Convalescent Plasma Antibody Levels and the Risk of Death from Covid-19.

BACKGROUND: Convalescent plasma has been widely used to treat coronavirus disease 2019 (Covid-19) under the presumption that such plasma contains potentially therapeutic antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can be passively transferred to the plasma recipient. Whether convalescent plasma with high antibody levels rather than low antibody levels is associated with a lower risk of death is unknown. METHODS: In a retrospective study based on a U.S. national registry, we determined the anti-SARS-CoV-2 IgG antibody levels in convalescent plasma used to treat hospitalized adults with Covid-19. The primary outcome was death within 30 days after plasma transfusion. Patients who were enrolled through July 4, 2020, and for whom data on anti-SARS-CoV-2 antibody levels in plasma transfusions and on 30-day mortality were available were included in the analysis. RESULTS: Of the 3082 patients included in this analysis, death within 30 days after plasma transfusion occurred in 115 of 515 patients (22.3%) in the high-titer group, 549 of 2006 patients (27.4%) in the medium-titer group, and 166 of 561 patients (29.6%) in the low-titer group. The association of anti-SARS-CoV-2 antibody levels with the risk of death from Covid-19 was moderated by mechanical ventilation status. A lower risk of death within 30 days in the high-titer group than in the low-titer group was observed among patients who had not received mechanical ventilation before transfusion (relative risk, 0.66; 95% confidence interval [CI], 0.48 to 0.91), and no effect on the risk of death was observed among patients who had received mechanical ventilation (relative risk, 1.02; 95% CI, 0.78 to 1.32). CONCLUSIONS: Among patients hospitalized with Covid-19 who were not receiving mechanical ventilation, transfusion of plasma with higher anti-SARS-CoV-2 IgG antibody levels was associated with a lower risk of death than transfusion of plasma with lower antibody levels. (Funded by the Department of Health and Human Services and others; ClinicalTrials.gov number, NCT04338360.).

Diagnostic delay in pulmonary blastomycosis: a case series reflecting a referral center experience.

PURPOSE: The diagnosis of pulmonary blastomycosis is usually delayed because of its non-specific presentation. We aimed to assess the extent of diagnostic delay in hospitalized patients and detect the step in the diagnostic process that requires the most improvement. METHODS: Adult patients diagnosed with pulmonary blastomycosis during a hospital admission between January 2010 through November 2021 were eligible for inclusion. Patients who did not have pulmonary involvement and who were diagnosed before admission were excluded. Demographics and comorbid conditions, specifics of disease presentation, and interventions were evaluated. The timing of the diagnosis, antifungal treatment, and patient outcomes were noted. Descriptive analytical tests were performed. RESULTS: A total of 43 patients were diagnosed with pulmonary blastomycosis during their admissions. The median age was 47 years, with 13 (30%) females. Of all patients, 29 (67%) had isolated pulmonary infection, while 14 (33%) had disseminated disease, affecting mostly skin and musculoskeletal system. The median duration between the initial symptoms and health care encounters was 4 days, and the time to hospital admission was 9 days. The median duration from the initial symptoms to the diagnosis was 20 days. Forty patients (93%) were treated with empirical antibacterials before a definitive diagnosis was made. In addition, corticosteroid treatment was empirically administered to 15 patients (35%) before the diagnosis, with indications such as suspicion of inflammatory processes or symptom relief. In 38 patients (88%), the first performed fungal diagnostic test was positive. Nineteen patients (44%) required admission to the intensive care unit, and 11 patients (26%) died during their hospital stay. CONCLUSION: There was a delay in diagnosis of patients with pulmonary blastomycosis, largely attributable to the lack of consideration of the etiological agent. Novel approaches to assist providers in recognizing the illness earlier and trigger evaluation are needed.

Association of Blood Pressure Variability with Delirium in Patients with Critical Illness.

