Steve L. Schiavone

After eleven years I am retiring from Valleywise Health as their CTO. This is not to say that I will fade into the obscurity of retirement. I consider this milestone to be an opportunity to explore other exciting options.

I am grateful for the recognition I have received from Valleywise Health, and for the many postings on LinkedIn (thank you Kelly Summers for lighting that fire!). During the 11 years I have been with Valleywise Health a lot has happened and achieved, not only witnessing the transformation of our healthcare system, but being at the forefront of designing and developing new technology-driven architectures and frameworks but in the introduction core and leading-edge foundational technologies. Healthcare has become so reliant on technology that the two worlds have merged and become indistinguishable from each other. Because of this shift, the IT organization has become a critical partner in supporting, enabling and importantly, enhancing the myriad of complex operational and clinical workflows.

As an Architect of technology, I have always attempted to maintain a balance between systems complexity and pragmatism, acutely aware of the fact that systems fail, but complex systems fail in complex and unpredictable ways. I thought, for maybe the benefit of anyone reading this narrative I would share some insights and caution into what made the Valleywise Health Care Reimagined initiative (just under $1 Billion investment) so successful, resulting in the construction of five new clinics, one Behavioral Health and ED hospital, one advanced central utility plant, one on-premise tier III data center, one tier III co-location high density data center, one conferencing center, an advanced medical simulation center and administration building and one acute care hospital providing advanced critical services and engineered to enhance its role as an academic teaching hospital.

The insights I would like to share fall under the idea of critical success factors (it is not my intention to be at all patronizing). I am happy to share examples of any of the artifacts I have produced. None of my artifacts are so abstract as to be untenable, some may even be obvious to some.

All IT-related efforts must always connect back to an IT strategic narrative or roadmap. This ensures alignment and architectural consistency and prevents unnecessary fragmentation and complexity. For Valleywise Health there exists a 400-page narrative outlining a technology roadmap spanning 4 years.

Introduction of new technology even “adds” or modifications to existing technology must adhere to a set of technology guiding principles. These would cover the entire technology stack. For Valleywise I wrote 17 separate documents detailing for example, Architectural guiding principles, Security guiding principles, Technology Life Cycle Management, Orchestration and Automation, Technical Impact Questionnaire and Technical Reference Architectures guidelines.

Program Management is clearly important. When you translate complex multifaceted set of technical objectives and designs into programs and projects there is a need to introduce a formal “translation” methodology. Care Reimagined yielded initially 23 IT infrastructure projects (~$40M investment) and as construction of buildings ensued an additional ~$40M for equipment. The program objective was “Strengthening the Foundation”. Project planning and translation from strategy to reality leveraging the myriad of frameworks under the guiding principles outlined above leveraged two project methodologies viz. PMP and Prince 2. The most important technique used in translation was the Product Breakdown Structure (PBS). PBS methodology allowed for a structured and systematic mapping approach to building project plans thereby deriving resource, timeline, dependencies and budgets accurately. This prevents on-the-fly development of project plans that have little to do with the designs needed to be built or the controls required to minimize project risk.

Conceptualization and visualizations. As you may know, introducing new technologies requires you to consider the old IT adage of People, Process, Technology, Data, and Culture. Without a consistent framework complexity and fragmentation ensues into ultimately, chaos. Keeping complexity in check is important throughout the life cycle of your architecture. Here is an example of such a concept that was actually used:

Enterprise Strengthening the Foundation - Model

A Cautionary Tale This deals with lessons learned from the field:

New technologies require the cooperation of many third parties and vendors from various specialties. Ensure, prior to any engagement you have a well-defined narrative, or brief and a set of guiding principles and standards defined. Without these you are asking people outside your organization to define these for you – this is a tragedy in the making. Their objective may not be yours.

Never request from third parties’ advice on strategy. If you do not have one, develop at least an architectural roadmap. If you require assistance there are players that are neutral non-vendor or manufacturer specific even if you are a COTS house. It will pay dividends if you have an internally defined technology roadmap that is developed and owned by you. This becomes the mechanism by which you measure and evaluate technologies available to you in the marketplace.

There is no such thing as technology providing strategic benefits or competitive advantage (controversial I understand). Truly. You cannot commoditize (and trivialize) the intellectual capital and worth of an organization by simply acquiring off-the-shelf technology. You must view technology benefits through a technology-based framework that has been thoughtfully engineered in-house. If you do not have this, you are at the mercy of vendors.

