ArticleBMJ open2024
An international consensus panel on the potential value of Digital Surgery.
Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe use of digital technology in surgery is increasing rapidly, with a wide array of new applications from presurgical planning to postsurgical performance assessment. Understanding the clinical and economic value of these technologies is vital for making appropriate health policy and purchasing decisions. We explore the potential value of digital technologies in surgery and produce expert consensus on how to assess this value.
designA modified Delphi and consensus conference approach was adopted. Delphi rounds were used to generate priority topics and consensus statements for discussion. SETTING AND
participantsAn international panel of 14 experts was assembled, representing relevant stakeholder groups: clinicians, health economists, health technology assessment experts, policy-makers and industry. PRIMARY AND SECONDARY OUTCOME MEASURES: A scoping questionnaire was used to generate research questions to be answered. A second questionnaire was used to rate the importance of these research questions. A final questionnaire was used to generate statements for discussion during three consensus conferences. After discussion, the panel voted on their level of agreement from 1 to 9; where 1=strongly disagree and 9=strongly agree. Consensus was defined as a mean level of agreement of >7.
resultsFour priority topics were identified: (1) how data are used in digital surgery, (2) the existing evidence base for digital surgical technologies, (3) how digital technologies may assist surgical training and education and (4) methods for the assessment of these technologies. Seven consensus statements were generated and refined, with the final level of consensus ranging from 7.1 to 8.6.
conclusionPotential benefits of digital technologies in surgery include reducing unwarranted variation in surgical practice, increasing access to surgery and reducing health inequalities. Assessments to consider the value of the entire surgical ecosystem holistically are critical, especially as many digital technologies are likely to interact simultaneously in the operating theatre.
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What OpenQuestion holds
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.