Health 2.0 / Medicine 2.0
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Health 2.0 / Medicine 2.0

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Introduction to Health 2.0 and Medicine 2.0

Introduction to Health 2.0 and Medicine 2.0

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    Health 2.0 / Medicine 2.0 Health 2.0 / Medicine 2.0 Presentation Transcript

    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR Health 2.0 / Medicine 2.0 how the social web change health and medicine James G. (Boram) Kim BiKE Lab., SNU jgkim@bike.re.kr Dental Service Management and Informatics ● School of Dentistry, Seoul National University ● June 2nd, 2011 Copyright 2011 Biomedical Knowledge Engineering Laboratory. All rights reserved.
    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR Brief History and De nitions 2 of 45
    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR 1999: e-Health e-Health is an emerging field in the intersection of medical informatics, public health and business, referring to health services and information delivered or enhanced through the Internet and related technologies. In a broad sense, the term characterizes not only a technical development, but also a state-of-mind, a way of thinking, an attitude, and a commitment for networked, global thinking, to improve health care locally, regionally, and worldwide by using information and communication technology. Gunther Eysenbach 3 of 45
    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR 2004: m-Health In general terms, m-Health can be defined as “mobile computing, medical sensor, and communications technologies for health care.” Robert S.H. Istepannian, Emil Jovanov, and Y.T. Zhang 4 of 45
    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR 2006: Health 2.0 Health 2.0 is the use of a specific set of Web tools (blogs, Podcasts, tagging, search, wikis, etc) by actors in health care including doctors, patient, and scientists, using principles of open source and generation of content by users, and the power of networks in order to personalize health care, collaborate, and promote health education. Benjamin Hughes, Indra Joshi, and Jonathan Wareham 5 of 45
    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR 2008: Medicine 2.0 Medicine 2.0 applications, services and tools are Web-based services for health care consumers, caregivers, patients, health professionals, and biomedical researchers, that use Web 2.0 technologies and/or semantic web and virtual-reality tools, to enable and facilitate specifically social networking, participation, apomediation, collaboration, and openness within and between these user groups. Gunther Eysenbach 6 of 45
    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR Facebook-like Medical Practices 7 of 45
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    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR Personally Controlled Health Records 10 of 45
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    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR Personal Health Applications 13 of 45
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    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR e-Patients 21 of 45
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    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR Doctor 2.0 28 of 45
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    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR Going Further 40 of 45
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    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR NATURE | Vol 457 | 19 February 2009 LETTERS 0.95 12 10 ILI percentage 45 queries 8 Mean correlation 6 4 0.90 2 0 2004 2005 2006 2007 2008 Year Figure 2 | A comparison of model estimates for the mid-Atlantic region (black) against CDC-reported ILI percentages (red), including points over 0.85 0 10 20 30 40 50 60 70 80 90 100 which the model was fit and validated. A correlation of 0.85 was obtained Number of queries over 128 points from this region to which the model was fit, whereas a correlation of 0.96 was obtained over 42 validation points. Dotted lines Figure 1 | An evaluation of how many top-scoring queries to include in the indicate 95% prediction intervals. The region comprises New York, New ILI-related query fraction. Maximal performance at estimating out-of- Jersey and Pennsylvania. sample points during cross-validation was obtained by summing the top 45 search queries. A steep drop in model performance occurs after adding query 81, which is ‘oscar nominations’. against weekly ILI percentages for individual states. The CDC does not make state-level data publicly available, but we validated our Combining the n 5 45 highest-scoring queries was found to obtain model against state-reported ILI percentages provided by the state the best fit. These 45 search queries, although selected automatically, of Utah, and obtained a correlation of 0.90 across 42 validation points appeared to be consistently related to ILIs. Other search queries in45 (Supplementary Fig. 3). 42 of the Google web search queries can be used to estimate ILI percentages top 100, not included in our model, included topics like ‘high school basketball’, which tend to coincide with influenza season in the accurately in each of the nine public health regions of the United
    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR 43 of 45
    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR H1N1 Content on Twitter Figure 4. Scatterplot of tweets sharing personal experiences and USA H1N1 incidence rate. doi:10.1371/journal.pone.0014118.g004 days. Search patterns were modified or deleted if approximately more than 30% of tweets did not reflect the concept. Validation Analysis. Concept query totals from the 9 selected days were recorded. Pearson’s correlations were used to measure the relationship between the proportions of selected categories resulting from the manual coding and the automated 43 of 45ts of manual versus automated analyses. Automated proportions were obtained by taking the
    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR It’s all about Participation. 44 of 45
    • Biomedical Knowledge Engineering Laboratory BIKE.RE.KR any questions? 45 of 45