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Background Accurate, comprehensive, cause-specific mortality estimates are crucial for informing public health decision making worldwide. Incorrectly or vaguely assigned deaths, defined as garbage-coded deaths, mask the true cause distribution. The Global Burden of Disease (GBD) study has developed methods to create comparable, timely, cause-specific mortality estimates; an impactful data processing method is the reallocation of garbage-coded deaths to a plausible underlying cause of death. We identify the pattern of garbage-coded deaths in the world and present the methods used to determine their redistribution to generate more plausible cause of death assignments. Methods We describe the methods developed for the GBD 2019 study and subsequent iterations to redistribute garbage-coded deaths in vital registration data to plausible underlying causes. These methods include analysis of multiple cause data, negative correlation, impairment, and proportional redistribution. We classify garbage codes into classes according to the level of specificity of the reported cause of death (CoD) and capture trends in the global pattern of proportion of garbage-coded deaths, disaggregated by these classes, and the relationship between this proportion and the Socio-Demographic Index. We examine the relative importance of the top four garbage codes by age and sex and demonstrate the impact of redistribution on the annual GBD CoD rankings. Results The proportion of least-specific (class 1 and 2) garbage-coded deaths ranged from 3.7% of all vital registration deaths to 67.3% in 2015, and the age-standardized proportion had an overall negative association with the Socio-Demographic Index. When broken down by age and sex, the category for unspecified lower respiratory infections was responsible for nearly 30% of garbage-coded deaths in those under 1 year of age for both sexes, representing the largest proportion of garbage codes for that age group. We show how the cause distribution by number of deaths changes before and after redistribution for four countries: Brazil, the United States, Japan, and France, highlighting the necessity of accounting for garbage-coded deaths in the GBD. Conclusions We provide a detailed description of redistribution methods developed for CoD data in the GBD; these methods represent an overall improvement in empiricism compared to past reliance on a priori knowledge.

Background Linking Brazilian databases demands the development of algorithms and processes to deal with various challenges including the large size of the databases, the low number and poor quality of personal identifiers available to be compared (national security number not mandatory), and some characteristics of Brazilian names that make the linkage process prone to errors. This study aims to describe and evaluate the quality of the processes used to create an individual-linked database for data-intensive research on the impacts on health indicators of the expansion of primary care in Rio de Janeiro City, Brazil. Methods We created an individual-level dataset linking social benefits recipients, primary health care, hospital admission and mortality data. The databases were pre-processed, and we adopted a multiple approach strategy combining deterministic and probabilistic record linkage techniques, and an extensive clerical review of the potential matches. Relying on manual review as the gold standard, we estimated the false match (false-positive) proportion of each approach (deterministic, probabilistic, clerical review) and the missed match proportion (false-negative) of the clerical review approach. To assess the sensitivity (recall) to identifying social benefits recipients’ deaths, we used their vital status registered on the primary care database as the gold standard. Results In all linkage processes, the deterministic approach identified most of the matches. However, the proportion of matches identified in each approach varied. The false match proportion was around 1% or less in almost all approaches. The missed match proportion in the clerical review approach of all linkage processes were under 3%. We estimated a recall of 93.6% (95% CI 92.8–94.3) for the linkage between social benefits recipients and mortality data. Conclusion The adoption of a linkage strategy combining pre-processing routines, deterministic, and probabilistic strategies, as well as an extensive clerical review approach minimized linkage errors in the context of suboptimal data quality.