BACKGROUND: The objective was to examine the association of blood pressure variability (BPV) during the first 24 h after intensive care unit admission with the likelihood of delirium and depressed alertness without delirium ("depressed alertness"). METHODS: This retrospective, observational, cohort study included all consecutive adult patients admitted to an intensive care unit at Mayo Clinic, Rochester, Minnesota, from July 1, 2004, through October 31, 2015. The primary outcomes were delirium and delirium-free days, and the secondary outcomes included depressed alertness and depressed alertness-free days. Logistic regression was performed to determine the association of BPV with delirium and depressed alertness. Proportional odds regression was used to assess the association of BPV with delirium-free days and depressed alertness-free days. RESULTS: Among 66,549 intensive care unit admissions, delirium was documented in 20.2% and depressed alertness was documented in 24.4%. Preserved cognition was documented in 55.4% of intensive care unit admissions. Increased systolic and diastolic BPV was associated with an increased odds of delirium and depressed alertness. The magnitude of the association per 5-mm Hg increase in systolic average real variability (the average of absolute value of changes between consecutive systolic blood pressure readings) was greater for delirium (odds ratio 1.34; 95% confidence interval 1.29-1.40; P < 0.001) than for depressed alertness (odds ratio 1.06; 95% confidence interval 1.02-1.10; P = 0.004). Increased systolic and diastolic BPV was associated with fewer delirium-free days but not with depressed alertness-free days. CONCLUSIONS: BPV in the first 24 h after intensive care unit admission is associated with an increased likelihood of delirium and fewer delirium-free days.

The Impact of Health Information Technology for Early Detection of Patient Deterioration on Mortality and Length of Stay in the Hospital Acute Care Setting: Systematic Review and Meta-Analysis.

OBJECTIVE: To evaluate the impact of health information technology (HIT) for early detection of patient deterioration on patient mortality and length of stay (LOS) in acute care hospital settings. DATA SOURCES: We searched MEDLINE and Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily, Embase, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Scopus from 1990 to January 19, 2021. STUDY SELECTION: We included studies that enrolled patients hospitalized on the floor, in the ICU, or admitted through the emergency department. Eligible studies compared HIT for early detection of patient deterioration with usual care and reported at least one end point of interest: hospital or ICU LOS or mortality at any time point. DATA EXTRACTION: Study data were abstracted by two independent reviewers using a standardized data extraction form. DATA SYNTHESIS: Random-effects meta-analysis was used to pool data. Among the 30 eligible studies, seven were randomized controlled trials (RCTs) and 23 were pre-post studies. Compared with usual care, HIT for early detection of patient deterioration was not associated with a reduction in hospital mortality or LOS in the meta-analyses of RCTs. In the meta-analyses of pre-post studies, HIT interventions demonstrated a significant association with improved hospital mortality for the entire study cohort (odds ratio, 0.78 [95% CI, 0.70-0.87]) and reduced hospital LOS overall. CONCLUSIONS: HIT for early detection of patient deterioration in acute care settings was not significantly associated with improved mortality or LOS in the meta-analyses of RCTs. In the meta-analyses of pre-post studies, HIT was associated with improved hospital mortality and LOS; however, these results should be interpreted with caution. The differences in patient outcomes between the findings of the RCTs and pre-post studies may be secondary to confounding caused by unmeasured improvements in practice and workflow over time.

Implementation and evaluation of sepsis surveillance and decision support in medical ICU and emergency department.

OBJECTIVE: To improve the timely diagnosis and treatment of sepsis many institutions implemented automated sepsis alerts. Poor specificity, time delays, and a lack of actionable information lead to limited adoption by bedside clinicians and no change in practice or clinical outcomes. We aimed to compare sepsis care compliance before and after a multi-year implementation of a sepsis surveillance coupled with decision support in a tertiary care center. DESIGN: Single center before and after study. SETTING: Large academic Medical Intensive Care Unit (MICU) and Emergency Department (ED). POPULATION: Patients 18 years of age or older admitted to *** Hospital MICU and ED from 09/4/2011 to 05/01/2018 with severe sepsis or septic shock. INTERVENTIONS: Electronic medical record-based sepsis surveillance system augmented by clinical decision support and completion feedback. MEASUREMENTS AND MAIN RESULTS: There were 1950 patients admitted to the MICU with the diagnosis of severe sepsis or septic shock during the study period. The baseline characteristics were similar before (N = 854) and after (N = 1096) implementation of sepsis surveillance. The performance of the alert was modest with a sensitivity of 79.9%, specificity of 76.9%, positive predictive value (PPV) 27.9%, and negative predictive value (NPV) 97.2%. There were 3424 unique alerts and 1131 confirmed sepsis patients after the sniffer implementation. During the study period average care bundle compliance was higher; however after taking into account improvements in compliance leading up to the intervention, there was no association between intervention and improved care bundle compliance (Odds ratio: 1.16; 95% CI: 0.71 to 1.89; p-value 0.554). Similarly, the intervention was not associated with improvement in hospital mortality (Odds ratio: 1.55; 95% CI: 0.95 to 2.52; p-value: 0.078). CONCLUSIONS: A sepsis surveillance system incorporating decision support or completion feedback was not associated with improved sepsis care and patient outcomes.

