Health services articles from across Nature Portfolio

Prediction tools offer great promise for clinicians in the prevention and treatment of psychosis, but none has been routinely implemented. Greater methodological rigour in the development and evaluation of these tools, along with consideration of a range of performance criteria, is necessary to maximize their potential for improving clinical decision making.

Understanding how adverse professional life experiences affect the mental well-being of cardiologists is important. An unmet and equally important need is to design and implement strategies to prevent emotional harassment and discrimination at health-care workplaces and to effectively support cardiologists who have been exposed to adverse professional life experiences. These strategies are especially needed for female, younger or divorced cardiologists.

Artificial intelligence (AI) and natural language processing (NLP) have found a highly promising application in automated clinical coding (ACC), an innovation that will have profound impacts on the clinical coding industry, billing and revenue management, and potentially clinical care itself. Dong et al. recently analyzed the technical challenges of ACC and proposed future directions. Primary challenges for ACC exist at the technological and implementation levels; clinical documents are redundant and complex, code sets like the ICD-10 are rapidly evolving, training sets are not comprehensive of codes, and ACC models have yet to fully capture the logic and rules of coding decisions. Next steps include interdisciplinary collaboration with clinical coders, accessibility and transparency of datasets, and tailoring models to specific use cases.