Background User interface (UI) design features such as screen layout, density of information, and use of colour may affect the usability of electronic prescribing (EP) systems, with usability problems previously associated with medication errors. To identify how to improve existing systems, our aim was to explore prescribers’ perspectives of UI features of a commercially available EP system, and how these may affect patient safety. Methods Two studies were conducted, each including ten participants prescribing a penicillin for a test patient with a penicillin allergy. In study 1, eye-gaze tracking was used as a means to explore visual attention and behaviour during prescribing, followed by a self-reported EP system usability scale. In study 2, a think-aloud method and semi-structured interview were applied to explore participants’ thoughts and views on prescribing, with a focus on UI design and patient safety. Results Study 1 showed high visual attention toward information on allergies and patient information, allergy pop-up alerts, and medication order review and confirmation, with less visual attention on adding medication. The system’s usability was rated ‘below average’. In study 2, participants highlighted EP design features and workflow, including screen layout and information overload as being important for patient safety, benefits of EP systems such as keeping a record of relevant information, and suggestions for improvement in relation to system design (colour, fonts, customization) and patient interaction. Conclusions Specific UI design factors were identified that may improve the usability and/or safety of EP systems. It is suggested that eye-gaze tracking and think-aloud methods are used in future experimental research in this area. Limitations include the small sample size; further work should include similar studies on other EP systems.

Background Enabling patients to be active users of their own medical records may promote the delivery of safe, efficient care across settings. Patients are rarely involved in designing digital health record systems which may make them unsuitable for patient use. We aimed to develop an evidence-based electronic health record (EHR) interface and participatory design process by involving patients and the public. Methods Participants were recruited to multi-step workshops involving individual and group design activities. A mixture of quantitative and qualitative questionnaires and observational methods were used to collect participant perspectives on interface design and feedback on the workshop design process. Results 48 recruited participants identified several design principles and components of a patient-centred electronic medical record interface. Most participants indicated that an interactive timeline would be an appropriate way to depict a medical history. Several key principles and design components, including the use of specific colours and shapes for clinical events, were identified. Participants found the workshop design process utilised to be useful, interesting, enjoyable and beneficial to their understanding of the challenges of information exchange in healthcare. Conclusion Patients and the public should be involved in EHR interface design if these systems are to be suitable for use by patient-users. Workshops, as used in this study, can provide an engaging format for patient design input. Design principles and components highlighted in this study should be considered when patient-facing EHR design interfaces are being developed.

Background Clinical decision support systems (DSS) aimed at supporting diagnosis are not widely used. This is mainly due to usability issues and lack of integration into clinical work and the electronic health record (EHR). In this study we examined the usability and acceptability of a diagnostic DSS prototype integrated with the EHR and in comparison with the EHR alone. Methods Thirty-four General Practitioners (GPs) consulted with 6 standardised patients (SPs) using only their EHR system (baseline session); on another day, they consulted with 6 different but matched for difficulty SPs, using the EHR with the integrated DSS prototype (DSS session). GPs were interviewed twice (at the end of each session), and completed the Post-Study System Usability Questionnaire at the end of the DSS session. The SPs completed the Consultation Satisfaction Questionnaire after each consultation. Results The majority of GPs (74%) found the DSS useful: it helped them consider more diagnoses and ask more targeted questions. They considered three user interface features to be the most useful: (1) integration with the EHR; (2) suggested diagnoses to consider at the start of the consultation and; (3) the checklist of symptoms and signs in relation to each suggested diagnosis. There were also criticisms: half of the GPs felt that the DSS changed their consultation style, by requiring them to code symptoms and signs while interacting with the patient. SPs sometimes commented that GPs were looking at their computer more than at them; this comment was made more often in the DSS session (15%) than in the baseline session (3%). Nevertheless, SP ratings on the satisfaction questionnaire did not differ between the two sessions. Conclusions To use the DSS effectively, GPs would need to adapt their consultation style, so that they code more information during rather than at the end of the consultation. This presents a potential barrier to adoption. Training GPs to use the system in a patient-centred way, as well as improvement of the DSS interface itself, could facilitate coding. To enhance patient acceptability, patients should be informed about the potential of the DSS to improve diagnostic accuracy. Electronic supplementary material The online version of this article (doi:10.1186/s12911-017-0477-6) contains supplementary material, which is available to authorized users.