Access to and safety of COVID-19 convalescent plasma in the United States Expanded Access Program: A national registry study.

BACKGROUND: The United States (US) Expanded Access Program (EAP) to coronavirus disease 2019 (COVID-19) convalescent plasma was initiated in response to the rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19. While randomized clinical trials were in various stages of development and enrollment, there was an urgent need for widespread access to potential therapeutic agents. The objective of this study is to report on the demographic, geographical, and chronological characteristics of patients in the EAP, and key safety metrics following transfusion of COVID-19 convalescent plasma. METHODS AND FINDINGS: Mayo Clinic served as the central institutional review board for all participating facilities, and any US physician could participate as a local physician-principal investigator. Eligible patients were hospitalized, were aged 18 years or older, and had-or were at risk of progression to-severe or life-threatening COVID-19; eligible patients were enrolled through the EAP central website. Blood collection facilities rapidly implemented programs to collect convalescent plasma for hospitalized patients with COVID-19. Demographic and clinical characteristics of all enrolled patients in the EAP were summarized. Temporal patterns in access to COVID-19 convalescent plasma were investigated by comparing daily and weekly changes in EAP enrollment in response to changes in infection rate at the state level. Geographical analyses on access to convalescent plasma included assessing EAP enrollment in all national hospital referral regions, as well as assessing enrollment in metropolitan areas and less populated areas that did not have access to COVID-19 clinical trials. From April 3 to August 23, 2020, 105,717 hospitalized patients with severe or life-threatening COVID-19 were enrolled in the EAP. The majority of patients were 60 years of age or older (57.8%), were male (58.4%), and had overweight or obesity (83.8%). There was substantial inclusion of minorities and underserved populations: 46.4% of patients were of a race other than white, and 37.2% of patients were of Hispanic ethnicity. Chronologically and geographically, increases in the number of both enrollments and transfusions in the EAP closely followed confirmed infections across all 50 states. Nearly all national hospital referral regions enrolled and transfused patients in the EAP, including both in metropolitan and in less populated areas. The incidence of serious adverse events was objectively low (<1%), and the overall crude 30-day mortality rate was 25.2% (95% CI, 25.0% to 25.5%). This registry study was limited by the observational and pragmatic study design that did not include a control or comparator group; thus, the data should not be used to infer definitive treatment effects. CONCLUSIONS: These results suggest that the EAP provided widespread access to COVID-19 convalescent plasma in all 50 states, including for underserved racial and ethnic minority populations. The study design of the EAP may serve as a model for future efforts when broad access to a treatment is needed in response to an emerging infectious disease. TRIAL REGISTRATION: ClinicalTrials.gov NCT#: NCT04338360.

Outcome after intubation for septic shock with respiratory distress and hemodynamic compromise: an observational study.

BACKGROUND: Acute respiratory failure in septic patients contributes to higher in-hospital mortality. Intubation may improve outcome but there are no specific criteria for intubation. Intubation of septic patients with respiratory distress and hemodynamic compromise may result in clinical deterioration and precipitate cardiovascular failure. The decision to intubate is complex and multifactorial. The purpose of this study was to evaluate the impact of intubation in patients with respiratory distress and predominant hemodynamic instability within 24 h after ICU admission for septic shock. METHODS: We conducted a retrospective analysis of a prospective registry of adult patients with septic shock admitted to the medical ICU at Mayo Clinic, between April 30, 2014 and December 31, 2017. Septic shock was defined by persistent lactate > 4 mmol/L, mean arterial pressure < 65 mmHg, or vasopressor use after 30 mL/kg fluid boluses and suspected or confirmed infection. Patients who remained hospitalized in the ICU at 24 h were separated into intubated while in the ICU and non-intubated groups. The primary outcome was hospital mortality. The first analysis used linear regression models and the second analysis used time-dependent propensity score matching to match intubated to non-intubated patients. RESULTS: Overall, 358 (33%) ICU patients were eventually intubated after their ICU admission and 738 (67%) were not. Intubated patients were younger, transferred more often from an outside facility, more critically ill, had more lung infection, and achieved blood pressure goals more often, but lactate normalization within 6 h occurred less often. Among those who remained hospitalized in the ICU 24 h after sepsis diagnosis, the crude in-hospital mortality was higher in intubated than non-intubated patients, 89 (26%) vs. 82 (12%), p < 0.001, as was the ICU mortality and ICU and hospital length of stay. After adjustment, intubation showed no effect on hospital mortality but resulted in fewer hospital-free days through day 28. One-to-one propensity resulted in similar conclusion. CONCLUSIONS: Intubation within 24 h of sepsis was not associated with hospital mortality but resulted in fewer 28-day hospital-free days. Although intubation remains a high-risk procedure, we did not identify an increased risk in mortality among septic shock patients with predominant hemodynamic compromise.

