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Background AIDSVu is a public resource for visualizing HIV surveillance data and other population-based information relevant to HIV prevention, care, policy, and impact assessment. Objective The site, AIDSVu.org, aims to make data about the US HIV epidemic widely available, easily accessible, and locally relevant to inform public health decision making. Methods AIDSVu develops visualizations, maps, and downloadable datasets using results from HIV surveillance systems, other population-based sources of information (eg, US Census and national probability surveys), and other data developed specifically for display and dissemination through the website (eg, pre-exposure prophylaxis [PrEP] prescriptions). Other types of content are developed to translate surveillance data into summarized content for diverse audiences using infographic panels, interactive maps, local and state fact sheets, and narrative blog posts. Results Over 10 years, AIDSVu.org has used an expanded number of data sources and has progressively provided HIV surveillance and related data at finer geographic levels, with current data resources providing HIV prevalence data down to the census tract level in many of the largest US cities. Data are available at the county level in 48 US states and at the ZIP Code level in more than 50 US cities. In 2019, over 500,000 unique users consumed AIDSVu data and resources, and HIV-related data and insights were disseminated through nearly 4,000,000 social media posts. Since AIDSVu’s inception, at least 249 peer-reviewed publications have used AIDSVu data for analyses or referenced AIDSVu resources. Data uses have included targeting of HIV testing programs, identifying areas with inequitable PrEP uptake, including maps and data in academic and community grant applications, and strategically selecting locations for new HIV treatment and care facilities to serve high-need areas. Conclusions Surveillance data should be actively used to guide and evaluate public health programs; AIDSVu translates high-quality, population-based data about the US HIV epidemic and makes that information available in formats that are not consistently available in surveillance reports. Bringing public health surveillance data to an online resource is a democratization of data, and presenting information about the HIV epidemic in more visual formats allows diverse stakeholders to engage with, understand, and use these important public health data to inform public health decision making.

The current COVID pandemic crisis made it even clearer that the solutions to several questions that public health must face require the access to good quality data. Several issues of the value and potential of health data and the current critical issues that hinder access are discussed in this paper. In particular, the paper (i) focuses on “real-world data” definition; (ii) proposes a review of the real-world data availability in our country; (iii) discusses its potential, with particular focus on the possibility of improving knowledge on the quality of care provided by the health system; (iv) emphasizes that the availability of data alone is not sufficient to increase our knowledge, underlining the need that innovative analysis methods (e.g., artificial intelligence techniques) must be framed in the paradigm of clinical research; and (v) addresses some ethical issues related to their use. The proposal is to realize an alliance between organizations interested in promoting research aimed at collecting scientifically solid evidence to support the clinical governance of public health.

Background Although electronic health information systems (EHIS) with immunization components exist in Kenya, questions and concerns remain about their use and alignment with the Kenya Ministry of Health’s (MOH) National Vaccine and Immunization Program (NVIP). This article reports on the findings of an assessment of select EHIS with immunization components in Kenya, specifically related to system design, development, and implementation. Methods We conducted a rapid assessment of select EHIS with immunization components in Kenya from January to May 2017 to understand the design, development, implementation of the EHIS including the lessons learned from their use. We also assessed how the data elements in the EHIS compared to the data elements in the Maternal and Child Health Booklet used in the existing paper based system in Kenya. Results The EHIS reviewed varied in purpose, content, and population covered. Only one system was built to focus specifically on immunization data. Substantial differences in system functionality and immunization-related data elements included in the EHIS were identified. None of the EHIS had all the data elements necessary to fully replace or operate independently from the standardized paper-based system for recording immunization data in Kenya. Conclusions Overall, the findings of this assessment highlighted substantial variation in the EHIS with immunization components. The findings provide insights and lessons learned for the Kenya MOH NVIP, immunization partners, vendors of EHIS, and users of EHIS to consider as Kenya transitions from paper-based to electronic immunization information systems.

