Predictors of bacteremia and death, including immune status, in a large single-center cohort of unvaccinated ICU patients with COVID-19 pneumonia.

BACKGROUND: We investigated the possible role of the immune profile at ICU admission, among other well characterized clinical and laboratory predictors of unfavorable outcome in COVID-19 patients assisted in ICU. METHODS: Retrospective analysis of clinical and laboratory data collected for all consecutive patients admitted to the ICUs of the General Hospital of Pescara (Abruzzo, Italy), between 1st March 2020 and 30th April 2021, with a confirmed diagnosis of COVID-19 respiratory failure. Logistic regressions were used to identify independent predictors of bacteremia and mortality. RESULTS: Out of 431 patients included in the study, bacteremia was present in N = 191 (44.3%) and death occurred in N = 210 (48.7%). After multivariate analysis, increased risk of bacteremia was found for viral reactivation (OR = 3.28; 95% CI:1.83-6.08), pronation (3.36; 2.12-5.37) and orotracheal intubation (2.51; 1.58-4.02). Increased mortality was found for bacteremia (2.05; 1.31-3.22), viral reactivation (2.29; 1.29-4.19) and lymphocytes < 0.6 × 103c/µL (2.32; 1.49-3.64). CONCLUSIONS: We found that viral reactivation, mostly due to Herpesviridae, was associated with increased risk of both bacteremia and mortality. In addition, pronation and intubation are strong predictors of bacteremia, which in turn together with severe lymphocytopenia due to SARS-CoV2 was associated with increased mortality. Most episodes of bacteremia, even due to Acinetobacter spp, were not predicted by microbiological evidence of colonization.

Monocyte Distribution Width as a predictor of community acquired sepsis in patients prospectively enrolled at the Emergency Department.

BACKGROUND: Monocyte Distribution Width (MDW), a simple cellular marker of innate monocyte activation, can be used for the early recognition of sepsis. We performed an observational prospective monocentric study to assess the predictive role of MDW in detecting sepsis in a sample of consecutive patients presenting at the Emergency Department. METHODS: Prospective observational study using demographic and clinical characteristics, past medical history and other laboratory measurements to predict confirmed sepsis using multivariate logistic regression. RESULTS: A total of 2724 patients were included in the study, of which 272 (10%) had sepsis or septic shock. After adjusting for known and potential risk factors, logistic regression found the following independent predictors of sepsis: SIRS equal to 1 (OR: 2.32, 1.16-4.89) and 2 or more (OR: 27.8, 14.8-56.4), MDW > 22 (OR: 3.73, 2.46-5.70), smoking (OR: 3.0, 1.22-7.31), end stage renal function (OR: 2.3, 1.25-4.22), neurodegenerative disease (OR: 2.2, 1.31-3.68), Neutrophils ≥ 8.9 × 103/µL (OR: 2.73, 1.82-4.11), Lymphocytes < 1.3 × 103/µL (OR: 1.72, 1.17-2.53) and CRP ≥ 19.1 mg/L (OR: 2.57, 1.63-4.08). A risk score derived from predictive models achieved high accuracy by using an optimal threshold (AUC: 95%; 93-97%). CONCLUSIONS: The study suggests that incorporating MDW in the clinical decision process may improve the early identification of sepsis, with minimal additional effort on the standard procedures adopted during emergency care.

The experiences of 33 national COVID-19 dashboard teams during the first year of the pandemic in the World Health Organization European Region: A qualitative study.

