Big Data. Big Decisions
InformationWeek
Special Coverage Series


Univ. North Carolina, IBM Team Up For Research, Personalized Care

Integration with IBM's technologies is expected to improve treatment of patients with diseases such as diabetes, cancer, and cystic fibrosis.

While many health care providers in the United States are just now considering rolling out electronic medical record systems, the University of North Carolina Health Care System is on its way with the help of IBM.

The university said this week that it's using data from its e-medical record and other clinical systems to provide improved quality of care for patients now, and more personalized treatments in the future.

UNC Health Care, the University of North Carolina's nonprofit, state-owned integrated health care system, is expanding its use of IBM InfoSphere, WebSphere, and Health Integration Framework technologies to improve research and treatment of patients with diseases such as diabetes, cancer, and cystic fibrosis.

IBM and UNC Health Care have been working together over the last two years to create a data warehouse that brings together several dozen sources of data, including information from UNC Health Care's e-medical record database, registration and insurance systems, nursing notes, and other clinical data.

By combining the data, UNC Health Care's doctors in the near term will be able to analyze and access data for improved disease management of pre-diabetic and diabetic patients based on current standards of quality care. In the longer term, the aim is to provide more personalized care to these patients, based individual risk factors, genetics, demographics, and other profile data.

"Our eye looking into the future is on providing more personalized medicine," said Dr. Don Spencer, a practicing physician and associate director of medical informatics at UNC Health Care. "In the nearer term, our eye is on the different standards of good diabetic care and how patients are receiving that." That includes ensuring that pre-diabetic patients are provided with treatments that can help prevent the development of full-blown diabetes, as well as giving diabetic patients regular eye, foot, and other care to prevent complication of their disease.

In the future, the system could allow UNC Health Care doctors to access and analyze research and other data that provides information about the best treatments available for diabetic patients with specific genetic characteristics, medical history, and more individualized needs. "I don't want to oversell this, but those are goals," Spencer said. Besides improving quality of care, the effort is also focused on enhancing research by providing UNC researchers with Web-based data analysis, reporting, and business intelligence tools for speeding up the development of new treatments, as well as the workflow involved with preparatory research to regulatory approval.

Research queries that in the past took weeks to perform can be accomplished in seconds, said John Soyring, IBM's VP of solutions and software. IBM has been working with a number of other large medical centers and researchers, including the Mayo Clinic and the Cleveland Clinic, for data warehouse and data analysis initiatives in the quest for improved patient care and personalized medicine.

UNC Health Care has been using in-patient and ambulatory care e-medical record systems for several years, said Spencer. Those systems were developed using internal and external consultants, as well as IBM infrastructure and data base technologies, he said.

In addition to research and care related to diabetes, the extended joint work between UNC Health Care and IBM will focus on cancer and cystic fibrosis.


The next round of Microsoft vs. Linux will be in the health care industry. InformationWeek has published an independent analysis of this topic. Download the report here (registration required).



Related Links

Related Reading


More Insights




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.