Tele-Critical Care: An Update From the Society of Critical Care Medicine Tele-ICU Committee.

OBJECTIVES: In 2014, the Tele-ICU Committee of the Society of Critical Care Medicine published an article regarding the state of ICU telemedicine, one better defined today as tele-critical care. Given the rapid evolution in the field, the authors now provide an updated review. DATA SOURCES AND STUDY SELECTION: We searched PubMed and OVID for peer-reviewed literature published between 2010 and 2018 related to significant developments in tele-critical care, including its prevalence, function, activity, and technologies. Search terms included electronic ICU, tele-ICU, critical care telemedicine, and ICU telemedicine with appropriate descriptors relevant to each sub-section. Additionally, information from surveys done by the Society of Critical Care Medicine was included given the relevance to the discussion and was referenced accordingly. DATA EXTRACTION AND DATA SYNTHESIS: Tele-critical care continues to evolve in multiple domains, including organizational structure, technologies, expanded-use case scenarios, and novel applications. Insights have been gained in economic impact and human and organizational factors affecting tele-critical care delivery. Legislation and credentialing continue to significantly influence the pace of tele-critical care growth and adoption. CONCLUSIONS: Tele-critical care is an established mechanism to leverage critical care expertise to ICUs and beyond, but systematic research comparing different models, approaches, and technologies is still needed.

Multicenter derivation and validation of an early warning score for acute respiratory failure or death in the hospital.

BACKGROUND: Acute respiratory failure occurs frequently in hospitalized patients and often starts before ICU admission. A risk stratification tool to predict mortality and risk for mechanical ventilation (MV) may allow for earlier evaluation and intervention. We developed and validated an automated electronic health record (EHR)-based model-Accurate Prediction of Prolonged Ventilation (APPROVE)-to identify patients at risk of death or respiratory failure requiring >= 48 h of MV. METHODS: This was an observational study of adults admitted to four hospitals in 2013 or a fifth hospital in 2017. Clinical data were extracted from the EHRs. The 2013 patients were randomly split 50:50 into a derivation/validation cohort. The qualifying event was death or intubation leading to MV >= 48 h. Random forest method was used in model derivation. APPROVE was calculated retrospectively whenever data were available in 2013, and prospectively every 4 h after hospital admission in 2017. The Modified Early Warning Score (MEWS) and National Early Warning Score (NEWS) were calculated at the same times as APPROVE. Clinicians were not alerted except for APPROVE in 2017cohort. RESULTS: There were 68,775 admissions in 2013 and 2258 in 2017. APPROVE had an area under the receiver operator curve of 0.87 (95% CI 0.85-0.88) in 2013 and 0.90 (95% CI 0.84-0.95) in 2017, which is significantly better than the MEWS and NEWS in 2013 but similar to the MEWS and NEWS in 2017. At a threshold of > 0.25, APPROVE had similar sensitivity and positive predictive value (PPV) (sensitivity 63% and PPV 21% in 2013 vs 64% and 16%, respectively, in 2017). Compared to APPROVE in 2013, at a threshold to achieve comparable PPV (19% at MEWS > 4 and 22% at NEWS > 6), the MEWS and NEWS had lower sensitivity (16% for MEWS and NEWS). Similarly in 2017, at a comparable sensitivity threshold (64% for APPROVE > 0.25 and 67% for MEWS and NEWS > 4), more patients who triggered an alert developed the event with APPROVE (PPV 16%) while achieving a lower false positive rate (FPR 5%) compared to the MEWS (PPV 7%, FPR 14%) and NEWS (PPV 4%, FPR 25%). CONCLUSIONS: An automated EHR model to identify patients at high risk of MV or death was validated retrospectively and prospectively, and was determined to be feasible for real-time risk identification. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02488174 . Registered on 18 March 2015.