Background: Governments across the World Health Organization (WHO) European Region have prioritised dashboards for reporting COVID-19 data. The ubiquitous use of dashboards for public reporting is a novel phenomenon. Objective: This study explores the development of COVID-19 dashboards during the first year of the pandemic and identifies common barriers, enablers and lessons from the experiences of teams responsible for their development. Methods: We applied multiple methods to identify and recruit COVID-19 dashboard teams, using a purposive, quota sampling approach. Semi-structured group interviews were conducted from April to June 2021. Using elaborative coding and thematic analysis, we derived descriptive and explanatory themes from the interview data. A validation workshop was held with study participants in June 2021. Results: Eighty informants participated, representing 33 national COVID-19 dashboard teams across the WHO European Region. Most dashboards were launched swiftly during the first months of the pandemic, February to May 2020. The urgency, intense workload, limited human resources, data and privacy constraints and public scrutiny were common challenges in the initial development stage. Themes related to barriers or enablers were identified, pertaining to the pre-pandemic context, pandemic itself, people and processes and software, data and users. Lessons emerged around the themes of simplicity, trust, partnership, software and data and change. Conclusions: COVID-19 dashboards were developed in a learning-by-doing approach. The experiences of teams reveal that initial underpreparedness was offset by high-level political endorsement, the professionalism of teams, accelerated data improvements and immediate support with commercial software solutions. To leverage the full potential of dashboards for health data reporting, investments are needed at the team, national and pan-European levels.

Reliability of predictive models to support early decision making in the emergency department for patients with confirmed diagnosis of COVID-19: the Pescara Covid Hospital score.

BACKGROUND: The hospital management of patients diagnosed with COVID-19 can be hampered by heterogeneous characteristics at entry into the emergency department. We aimed to identify demographic, clinical and laboratory parameters associated with higher risks of hospitalisation, oxygen support, admission to intensive care and death, to build a risk score for clinical decision making at presentation to the emergency department. METHODS: We carried out a retrospective study using linked administrative data and laboratory parameters available in the initial phase of the pandemic at the emergency department of the regional reference hospital of Pescara, Abruzzo, Italy, March-June 2020. Logistic regression and Cox modelling were used to identify independent predictors for risk stratification. Validation was carried out collecting data from an extended timeframe covering other variants of concern, including Alpha (December 2020-January 2021) and Delta/Omicron (January-March 2022). RESULTS: Several clinical and laboratory parameters were significantly associated to the outcomes of interest, independently from age and gender. The strongest predictors were: for hospitalisation, monocyte distribution width ≥ 22 (4.09; 2.21-7.72) and diabetes (OR = 3.04; 1.09-9.84); for oxygen support: saturation < 95% (OR = 11.01; 3.75-41.14), lactate dehydrogenase≥237 U/L (OR = 5.93; 2.40-15.39) and lymphocytes< 1.2 × 103/µL (OR = 4.49; 1.84-11.53); for intensive care, end stage renal disease (OR = 59.42; 2.43-2230.60), lactate dehydrogenase≥334 U/L (OR = 5.59; 2.46-13.84), D-dimer≥2.37 mg/L (OR = 5.18; 1.14-26.36), monocyte distribution width ≥ 25 (OR = 3.32; 1.39-8.50); for death, procalcitonin≥0.2 ng/mL (HR = 2.86; 1.95-4.19) and saturation < 96% (HR = 2.74; 1.76-4.28). Risk scores derived from predictive models using optimal thresholds achieved values of the area under the curve between 81 and 91%. Validation of the scoring algorithm for the evolving virus achieved accuracy between 65 and 84%. CONCLUSIONS: A set of parameters that are normally available at emergency departments of any hospital can be used to stratify patients with COVID-19 at risk of severe conditions. The method shall be calibrated to support timely clinical decision during the first hours of admission with different variants of concern.

Adherence to General Diabetes and Foot Care Processes, with Prompt Referral, Are Associated with Amputation-Free Survival in People with Type 2 Diabetes and Foot Ulcers: A Scottish National Registry Analysis.

