The AHRQ PSNet Collection comprises an extensive selection of resources relevant to the patient safety community. These resources come in a variety of formats, including literature, research, tools, and Web sites. Resources are identified using the National Library of Medicine’s Medline database, various news and content aggregators, and the expertise of the AHRQ PSNet editorial and technical teams.
Hailu EM, Maddali SR, Snowden JM, et al. Health Place. 2022;78:102923.
Racial and ethnic health disparities are receiving increased attention, and yet structural racism continues to negatively impact communities of color. This review identified only six papers studying the impact of structural racism on severe maternal morbidity (SMM). Despite heterogeneity in measures and outcomes, the studies all demonstrated a link between structural racism and SMM; additional research is required.
Atallah F, Hamm RF, Davidson CM, et al. Am J Obstet Gynecol. 2022;227:b2-b10.
The reduction of cognitive bias is generating increased interest as a diagnostic error reduction strategy. This statement introduces the concept of cognitive bias and discusses methods to manage the presence of bias in obstetrics such as debiasing training and teamwork.
Navathe AS, Liao JM, Yan XS, et al. Health Aff (Millwood). 2022;41:424-433.
Opioid overdose and misuse continues to be a major public health concern with numerous policy- and organization-level approaches to encourage appropriate clinician prescribing. A northern California health system studied the effects of three interventions (individual audit feedback, peer comparison, both combined) as compared to usual care at several emergency department and urgent care sites. Peer comparison and the combined interventions resulted in a significant decrease in pills per prescription.
Improving maternal safety is an ongoing patient safety priority. This systematic review concluded that maternal near miss events are negatively associated with various aspects of quality of life. Women exposed to maternal near miss events were more likely to have overall lower quality of life, poorer mental and social health, and suffer negative economic consequences.
Park Y, Hu J, Singh M, et al. JAMA Netw Open. 2021;4:e213909.
Machine learning uses data and statistical methods to enhance risk prediction models and it has been promoted as a tool to improve healthcare safety. Using Medicaid claims data for a large cohort of White and Black pregnant females, this study evaluated approaches to reduce bias in clinical prediction algorithms for postpartum depression and mental health service utilization. The researchers found that a reweighing method in machine learning models was associated with a greater reduction in bias than excluding race from the prediction models. The authors suggest further examination of potentially biased data informing clinical prediction models and consideration of other methods to mitigate bias.
Lippke S, Derksen C, Keller FM, et al. Int J Environ Res Public Health. 2021;18:2616.
Communication is an essential component of safe patient care. This review of 71 studies found that communication training interventions in obstetrics can improve communication skills and behavior, particularly when combined with team training. The authors identified a lack of evidence regarding the effect of communication trainings on patient safety outcomes and suggest that future research should assess this relationship. Study findings underscore the need for adequate communication trainings to be provided to all staff and expectant mothers and their partners.
Much of the evidence about preventable harm in patients with psychiatric illnesses is limited to inpatient psychiatric facilities. This case-control study explores patient-related factors that place patients at an increased risk for patient safety incidents in primary or emergency care. While differences in income, education, and foreign background had some association with preventable harm, researchers found that psychiatric illness nearly doubled the risk of preventable harm among both emergency and primary care patients, with nearly half (46%) of harm attributable to diagnostic errors.
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