Background This is the seventh in a series of papers reporting Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. The SHARE Program was a systematic, integrated, evidence-based program for resource allocation within a large Australian health service. It aimed to facilitate proactive use of evidence from research and local data; evidence-based decision-making for resource allocation including disinvestment; and development, implementation and evaluation of disinvestment projects. From the literature and responses of local stakeholders it was clear that provision of expertise and education, training and support of health service staff would be required to achieve these aims. Four support services were proposed. This paper is a detailed case report of the development, implementation and evaluation of a Data Service, Capacity Building Service and Project Support Service. An Evidence Service is reported separately. Methods Literature reviews, surveys, interviews, consultation and workshops were used to capture and process the relevant information. Existing theoretical frameworks were adapted for evaluation and explication of processes and outcomes. Results Surveys and interviews identified current practice in use of evidence in decision-making, implementation and evaluation; staff needs for evidence-based practice; nature, type and availability of local health service data; and preferred formats for education and training. The Capacity Building and Project Support Services were successful in achieving short term objectives; but long term outcomes were not evaluated due to reduced funding. The Data Service was not implemented at all. Factors influencing the processes and outcomes are discussed. Conclusion Health service staff need access to education, training, expertise and support to enable evidence-based decision-making and to implement and evaluate the changes arising from those decisions. Three support services were proposed based on research evidence and local findings. Local factors, some unanticipated and some unavoidable, were the main barriers to successful implementation. All three proposed support services hold promise as facilitators of EBP in the local healthcare setting. The findings from this study will inform further exploration. Electronic supplementary material The online version of this article (doi:10.1186/s12913-017-2388-8) contains supplementary material, which is available to authorized users.

This paper examines the dynamic relationship between data, participation and value through an analysis of developments in Alzheimer’s disease research. Alzheimer’s disease has risen rapidly up national and international policy agendas, particularly in Europe and North America. Research funding and initiatives have proliferated, many of which emphasise the potential value associated with existing data sources. The paper argues that the potential of these initiatives lies not only in realising the value of data through circulation, exchange and recombination, but also in restructuring of the relations of data production and use, notably through the extension and intensification of research participation. As Alzheimer’s research focuses away from clinical settings and symptomatic ‘people with dementia’, participants in existing research studies are reimagined as potential participants in future research studies, as ‘people with data’. Building on analyses of the role of clinical labour in the production of biovalue, the paper argues that reworked relations of data reuse and reproduction suggest the ongoing and repeated attachments between data and bodies involved in the production of value. It concludes that this raises questions related to the study of research participation and requires revisiting discussions about the appropriate representation of research participant interests.

The inclusion of social determinants of health offers a more comprehensive lens to fully appreciate and effectively address health. However, decision-makers across sectors still struggle to appropriately recognise and act upon these determinants, as illustrated by the ongoing COVID-19 pandemic. Consequently, improving the health of populations remains challenging. This paper seeks to draw insights from the literature to better understand decision-making processes affecting health and the potential to integrate data on social determinants. We summarised commonly cited conceptual approaches across all stages of the policy process, from agenda-setting to evaluation. Nine conceptual approaches were identified, including two frameworks, two models and five theories. From across the selected literature, it became clear that the context, the actors and the type of the health issue are critical variables in decision-making for health, a process that by nature is a dynamic and adaptable one. The majority of these conceptual approaches implicitly suggest a possible role for data on social determinants of health in decision-making. We suggest two main avenues to make the link more explicit: the use of data in giving health problems the appropriate visibility and credibility they require and the use of social determinants of health as a broader framing to more effectively attract the attention of a diverse group of decision-makers with the power to allocate resources. Social determinants of health present opportunities for decision-making, which can target modifiable factors influencing health—i.e. interventions to improve or reduce risks to population health. Future work is needed to build on this review and propose an improved, people-centred and evidence-informed decision-making tool that strongly and explicitly integrates data on social determinants of health. Supplementary Information The online version contains supplementary material available at 10.1007/s11524-021-00560-z.

