Obstetric anaesthesia practice: Dashboard as a dynamic audit tool

How Do We Use Dashboards to Enhance Quality in Cardiac Anesthesia?

The use of clinical dashboards has expanded significantly in healthcare in recent years in a variety of settings. The ability to analyze data related to quality metrics in one screen is highly desirable for cardiac anesthesiologists, as they have considerable influence on important clinical outcomes. Building a robust quality program within cardiac anesthesia relies on consistent access and review of quality outcome measures, process measures, and operational measures through a clinical dashboard. Signals and trends in these measures may be compared to other cardiac surgical programs to analyze gaps and areas for quality improvement efforts. In this article, the authors describe how they designed a clinical cardiac anesthesia dashboard for quality efforts at their institution.

A Dashboard for Tracking Mortality After Cardiac Surgery Using a National Administrative Database

BACKGROUND

Mortality after cardiac surgery is publicly reportable and used as a quality metric by national organizations. However, detailed institutional comparisons are often limited in publicly reported ratings, while publicly reported mortality data are generally limited to 30-day outcomes. Dashboards represent a useful method for aggregating data to identify areas for quality improvement.

METHODS

We present the development of a dashboard of cardiac surgery performance using cardiac surgery admissions in a national administrative dataset, allowing institutions to better analyze their clinical outcomes. We identified cardiac surgery admissions in the Medicare Limited Data Sets from April 2016 to March 2017 using diagnosis-related group (DRG) codes for cardiac valve and coronary bypass surgeries.

RESULTS

Using these data, we created a dashboard prototype to enable hospitals to compare their individual performance against state and national benchmarks, by all cardiac surgeries, specific cardiac surgery DRGs and by specific surgeons. Mortality rates are provided at 30, 60 and 90 days post-operatively as well as 1 year. Users can filter results by state, hospital and surgeon, and visualize summary data comparing these filtered results to national metrics. Examples of using the dashboard to examine hospital and individual surgeon mortality are provided.

CONCLUSIONS

We demonstrate how this database can be used to compare data between comparator hospitals on local, state and national levels to identify trends in mortality and areas for quality improvement.

Development, implementation and preliminary evaluation of clinical dashboards in a department of anesthesia

Clinical dashboards summarize indicators of high-volume patient data in a concise, user-friendly visual format. There are few studies of the use of dashboards to improve professional practice in anesthesiology. The objective of the present study was to describe the user-centered development, implementation and preliminary evaluation of clinical dashboards dealing with anesthesia unit management and quality assessment in a French university medical center. User needs and technical requirements were identified in end user interviews and then synthesized. Several representations were then developed (according to good visualization practice) and submitted to end users for appraisal. Lastly, dashboards were implemented and made accessible for everyday use via the medical center’s network. After a period of use, end user feedback on the dashboard platform was collected as a system usability score (range 0 to 100). Seventeen themes (corresponding to 29 questions and 42 indicators) were identified. After prioritization and feasibility assessment, 10 dashboards were ultimately implemented and deployed. The dashboards variously addressed the unit’s overall activity, compliance with guidelines on intraoperative hemodynamics, ventilation and monitoring, and documentation of the anesthesia procedure. The mean (standard deviation) system usability score was 82.6 (11.5), which corresponded to excellent usability. We developed clinical dashboards for a university medical center’s anesthesia units. The dashboards’ deployment was well received by the center’s anesthesiologists. The dashboards’ impact on activity and practice after several months of use will now have to be assessed.

An Automated Fast Healthcare Interoperability Resources-Based 12-Lead Electrocardiogram Mobile Alert System for Suspected Acute Coronary Syndrome

PURPOSE

For patients with time-critical acute coronary syndrome, reporting electrocardiogram (ECG) findings is the most important component of the treatment process. We aimed to develop and validate an automated Fast Healthcare Interoperability Resources (FHIR)-based 12-lead ECG mobile alert system for use in an emergency department (ED).

MATERIALS AND METHODS

An automated FHIR-based 12-lead ECG alert system was developed in the ED of an academic tertiary care hospital. The system was aimed at generating an alert for patients with suspected acute coronary syndrome based on interpretation by the legacy device. The alert is transmitted to physicians both via a mobile application and the patient's electronic medical record (EMR). The automated FHIR-based 12-lead ECG alert system processing interval was defined as the time from ED arrival and 12-lead ECG capture to the time when the FHIR-based notification was transmitted.

RESULTS

During the study period, 3812 emergency visits and 1581 12-lead ECGs were recorded. The FHIR system generated 155 alerts for 116 patients. The alerted patients were significantly older [mean (standard deviation): 68.1 (12.4) years vs. 59.6 (16.8) years, p<0.001], and the cardiac-related symptom rate was higher (34.5% vs. 19%, p<0.001). Among the 155 alerts, 146 (94%) were transmitted successfully within 5 minutes. The median interval from 12-lead ECG capture to FHIR notification was 2.7 min [interquartile range (IQR) 2.2-3.1 min] for the group with cardiac-related symptoms and 3.0 min (IQR 2.5-3.4 min) for the group with non-cardiac-related symptoms.

CONCLUSION

An automated FHIR-based 12-lead ECG mobile alert system was successfully implemented in an ED.