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March 5, 2013: I. Sim What Next for Health and Research Informatics? Epi 206 – Medical Informatics Ida Sim, MD, PhD March 5, 2013 Division of General Internal.

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Presentation on theme: "March 5, 2013: I. Sim What Next for Health and Research Informatics? Epi 206 – Medical Informatics Ida Sim, MD, PhD March 5, 2013 Division of General Internal."— Presentation transcript:

1 March 5, 2013: I. Sim What Next for Health and Research Informatics? Epi 206 – Medical Informatics Ida Sim, MD, PhD March 5, 2013 Division of General Internal Medicine, and Center for Clinical and Translational Informatics UCSF New Clinical Research Paradigms Copyright Ida Sim, 2013. All federal and state rights reserved for all original material presented in this course through any medium, including lecture or print.

2 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics Interim Summary Health system is highly fragmented, information systems are patchwork and support transactions rather than knowledge work Computing challenges include –naming data (e.g., ICD-9 vs SNOMED) –decision support (e.g., rules, probabilistic reasoning, different kinds of decision and reasoning problems that need solving, NLP) –workflow integration impeded by closed/siloed systems EHR adoption is increasing (driven by Meaningful Use payments), but CDSS adoption is low, and clinical research informatics usage is early Health care and research are poised for disruption by digital technologies

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4 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics Outline Plateau of Productivity: The Learning Health(care) System The Uneven Present –new models of care –the Digital Divide The Uneven Future for Research –Web X.0 research paradigms

5 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics Ideal Health (Care) System Because we don’t already know how to do everything… A “learning health(care) system” –“that is designed to generate and apply the best evidence for the collaborative health care choices of each patient and provider; to drive the process of discovery as a natural outgrowth of patient care” (IOM Evidence-Based Medicine Roundtable) Friedman, et al. Achieving a Nationwide Learning Health System. Sci Transl Med 2010; 2(57):57cm29

6 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics What Learning Occurs Now? Studies are expensive, difficult to conduct, 30-40% of studies never accrue enough patients Studies take years to answer limited questions in limited populations Study designs and results are heterogenous, limiting ability to pool findings or make summary interpretations Research questions don’t address combination treatments (e.g., ACEI and amlodipine) Research questions often don't answer front-line clinical needs –little data on mid- to long-term effectiveness of antidepressants Overall lack of relevance, generalizability, and sustainability Moss, et al. NEJM 2011; 364(9):789-761 Crowley, et al. JAMA 2004; 291(9):1120-6 etc.

7 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics What Learning is Needed? Population-level efficacy and effectiveness –for endpoints, not only intermediate outcomes –for patient-centered outcomes (symptoms, side effects) Predictive precision (e.g., depression, asthma for this patient) –model-based learning of biophysical medicine Therapeutic precision (best therapy for this patient) –informed by, but not limited to, genomic info –learning from experience (e.g., outcomes research) How to promote and sustain behavior change What are prevalence, natural hx, etc. even of rare diseases? How to enable patients, families, communities, and clinicians to maintain wellness and manage chronic illness together? etc. etc.

8 Five Rings of Human Health Schatz, BR, et al. Healthcare Infrastructure: Health Systems for Individuals and Populations. Springer, 2013.

9 The Uneven Future Tech, biomedical, and macro factors driving a radically different health(care) future –Eric Topol: Creative Destruction of Medicine and TED talkCreative Destruction of MedicineTED talk Personalization of consumer experience will be expected in health too Goal is a “learning system” based on big data Puts premium on intelligent data analysis of open and disparate data New research paradigms open up But first, where is the Uneven Present? March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics

10 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics Outline Plateau of Productivity: The Learning Health(care) System The Uneven Present –new models of care –the Digital Divide The Uneven Future for Research

11 February 26, 2013: I. Sim What Next? Epi 206 – Medical Informatics Web X.0 Web 1.0: web of links to static information with simple links between them –e.g., Wikipedia, NYTimes.com 1 Web 2.0: people are as important as computers in the network –Facebook, Twitter, Google +, Instagram, Tumblr… Web 3.0 (Semantic Web) –each data item is “tagged” with ontology terms so computer can “understand” everything on the web –I.e., the contents of HTML “buckets” are standardized, using RDF (Resource Description Framework), OWL (Web Ontology Language), etc. Web +1 web of things 1 except http://www.nytimes.com/projects/2012/snow-fall/?hp#/?part=tunnel-creek

12 February 26, 2013: I. Sim What Next? Epi 206 – Medical Informatics Web 2.0 Principles User-generated content Harness power/wisdom of crowds Openness Architecture of participation Niche markets (P. Anderson, What is Web 2.0? JISC Tech and Standards Watch, Feb 2007)

