Click here to close now.

Welcome!

Cloud Expo Authors: Liz McMillan, Pat Romanski, Carmen Gonzalez, Michael Jannery, AppDynamics Blog

Blog Feed Post

MaaS applied to Healthcare – Use Case Practice

MaaS (Model as a Service) might allow building and controlling shared healthcare Cloud-ready data, affording agile data design, economies of scale and maintaining a trusted environment and scaling security. With MaaS, models map infrastructure and allow controlling persistent storage and deployment audit in order to certify th at data are coherent and remain linked to specific storage. As a consequence, models allow to check where data is deployed and stored. MaaS can play a crucial role in supplying services in healthcare: the model containing infrastructure properties includes information to classify the on-premise data Cloud service in terms of data security, coherence, outage, availability, geo-location and to secure an assisted service deployment and virtualization.

Introduction
Municipalities are opening new exchange information with healthcare institutes. The objective is sharing medical research, hospital acceptance by pathology, assistance and hospitalization with doctors, hospitals, clinics and, of course, patients. This open data [6] should improve patient care, prevention, prophylaxis and appropriate medical booking and scheduling by making information sharing more timely and efficient. From the data management point of view it means the service should assure data elasticity, multi-tenancy, scalability, security together with physical and logical architectures that represent the guidelines to design healthcare services.

Accordingly, healthcare services in the Cloud must primarily secure the following data properties [2]:
-      data location;
-      data persistence;
-      data discovery and navigation;
-      data inference;
-      confidentiality;
-      availability;
-      on-demand data secure deleting/shredding [4] [5] [11] [12].

These properties should be defined during the service design and data models play the “on-premise” integral role in defining, managing and protecting healthcare data in the Cloud. When creating healthcare data models, the service is created as well and properties for confidentiality, availability, authenticity, authorization, authentication and integrity [12] have to be defined inside: here is how MaaS provides preconfigured service properties.

Applying MaaS to Healthcare – Getting Practice
Applying MaaS to design and deploy healthcare services means explaining how apply the DaaS (Database as a Service, see [2] and [4]) lifecycle to realize faster and positive impacts on the go-live preparation with Cloud services. The Use Case introduces the practices how could be defined the healthcare service and then to translate them into the appropriate guidelines. Therefore, the DaaS lifecycle service practices we are applying are [4]:

Take into account, healthcare is a dynamic complex environment with many actors: patients, physicians, IT professionals, chemists, lab technicians, researchers, health operators…. The Use Case we are introducing tries to consider the whole system. It provides the main tasks along the DaaS lifecycle and so how the medical information might be managed and securely exchanged [12] among stakeholders for multiple entities such as hospital, clinics, pharmacy, labs and insurance companies.

The Use Case
Here is how MaaS might cover the Use Case and DaaS lifecycle best practices integrate the above properties and directions:

Objective To facilitate services to healthcare users and to improve exchange information experience among stakeholders. The Use Case aims to reduce costs of services by rapid data designing, updating, deployment and to provide data audit and control. To improve user experience with healthcare knowledge.
Description Current costs of data design, update and deployment are expensive and healthcare information (clinical, pharmaceutical, prevention, prophylaxis…) is not delivered fast enough based upon user experience;
Costs for hospitalization and treatments information should be predictable based upon user experience and interaction.
Actors Clinical and Research Centres;
Laboratories;
Healthcare Institute/Public Body  (Access Administrators);
Healthcare Institute/Public Body (Credentials, Roles Providers);
Patients;
IT Operations (Cloud Providers, Storage Providers, Clinical Application Providers).
Requirements Reducing costs and rapidly delivering relevant data to users, stakeholders and healthcare institutes;
Enabling decision making information to actors who regularly need access [11] [12] to healthcare services but lack the scale to exchange (and require) more dedicated services and support;
Fast supporting and updating healthcare data to users due to large reference base with many locations and disparate applications;
Ensuring compliance and governance directions are currently applied, revised and supervised;
Data security, confidentiality, availability, authenticity, authorization, authentication and integrity to be defined “on-premise”.
Pre-processing and post-processing Implementing and sharing data models;
Designing data model properties according to private, public and/or hybrid Cloud requirements;
Designing “on-premise” of the data storage model;
Modeling data to calculate “a priori” physical resources allocation;
Modeling data to predict usage “early” and to optimize database handling;
Outage is covered by versions and changes archived based on model partitioning;
Content discovery assists in identifying and auditing data to restore the service to previous versions and to irrecoverably destroying the data, if necessary, is asked by the regulations.
Included and extended use case Deployment is guided from model properties and architecture definition;
Mapping of data is defined and updated, checking whether the infrastructure provider has persistence and finding out whether outages are related to on-line tasks;
Deploying and sharing are guided from model properties and architecture definition.