Background In the UK, several initiatives have resulted in the creation of local data warehouses of electronic patient records. Originally developed for commissioning and direct patient care, they are potentially useful for research, but little is known about them outside their home area. We describe one such local warehouse, the Whole Systems Integrated Care (WSIC) database in NW London, and its potential for research as the “Discover” platform. We compare Discover with the Clinical Practice Research Datalink (CPRD), a popular UK research database also based on linked primary care records. Methods We describe the key features of the Discover database, including scope, architecture and governance; descriptive analyses compare the population demographics and chronic disease prevalences with those in CPRD. Results As of June 2019, Discover held records for a total of 2.3 million currently registered patients, or 95% of the NW London population; CPRD held records for over 11 million. The Discover population matches the overall age-sex distribution of the UK and CPRD but is more ethnically diverse. Most Discover chronic disease prevalences were comparable to the national rates. Unlike CPRD, Discover has identifiable care organisations and postcodes, allowing mapping and linkage to healthcare provider variables such as staffing, and includes contacts with social, community and mental health care. Discover also includes a consent-to-contact register of over 3000 volunteers to date for prospective studies. Conclusions Like CPRD, Discover has been a number of years in the making, is a valuable research tool, and can serve as a model for other areas developing similar data warehouses.

Background COPD is a highly heterogeneous disease composed of different phenotypes with different aetiological and prognostic profiles and current classification systems do not fully capture this heterogeneity. In this study we sought to discover, describe and validate COPD subtypes using cluster analysis on data derived from electronic health records. Methods We applied two unsupervised learning algorithms (k-means and hierarchical clustering) in 30,961 current and former smokers diagnosed with COPD, using linked national structured electronic health records in England available through the CALIBER resource. We used 15 clinical features, including risk factors and comorbidities and performed dimensionality reduction using multiple correspondence analysis. We compared the association between cluster membership and COPD exacerbations and respiratory and cardiovascular death with 10,736 deaths recorded over 146,466 person-years of follow-up. We also implemented and tested a process to assign unseen patients into clusters using a decision tree classifier. Results We identified and characterized five COPD patient clusters with distinct patient characteristics with respect to demographics, comorbidities, risk of death and exacerbations. The four subgroups were associated with 1) anxiety/depression; 2) severe airflow obstruction and frailty; 3) cardiovascular disease and diabetes and 4) obesity/atopy. A fifth cluster was associated with low prevalence of most comorbid conditions. Conclusions COPD patients can be sub-classified into groups with differing risk factors, comorbidities, and prognosis, based on data included in their primary care records. The identified clusters confirm findings of previous clustering studies and draw attention to anxiety and depression as important drivers of the disease in young, female patients. Electronic supplementary material The online version of this article (10.1186/s12911-019-0805-0) contains supplementary material, which is available to authorized users.

Background Technology can potentially enable the implementation of a value-based healthcare system, where the impact of quality of care is offered at optimised cost for maximised patient benefit. Technology can deliver value by aiding in data collection to evaluate outcomes and measure costs on a patient and population level. Healthcare organisations, however, face several challenges and risks that result almost exclusively from the use of these technologies. Discussion Some challenges associated with healthcare technology include their unsustainability, due to lack of scale-up plans and timely evaluations. Other risks include noncompliance with data protection policies, inadequate data governance, and overestimated expectations resulting from the rapid introduction of new technologies. Conclusion Organisations need to consider the risks and challenges associated with the use of technology and develop comprehensive strategies that mitigate factors leading to non-adoption and to realise benefits for achieving a value-based healthcare system.