13 February 26, 2013: I. Sim What Next? Epi 206 – Medical Informatics User-Generated Content Anyone anywhere is a source of content –YouTube, Flickr, Wikipedia, Instagram, Tumblr, citizen journalism, blogs, e.g. –http://PatientsLikeMe.com/http://PatientsLikeMe.com/ –http://www.ganfyd.org/index.php?title=Main_Pagehttp://www.ganfyd.org/index.php?title=Main_Page Exists in parallel with Web 1.0 hierarchical information sources –NIH MedlinePlusNIH MedlinePlus –WebMD.com

14 February 26, 2013: I. Sim What Next? Epi 206 – Medical Informatics Power/Wisdom of Crowds Tapping into distributed intelligence –wikipedia (as accurate as Encyclopedia Britannica) –www.intrade.com “stock market”www.intrade.com –Google Flu, HealthMapGoogle FluHealthMap Use distributed machine and people resources –parallel computing for cheap: Einstein@homeEinstein@home –FoldIt for protein foldingFoldIt Crowdsourcing: –633,200 questions in health http://wiki.answers.com/Q/FAQ/431 http://wiki.answers.com/Q/FAQ/431

15 February 26, 2013: I. Sim What Next? Epi 206 – Medical Informatics Openness Dimensions of openness –open source code: community improvement (e.g., VistA VA EHR system) –open access: no restrictions on use or distribution of content –open participation: everyone can participate communal management, flat hierarchies, emergent decisions Allows “mash-ups” of freed data -e.g., Community Health Data InitiativeCommunity Health Data Initiative -http://www.googlelittrips.com/GoogleLit/Home.html for Aeneid, Grapes of Wrath, user-generated road trips...http://www.googlelittrips.com/GoogleLit/Home.html

16 February 26, 2013: I. Sim What Next? Epi 206 – Medical Informatics Architecture of Participation Network externalities: “the service automatically gets better the more people use it” e.g., –fax machines, cell phones...the more the better –Google search: the more “link paths” people tread, the richer the data for the Google search algorithm –Amazon book ratings, Netflix ratings How important is anonymity for this in healthcare? –http://www.curetogether.com/http://www.curetogether.com/ –http://whoissick.org/sickness/http://whoissick.org/sickness/ –better epi data if everyone contributed to public health data 1-3% refuse to share clinical data for research

17 February 26, 2013: I. Sim What Next? Epi 206 – Medical Informatics Niche Markets “The web” is unlimited resource –can service even extremely small market niches Shape of the web: the “long tail”long tail where traditional focus is with infinitely long tail, majority of action is here # people market niche/things being done

18 February 26, 2013: I. Sim What Next? Epi 206 – Medical Informatics Niche Markets in Health Rare diseases –PatientsLikeMe Geographic, ethnic, other niches –Russian-speaking boy scouts with ADHD in rural Montana

19 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics Online Care Cognitive behavioral therapy –for sleep: www.shuti.netwww.shuti.net –15 mins. of Cognitive Bias Modification vs. hours of talk therapy “all it requires is sitting in front of a computer and using a program that subtly alters harmful thought patterns” (Economist, Mar 5, 2011, p. 85) Counseling –http://www.liveperson.com/experts/professional-counseling/http://www.liveperson.com/experts/professional-counseling/ Virtual MD visits include live video chat and instant messaging (defunct now) –https://platform.hellohealth.com/PublicPortalServlet/DoctorsList.jsphttps://platform.hellohealth.com/PublicPortalServlet/DoctorsList.jsp

20 Non-Traditional Health Players CVS Minute Clinics ZocDoc Open Table for booking doctorsZocDoc Castlight price transparency for expendituresCastlight Aetna bought iTriage, part of new Consumer Platform AT&T ForHealth platform @Walmart, Cisco, Intel … March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics

21 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics Outline Plateau of Productivity: The Learning Health(care) System The Uneven Present –new models of care –the Digital Divide The Uneven Future for Research

22 Huge growth in Internet use across all segments Race/ethnic and age divide on usage –interaction with income and education February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

23 February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics Action is in mobile

24 Majority of Internet users access via mobile No race/ethnic difference February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

25 Mobile is preferred or only way of getting online by more –youth –minorities –low income February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

26 February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

27 About a third of mobile users overall access health information More use in –youth –minorities –higher income –higher education February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