Following, we apply MaaS’ properties (a subset) to the above healthcare Use Case. Per contra, Data Model properties (a subset) are applied along the DaaS lifecycle states:


MaaS Properties

DaaS Lifecycle States

Healthcare Data Model Properties
Data Location Create Data Model
Model Archive and Change
Deploy and Share
Data models contain partitioning properties and can include data location constraints. User tagging of data (a common Web 2.0 practice, through the use of clinic user-defined properties) should be managed. Support to compliant storage for preventative care data records should be provided
Data persistence Create Data Model
Model Archive & Change
Secure delete
For any partition, sub-model, or version of models, data model has to label and trace data location. Model defines a map specifying where data is stored (ambulatory care, clinical files have different storages). Providers persistence can be registered. Data discovery can update partition properties to identify where data is located
Data inference Create Data Model Data model has to support inference and special data aggregation: ambulatory might inference patient’s insurance file. All inferences and aggregations are defined, updated and tested into the model
Confidentiality Create Data Model
Populate, Use and Test
Data model guides rights assignment, access controls, rights management, and application data security starting from data model. As different tenants (hospitals, clinics, insurance companies and pharmacies) access the data, users and tenants should be defined inside the model. Logical and physical controls have to be set
High availability Deploy and Share
Model Archive and Change
Data model and partitioning configuration together with model changes and versions permits mastering of a recovery scheme and restoration when needed. Data inventory (classified by Surgery, Radiology, Cardiology, for example) vs discovery have to be traced and set.
Fast updates at low cost Create Data Model
Generate Schema/Update Data Model
Data reverse and forward engineering permits change management and version optimization in real-time directly on data deployed properties
Multi-database partitioning Create Data Model
Deploy and Share
Bi-directional partitioning in terms of deployment, storage, and evolution through model versioning has to be set. Multi-DBMS version management helps in sharing multi-partitioning deployments: for example, Insurance and Surgery by Patient, normally are partitioned and belong to different tenants vs different databases
Near-zero configuration and administration Create Data Model
Generate Schema/Update Data Model
Data models cover and contain all data properties including scripts, stored procedures, queries, partitions, changes and all configuration and administration properties. This means administrative actions decrease to leave more time for data design and update (and deployment). Regulation compliance can be a frequent administration task: models ensure that healthcare compliance and governance is currently aligned



The Outcome
MaaS defines service properties through which the DaaS process can be implemented and maintained. As a consequence, applying the Use Case through the introduced directions, the following results should be outlined.

Qualitative Outcomes:
1)    Healthcare actors share information on the basis of defined “on-premise” data models: models can be implemented and deployed using a model-driven paradigm;
2)    Data Models are standardized in terms of naming convention and conceptual templates (Pharma, Insurance, Municipality… and so on): in fact, models can be modified and updated with respect the knowledge they were initially designed;
3)    Storage and partitioning in the Cloud can be defined “a priori” and periodic audits can be set to certify that data are coherent and remain linked to specific sites;
4)    The users consult the information and perform 2 tasks:
4.1) try the (best) search and navigate the knowledge for personal and work activities;
4.2) give back information about user experience and practice/procedures that should be updated, rearranged, downsized or extended depending upon community needs, types of interaction, events or public specific situations.
5)    Models are “on-premise” policy-driven tools. Regulation compliance rules can be included in the data model. Changes on current compliance constraints means changes on the data model before it is deployed with the new version.

