System Architecture of a European Platform for Health Policy Decision Making: MIDAS.

Background: Healthcare data is a rich yet underutilized resource due to its disconnected, heterogeneous nature. A means of connecting healthcare data and integrating it with additional open and social data in a secure way can support the monumental challenge policy-makers face in safely accessing all relevant data to assist in managing the health and wellbeing of all. The goal of this study was to develop a novel health data platform within the MIDAS (Meaningful Integration of Data Analytics and Services) project, that harnesses the potential of latent healthcare data in combination with open and social data to support evidence-based health policy decision-making in a privacy-preserving manner. Methods: The MIDAS platform was developed in an iterative and collaborative way with close involvement of academia, industry, healthcare staff and policy-makers, to solve tasks including data storage, data harmonization, data analytics and visualizations, and open and social data analytics. The platform has been piloted and tested by health departments in four European countries, each focusing on different region-specific health challenges and related data sources. Results: A novel health data platform solving the needs of Public Health decision-makers was successfully implemented within the four pilot regions connecting heterogeneous healthcare datasets and open datasets and turning large amounts of previously isolated data into actionable information allowing for evidence-based health policy-making and risk stratification through the application and visualization of advanced analytics. Conclusions: The MIDAS platform delivers a secure, effective and integrated solution to deal with health data, providing support for health policy decision-making, planning of public health activities and the implementation of the Health in All Policies approach. The platform has proven transferable, sustainable and scalable across policies, data and regions.

NewsMeSH: A new classifier designed to annotate health news with MeSH headings.

MOTIVATION: In the age of big data, the amount of scientific information available online dwarfs the ability of current tools to support researchers in locating and securing access to the necessary materials. Well-structured open data and the smart systems that make the appropriate use of it are invaluable and can help health researchers and professionals to find the appropriate information by, e.g., configuring the monitoring of information or refining a specific query on a disease. METHODS: We present an automated text classifier approach based on the MEDLINE/MeSH thesaurus, trained on the manual annotation of more than 26 million expert-annotated scientific abstracts. The classifier was developed tailor-fit to the public health and health research domain experts, in the light of their specific challenges and needs. We have applied the proposed methodology on three specific health domains: the Coronavirus, Mental Health and Diabetes, considering the pertinence of the first, and the known relations with the other two health topics. RESULTS: A classifier is trained on the MEDLINE dataset that can automatically annotate text, such as scientific articles, news articles or medical reports with relevant concepts from the MeSH thesaurus. CONCLUSIONS: The proposed text classifier shows promising results in the evaluation of health-related news. The application of the developed classifier enables the exploration of news and extraction of health-related insights, based on the MeSH thesaurus, through a similar workflow as in the usage of PubMed, with which most health researchers are familiar.

Identifying Key Predictors of Cognitive Dysfunction in Older People Using Supervised Machine Learning Techniques: Observational Study.

BACKGROUND: Machine learning techniques, specifically classification algorithms, may be effective to help understand key health, nutritional, and environmental factors associated with cognitive function in aging populations. OBJECTIVE: This study aims to use classification techniques to identify the key patient predictors that are considered most important in the classification of poorer cognitive performance, which is an early risk factor for dementia. METHODS: Data were used from the Trinity-Ulster and Department of Agriculture study, which included detailed information on sociodemographic, clinical, biochemical, nutritional, and lifestyle factors in 5186 older adults recruited from the Republic of Ireland and Northern Ireland, a proportion of whom (987/5186, 19.03%) were followed up 5-7 years later for reassessment. Cognitive function at both time points was assessed using a battery of tests, including the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), with a score <70 classed as poorer cognitive performance. This study trained 3 classifiers-decision trees, Naïve Bayes, and random forests-to classify the RBANS score and to identify key health, nutritional, and environmental predictors of cognitive performance and cognitive decline over the follow-up period. It assessed their performance, taking note of the variables that were deemed important for the optimized classifiers for their computational diagnostics. RESULTS: In the classification of a low RBANS score (<70), our models performed well (F1 score range 0.73-0.93), all highlighting the individual's score from the Timed Up and Go (TUG) test, the age at which the participant stopped education, and whether or not the participant's family reported memory concerns to be of key importance. The classification models performed well in classifying a greater rate of decline in the RBANS score (F1 score range 0.66-0.85), also indicating the TUG score to be of key importance, followed by blood indicators: plasma homocysteine, vitamin B6 biomarker (plasma pyridoxal-5-phosphate), and glycated hemoglobin. CONCLUSIONS: The results suggest that it may be possible for a health care professional to make an initial evaluation, with a high level of confidence, of the potential for cognitive dysfunction using only a few short, noninvasive questions, thus providing a quick, efficient, and noninvasive way to help them decide whether or not a patient requires a full cognitive evaluation. This approach has the potential benefits of making time and cost savings for health service providers and avoiding stress created through unnecessary cognitive assessments in low-risk patients.

TAQIH, a tool for tabular data quality assessment and improvement in the context of health data.

