Cloud Computing and Software as a Service in BMI

1. Cloud Computing and Software as a Service in BMI Timoteus Ziminski Computer Science & Engineering Department The University of Connecticut tbz@engr.uconn.edu Spring 2011

2. Overview • Background • Definition • Providers • Technologies • BMI in the Cloud • Application Fields • Example: Virtual Patient Chart • Limitations • Conclusion • Critique • Research topics

3. Overview • Background • Definition • Providers • Technologies • BMI in the Cloud • Application Fields • Example: Virtual Patient Chart • Limitations • Conclusion • Critique • Research topics

4. Background What is the Cloud?

5. Definition • NIST definition: • Bottom line: computing paradigm that hides complexity through a notion of abstract resources • Although this paradigm is still considered to be under development, several very mature platforms are apparent. “Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.”

6. Providers • Google • Mail, Calendar, Health, Maps, Docs, Google Apps • Amazon • Amazon Web Services (AWS), Simple Storage System (Amazon S3) • IBM • SmartCloud Services, LotusLive, Blueworks, Collaborative Care • Microsoft • Azure, WindowsServer Hyper-V, Office 365 • And many, many more… • Enormous range of products covering a variety of tasks: development, testing, training, archiving, analysis, and collaboration

7. Service Models • Heterogeneous types of service can be embedded into the cloud • All options hide underlying infrastructure to a certain level • Software as a Service (SaaS) • Provides applications • Cross-device and cross-platform capabilities • Platform as a Service (PaaS) • Access to the cloud hosting environment • Deployment of applications • Infrastructure as a Service (IaaS) • Provides access to basic resources • CPU, network, storage

8. Characteristics • On-demand self service • Services are mostly automatic • Broad network access • Usage of standard mechanisms • Allows thin clients • Resource pooling • No control about physical instances • Rapid elasticity • Resources are presented as unlimited • Capacities grow and shrink automatically according to requirements • Measured service • Pay for what you use • Little up-front capital needed

9. Deployment Models for Cloud Infrastructure • Private • Access by one organization • Management in-house or by third party • Community • Shared across multiple organizations • Public • Accessible by general public or large number of organizations • Typically used for selling cloud applications • Hybrid • Composite of multiple clouds

10. Importance to IT Market

11. Technologies: On the Hard Side • Cloud computing requires reliable, efficient and powerful data centers • General hardware progress gives advantages • Disc space, memory, energy efficiency • More important, networking and virtualization technologies are fueling the development of cloud applications • Omnipresent access to low latency broadband internet • Multiplexing architectures • Hardware virtualization support • Clustering techniques

12. Technologies: On the Hard Side (ctd.) • Lightweight, always connected end devices are increasingly popular • Tablet PCs, Smartphones, Laptops (Cr-48) • Usage of multiple platforms simultaneously creates synchronization issues

13. Technologies: On the Soft Side • On the server side virtualization software plays an important role • VMware, VirtualBox, Virtual PC, Xen • From an organizational perspective, Service-oriented Architectures allow the decomposition of IT processes • Encapsulation into service with interfaces • Create potential for replacement of local services with options from the cloud • Possible implementations • REST: HTTP/S or SOAP RPC • Web Services: XML, WSDL, UDDI, SOAP • CORBA

14. Technologies: On the Soft Side (ctd.) • Development of operating systems which heavily rely on cloud applications • Android, iOS, Chromium OS • Increasingly sophisticated web browsers • IE9, Firefox 4, Chrome, Safari 5 • HTML5, JavaScript/AJAX, Flash, Silverlight • To some extent also programming language concepts and libraries • Java, Python, Perl, Ruby, Scala

15. Overview Cloud Resources Provide Use Provide

16. Overview • Background • Definition • Providers • Technologies • BMI in the Cloud • Application Fields • Example: Virtual Patient Chart • Limitations • Conclusion • Critique • Research topics

17. Application Fields • In which BMI areas can we leverage the benefits of Cloud Computing?

18. Clinical Informatics Challenges • Patient records • Electronic Medical Records, Personal Healthcare Records • Inherit need for efficient and reliable large-scale data storage and exchange • Collaboration between • Healthcare professionals • Team-based collaboration • Transition of care • Healthcare organizations • Practices, Labs, Pharmacies, Clinics, Hospitals • Domains • Providers, Payers, Researchers

19. CC Benefits for Clinical Informatics • Personal Healthcare Records • Google Health, Microsoft Health Vault, WebMD • Electronic Medical Records • First attempts to organize EMRs in private clouds • Modular approaches with plug-in architectures • Health information exchange • Decision support • Automatic note processing, voice recognition • Patient education • Opens the door for stepwise integration via a cloud of clouds • Hybrid clouds regulate the amount of exchanged data

20. CC Benefits for Clinical Informatics • Implementing HIE in the context of small practices • Application service provider model • Limits requirements and costs • Technical knowledge can remain on provider side • Maintenance reduces to thin clients • Compliance with regulations becomes provider task • Data warehousing • Example: Data from the pathology laboratory • In-house solutions create further data silos • The cloud concept opens the doors for affordable generic solutions

21. Virtual Patient Chart

22. CC benefits for Clinical Informatics (ctd.) • Virtual chart • Cloud computing services can provide very abstract storage resources • Space and performance is presented as limitless and automatically adjustable • Highly accessible and easy to synchronize across platforms • We are starting to have experience real-life proof platforms for real-time collaboration on documents • Is that enough?

