Improved Screening Mammogram Workflow by Maximizing PACS Streamlining Capabilities in an Academic Breast Center

Improving radiologist productivity in screening mammogram interpretation

At our institution, a backlog of unread screening mammograms accumulated with a peak turnaround time of 198 h (8.25 days). Three major root causes of workflow inefficiencies were identified: radiologist interruptions, paper-based workflow, and a cumbersome report dictation workflow. A batched, digitized workflow with reporting assistance called "Uninterrupted with Assistant" was implemented. Following the intervention, the mean report turnaround time (TAT) was significantly decreased by 38.8 % (51.0 ± 16.0 vs 83.3 ± 46.6 h, p = 0.014) and the institutional goal for TAT (72 h) was met more often (93.3 %, 14/15 weeks vs 35.3 %, 6/17 weeks). Radiologist distraction in the new assignment was significantly lower (2.0 ± 1.4 SD) compared to the traditional "Interrupted" setting (5.6 ± 2.8 SD, t = -4.956, p < 0.01). Radiologist fatigue in the new assignment (2.6 ± 1.6 SD) was also significantly lower compared to the "Interrupted" setting (4.8 ± 2.2 SD, t = -5.159, p < 0.01). The average daily volume of screening mammograms interpreted in the "Uninterrupted with Assistant" assignment (50.3 ± 13.9 SD) was greater than in the "Interrupted" setting (21.0 ± 11.3). These interventions offer strategies to improve productivity and address practical issues of burnout and workforce retention.

Impact of Interruptions During Screening Mammography on Physician Well-Being and Patient Care

OBJECTIVE

To assess the impact of interruptions on radiologists' efficiency, accuracy, and job satisfaction in interpreting screening mammograms.

METHODS

This institutional review board-approved retrospective reader study recruited nine breast radiologists from a single academic institution [name withheld] to interpret 150 screening mammograms performed between December 1, 2008, and December 31, 2015 under two different reading conditions, as follows: (1) uninterrupted batch reading and (2) interrupted reading. The 150 cases consisted of 125 normal mammograms and 25 mammograms with subtle breast cancers. Cases were divided into two groups of 75 cases each (cohort 1 and cohort 2), with a comparable distribution of cancer cases. Four rounds of 75 cases each were conducted with a 6-week washout period between rounds 2 and 3. After completing each interpretation session, readers completed a seven-question survey, assessing perceptions of mental and physical effort, level of frustration, and performance satisfaction. Clinical performance metrics (reading time, recall rate, sensitivity, specificity, accuracy, and positive predictive value 1) were calculated.

RESULTS

Recall rates were significantly (P = .04) higher during interrupted reading sessions (35.4%) than they were during uninterrupted batch reading sessions (31.4%). Accuracy was significantly (P = .049) worse in the interrupted reading sessions (69.5%), compared with uninterrupted sessions (73.6%). Differences in overall image interpretation times were not statistically significant (P = .065). Compared with uninterrupted batch reading sessions, readers during interrupted sessions reported feeling busier (P < .001), encountered higher levels of cognitive demand (P = .005), experienced elevated levels of physical fatigue (P = .004), and expressed lower levels of satisfaction with their performance (P = .041).

CONCLUSION

Interruptions during interpretation of screening mammography have deleterious effects on physician performance and their sense of well-being.

Electronic Worklist Improves Timeliness of Screening Mammogram Interpretation in an Urban Underserved Population

OBJECTIVES

To evaluate the impact of an electronic workflow update on screening mammography turnaround time and time to diagnostic imaging for mammography performed on our urban mobile mammography van and at an urban community health center.

METHOD

Prior to 10/15/2019, screening exams for the mammography van and urban community health center were made available for interpretation to a single designated radiologist via a manually generated paper list. On 10/15/2019, screening exams were routed electronically onto PACS for any breast radiologist across our Network to interpret. Screening mammogram turnaround time (defined as time form image acquisition to report finalization), time to diagnostic imaging, and time to tissue sampling were collected for pre- and post-implementation periods (6/1-9/30/2019 and 11/1/2019-2/29/2020, respectively) and compared via student t-test and statistical process control analyses.

