Welcome!

Machine Learning Authors: Yeshim Deniz, Pat Romanski, Rene Buest, Nate Vickery, Elizabeth White

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
Kubernetes is an open source system for automating deployment, scaling, and management of containerized applications. Kubernetes was originally built by Google, leveraging years of experience with managing container workloads, and is now a Cloud Native Compute Foundation (CNCF) project. Kubernetes has been widely adopted by the community, supported on all major public and private cloud providers, and is gaining rapid adoption in enterprises. However, Kubernetes may seem intimidating and complex ...
SYS-CON Events announced today that Calligo, an innovative cloud service provider offering mid-sized companies the highest levels of data privacy and security, has been named "Bronze Sponsor" of SYS-CON's 21st International Cloud Expo ®, which will take place on Oct 31 - Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Calligo offers unparalleled application performance guarantees, commercial flexibility and a personalised support service from its globally located cloud plat...
"We focus on SAP workloads because they are among the most powerful but somewhat challenging workloads out there to take into public cloud," explained Swen Conrad, CEO of Ocean9, Inc., in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"Outscale was founded in 2010, is based in France, is a strategic partner to Dassault Systémes and has done quite a bit of work with divisions of Dassault," explained Jackie Funk, Digital Marketing exec at Outscale, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We are still a relatively small software house and we are focusing on certain industries like FinTech, med tech, energy and utilities. We help our customers with their digital transformation," noted Piotr Stawinski, Founder and CEO of EARP Integration, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"I think DevOps is now a rambunctious teenager – it’s starting to get a mind of its own, wanting to get its own things but it still needs some adult supervision," explained Thomas Hooker, VP of marketing at CollabNet, in this SYS-CON.tv interview at DevOps Summit at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We've been engaging with a lot of customers including Panasonic, we've been involved with Cisco and now we're working with the U.S. government - the Department of Homeland Security," explained Peter Jung, Chief Product Officer at Pulzze Systems, in this SYS-CON.tv interview at @ThingsExpo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We're here to tell the world about our cloud-scale infrastructure that we have at Juniper combined with the world-class security that we put into the cloud," explained Lisa Guess, VP of Systems Engineering at Juniper Networks, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
There is a huge demand for responsive, real-time mobile and web experiences, but current architectural patterns do not easily accommodate applications that respond to events in real time. Common solutions using message queues or HTTP long-polling quickly lead to resiliency, scalability and development velocity challenges. In his session at 21st Cloud Expo, Ryland Degnan, a Senior Software Engineer on the Netflix Edge Platform team, will discuss how by leveraging a reactive stream-based protocol,...
"With Digital Experience Monitoring what used to be a simple visit to a web page has exploded into app on phones, data from social media feeds, competitive benchmarking - these are all components that are only available because of some type of digital asset," explained Leo Vasiliou, Director of Web Performance Engineering at Catchpoint Systems, in this SYS-CON.tv interview at DevOps Summit at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
Your homes and cars can be automated and self-serviced. Why can't your storage? From simply asking questions to analyze and troubleshoot your infrastructure, to provisioning storage with snapshots, recovery and replication, your wildest sci-fi dream has come true. In his session at @DevOpsSummit at 20th Cloud Expo, Dan Florea, Director of Product Management at Tintri, provided a ChatOps demo where you can talk to your storage and manage it from anywhere, through Slack and similar services with...
"We want to show that our solution is far less expensive with a much better total cost of ownership so we announced several key features. One is called geo-distributed erasure coding, another is support for KVM and we introduced a new capability called Multi-Part," explained Tim Desai, Senior Product Marketing Manager at Hitachi Data Systems, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"I'm here to leverage my secret sauce, which is using outsourced development and the company that I utilize is delaPlex Software and they've basically allowed me to win Fortune 500 companies," noted Justin Witz, CTO of FRA and PlanTools, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"As we've gone out into the public cloud we've seen that over time we may have lost a few things - we've lost control, we've given up cost to a certain extent, and then security, flexibility," explained Steve Conner, VP of Sales at Cloudistics,in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We are an IT services solution provider and we sell software to support those solutions. Our focus and key areas are around security, enterprise monitoring, and continuous delivery optimization," noted John Balsavage, President of A&I Solutions, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
As enterprise cloud becomes the norm, businesses and government programs must address compounded regulatory compliance related to data privacy and information protection. The most recent, Controlled Unclassified Information and the EU’s GDPR have board level implications and companies still struggle with demonstrating due diligence. Developers and DevOps leaders, as part of the pre-planning process and the associated supply chain, could benefit from updating their code libraries and design by in...
"Peak 10 is a hybrid infrastructure provider across the nation. We are in the thick of things when it comes to hybrid IT," explained Michael Fuhrman, Chief Technology Officer at Peak 10, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We were founded in 2003 and the way we were founded was about good backup and good disaster recovery for our clients, and for the last 20 years we've been pretty consistent with that," noted Marc Malafronte, Territory Manager at StorageCraft, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
DevOps at Cloud Expo, taking place October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 21st Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to w...
Internet of @ThingsExpo, taking place October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 21st Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The Internet of Things (IoT) is the most profound change in personal and enterprise IT since the creation of the Worldwide Web more than 20 years ago. All major researchers estimate there will be tens of billions devic...