Big Data. Big Decisions
InformationWeek
Special Coverage Series

Commentary


Guerra On Healthcare: Policy Trumping Health IT Experience

There's no substitution for working your way up through the ranks. Unfortunately, many of the federal policymakers have never been in the trenches--and it shows.

Like most people, I've worked my way up in my chosen profession. For me, in journalism, that started with formal education, then entry-level jobs focused on learning the basics like copy editing, interviewing, and writing. After that came practice and eventual comfort with the multi-sourced feature story, which called for weaving several perspectives into a readable tapestry.

By the time I had moved into a position of management, I had mastered the tasks those reporting to me would be responsible for. I didn't just have an idea of what it took to complete those tasks--from both a skill level and time requirement point of view--I knew exactly what it took. That meant I could properly set assignments--including topics, number of sources, and deadlines--with confidence. I could subsequently recognize high-level work and remediate that which had fallen short because, again, I had done the work myself.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

Most of you are in the same position, having worked your way up from ground-floor positions in the IT shop to ever higher levels of responsibility and management. Today, you find yourselves in the CIO role. Such a path to power means you also know how long things should take and are able to appreciate superior work, while holding to account those who fall short of reasonable expectations.

The problem with the Meaningful Use program is the undue influence by those who have never worked in the healthcare IT trenches, never implemented a system, never received a verbal thrashing from a cardio-thoracic surgeon who'd been up for 36 hours and found himself unable to remember a password he'd recently been prompted to change (7 characters, 2 caps, and at least 1 digit, please!).

Never have the trenches been better illuminated than the seminal "Meditech 6.0 Diary" series, which chronicles one organization's upgrade from Meditech Magic 5.63 to Meditech 6.0. It's being written by Jorge Grillo, CIO at Canton-Potsdam Hospital. Amazingly, we're already at Part 10 of the monthly chronicle, and continue to see the sausage being ground in all its gory detail. For those who've never seen code before, this is what healthcare IT change takes--and here we're talking about an upgrade, not even a new install. The series is all the more relevant and representative due to Meditech's vast footprint in the market.

I know some on the federal Health IT Policy Committee are going by feel, rather than fact, because I've literally heard them say as much. Statements like, "I just feel like they should be able to do better than 10% on this," aren't as rare as one might hope. Consistently, one who lives in the trenches, Intermountain CIO Marc Probst, has asked if there isn't better data upon which to build the Meaningful Use measures, yet the speed with which the program inexorably roars downstream leaves little time for quantitative analysis, let alone reflection.

And though reflection would be the best treatment for this patient, it has to be done right. Simply reviewing the applications of those who've attested won't do. If only five students from a class of 30 show up for the final exam, and all get As, should the teacher get a gold star? Perhaps the teacher would like you to think so, as his bonus may be tied to performance, but we know better. We know the 25 who didn't show up matter. We have to find out if they thought the test was too hard to bother, or (in the case of eligible providers) if they never even heard about it at all.

Anthony Guerra is the founder and editor of healthsystemCIO.com, a site dedicated to serving the strategic information needs of healthcare CIOs. He can be reached at aguerra@healthsystemCIO.com.

In the new, all-digital InformationWeek Healthcare: iPads are leading a new wave of devices into the exam room. Are security, tech support, and infection control up to the task? Download it now. (Free registration required.)



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.