28 February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

29 Digital Divide Still Exists Minorities with higher cell usage, more cell- only households, more social computing Language is strong predicator –foreign-born Latinos much lower use of Internet, English-speaking Latinos equal to whites Also health literacy –low health literacy predicts lower e-health use (Sakar, J Health Commun, 2010) Don't automatically apply old assumptions/data from the “real” world to the virtual world February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

30 Summary of the Present Lots of new models of care, new players Social computing coming into play Digital divide exists in non-traditional ways –is increasingly about how technology is used, not whether it is available –overall trend to going online via mobile not desktop Uneven availability and uptake –Internet and broadband use lower in elderly, rural, low income, and chronically ill February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

31 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics Outline Plateau of Productivity: The Learning Health(care) System The Uneven Present –new models of care –the Digital Divide The Uneven Future for Research

32 February 26, 2013: I. Sim What Next? Epi 206 – Medical Informatics Web X.0 Web 1.0: web of links to static information with simple links between them –e.g., Wikipedia, NYTimes.com Web 2.0: people are as important as computers in the network –Facebook, Twitter, Google +… Web 3.0 (Semantic Web) –each data item is “tagged” with ontology terms so computer can “understand” everything on the web –I.e., the contents of HTML “buckets” are standardized, using RDF (Resource Description Framework), OWL (Web Ontology Language), etc. Web +1 web of things

33 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics Web 1.0 Research Websites that collect information, deliver video, etc. U-Can-Poop-Too Study –http://ucp2.bht.virginia.edu/interest/studyhttp://ucp2.bht.virginia.edu/interest/study Stop Smoking –https://www.stopsmoking.ucsf.edu/https://www.stopsmoking.ucsf.edu/

34 "Web 1.0" Resources at UCSF Building websites, with templates, etc. –http://drupal.ucsf.edu/http://drupal.ucsf.edu/ Distributed trials –Mytrus: e-consent, randomization, online data collectionMytrus Mobile data collection –RedCAP, Qualtrics, etc., see http://ctsi.mobiledata.sgizmo.com/s3 http://ctsi.mobiledata.sgizmo.com/s3 February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

35 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics Development Decisions The “specs” (specifications) –what is your system supposed to do? for whom? –what specific functions will it have? –do use case scenarios (step-by-step, storyboards, etc) Basic technical choices –“form factor”: kiosk, desktop, laptop, notebook, tablet, phone… –operating system (e.g., Mac vs PC, or Android vs iPhone vs mobile web) check browser and platform usage statisticsusage statistics Find a developer –internal: UCSF Mobile Services or TelemedicineTelemedicine –external: contact Tuhin.Sinha@ucsf.edu in ITA for referrals and standard contracts

36 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics Agile Design Traditional approach –design a website or system; pilot it on a few users, improve it; run RCT; analyze data; publish (over 2-3 years) Agile design approach user interaction design rapid cycle iteration with qualitative and quantitative user studies Why wait till end of RCT to find out that “the system” didn’t work or wasn’t used, and have little idea why? –user engagement a critical problem for digital health interventions, need to explore methods

37 User Interaction Design The practice of designing interactive digital products –more than user interface, is user experience, ie how iPhone feels different than Android User interaction design expertise –http://www.coroflot.com/public/individual_search_results.asp?k eywordshttp://www.coroflot.com/public/individual_search_results.asp?k eywords –contact Beth Berrean BerreanB@MEDSCH.UCSF.EDU, UCSF Mobile Services BerreanB@MEDSCH.UCSF.EDU Participatory design –involve your users in design right from the beginning –e.g., test out different data visualizations, http://www.visualizing.org/data visualizations http://www.visualizing.org/ March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics

38 Rapid Cycle Field Testing Qualitative –surveys, interviews, video recordings, “talk-aloud protocols” Quantitative –user analytics track app launches, clicks, dwells, scrolls, links to web and back…e.g., Flurry.com Google launched 450 search engine improvements in 2007, each one tested rigorously through real-time user analytics each one tested rigorously March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics

39 Web 2.0 Research Games and simulation for health –http://www.gamesforhealth.org/, http://healthcaregames.wisc.edu/http://www.gamesforhealth.org/http://healthcaregames.wisc.edu/ –http://secondlife.com/?v=1.1http://secondlife.com/?v=1.1 PatientsLikeMe.com on lithium for ALS –observational study prompted by a small Italian study, negative results published in Nature Biotechpublished Crowdscience –http://diygenomics.org/ correlating personal genome with outcomes of personal interest (e.g,. empathy)http://diygenomics.org/ –mining Twitter, GPS locations, online social status for predictors of health, real-time GermTracker predictors of healthGermTracker Ethics and informed consent are evolvingevolving February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

