Algorithms are commonly used to guide clinical decision-making, but concerns have been raised regarding bias due to the use of race-based data. This qualitative analysis examined perspectives of 42 stakeholders (e.g., individuals, representatives from clinical professional societies or payers, etc.) regarding the use of race- and ethnicity-based algorithms in healthcare. Seven themes were identified, highlighting concerns regarding bias, algorithm transparency, lack of standardization regarding how race and social determinants are collected and defined, and the use of a social construct as a proxy in clinical decision-making.

Prior studies have shown that adverse events can increase during the implementation of a new electronic health record (EHR) system. EHR transitions are remarkably expensive, laborious, personnel devouring, and time consuming. This article presents recommendations to facilitate transitions between one EHR system to another and opportunities for problem mitigation to avoid patient safety events.

Surgical site infections are a common hospital-acquired condition. This clinical guideline reviews the literature and gathers expert opinion to identify generalizable evidence-based strategies to reduce surgical site infections. The authors highlight antimicrobial, preoperative hygiene, glycemic control, and skin preparation procedures to prevent infection.

… of these systems has revealed new safety concerns. A prior study funded by the US Food and Drug Administration … or duplicate orders that were not detected by the system. A WebM&M commentary discussed an error that led to patient …

Although diagnostic errors cause considerable morbidity and mortality, thus far organizations have focused on preventing errors that are more easily measured. This commentary provides two examples of organizational approaches to minimizing diagnostic error. In one, Maine Medical Center established a voluntary reporting system for diagnostic error coupled with a revised root cause analysis process to determine both cognitive and systems causes of these errors. In the other example, the Kaiser Permanente system leveraged their electronic medical record to establish electronic "safety nets" to identify patients at risk of diagnostic error. These mainly focused on ensuring appropriate follow-up of abnormal lab tests (particularly cancer screening tests) and sufficient monitoring of high-risk medications. As failure to appropriately follow-up on lab abnormalities is a common source of patient harm in ambulatory care, this system—which identified thousands of patients requiring urgent follow-up—likely averted many cases of preventable harm. An accompanying editorial by Dr. Hardeep Singh encourages health care organizations to develop processes for examining missed opportunities for making timely diagnoses.