Background Increased digitalization of healthcare comes along with the cost of cybercrime proliferation. This results to patients’ and healthcare providers' skepticism to adopt Health Information Technologies (HIT). In Europe, this shortcoming hampers efficient cross-border health data exchange, which requires a holistic, secure and interoperable framework. This study aimed to provide the foundations for designing a secure and interoperable toolkit for cross-border health data exchange within the European Union (EU), conducted in the scope of the KONFIDO project. Particularly, we present our user requirements engineering methodology and the obtained results, driving the technical design of the KONFIDO toolkit. Methods Our methodology relied on four pillars: (a) a gap analysis study, reviewing a range of relevant projects/initiatives, technologies as well as cybersecurity strategies for HIT interoperability and cybersecurity; (b) the definition of user scenarios with major focus on cross-border health data exchange in the three pilot countries of the project; (c) a user requirements elicitation phase containing a threat analysis of the business processes entailed in the user scenarios, and (d) surveying and discussing with key stakeholders, aiming to validate the obtained outcomes and identify barriers and facilitators for HIT adoption linked with cybersecurity and interoperability. Results According to the gap analysis outcomes, full adherence with information security standards is currently not universally met. Sustainability plans shall be defined for adapting existing/evolving frameworks to the state-of-the-art. Overall, lack of integration in a holistic security approach was clearly identified. For each user scenario, we concluded with a comprehensive workflow, highlighting challenges and open issues for their application in our pilot sites. The threat analysis resulted in a set of 30 user goals in total, documented in detail. Finally, indicative barriers of HIT acceptance include lack of awareness regarding HIT risks and legislations, lack of a security-oriented culture and management commitment, as well as usability constraints, while important facilitators concern the adoption of standards and current efforts for a common EU legislation framework. Conclusions Our study provides important insights to address secure and interoperable health data exchange, while our methodological framework constitutes a paradigm for investigating diverse cybersecurity-related risks in the health sector. Electronic supplementary material The online version of this article (10.1186/s12911-018-0664-0) contains supplementary material, which is available to authorized users.

Background Chronic obstructive pulmonary disease (COPD) and asthma are considered as the two most widespread obstructive lung diseases, whereas they affect more than 500 million people worldwide. Unfortunately, the requirement for detailed geometric models of the lungs in combination with the increased computational resources needed for the simulation of the breathing did not allow great progress to be made in the past for the better understanding of inflammatory diseases of the airways through detailed modelling approaches. In this context, computational fluid dynamics (CFD) simulations accompanied by fluid particle tracing (FPT) analysis of the inhaled ambient particles are deemed critical for lung function assessment. Also they enable the understanding of particle depositions on the airways of patients, since these accumulations may affect or lead to inflammations. In this direction, the current study conducts an initial investigation for the better comprehension of particle deposition within the lungs. More specifically, accurate models of the airways obstructions that relate to pulmonary disease are developed and a thorough assessment of the airflow behavior together with identification of the effects of inhaled particle properties, such as size and density, is conducted. Our approach presents a first step towards an effective personalization of pulmonary treatment in regards to the geometric characteristics of the lungs and the in depth understanding of airflows within the airways. Methods A geometry processing technique involving contraction algorithms is established and used to employ the different respiratory arrangements associated with lung related diseases that exhibit airways obstructions. Apart from the normal lung case, two categories of obstructed cases are examined, i.e. models with obstructions in both lungs and models with narrowings in the right lung only. Precise assumptions regarding airflow and deposition fraction (DF) over various sections of the lungs are drawn by simulating these distinct incidents through the finite volume method (FVM) and particularly the CFD and FPT algorithms. Moreover, a detailed parametric analysis clarifies the effects of the particles size and density in terms of regional deposition upon several parts of the pulmonary system. In this manner, the deposition pattern of various substances can be assessed. Results For the specific case of the unobstructed lung model most particles are detected on the right lung (48.56% of total, when the air flowrate is 12.6 L/min), a fact that is also true when obstructions arise symmetrically in both lungs (51.45% of total, when the air flowrate is 6.06 L/min and obstructions occur after the second generation). In contrast, when narrowings are developed on the right lung only, most particles are pushed on the left section (68.22% of total, when the air flowrate is 11.2 L/min) indicating that inhaled medication is generally deposited away from the areas of inflammation. This observation is useful when designing medical treatment of lung diseases. Furthermore, particles with diameters from 1 μm to 10 μm are shown to be mainly deposited on the lower airways, whereas particles with diameters of 20 μm and 30 μm are mostly accumulated in the upper airways. As a result, the current analysis indicates increased DF levels in the upper airways when the particle diameter is enlarged. Additionally, when the particles density increases from 1000 Kg/m3 to 2000 Kg/m3, the DF is enhanced on every generation and for all cases investigated herein. The results obtained by our simulations provide an accurate and quantitative estimation of all important parameters involved in lung modeling. Conclusions The treatment of respiratory diseases with inhaled medical substances can be advanced by the clinical use of accurate CFD and FPT simulations and specifically by evaluating the deposition of inhaled particles in a regional oriented perspective in regards to different particle sizes and particle densities. Since a drug with specific characteristics (i.e. particle size and density) exhibits maximum deposition on particular lung areas, the current study provides initial indications to a qualified physician for proper selection of medication.