BACKGROUND AND OBJECTIVES: Data curation is a tedious task but of paramount relevance for data analytics and more specially in the health context where data-driven decisions must be extremely accurate. The ambition of TAQIH is to support non-technical users on 1) the exploratory data analysis (EDA) process of tabular health data, and 2) the assessment and improvement of its quality. METHODS: A web-based tool has been implemented with a simple yet powerful visual interface. First, it provides interfaces to understand the dataset, to gain the understanding of the content, structure and distribution. Then, it provides data visualization and improvement utilities for the data quality dimensions of completeness, accuracy, redundancy and readability. RESULTS: It has been applied in two different scenarios. (1) The Northern Ireland General Practitioners (GPs) Prescription Data, an open data set containing drug prescriptions. (2) A glucose monitoring tele health system dataset. Findings on (1) include: Features that had significant amount of missing values (e.g. AMP_NM variable 53.39%); instances that have high percentage of variable values missing (e.g. 0.21% of the instances with > 75% of missing values); highly correlated variables (e.g. Gross and Actual cost almost completely correlated (∼ + 1.0)). Findings on (2) include: Features that had significant amount of missing values (e.g. patient height, weight and body mass index (BMI) (> 70%), date of diagnosis 13%)); highly correlated variables (e.g. height, weight and BMI). Full detail of the testing and insights related to findings are reported. CONCLUSIONS: TAQIH enables and supports users to carry out EDA on tabular health data and to assess and improve its quality. Having the layout of the application menu arranged sequentially as the conventional EDA pipeline helps following a consistent analysis process. The general description of the dataset and features section is very useful for the first overview of the dataset. The missing value heatmap is also very helpful in visually identifying correlations among missing values. The correlations section has proved to be supportive as a preliminary step before further data analysis pipelines, as well as the outliers section. Finally, the data quality section provides a quantitative value to the dataset improvements.

Exploring patient information needs in type 2 diabetes: A cross sectional study of questions.

This study set out to analyze questions about type 2 diabetes mellitus (T2DM) from patients and the public. The aim was to better understand people's information needs by starting with what they do not know, discovered through their own questions, rather than starting with what we know about T2DM and subsequently finding ways to communicate that information to people affected by or at risk of the disease. One hundred and sixty-four questions were collected from 120 patients attending outpatient diabetes clinics and 300 questions from 100 members of the public through the Amazon Mechanical Turk crowdsourcing platform. Twenty-three general and diabetes-specific topics and five phases of disease progression were identified; these were used to manually categorize the questions. Analyses were performed to determine which topics, if any, were significant predictors of a question's being asked by a patient or the public, and similarly for questions from a woman or a man. Further analysis identified the individual topics that were assigned significantly more often to the crowdsourced or clinic questions. These were Causes (CI: [-0.07, -0.03], p < .001), Risk Factors ([-0.08, -0.03], p < .001), Prevention ([-0.06, -0.02], p < .001), Diagnosis ([-0.05, -0.02], p < .001), and Distribution of a Disease in a Population ([-0.05,-0.01], p = .0016) for the crowdsourced questions and Treatment ([0.03, 0.01], p = .0019), Disease Complications ([0.02, 0.07], p < .001), and Psychosocial ([0.05, 0.1], p < .001) for the clinic questions. No highly significant gender-specific topics emerged in our study, but questions about Weight were more likely to come from women and Psychosocial questions from men. There were significantly more crowdsourced questions about the time Prior to any Diagnosis ([(-0.11, -0.04], p = .0013) and significantly more clinic questions about Health Maintenance and Prevention after diagnosis ([0.07. 0.17], p < .001). A descriptive analysis pointed to the value provided by the specificity of questions, their potential to disclose emotions behind questions, and the as-yet unrecognized information needs they can reveal. Large-scale collection of questions from patients across the spectrum of T2DM progression and from the public-a significant percentage of whom are likely to be as yet undiagnosed-is expected to yield further valuable insights.

Performance analysis of a new hypersonic vitrector system.

PURPOSE: To evaluate porcine vitreous flow and water flow rates in a new prototype hypersonic vitrectomy system compared to currently available pneumatic guillotine vitrectors (GVs) systems. METHODS: Two vitrectors were tested, a prototype, ultrasound-powered, hypersonic vitrector (HV) and a GV. Porcine vitreous was obtained within 12 to 24 h of sacrifice and kept at 4°C. A vial of vitreous or water was placed on a precision balance and its weight measured before and after the use of each vitrector. Test parameters included changes in aspiration levels, vitrector gauge, cut rates for GVs, % ultrasound (US) power for HVs, and port size for HVs. Data was analysed using linear regression and t-tests. RESULTS: There was no difference in the total average mean water flow between the 25-gauge GV and the 25-gauge HV (t-test: P = 0.363); however, 25-gauge GV was superior (t-test: P < 0.001) in vitreous flow. The 23-gauge GV was only more efficient in water and vitreous removal than 23-gauge HV needle-1 (Port 0.0055) (t-test: P < 0.001). For HV, wall thickness and gauge had no effect on flow rates. Water and vitreous flows showed a direct correlation with increasing aspiration levels and % US power (p<0.05). CONCLUSIONS: The HV produced consistent water and vitreous flow rates across the range of US power and aspiration levels tested. Hypersonic vitrectomy may be a promising new alternative to the currently available guillotine-based technologies.