Background: The number of injured far exceeds those dead and the average injury to mortality ratio in earthquakes stands at 3:1. Immediate effective medical response significantly influences injury outcomes and thus the overall health impact of earthquakes. Inadequate or mismanagement of injuries may lead to disabilities. The lack of precise data from immediate aftermath is seen as a remarkable weak point in disaster epidemiology and warrants evidence generation. Objective: To analyze the epidemiology of injuries and the treatment imparted at a secondary rural hospital in the Kutch district, Gujarat, India following the January 26, 2001 earthquake. Design/Methods: Discharge reports of patients admitted to the hospital over 10 weeks were analyzed retrospectively for earthquake-related injuries. Results: Orthopedic injuries, (particularly fractures of the lower limbs) were predominant and serious injuries like head, chest, abdominal, and crush syndrome were minimal. Wound infections were reported in almost 20% of the admitted cases. Surgical procedures were more common than conservative treatment. The most frequently performed surgical procedures were open reduction with internal fixation and cleaning and debridement of contaminated wounds. Four secondary deaths and 102 transfers to tertiary care due to complications were reported. Conclusion: The injury epidemiology reported in this study is in general agreement with most other studies reporting injury epidemiology except higher incidence of distal orthopedic injuries particularly to the lower extremities. We also found that young males were more prone to sustaining injuries. These results warrant further research. Inconsistent data reporting procedures against the backdrop of inherent disaster data incompleteness calls for urgent standardization of reporting earthquake injuries for evidence-based response policy planning. Keywords: disaster; earthquake; injury; epidemiology; data; standardization (Published: 25 July 2011) Citation: Global Health Action 2011, 4 : 7196 - DOI: 10.3402/gha.v4i0.7196 This paper is part of the Cluster Health and health systems impact of natural disasters - more papers from this cluster can be found here .

Objectives To review the literature on individual community professionals’ caseload management (behaviours related to assessment, treatment and discharging of clients) to identify the main themes and concepts, and to synthesize the findings to inform practice, policy and research. Methods Publications were systematically identified from electronic databases, hand searches of bibliographies, and contact with professional organizations. There were no restrictions on language, the nature of publications or publication year. Procedures were systematically applied for quality appraisal and data extraction. Qualitative and descriptive quantitative methods were used for data analysis and synthesis. Results Search criteria yielded 2048 papers of which 42 papers met the inclusion criteria. Thirty-five percent of these were based on research, the rest on professionals’ experiences. The papers covered 16 professional and 20 client populations, and their quality was generally poor. Analysis identified six broad themes: definitions of caseload management, caseload measurement and ‘tools’, models of caseload management practice, client- professional relationship, discharging and professional guidance. Six papers presented issues that related to but did not fit within these themes. Current caseload management tools and models of caseload management practice had a poor evidence base. Five papers described benefits of team-based approaches. Professional guidance for caseload management is limited in detail and relevance to daily practice. Conclusions Although there is a considerable literature on caseload management, it is not possible to make summative conclusions. Policy-makers and professional bodies should encourage and support development of research evidence about the ways to achieve effective, efficient and equitable caseload management. Health and social care services considering implementing caseload management tools or models of practice should critically appraise their basis, and consider their potential advantages as well as disadvantages.

What happens when someone rings an emergency hotline for help? How is the emergency handled? How does the emergency service swing into action? Prompt and competent intervention and assessment of the gravity of the situation in a few crucial seconds: these are the quality standards that regulate the organization of emergency operations centers. For a number of years various groups of social science researchers have carried forward a program for the systematic study of work using ethnographic and naturalistic methods of analysis. An interest in work is certainly nothing new in the social sciences, and in sociology in particular. What is new, though, is the particular analytical viewpoint from which such research is now conducted. This program has dispensed with large-scale theorization and has concentrated on the empirical study of activities and practices, achieving an unprecedented level of detail and analytical fineness. Indeed, only by proceeding at this fine level of detail—made possible by the use of videorecordings—has it been possible to document the extraordinary and subtle collaborative production of work, and to do so at a level which extends well beyond the conscious awareness of people in their everyday routine. This aspect concerns in particular the capacity of the latest generation of studies of work to document the tacit procedures and forms of common-sense reasoning involved in the performance of tasks in concrete work settings. This paper focuses on the ways in which the dispatch is done in a medical emergency operation center. Although we know a great deal about the interaction between caller and call-taker from previous research, we know much less about the social organization that makes the dispatch possible. The data analyzed in this paper derive from a research project in which I have been engaged for a number of years on operation centers for the 118 emergency telephone number in Italy. Contrasting the data obtained from audiorecording with the data obtained from videorecording, I will show that a dispatch does not consist purely in information transfer, but is the outcome of intense coordination work among the actors involved face to face and through the mediation of technological apparatus. URN: urn:nbn:de:0114-fqs0803408, Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, Vol 9, No 3 (2008): Visual Methods