Aims: To compare different packages of care across care providers in Scotland on foot-related outcomes. Methods: A retrospective cohort study with primary and secondary care electronic health records from the Scottish Diabetes Registry, including 6,845 people with type 2 diabetes and a first foot ulcer occurring between 2013 and 2017. We assessed the association between exposure to care processes and major lower extremity amputation and death. Proportional hazards were used for time-to-event univariate and multivariate analyses, adjusting for case-mix characteristics and care processes. Results were expressed in terms of hazard ratios with 95% confidence intervals. Results: 2,243 (32.7%) subjects had a major amputation or death. Exposure to all nine care processes at all ages (HR = 0.63; 95% CI: 0.58-0.69; p < .001) and higher foot care attendance in people aged >70 years (HR = 0.88; 0.78-0.99; p = .03) were associated with longer major amputation-free survival. Waiting time ≥ 12 weeks between ulceration and clinic attendance was associated with worse outcomes (HR = 1.59; 1.37-1.84; p < .001). In people > 70 years, minor amputations were associated with improved major amputation-free survival (HR = 0.69; 0.52-0.92; p = .01). Conclusions: Strict adherence to a standardised package of general diabetes care before foot ulceration, timely foot care after ulceration, and specific treatment pathways were associated with longer major amputation-free survival among a large cohort of people with type 2 diabetes in Scotland, with a larger impact on older age groups.

The Effect of the COVID-19 Pandemic on Glycemic Monitoring and Other Processes of Care for Type 2 Diabetes: Protocol for a Retrospective Cohort Study.

BACKGROUND: Social distancing and other nonpharmaceutical interventions to reduce the spread of COVID-19 infection in the United Kingdom have led to substantial changes in delivering ongoing care for patients with chronic conditions, including type 2 diabetes mellitus (T2DM). Clinical guidelines for the management and prevention of complications for people with T2DM delivered in primary care services advise routine annual reviews and were developed when face-to-face consultations were the norm. The shift in consultations from face-to-face to remote consultations caused a reduction in direct clinical contact and may impact the process of care for people with T2DM. OBJECTIVE: The aim of this study is to explore the impact of the COVID-19 pandemic's first year on the monitoring of people with T2DM using routine annual reviews from a national primary care perspective in England. METHODS: A retrospective cohort study of adults with T2DM will be performed using routinely collected primary care data from the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC). We will describe the change in the rate of monitoring of hemoglobin A1c (HbA1c) between the first year of the COVID-19 pandemic (2020) and the preceding year (2019). We will also report any change in the eight checks that make up the components of these reviews. The change in HbA1c monitoring rates will be determined using a multilevel logistic regression model, adjusting for patient and practice characteristics, and similarly, the change in a composite measure of the completeness of all eight checks will be modeled using ordinal regression. The models will be adjusted for the following patient-level variables: age, gender, socioeconomic status, ethnicity, COVID-19 shielding status, duration of diabetes, and comorbidities. The model will also be adjusted for the following practice-level variables: urban versus rural, practice size, Quality and Outcomes Framework achievement, the National Health Service region, and the proportion of face-to-face consultations. Ethical approval was provided by the University of Oxford Medical Sciences Interdivisional Research Ethics Committee (September 2, 2021, reference R77306/RE001). RESULTS: The analysis of the data extract will include 3.96 million patients with T2DM across 700 practices, which is 6% of the available Oxford-RCGP RSC adult population. The preliminary results will be submitted to a conference under the domain of primary care. The resulting publication will be submitted to a peer-reviewed journal on diabetes and endocrinology. CONCLUSIONS: The COVID-19 pandemic has impacted the delivery of care, but little is known about the process of caring for people with T2DM. This study will report the impact of the COVID-19 pandemic on these processes of care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35971.

Patient Safety Monitoring in Acute Care in a Decentralized National Health Care System: Conceptual Framework and Initial Set of Actionable Indicators.

