Emerging Technologies in Healthcare

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Introduction to Emerging Technologies in Healthcare

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  • An electronic health record is defined by the National Alliance for Health Information Technology as an electronic record of health-related information on an individual that conforms to nationally recognized interoperability standards and that can be created, managed, and consulted by authorized clinicians and staff across more than one health care organization.In layman’s terms EHRs are computerized versions of patients’ clinical, demographic and administrative data. The records may include treatment histories, medical test reports and images stored in an electronic format.Health information exchange (HIE) is the electronic movement of health-related information among organizations according to nationally recognized standards. HIE also sometimes is referred to as a health information network (HIN).
  • Patients, doctors, insurers, government and researchers will all make better decisions in healthcare with better information, which we will get from the grand healthcare platform. We need to turn our islands of healthcare data into a network of networks that is ultimately global..
  • Volume. Many factors contribute to the increase in data volume transaction-based data stored through the yearstext data constantly streaming in from social mediaincreasing amounts of sensor data being collected, etc. VarietyData today comes in all types of formats, traditional structured data, text documents, email, meter-collected data, video, audio, stock ticker data and financial transactions. By some estimates, 80 percent of an organization's data is not numeric! But it still must be included in analyses and decision making.VelocityHow fast data is being produced and how fast the data must be processed to meet demand. VariabilityIn addition to the increasing velocities and varieties of data, data flows can be highly inconsistent with periodic peaks. Fro example:Is something big trending in the social media? Perhaps there is a high-profile IPO looming. ComplexityWhen you deal with huge volumes of data, it comes from multiple sources. It is quite an undertaking to link, match, cleanse and transform data across systems. However, it is necessary to connect and correlate relationships, hierarchies and multiple data linkages or your data can quickly spiral out of control. Data governance can help you determine how disparate data relates to common definitions and how to systematically integrate structured and unstructured data assets to produce high-quality information that is useful, appropriate and up-to-date.
  • No single approach or standard. This field is still evolving.
  • Thedefacthaddo
  • Volume. Many factors contribute to the increase in data volume transaction-based data stored through the yearstext data constantly streaming in from social mediaincreasing amounts of sensor data being collected, etc. VarietyData today comes in all types of formats, traditional structured data, text documents, email, meter-collected data, video, audio, stock ticker data and financial transactions. By some estimates, 80 percent of an organization's data is not numeric! But it still must be included in analyses and decision making.VelocityHow fast data is being produced and how fast the data must be processed to meet demand. VariabilityIn addition to the increasing velocities and varieties of data, data flows can be highly inconsistent with periodic peaks. Fro example:Is something big trending in the social media? Perhaps there is a high-profile IPO looming. ComplexityWhen you deal with huge volumes of data, it comes from multiple sources. It is quite an undertaking to link, match, cleanse and transform data across systems. However, it is necessary to connect and correlate relationships, hierarchies and multiple data linkages or your data can quickly spiral out of control. Data governance can help you determine how disparate data relates to common definitions and how to systematically integrate structured and unstructured data assets to produce high-quality information that is useful, appropriate and up-to-date.
  • Apache Sqoopis a tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data.Apache Oozie is a workflow/coordination system to manage Apache Hadoop(TM) jobs.HBase is an open-source, distributed, versioned, column-oriented store modeled after Google's Bigtable: A Distributed Storage System for Structured Data. Use HBase when you need random, realtime read/write access to your Big Data.Hive: A data warehouse infrastructure that provides data summarization and ad hoc querying.Mahout: A Scalable machine learning and data mining library.Pig: A high-level data-flow language and execution framework for parallel computation.Cascading is an application framework for Java developers to quickly and easily develop robust Data Analytics and Data Management applications on Apache Hadoop.Crunch, a Java library that aims to make writing, testing, and running MapReduce pipelines easy, efficient, and even fun. Crunch’s design is modeled after Google’s FlumeJava, focusing on a small set of simple primitive operations and lightweight user-defined functions that can be combined to create complex, multi-stage pipelines.