Evaluating Muscle Mass by Using Markers of Kidney Function: Development of the Sarcopenia Index.

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/m, and 1.9 (1.7-2.2) m, 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) 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.

Information needs for the rapid response team electronic clinical tool.

BACKGROUND: Information overload in healthcare is dangerous. It can lead to critical errors and delays. During Rapid Response Team (RRT) activations providers must make decisions quickly to rescue patients from physiological deterioration. In order to understand the clinical data required and how best to present that information in electronic systems we aimed to better assess the data needs of providers on the RRT when they respond to an event. METHODS: A web based survey to evaluate clinical data requirements was created and distributed to all RRT providers at our institution. Participants were asked to rate the importance of each data item in guiding clinical decisions during a RRT event response. RESULTS: There were 96 surveys completed (24.5% response rate) with fairly even distribution throughout all clinical roles on the RRT. Physiological data including heart rate, respiratory rate, and blood pressure were ranked by more than 80% of responders as being critical information. Resuscitation status was also considered critically useful by more than 85% of providers. CONCLUSION: There is a limited dataset that is considered important during an RRT. The data is widely available in EMR. The findings from this study could be used to improve user-centered EMR interfaces.

Delayed Rapid Response Team Activation Is Associated With Increased Hospital Mortality, Morbidity, and Length of Stay in a Tertiary Care Institution.

OBJECTIVE: To identify whether delays in rapid response team activation contributed to worse patient outcomes (mortality and morbidity). DESIGN: Retrospective observational cohort study including all rapid response team activations in 2012. SETTING: Tertiary academic medical center. PATIENTS: All those 18 years old or older who had a rapid response team call activated. Vital sign data were abstracted from individual patient electronic medical records for the 24 hours before the rapid response team activation took place. Patients were considered to have a delayed rapid response team activation if more than 1 hour passed between the first appearance in the record of an abnormal vital sign meeting rapid response team criteria and the activation of an rapid response team. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 1,725 patients were included in the analysis. Data were compared between those who had a delayed rapid response team activation and those who did not. Fifty seven percent patients met the definition of delayed rapid response team activation. Patients in high-frequency physiologic monitored environments were more likely to experience delay than their floor counterparts. In the no-delay group, the most common reasons for rapid response team activation were tachycardia/bradycardia at 29% (217/748), respiratory distress/low SpO2 at 28% (213/748), and altered level of consciousness at 23% (170/748) compared with respiratory distress/low SpO2 at 43% (423/977), tachycardia/bradycardia at 33% (327/977), and hypotension at 27% (261/977) in the delayed group. The group with no delay had a higher proportion of rapid response team calls between 8:00 and 16:00, whereas those with delay had a higher proportion of calls between midnight and 08:00. The delayed group had higher hospital mortality (15% vs 8%; adjusted odds ratio, 1.6; p = 0.005); 30-day mortality (20% vs 13%; adjusted odds ratio, 1.4; p = 0.02); and hospital length of stay (7 vs 6 d; relative prolongation, 1.10; p = 0.02) compared with the no-delay group. CONCLUSIONS: Delays in rapid response team activation occur frequently and are independently associated with worse patient mortality and morbidity outcomes.

The Effect of an Electronic Checklist on Critical Care Provider Workload, Errors, and Performance.

PURPOSE: The strategy used to improve effective checklist use in intensive care unit (ICU) setting is essential for checklist success. This study aimed to test the hypothesis that an electronic checklist could reduce ICU provider workload, errors, and time to checklist completion, as compared to a paper checklist. METHODS: This was a simulation-based study conducted at an academic tertiary hospital. All participants completed checklists for 6 ICU patients: 3 using an electronic checklist and 3 using an identical paper checklist. In both scenarios, participants had full access to the existing electronic medical record system. The outcomes measured were workload (defined using the National Aeronautics and Space Association task load index [NASA-TLX]), the number of checklist errors, and time to checklist completion. Two independent clinician reviewers, blinded to participant results, served as the reference standard for checklist error calculation. RESULTS: Twenty-one ICU providers participated in this study. This resulted in the generation of 63 simulated electronic checklists and 63 simulated paper checklists. The median NASA-TLX score was 39 for the electronic checklist and 50 for the paper checklist (P = .005). The median number of checklist errors for the electronic checklist was 5, while the median number of checklist errors for the paper checklist was 8 (P = .003). The time to checklist completion was not significantly different between the 2 checklist formats (P = .76). CONCLUSION: The electronic checklist significantly reduced provider workload and errors without any measurable difference in the amount of time required for checklist completion. This demonstrates that electronic checklists are feasible and desirable in the ICU setting.