Background:\ud Patient data from general practices is already used for many types of epidemiological research and increasingly, primary care systems to facilitate randomized clinical trials. The EU funded project TRANSFoRm aims to create a “Learning Healthcare System” at a European level that is able to support all types of research using primary care data, to recruit patients and follow patients in clinical studies and to improve diagnosis and therapy. The implementation of such a Learning Healthcare System needs an information model for clinical research (CRIM), as an informational backbone to integrate aspects of primary care with clinical trials and database searches.\ud \ud Methods:\ud Workflow descriptions and corresponding data objects of two clinical use cases (Gastro-Oesophageal Reflux Disease and Type 2 Diabetes) were described in UML activity diagrams. The components of activity diagrams were mapped to information objects of PCROM (Primary Care Research Object Model) and BRIDG (Biomedical Research Integrated Domain Group) and evaluated. The class diagram of PCROM was adapted to comply with workflow descriptions.\ud \ud Results:\ud The suitability of PCROM, a primary care information model already used for clinical trials, to act as an information model for TRANSFoRm was evaluated and resulted in its extension with 14 new information object types, two extensions of existing objects and the introduction of two new high-ranking concepts (CARE area and ENTRY area). No PCROM component was redundant. Our result illustrates that in primary care based research an important but underestimated portion of research activity takes place in the area of care (e.g. patient consultation, screening, recruitment and response to adverse events). The newly introduced CARE area for care-related research activities accounts for this shift and includes Episode of Care and Encounter as two new basic elements. In the ENTRY area different aspects of data collection were combined, including data semantics for observations, assessment activities, intervention activities and patient reporting to enable case report form (CRF) based data collection combined with decision support.\ud \ud Conclusions\ud Research with primary care data needs an extended information model that covers research activities at the care site which are characteristic for primary care based research and the requirements of the complicated data collection processes.

Background Immediate access to patients’ complete health records via electronic databases could improve healthcare and facilitate health research. However, the possible benefits of a national electronic health records (EHR) system must be balanced against public concerns about data security and personal privacy. Successful development of EHR requires better understanding of the views of the public and those most affected by EHR: users of the National Health Service. This study aims to explore the correlation between personal healthcare experience (including number of healthcare contacts and number and type of longer term conditions) and views relating to development of EHR for healthcare, health services planning and policy and health research. Methods/design A multi-site cross-sectional self-complete questionnaire designed and piloted for use in waiting rooms was administered to patients from randomly selected outpatients’ clinics at a university teaching hospital (431 beds) and general practice surgeries from the four primary care trusts within the catchment area of the hospital. All patients entering the selected outpatients clinics and general practice surgeries were invited to take part in the survey during August-September 2011. Statistical analyses will be conducted using descriptive techniques to present respondents’ overall views about electronic health records and logistic regression to explore associations between these views and participants’ personal circumstances, experiences, sociodemographics and more specific views about electronic health records. Discussion The study design and implementation were successful, resulting in unusually high response rates and overall recruitment (85.5%, 5336 responses). Rates for face-to-face recruitment in previous work are variable, but typically lower (mean 76.7%, SD 20). We discuss details of how we collected the data to provide insight into how we obtained this unusually high response rate.