Ultrastructural and histopathologic findings after pars plana vitrectomy with a new hypersonic vitrector system. Qualitative preliminary assessment.

PURPOSE: Preliminary assessment of a new prototype ultrasound-based hypersonic vitrector (HV) by qualitatively examining the histopathological changes in the retina and vitreous body after pars plana vitrectomy (PPV) and its ability to fragment vitreous collagen. METHODS: Fourteen porcine cadaveric eyes, 20 eyes in live swine and six human cadaveric eyes underwent PPV using the HV or a pneumatic guillotine vitrector (GV). An additional 4 porcine crystalline lenses were touched with either the HV or GV for 1 minute. Following PPV, human vitreous was removed and processed for electron microscopy (EM). Eyes and lenses were fixed and sectioned for light microscopy (LM). RESULTS: There were no macroscopic retinal or optic nerve defects associated with either HV or GV PPVs. Cadaveric retinal specimens showed separation of the inner limiting membrane (ILM) and vacuolization and fragmentation at the nerve fiber layer (NFL) and the ganglion cell layer (GCL). ILM fragmentation and separation were found after PPV in live swine with both vitrectors. Small disruptions of the posterior capsule or structural lens defects were found after HV touch. The EM analysis revealed more fragmentation of human vitreous collagen fibrils after HV compared to GV PPV. CONCLUSIONS: LM and EM analysis of retina, vitreous, and crystalline lens after PPV showed similar morphological changes using the HV or the GV. Vitreous fragmentation appeared more effective with the HV. Overall this study suggests that the HV may be a promising new technology. More work is needed to quantitatively assess its safety and efficacy.

Soliciting and Responding to Patients' Questions about Diabetes Through Online Sources.

When patients cannot get answers from health professionals or retain the information given, increasingly they search online for answers, with limited success. Researchers from the United States, Ireland, and the United Kingdom explored this problem for patients with type 2 diabetes mellitus (T2DM). In 2014, patients attending an outpatient clinic (UK) were asked to submit questions about diabetes. Ten questions judged representative of different types of patient concerns were selected by the researchers and submitted to search engines within trusted and vetted websites in the United States, Ireland, and the United Kingdom. Two researchers independently assessed if answers could be found in the three top-ranked documents returned at each website. The 2014 search was repeated in June, 2016, examining the two top-ranked documents returned. One hundred and sixty-four questions were collected from 120 patients during 12 outpatient clinics. Most patients had T2DM (95%). Most questions were about diabetes (N = 155) with the remainder related to clinic operation (N = 9). Of the questions on diabetes, 152 were about T2DM. The 2014 assessment found no adequate answers to the questions in 90 documents (10 questions, 3 websites, 3 top documents). In the 2016 assessment, 1 document out of 60 (10 questions, 3 websites, 2 top documents) provided an adequate answer relating to 1 of the 10 questions. Available online sources of information do not provide answers to questions from patients with diabetes. Our results highlight the urgent need to develop novel ways of providing answers to patient questions about T2DM.

Quantifying Proton Fields for Midline Brain Tumors: A Benefit/Cost Analysis of Planning Objectives.

PURPOSE: We sought to quantify the optimum number of beams by using a midline sagittal arrangement for midline brain tumors when considering the competing demands of a high degree of target conformation and maximizing reduction of nontarget brain dose. The volume of nontarget brain tissue receiving between 5 and 20 Gy (V5-V20) was selected to measure "low-dose bath" to normal brain. MATERIALS AND METHODS: An exploratory model was developed with 6 midline brain targets created by using spheres of 1-, 3-, and 5-cm diameters located in superficial and deep locations. For each, five 3-dimensional proton treatment plans with uniform beam scanning were generated by using 1 to 5 fields. Dose-volume histograms were analyzed to calculate conformation number and V5-V20. A benefit/cost analysis was performed to determine the marginal gain in conformation number and the marginal cost of V5-V20 for the addition of each field and hypothesize the optimum number of treatment fields. We tested our hypothesis by re-planning 10 actual patient tumors with the same technique to compare the averages of these 50 plans to our model. RESULTS: Our model and validation cohort demonstrated the largest marginal benefit in target conformation and the lowest marginal cost in normal brain V5-V20 with the addition of a second proton field. The addition of a third field resulted in a relative marginal benefit in target conformation of just 3.9% but a relative marginal cost in V5-V20 of 78.7%. Normal brain absolute V5-V20 increased in a nearly linear fashion with each additional field. CONCLUSIONS: When treating midline brain lesions with 3-dimensional proton therapy in an array of midline sagittal beams, our model suggests the most appropriate number of fields is 2. There was little marginal benefit in target conformation and increasing cost of normal brain dose when increasing the number of fields beyond this.