Bayesian inference is a common method for conducting parameter estimation for dynamical systems. Despite the prevalent use of Bayesian inference for performing parameter estimation for dynamical systems, there is a need for a formalized and detailed methodology. This paper presents a comprehensive methodology for dynamical system parameter estimation using Bayesian inference and it covers utilizing different distributions, Markov Chain Monte Carlo (MCMC) sampling, obtaining credible intervals for parameters, and prediction intervals for solutions. A logistic growth example is given to illustrate the methodology.

Medical cyber-physical systems (MCPS) represent a platform through which patient health data are acquired by emergent Internet of Things (IoT) sensors, preprocessed locally, and managed through improved machine intelligence algorithms. Wireless medical cyber-physical systems are extensively adopted in the daily practices of medicine, where vast amounts of data are sampled using wireless medical devices and sensors and passed to decision support systems (DSSs). With the development of physical systems incorporating cyber frameworks, cyber threats have far more acute effects, as they are reproduced in the physical environment. Patients’ personal information must be shielded against intrusions to preserve their privacy and confidentiality. Therefore, every bit of information stored in the database needs to be kept safe from intrusion attempts. The IWMCPS proposed in this work takes into account all relevant security concerns. This paper summarizes three years of fieldwork by presenting an IWMCPS framework consisting of several components and subsystems. The IWMCPS architecture is developed, as evidenced by a scenario including applications in the medical sector. Cyber-physical systems are essential to the healthcare sector, and life-critical and context-aware health data are vulnerable to information theft and cyber-okayattacks. Reliability, confidence, security, and transparency are some of the issues that must be addressed in the growing field of MCPS research. To overcome the abovementioned problems, we present an improved wireless medical cyber-physical system (IWMCPS) based on machine learning techniques. The heterogeneity of devices included in these systems (such as mobile devices and body sensor nodes) makes them prone to many attacks. This necessitates effective security solutions for these environments based on deep neural networks for attack detection and classification. The three core elements in the proposed IWMCPS are the communication and monitoring core, the computational and safety core, and the real-time planning and administration of resources. In this study, we evaluated our design with actual patient data against various security attacks, including data modification, denial of service (DoS), and data injection. The IWMCPS method is based on a patient-centric architecture that preserves the end-user’s smartphone device to control data exchange accessibility. The patient health data used in WMCPSs must be well protected and secure in order to overcome cyber-physical threats. Our experimental findings showed that our model attained a high detection accuracy of 92% and a lower computational time of 13 sec with fewer error analyses.

The ageing population increases the demand for customized home care. As a result, sensing technologies are finding their way into the home environment. However, challenges associated with how users interact with sensors and data are not well-researched, particularly from a design perspective. This review explores the literature on important research projects around sensors, design and smart healthcare in smart homes, and highlights challenges for design research. A PRISMA protocol-based screening procedure is adopted to identify relevant articles (n = 180) on the subject of sensors, design and smart healthcare. The exploration and analysis of papers are performed using hierarchical charts, force-directed layouts and ‘bedraggled daisy’ Venn diagrams. The results show that much work has been carried out in developing sensors for smart home care. Less attention is focused on addressing challenges posed by sensors in homes, such as data accessibility, privacy, comfort, security and accuracy, and how design research might solve these challenges. This review raises key design research questions, particularly in working with sensors in smart home environments.