OBJECTIVES: Monitoring patient safety is critical for continuous quality improvement in acute care. We carried out a national project to identify a conceptual framework with core indicators that could be uniformly applied in the decentralized health system of Italy. METHODS: We used key international references to identify a framework with a core list of indicators and data sources for calculation in 4 hospitals in the Lombardy region. Two different data processing methods were applied: (a) centralized analysis of national databases and (b) decentralized data extraction and calculation using different hospital data available in Lombardy. RESULTS: Agreement was reached on a conceptual framework for patient safety monitoring in acute care, including structures, processes, and outcomes as vertical dimensions and health care needs as horizontal axes. We were able to compute 15 of 32 indicators through the application of a range of methods. The calculation of indicators using national databases was based on international standards. The consistency of the estimates obtained through the use of different methods and data sources seemed limited. CONCLUSIONS: We successfully identified a conceptual framework for patient safety in acute care including actionable indicators that can be calculated routinely using different data sources at national, regional, and hospital levels. Further work is required to compare methods and understand whether a combination of strategies at national and local levels could be proven effective.

Monocyte distribution width (MDW) as a new tool for the prediction of sepsis in critically ill patients: a preliminary investigation in an intensive care unit.

BACKGROUND: Monocyte Distribution Width (MDW), a simple proxy marker of innate monocyte activation, can be used for the early recognition of sepsis along with Procalcitonin. This study explored the added value of MDW as an early predictor of ensuing sepsis in patients hospitalised in an Intensive Care Unit. METHODS: We performed an observational prospective monocentric study to estimate the analytical performance of MDW in detecting ensuing sepsis in a sample of consecutive patients assisted in an Intensive Care Unit for > 48 h for any reason. Demographic and clinical characteristics, past medical history and other laboratory measurements were included as potential predictors of confirmed sepsis in multivariate logistic regression. RESULTS: A total of 211 patients were observed, 129 of whom were included in the final sample due to the suspect of ensuing sepsis; of these, 74 (57%) had a confirmed diagnosis of sepsis, which was best predicted with the combination of MDW > 23.0 and PCT > 0.5 ng/mL (Positive Predictive Value, PPV: 92.6, 95% CI: 82.1-97.9). The best MDW cut-off to rule out sepsis was ≤20.0 (Negative Predictive Value, NPV: 86.4, 95% CI: 65.1-97.1). Multivariate analyses using both MDW and PCT found a significant association for MDW > 23 only (OR:17.64, 95% CI: 5.53-67.91). CONCLUSION: We found that values of MDW > 23 were associated with a high PPV for sepsis, whereas values of MDW ≤ 20 were associated with a high NPV. Our findings suggest that MDW may help clinicians to monitor ICU patients at risk of sepsis, with minimal additional efforts over standard of care.

Dashboards to reduce inappropriate prescribing of metformin and aspirin: A quality assurance programme in a primary care sentinel network.

AIMS: To pilot two dashboards to monitor prescribing of metformin and aspirin according to the National Institute for Health and Care Excellence (NICE) 'Do-Not-Do' recommendations. METHODS: This quality assurance programme was conducted in twelve general practices of the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) network. We developed dashboards to flag inappropriate prescribing of metformin and aspirin to people with type 2 diabetes mellitus (T2DM). In Phase 1, six practices (Group A) received a dashboard flagging suboptimal metformin prescriptions in people with reduced renal function. The other six practices (Group B) were controls. In Phase 2, Group B were provided a dashboard to flag inappropriate aspirin prescribing and Group A were controls. We used logistic regression to explore associations between dashboard exposure and inappropriate prescribing. RESULTS: The cohort comprised 5644 individuals (Group A, n = 2656; Group B, n = 2988). Half (51.6%, n = 2991) were prescribed metformin of which 15 (0.5%) were inappropriate (Group A, n = 10; Group B, n = 5). A fifth (17.6%, n = 986) were prescribed aspirin of which 828 (84.0%) were inappropriate. During Phase 1, metformin was stopped in 50% (n = 5) of people in Group A, compared with 20% (n = 1) in the control group (Group B); in Phase 2, the odds ratio of inappropriate aspirin prescribing was significantly lower in practices that received the dashboard versus control (0.44, 95%CI 0.27-0.72). CONCLUSIONS: It was feasible to use a dashboard to flag inappropriate prescribing. Whilst underpowered to report a change in metformin, we demonstrated a reduction in inappropriate aspirin prescribing.