Security starts at the conceptualization stage of any IT endeavor; it is part of a solution’s DNA. At Valleywise Health we layered security across the entire technology stack leveraging multiple technology standards as guidance. Under the concept of people, process et al., data drove many of the attributes that define quality, resilience, performance, capacity (queuing theory), encapsulation, zoning and segregation utilizing techniques such as “a day in the life of a packet” scenarios. If you cannot trace and account for how a single packet of data moves and changes through your architecture, you cannot hope to secure it.

If there are so many IT Gurus in the world, why do we have deployment failures, IT system failures and disasters. You must invest in not only technology but in skilled people/technicians and develop robust and strict process models to run your shop. To safeguard our multiple environments, we defined and developed a framework referred to as Systems Landscape Management Framework.

Every piece of technology has an operationalization dimension to it. This enables you to objectively assess its worth or merit (fit). It enables one to assess the cost of maintenance and service through the lens of life cycle management, it allows you to assess the skill levels needed to support and maintain the technology. You would not introduce a technology that you do not have the skills or means to support. However, this unfortunately happens.

AI, as with all innovations, has and continues to generate a great deal of hyperbole. My personal take and hence cautionary tale are the following points:

Intelligence is ill-defined and cannot be reliably measured, therefore what cannot be quantified cannot be encoded so is Artificial Intelligence a misnomer?

The term artificial intelligence is anthropomorphized by the media, attributing human-like characteristics thereby preventing critical thinking from being applied concerning its merit and true worth.

Software is generally flawed (a universal truth). AI and Machine Learning is software that has been written (in majority) by people (excluding certain advanced ML capabilities). Algorithms and in particular (training) data contain elements whose integrity and veracity are questionable. Caution needs to be applied to cleansing, normalization, standardization, and splitting of data used to either modify or create new underlying patterns used in a model.

It is hard on many occasions to reverse engineer outcomes generated by AI or machine learning and therefore one cannot always validate its output.

In the law of probability and large numbers one can create any unique work of literature, work of art even “accurate” clinical outcomes and diagnosis – there is no mysticism, no mind, consciousness nor intelligence. Given sufficient resources (data) and time, any event no matter how low has the probability of happening. Critical thinking needs to be applied in all cases. Do not overvalue is usefulness in your individual cases.

If you wish to evaluate AI, and Machine Learning (and their subsets) you would sandbox and attempt to evaluate outcomes by having robust business case, feasibility study, whilst maintaining an objective and quantifiable set of evaluation models. (Critical thinking 101.)

Security relative to AI and ML is complex and underdeveloped in part because of the “black box” nature of these worlds. You cannot secure what you do not see (or understand).

It is clear (superintelligent) AI and Machine Learning are powerful tools and are here to stay and will innervate itself in every aspect of society. As with all new technology its application and usefulness must be thoughtfully balanced and considered.

I have no personal stake in the narrative I wrote. If anyone wants examples of my documents, I can provide them (they will be sanitized to ensure confidentiality). I may over time add more to this article from other industries I worked in – if requested.

Steve L. Schiavone

Fountain Hills, Arizona, United States

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Steve L. Schiavone

Fountain Hills, Arizona, United States 4K followers 500+ connections

See your mutual connections View mutual connections with Steve L. Sign in Welcome back Email or phone Password Show Forgot password? Sign in or New to LinkedIn? Join now or New to LinkedIn? Join now

Articles by Steve L.

CTO - After all these years

By Steve L. Schiavone

Why Healthcare is not synonymous with Manufacturing

By Steve L. Schiavone

Activity

This incredible human being brings his 19 year old dog to the lake everyday, to give him couple hours of sleep and sweet dreams. Shep can not sleep -…

Liked by Steve L. Schiavone

View Steve L.’s full profile

Other similar profiles

Kelly Summers, CHCIO, CDH-E

Allison Summers

Jennifer Tonis

Nick Summers

Campbell Moorhouse

Rodolfo Szoke

Matt Hall

Steve Reese

Marion DE Civ USAF U Kehr

Kathryn Miller

Karen Lipman

Anissa Talley

Michael Parks

Mary Lee DeCoster

Doug Baden

Diane Wynn, PMP

Sean Pardo, MSHA

Courtney Hunt

Simeon Brandon

Jamey Jameson

Explore collaborative articles

Add new skills with these courses

CCSK Cert Prep: 1 Cloud Architecture

IoT Foundations: Operating System Applications

Nano Tips for Moving to the Cloud for Business Leaders with Rashim Mogha

Fountain Hills, Arizona, United States

4K followers 500+ connections

View mutual connections with Steve L.

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