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Homegrown work lists fill information system void

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Many radiology departments aren’t waiting for commercial information systems to address pressing needs like automatic work list prioritization. They are developing their own tools for tackling this common problem, according to presentations at a Monday scientific session.

Many radiology departments aren't waiting for commercial information systems to address pressing needs like automatic work list prioritization. They are developing their own tools for tackling this common problem, according to presentations at a Monday scientific session.

 

 

 

 

 

 

 

 

 

UPMC's work list engine moves high priority cases to the top of the radiology work list and highlights them in red. (Provided by M. Morgan).

 

Several institutions have moved their work lists away from a first-in, first-out model of case interpretation. By developing tools that look for high-priority studies, departments can zero in on the most urgent cases.

Through the use of a homegrown automated radiology triage system launched in July of 2005, radiologists at the University of Cincinnati and the Cincinnati Children's Hospital Medical Center improved reading times for inpatient and outpatient exams, and decreased final sign-off times for emergency department and inpatient exams, according to Dr. Mark Halsted, chief of radiology informatics core research at the medical center.

The Web-based system, RadStream, was launched in July 2005. It ensures that the most acute cases are moved up to the top of the work list and that urgent results are immediately presented to referring physicians.

The system also provides documentation and keeps a permanent log of all communications regarding cases, including the time, date, and staff involved in each communication event.

The system was popular with the hospital's radiologists, according to a survey conducted by Halstead and colleagues. After implementation, radiologists reported a 22% decrease in interruptions during the day. Fewer interruptions could save nearly 1500 radiologist hours per year, according to Halsted.

"We need to help busy radiologists prioritize their tasks," commented Dr. Matthew Morgan at the University of Pittsburgh Medical Center.

Morgan and colleagues developed an in-house software algorithm that highlights time-critical exams and automatically prioritizes a radiologist's work list.

When developing the system, researchers defined two types of urgent exams: patient exams from the ER, and exams read by radiology residents or by clinicians providing preliminary reads.

The software algorithm developed by the university moved away from the work list's default filtering method which first looked at division and study time as parameters. The logic built into the software prioritizes exams by patient location as well as stat and urgent notifications by physicians.

Studying the effects of the new system in their neuroradiology division, Morgan and colleagues reported that the new work list decreased the time from exam completion to final interpretation from 9.6 hours to 7.8 hours for urgent studies.

"The radiology workflow needs to be aligned with clinical workflow," said Dr. Kevin McEnery, an associate professor of radiology at the University of Texas M.D. Anderson Cancer Center.

McEnery continued the theme of what he called smart radiology. He outlined how his institution moved away from the typical first-in, first-out mode of interpretation by developing a work list engine that gathers data from the PACS, the RIS, the EMR, and the HIS.

The engine allows researchers to manage the workflow of close to 1500 cases. Radiologists in the department have expressed satisfaction with the workflow, McEnery said.

Some of that satisfaction resulted from eliminating repeated interruptions caused by ad hoc prioritization, according to McEnery. In-patient studies and STAT cases receive higher priority.

The work list prioritization solutions presented during the session were all homegrown, reflecting a dearth of work list solutions from the commercial community, noted Dr. Paul Chang, chief of radiology informatics at the University of Pittsburgh Medical Center, during a panel discussion at the end of the session. Because users of these information systems all have their own idiosyncracies, looking to vendors for a one size fits all solution may not even be feasible, according to Chang.

During the discussion, Dr. Keith Dreyer, vice chairman of radiology computing and information sciences at Massachusetts General Hospital, stressed the need for service- oriented architectures from vendors, which would provide the services and the tools departments require to tailor and customize products to fit individual needs.

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