A nationwide participatory programme to measure person-centred hospital care in Italy: Results and implications for continuous improvement.

BACKGROUND: Patient-centredness has been targeted by the Italian government as a key theme for the future development of health services. OBJECTIVE: Measuring patient-centred health services in partnership with citizens, health professionals and decision makers. DESIGN: National participatory survey in a large test set of hospitals at national level. SETTING AND PARTICIPANTS: A total of 387 hospital visits conducted in 16 Italian regions by over 1,500 citizens and health professionals during 2017-2018. MAIN VARIABLES AND OUTCOME MEASURES: An ad hoc checklist was used to assess person-centredness in hospital care through 243 items, grouped in 4 main areas, 12 sub-areas and 29 person-centred criteria (scored 0-10). GEE linear multivariate regression was used to explore the relation between hospital characteristics and person-centredness. RESULTS: Person-centred scores were moderately high, with substantial variation overall (median score: 7.0, range: 3.2-9.5) and by area (Care Processes: 6.8, 2.0-9.8; Access: 7.4, 2.7-9.7; Transparency: 6.7, 3.4-9.5 and Relationship: 7.3, 0.8-10.0). Multivariate regression found higher scores for increasing volumes of activity (quartile increase: +0.21; 95% CI: 0.13, 0.29) and lower scores in the south and islands (-1.03; -1.62,-0.45). DISCUSSION: The checklist has been applied successfully by over 1,500 collaborators who assessed hospitals in 16 distinct Regions and Autonomous Provinces of Italy. Despite an overall positive mark, all scores were highly variable by location and hospital characteristics. CONCLUSION AND PATIENT OR PUBLIC CONTRIBUTION: A national participatory programme to improve patient-centredness in Italian hospitals highlighted critical areas with the direct input of citizens.

Health service organisation impact on lower extremity amputations in people with type 2 diabetes with foot ulcers: systematic review and meta-analysis.

AIMS: Despite the evidence available on the epidemiology of diabetic foot ulcers and associated complications, it is not clear how specific organizational aspects of health care systems can positively affect their clinical trajectory. We aim to evaluate the impact of organizational aspects of care on lower extremity amputation rates among people with type 2 diabetes affected by foot ulcers. METHODS: We conducted a systematic review of the scientific literature published between 1999 and 2019, using the following key terms as search criteria: people with type 2 diabetes, diagnosed with diabetic foot ulcer, treated with specific processes and care pathways, and LEA as primary outcome. Overall results were reported as pooled odds ratios and 95% confidence intervals obtained using fixed and random effects models. RESULTS: A total of 57 studies were found eligible, highlighting the following arrangements: dedicated teams, care pathways and protocols, multidisciplinary teams, and combined interventions. Among them, seven studies qualified for a meta-analysis. According to the random effects model, interventions including any of the four arrangements were associated with a 29% reduced risk of any type of lower extremity amputation (OR = 0.71; 95% CI 0.52-0.96). The effect was larger when focusing on major LEAs alone, leading to a 48% risk reduction (OR = 0.52; 95% CI 0.30-0.91). CONCLUSIONS: Specific organizational arrangements including multidisciplinary teams and care pathways can prevent half of the amputations in people with diabetes and foot ulcers. Further studies using standardized criteria are needed to investigate the cost-effectiveness to facilitate wider implementation of improved organizational arrangements. Similarly, research should identify specific roadblocks to translating evidence into action. These may be structures and processes at the health system level, e.g. availability of professionals with the right skillset, reimbursement mechanisms, and clear organizational intervention implementation guidelines.