The May 2022 proposal from the European commission for a ‘European health data space’ envisages advantages for health from exploiting the growing mass of health data in Europe. However, key stakeholders have identified aspects that demand clarification to ensure success. Data will need to be freed from traditional silos to flow more easily and to cross artificial borders. Wide engagement will be necessary among healthcare professionals, researchers, and the patients and citizens that stand to gain the most but whose trust must be won if they are to allow use or transfer of their data. This paper aims to alert the wider scientific community to the impact the ongoing discussions among lawmakers will have. Based on the literature and the consensus findings of an expert multistakeholder panel organised by the European Alliance for Personalised Medicine (EAPM) in June 2022, it highlights the key issues at the intersection of science and policy, and the potential implications for health research for years, perhaps decades, to come.

Background Multidisciplinary teams (MDTs) are an integral component in the delivery of health care. This is particularly evident in the delivery of cancer care, where multidisciplinary teams are internationally recognized as the preferred method for service delivery. The use of health information systems and technology are key enabling factors for building the capacity of MDTs to engage in improvement and implementation projects but there is scant research on how MDTs make use of technology and information systems or the kinds of systems needed for them to undertake improvement and implementation research. This paper reports findings on how seven MDTs in cancer care utilized technological and information systems and the barriers and enabling factors that impacted on their uptake. Methods Seven multidisciplinary teams from two large metropolitan hospitals participated in the study. Qualitative methods including structured observations and semi structured interviews that explored how teams engaged in research and improvement activities were utilized. Participants were also observed and interviewed in relation to their use of data and health information systems. Findings were subject to content analysis and key themes were identified. Interviews were transcribed and de-identified and key themes were subsequently discussed with participants to allow for member checking and further clarification of findings. Results A total of 43 MDT meetings across seven tumor streams were observed. Of these, observation notes from 13 meetings contained direct references to emerging technologies and health information systems. Findings from 15 semi-structured interviews were also analyzed in relation to how MDTs used technology in weekly meetings, and the perceived impact of technology. Three broad themes emerged: (1) methods for data collection and use by MDTs, (2) the impact of technology on the MDT meeting environment, and (3) the impact of technology and information systems on clinical decision making. Conclusion The study demonstrates that real time data collection and imaging may improve patient centered care coordination. However, ICTs can be used sub-optimally by teams. We therefore urge additional research to identify the enabling factors that support better collection and use of outcome data from ICT. Electronic supplementary material The online version of this article (10.1186/s12913-018-3242-3) contains supplementary material, which is available to authorized users.

