Expectations for antibiotics increase their prescribing: Causal evidence about localized impact.

Objective: Clinically irrelevant but psychologically important factors such as patients' expectations for antibiotics encourage overprescribing. We aimed to (a) provide missing causal evidence of this effect, (b) identify whether the expectations distort the perceived probability of a bacterial infection either in a preor postdecisional distortions pathway, and (c) detect possible moderators of this effect. Method: Family physicians expressed their willingness to prescribe antibiotics (Experiment 1, n1 = 305) or their decision to prescribe (Experiment 2, n2 = 131) and assessed the probability of a bacterial infection in hypothetical patients with infections either with low or high expectations for antibiotics. Response order of prescribing/ probability was manipulated in Experiment 1. Results: Overall, the expectations for antibiotics increased intention to prescribe (Experiment 1, F(1, 301) = 25.32, p < .001, ηp2 = .08, regardless of the response order; Experiment 2, odds ratio [OR] = 2.31, and OR = 0.75, Vignettes 1 and 2, respectively). Expectations for antibiotics did not change the perceived probability of a bacterial infection (Experiment 1, F(1, 301) = 1.86, p = .173, ηp2 = .01, regardless of the response order; Experiment 2, d=-0.03, and d = +0.25, Vignettes 1 and 2, respectively). Physicians' experience was positively associated with prescribing, but it did not moderate the expectations effect on prescribing. Conclusions: Patients' and their parents' expectations increase antibiotics prescribing, but their effect is localized-it does not leak into the perceived probability of a bacterial infection. Interventions reducing the overprescribing of antibiotics should target also psychological factors

Prevalence and alternative explanations influence cancer diagnosis: An experimental study with physicians.

Objective: Cancer causes death to millions of people worldwide. Early detection of cancer in primary care may enhance patients’ chances of survival. However, physicians often miss early cancers, which tend to present with undifferentiated symptoms. Within a theoretical framework of the hypothesis generation (HyGene) model, together with psychological literature, we studied how 2 factors—cancer prevalence and an alternative explanation for the patient’s symptoms—impede early cancer detection, as well as prompt patient management. Method: Three hundred family physicians diagnosed and managed 2 patient cases, where cancer was a possible diagnosis (one colorectal cancer, the other lung cancer). We employed a 2 (cancer prevalence: low vs. high) × 2 (alternative explanation: present vs. absent) between-subjects design. Cancer prevalence was manipulated by changing either patient age or sex; the alternative explanation for the symptoms was manipulated by adding or removing a relevant clinical history. Each patient consulted twice. Results: In a series of random-intercept logistic models, both higher prevalence (OR = 1.92, 95% confidence interval [CI 1.27, 2.92]) and absence of an alternative explanation (OR = 1.70, 95% CI [1.11, 2.59]) increased the likelihood of a cancer diagnosis, which, in turn, increased the likelihood of prompt referral (OR = 22.84, 95% CI [16.14, 32.32]). Conclusions: These findings confirm the probabilistic nature of the diagnosis generation process and validate the application of the HyGene model to early cancer detection. Increasing the salience of cancer—such as listing cancer as a diagnostic possibility—during the initial hypothesis generation phase may improve early cancer detection

The Role of Physicians’ First Impressions in the Diagnosis of Possible Cancers without Alarm Symptoms

Background. First impressions are thought to exert a disproportionate influence on subsequent judgments; however, their role in medical diagnosis has not been systematically studied. We aimed to elicit and measure the association between first impressions and subsequent diagnoses in common presentations with subtle indications of cancer. Methods. Ninety UK family physicians conducted interactive simulated consultations online, while on the phone with a researcher. They saw 6 patient cases, 3 of which could be cancers. Each cancer case included 2 consultations, whereby each patient consulted again with nonimproving and some new symptoms. After reading an introduction (patient description and presenting problem), physicians could request more information, which the researcher displayed online. In 2 of the possible cancers, physicians thought aloud. Two raters coded independently the physicians’ first utterances (after reading the introduction but before requesting more information) as either acknowledging the possibility of cancer or not. We measured the association of these first impressions with the final diagnoses and management decisions. Results. The raters coded 297 verbalizations with high interrater agreement (Kappa = 0.89). When the possibility of cancer was initially verbalized, the odds of subsequently diagnosing it were on average 5 times higher (odds ratio 4.90 [95% CI 2.72 to 8.84], P &lt; 0.001), while the odds of appropriate referral doubled (OR 1.98 [1.10 to 3.57], P = 0.002). The number of cancer-related questions physicians asked mediated the relationship between first impressions and subsequent diagnosis, explaining 29% of the total effect. Conclusion. We measured a strong association between family physicians’ first diagnostic impressions and subsequent diagnoses and decisions. We suggest that interventions to influence and support the diagnostic process should target its early stage of hypothesis generation. </jats:p

Predecisional information distortion in physicians’ diagnostic judgments: Strengthening a leading hypothesis or weakening its competitor?