  • Emerging Technologies in Healthcare

    1. 1. EmergingTechnologiesin HealthcareVirendra Prasad, GM-Engineering, EdifecsJuly 26, 2012
    2. 2. Tele communication in India ( July 2012)• Late nineties, India invested in Cellular instead of wired phone lines• Indias mobile phone subscribers base touches 929 million• Wireline: 33 million• Wireless: 929 million (~ 28 time of wire line)• Overall teledensity in India reached 79.28 per centBenefit of Emerging Technology Adoption
    3. 3. GlobalConnected Healthcare WorldMore information, more connected, leads to better careand better research.
    4. 4. Creating a connected healthcare worldNetwork of networks
    5. 5. Network of networksEssential components for a connected healthcare worldSource: CSC
    6. 6. Emerging Technologies1. SmartphoneInformation wherever you are2. Virtual Reality/3D gamingSimulation of real world scenario3. Wearable DevicesUnobtrusive continuous health monitoring4. OntologyKnowledge as a set of concepts within a domain, and the relationshipsamong those concepts.5. Machine LearningData to Information6. Big DataUnlimited storage and compute7. Cloud ComputingDeliver Infrastructure, Platform and/or Application as Service8. Crowd SourcingLeverage the crowd
    7. 7. SmartphoneInformation wherever you are
    8. 8. SmartphoneInformation wherever you are Smartphone are becoming rich in personalized information center duetheir following abilities: Portable personal device with phone, camera, music, internet andapps PIM: Personal Information Management Profiles tracker – likes and dislike profiling Location information: GPS Information Guide: Search, directions, deals etc. Sensors Three-axis gyro Accelerometer Proximity sensor Ambient light sensor Notifications Apps for almost everything About 5,800 health care smartphone applications Perfect device for collecting personal information through direct dataentry or indirect through sensors and preferences that can be useful forpersonal healthcare and wellness management.
    9. 9. SmartphoneApplications in healthcare Medical Content and First Aid Boost Health and Fitness Health Monitoring and Treatment Training on the Go System Monitoring Collaboration
    10. 10. Medical Content and First AidiTriageCreated by two ER docs, iTriage helps you answer the questions: “What medical condition could I have?” and “Whereshould I go for treatment?”
    11. 11. Medical Content and First AidWebMDWebMD helps you with your decision-making and health improvement efforts by providing mobile access 24/7 tomobile-optimized health information and decision-support tools including WebMD’s Symptom Checker, Drugs &Treatments, First Aid Information and Local Health Listings.
    12. 12. Boost Health and FitnessGPS enabled fitness Apps
    13. 13. Health Monitoring and TreatmentiHealthiHealths Blood Pressure Dock lets you take more control of your personal healthcare using iPhone 4, iPad andiPod touch (4th Gen.).
    14. 14. Training on the GoRNotes: Nurse’s Clinician Pocket GuideRNotes® helps nurses provide premium patient care by putting the latest quick-reference, clinically-focused nursinginformation at their fingertips.
    15. 15. Payers related use cases Provider Support Apps for Members, e.g. health4me fromUnitedhealthcare. Visibility on the Go Tracking information Dashboards Business Process Exception Management Monitoring Notifications
    16. 16. Virtual Reality (VR) / 3D gamingSimulation of real world scenarios
    17. 17. Virtual Reality(VR) Surgery Surgical navigation, IGS, CAS, AR surgery, androbot-assisted surgery Medical Data Visualization Multi-modality image fusion, advanced 2D/3D/4Dimage reconstruction, and pre-operative planningand other advanced analytical software tools Education and Training Virtual surgical simulators and other simulators formedical patient procedures Rehabilitation and Therapy Immersive VR systems for painmanagement, behavioral therapy, psychologicaltherapy, physical rehabilitation, and motor skillstraining
    18. 18. 3D GamingPulse !!: Virtual Clinical Learning Lab for Health CareTraining Pulse!! is the first ever, immersive virtual learning spacefor training health care professionals in clinical skills.Cutting-edge graphics recreate a lifelike, interactive,virtual environment in which civilian and military heathcare professionals practice clinical skills in order to betterrespond to injuries sustained during catastrophicincidents, such as combat or bioterrorism. It is developed in partnership with Texas A & M University- Corpus Christi and is funded from a federal grant fromthe Department of the Navys Office of Naval Research.
