Dataset Information

The Pediatric Emergency Care Applied Research Network Registry: A Multicenter Electronic Health Record Registry of Pediatric Emergency Care.

ABSTRACT:

Background

Electronic health record (EHR)-based registries allow for robust data to be derived directly from the patient clinical record and can provide important information about processes of care delivery and patient health outcomes.

Methods

A data dictionary, and subsequent data model, were developed describing EHR data sources to include all processes of care within the emergency department (ED). ED visit data were deidentified and XML files were created and submitted to a central data coordinating center for inclusion in the registry. Automated data quality control occurred prior to submission through an application created for this project. Data quality reports were created for manual data quality review.

Results

The Pediatric Emergency Care Applied Research Network (PECARN) Registry, representing four hospital systems and seven EDs, demonstrates that ED data from disparate health systems and EHR vendors can be harmonized for use in a single registry with a common data model. The current PECARN Registry represents data from 2,019,461 pediatric ED visits, 894,503 distinct patients, more than 12.5 million narrative reports, and 12,469,754 laboratory tests and continues to accrue data monthly.

Conclusion

The Registry is a robust harmonized clinical registry that includes data from diverse patients, sites, and EHR vendors derived via data extraction, deidentification, and secure submission to a central data coordinating center. The data provided may be used for benchmarking, clinical quality improvement, and comparative effectiveness research.

SUBMITTER: Deakyne Davies SJ

PROVIDER: S-EPMC5966304 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Pediatric Emergency Care Applied Research Network Registry: A Multicenter Electronic Health Record Registry of Pediatric Emergency Care.

Deakyne Davies Sara J SJ Grundmeier Robert W RW Campos Diego A DA Hayes Katie L KL Bell Jamie J Alessandrini Evaline A EA Bajaj Lalit L Chamberlain James M JM Gorelick Marc H MH Enriquez Rene R Casper T Charles TC Scheid Beth B Kittick Marlena M Dean J Michael JM Alpern Elizabeth R ER

Applied clinical informatics 20180401 2

<h4>Background</h4>Electronic health record (EHR)-based registries allow for robust data to be derived directly from the patient clinical record and can provide important information about processes of care delivery and patient health outcomes.<h4>Methods</h4>A data dictionary, and subsequent data model, were developed describing EHR data sources to include all processes of care within the emergency department (ED). ED visit data were deidentified and XML files were created and submitted to a ce ...[more]

PMID: 29791930

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Project description:ImportanceComputed tomographic (CT) scanning is the standard for the rapid diagnosis of intracranial injury, but it is costly and exposes patients to ionizing radiation. The Pediatric Emergency Care Applied Research Network (PECARN) rules for identifying children with minor head trauma who are at very low risk of clinically important traumatic brain injury (ciTBI) are widely used to triage CT imaging.ObjectiveTo examine whether optimal classification trees (OCTs), which are novel machine-learning classifiers, improve on PECARN rules' predictive accuracy.Design, setting, and participantsA secondary analysis of prospective, publicly available data on emergency department visits for head trauma used by the PECARN group to develop their tool was conducted to derive OCT-based prediction rules for ciTBI in a development cohort and compare their predictive performance vs the PECARN rules in a validation cohort among children who were younger than 2 years and 2 years or older. Data on 42 412 children with head trauma and without severely altered mental status who were examined between June 1, 2004, and September 30, 2006, were gathered from 25 emergency departments in North America participating in PECARN. Data analysis was conducted from September 15, 2016, to December 18, 2018.Main outcomes and measuresThe outcome was ciTBI, with predictive performance measured by estimating the sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio for the OCT and the PECARN rules. The OCT and PECARN rules' performance was compared by estimating ratios for each measure.ResultsOf the 42 412 children (15 996 [37.7%] girls) included in the analysis, 10 718 were younger than 2 years (25.3%; mean [SD] age, 11.6 [0.6] months) and 31 694 were 2 years or older (74.7%; age, 9.1 [4.9] years). Compared with PECARN rules, OCTs misclassified 0 vs 1 child with ciTBI in the younger and 10 vs 9 children with ciTBI in the older cohort, and correctly identified more children with very low risk of ciTBI in the younger (7605 vs 5701) and older (20 594 vs 18 134) cohorts. In the validation cohorts, compared with the PECARN rules, the OCTs had statistically significantly better specificity (in the younger cohort: 69.3%; 95% CI, 67.4%-71.2% vs 52.8%; 95% CI, 50.8%-54.9%; in the older cohort: 65.6%; 95% CI, 64.5%-66.8% vs 57.6%; 95% CI, 56.4%-58.8%), positive predictive value (odds ratios, 1.54; 95% CI, 1.36-1.74 and 1.23; 95% CI, 1.17-1.30, in younger and older children, respectively), and positive likelihood ratio (risk ratios, 1.54; 95% CI, 1.36-1.74 and 1.23; 95% CI, 1.17-1.30, in younger and older children, respectively). There were no statistically significant differences in the sensitivity, negative predictive value, and negative likelihood ratio between the 2 sets of rules.Conclusions and relevanceIf implemented, OCTs may help reduce the number of unnecessary CT scans, without missing more patients with ciTBI than the PECARN rules.

