Radiology is a complex service line. It is an ever-changing landscape fueled by ongoing hospital mergers and acquisitions, relentless downward pressure on reimbursement, the continued impact of the coronavirus pandemic on procedure volumes and deferred technology investments, and an industry shift toward enterprise imaging strategies. Value-based care initiatives have transformed many radiology departments and required leaders to scrutinize how their service line is managed.
Making matters even more challenging, imaging workflows are constantly disrupted: Stat cases interrupt scheduled orders, patients miss appointments, equipment needs to be taken out of service for repair and routine maintenance, and staff productivity varies widely because of caseload surges, complicated studies and other process inefficiencies.
A Modern Approach
Navigating this complex landscape requires that radiology administrators, clinicians and IT managers have access to data-driven decision-making tools that consolidate relevant historical and real-time data from the myriad of disparate systems and data siloes that typically exist. There are a number of data analytics applications available. However, most are not typically designed to tap into all those data silos — EHR, PACS, VNA, RIS, scheduling software, documentation systems, billing systems, and so on — and cohesively aggregate the meaningful information needed to illuminate operational inefficiencies and clinical roadblocks. In addition, these analytics applications typically require staff with specialized skills and do not offer real-time, self-service insights.
Envisioning the Ideal Solution
Medical imaging professionals agree about the ideal: A self-service, cloud-based solution that requires minimal training and implementation effort and can integrate insights from a wide range of disparate systems. For such a tool to be successful, it needs to embody several key attributes.
The solution must be intuitive to use, with minimal training for a large and diverse group of people. Department leads, radiologists and IT specialists are all well-educated and endure heavy workloads. They all have a vested interest in unlocking hidden insights from the data silos to continuously improve operations, patient care and system performance. These busy professionals will not embrace a platform that is too difficult to learn or cumbersome to use. They need a self-service solution that allows them to get in, get what they need and get out.
It must support data liquidity. According to Will Bryant, principal at Point B Direct, a staffing and recruiting firm, data liquidity is “the ability of data to flow throughout the healthcare system easily and securely.”1 For multidimensional visualization, data needs to be ubiquitously accessible, regardless of where it is stored. Users require a seamless experience without having to understand data flows, source systems and records.
For example, if a department administrator wants to analyze the average case interpretation time per radiologist, they should not need to know that the PACS logs study access per user, the dictation system timestamps clinical report production and the RIS tracks case assignments. They just want to run the query and let the system fetch and aggregate the data into intelligent results.
Human behavioral traits also need to be addressed to make a real difference. The platform needs to be widely adopted within the organization to affect positive change. Collaboration tools that help staff contribute to overall success and improvement creates a sense of inclusion and alignment that will yield better outcomes and increase buy-in across the organization.
Engagement throughout the entire radiology service line is also imperative. To positively stimulate self-development, radiologists should be able to access personal metrics that assess their performance and anonymously compare it to their peers. Additionally, management needs tools that produce engaging, actionable insights relevant for both clinical and operational staff. This can strengthen multidisciplinary teamwork and supports the common goal of improving clinical outcomes through continuous performance improvement.
A modern, multidimensional and intelligent analytics platform needs to conform to industry-standard patient privacy, security and data governance policies. Multiple layers of advanced cybersecurity protection are needed for a solution intended to data mine multiple mission-critical clinical and operational systems.
Stepwise Adoption
To successfully plan and implement a complex IT system, it is best to take a phased approach, beginning with the area that will make the largest impact on the organization. For a medical imaging enterprise analytics tool, it is ideal to tackle the operations functions first. Capturing actionable operational insights that justify improvements such as optimizing staff and patient scheduling, better modality utilization, and balancing physician workloads will go far in building credibility and quickly realizing a return-on-investment.
Next, leverage initial success in operations and expand focus on clinical workflows and resources. For example, obtaining the insights needed to understand turnaround times, assess average daily caseload assignments per radiologist or compare actual patient throughput against departmental goal metrics.
Finally, complete the system deployment with financial analytics and insights, billing and coding procedures, order processing, payer performance, and so on to elevate awareness of organizational health across the radiology service line. It is important to determine at each phase whether the results meet expectations. If they do not, figure out why and course-correct before moving to the next phase.
Bringing it Together
Today’s medical imaging environment continues to increase in complexity, and with no end in sight. Adding more and more clinical and operational IT systems increases the influx of integration and interoperability challenges and creates new disparate sources of potentially valuable information. The fragmented rise of data silos impedes valuable, data-driven decision-making for administrators, clinicians and IT managers trying to stay afloat and improve operational and clinical excellence.
To navigate these strong currents, a modern, cross-system business operations platform is necessary to bridge disparate clinical IT systems and provide the comprehensive insights and understanding that are required to improve the business. These next-generation tools need to be intuitive and collaborative to engage the entire staff to assimilate the integrated information into their regular activities. Democratizing medical imaging data empowers people to transform the enterprise medical imaging service line, which leads to improved operational performance, better financial results, and enhanced physician and patient experiences.
Ray Scott formally accepted the chairman’s role after working with and mentoring the HealthLevel team for two years. He is well known in healthcare IT for pioneering clinical health information exchange, interoperability and analytics with Axolotl Corp., which he co-founded and led as CEO (acquired by UHG/Optum). Prior to Axolotl, Scott managed and grew a number of software companies in Europe.
Reference:
1. www.pointb.com/insights/successful-healthcare-analytics-data-liquidity/ Accessed Sept. 29 2021.
July 26, 2024 
