A surveillance system to assess the need for updating systematic reviews.

BackgroundSystematic reviews (SRs) can become outdated as new evidence emerges over time. Organizations that produce SRs need a surveillance method to determine when reviews are likely to require updating. This report describes the development and initial results of a surveillance system to assess SRs produced by the Agency for Healthcare Research and Quality (AHRQ) Evidence-based Practice Center (EPC) Program.MethodsTwenty-four SRs were assessed using existing methods that incorporate limited literature searches, expert opinion, and quantitative methods for the presence of signals triggering the need for updating. The system was designed to begin surveillance six months after the release of the original review, and then ceforth every six months for any review not classified as being a high priority for updating. The outcome of each round of surveillance was a classification of the SR as being low, medium or high priority for updating.ResultsTwenty-four SRs underwent surveillance at least once, and ten underwent surveillance a second time during the 18 months of the program. Two SRs were classified as high, five as medium, and 17 as low priority for updating. The time lapse between the searches conducted for the original reports and the updated searches (search time lapse - STL) ranged from 11 months to 62 months: The STL for the high priority reports were 29 months and 54 months; those for medium priority reports ranged from 19 to 62 months; and those for low priority reports ranged from 11 to 33 months. Neither the STL nor the number of new relevant articles was perfectly associated with a signal for updating. Challenges of implementing the surveillance system included determining what constituted the actual conclusions of an SR that required assessing; and sometimes poor response rates of experts.ConclusionIn this system of regular surveillance of 24 systematic reviews on a variety of clinical interventions produced by a leading organization, about 70% of reviews were determined to have a low priority for updating. Evidence suggests that the time period for surveillance is yearly rather than the six months used in this project

Barriers to point-of-care ultrasound utilization during cardiac arrest in the emergency department: a regional survey of emergency physicians

Though point-of-care ultrasound (POCUS) is recognized as a useful diagnostic and prognostic intervention during cardiac arrest (CA), critics advise caution. The purpose of this survey study was to determine the barriers to POCUS during CA in the Emergency Department (ED). Two survey instruments were distributed to emergency medicine (EM) attending and resident physicians at three academic centers in the South Florida. The surveys assessed demographics, experience, proficiency, attitudes and barriers. Descriptive and inferential statistics along with Item Response Theory Logistic Model and the Friedman Test with Wilcoxon Signed Rank tests were used to profile responses and rank barriers. 206 EM physicians were invited to participate in the survey, and 187 (91%) responded. 59% of attending physicians and 47% of resident physicians reported that POCUS is performed in all their cases of CA. 5% of attending physicians and 0% of resident physicians reported never performing POCUS during CA. The top-ranked departmental barrier for attending physicians was “No structured curriculum to educate physicians on POCUS.” The top-ranked personal barriers were “I do not feel comfortable with my POCUS skills” and “I do not have sufficient time to dedicate to learning POCUS.” The top-ranked barriers for resident physicians were “Time to retrieve and operate the machine” and “Chaotic milieu.” While our study demonstrates that most attending and resident physicians utilize POCUS in CA, barriers to high-quality implementation exist. Top attending physician barriers relate to POCUS education, while the top resident physician barriers relate to logistics and the machines. Interventions to overcome these barriers might lead to optimization of POCUS performance during CA in the ED

Data from: Reducing early infant mortality in India: results of a prospective cohort of pregnant women utilizing emergency medical services

Objectives: To describe the demographic characteristics and clinical outcomes of neonates born within 7 days of public ambulance transport to hospitals across five states in India. Design: Prospective observational study. Setting: Five Indian states using a centralised EMS agency that transported 3.1 million pregnant women in 2014. Participants: Over 6 weeks in 2014, this study followed a convenience sample of 1,431 neonates born to women utilizing a public-private ambulance service for a ‘pregnancy related’ problem. Initial calls were deemed ‘pregnancy related’ if categorised by EMS dispatchers as ‘pregnancy’, ‘childbirth’, ‘miscarriage’ or ‘labour pains’. Interfacility transfers, patients absent on ambulance arrival, refusal of care, and neonates born to women beyond 7 days of using the service were excluded. Main outcome measures: Death at 2, 7 and 42 days after delivery. Results: Among 1,684 women, 1,411 gave birth to 1,431 newborns within 7 days of initial ambulance transport. Median maternal age at delivery was 23 years (IQR: 21-25). Most mothers were from rural/tribal areas (92.5%) and lower social (79.9%) and economic status (69.9%). Follow-up rates at 2, 7 and 42 days were 99.8%, 99.3% and 94.1%, respectively. Cumulative mortality rates at 2, 7 and 42-days follow-up were 41, 53 and 62 per 1000 births, respectively. The perinatal mortality rate (PMR) was 53 per 1000. Preterm birth [OR: 2.89, 95% CI: 1.67-5.00], twin deliveries (OR: 2.80, 95% CI: 1.10-7.15), and cesarean section (2.21, 95% CI: 1.15-4.23) were the strongest predictors of mortality. Conclusions: The perinatal mortality rate associated with this cohort of patients with high-acuity conditions of pregnancy was nearly two times the most recent rate for India as a whole (28 per 1000 births). EMS data has the potential to provide more robust estimates of PMR, reduce inequities in timely access to healthcare, and increase facility-based care through service of marginalized populations

