Dear Colleagues,
Possibly this paper will present a slightly different perspective for organizing considerations about the impact of open access journals….
Further the OA platform also brings forward a relatively new style of open access publishing. One's paper is published quickly and it is immediately open to peer review. I think I mentioned Qeios to HIFA once before. Qeios has become my favorite.
Best, David
Predicting the Probability That Open-Access Clinical Literature Saves Lives. Qeios. doi:10.32388/U2SYIR. https://www.qeios.com/read/U2SYIR
Abstract
Whether open-access (OA) clinical literature directly saves lives is frequently debated, yet empirical documentation is scarce because clinical notes rarely record how evidence was accessed. This study synthesizes high-impact cases of OA-enabled clinical change—most notably the SARS-CoV-2 PCR diagnostic protocol and the RECOVERY dexamethasone findings—and develops an expanded Bayesian predictive model estimating the probability that a single clinician reading one OA article saves a life. We integrate three primary evidence bases: (1) clinician-reported rates of practice change following article consultation, (2) the proportion of clinical decisions that influence short- or long-term mortality, and (3) empirically observed mortality reductions following OA-mediated dissemination of life-saving therapeutic evidence. We then extend this model by incorporating additional determinants of diagnostic and therapeutic accuracy, including medical error rates, years of clinical experience, multimorbidity-dependent diagnostic entropy, cognitive load, structural barriers, team-based reliability, guideline adherence, and electronic health record (EHR)–related error susceptibility, formalized in a multilevel Bayesian framework. The core model yields a probability range of p ≈ 0.003–0.02 that a clinician–article encounter prevents one death, corresponding to a Number Needed to Treat (NNT) analog of approximately 50–330 clinician–article encounters. After accounting for heterogeneity in clinical acuity, multimorbidity, and the extended set of clinician and system parameters, hierarchical Bayesian extensions adjust the predictive interval to p ≈ 0.002–0.03 and NNT ≈ 30–500. The integrated analysis demonstrates that OA literature meaningfully increases the probability of life-saving clinical decisions, especially in high-acuity environments where marginal improvements in evidence latency and accuracy have large mortality consequences.
HIFA Profile: David Cawthorpe is Adjunct Assistant Professor at the University of Calgary, Canada. His professional interests include: Human Development, Developmental Psychopathology, and Delivery of low bandwidth medical education curriculum. cawthord AT ucalgary.ca