    19. 19. Wearable DevicesUnobtrusive continuous health monitoring
    20. 20. Wearable Devices Wearable devices equipped with sensors, Webconnections, or both, help consumers and healthcareproviders track health and fitness. ABI Research last year estimated that the market forwearable health-related devices, ranging from heartmonitors to biosensors that read body temperature andmotion, will reach more than 100 million device salesannually by 2016.
    21. 21. Basic B1 The consumer-oriented Basis B1 wrist band incorporates fivesensors to provide a precise view of a persons health immediatelyand over extended periods of time. an optical blood flow sensor that detects heart rate, throughpulse or blood flow; a 3D accelerometer, a highly sensitive sensor that detects thesmallest movements, regardless of whether users are alert andactive or sleeping; a body temperature sensor to measure exertion during activity; an ambient temperature sensor to detect the outsidetemperature and compare it to body temperature to boost theaccuracy of caloric burn calculations; and a galvanic skin response sensor to measure the intensity ofsweat output.
    22. 22. Health Monitoring and TreatmentRaisin: A raisin that can save yourlife The FDA recently approved the marketing of anew medical device, Raisin Personal Monitor,worn like a band-aid that receives data from asensor you swallow in a pill and then sends outa wireless health report. The device manufacturer, Proteus Biomedical,developed ingestible sensors made out of foodproducts that serve as markers in the body.Then it transmits an ultra-low-power signal tothe Raisin, recording everything fromdate/time, type of drug, dose, place ofmanufacture and physical reactions. It was designed primarily for heart failurepatients, but the applications may extend toother conditions.Image by Proteus Biomedical
    23. 23. OntologyKnowledge as a set of concepts within a domain, andthe relationships among those concepts.
    24. 24. Ontology Ontology models knowledge as a set of concepts within a domain, and therelationships among those concepts. An ontology renders shared vocabulary and taxonomy which models a domainwith the definition of objects and/or concepts and their properties and relations. Ontology helps in taking a data and converts into information using common setof concepts or terminology so that the information can be: Categorized Uniform meaning so that it can be compared with other set of data Used in Artificial Intelligence, the Semantic Web, biomedical informatics, libraryscience, enterprise bookmarking, Knowledge Management. Healthcare Usages: EHR HIE Translation: ICD10  ICD9 Unstructured data processing Analytics
    25. 25. Machine LearningData to Information
    26. 26. Machine Learning Machine Learning is the study of computer algorithms thatimprove automatically through experience. Main Algorithm Types Supervised Learning Classification Regression Unsupervised Learning Clustering Density Estimation Applications Natural Language Process, useful for EHR Fraud Detection Predictive Analytics Forecasting
    27. 27. Big DataUnlimited storage and compute
    28. 28. Big Data Data Characteristics Volume Variety Velocity Variability Complexity Desired Properties of a Big Data System Robust and fault-tolerant Low latency reads and updates Scalable General System Extensible Allows ad hoc queries Minimal maintenance Debuggable Big Data is data sets that exceeds the boundaries and size of the normal processing capabilities forcingyou to take non traditional approach. Big data is a popular overloaded term used to describe the exponential growth, availability and use ofinformation, both structured and unstructured.
