Differential diagnosis checklists reduce diagnostic error differentially: a randomized experiment

Introduction Wrong and missed diagnoses contribute substantially to medical error. Can a prompt to generate alternative diagnoses (prompt) or a differential diagnosis checklist (DDXC) increase diagnostic accuracy? How do these interventions affect the diagnostic process and self-monitoring? Methods Advanced medical students (N = 90) were randomly assigned to one of four conditions to complete six computer-based patient cases: group 1 (prompt) was instructed to write down all diagnoses they considered while acquiring diagnostic test results and to finally rank them. Groups 2 and 3 received the same instruction plus a list of 17 differential diagnoses for the chief complaint of the patient. For half of the cases, the DDXC contained the correct diagnosis (DDXC+), and for the other half, it did not (DDXC−; counterbalanced). Group 4 (control) was only instructed to indicate their final diagnosis. Mixed-effects models were used to analyse results. Results Students using a DDXC that contained the correct diagnosis had better diagnostic accuracy, mean (standard deviation), 0.75 (0.44), compared to controls without a checklist, 0.49 (0.50), P < 0.001, but those using a DDXC that did not contain the correct diagnosis did slightly worse, 0.43 (0.50), P = 0.602. The number and relevance of diagnostic tests acquired were not affected by condition, nor was self-monitoring. However, participants spent more time on a case in the DDXC−, 4:20 min (2:36), P ≤ 0.001, and DDXC+ condition, 3:52 min (2:09), than in the control condition, 2:59 min (1:44), P ≤ 0.001. Discussion Being provided a list of possible diagnoses improves diagnostic accuracy compared with a prompt to create a differential diagnosis list, if the provided list contains the correct diagnosis. However, being provided a diagnosis list without the correct diagnosis did not improve and might have slightly reduced diagnostic accuracy. Interventions neither affected information gathering nor self-monitoring

Harnessing the wisdom of crowds can improve guideline compliance of antibiotic prescribers and support antimicrobial stewardship

open access articleAntibiotic overprescribing is a global challenge contributing to rising levels of antibiotic resistance and mortality. We test a novel approach to antibiotic stewardship. Capitalising on the concept of “wisdom of crowds”, which states that a group’s collective judgement often outperforms the average individual, we test whether pooling treatment durations recommended by different prescribers can improve antibiotic prescribing. Using international survey data from 787 expert antibiotic prescribers, we run computer simulations to test the performance of the wisdom of crowds by comparing three data aggregation rules across different clinical cases and group sizes. We also identify patterns of prescribing bias in recommendations about antibiotic treatment durations to quantify current levels of overprescribing. Our results suggest that pooling the treatment recommendations (using the median) could improve guideline compliance in groups of three or more prescribers. Implications for antibiotic stewardship and the general improvement of medical decision making are discussed. Clinical applicability is likely to be greatest in the context of hospital ward rounds and larger, multidisciplinary team meetings, where complex patient cases are discussed and existing guidelines provide limited guidance

“I’ve Just Been Pretending I Can See This Stuff!”: Group Member Voice in Decision Making with a Hidden Profile

This research seeks to expand our knowledge of what underlies group performance in Hidden Profile decision tasks, adopting a mixed methods approach. We created a new mental simulation intervention designed to improve group decision outcomes and information exchange and tested it across two studies. We supplemented our quantitative statistical analysis with Thematic Analysis, to explore and better understand the motivations and utterances of individual group members, which we contend are key to increasing understanding of the challenges operating at individual and group levels in Hidden Profile decision tasks. Much group decision-making research uses quantitative methodologies, searching for causal explanations of why things happen as they do in group processes. As a subset of this area, existent Hidden Profile research is centred in the quantitative domain. Yet qualitative research can improve the understanding of group phenomena, such as communication style, which is important in groups’ decision-making. To our knowledge, no Hidden Profile research has taken a similar approach, so this paper makes a unique contribution. Results indicated the mental simulation had a positive effect on information exchange and decision quality in a Hidden Profile hiring task

Evaluation of Colloids and Activation Agents for Determination of Melamine Using UV-SERS

UV-SERS measurements offer a great potential for environmental or food (detection of food contaminats) analytics. Here, the UV-SERS enhancement potential of various kinds of metal colloids, such as Pd, Pt, Au, Ag, Au-Ag core-shell, and Ag-Au core-shell with different shapes and sizes, were studied using melamine as a test molecule. The influence of different activation (KF, KCl, KBr, K 2SO 4) agents onto the SERS activity of the nanomaterials was investigated, showing that the combination of a particular nanoparticle with a special activation agent is extremely crucial for the observed SERS enhancement. In particular, the size dependence of spherical nanoparticles of one particular metal on the activator has been exploited. By doing so, it could be shown that the SERS enhancement increases or decreases for increasing or decreasing size of a nanoparticle, respectively. Overall, the presented results demonstrate the necessity to adjust the nanoparticle size and the activation agent for different experiments in order to achieve the best possible UV-SERS results

Collective Intelligence Increases Diagnostic Accuracy in a General Practice Setting.