Quantitative Outcomes:
1)    Measurable and traceable costs reduction (to be calculated as a function of annual Cloud Fee, Resources tuning and TCO);
2)    Time reduction in terms of knowledge fast design, update, deployment, portability, reuse (to be calculated as a function of SLA, data and application management effort and ROI);
3)    Risk reduction accordingly to “on-premise” Cloud service design and control (to be calculated as a function of recovery time, chargeback on cost of applied countermeasures compared with periodical audit based upon model information).

Conclusion
MaaS might provide the real opportunity to offer a unique utility-style model life cycle to accelerate cloud data optimization and performance in the healthcare network. MaaS applied to healthcare services might be the right way to transform the medical service delivery in the Cloud. MaaS defines “on-premise” data security, coherence, outage, availability, geo-location and an assisted service deployment. Models are adaptable to various departmental needs and organizational sizes, simplify and align healthcare domain-specific knowledge combining the data model approach and the on-demand nature of cloud computing. MaaS agility is the key requirements of data services design, incremental data deployment and progressive data structure provisioning. Finally, the model approach allows the validation of service evolution. The models’ versions and configurations are a catalogue to manage both data regulation compliance [12] and data contract’s clauses in the Cloud among IT, Providers and Healthcare actors [9].

References
[1] N. Piscopo - ERwin® in the Cloud: How Data Modeling Supports Database as a Service (DaaS) Implementations
[2] N. Piscopo - CA ERwin® Data Modeler’s Role in the Relational Cloud
[3] D. Burbank, S. Hoberman - Data Modeling Made Simple with CA ERwin® Data Modeler r8
[4] N. Piscopo – Best Practices for Moving to the Cloud using Data Models in the DaaS Life Cycle
[5] N. Piscopo – Using CA ERwin® Data Modeler and Microsoft SQL Azure to Move Data to the Cloud within the DaaS Life Cycle
[6] N. Piscopo – MaaS (Model as a Service) is the emerging solution to design, map, integrate and publish Open Data http://cloudbestpractices.net/2012/10/21/maas/
[7] N. Piscopo - MaaS Workshop, Awareness, Courses Syllabus
[8] N. Piscopo - DaaS Workshop, Awareness, Courses Syllabus
[9] N. Piscopo – Applying MaaS to DaaS (Database as a Service ) Contracts. An intorduction to the Practice http://cloudbestpractices.net/2012/11/04/applying-maas-to-daas/
[10] N. M. Josuttis – SOA in Practice
[11] H. A. J. Narayanan, M. H. GüneşEnsuring Access Control in Cloud Provisioned Healthcare Systems
[12] Kantara Initiatives -http://kantarainitiative.org/confluence/display/uma/UMA+Scenarios+and+Use+Cases

Disclamer
This document is provided AS-IS for your informational purposes only. In no event the contains of “How MaaS might be applied to Healthcare – A Use Case” will be liable to any party for direct, indirect, special, incidental, economical (including lost business profits, business interruption, loss or damage of data, and the like) or consequential damages, without limitations, arising out of the use or inability to use this documentation or the products, regardless of the form of action, whether in contract, tort (including negligence), breach of warranty, or otherwise, even if an advise of the possibility of such damages there exists. Specifically, it is disclaimed any warranties, including, but not limited to, the express or implied warranties of merchantability, fitness for a particular purpose and non-infringement, regarding this document or the products’ use or performance. All trademarks, trade names, service marks and logos referenced herein belong to their respective companies/offices.


Read the original blog entry...