RESULTS

The number of screening exams in the pre- and post-implementation periods were 851 and 728 exams, respectively. Patients were predominately Black and/or African American (400/1579, 25%), non-English speaking (858/1579, 54%) and insured by Medicaid (751/1579, 48%). After implementation of the electronic workflow, turnaround time decreased from 101.0 to 36.4 hours (63.9%, P <0.001) and statistical process control analyses showed sustained decrease in mean turnaround time. However, mean time to diagnostic imaging and tissue sampling were unchanged after implementation (39 vs 45, days; P = 0.330 and 43 vs 59; P = 0.187, respectively).

CONCLUSION

Electronic workflow management can reduce screening mammography turnaround time for underserved populations, but additional efforts are warranted to improve time to imaging follow-up for abnormal screening mammograms.

Utilizing the Hub-and-Spoke Model to Deliver Quality Breast Imaging in a Large Health System

Healthcare systems are constantly expanding and gaining new territories. This growth is met with challenges in the organization and delivery of quality health care services to a large geographical area. The need for provider and staff coverage at the new sites often outpaces the rate at which additional providers and staff are hired. The need for new technology, equipment, and administrative support to oversee the new sites may also lag. The overall result could compromise patient experience at these outlying locations. The breast imaging division at University Hospitals Cleveland Medical Center (UHCMC) instituted many changes to support UHCMC's continual growth while focusing on consistent quality of care and optimal patient experience. Changes included adoption of the hub-and-spoke organization-design model and incorporation of the integrated practice unit (IPU) concept. In the hub-and-spoke organization-design model, full services are offered at a central hub, with additional limited services provided at the peripheral spoke sites. The IPU is a dedicated team of clinical and nonclinical personnel providing the full care cycle centered on a specific medical condition such as breast health. The breast imaging hubs and spokes are incorporated into the breast health IPUs to provide uniform quality care across a large health system. The purpose of this article is to describe how the breast imaging division, functioning as members of the breast care IPU, utilized the hub-and-spoke concept to provide quality breast imaging services throughout the expanding health system.

Improvement of radiology reporting in a clinical cancer network: impact of an optimised multidisciplinary workflow

PURPOSE

To assess the effectiveness of implementing a quality improvement project in a clinical cancer network directed at the response assessment of oncology patients according to RECIST-criteria.

METHODS

Requests and reports of computed tomography (CT) studies from before (n = 103) and after (n = 112) implementation of interventions were compared. The interventions consisted of: a multidisciplinary working agreement with a clearly described workflow; subspecialisation of radiologists; adaptation of the Picture Archiving and Communication System (PACS); structured reporting.

RESULTS

The essential information included in the requests and the reports improved significantly after implementation of the interventions. In the requests, mentioning start date increased from 2% to 49%; date of baseline CT from 7% to 64%; nadir date from 1% to 41%. In the reports, structured layout increased from 14% to 86%; mentioning target lesions from 18% to 80% and non-target lesions from 11% to 80%; measurements stored in PACS increased from 76% to 97%; labelled key images from 38% to 95%; all p values < 0.001.

CONCLUSION

The combination of implementation of an optimised workflow, subspecialisation and structured reporting led to significantly better quality radiology reporting for oncology patients receiving chemotherapy. The applied multifactorial approach can be used within other radiology subspeciality areas as well.

KEY POINTS

• Undeveloped subspecialisation makes adherence to RECIST guidelines difficult in general hospitals. • A clinical cancer network provides opportunities to improve healthcare. • Optimised workflow, subspecialisation and structured reporting substantially improve request and report quality. • Good interdisciplinary communication between oncologists, radiologists and others contributes to quality improvement.