Kostopoulou O, Tracey C, Delaney BC. J Am Med Inform Assoc. 2021;28:1461-1467.
In addition to being used for patient-specific clinical purposes, data within the electronic health record (EHR) may be used for other purposes including epidemiological research. Researchers in the UK developed and tested a clinical decision support system (CDSS) to evaluate changes in the types and number of observations that primary care physicians entered into the EHR during simulated patient encounters. Physicians documented more clinical observations using the CDSS compared to the standard electronic health record. The increase in documented clinical observations has the potential to improve validity of research developed from EHR data.
Delvaux N, Piessens V, Burghgraeve TD, et al. Implement Sci. 2020;15:100.
Clinical decision support systems (CDSS) and computerized physician order entry (CPOE) have the potential to improve patient safety. This randomized trial evaluated the impact of integrating CDSS into CPOE among general practitioners in Belgium. The intervention improved appropriateness and decreased volume of laboratory test ordering and did not show any increases in diagnostic errors.
McCradden MD, Joshi S, Anderson JA, et al. J Am Med Info Asso. 2020;27:2024-2027.
The authors discuss the challenges social inequalities pose to machine learning models, provide several recommendations for adopting ethical principles for the delivery of machine learning-assisted health care.
Ganguli I, Simpkin AL, Lupo C, et al. JAMA Netw Open. 2019;2:e1913325.
Cascades of care (or follow up) on incidental findings from diagnostic tests are common but are not always clinically meaningful. This study reports the results of a nationally representative group of physicians who were surveyed on their experiences with cascades. Almost all respondents had experienced cascades and many reported harms to patients and personal frustration and anxiety that may contribute to physician burnout.
Whitaker P. New Statesman. August 2, 2019;148:38-43.
Artificial intelligence (AI) and advanced computing technologies can enhance clinical decision-making. Exploring the strengths and weaknesses of artificial intelligence, this news article cautions against the wide deployment of AI until robust evaluation and implementation strategies are in place to enhance system reliability. A recent PSNet perspective discussed emerging safety issues in the use of artificial intelligence.
Dr. Saria is the John C. Malone Assistant Professor of computer science, statistics, and health policy at Johns Hopkins University. Her research focuses on developing next generation diagnostic, surveillance, and treatment planning tools to reduce adverse events and individualize health care for complex diseases. We spoke with her about artificial intelligence in health care.
Health care is working to provide high-value care and prevent overuse while ensuring patient safety. This commentary highlights the importance of educational initiatives, mentors, and use of clinical decision support to help clinicians determine what amount of care is appropriate for a given clinical situation.
Use of artificial intelligence (AI) and computer algorithms as tools to improve diagnosis have both risks and benefits. This commentary explores challenges to implementing AI systems at the front line of care in a safe manner and identifies weaknesses of advanced computing systems that influence their reliability.
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