More Stories By Cloud Best Practices Network

The Cloud Best Practices Network is an expert community of leading Cloud pioneers. Follow our best practice blogs at http://CloudBestPractices.net

@CloudExpo Stories
Hadoop as a Service (as offered by handful of niche vendors now) is a cloud computing solution that makes medium and large-scale data processing accessible, easy, fast and inexpensive. In his session at Big Data Expo, Kumar Ramamurthy, Vice President and Chief Technologist, EIM & Big Data, at Virtusa, will discuss how this is achieved by eliminating the operational challenges of running Hadoop, so one can focus on business growth. The fragmented Hadoop distribution world and various PaaS soluti...
Since 2008 and for the first time in history, more than half of humans live in urban areas, urging cities to become “smart.” Today, cities can leverage the wide availability of smartphones combined with new technologies such as Beacons or NFC to connect their urban furniture and environment to create citizen-first services that improve transportation, way-finding and information delivery. In her session at @ThingsExpo, Laetitia Gazel-Anthoine, CEO of Connecthings, will focus on successful use c...
The Workspace-as-a-Service (WaaS) market will grow to $6.4B by 2018. In his session at 16th Cloud Expo, Seth Bostock, CEO of IndependenceIT, will begin by walking the audience through the evolution of Workspace as-a-Service, where it is now vs. where it going. To look beyond the desktop we must understand exactly what WaaS is, who the users are, and where it is going in the future. IT departments, ISVs and service providers must look to workflow and automation capabilities to adapt to growing ...
Platform-as-a-Service (PaaS) is a technology designed to make DevOps easier and allow developers to focus on application development. The PaaS takes care of provisioning, scaling, HA, and other cloud management aspects. Apache Stratos is a PaaS codebase developed in Apache and designed to create a highly productive developer environment while also supporting powerful deployment options. Integration with the Docker platform, CoreOS Linux distribution, and Kubernetes container management system ...
There are many considerations when moving applications from on-premise to cloud. It is critical to understand the benefits and also challenges of this migration. A successful migration will result in lower Total Cost of Ownership, yet offer the same or higher level of robustness. In his session at 15th Cloud Expo, Michael Meiner, an Engineering Director at Oracle, Corporation, will analyze a range of cloud offerings (IaaS, PaaS, SaaS) and discuss the benefits/challenges of migrating to each of...
Cloud data governance was previously an avoided function when cloud deployments were relatively small. With the rapid adoption in public cloud – both rogue and sanctioned, it’s not uncommon to find regulated data dumped into public cloud and unprotected. This is why enterprises and cloud providers alike need to embrace a cloud data governance function and map policies, processes and technology controls accordingly. In her session at 15th Cloud Expo, Evelyn de Souza, Data Privacy and Compliance...
As organizations shift toward IT-as-a-service models, the need for managing and protecting data residing across physical, virtual, and now cloud environments grows with it. CommVault can ensure protection &E-Discovery of your data – whether in a private cloud, a Service Provider delivered public cloud, or a hybrid cloud environment – across the heterogeneous enterprise. In his session at 16th Cloud Expo, Randy De Meno, Chief Technologist - Windows Products and Microsoft Partnerships, will disc...
Containers and microservices have become topics of intense interest throughout the cloud developer and enterprise IT communities. Accordingly, attendees at the upcoming 16th Cloud Expo at the Javits Center in New York June 9-11 will find fresh new content in a new track called PaaS | Containers & Microservices Containers are not being considered for the first time by the cloud community, but a current era of re-consideration has pushed them to the top of the cloud agenda. With the launch ...
VictorOps is making on-call suck less with the only collaborative alert management platform on the market. With easy on-call scheduling management, a real-time incident timeline that gives you contextual relevance around your alerts and powerful reporting features that make post-mortems more effective, VictorOps helps your IT/DevOps team solve problems faster.
HP and Aruba Networks on Monday announced a definitive agreement for HP to acquire Aruba, a provider of next-generation network access solutions for the mobile enterprise, for $24.67 per share in cash. The equity value of the transaction is approximately $3.0 billion, and net of cash and debt approximately $2.7 billion. Both companies' boards of directors have approved the deal. "Enterprises are facing a mobile-first world and are looking for solutions that help them transition legacy investme...
