RSNA: Dashboards driving toward a culture of accountability
CHICAGO--Digital dashboards help radiology practices keep their eyes on the road by providing information to help decision makers and stakeholders understand and adapt the practice, explained Paul Nagy, PhD, associate professor of diagnostic radiology and nuclear medicine in the department of diagnostic imaging at the University of Maryland in Baltimore, at the annual Radiological Society of North America (RSNA) meeting.
Nagy started with a brief description of business intelligence in the pre-information age. In the 20th century, businesses made decisions with relatively little information.
Fast forward to 2006, or the dawn of the age of analytics. Today, said Nagy, information is heavily available. Some practices, however, remain entrenched in the reactive business intelligence mode. That is, they make business decisions based on outdated information such as last month’s CT wait time.
In contrast, Nagy introduced mature business intelligence, which relies on statistical analysis and predictive modeling to inform decisions. How do radiology practices transition to mature business intelligence? They need data from multiple sources including RIS, PACS, speech recognition and order entry systems. Data is placed in a data warehouse and pulled for graphic display on a digital dashboard. The dashboard provides a quick overview of key performance indicators, which Nagy termed "decision support for management."
An effective dashboard requires three types of metrics—volume, performance and quality. The department of diagnostic imaging at the University of Maryland houses its metrics in a homegrown data warehouse to provide a transparent view of the department for all key players, which fosters a culture of accountability. “We need this culture to raise awareness about our problems and align key players to solve the problems of radiology,” states Nagy. This approach helps the department ask and answer questions about trends and patterns of practices within a few minutes.
Nagy closed with a bit of good news for his colleagues. Although his pioneering department had to take a homegrown approach with its dashboard, radiology vendors have recognized the advantages of the model and are moving in the right direction with new dashboard solutions.
Nagy started with a brief description of business intelligence in the pre-information age. In the 20th century, businesses made decisions with relatively little information.
Fast forward to 2006, or the dawn of the age of analytics. Today, said Nagy, information is heavily available. Some practices, however, remain entrenched in the reactive business intelligence mode. That is, they make business decisions based on outdated information such as last month’s CT wait time.
In contrast, Nagy introduced mature business intelligence, which relies on statistical analysis and predictive modeling to inform decisions. How do radiology practices transition to mature business intelligence? They need data from multiple sources including RIS, PACS, speech recognition and order entry systems. Data is placed in a data warehouse and pulled for graphic display on a digital dashboard. The dashboard provides a quick overview of key performance indicators, which Nagy termed "decision support for management."
An effective dashboard requires three types of metrics—volume, performance and quality. The department of diagnostic imaging at the University of Maryland houses its metrics in a homegrown data warehouse to provide a transparent view of the department for all key players, which fosters a culture of accountability. “We need this culture to raise awareness about our problems and align key players to solve the problems of radiology,” states Nagy. This approach helps the department ask and answer questions about trends and patterns of practices within a few minutes.
Nagy closed with a bit of good news for his colleagues. Although his pioneering department had to take a homegrown approach with its dashboard, radiology vendors have recognized the advantages of the model and are moving in the right direction with new dashboard solutions.