Background Since the outbreak of COVID-19, the development of dashboards as dynamic, visual tools for communicating COVID-19 data has surged worldwide. Dashboards can inform decision-making and support behavior change. To do so, they must be actionable. The features that constitute an actionable dashboard in the context of the COVID-19 pandemic have not been rigorously assessed. Objective The aim of this study is to explore the characteristics of public web-based COVID-19 dashboards by assessing their purpose and users (“why”), content and data (“what”), and analyses and displays (“how” they communicate COVID-19 data), and ultimately to appraise the common features of highly actionable dashboards. Methods We conducted a descriptive assessment and scoring using nominal group technique with an international panel of experts (n=17) on a global sample of COVID-19 dashboards in July 2020. The sequence of steps included multimethod sampling of dashboards; development and piloting of an assessment tool; data extraction and an initial round of actionability scoring; a workshop based on a preliminary analysis of the results; and reconsideration of actionability scores followed by joint determination of common features of highly actionable dashboards. We used descriptive statistics and thematic analysis to explore the findings by research question. Results A total of 158 dashboards from 53 countries were assessed. Dashboards were predominately developed by government authorities (100/158, 63.0%) and were national (93/158, 58.9%) in scope. We found that only 20 of the 158 dashboards (12.7%) stated both their primary purpose and intended audience. Nearly all dashboards reported epidemiological indicators (155/158, 98.1%), followed by health system management indicators (85/158, 53.8%), whereas indicators on social and economic impact and behavioral insights were the least reported (7/158, 4.4% and 2/158, 1.3%, respectively). Approximately a quarter of the dashboards (39/158, 24.7%) did not report their data sources. The dashboards predominately reported time trends and disaggregated data by two geographic levels and by age and sex. The dashboards used an average of 2.2 types of displays (SD 0.86); these were mostly graphs and maps, followed by tables. To support data interpretation, color-coding was common (93/158, 89.4%), although only one-fifth of the dashboards (31/158, 19.6%) included text explaining the quality and meaning of the data. In total, 20/158 dashboards (12.7%) were appraised as highly actionable, and seven common features were identified between them. Actionable COVID-19 dashboards (1) know their audience and information needs; (2) manage the type, volume, and flow of displayed information; (3) report data sources and methods clearly; (4) link time trends to policy decisions; (5) provide data that are “close to home”; (6) break down the population into relevant subgroups; and (7) use storytelling and visual cues. Conclusions COVID-19 dashboards are diverse in the why, what, and how by which they communicate insights on the pandemic and support data-driven decision-making. To leverage their full potential, dashboard developers should consider adopting the seven actionability features identified.

BackgroundLow socioeconomic status (SES) is persistently associated with poor health and suboptimal use of healthcare services, and more unplanned healthcare use. Suboptimal use of emergency and acute healthcare services may increase health inequalities, due to late diagnosis or lack of continuity of care. Given that health literacy has been associated with healthcare utilisation and with education attainment, we sought to explore whether health literacy is related to the use of out-of-hours (OOH) Primary Care Services (PCSs). Additionally, we aimed to study whether and to what extent health literacy accounts for some of the association between education and OOH PSC use.MethodsA survey including measures of education attainment, health literacy (assessed by means of the Dutch version of the nine-dimension Health Literacy Questionnaire) and use of PCS was conducted among a sample of adults diagnosed with (any) somatic chronic condition in the Netherlands (response 76.3%, n = 1811). We conducted linear and logistic regression analyses to examine associations between education level and PCS use in the past year. We performed mediation analyses to assess whether the association between education and PCS use was (partly) explained by different aspects of health literacy. We adjusted the models for patient characteristics such as age and morbidity.ResultsHigher education attainment was associated with higher scores on the health literacy aspects Appraisal of health information, and Navigating the healthcare system. Additionally, appraisal and navigating the healthcare system partially accounted for educational differences in PCS use. Finally, higher appraisal of health information scores were associated with higher PCS utilisation.ConclusionSeveral aspects of health literacy were demonstrated to relate to PCS use, and partly accounted for educational differences herein. Accordingly, developing health literacy within individuals or communities may help to reduce inappropriate PCS use among people with low education.

Background: The COVID-19 pandemic is a complex global public health crisis presenting clinical, organisational and system-wide challenges. Different research perspectives on health are needed in order to manage and monitor this crisis. Performance intelligence is an approach that emphasises the need for different research perspectives in supporting health systems' decision-makers to determine policies based on well-informed choices. In this paper, we present the viewpoint of the Innovative Training Network for Healthcare Performance Intelligence Professionals (HealthPros) on how performance intelligence can be used during and after the COVID-19 pandemic. Discussion: A lack of standardised information, paired with limited discussion and alignment between countries contribute to uncertainty in decision-making in all countries. Consequently, a plethora of different non-data-driven and uncoordinated approaches to address the outbreak are noted worldwide. Comparative health system research is needed to help countries shape their response models in social care, public health, primary care, hospital care and long-term care through the different phases of the pandemic. There is a need in each phase to compare context-specific bundles of measures where the impact on health outcomes can be modelled using targeted data and advanced statistical methods. Performance intelligence can be pursued to compare data, construct indicators and identify optimal strategies. Embracing a system perspective will allow countries to take coordinated strategic decisions while mitigating the risk of system collapse.A framework for the development and implementation of performance intelligence has been outlined by the HealthPros Network and is of pertinence. Health systems need better and more timely data to govern through a pandemic-induced transition period where tensions between care needs, demand and capacity are exceptionally high worldwide. Health systems are challenged to ensure essential levels of healthcare towards all patients, including those who need routine assistance.

ObjectiveUnhealthy food choices follow a socioeconomic gradient that may partly be explained by one’s ‘cultural capital’, as defined by Bourdieu. We aim 1) to carry out a systematic review to identify existing quantitative measures of cultural capital, 2) to develop a questionnaire to measure cultural capital for food choices, and 3) to empirically test associations of socioeconomic position with cultural capital and food choices, and of cultural capital with food choices.DesignWe systematically searched large databases for the key-word ‘cultural capital’ in title or abstract. Indicators of objectivised cultural capital and family institutionalised cultural capital, as identified by the review, were translated to food choice relevant indicators. For incorporated cultural capital, we used existing questionnaires that measured the concepts underlying the variety of indicators as identified by the review, i.e. participation, skills, knowledge, values. The questionnaire was empirically tested in a postal survey completed by 2,953 adults participating in the GLOBE cohort study, The Netherlands, in 2011.ResultsThe review yielded 113 studies that fulfilled our inclusion criteria. Several indicators of family institutionalised (e.g. parents’ education completed) and objectivised cultural capital (e.g. possession of books, art) were consistently used. Incorporated cultural capital was measured with a large variety of indicators (e.g. cultural participation, skills). Based on this, we developed a questionnaire to measure cultural capital in relation to food choices. An empirical test of the questionnaire showed acceptable overall internal consistency (Cronbach’s alpha of .654; 56 items), and positive associations between socioeconomic position and cultural capital, and between cultural capital and healthy food choices.ConclusionsCultural capital may be a promising determinant for (socioeconomic inequalities in) food choices.