Channeling the Power of Imaging Data
In this era of data-driven healthcare, hospitals and healthcare systems are inundated with a continual flow of “raw material” that can potentially improve patient outcomes and drive more efficient, cost-effective care. Imaging, in particular, plays an integral role in diagnostic and treatment decision-making in almost every disease state, generating a wealth of data that has the potential to provide insights into optimizing the imaging cycle from start to finish. Yet, many radiology departments and practices are hindered by fragmented and disparate data from unintegrated sources and vendors, leading to wasted time and resources spent sifting through often unreliable and inaccurate data. Data that, if properly aggregated and analyzed, could identify opportunities for addressing operational inefficiencies, enhancing patient care, and promoting financial growth.
Enter intelligent analytics
Artificial intelligence (AI) and machine learning have become an integral part of healthcare; aggregating and analyzing data to pinpoint variations in care and assist in clinical decision-making. In combining the right analytical tools and human expertise, Chief Operating Officers, Imaging Directors, and Clinical Directors have the ability to access resources that can shed light on key imaging performance indicators such as protocols, dose, image quality, workflows, and scheduling. To further understand how data analytics and expert coaching can optimize an imaging department, it’s useful to examine how the right performance solutions and resources can generate actionable, factual data that can boost operations and enhance quality of care.
Improving operational efficiency
Despite the recent explosion of imaging utilization, coupled with major advances in information technology (IT), many imaging software systems remain nonintegrated and underutilized in imaging protocoling, resulting in repeat imaging, delays in diagnosis, and increases in radiation exposure.2 Combining artificial intelligence (AI) algorithms with expert expertise can help imaging operations to run more effectively and reduce variations in care that can lead to backlogged work flows and longer wait times for patients.
In one recent example, a private radiology practice in Germany, Radiomed, seeking to improve the operational efficiency and performance of its magnetic resonance (MR) capabilities, utilized a partner program that combined applied intelligence to help providers find and consolidate relevant data to help guide better business decisions for improved efficiency and patient care.3 The information generated by the program enabled the Radiomed team to identify where changes to their scheduling could accommodate increased imaging capacity, allowing the Radiomed team to make necessary changes to protocol and scheduling. This resulted in an increase of 36.5 percent exams per week, a 4-week reduction in patient wait times, and an estimated $320K increase in revenue per year.3
"We entered the project to improve MR performance, and what happened since then is beyond my expectations," says Dr. Christopher Ahlers, a radiologist at Radiomed in Wiesbaden, Germany. “We’ve been able to increase productivity while maintaining quality, and in some points improving quality because we now spend time on things we feel are most important.”3
It’s well documented that care variation may lead to costly and unnecessary errors, delays and bottlenecks in patient care, as well as wasted resources and suboptimal quality of care. The introduction of data analytics with enhanced human expertise, as shown in the Radiomed example, has the potential to make imaging operations more streamlined and responsive to patients’ needs. In addition, standardized and optimized protocols can also help in complying with regulatory guidelines for dose management while maintaining image quality. This is of particular importance in hospital imaging departments since The Efficient Use of Medical Imaging is one of 7 key measurement groups used by Medicare to calculate a hospital’s overall rating reported on its Hospital Compare website.4
Improving Staff Performance and Driving Financial Growth
Reducing variations in equipment usage can also contribute to an improved return on investment and better scheduling, resulting in increased patient volumes, more satisfied patients, and increased referrals. From a staff perspective, standardized clinical protocols and best practices in workflow design can increase team collaboration, improve performance, and allow for assessments of training needs that can improve the quality of services delivered to patients. Data insights can also help benchmark trends in equipment mix and utilization, optimizing asset use and aiding in capital planning.
A model for achieving data-driven insights
What has been shown is an example of a comprehensive, vendor agnostic program that combines the power of real-time analytics, using protocol data collected automatically from imaging devices, bringing together key information regarding equipment utilization, dose levels, staff performance, patient experience, and physician referrals. Through dynamic and connected dashboards, imaging directors and clinical directors and managers can regularly view key performance indicators organized by modality, site, and department, enabling
- The ability to pinpoint inefficiencies and help plan for critical unanticipated variables and outliers as they arise
- The facilitation of daily work operations, allowing more time to be spent with the patients
- Financial growth opportunities due to streamlined protocols, leading to greater patient volume and optimized equipment usage
In addition, ongoing coaching from technical experts can also help to interpret the data, making it more actionable, as well as providing follow-up on performance actions and initiatives.
Understanding the story the data Is telling
In creating visibility from a unified and comprehensive series of dashboards, imaging departments can reliably utilize actionable insights across a series of performance indicators and assets. Given the explosion in imaging utilization, coupled with the growing role of data analytics and AI in healthcare, a partnership with a comprehensive program that can illuminate the right data needed to uncover opportunities for improving imaging performance and clinical outcomes, imaging departments and practices can take important steps in truly understanding the power of their data.
- Artificial Intelligence in Radiology, Nature Reviews, Cancer, August 2018. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6268174/ Accessed January 20, 2020.
- Informatics Solutions for Driving an Effective and Efficient Radiology Practice, ©RSNA, 2018. https://pubs.rsna.org/doi/full/10.1148/rg.2018180037 Accessed January 20, 2020.
- Imaging Insights, GE Healthcare, 2018 General Electric Company. https://www.gehealthcare.com/products/imaging-insights Accessed January 20, 2020.
- gov Hospital Compare, Hospital Compare Overall Hospital Rating, 2018. https://www.medicare.gov/hospitalcompare/Data/Measure-groups.html Accessed January 20, 2020.