For which clinical rules do doctors want decision support, and why? A survey of Dutch general practitioners.

Despite the promise of decision support for improving care, alerts are often overridden or ignored. We evaluated Dutch general practitioners’ intention to accept decision support in a proposed implementation based on clinical rules regarding care for elderly patients, and their reasons for wanting or not wanting support. We developed a survey based on literature and structured interviews and distributed it to all doctors who would receive support in the proposed implementation (n = 43), of which 65 percent responded. The survey consisted of six questions for each of 20 clinical rules. Despite concerns about interruption, doctors tended to choose more interruptive forms of support. Doctors wanted support when they felt the rule represented minimal care, perceived a need to improve care, and felt responsible for the action and that they might forget to perform the action; doctors declined support due to feeling that it was unnecessary and due to concerns about interruption

A case study of an individual participant data meta-analysis of diagnostic accuracy showed that prediction regions represented heterogeneity well

The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings

Stop smoking advice by practice assistants after routine cervical screening in general practice: a qualitative exploration of potential barriers and enablers

Background Cervical screening could be an appropriate routine moment to provide female smokers with tailored stop smoking advice. In Dutch general practice, cervical smears are performed by practice assistants. Objectives This study was performed in preparation for a randomised trial to identify potential barriers and enablers for a brief stop smoking strategy performed by trained practice assistants after routine cervical screening. Methods Between December 2016 and March 2017 three focus group meetings were held with ten practice assistants, three nurses, and six general practitioners to explore their views and expectations towards the proposed approach. We analysed data using thematic analysis. Identified factors are presented within the framework of the Social-Ecological Model. Results Potential barriers and enablers were identified at individual, interpersonal, and workplace levels. Practice assistants, nurses and GPs did not consider assistants to have a role in stop smoking care. They believed it is feasible to register smoking status but had reservations towards providing advice by assistants, for which knowledge and skills are needed. Practice assistants' own beliefs about smokers and smokers' response to stop smoking advice might influence how assistants and smokers interact. An explanation of why advice is given could help, provided assistants have enough time and experience with the smear. The nurses' availability and general practitioners' view on prevention might affect the delivery of the strategy by the assistant. Conclusion At individual, interpersonal, and workplace levels, several factors could influence the provision of a stop smoking strategy by a practice assistant.Prevention, Population and Disease management (PrePoD)Public Health and primary car