23. A Word of Warning… Cloud Computing is another useful tool, not the silver bullet!

24. Bioinformatics Challenges • Heavy computational analysis tasks • DNA sequencing • Genomics • Protein microarrays • Mutation analysis • In addition to the specific hardware for the analysis, we need • Storage • Petabyte scale • CPU cycles

25. CC Benefits for Bioinformatics • The cloud starts to offer elegant solutions for large-scale data storage • Know-how about hardware and data management can cumulate at service providers • Elastic nature and “pay as you go” payment models increase accessibility for institutions • Do research rather than worrying about backups • Algorithmic tasks are the more at home in the domain of Grid computing • However, the cloud can increase discoverability and streamline the access to Grid resources

26. Medical Imaging Informatics • Essentially very similar arguments as discussed for the field of Bioinformatics

27. Public Health Informatics Challenges • Tracking trends • Large scale data warehousing • Regional • State-wide • Population wide • Disease Control and Prevention • Emergency response

28. CC Benefits for Public Health Informatics • Collection of public health data • Virtual chart would a valuable source • Inter-cloud communication • The nature of the cloud facilitates: • Storage of public health data • Analysis of public health data • Outcomes can be provided through cloud services

29. Clinical Research Informatics Challenges • Repositories and Databases • Data acquisition • De-identification • Data sharing • Cohort building • Support of clinical trials • Data collection • Data management • Data analysis

30. CC Benefits for Clinical Research Informatics • Outsource responsibility for regulation conform de-identification • Data management services • Break open data silos • Reuse collected data • Template based solutions for trial management • Promotion of best practices • Supporting tools • Exploit mobile devices and adequate apps for data collection during trials • Mobile phones, tablets

31. HIT Training Challenges • Training is an important and often underestimated component • Who requires training? • Healthcare professionals • Students of related fields • In what areas can we train • Medical education • Transfer of new knowledge • Skills in using software components • EHR, Practice Management, e-Prescribing • Adherence to best practices

32. CC Benefits for HIT Training • Virtualization has proven to be a powerful tool to provide training environments and programs • Training in a Cloud is a popular product • Scalable • Flexible • Cost efficient • Deployment and management of training environments is largely simplified by the “disposable” nature of virtual platforms • Service providers can offer cost efficient programs and cover a larger variety of topics

33. Limitations • Cloud computing and SaaS has some risks and limitations that we need to recognize in the context of BMI • Trust and Security • Reliability and Availibility • Performance • Standardization • Overhead

34. Trust and Security • Loading data off sensitive outside of organizational boundaries is by definition a security risk that has to be weighted against potential benefits • Third parties are gaining access • Service providers, governmental institutions • Limitations through policies and regulations have to be taken into consideration • Cloud computing does not make any assumptions about physical locations • Data can travel outside of country boarders • Employ suitable secure data transfer and encryption techniques • Currently still performance problems

35. Reliability and Availability • BMI systems are frequently of critical importance • Clinical care systems can directly influence decisions that can have potentially crucial impact on the well being of patients • Risk system outages and performance problems • Recent outage of AWS • Not an acceptable scenario for many BMI settings • Absorbing the impact • Local failover • Sacrifices advantages of low complexity

36. Performance • SaaS solutions have matured over the past years • Sophisticated Frontends • Low latency broadband internet • However, the healthcare domain tends to be very unforgiving towards workflow disruptions • Potential fluctuations in QoS can have harsh impact on the acceptance of services

37. Standardization • Cloud Computing does not give any immediate advantages regarding interoperability • Data models, standards and ontologies are a completely separate issue. • Even worse, there are binding standards for cloud interfaces • Potential vender lock • Over 10 national and international organizations are currently working on establishing standards

38. Overhead • Technologies such as Web Service and SOAP RPC which are used in Cloud Computing might be still too heavy weight for building a system that is aiming to span over the complete healthcare system • From this ultra large scale system perspective we might need to rely on even more abstract concepts such as HTTP/S REST.

39. Overview • Background • Definition • Providers • Technologies • BMI in the Cloud • Application Fields • Example: Virtual Patient Chart • Limitations • Conclusion • Critique • Research topics

40. Critique • Just another hype? • A lot of advertisement • Similar buzz-word overload as with SOA • In fact, often no solid distinguishing of the patterns • Nothing new? • Similar middleware concepts and ideas go far back • Existent services get tagged with the Cloud label • But noteworthy • Aligns with the current development of clients • Conceptually targets many BMI problems • Hardware and network progress enabled well convincing platforms and application suites

41. Research Topics • Improving the Cloud • Trust and Security • Scheduling and Virtualization • Mobile Cloud Computing • Inter-cloud communication (cloud of clouds) • Leveraging the Cloud • Data Analysis • Data Management • Data Modeling • Text and Voice recognition • Conferences • IEEE CLOUD, Cloud Expo, Cloud Connect

42. Thank you! Questions?