Making Use of Comparable Health Data to Improve Quality of Care and Outcomes in Diabetes: The EUBIROD Review of Diabetes Registries and Data Sources in Europe.

Background: Registries and data sources contain information that can be used on an ongoing basis to improve quality of care and outcomes of people with diabetes. As a specific task of the EU Bridge Health project, we carried out a survey of diabetes-related data sources in Europe. Objectives: We aimed to report on the organization of different sources of diabetes information, including their governance, information infrastructure and dissemination strategies for quality control, service planning, public health, policy and research. Methods: Survey using a structured questionnaire to collect targeted data from a network of collaborating institutions managing registries and data sources in 17 countries in the year 2017. Results: The 18 data sources participating in the study were most frequently academic centres (44.4%), national (72.2%), targeting all types of diabetes (61.1%) covering no more than 10% of the target population (44.4%). Although population-based in over a quarter of cases (27.8%), sources relied predominantly on provider-based datasets (38.5%), fewer using administrative data (16.6%). Data collection was continuous in the majority of cases (61.1%), but 50% could not perform data linkage. Public reports were more frequent (72.2%) as well as quality reports (77.8%), but one third did not provide feedback to policy and only half published ten or more peer reviewed papers during the last 5 years. Conclusions: The heterogeneous implementation of diabetes registries and data sources hampers the comparability of quality and outcomes across Europe. Best practices exist but need to be shared more effectively to accelerate progress and deliver equitable results for people with diabetes.

Consistency of safety monitoring using routine national databases: results using a quality of care interpretative model.

BACKGROUND: In the framework of targeted action for continuous safety monitoring, we aimed to evaluate the consistency of indicators derived from available databases for regular reporting. METHODS: We used a quality of care interpretative model to select characteristics from five national databases, aggregated and linked by homogeneous groups of providers. The target population included all subjects admitted to public hospitals for acute care in four regions of Italy between 2011 and 2013. The association between structures, processes and safety-related outcomes was investigated using odds ratios from generalized estimating equations logistic regression. Outcome measures included claims of malpractice and five patient safety indicators calculated from discharge abstracts using standardized algorithms. RESULTS: Over 3 years, claims of malpractice and sepsis increased, whereas deep vein thrombosis and pulmonary embolism decreased. Hospitals with high vs. low volume of discharges were associated with -16% lower rates of claims, but +12% increased risk of sepsis. Compared with research institutes, university clinics had -17% lower rates of claims and -41% cases of dehiscence, with a +32% increased risk of deep vein thrombosis. Local health care authorities recorded -49% deep vein thrombosis, -26% pulmonary embolism, -40% sepsis and +37% risk of claims. Hospitals submitting cases of safe practices and implementing safety recommendations showed significantly higher rates for most outcome measures. CONCLUSIONS: Indicators from regular databases can be conveniently used to develop a national safety monitoring system for hospital care. Although deeper analysis is needed, institutions with a higher propensity to implement safe practices and recommendations consistently showed higher rates of adverse events.

Assessing data protection and governance in health information systems: a novel methodology of Privacy and Ethics Impact and Performance Assessment (PEIPA).

BACKGROUND: Data processing of health research databases often requires a Data Protection Impact Assessment to evaluate the severity of the risk and the appropriateness of measures taken to comply with the European Union (EU) General Data Protection Regulation (GDPR). We aimed to define and apply a comprehensive method for the evaluation of privacy, data governance and ethics among research networks involved in the EU Project Bridge Health. METHODS: Computerised survey among associated partners of main EU Consortia, using a targeted instrument designed by the principal investigator and progressively refined in collaboration with an international advisory panel. Descriptive measures using the percentage of adoption of privacy, data governance and ethical principles as main endpoints were used for the analysis and interpretation of the results. RESULTS: A total of 15 centres provided relevant information on the processing of sensitive data from 10 European countries. Major areas of concern were noted for: data linkage (median, range of adoption: 45%, 30%-80%), access and accuracy of personal data (50%, 0%-100%) and anonymisation procedures (56%, 11%-100%). A high variability was noted in the application of privacy principles. CONCLUSIONS: A comprehensive methodology of Privacy and Ethics Impact and Performance Assessment was successfully applied at international level. The method can help implementing the GDPR and expanding the scope of Data Protection Impact Assessment, so that the public benefit of the secondary use of health data could be well balanced with the respect of personal privacy.