    29. 29. Big Data Technical Approach NoSQL Storage Distributed Storage Parallel Processing MapReduce Lambda Architecture The Lambda Architecture solves the problem of computing arbitrary functions on arbitrary data in realtime bydecomposing the problem into three layers1. Speed Layer Compensate the high latency of update to serving layer Fast incremental algorithm Batch layer eventually override speed layer2. Serving layer Random access to batch view Updated by batch layer3. Batch Layer Store master dataset Compute arbitrary view
    30. 30. Hadoop Hadoop is a platform that provides both distributed storage and computational capabilities. Hadoop was first conceived to fix a scalability issue that existed in Nutch, an open source crawler and searchengine. It is based on Google papers on Google File System (GFS), and MapReduce, a computational frameworks forparallel processing.Figure 1.1 The Hadoop environmentBecause you’re coming to this book with an interest in getting some practical3This section will look at Hadoop from an architectural perspective, examinehow industry uses it and consider some of its weaknesses. Once we get through thebackground we’ll look at how we can install Hadoop and run a MapReduce job.Hadoop proper, as shown in the following figure 1.2, is a distributedmaster-slave architecture that consists of the Hadoop Distributed File System3(HDFS) for storage, and MapReduce for computational capabilities. Traits intrinsicto Hadoop are data partitioning and parallel computation of large data sets. Itsstorage and computational capabilities scale with the addition of hosts to a Hadoopcluster, and can reach volume sizes in the petabytes on clusters with thousands ofhosts.Footnote 3m A model of communication where one process called the master has control over one or moreother processes, called slaves.Figure 1.2 High-level Hadoop architecture4
    31. 31. Hadoop: MapReduce8
    32. 32. Hadoop: Related TechnologyThe Hadoop ecosystem is diverse and grows by the day. It’s impossible to keeptrack of all the various projects that interact with Hadoop in some form. In thisbook the focus is on the tools that are currently receiving the highest adoption fromusers, as shown in the following figure 1.9 .Figure 1.9 Hadoop and related technologies
    33. 33. Big Data Use cases Batch Transaction Processing Analytics Test Data selection based onrules/scenarios Search EHR & HIE
    34. 34. Cloud ComputingDeliver as service
    35. 35. Cloud Computing Cloud computing is the delivery of computingand storage capacity as a service. The name comes from the use of a cloud-shaped symbol as an abstraction for thecomplex infrastructure it contains in systemdiagrams. Cloud computing entrusts services with a usersdata, software and computation over a network. There are three types of cloud computing: Infrastructure as a Service (IaaS) Platform as a Service (PaaS) Software as a Service (SaaS)
    36. 36. eMixElectronic Medical Information Exchange A cloud-based virtualized radiological image and information report service, provides secureaccess for physicians, hospitals and patients to view images and information. In the past, this was done by setting up a special network connection to transmit thefile, express-mailing a CD, or printing and mailing the image (film).http://www.emix.com/
    37. 37. Crowd SourcingLeverage the crowd
    38. 38. Crowd Sourcing Crowd sourcing is a process that involves outsourcing tasks to a distributedgroup of people. This process can occur both online and offline. The difference between crowdsourcing and ordinary outsourcing is that a taskor problem is outsourced to an undefined public rather than a specificbody, such as paid employees. Crowd sourcing delivers the elasticity of cloud by leveraging peer-to-peertechnologies. It also mitigates concerns about loss of privacy, since a single cloud providerdoes not have a global view of anyone’s data. Also, it presents a more economical solution compared to cloud computing:instead of paying a cloud provider for services, the contribution is made in-kind by becoming part of the computing system that offers computingpower, storage capacity, data or knowledge. As a consequence, the conceptof “cloud owner” is removed from the equation. Human brain guided computation is able to perform task that computers cannot do. Example, quality or accuracy of a content on Wikipedia.
    39. 39. Crowd Sourcing: Challenges Will we be able to crowd-source CPU hours in the future? Will the crowd carry sensors on their mobile devices to make thenetwork more aware of environmental situations? Do new security questions arise? How should we deal with performance issues? How can we extract high-quality answers from data created by thecrowd, which implies many small contributions from well-intentioned providers that may not be correct?
    40. 40. Crowd Sourcing: Examples SETI@home Search for Extraterrestrial Intelligence (SETI) (http://setiathome.berkeley.edu/) An early example of crowd computing was the discovery ofa gold deposit location at the Moribund Red Lake Mine inNorthern Ontario. Using all available data, the company,Goldcorp, Inc. had been unable to identify the location ofnew deposits on their land. In desperation, the CEO put allrelevant geological data on the web and created a contest,open to anyone in the world. An obscure firm in Australiaused their software and algorithms to crack the puzzle. Asa result, the company found an additional 8 million ouncesof gold at the mine. The only cost was the nominal prizemoney awarded. Real Time Traffic information including jams, speed,construction etc.
    41. 41. Crowd Sourcing: Use Cases Enterprise Use Cases Managing business processes for their customers Moderating images and user-generated content Analyzing sentiment for brands in Social Media Improving search relevance Processing data (business listings, points-of-interest, contacts, etc…) Structuring and normalizing digital content
    42. 42. MeditationLet the brain do the healing …
    43. 43. Thank you!

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