Identifying and addressing barriers to implementing core electronic health record use metrics for ambulatory care: Virtual consensus conference proceedings

Precise, reliable, valid metrics that are cost-effective and require reasonable implementation time and effort are needed to drive electronic health record (EHR) improvements and decrease EHR burden. Differences exist between research and vendor definitions of metrics. PROCESS:  We convened three stakeholder groups (health system informatics leaders, EHR vendor representatives, and researchers) in a virtual workshop series to achieve consensus on barriers, solutions, and next steps to implementing the core EHR use metrics in ambulatory care. CONCLUSION:  Actionable solutions identified to address core categories of EHR metric implementation challenges include: (1) maintaining broad stakeholder engagement, (2) reaching agreement on standardized measure definitions across vendors, (3) integrating clinician perspectives, and (4) addressing cognitive and EHR burden. Building upon the momentum of this workshop\u27s outputs offers promise for overcoming barriers to implementing EHR use metrics

Deregulation of Rab and Rab Effector Genes in Bladder Cancer

Growing evidence indicates that Rab GTPases, key regulators of intracellular transport in eukaryotic cells, play an important role in cancer. We analysed the deregulation at the transcriptional level of the genes encoding Rab proteins and Rab-interacting proteins in bladder cancer pathogenesis, distinguishing between the two main progression pathways so far identified in bladder cancer: the Ta pathway characterized by a high frequency of FGFR3 mutation and the carcinoma in situ pathway where no or infrequent FGFR3 mutations have been identified. A systematic literature search identified 61 genes encoding Rab proteins and 223 genes encoding Rab-interacting proteins. Transcriptomic data were obtained for normal urothelium samples and for two independent bladder cancer data sets corresponding to 152 and 75 tumors. Gene deregulation was analysed with the SAM (significant analysis of microarray) test or the binomial test. Overall, 30 genes were down-regulated, and 13 were up-regulated in the tumor samples. Five of these deregulated genes (LEPRE1, MICAL2, RAB23, STXBP1, SYTL1) were specifically deregulated in FGFR3-non-mutated muscle-invasive tumors. No gene encoding a Rab or Rab-interacting protein was found to be specifically deregulated in FGFR3-mutated tumors. Cluster analysis showed that the RAB27 gene cluster (comprising the genes encoding RAB27 and its interacting partners) was deregulated and that this deregulation was associated with both pathways of bladder cancer pathogenesis. Finally, we found that the expression of KIF20A and ZWINT was associated with that of proliferation markers and that the expression of MLPH, MYO5B, RAB11A, RAB11FIP1, RAB20 and SYTL2 was associated with that of urothelial cell differentiation markers. This systematic analysis of Rab and Rab effector gene deregulation in bladder cancer, taking relevant tumor subgroups into account, provides insight into the possible roles of Rab proteins and their effectors in bladder cancer pathogenesis. This approach is applicable to other group of genes and types of cancer

The Open Anchoring Quest Dataset: Anchored Estimates from 96 Studies on Anchoring Effects

People’s estimates are biased toward previously considered numbers (anchoring). We have aggregated all available data from anchoring studies that included at least two anchors into one large dataset. Data were standardized to comprise one estimate per row, coded according to a wide range of variables, and are available for download and analyses online (https://metaanalyses.shinyapps.io/OpAQ/). Because the dataset includes both original and meta-data it allows for fine-grained analyses (e.g., correlations of estimates for different tasks) but also for meta-analyses (e.g., effect sizes for anchoring effects)