A Provider-Focused Intervention to Promote Optimal Care of Pediatric Patients With Suspected Elbow Fracture.

OBJECTIVE: Emergency department (ED) and urgent care (UC) physicians' accurate assessment of the neurovascular and musculoskeletal (NV/MSK) examination in pediatric patients with suspected elbow fracture is crucial to the early recognition of neurovascular compromise. Our objective was to determine the impact of computer-based simulation (CBS) and computerized clinical decision support systems (CCDSS) on ED and UC physicians' assessment of the NV/MSK examination of pediatric patients with elbow fracture as noted in their documentation. METHODS: All ED UC physician participants received CBS training about management of pediatric patients with suspected elbow fracture. Participants were then randomized to receive CCDSS (intervention arm) when an eligible patient was seen or no further intervention (comparison arm.) Participants received feedback on the proportion of patients with discharge diagnosis of elbow fracturewith proper examination elements documented. RESULTS: Twenty-eight ED and UC physicians were enrolled - 14 in each arm. Over the span of 16 weeks, 50 patients with a discharge diagnosis of elbow fracture were seen - 25 in each arm. Twenty-two of 25 (88%) patients seen by intervention arm participants had a complete NV/MSK examination documented. Six of 25 (24%) patients seen by comparison arm participants had a complete NV/MSK examination documented. Elements most commonly missed in the comparison arm included documentation of ulnar pulse as well as radial, median, and ulnar nerve motor functions. CONCLUSIONS: Compared with single CBS training alone, repeated exposure to CCDSS after CBS training resulted in improved documentation of the NV/MSK status of pediatric patients with elbow fracture.

Implementation of a learning healthcare system for sickle cell disease.

OBJECTIVE: Using sickle cell disease (SCD) as a model, the objective of this study was to create a comprehensive learning healthcare system to support disease management and research. A multidisciplinary team developed a SCD clinical data dictionary to standardize bedside data entry and inform a scalable environment capable of converting complex electronic healthcare records (EHRs) into knowledge accessible in real time. MATERIALS AND METHODS: Clinicians expert in SCD care developed a data dictionary to describe important SCD-associated health maintenance and adverse events. The SCD data dictionary was deployed in the EHR using EPIC SmartForms, an efficient bedside data entry tool. Additional data elements were extracted from the EHR database (Clarity) using Pentaho Data Integration and stored in a data analytics database (SQL). A custom application, the Sickle Cell Knowledgebase, was developed to improve data analysis and visualization. Utilization, accuracy, and completeness of data entry were assessed. RESULTS: The SCD Knowledgebase facilitates generation of patient-level and aggregate data visualization, driving the translation of data into knowledge that can impact care. A single patient can be selected to monitor health maintenance, comorbidities, adverse event frequency and severity, and medication dosing/adherence. CONCLUSIONS: Disease-specific data dictionaries used at the bedside will ultimately increase the meaningful use of EHR datasets to drive consistent clinical data entry, improve data accuracy, and support analytics that will facilitate quality improvement and research.