Testing modes of computerized sepsis alert notification delivery systems.

BACKGROUND: The number of electronic health record (EHR)-based notifications continues to rise. One common method to deliver urgent and emergent notifications (alerts) is paging. Despite of wide presence of smartphones, the use of these devices for secure alerting remains a relatively new phenomenon. METHODS: We compared three methods of alert delivery (pagers, EHR-based notifications, and smartphones) to determine the best method of urgent alerting in the intensive care unit (ICU) setting. ICU clinicians received randomized automated sepsis alerts: pager, EHR-based notification, or a personal smartphone/tablet device. Time to notification acknowledgement, fatigue measurement, and user preferences (structured survey) were studied. RESULTS: Twenty three clinicians participated over the course of 3 months. A total of 48 randomized sepsis alerts were generated for 46 unique patients. Although all alerts were acknowledged, the primary outcome was confounded by technical failure of alert delivery in the smartphone/tablet arm. Median time to acknowledgment of urgent alerts was shorter by pager (102 mins) than EHR (169 mins). Secondary outcomes of fatigue measurement and user preference did not demonstrate significant differences between these notification delivery study arms. CONCLUSIONS: Technical failure of secure smartphone/tablet alert delivery presents a barrier to testing the optimal method of urgent alert delivery in the ICU setting. Results from fatigue evaluation and user preferences for alert delivery methods were similar in all arms. Further investigation is thus necessary to understand human and technical barriers to implementation of commonplace modern technology in the hospital setting.

Information Needs Assessment for a Medicine Ward-Focused Rounding Dashboard.

To identify the routine information needs of inpatient clinicians on the general wards for the development of an electronic dashboard. Survey of internal medicine and subspecialty clinicians from March 2014-July 2014 at Saint Marys Hospital in Rochester, Minnesota. An information needs assessment was generated from all unique data elements extracted from all handoff and rounding tools used by clinicians in our ICUs and general wards. An electronic survey was distributed to 104 inpatient medical providers. 89 unique data elements were identified from currently utilized handoff and rounding instruments. All data elements were present in our multipurpose ICU-based dashboard. 42 of 104 (40 %) surveys were returned. Data elements important (50/89, 56 %) and unimportant (24/89, 27 %) for routine use were identified. No significant differences in data element ranking were observed between supervisory and nonsupervisory roles. The routine information needs of general ward clinicians are a subset of data elements used routinely by ICU clinicians. Our findings suggest an electronic dashboard could be adapted from the critical care setting to the general wards with minimal modification.

Impact of the Electronic Medical Record on Mortality, Length of Stay, and Cost in the Hospital and ICU: A Systematic Review and Metaanalysis.

OBJECTIVE: To evaluate effects of health information technology in the inpatient and ICU on mortality, length of stay, and cost. Methodical evaluation of the impact of health information technology on outcomes is essential for institutions to make informed decisions regarding implementation. DATA SOURCES: EMBASE, Scopus, Medline, the Cochrane Review database, and Web of Science were searched from database inception through July 2013. Manual review of references of identified articles was also completed. STUDY SELECTION: Selection criteria included a health information technology intervention such as computerized physician order entry, clinical decision support systems, and surveillance systems, an inpatient setting, and endpoints of mortality, length of stay, or cost. Studies were screened by three reviewers. Of the 2,803 studies screened, 45 met selection criteria (1.6%). DATA EXTRACTION: Data were abstracted on the year, design, intervention type, system used, comparator, sample sizes, and effect on outcomes. Studies were abstracted independently by three reviewers. DATA SYNTHESIS: There was a significant effect of surveillance systems on in-hospital mortality (odds ratio, 0.85; 95% CI, 0.76-0.94; I=59%). All other quantitative analyses of health information technology interventions effect on mortality and length of stay were not statistically significant. Cost was unable to be quantitatively evaluated. Qualitative synthesis of studies of each outcome demonstrated significant study heterogeneity and small clinical effects. CONCLUSIONS: Electronic interventions were not shown to have a substantial effect on mortality, length of stay, or cost. This may be due to the small number of studies that were able to be aggregately analyzed due to the heterogeneity of study populations, interventions, and endpoints. Better evidence is needed to identify the most meaningful ways to implement and use health information technology and before a statement of the effect of these systems on patient outcomes can be made.

