Our goal at Emergency Care Partners (ECP) is to improve patient experience and satisfaction by optimizing Emergency Department (ED) throughput, highlighting areas of opportunities that yield the biggest improvements, and assist in change management and implementation. If you would like to learn more about our approach with data or if you would like to discuss how we can help your emergency department, contact our team of experts.
Emergency Care Partner’s ability to integrate with a hospital’s EMR support our partners with the ability to better manage patient volume, optimize coverage, and evaluate provider productivity, therefore maximizing ED throughput efficiency. We are also able to assist with billing reconciliation, provide data quality improvements for accurate reporting and support implementation of patient census tracking. Process improvements are made possible by deploying the following resources:
Emergency Care Partner’s Senior Industrial Engineer, walks through and demonstrates a discrete event simulation model. The simulation was created leveraging the integrated EMR data from a partner group’s hospital.
Dr. Mark Laperouse, Chief Medical Officer at Professional Emergency Physician Associates (PEPA) talks about how they are leveraging data to customize solutions and improve outcomes in the emergency departments they serve.
Our process begins by focusing on 4 EMR data file exports: demographic, lab orders, radiology and caregiver. These 4 extracts, or flat files, are triggered to be sent daily which includes data from the past 3 days of runtime. Our team imports these files into our analytics platform to provide digestible and customizable reports.
This extract includes all individual process events that occur from the time the patient gets registered in the emergency department to the time they are discharged or admitted to the inpatient floor. Time-stamps are associated with patient flow depending upon acuity, disposition and chief complaint. These data points are then used to analyze and report various ED throughput metrics including but not limited to Length of Stay (LOS), Door to Provider, Door to Disposition, Door to Decision to Admit, Left Without Being Seen (LWBS). This methodology allows our partners to keep track of any trends and correlation between these overall KPIs and patient satisfaction scores. Patient arrival-time patterns by hour of the day and build-up in ED provide useful insights for both management and clinical leadership teams to evaluate any changes in the existing coverage and plan for future needs. Demographic data is integrated with the other EMR data file exports to provide a holistic view of the current state of the process metrics and visualize opportunities for improvements in the ED.
Our team of experts are able to integrate with various EMRs including but not limited to EPIC, Cerner, Meditech and McKesson. Our integration process is planned over 3 phases.
Phase 1 begins with the distribution of a specification document with a detailed description of each field in the EMR files requested from the hospital. Our team collaborates with the hospital integration team to discuss and resolve any issues or concerns related to the scope and requirements of the project before we kick-off to the next phase.
The received data is processed and validated daily through multiple checkpoints before it is uploaded into ECP’s data warehouse. Various sets of rules are built-in to flag any incorrect or erroneous data in new or existing records. These rules are defined under 2 broad categories depending upon their severity and use case for each facility.
These set of rules are built to restrict loading incorrect data in our database and would require manual intervention to understand what went wrong in the file. These issues could include but are not limited to data formatting, missing data, and missing files. Our data engineering team is notified in real time to resolve these conflicts and take appropriate measures to remedy the issues. In some cases, we share these findings with hospital leadership to make suggested changes in the files on their end to improve data efficiency.