Brit J Hosp Med
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Predictive algorithms have myriad potential clinical decision-making implications from prognostic counselling to improving clinical trial efficiency. Large observational (or "real world") cohorts are a common data source for the development and evaluation of such tools. There is significant optimism regarding the benefits and use cases for risk-based care, but there is a notable disparity between the volume of clinical prediction models published and implementation into healthcare systems that drive and realise patient benefit. Considering the perspective of a clinician or clinical researcher that may encounter clinical predictive algorithms in the near future as a user or developer, this editorial: (1) discusses the ways in which prediction models built using observational data could inform better clinical decisions; (2) summarises the main steps in producing a model with special focus on key appraisal factors; and (3) highlights recent work driving evolution in the ways that we should conceptualise, build and evaluate these tools.
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The contribution of health care to environmental and climate crises is significant, under-addressed, and with consequences for human health. This editorial is a call to action. Focusing on pharmaceuticals as a major environmental threat, we examine pharmaceutical impacts across their lifecycle, summarising greenhouse gas emissions, pollution, and biodiversity loss, and outlining challenges and opportunities to reduce this impact. We urge health care decision-makers and providers to urgently consider environmental factors in their decision-making relating to both policy, and practice, promoting actions such as rational prescribing, non-pharmaceutical interventions, and research and advocacy for sustainable production, procurement, and use.