A surveillance system to assess the need for updating systematic reviews.

BackgroundSystematic reviews (SRs) can become outdated as new evidence emerges over time. Organizations that produce SRs need a surveillance method to determine when reviews are likely to require updating. This report describes the development and initial results of a surveillance system to assess SRs produced by the Agency for Healthcare Research and Quality (AHRQ) Evidence-based Practice Center (EPC) Program.MethodsTwenty-four SRs were assessed using existing methods that incorporate limited literature searches, expert opinion, and quantitative methods for the presence of signals triggering the need for updating. The system was designed to begin surveillance six months after the release of the original review, and then ceforth every six months for any review not classified as being a high priority for updating. The outcome of each round of surveillance was a classification of the SR as being low, medium or high priority for updating.ResultsTwenty-four SRs underwent surveillance at least once, and ten underwent surveillance a second time during the 18 months of the program. Two SRs were classified as high, five as medium, and 17 as low priority for updating. The time lapse between the searches conducted for the original reports and the updated searches (search time lapse - STL) ranged from 11 months to 62 months: The STL for the high priority reports were 29 months and 54 months; those for medium priority reports ranged from 19 to 62 months; and those for low priority reports ranged from 11 to 33 months. Neither the STL nor the number of new relevant articles was perfectly associated with a signal for updating. Challenges of implementing the surveillance system included determining what constituted the actual conclusions of an SR that required assessing; and sometimes poor response rates of experts.ConclusionIn this system of regular surveillance of 24 systematic reviews on a variety of clinical interventions produced by a leading organization, about 70% of reviews were determined to have a low priority for updating. Evidence suggests that the time period for surveillance is yearly rather than the six months used in this project

Defining High-risk Emergency Chief Complaints: Data-driven Triage for Low- and Middle-income Countries.

ObjectivesEmergency medicine in low- and middle-income countries (LMICs) is hindered by lack of research into patient outcomes. Chief complaints (CCs) are fundamental to emergency care but have only recently been uniquely codified for an LMIC setting in Uganda. It is not known whether CCs independently predict emergency unit patient outcomes.MethodsPatient data collected in a Ugandan emergency unit between 2009 and 2018 were randomized into validation and derivation data sets. A recursive partitioning algorithm stratified CCs by 3-day mortality risk in each group. The process was repeated in 10,000 bootstrap samples to create an averaged risk ranking. Based on this ranking, CCs were categorized as "high-risk" (>2× baseline mortality), "medium-risk" (between 2 and 0.5× baseline mortality), and "low-risk" (<0.5× baseline mortality). Risk categories were then included in a logistic regression model to determine if CCs independently predicted 3-day mortality.ResultsOverall, the derivation data set included 21,953 individuals with 7,313 in the validation data set. In total, 43 complaints were categorized, and 12 CCs were identified as high-risk. When controlled for triage data including age, sex, HIV status, vital signs, level of consciousness, and number of complaints, high-risk CCs significantly increased 3-day mortality odds ratio (OR = 2.39, 95% confidence interval [CI] = 1.95 to 2.93, p < 0.001) while low-risk CCs significantly decreased 3-day mortality odds (OR = 0.16, 95% CI = 0.09 to 0.29, p < 0.001).ConclusionsHigh-risk CCs were identified and found to predict increased 3-day mortality independent of vital signs and other data available at triage. This list can be used to expand local triage systems and inform emergency training programs. The methodology can be reproduced in other LMIC settings to reflect their local disease patterns