An in-depth assessment of diabetes-related lower extremity amputation rates 2000-2013 delivered by twenty-one countries for the data collection 2015 of the Organization for Economic Cooperation and Development (OECD).

BACKGROUND: International comparisons of diabetes-related lower extremity amputation rates are still hampered by different criteria used for data collection and analysis. We aimed to evaluate trends and variation of major/minor amputations, using agreed definitions adopted by the Organization for Economic Cooperation and Development in 2015. METHODS: Direct age-sex standardized rates were calculated per 100,000 subjects per year between 2000 and 2013, using major/minor amputations with diabetes diagnosis as numerators and the total population or number of people with diabetes as denominators. Longitudinal trends were investigated using generalized estimating equations. RESULTS: Twenty-one countries reported major amputations referred to the general population, showing a mean reduction from 10.8 to 7.5 per 100,000 (- 30.6%). Eleven countries also reported major amputations among people with diabetes, showing a mean reduction from 182.9 to 128.3 per 100,000 (- 29.8%). Minor amputations remained stable over the study period. Longitudinal trends showed a significant average annual decrease of - 0.19 per 100,000 in the general population (95% CI - 0.36 to - 0.02; p = .03) and - 4.52 per 100,000 among subjects with diabetes (95% CI - 6.09 to - 2.94; p < .001). The coefficient of variation of major amputation rates between countries was fairly high (64%-in the total population, 67% among people with diabetes). CONCLUSIONS: The study highlighted a clinically significant reduction of major amputations, in both the general population and among people with diabetes. The use of standardized definitions, while increasing the comparability of multinational data, highlighted remarkable differences between countries. These results can help identifying and sharing best practices effectively on a global scale.

A Position Statement on Population Data Science: The Science of Data about People.

Information is increasingly digital, creating opportunities to respond to pressing issues about human populations using linked datasets that are large, complex, and diverse. The potential social and individual benefits that can come from data-intensive science are large, but raise challenges of balancing individual privacy and the public good, building appropriate socio-technical systems to support data-intensive science, and determining whether defining a new field of inquiry might help move those collective interests and activities forward. A combination of expert engagement, literature review, and iterative conversations led to our conclusion that defining the field of Population Data Science (challenge 3) will help address the other two challenges as well. We define Population Data Science succinctly as the science of data about people and note that it is related to but distinct from the fields of data science and informatics. A broader definition names four characteristics of: data use for positive impact on citizens and society; bringing together and analyzing data from multiple sources; finding population-level insights; and developing safe, privacy-sensitive and ethical infrastructure to support research. One implication of these characteristics is that few people possess all of the requisite knowledge and skills of Population Data Science, so this is by nature a multi-disciplinary field. Other implications include the need to advance various aspects of science, such as data linkage technology, various forms of analytics, and methods of public engagement. These implications are the beginnings of a research agenda for Population Data Science, which if approached as a collective field, can catalyze significant advances in our understanding of trends in society, health, and human behavior.

Quality and Predictors of Diabetes Care Among Patients With Schizophrenia: A Danish Nationwide Study.

