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Incomplete or delayed communication of imaging results can result in harm to the patient and have legal ramifications for the providers involved. This commentary presents a closed-loop communication model for the ordering clinician and radiologist. The model suggests the ordering clinician categorize the radiology report as “concordant” or “discordant”, and if discordant, provide an explanation.

Analysis of closed malpractice claims can be used to identify potential safety hazards in a variety of clinical settings. This analysis of closed emergency department malpractice claims indicates that diagnostic errors dominate, and clinical judgment and documentation categories continue to be associated with a higher likelihood of payout. Subcategories and contributing factors are also discussed.

To reduce medical errors caused by fatigue, the Accreditation Council for Graduate Medical Education (ACGME) adopted duty hour restrictions for ACGME-accredited residency programs; however, other healthcare fields have not yet done so. This review presents the limited existing evidence for regulating duty hours for radiologists and proposes that additional research needs to be completed before implementing restrictions.

Wrong blood in tube (WBIT) errors can result in serious diagnostic and treatment errors, but may go unrecognized by clinical staff. In this study, machine learning was used to identify potential WBIT errors which were then compared to manual review by laboratory staff. The machine learning models showed higher accuracy, sensitivity, and specificity compared to manual review. 

Achieving diagnostic safety requires multidisciplinary approaches. Based on interviews with safety leaders across the United States, this article discusses how different organizations approach diagnostic safety. Respondents discuss barriers to implementing diagnostic safety activities as well as strategies to overcome barriers, highlighting the role of patient engagement and dedicated diagnostic safety champions.

Black and brown patients have experienced disproportionately poorer outcomes from COVID-19 infection as compared with white patients. This study found that patients who identified as Asian, Black, or Hispanic may not have received timely diagnosis or treatment due to inaccurately measured pulse oximetry (SpO2). These inaccuracies and discrepancies should be considered in COVID outcome research as well as other respiratory illnesses that rely on SpO2 measurement for treatment.

Missed or delayed diagnosis in primary care may result in serious complications for patients. This prospective study followed adults presenting to primary care with new or unresolved symptoms for 12 months. 32% of patients received a diagnosis within one month; most of the rest still did not have a diagnosis at 12 months (50%). The authors suggest interventions aimed at improving diagnosis should be system-based, not specific to a single medical issue or population.

Diagnostic errors can be identified by measuring concordance of initial and final diagnosis, for instance admission and discharge diagnoses. In this study, researchers developed and tested an automated trigger system to determine concordance between pairs of diagnoses. In comparison to the reference standard (concordance determined by experts) the automated system performance was excellent.

Delays in diagnosis and treatment can lead to poor outcomes for patients. Researchers reviewed root cause analysis (RCA) reports to identify factors contributing to delays in diagnosis and treatment among surgical patients at the Veterans Health Administration. Of the 163 RCAs identified, 73% reflected delays in treatment, 15% reflected delays in diagnosis, and 12% reflected delays in surgery. Policies and processes (e.g., lack of standardized processes, procedures not followed correctly) was the largest contributing factor, followed by communication challenges, and equipment or supply issues.

Clinical decision support (CDS) systems are designed to improve diagnosis. Researchers surveyed emergency department physicians about their evaluation of human factors-based CDS systems to improve diagnosis of pulmonary embolism. Although perceived usability was high, use of the CDS tool in the real clinical environment was low; the authors identified several barriers to use, including lack of workflow integration.

Root cause analysis is a commonly used tool to identify systems-related factors that contributed to an adverse event. This study assessed a system-based approach, (i.e., collaborative case reviews (CCR) co-led by radiology and an institutional patient safety program) to identify contributing factors and explore the strength of recommended actions in the radiology department at a large academic medical center. Stronger action items, such as standardization of processes, were implemented in 41% of events, and radiology had higher completion rates than other hospital departments.

The COVID-19 pandemic dramatically increased the use of telehealth, including remote primary care triage and assessment. This qualitative study explored patients’ and clinicians’ experiences managing suspected COVID-19 during remote triage and assessment. Findings highlight the need to strengthen organizational resilience, develop and implement triage decision support tools, and address vulnerable and unsupported groups (e.g., the elderly, vulnerable and homebound patients).

COVID-19 restrictions and patient safety concerns have greatly expanded the use of telehealth and virtual visits. Through patient satisfaction surveys and patient complaints, this US hospital evaluated the quality and safety of virtual visits in March and April of 2020. Five patient complaints were submitted during this timeframe and overall patient satisfaction remained high. Safety and quality risks were identified (e.g., diagnostic error) and best practices were established.

Incomplete or delayed referrals from primary care providers to specialty care can cause diagnostic delays and patient harm. A systems engineering analysis was conducted to identify vulnerabilities in the referral process and develop a framework to close the loop between primary and specialty care. Low reliability processes, such as workarounds, were identified and human factors approaches were recommended to improve successful referral rates.