40 The Internet of Things http://www.youtube.com/watch?v=sfEbMV295Kk February 26, 2013: I. Sim What Next? Epi 206 – Medical Informatics

41 Health Things February 26, 2013: I. Sim What Next? Epi 206 – Medical Informatics FitBit: steps, distance, calories burnedFitBit Sleep: Zeo, SmartAlarm appZeo AliveCor ECG Wearable sensors –Corventis Piix: holter sticker –Sensing Tattoos for blood glucose, oxygen, sodium levelsSensing Tattoos –Nike+ shoe, Smartex clothes Mood sensors: –Affectiva skin impedance, voice stress analysisAffectiva –Xpression 200 millisecond long acoustic snapshots for voice stress analysis ( calms, happy, sad, angry, or anxious/frightened)Xpression Embedded, distributed sensors –in the home: Kaiser Garfield Innovation CenterKaiser Garfield Innovation Center

42 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics 24/7/anywhere/everyone Care/Research Small, cheap, highly networked devices, distributed everywhere doing everything (everyware) –e.g., GreenGoose tagsGreenGoose Near-patient testing –Ucheck checking urinalysis via your iPhone and cameraUcheck –iBGStar glucometer Environmental mapping of symptoms –asthmamd.com mapping of PEFR of thousands of users in real-time during Icelandic volcanic explosion

43 Web n.0 Research Asthmapolis and their SpiroScout GPS-wifi enabled inhalerAsthmapolis –allows you to "quantify the burden of asthma in a community, explore environmental exposures and how they correlate with asthma symptoms, and identify spatial and temporal patterns of disease." Health eHeart (Jeff Olguin, Mark Pletcher, UCSF)Health eHeart –a virtual Framingham for cardiovascular research CalIT2 projects Quantified Self –overview: http://www.economist.com/node/21548493http://www.economist.com/node/21548493 March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics

44 Larry Smarr story UCSD computer science professor –overweight, arrived in SD in 2000 Quantified his four "pillars of health" (TicTrac displays together) –nutrition: can use LoseIt, many others –exercise: can use FitBit, FuelBand, etc. –stress management: GPS4Soul, etc –sleep: Zeo, Up band, SmartAlarm, etc. Biomarkers –from consumer labs, e.g., www.yourfuturehealth.com February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

45 Larry Smarr story February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

46 Larry Smarr story Lost weight, exercised, slept better, optimized omega-3, DHA scores, AA/EPA ratio, TG/HDL, etc. But CRP was high, and had suddenly doubled over a year –presented with acute diverticulitis, took antibiotics –CRP came down, but was still higher than normal –carotid artery plaques growing despite optimal lipids and "anti-inflammatory diet" Quantified his stool February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

47 Larry Smarr story February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics Stool lactoferrin correlated with serum CRP levels –and IBD? Got scoped –inflammation seen, doc said it wasn't IBD Rescoped and bx'ed –Crohns, rare late onset (5% are > 60y)

48 Larry Smarr story Genomics –23andMe SNP profile23andMe –had 80% increased risk of Crohn's with rs1004819 SNP37 located in IL-23 receptor gene Stool flora and microbiome –he had much lower stool flora diversity, took long time to replenish after antibiotics for diverticulitis –now exploring stool microbiome (see e.g., uBiome) correlating stool metagenomics with clinical Crohn's February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics

49 February 26, 2013: I. Sim Research Informatics Epi 206 — Medical Informatics The point of this article is that the combination of trend-revealing graphs of time series of individual biochemical markers, with population-wide comparisons to people with different health outcomes, is transforming biomedical research, and ultimately clinical care, into an entirely new paradigm. In this new world, we become personally responsible for monitoring our bodies, noticing deviations from trends, and making appropriate changes. Use of this paradigm will allow us to avoid many of today’s chronic disease states. In coming decades, the new model will be “maintenance of wellness” rather than “treatment of chronic illness.” http://lsmarr.calit2.net/repository/092811_Special_Letter,_Smarr.final.pdf

50 Summary: New Research Paradigms A “flat” world, blending health and healthcare unbounded by place or time Lots of data, lots of things, everyone is “in” –many non-traditional health players Challenges will be –aggregating smaller data into Big Data (and back into personalized small data) –analyzing Big Data in appropriate clinical, social, environmental, etc. context –drawing scientific conclusions, showing validity March 12, 2013: I. Sim What Next? Epi 206 – Medical Informatics

51 February 5, 2013: I. Sim Overview Medical Informatics Next Class Research methodology in the Digital Age


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