La recherche interventionnelle en santé mondiale est souvent effectuée au moyen de partenariats scientifiques internationaux. Mais la réalisation de telles recherches, notamment dans les pays à faible revenu où les enjeux de pouvoir, d’argent et de relations interculturelles sont exacerbés, soulève de nombreux défis éthiques, notamment concernant la conduite responsable lors des recherches collaboratives. L’un d’eux est la conservation, l’accès, l’utilisation et la publication des données. Malgré l’existence de multiples politiques et documents phares sur l’éthique et la conduite responsable de la recherche, les chercheurs en recherche interventionnelle sont encore peu outillés pour faire face à ce défi. Dans le contexte d’un programme de recherches interventionnelles réalisées au Burkina Faso, les auteurs souhaitent partager leur expérience dans le développement d’une politique interne concernant leurs données. Après avoir évoqué le contexte global et particulier, l’article présente le processus de formulation et d’adoption de cette politique par les chercheurs d’une équipe interdisciplinaire et internationale (Allemagne, Burkina Faso, Canada, France). Les valeurs qui enchâssent cette politique interne sont la transparence, la prévention, le consensus autour du processus de production, le respect des principes internationaux, l’accès libre aux connaissances produites et la préoccupation pour leur diffusion et utilisation. La politique se présente en plusieurs parties : objet, types et statuts des chercheurs impliqués, conservation des données, accès et utilisation des données, production scientifique et paternité. Les principaux défis rencontrés par les chercheurs pour formuler cette politique sont analysés dans un souci de partage pour susciter un débat rarement abordé. La confiance, la transparence et le respect mutuel doivent être au cœur de tout partenariat scientifique en recherche interventionnelle., Interventional global health research is often carried out through international scientific partnerships. However, the conduct of such research, especially in low-income countries where issues of power, money and intercultural relations are exacerbated, raises many ethical challenges particularly related to responsible conduct in collaborative research. One of these challenges is the storage, access, use and publication of data. Despite the existence of multiple influential policies and documents on ethics and the responsible conduct of research, researchers in intervention research are still not equipped to deal with such challenges. In the context of an intervention research program conducted in Burkina Faso, the authors would like to share their experience in the development of an internal policy concerning their data. After presenting the global and the particular context, the paper presents the process of policy formulation and its adoption by the researchers of an interdisciplinary and international team (Burkina Faso, Canada, France, Germany). The values that entrench this internal policy are: transparency, prevention, consensus about the production process, respect for international principles, free access to the knowledge produced and concerns regarding its dissemination and use. The policy is presented in several parts: aim, types and status of the participating researchers, data storage, access and use of data, scientific production and authorship. The main challenges faced by researchers in formulating this policy are analyzed in a shared desire to spark a debate that is rarely addressed. Trust, transparency and mutual respect should be central to any scientific partnership in intervention research., Article

Coordinated, integrated care requires connected “inputs, delivery, management and organization of services related to diagnosis, treatment, care, rehabilitation and health promotion” (Grone & Barbero, 2002). Connected health (CH) offers a key building block as a “paradigm shift, looking after the individual and community health in a process that speaks to the health journey of the person, through the entire lifespan, leveraging a variety of technologies to do so” (ENJECT, 2016). However, CH is failing to reach its full potential – and therefore failing in its contribution to the realization of integrated care. We conducted a multi-disciplinary literature review across business, technology and healthcare journals, triangulated with a survey of CH experts from academia, industry and clinical settings representing 19 European countries (ENJECT, COST Action TD1405). We hereby identify key vectors for CH and related drivers of change: Policy and regulation: There is a gap between national policy/strategy statements and local or regional implementation, despite 80% of European countries having a national CH strategy and political support of CH. Currently, 2/3 of European countries rely on generic privacy, security or other legislation whereas customised regulation would better recognise the uniqueness of health-related data and its need to flow within specified channels. Technology and interoperability: Interoperability is an ongoing process in healthcare across Europe with ePrescription and Electronic Health Records leading the field while personal health systems adoption varies. Again privacy and security concerns come to the fore, as well as usability and ease-of-adoption related issues. Training and education: Training programmes are beginning to incorporate CH elements to equip future healthcare leaders to fully exploit CH’s potential, however this is neither widespread nor in-depth. An emerging topic is education of health professionals in skills needed to participate in the design and adoption of CH solutions. Health literacy programmes targeting the general public are largely ad hoc and rely on unconnected methods such as leaflets and booklets. Business and revenue models: Europe’s healthcare business models typically involve public and private providers while relying largely on public funding. CH reimbursement and revenue models are limited and non- standard. Innovation at both service and process levels is slow to diffuse and reimbursement models stymied due to a lack of standardised evaluation methodologies or agreement on what constitutes value. Value creation models in health are primarily built to address medical conditions, rather than prevention and self-care. Citizen and Clinician engagement: Actors considered across both academic papers and survey vary – from industry giants, start-ups, researchers and social entrepreneurs, to government and regulatory agencies. Academic authors speak of users, patients, customers, funders and payers, highlighting the complex nature of CH markets. On the practice side, inclusion of patients in the design and development of connected health solutions relies on voluntary methods in 2/3 of European countries. We lack methods - to include a wider range of citizens, and to develop skills for both care professionals and citizens to fully participate in design and development of CH solutions. Conclusion: Key enablers for CH span multiple directions and scales.