Decision makers have been found to bias their interpretation of incoming information to support an emerging judgment (predecisional information distortion). This is a robust finding in human judgment, and was recently also established and measured in physicians’ diagnostic judgments (Kostopoulou et al. 2012). The two studies reported here extend this work by addressing the constituent modes of distortion in physicians. Specifically, we studied whether and to what extent physicians distort information to strengthen their leading diagnosis and/or to weaken a competing diagnosis. We used the “stepwise evolution of preference” method with three clinical scenarios, and measured distortion on separate rating scales, one for each of the two competing diagnoses per scenario

Early diagnostic suggestions improve accuracy of GPs:a randomised controlled trial using computer-simulated patients

Background: Designers of computerised diagnostic support systems (CDSSs) expect physicians to notice when they need advice and enter into the CDSS all information that they have gathered about the patient. The poor use of CDSSs and the tendency not to follow advice once a leading diagnosis emerges would question this expectation.Aim: To determine whether providing GPs with diagnoses to consider before they start testing hypotheses improves accuracy.Design and setting: Mixed factorial design, where 297 GPs diagnosed nine patient cases, differing in difficulty, in one of three experimental conditions: control, early support, or late support.Method: Data were collected over the internet. After reading some initial information about the patient and the reason for encounter, GPs requested further information for diagnosis and management. Those receiving early support were shown a list of possible diagnoses before gathering further information. In late support, GPs first gave a diagnosis and were then shown which other diagnoses they could still not discount.Results: Early support significantly improved diagnostic accuracy over control (odds ratio [OR] 1.31; 95% confidence interval [95%CI] = 1.03 to 1.66, P = 0.027), while late support did not (OR 1.10; 95% CI = 0.88 to 1.37). An absolute improvement of 6% with early support was obtained. There was no significant interaction with case difficulty and no effect of GP experience on accuracy. No differences in information search were detected between experimental conditions.Conclusion: Reminding GPs of diagnoses to consider before they start testing hypotheses can improve diagnostic accuracy irrespective of case difficulty, without lengthening information search

Aiding Lay Decision Making Using a Cognitive Competencies Approach

Two prescriptive approaches have evolved to aid human decision making: just in time interventions that provide support as a decision is being made; and just in case interventions that educate people about future events that they may encounter so that they are better prepared to make an informed decision when these events occur. We review research on these two approaches developed in the context of supporting everyday decisions such as choosing an apartment, a financial product or a medical procedure. We argue that the lack of an underlying prescriptive theory has limited the development and evaluation of these interventions. We draw on recent descriptive research on the cognitive competencies that underpin human decision making to suggest new ways of interpreting how and why existing decision aids may be effective and suggest a different way of evaluating their effectiveness. We also briefly outline how our approach has the potential to develop new interventions to support everyday decision making and highlight the benefits of drawing on descriptive research when developing and evaluating interventions

Translational Medicine and Patient Safety in Europe:TRANSFoRm - Architecture for the Learning Health System in Europe

The Learning Health System (LHS) describes linking routine healthcare systems directly with both research translation and knowledge translation as an extension of the evidence-based medicine paradigm, taking advantage of the ubiquitous use of electronic health record (EHR) systems. TRANSFoRm is an EU FP7 project that seeks to develop an infrastructure for the LHS in European primary care. Methods. The project is based on three clinical use cases, a genotype-phenotype study in diabetes, a randomised controlled trial with gastroesophageal reflux disease, and a diagnostic decision support system for chest pain, abdominal pain, and shortness of breath. Results. Four models were developed (clinical research, clinical data, provenance, and diagnosis) that form the basis of the projects approach to interoperability. These models are maintained as ontologies with binding of terms to define precise data elements. CDISC ODM and SDM standards are extended using an archetype approach to enable a two-level model of individual data elements, representing both research content and clinical content. Separate configurations of the TRANSFoRm tools serve each use case. Conclusions. The project has been successful in using ontologies and archetypes to develop a highly flexible solution to the problem of heterogeneity of data sources presented by the LHS

What You Find Depends on How You Measure It: Reactivity of Response Scales Measuring Predecisional Information Distortion in Medical Diagnosis

“Predecisional information distortion” occurs when decision makers evaluate new information in a way that is biased towards their leading option. The phenomenon is well established, as is the method typically used to measure it, termed “stepwise evolution of preference” (SEP). An inadequacy of this method has recently come to the fore: it measures distortion as the total advantage afforded a leading option over its competitor, and therefore it cannot differentiate between distortion to strengthen a leading option (“proleader” distortion) and distortion to weaken a trailing option (“antitrailer” distortion). To address this, recent research introduced new response scales to SEP. We explore whether and how these new response scales might influence the very proleader and antitrailer processes that they were designed to capture (“reactivity”). We used the SEP method with concurrent verbal reporting: fifty family physicians verbalized their thoughts as they evaluated patient symptoms and signs (“cues”) in relation to two competing diagnostic hypotheses. Twenty-five physicians evaluated each cue using the response scale traditional to SEP (a single response scale, returning a single measure of distortion); the other twenty-five did so using the response scales introduced in recent studies (two separate response scales, returning two separate measures of distortion: proleader and antitrailer). We measured proleader and antitrailer processes in verbalizations, and compared verbalizations in the single-scale and separate-scales groups. Response scales did not appear to affect proleader processes: the two groups of physicians were equally likely to bolster their leading diagnosis verbally. Response scales did, however, appear to affect antitrailer processes: the two groups denigrated their trailing diagnosis verbally to differing degrees. Our findings suggest that the response scales used to measure information distortion might influence its constituent processes, limiting their generalizability across and beyond experimental studies