BACKGROUND General practitioners (GPs) work in an ill-defined environment where diagnostic errors are prevalent. Previous research indicates that aggregating independent diagnoses can improve diagnostic accuracy in a range of settings. We examined whether aggregating independent diagnoses can also improve diagnostic accuracy for GP decision making. In addition, we investigated the potential benefit of such an approach in combination with a decision support system (DSS). METHODS We simulated virtual groups using data sets from 2 previously published studies. In study 1, 260 GPs independently diagnosed 9 patient cases in a vignette-based study. In study 2, 30 GPs independently diagnosed 12 patient actors in a patient-facing study. In both data sets, GPs provided diagnoses in a control condition and/or DSS condition(s). Each GP's diagnosis, confidence rating, and years of experience were entered into a computer simulation. Virtual groups of varying sizes (range: 3-9) were created, and different collective intelligence rules (plurality, confidence, and seniority) were applied to determine each group's final diagnosis. Diagnostic accuracy was used as the performance measure. RESULTS Aggregating independent diagnoses by weighing them equally (i.e., the plurality rule) substantially outperformed average individual accuracy, and this effect increased with increasing group size. Selecting diagnoses based on confidence only led to marginal improvements, while selecting based on seniority reduced accuracy. Combining the plurality rule with a DSS further boosted performance. DISCUSSION Combining independent diagnoses may substantially improve a GP's diagnostic accuracy and subsequent patient outcomes. This approach did, however, not improve accuracy in all patient cases. Therefore, future work should focus on uncovering the conditions under which collective intelligence is most beneficial in general practice. HIGHLIGHTS We examined whether aggregating independent diagnoses of GPs can improve diagnostic accuracy.Using data sets of 2 previously published studies, we composed virtual groups of GPs and combined their independent diagnoses using 3 collective intelligence rules (plurality, confidence, and seniority).Aggregating independent diagnoses by weighing them equally substantially outperformed average individual GP accuracy, and this effect increased with increasing group size.Combining independent diagnoses may substantially improve GP's diagnostic accuracy and subsequent patient outcomes

Comparative characteristics of older people with type 1 diabetes treated with continuous subcutaneous insulin infusion or insulin injection therapy : data from the German/Austrian DPV registry

Aim: To compare clinical characteristics and outcomes in adults with type 1 diabetes aged ≥ 60 years using continuoussubcutaneous insulin infusion (CSII) vs. insulin injection therapy. Further, to determine the percentage of older adults with type 1 diabetes using CSII. Research design and methods: Retrospective study using data of the Diabetes Prospective Follow-up Registry (DPV). Including percentage CSII use from 2008 to 2018, and the characteristics of 9547 individuals extracted from the DPV in March 2019 (N=1404 CSII; N=8143 insulin injection therapy). Wilcoxon rank sum tests were used for continuous variables and chi-square tests for categorical variables to compare clinical characteristics of people using CSII vs. insulin injection therapy. Adjusted analyses used generalized linear models to compare diabetes-related outcomes. Results: CSII usage has increased in older adults (from 12% in 2008 to 23% in 2018). After adjustment, CSII was associated with lower HbA1c [60.7 mmol/mol (7.7±0.1%) vs. 62.8% (7.9±0.1%)], lower daily insulin dose (0.49±0.02 vs. 0.61±0.01 IU/kg), fewer days in hospital (8.1±0.12 vs. 11.2±0.11 days/person-year), fewer severe hypoglycaemic events (0.16±0.02 vs. 0.21±0.03 events/person-year) and fewer diabetic ketoacidosis (0.06±0.01 vs. 0.08±0.01 events/person-year). Individuals on CSII showed lower rates of microalbuminuria and also have a diagnosis of depression and neuropathy. Conclusions: A growing number of older adults are using insulin pumps. Older age in itself should not be seen as a contraindication for CSII

sj-docx-1-mdm-10.1177_0272989X241241001 – Supplemental material for Collective Intelligence Increases Diagnostic Accuracy in a General Practice Setting

Supplemental material, sj-docx-1-mdm-10.1177_0272989X241241001 for Collective Intelligence Increases Diagnostic Accuracy in a General Practice Setting by Matthew D. Blanchard, Stefan M. Herzog, Juliane E. Kämmer, Nikolas Zöller, Olga Kostopoulou and Ralf H. J. M. Kurvers in Medical Decision Making</p

BIODIVERSITY IN FOREST ECOSYSTEMS

Road density has increased in the Canary Islands’ forests during the last century, affecting an unknown amount of forested area. We studied road effects on vegetation in the relict laurel forest of Tenerife. We assessed edge effects on plant species richness, plant composition and litter production. Effects of anthropogenic corridors on vegetation differed between paved roads and unpaved trails. Opportunistic species (shade intolerant) dominated road edges, but composition differed among all sites. Multivariate analysis revealed convergence in species composition along the corridor-interior gradient. For trails, both species richness and litter production did not differ significantly between edge and interior. Road edge effects on vegetation were detectable only within the first 10 m towards the interior. This suggests that the main effects of roads and trails on species richness are limited to the immediate edge of the laurel forest. Litter fall along road edges was half that of the interior. However, no significant differences were detected due to the high variability of the data. A buffer of approximately 10 m would result in the reduction of the total area of the remaining undisturbed laurel forest. Based on these results, the building of new paved roads should not be considered. Low human population inflow into the Anaga Rural Park needs to be maintained on a sustainable basis. Forest managers should take these road/trail effects into account when planning new road openings in this ecosystem