies of electronic health records (EHRs). Methods: A literature search was conducted for articles published through January 2015 using MEDLINE (Ovid), EMBASE, Scopus, and Web of Science, supplemented by citation and reference list reviews. Studies were included if they tested the usability of hospital and clinic EHR systems in the inpatient, outpatient, emergency department, or operating room setting. Results: A total of 4848 references were identified for title and abstract screening. Full text screening was performed for 197 articles, with 120 meeting the criteria for study inclusion. Conclusion: A review of the literature demonstrates a paucity of quality published studies describing scientifically valid and reproducible usability evaluations at various stages of EHR system development. A lack of formal and standardized reporting of EHR usability evaluation results is a major contributor to this knowledge gap, and efforts to improve this deficiency will be one step of moving the field of usability engineering forward.

Abstract Rationale Respiratory failure represents a major risk for morbidity and mortality. Although generally managed in the intensive care unit (ICU), respiratory failure often begins elsewhere. Checklists of care processes to minimize the duration of mechanical ventilation and adverse events are routinely used in the ICU, but are uncommonly used outside the ICU. Objectives To develop consensus among a multidisciplinary expert panel on care practices to include in a checklist of best practices for critically ill patients with respiratory failure before and after ICU admission. Methods A multidisciplinary expert panel was assembled. The panel was tasked with creating a checklist of care processes aimed at decreasing progression to respiratory failure, duration of mechanical ventilation, mortality in mechanical ventilation, and adverse events. Over the course of multiple teleconferences and e-mail communications, the Prevention of Organ Failure Checklist list was reviewed, refined, and voted upon. Items that received greater than 75% of the vote were included in the final checklist. Measurements and Main Results: Using a modified Delphi process, the expert panel was able to compile Prevention of Organ Failure Checklist into 20 items that aimed to decrease mechanical ventilation by assessing the causes of acute respiratory failure, ventilation strategies, sedation, and general critical care processes, as well as to avoid unwanted or nonbeneficial interventions. Conclusions The modified Delphi process identified readily available preventative interventions suitable for checklist implementation in patients with or progressing to respiratory failure even before ICU admission.

Ventilator-associated events (VAEs) are associated with increased risk of poor outcomes, including death. Bundle practices including thromboembolism prophylaxis, stress ulcer prophylaxis, oral care, and daily sedation breaks and spontaneous breathing trials aim to reduce rates of VAEs and are endorsed as quality metrics in the intensive care units. We sought to create electronic search algorithms (digital signatures) to evaluate compliance with ventilator bundle components as the first step in a larger project evaluating the ventilator bundle effect on VAE. We developed digital signatures of bundle compliance using a retrospective cohort of 542 ICU patients from 2010 for derivation and validation and testing of signature accuracy from a cohort of random 100 patients from 2012. Accuracy was evaluated against manual chart review. Overall, digital signatures performed well, with median sensitivity of 100% (range, 94.4%–100%) and median specificity of 100% (range, 100%–99.8%). Automated ascertainment from electronic medical records accurately assesses ventilator bundle compliance and can be used for quality reporting and research in VAE.