Skeuomorphism usually means retaining existing design cues in something new that doesn’t actually need them. However, the concept of skeuomorphism can be thought of as relating more broadly to applying existing patterns to new technologies that, in fact, cry out for new approaches. In his session at DevOps Summit, Gordon Haff, Senior Cloud Strategy Marketing and Evangelism Manager at Red Hat, will discuss why containers should be paired with new architectural practices such as microservices ra...
Roberto Medrano, Executive Vice President at SOA Software, had reached 30,000 page views on his home page - http://RobertoMedrano.SYS-CON.com/ - on the SYS-CON family of online magazines, which includes Cloud Computing Journal, Internet of Things Journal, Big Data Journal, and SOA World Magazine. He is a recognized executive in the information technology fields of SOA, internet security, governance, and compliance. He has extensive experience with both start-ups and large companies, having been ...
The industrial software market has treated data with the mentality of “collect everything now, worry about how to use it later.” We now find ourselves buried in data, with the pervasive connectivity of the (Industrial) Internet of Things only piling on more numbers. There’s too much data and not enough information. In his session at @ThingsExpo, Bob Gates, Global Marketing Director, GE’s Intelligent Platforms business, to discuss how realizing the power of IoT, software developers are now focu...
Operational Hadoop and the Lambda Architecture for Streaming Data Apache Hadoop is emerging as a distributed platform for handling large and fast incoming streams of data. Predictive maintenance, supply chain optimization, and Internet-of-Things analysis are examples where Hadoop provides the scalable storage, processing, and analytics platform to gain meaningful insights from granular data that is typically only valuable from a large-scale, aggregate view. One architecture useful for capturing...
SYS-CON Events announced today that Vitria Technology, Inc. will exhibit at SYS-CON’s @ThingsExpo, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. Vitria will showcase the company’s new IoT Analytics Platform through live demonstrations at booth #330. Vitria’s IoT Analytics Platform, fully integrated and powered by an operational intelligence engine, enables customers to rapidly build and operationalize advanced analytics to deliver timely business outcomes ...
DevOps is about increasing efficiency, but nothing is more inefficient than building the same application twice. However, this is a routine occurrence with enterprise applications that need both a rich desktop web interface and strong mobile support. With recent technological advances from Isomorphic Software and others, it is now feasible to create a rich desktop and tuned mobile experience with a single codebase, without compromising performance or usability.
SYS-CON Events announced today Arista Networks will exhibit at SYS-CON's DevOps Summit 2015 New York, which will take place June 9-11, 2015, at the Javits Center in New York City, NY. Arista Networks was founded to deliver software-driven cloud networking solutions for large data center and computing environments. Arista’s award-winning 10/40/100GbE switches redefine scalability, robustness, and price-performance, with over 3,000 customers and more than three million cloud networking ports depl...
The speed of software changes in growing and large scale rapid-paced DevOps environments presents a challenge for continuous testing. Many organizations struggle to get this right. Practices that work for small scale continuous testing may not be sufficient as the requirements grow. In his session at DevOps Summit, Marc Hornbeek, Sr. Solutions Architect of DevOps continuous test solutions at Spirent Communications, will explain the best practices of continuous testing at high scale, which is r...
SYS-CON Events announced today that Open Data Centers (ODC), a carrier-neutral colocation provider, will exhibit at SYS-CON's 16th International Cloud Expo®, which will take place June 9-11, 2015, at the Javits Center in New York City, NY. Open Data Centers is a carrier-neutral data center operator in New Jersey and New York City offering alternative connectivity options for carriers, service providers and enterprise customers.
Thanks to Docker, it becomes very easy to leverage containers to build, ship, and run any Linux application on any kind of infrastructure. Docker is particularly helpful for microservice architectures because their successful implementation relies on a fast, efficient deployment mechanism – which is precisely one of the features of Docker. Microservice architectures are therefore becoming more popular, and are increasingly seen as an interesting option even for smaller projects, instead of bein...