Project description:ObjectivesIndividual-level social needs have been shown to substantially impact emergency department (ED) care transitions of older adults. The Geriatric Emergency care Applied Research (GEAR) Network aimed to identify care transition interventions, particularly addressing social needs, and prioritize future research questions.MethodsGEAR engaged 49 interdisciplinary stakeholders, derived clinical questions, and conducted searches of electronic databases to identify ED discharge care transition interventions in older adult populations. Informed by the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE) framework, data extraction and synthesis of included studies included the degree that intervention components addressed social needs and their association with patient outcomes. GEAR convened a consensus conference to identify topics of highest priority for future care transitions research.ResultsOur search identified 248 unique articles addressing care transition interventions in older adult populations. Of these, 17 individual care transition intervention studies were included in the current literature synthesis. Overall, common care transition interventions included coordination efforts, comprehensive geriatric assessments, discharge planning, and telephone or in-person follow-up. Fourteen of the 17 care transition intervention studies in older adults specifically addressed at least one social need within the PRAPARE framework, most commonly related to access to food, medicine, or health care. No care transition intervention addressing social needs in older adult populations consistently reduced subsequent health care utilization or other patient-centered outcomes. GEAR stakeholders identified that determining optimal outcome measures for ED-home transition interventions was the highest priority area for future care transitions research.ConclusionsED care transition intervention studies in older adults frequently address at least one social need component and exhibit variation in the degree of success on a wide array of health care utilization outcomes.

Project description:BackgroundOlder adult delirium is often unrecognized in the emergency department (ED), yet the most compelling research questions to overcome knowledge-to-practice deficits remain undefined. The Geriatric Emergency care Applied Research (GEAR) Network was organized to identify and prioritize delirium clinical questions.MethodsGEAR identified and engaged 49 transdisciplinary stakeholders including emergency physicians, geriatricians, nurses, social workers, pharmacists, and patient advocates. Adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews, clinical questions were derived, medical librarian electronic searches were conducted, and applicable research evidence was synthesized for ED delirium detection, prevention, and management. The scoping review served as the foundation for a consensus conference to identify the highest priority research foci.ResultsIn the scoping review, 27 delirium detection "instruments" were described in 48 ED studies and used variable criterion standards with the result of delirium prevalence ranging from 6% to 38%. Clinician gestalt was the most common "instrument" evaluated with sensitivity ranging from 0% to 81% and specificity from 65% to 100%. For delirium management, 15 relevant studies were identified, including one randomized controlled trial. Some intervention studies targeted clinicians via education and others used clinical pathways. Three medications were evaluated to reduce or prevent ED delirium. No intervention consistently prevented or treated delirium. After reviewing the scoping review results, the GEAR stakeholders identified ED delirium prevention interventions not reliant on additional nurse or physician effort as the highest priority research.ConclusionsTransdisciplinary stakeholders prioritize ED delirium prevention studies that are not reliant on health care worker tasks instead of alternative research directions such as defining etiologic delirium phenotypes to target prevention or intervention strategies.

Project description:ObjectivesTo describe the Children's Hospital Association's Improving Pediatric Sepsis Outcomes sepsis definitions and the identified patients; evaluate the definition using a published framework for evaluating sepsis definitions.DesignObservational cohort.SettingMulticenter quality improvement collaborative of 46 hospitals from January 2017 to December 2018, excluding neonatal ICUs.PatientsImproving Pediatric Sepsis Outcomes Sepsis was defined by electronic health record evidence of suspected infection and sepsis treatment or organ dysfunction. A more severely ill subgroup, Improving Pediatric Sepsis Outcomes Critical Sepsis, was defined, approximating septic shock.InterventionsParticipating hospitals identified patients, extracted data, and transferred de-identified data to a central data warehouse. The definitions were evaluated across domains of reliability, content validity, construct validity, criterion validity, measurement burden, and timeliness.Measurements and main resultsForty hospitals met data quality criteria across four electronic health record platforms. There were 23,976 cases of Improving Pediatric Sepsis Outcomes Sepsis, including 8,565 with Improving Pediatric Sepsis Outcomes Critical Sepsis. The median age was 5.9 years. There were 10,316 (43.0%) immunosuppressed or immunocompromised patients, 4,135 (20.3%) with central lines, and 2,352 (11.6%) chronically ventilated. Among Improving Pediatric Sepsis Outcomes Sepsis patients, 60.8% were admitted to intensive care, 26.4% had new positive-pressure ventilation, and 19.7% received vasopressors. Median hospital length of stay was 6.0 days (3.0-13.0 d). All-cause 30-day in-hospital mortality was 958 (4.0%) in Improving Pediatric Sepsis Outcomes Sepsis; 541 (6.3%) in Improving Pediatric Sepsis Outcomes Critical Sepsis. The Improving Pediatric Sepsis Outcomes Sepsis definitions demonstrated strengths in content validity, convergent construct validity, and criterion validity; weakness in reliability. Improving Pediatric Sepsis Outcomes Sepsis definitions had significant initial measurement burden (median time from case completion to submission: 15 mo [interquartile range, 13-18 mo]); timeliness improved once data capture was established (median, 26 d; interquartile range, 23-56 d).ConclusionsThe Improving Pediatric Sepsis Outcomes Sepsis definitions demonstrated feasibility for large-scale data abstraction. The patients identified provide important information about children treated for sepsis. When operationalized, these definitions enabled multicenter identification and data aggregation, indicating practical utility for quality improvement.

Dataset Information

The Pediatric Emergency Care Applied Research Network Registry: A Multicenter Electronic Health Record Registry of Pediatric Emergency Care.

Background

Methods

Results

Conclusion

Publications

The Pediatric Emergency Care Applied Research Network Registry: A Multicenter Electronic Health Record Registry of Pediatric Emergency Care.

Similar Datasets

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