Predictors of Delayed Postoperative Respiratory Depression Assessed from Naloxone Administration.

BACKGROUND: The aim of this study was to identify patient and procedural characteristics associated with postoperative respiratory depression or sedation requiring naloxone intervention. METHODS: We identified patients who received naloxone to reverse opioid-induced respiratory depression or sedation within 48 hours after discharge from anesthetic care (transfer from the postanesthesia care unit or transfer from the operating room to postoperative areas) between July 1, 2008, and June 30, 2010. Patients were matched to 2 control subjects based on age, sex, and exact type of procedure performed during the same year. A chart review was performed to identify patient, anesthetic, and surgical factors that may be associated with risk for intervention requiring naloxone. In addition, we identified all patients who developed adverse respiratory events (hypoventilation, apnea, oxyhemoglobin desaturation, pain/sedation mismatch) during phase 1 anesthesia recovery. We performed conditional logistic regression taking into account the 1:2 matched set case-control study design to assess patient and procedural characteristics associated with naloxone use. RESULTS: We identified 134 naloxone administrations, 58% within 12 hours of discharge from anesthesia care, with an incidence of 1.6 per 1000 (95% confidence interval [CI], 1.3-1.9) anesthetics. The presence of obstructive sleep apnea (odds ratio [OR] = 2.45; 95% CI, 1.27-4.66; P = 0.008) and diagnosis of an adverse respiratory event in the postanesthesia recovery room (OR = 5.11; 95% CI, 2.32-11.27; P < 0.001) were associated with an increased risk for requiring naloxone to treat respiratory depression or sedation after discharge from anesthesia care. After discharge from anesthesia care, patients administered naloxone used a greater median dose of opioids (10 [interquartile range, 0-47.1] vs 5 [0-24.8] IV morphine equivalents, P = 0.020) and more medications with sedating side effects (n = 41 [31%] vs 24 [9%]; P < 0.001). CONCLUSIONS: Obstructive sleep apnea and adverse respiratory events in the recovery room are harbingers of increased risk for respiratory depression or sedation requiring naloxone after discharge from anesthesia care. Also, patients administered naloxone received more opioids and other sedating medications after discharge from anesthetic care. Our findings suggest that these patients may benefit from more careful monitoring after being discharged from anesthesia care.

Do patients in a medical or surgical ICU benefit from a neurologic consultation?

Neurological complications are common in general medical and surgical intensive care units (ICU); they can prolong ICU and hospital stay and worsen outcome, including mortality. We performed a descriptive analysis of neurological consultations in non-neurological ICUs to determine the frequency of various neurological complications and to assess the diagnostic yield, therapeutic implications and prognostic benefit of these consultations. This is a retrospective single group cohort study of all neurological consultations for patients admitted to non-neurological (medical, respiratory care unit, cardiac, cardiothoracic, surgical and trauma) ICUs at Saint Marys Hospital (Mayo Clinic, Rochester) over a 24-month period (01 January 2010 to 31 December 2011). Equal numbers of neurological consultations (174, 50% each) were requested from medical ICUs and surgical ICUs. Altered consciousness (158, 45%), seizure (76, 22%) and focal deficits (75, 22%) were the most common reasons for consultations. Diagnostic, prognostic and therapeutic benefit was considered present in 89%, 38% and 39% patients respectively. Treatment change following neurological consultation occurred in 48% patients. Encephalopathy, stroke, seizure and anoxic brain injury were the most common causes of neurological complications in non-neurological ICUs with sedatives and opiates being the most common cause of encephalopathy. Almost half of the patients had change in treatment following neurological consultation. Neurological consultations in non-neurological ICU's are beneficial for patient's care in terms of diagnosis, treatment and prognosis.