ArticleThe journal of climate change and health
Leveraging digitization to decarbonize healthcare - medication prescribing information as an exemplar.
Article in The journal of climate change and health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
2 authors.
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Abstract
The U.S. healthcare sector accounts for an estimated 8.5 % of national greenhouse gas emissions and addressing healthcare emissions is a critical priority to mitigate their negative impacts on human and planetary health. Most are indirect emissions from upstream supply chains such as construction and manufacturing, but downstream reforms can be easier to implement and can deliver meaningful, near-term reductions. For example, increased digitization and reduced dependency on paper in healthcare have potential to improve patient care, safety, equity, and experience while reducing environmental impacts and costs. If implemented at scale, the potential reductions are substantial. A promising area for decarbonization is the transition of Prescribing Information (PI) from a dual system to a digital-first system. In the dual system both digital and printed information must be provided with the 6.7 billion prescriptions dispensed by U.S. retailers annually. To produce printed PIs requires 1.8 million trees and generates 640 kt of CO
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.