Click here to close now.




















Welcome!

Microservices Expo Authors: Pat Romanski, Elizabeth White, VictorOps Blog, SmartBear Blog, Liz McMillan

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

@MicroservicesExpo Stories
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, discussed why containers should be paired with new architectural practices such as microservices rathe...
SYS-CON Events announced today that G2G3 will exhibit at SYS-CON's @DevOpsSummit Silicon Valley, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. Based on a collective appreciation for user experience, design, and technology, G2G3 is uniquely qualified and motivated to redefine how organizations and people engage in an increasingly digital world.
Any Ops team trying to support a company in today’s cloud-connected world knows that a new way of thinking is required – one just as dramatic than the shift from Ops to DevOps. The diversity of modern operations requires teams to focus their impact on breadth vs. depth. In his session at DevOps Summit, Adam Serediuk, Director of Operations at xMatters, Inc., will discuss the strategic requirements of evolving from Ops to DevOps, and why modern Operations has begun leveraging the “NoOps” approa...
Puppet Labs has announced the next major update to its flagship product: Puppet Enterprise 2015.2. This release includes new features providing DevOps teams with clarity, simplicity and additional management capabilities, including an all-new user interface, an interactive graph for visualizing infrastructure code, a new unified agent and broader infrastructure support.
Early in my DevOps Journey, I was introduced to a book of great significance circulating within the Web Operations industry titled The Phoenix Project. (You can read our review of Gene’s book, if interested.) Written as a novel and loosely based on many of the same principles explored in The Goal, this book has been read and referenced by many who have adopted DevOps into their continuous improvement and software delivery processes around the world. As I began planning my travel schedule last...
Several years ago, I was a developer in a travel reservation aggregator. Our mission was to pull flight and hotel data from a bunch of cryptic reservation platforms, and provide it to other companies via an API library - for a fee. That was before companies like Expedia standardized such things. We started with simple methods like getFlightLeg() or addPassengerName(), each performing a small, well-understood function. But our customers wanted bigger, more encompassing services that would "do ...
SYS-CON Events announced today that DataClear Inc. will exhibit at the 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. The DataClear ‘BlackBox’ is the only solution that moves your PC, browsing and data out of the United States and away from prying (and spying) eyes. Its solution automatically builds you a clean, on-demand, virus free, new virtual cloud based PC outside of the United States, and wipes it clean...
Docker containerization is increasingly being used in production environments. How can these environments best be monitored? Monitoring Docker containers as if they are lightweight virtual machines (i.e., monitoring the host from within the container), with all the common metrics that can be captured from an operating system, is an insufficient approach. Docker containers can’t be treated as lightweight virtual machines; they must be treated as what they are: isolated processes running on hosts....
Culture is the most important ingredient of DevOps. The challenge for most organizations is defining and communicating a vision of beneficial DevOps culture for their organizations, and then facilitating the changes needed to achieve that. Often this comes down to an ability to provide true leadership. As a CIO, are your direct reports IT managers or are they IT leaders? The hard truth is that many IT managers have risen through the ranks based on their technical skills, not their leadership ab...
SYS-CON Events announced today that HPM Networks will exhibit at the 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. For 20 years, HPM Networks has been integrating technology solutions that solve complex business challenges. HPM Networks has designed solutions for both SMB and enterprise customers throughout the San Francisco Bay Area.
SYS-CON Events announced today the Containers & Microservices Bootcamp, being held November 3-4, 2015, in conjunction with 17th Cloud Expo, @ThingsExpo, and @DevOpsSummit at the Santa Clara Convention Center in Santa Clara, CA. This is your chance to get started with the latest technology in the industry. Combined with real-world scenarios and use cases, the Containers and Microservices Bootcamp, led by Janakiram MSV, a Microsoft Regional Director, will include presentations as well as hands-on...
The pricing of tools or licenses for log aggregation can have a significant effect on organizational culture and the collaboration between Dev and Ops teams. Modern tools for log aggregation (of which Logentries is one example) can be hugely enabling for DevOps approaches to building and operating business-critical software systems. However, the pricing of an aggregated logging solution can affect the adoption of modern logging techniques, as well as organizational capabilities and cross-team ...
DevOps has traditionally played important roles in development and IT operations, but the practice is quickly becoming core to other business functions such as customer success, business intelligence, and marketing analytics. Modern marketers today are driven by data and rely on many different analytics tools. They need DevOps engineers in general and server log data specifically to do their jobs well. Here’s why: Server log files contain the only data that is completely full and accurate in th...
SYS-CON Events announced today that Pythian, a global IT services company specializing in helping companies leverage disruptive technologies to optimize revenue-generating systems, has been named “Bronze Sponsor” of SYS-CON's 17th Cloud Expo, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. Founded in 1997, Pythian is a global IT services company that helps companies compete by adopting disruptive technologies such as cloud, Big Data, advance...
In today's digital world, change is the one constant. Disruptive innovations like cloud, mobility, social media, and the Internet of Things have reshaped the market and set new standards in customer expectations. To remain competitive, businesses must tap the potential of emerging technologies and markets through the rapid release of new products and services. However, the rigid and siloed structures of traditional IT platforms and processes are slowing them down – resulting in lengthy delivery ...
In his session at 17th Cloud Expo, Ernest Mueller, Product Manager at Idera, will explain the best practices and lessons learned for tracking and optimizing costs while delivering a cloud-hosted service. He will describe a DevOps approach where the applications and systems work together to track usage, model costs in a granular fashion, and make smart decisions at runtime to minimize costs. The trickier parts covered include triggering off the right metrics; balancing resilience and redundancy ...
Whether you like it or not, DevOps is on track for a remarkable alliance with security. The SEC didn’t approve the merger. And your boss hasn’t heard anything about it. Yet, this unruly triumvirate will soon dominate and deliver DevSecOps faster, cheaper, better, and on an unprecedented scale. In his session at DevOps Summit, Frank Bunger, VP of Customer Success at ScriptRock, will discuss how this cathartic moment will propel the DevOps movement from such stuff as dreams are made on to a prac...
It’s been proven time and time again that in tech, diversity drives greater innovation, better team productivity and greater profits and market share. So what can we do in our DevOps teams to embrace diversity and help transform the culture of development and operations into a true “DevOps” team? In her session at DevOps Summit, Stefana Muller, Director, Product Management – Continuous Delivery at CA Technologies, answered that question citing examples, showing how to create opportunities for ...
What does “big enough” mean? It’s sometimes useful to argue by reductio ad absurdum. Hello, world doesn’t need to be broken down into smaller services. At the other extreme, building a monolithic enterprise resource planning (ERP) system is just asking for trouble: it’s too big, and it needs to be decomposed.
The Microservices architectural pattern promises increased DevOps agility and can help enable continuous delivery of software. This session is for developers who are transforming existing applications to cloud-native applications, or creating new microservices style applications. In his session at DevOps Summit, Jim Bugwadia, CEO of Nirmata, will introduce best practices, patterns, challenges, and solutions for the development and operations of microservices style applications. He will discuss ...