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Katia Passera /Paolo Malighetti Bergamo University

Smart[ er ] Citizens. Harvard University Graduate School of Design. Bergamo University. Health Data and Computation strategies. Katia Passera /Paolo Malighetti Bergamo University. Objectives.

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Katia Passera /Paolo Malighetti Bergamo University

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  1. Smart[er] Citizens Harvard University Graduate School of Design Bergamo University Health Data and Computation strategies KatiaPassera/Paolo Malighetti Bergamo University

  2. Objectives • Introduce how to use data and data analysis in order to better address issue/challenge in health area • In particular, data play a key role in different aspects: • to describe/measure a specific issue into the context • to understand relationships and causes of the issue • into design solution • in testing and validation of solution

  3. Describe/Measure the issue in the context Research of available information Contextualize the issue and required needs Quantify the issue How many people are involved in? How does it weight with respect to the population?Comparison with territory ( differences with region, Italy, Europe, World) Trend analysis along time (trend of the issue) Current response of the territory to the issue Number and type of responsive structures and localization (hospitals, healthcare facilities, …) Already existing projects

  4. Describe/Measure the issue in the contextTools: Database and Data Analysis • From ISTAT, demographical and some health data, habits, behaviors:1) www.demo.istat.it2) http://dati.istat.it/3) available software to perform analysis on database (download hfa.zip at http://www.istat.it/it/archivio/14562)

  5. Describe/Measure the issue in the contextDatabase and Data Analysis • From ASL, information of healthcare facilities and services:1) http://www.asl.bergamo.it/2) http://rsacommunity.asl.bergamo.it/RSACommunityBG/

  6. Describe/Measure the issue in the contextDatabase and Data Analysis • Other databases for epidemiological information:1) http://www.epicentro.iss.it/stumenti/BancheDati.asp 2) http://www.epidemiologia.it/?q=node/192 /

  7. Describe/Measure the issue in the contextDatabase and Data Analysis Given the data, the first step of data analysis is to provide simple summaries of data (descriptive statistics). Such summaries may be: - quantitative, i.e. measures of central tendency (mean, median, mode) and measures of variability or dispersion ( standard deviation (or variance), the minimum and maximum values of the variables, kurtosis and skewness) - visual, i.e. simple-to-understand graphs (histograms, bar chart, pie chart, box-plot)

  8. Identify possible relationships and causes • Find relationship among data • Find differencese.g.: difference male/female, young/old, spatial… • Identify possible causes of the issue • Find relationship between issue and possible causes • e.g.: weight vs. lifestyle

  9. Identify possible relationships and causes • Quantitative measures such as correlation (e.g. Pearson's r), the slope in regression analysis, … • Graphical representation (e.g. scatterplots)  • - Statistical hypothesis tests (T-tests, Chi-squared tests) to investigate differences and changes

  10. Data implementation into design solution In health, the data can come from a broad spectrum of digital sources, including computing, communications, sensors, medical equipment, and wearable devices. Combining these data streams will offer enormous opportunities to improve medical and self-care through large-scale data harvesting. Some examples: To create real-time responsive devices To bring information to improve lifestyles/ to influence people behaviors To increase awareness in choices that influence health To help care giver in doing their jobs To make health service more efficient …

  11. Data implementation into design solution DATA PROCESSING IS A CRUCIAL STEP Data processing is "the collection and manipulation of items of data to produce meaningful information." Data processing may involve various processes, including: 1) Validation (ensuring that supplied data is clean, correct and useful) 2) Sorting (arranging items in some sequence and/or in different sets) 3) Summarization  (reducing detail data to its main points) 4) Aggregation (combining multiple pieces of data) 5) Analysis(collection, organization, analysis, interpretation, presentation of data)

  12. Data implementation into design solution Some criticisms: Translate qualitative information into quantitative parameters Data coding Integration of data coming from different sources Reliability of data How to make data usable and easy to understand (visualize the information, e.g. parametric maps) Privacy

  13. Data implementation into design solution • http://www.healthmap.org/en/ HealthMap brings together disparate data sources, including online news aggregators, eyewitness reports, expert-curated discussions and validated official reports, to achieve a unified and comprehensive view of the current global state of infectious diseases and their effect on human and animal health. Through an automated process, updating 24/7/365, the system monitors, organizes, integrates, filters, visualizes and disseminates online information about emerging diseases in nine languages, facilitating early detection of global public health threats.

  14. Data implementation into design solution http://www.patientslikeme.com/ PatientsLikeMe is a patient network that improves lives and a real-time research platform that advances medicine. On PatientsLikeMe’s network, people connect with others who have the same disease or condition and track and share their own experiences.

  15. Data implementation into design solution • http://www.heatwalkingcycling.org/ This tool is designed to help you conduct an economic assessment of the health benefits of walking or cycling by estimating the value of reduced mortality that results from specified amounts of walking or cycling.

  16. Data implementation into design solution http://www.bbc.co.uk/news/technology-22984876 iPad-like device and motion sensors to help people live with Alzheimer’s in the home The magic carpet, designed to detect and even predict, when old people fall at home

  17. Test and validate the solution Testing and validation are procedures that are used together for checking that a product, service, or system meets requirements and specifications and that it fulfills its intended purpose. How to test and validate: 1) Technological requirements: specificity, accuracy, repeatability,… 2) Economic requirements: sustainability, scalability, … 3) User requirements: user-friendly, feasibility, … In health area, there is also a clinical validation, that is a validation that are regulated by health authority/ethics committee approval. It is based on clinical trials, which are sets of tests in medical research and drug development that generate safety and efficacy data for health interventions.

  18. Test and validate the solution http://health-lab.nl/index.php?option=com_content&view=article&id=73 http://health-lab.nl/images/Downloads_docs/Pitch_Smart_Health_Labs_Amsterdam_-_Manchester_270913.pdf

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