Signing a colleague's radiology report

Utilizing Longitudinal Chest X-Rays and Reports to Pre-fill Radiology Reports

Despite the reduction in turn-around times in radiology reporting with the use of speech recognition software, persistent communication errors can significantly impact the interpretation of radiology reports. Pre-filling a radiology report holds promise in mitigating reporting errors, and despite multiple efforts in literature to generate comprehensive medical reports, there lacks approaches that exploit the longitudinal nature of patient visit records in the MIMIC-CXR dataset. To address this gap, we propose to use longitudinal multi-modal data, i.e., previous patient visit CXR, current visit CXR, and the previous visit report, to pre-fill the "findings" section of the patient's current visit. We first gathered the longitudinal visit information for 26,625 patients from the MIMIC-CXR dataset, and created a new dataset called Longitudinal-MIMIC. With this new dataset, a transformer-based model was trained to capture the multi-modal longitudinal information from patient visit records (CXR images + reports) via a cross-attention-based multi-modal fusion module and a hierarchical memory-driven decoder. In contrast to previous works that only uses current visit data as input to train a model, our work exploits the longitudinal information available to pre-fill the "findings" section of radiology reports. Experiments show that our approach outperforms several recent approaches by ≥3% on F1 score, and ≥2% for BLEU-4, METEOR and ROUGE-L respectively. Code will be published at https://github.com/CelestialShine/Longitudinal-Chest-X-Ray.

Syntactic and semantic errors in radiology reports associated with speech recognition software

Speech recognition software can increase the frequency of errors in radiology reports, which may affect patient care. We retrieved 213,977 speech recognition software-generated reports from 147 different radiologists and proofread them for errors. Errors were classified as "material" if they were believed to alter interpretation of the report. "Immaterial" errors were subclassified as intrusion/omission or spelling errors. The proportion of errors and error type were compared among individual radiologists, imaging subspecialty, and time periods. In all, 20,759 reports (9.7%) contained errors, of which 3992 (1.9%) were material errors. Among immaterial errors, spelling errors were more common than intrusion/omission errors ( p < .001). Proportion of errors and fraction of material errors varied significantly among radiologists and between imaging subspecialties ( p < .001). Errors were more common in cross-sectional reports, reports reinterpreting results of outside examinations, and procedural studies (all p < .001). Error rate decreased over time ( p < .001), which suggests that a quality control program with regular feedback may reduce errors.

Preventing errors in laterality

An error in laterality is the reporting of a finding that is present on the right side as on the left or vice versa. While different medical and surgical specialties have implemented protocols to help prevent such errors, very few studies have been published that describe these errors in radiology reports and ways to prevent them. We devised a system that allows the radiologist to view reports in a separate window, displayed in a simple font and with all terms of laterality highlighted in separate colors. This allows the radiologist to correlate all detected laterality terms of the report with the images open in PACS and correct them before the report is finalized. The system is monitored every time an error in laterality was detected. The system detected 32 errors in laterality over a 7-month period (rate of 0.0007 %), with CT containing the highest error detection rate of all modalities. Significantly, more errors were detected in male patients compared with female patients. In conclusion, our study demonstrated that with our system, laterality errors can be detected and corrected prior to finalizing reports.

Voice recognition dictation: radiologist as transcriptionist

Continuous voice recognition dictation systems for radiology reporting provide a viable alternative to conventional transcription services with the promise of shorter report turnaround times and increased cost savings. While these benefits may be realized in academic institutions, it is unclear how voice recognition dictation impacts the private practice radiologist who is now faced with the additional task of transcription. In this article, we compare conventional transcription services with a commercially available voice recognition system with the following results: 1) Reports dictated with voice recognition took 50% longer to dictate despite being 24% shorter than those conventionally transcribed, 2) There were 5.1 errors per case, and 90% of all voice recognition dictations contained errors prior to report signoff while 10% of transcribed reports contained errors. 3). After signoff, 35% of VR reports still had errors. Additionally, cost savings using voice recognition systems in non-academic settings may not be realized. Based on average radiologist and transcription salaries, the additional time spent dictating with voice recognition costs an additional $6.10 per case or $76,250.00 yearly. The opportunity costs may be higher. Informally surveyed, all radiologists expressed dissatisfaction with voice recognition with feelings of frustration, and increased fatigue. In summary, in non-academic settings, utilizing radiologists as transcriptionists results in more error ridden radiology reports and increased costs compared with conventional transcription services.

Survival strategies for radiology: some practical tips on how to reduce the risk of being sued and losing

The average indemnification for radiologists has tripled in the past 15 years, making risk management in radiology necessary to reduce the threat of being sued and losing. More than 75% of radiology lawsuits allege failure to diagnose or failure to communicate in a timely manner: ultimately, one third of these lawsuits are lost by the radiologist. A failure to communicate results in a timely manner is one of the greatest problems facing radiologists today, and it is a causal factor in 80% of lawsuits. Although rarely the primary factor for these suits, this is the one area in medical malpractice litigation in which radiologists can play a crucial role in reducing risk and liability. This article provides some practical tips on how to reduce the risk for being sued and losing.