OBJECTIVE: Patients with schizophrenia have a high prevalence of diabetes, but data on diabetes care quality for these patients are limited. This nationwide study compared the quality of diabetes care among individuals with and without schizophrenia and identified predictors of care quality. METHODS: In a population-based cohort study, 83,813 individuals with diabetes seen at hospital outpatient clinics between 2005 and 2013, including 669 with comorbid schizophrenia, were identified from Danish registries. High-quality diabetes care was defined as having received ≥80% of guideline-recommended process performance measures. Variables assessed as predictors of diabetes care included patient-specific (sex, age, smoking, substance abuse, Global Assessment of Functioning score, and duration of schizophrenia), provider-specific (quality of schizophrenia care), and system-specific (annual patient contact volume of the diabetes clinic) factors. RESULTS: Compared with individuals with diabetes only, those with diabetes and schizophrenia were less likely to receive high-quality diabetes care (relative risk [RR]=.91, 95% confidence interval [CI]=.88-.95) and less likely to receive several individual process performance measures of diabetes care, including blood pressure monitoring (RR=.98, CI=.96-.99), treatment with antihypertensive drugs (RR=.83, CI=.70-.97) and angiotensin-converting enzyme/angiotensin II receptor inhibitors (RR=.72, CI=.55-.93), screening for albuminuria (RR=.96, CI=.93-.99), eye examination at least once every second year (RR=.97, CI=.94-.99), and foot examination (RR=.96, CI=.93-.99). Predictors of poor diabetes care among individuals with schizophrenia included documented drug abuse and low contact volume of the diabetes clinic. CONCLUSIONS: Individuals with schizophrenia received lower-quality diabetes care compared with those without schizophrenia. However, absolute differences in care were modest.

Essential levels of health information in Europe: an action plan for a coherent and sustainable infrastructure.

The European Union needs a common health information infrastructure to support policy and governance on a routine basis. A stream of initiatives conducted in Europe during the last decade resulted into several success stories, but did not specify a unified framework that could be broadly implemented on a continental level. The recent debate raised a potential controversy on the different roles and responsibilities of policy makers vs the public health community in the construction of such a pan-European health information system. While institutional bodies shall clarify the statutory conditions under which such an endeavour is to be carried out, researchers should define a common framework for optimal cross-border information exchange. This paper conceptualizes a general solution emerging from past experiences, introducing a governance structure and overarching framework that can be realized through four main action lines, underpinned by the key principle of "Essential Levels of Health Information" for Europe. The proposed information model is amenable to be applied in a consistent manner at both national and EU level. If realized, the four action lines outlined here will allow developing a EU health information infrastructure that would effectively integrate best practices emerging from EU public health initiatives, including projects and joint actions carried out during the last ten years. The proposed approach adds new content to the ongoing debate on the future activity of the European Commission in the area of health information.

Cross-border flow of health information: is 'privacy by design' enough? Privacy performance assessment in EUBIROD.

BACKGROUND: The EUBIROD project aims to perform a cross-border flow of diabetes information across 19 European countries using the BIRO information system, which embeds privacy principles and data protection mechanisms in its architecture (privacy by design). A specific task of EUBIROD was to investigate the variability in the implementation of the EU Data Protection Directive (DPD) across participating centres. METHODS: Compliance with privacy requirements was assessed by means of a specific questionnaire administered to all participating diabetes registers. Items included relevant issues e.g. patient consent, accountability of data custodian, communication (openness) and complaint procedures (challenging compliance), authority to disclose, accuracy, access and use of personal information, and anonymization. The identification of an ad hoc scoring system and statistical software allowed an overall quali-quantitative analysis and independent evaluation of questionnaire responses, automated through a dedicated IT platform ('privacy performance assessment'). RESULTS: A total of 18 diabetes registers from different countries completed the survey. Over 50% of the registers recorded a maximum score for accountability, openness, anonymization and challenging compliance. Low average values were found for disclosure and disposition, access, consent, use of personal information and accuracy. A high heterogeneity was found for anonymization, consent, accuracy and access. CONCLUSIONS: The novel method of privacy performance assessment realized in EUBIROD may improve the respect of privacy in each data source, reduce overall variability in the implementation of privacy principles and favour a sound and legitimate cross-border exchange of high quality data across Europe.