Related Experiment Video
Updated: Feb 22, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Developing risk management dashboards using risk and quality measures: A visual best practices approach
Robert F Bunting1, Dana Siegal2
130 years of health care experience in risk management, quality improvement, data analytics, and laboratory science.
Healthcare quality measures are not a complete substitute for comprehensive risk management. A robust approach integrates quality measures, risk measures, and other metrics for effective enterprise risk management programs.
Area of Science:
- Healthcare Management
- Risk Management
- Health Informatics
Background:
- Quality measures are frequently used as a proxy for risk management in healthcare.
- However, quality measures alone are insufficient for comprehensive risk management.
- A gap exists in fully evaluating enterprise risk management (ERM) effectiveness.
Purpose of the Study:
- To differentiate between quality measures and risk management measures.
- To propose a comprehensive framework for evaluating ERM programs.
- To provide guidance on selecting and visualizing key performance indicators for risk management.
Main Methods:
- Literature review of existing quality and risk measures.
- Conceptualization of a multi-faceted approach to risk management measurement.
- Development of principles for dashboard design and visual best practices.
Main Results:
- Quality measures capture only certain aspects of risk management.
- A comprehensive strategy requires integrating quality measures, risk measures, and other unclassified metrics.
- Effective ERM evaluation hinges on identifying informative measures and optimal dashboard design.
Conclusions:
- Relying solely on quality measures for risk management is inadequate.
- A blended approach incorporating diverse measures is essential for robust ERM.
- Strategic dashboard design and visualization are critical for assessing ERM program value.
Related Concept Videos
Run Charts
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
Guidelines and Strategies for Safe Computer Charting
Maintain Confidentiality and Security:
Interpreting R Charts
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
Interpreting Run Charts
The R Chart
R charts are pivotal for pinpointing shifts in process variability. Stability is indicated when all data points remain within the defined upper and lower...