Background Computerized decision support systems (DSS) have mainly focused on improving clinicians' diagnostic accuracy in unusual and challenging cases. However, since diagnostic omission errors may predominantly result from incomplete workup in routine clinical practice, the provision of appropriate patient- and context-specific reminders may result in greater impact on patient safety. In this experimental study, a mix of easy and difficult simulated cases were used to assess the impact of a novel diagnostic reminder system (ISABEL) on the quality of clinical decisions made by various grades of clinicians during acute assessment. Methods Subjects of different grades (consultants, registrars, senior house officers and medical students), assessed a balanced set of 24 simulated cases on a trial website. Subjects recorded their clinical decisions for the cases (differential diagnosis, test-ordering and treatment), before and after system consultation. A panel of two pediatric consultants independently provided gold standard responses for each case, against which subjects' quality of decisions was measured. The primary outcome measure was change in the count of diagnostic errors of omission (DEO). A more sensitive assessment of the system's impact was achieved using specific quality scores; additional consultation time resulting from DSS use was also calculated. Results 76 subjects (18 consultants, 24 registrars, 19 senior house officers and 15 students) completed a total of 751 case episodes. The mean count of DEO fell from 5.5 to 5.0 across all subjects (repeated measures ANOVA, p < 0.001); no significant interaction was seen with subject grade. Mean diagnostic quality score increased after system consultation (0.044; 95% confidence interval 0.032, 0.054). ISABEL reminded subjects to consider at least one clinically important diagnosis in 1 in 8 case episodes, and prompted them to order an important test in 1 in 10 case episodes. Median extra time taken for DSS consultation was 1 min (IQR: 30 sec to 2 min). Conclusion The provision of patient- and context-specific reminders has the potential to reduce diagnostic omissions across all subject grades for a range of cases. This study suggests a promising role for the use of future reminder-based DSS in the reduction of diagnostic error.

Background The commercial development and expansion of mobile phone networks has led to the creation of devices combining mobile phones and personal digital assistants, which could prove invaluable in a clinical setting. This pilot study aimed to look at how one such device compared with the current pager system in facilitating inter-professional communication in a hospital clinical team. Methods The study looked at a heterogeneous team of doctors (n = 9) working in a busy surgical setting at St. Mary's Hospital in London and compared the use of a personal digital assistant with mobile phone and web-browsing facilities to the existing pager system. The primary feature of this device being compared to the conventional pager was its use as a mobile phone, but other features evaluated included the ability to access the internet, and reference data on the device. A crossover study was carried out for 6 weeks in 2004, with the team having access to the personal digital assistant every alternate week. The primary outcome measure for assessing efficiency of communication was the length of time it took for clinicians to respond to a call. We also sought to assess the ease of adoption of new technology by evaluating the perceptions of the team (n = 9) to personal digital assistants, by administering a questionnaire. Results Doctors equipped with a personal digital assistant rather than a pager, responded more quickly to a call and had a lower of failure to respond rate (RR: 0.44; 95%CI 0.20–0.93). Clinicians also found this technology easy to adopt as seen by a significant reduction in perceptions of nervousness to the technology over the six-week study period (mean (SD) week 1: 4.10 (SD 1.69) vs. mean (SD) week 6: 2.20 (1.99); p = 0.04). Conclusion The results of this pilot study show the possible effects of replacing the current hospital pager with a newer, more technologically advanced device, and suggest that a combined personal digital assistant and mobile phone device may improve communication between doctors. In the light of these encouraging preliminary findings, we propose a large-scale clinical trial of the use of these devices in facilitating inter-professional communication in a hospital setting.