Background Evidence-based health workforce policies are essential to ensure the provision of high-quality health services and to support the attainment of universal health coverage (UHC). This paper describes the main characteristics of available health workforce data for 74 of the 75 countries identified under the ‘Countdown to 2015’ initiative as accounting for more than 95% of the world’s maternal, newborn and child deaths. It also discusses best practices in the development of health workforce metrics post-2015. Methods Using available health workforce data from the Global Health Workforce Statistics database from the Global Health Observatory, we generated descriptive statistics to explore the current status, recent trends in the number of skilled health professionals (SHPs: physicians, nurses, midwives) per 10 000 population, and future requirements to achieve adequate levels of health care in the 74 countries. A rapid literature review was conducted to obtain an overview of the types of methods and the types of data sources used in human resources for health (HRH) studies. Results There are large intercountry and interregional differences in the density of SHPs to progress towards UHC in Countdown countries: a median of 10.2 per 10 000 population with range 1.6 to 142 per 10 000. Substantial efforts have been made in some countries to increase the availability of SHPs as shown by a positive average exponential growth rate (AEGR) in SHPs in 51% of Countdown countries for which there are data. Many of these countries will require large investments to achieve levels of workforce availability commensurate with UHC and the health-related sustainable development goals (SDGs). The availability, quality and comparability of global health workforce metrics remain limited. Most published workforce studies are descriptive, but more sophisticated needs-based workforce planning methods are being developed. Conclusions There is a need for high-quality, comprehensive, interoperable sources of HRH data to support all policies towards UHC and the health-related SDGs. The recent WHO-led initiative of supporting countries in the development of National Health Workforce Accounts is a very promising move towards purposive health workforce metrics post-2015. Such data will allow more countries to apply the latest methods for health workforce planning. Electronic supplementary material The online version of this article (doi:10.1186/s12960-017-0190-7) contains supplementary material, which is available to authorized users.

Aim: Although working life issues are subject to European health monitoring schemes, not many routine data sources include information on occupations or working conditions. Additional in-depth analysis is therefore necessary for diseases with high public health impact. The aim of this paper is to introduce a multidimensional ranking procedure for priority setting of diseases based on European and national data. Subject and methods: Multidimensional ranking was carried out on ten disease-specific indicators. First, suitable data sources were identified and information on indicators was retrieved. Second, the diseases were sorted by their ranks according to each indicator. Third, all ranks were added to a rank sum. Finally, the diseases were sorted by their rank sum. Results: Diseases of the circulatory system account for the highest rank sum. The high public health impact is visible in regard to most criteria, particularly to mortality, hospital discharges, and costs. Diseases of the digestive system rank second mainly because of high ranks for hospital discharges and costs. The third place is assigned to diseases of the musculoskeletal system. Conclusion: A multidimensional ranking procedure has advantages when used for priority setting of diseases. The procedure leads to an overall rank as a summary measure for the public health impact but information for each indicator is still retrieved. Furthermore, the procedure uses ranks and is therefore scale invariant. However, ranking procedures do not lead to a selection of diseases but a rank order. So, there is still a decision rule required to determine which diseases are selected e.g. for in-depth health reporting.

Incomplete data abound in epidemiological and clinical studies. When the missing data process is not properly investigated, inferences may be misleading. An increasing number of models that incorporate nonrandom incomplete data have become available. At the same time, however, serious doubts have arisen about the validity of these models, known to rely on strong and unverifiable assumptions. A common conclusion emerging from the current literature is the clear need for a sensitivity analysis. We propose in this paper a detailed sensitivity analysis using graphical and analytical techniques to understand the impact of missing-data assumptions on inferences. Specifically, we explore the influence of perturbing a missing at random model locally in the direction of non-random dropout models. Data from a psychiatric trial are used to illustrate the methodology. © Springer Science+Business Media LLC 2006. ispartof: Health Services and Outcomes Research Methodology vol:6 issue:1-2 pages:37-57 status: published