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Patel J, Otto E, Taylor JS, et al. Dermatol Online J. 2021;27(3).

In an update to their 2010 article, this review’s authors summarized the patient safety literature in dermatology from 2009 to 2020. In addition to topics covered in the 2010 article, this article also includes diagnostic errors related to telemedicine, laser safety, scope of practice, and infections such as COVID-19. The authors recommend further studies, and reports are needed to reduce errors and improve patient safety.
Reynolds KA, Hellquist K, Ibrahim SA, et al. Arch Dermatol Res. 2021;Epub May 27.
Adverse events associated with pharmacy compounding (e.g., parenteral nutrition, sterile compounding) are well-documented. This survey of state medical and osteopathic boards gathered information about compounding-associated adverse events in physician offices and use of compounding standards. Findings indicate that the incidence of in-office compounding-related adverse events is low and that the majority of respondents had not incorporated compounding standards into their regulations.

The American Society for Dermatologic Surgery Association and the Northwestern University Department of Dermatology.

Voluntary reporting systems collect adverse event data to inform improvement and education efforts. This site provides a platform for physicians and their staff to submit adverse experiences associated with dermatologic surgery equipment, medications or biologics.

Oglethorpe A. Women's Health. November 4, 2020.

Skin condition diagnosis is a visual activity that is vulnerable to error. This article highlights how conditions such as psoriasis and skin cancer can be misdiagnosed. The piece shares recommendations for patients to obtain an accurate diagnosis such as seeking a second opinion and preparing for appointments with notes and questions.
Tschandl P, Rinner C, Apalla Z, et al. Nat Med. 2020;Epub Jun 22.
This study explored the use of artificial intelligence (AI)-based support in clinical decision-making in dermatology. The authors propose a framework for future research on image-based diagnostics to improve AI use in clinical practice.
Nelson CA, Pérez-Chada LM, Creadore A, et al. JAMA Dermatol. 2020;156(5):501-512.
Researchers in this study used semi-structured interviews to explore how patients perceive the use of direct-to-patient and clinician decision-support artificial intelligence (AI) tools for skin cancer screening. Common perceived benefits included increased diagnostic speed and health care access, while increased anxiety was a common risk. Patients perceived more accurate diagnoses (69%) and less accurate diagnoses (85%) to be both the greatest strength and weakness of these tools. The vast majority of patients (94%) expressed the importance of a symbiotic relationship between patients, physicians and AI tools. The related commentary discusses the importance of including the patient perspective in the development and implementation of AI tools in healthcare.
Freeman K, Dinnes J, Chuchu N, et al. BMJ. 2020;368:m127.
Delays in cancer diagnosis can lead to adverse patient outcomes. This systematic review examined whether smartphone-based apps can assist patients in assessing skin cancer risk and whether they should seek medical attention for suspicious lesions. The review included nine studies evaluating six different smartphone apps; reported sensitivity and specificity varied widely across studies. The authors note limitations of the included studies, such as failure to recruit a population representative of the general population. Findings are consistent with earlier studies reporting poor performance of smartphone apps for melanoma detection. Although these apps are intended to reduce delays in diagnosis, the authors conclude they can’t be relied upon for detection of all cases of skin cancer.
Dick V, Sinz C, Mittlböck M, et al. JAMA dermatology. 2019.
Advanced computing holds promise for reducing missed diagnoses of cancer. This metanalysis found that computer-aided diagnosis effectively detects melanoma; however, studies were low in quality. The authors suggest that these systems may help assist dermatologists in overcoming the limitations of human cognition for performing repetitive tasks.
Tschandl P, Codella N, Akay BN, et al. The Lancet. Oncology. 2019;20:938-947.
Machine learning may have the potential to improve clinical decision-making and diagnosis. In this study, machine-learning algorithms generally performed better than human experts in accurately diagnosing 7 types of pigmented skin lesions and the top 3 algorithms performed better than the 27 physicians.
Lowenstein EJ, Sidlow R. J Dermatol. 2018;179(6):1263-1276.
Cognitive shortcuts, or heuristics, are often used by experts to make decisions. This two-part review examines how heuristics affect diagnosis in dermatology. The first article discusses the strengths and weaknesses in visual diagnosis behaviors. The second recommends techniques for improving decision making and self-awareness of thought processes to avoid diagnostic error in dermatology practice.
Cossman JP, Wang M, Fischer AA. J Am Acad Dermatol. 2018;79(5):981-983.
A key component of resident education is learning from mistakes in real time to improve practice. An open and psychologically safe clinical learning environment enables residents and the health care workforce to develop the skills required to manage such situations appropriately.
Anderson AM, Matsumoto M, Saul MI, et al. JAMA dermatology. 2018;154:569-573.
Diagnostic errors among physician extenders are understudied, especially in subspecialty settings. In this study, physician assistants working in dermatology clinics performed more biopsies and diagnosed fewer skin cancers and melanoma than board-certified dermatologists. The authors were unable to assess how often either clinician type missed diagnoses of skin cancer.
O'Connor DM, Jew OS, Perman MJ, et al. JAMA dermatology. 2017;153:1243-1248.
Teledermatology can reduce time to treatment and improve access to specialists. This small randomized controlled trial assessed the accuracy of parent-submitted smartphone photographs for diagnosing pediatric skin conditions compared to in-person dermatology. Teledermatology had high diagnostic accuracy and there was no significant difference when parents were given photography instructions. A previous PSNet interview discussed telemedicine and patient safety.
Resneck JS, Abrouk M, Steuer M, et al. JAMA dermatology. 2016;152:768-75.
Telemedicine is being more widely used in order to increase access to care. A relatively new aspect of telemedicine is direct-to-consumer telemedicine, including teledermatology. Using secret shoppers who submitted photographs and clinical information to teledermatology sites, this study found poor diagnostic accuracy and failure to elicit important information. Other studies have also raised concerns about the diagnostic accuracy of virtual clinical visits.
An attending physician recommended using acetic acid to evaluate a lesion on the perineum of a woman who had previously experienced a wart in the same area. The resident physician asked the medical assistant for acetic acid and unknowingly received trichloroacetic acid, which burned the patient's skin.

Lolis M, Dunbar SW, Goldberg DJ, et al. J Am Acad Dermatol. 2015;73(1):1-26.

This two-part review series explores patient safety in dermatologic practice. The first article discusses safety issues and error reduction tactics in dermatologic surgical practice, highlighting the importance of correct site identification. The second review examines safety problems associated with cosmetic procedures, including complications around nonphysician operators in this field.