Concrete Examples of How Health Intelligence Saves Lives
An excellent article in Health Data Management by Greg Gillespie gives some wonderful examples of the power of analytics to improve health outcomes, looking at data from some of the 2,000+ clinical trials that Cleveland Clinic is currently running.
I strongly encourage you to read the original article (also available in pdf format), but here are summaries of the three use cases highlighted: hand-washing analytics, central-line analytics, and blood-transfusion analytics.
Data Transparency and Hand-Washing Compliance
Cleveland Clinic uses SAP BusinessObjects Dashboards (Xcelsius) to display information, change behavior, and avoid infections:
Cleveland Clinic has developed a program where staff from compliance anonymously watch workers in different departments and record whether they do in fact follow hand hygiene guidelines. Their findings are uploaded into Cleveland Clinic’s enterprise analytics system and are accessible via a dashboard tab.
Four years ago, the system was showing a 40 percent compliance rate with hand hygiene guidelines. Now the compliance rate is staying well over 90 percent, staving off a significant number of hospital-acquired infections and other complications arising from hygiene issues.
“That’s the critical value of data transparency—you can show people what they’re really doing as opposed to what they think they’re doing, and we can show it on a department, unit-by-unit or individual practitioner level,” says Steve Davis M.D. “I’ve found that when you put that kind of information in front of physicians, their competitive streak really comes out. No one likes to get a ‘C’ on their report card, and if you don’t have data everyone assumes they’re getting an ‘A.’ When they find out they’re not, then they get moving.”
[By coincidence, a post in the Decision Factor blog also takes up the theme of hand-washing this week, arguing that data cleansing is the single most important means of avoiding bad decisions. ]
Reducing Infections While Saving Money
By carefully collecting and analyzing data, Cleveland Clinic has been able to reduce infection rates, spend less on equipment, and avoid costs of up to $30,000 per affected patient:
The Centers for Disease Control and Prevention estimate that nearly 250,000 of the bloodstream infections occur annually from procedural issues associated with inserting and maintaining central lines—tubes inserted near the heart or a large blood vessel that are used to give fluids, antibiotics, medical treatments such as chemotherapy, and liquid food.
Overhauling the health system’s approach to central-line infections had a significant financial return in addition to the clinical benefits.
Before clinical and business analytics were applied, each individual unit was responsible for ordering their own lines, which meant that more than 30 different lines (and more than 90 different PICC lines, another type of tube) were being used across Cleveland Clinic, which was not only financially inefficient but also clinically dangerous.
By streamlining the purchasing to one vendor, the equipment and maintenance costs dropped significantly. And standardizing the clinical processes resulted in major cost avoidance—it’s estimated by the Health Research & Educational trust that central-line infections add upwards of $30,000 in treatment costs per afflicted patient.
Best-Practice Blood Transfusions
A blood transfusion dashboard helps identify physicians that haven’t kept up with the latest information in health best practice, improve the supply of blood, and reduces costs:
Andrew Proctor, administrative director of medical operations for Cleveland Clinic has developed a blood utilization dashboard that enables department heads and others to drill down to a physician level how much blood is being used for transfusions.
Standard industry practice used call for ordering transfusions if a patient’s hemoglobin count was below 10 after surgery or due to critical illness, But about a decade ago, says Davis, medical research showed convincingly that blood transfusions given at those hemoglobin values, and even significantly lower, in nearly all cases did more harm than good, providing few benefits and increasing the risks of nosocomial infections.
“Blood transfusions is another area where physician behavior has changed slower than the evidence, and our data is helping drive that behavioral change by enabling us to determine where blood utilization still goes against best practices, and addressing the issue on a unit or individual physician basis,” Davis says.
The result has been a significant reduction in blood utilization, which equates to a significant reductions in costs associated with maintaining the blood supply, and an improvement in patient outcomes.
Health Data + Analysis Saves Lives
I believe we’ve only scratched the surface of what is possible using analytics. New developments in big data mobile, cloud, analytic, and collaborative technology are combining to create new ways of improving health care.
Examples include the new SAP Collaborative E-Care Management application that connects patients, care providers and their families through medical monitoring software and mobile devices to better manage their health with individualized treatment plans:
And the pioneering work being done in conjunction with Charité, Europe’s largest teaching hospital, to enable mobile access to health data anytime, anywhere, including the SAP HANA-based Oncolyzer cancer-research application.
For more information, visit the Healthcare area of SAP.com
SAP Innovation Tour in the Baltics
I’m in the Baltics this week (Estonia, Lithuania, Latvia), presenting a business innovation keynote and a big data track session as part of the SAP Innovation Forum.
Yesterday’s sessions in Tallinn were fascinating, including:
- Industry thought leader Peep Aavikso, on why smart companies need smart people
- Janeck Gustavson of Eesti Energy talking about their use of SAP Business Planning and Consolidation (BPC)
- A very passionate talk from Olga Lustsik of Swedbank Estonia explaining the power of activity based costing, and how they have implemented SAP Profit and Cost Management (PCM)
- An interactive whiteboarding session with SAP’s Santosh Takoor explaining how to align corporate strategy with systems of execution for best in class operations in finance (with SAP Enterprise Performance Management and lots of compelling customer examples)
- SAP’s Dr. Jens Baumman on rapid deployment solutions for SAP ERP
- SAP’s Eero Koskinen on the power of SAP HANA
- And finally a GREAT demonstration of the latest SAP solutions and prototypes by the SAP Demo team
My keynote presentation was based on some of the material from a previous post: 2012, The Year Analytics Means Business
Here are the slides:
- Business In The Moment: From Reactive to Proactive (pdf)
- Business in The Moment: From Reactive to Proactive (ppt)
And for my track session:
- Turn Big Data Into Business Value With Real-Time BI (pdf)
- Turn Big Data Into Business Value With Real-Time BI (ppt)
Today’s sessions are in Vilnius, Lithuania, including a fascinating presentation from Sarunas Chomentauskas, Co-founder of Metasite Business Solutions, on how they have used open-source Big Data technologies for their customers including customer churn, and machine learning techniques including how to explain the difference between a dog and a cat to a computer…
I’ll update this post over the course of the coming days. You can follow the tour on twitter using the #SAPInnovation hashtag.
Dawn this morning over Vilnius, Lithuania
Presentation: How Big Data Shapes Business Results
Steve Lucas and Timo Elliott onstage at SAP BI 2012, Las Vegas. Image courtesy of Matthias Wild
At this week’s SAP BI2012 conference, I had the honor of co-presenting the keynote, “How Big Data Shapes Business Results” with Steve Lucas, SAP EVP Business Analytics, Database & Technology, and with demo support from Fred Samson.
The big theme of the last year has been big data. There was a lot of innovation in many areas, but big data has had a huge impact on both how organizations plan their overall technology strategy as well as affecting other specific strategies such as analytics, cloud, mobile, social, and collaboration.
Steve kicked off by addressing the confusion (and cynicism) about the definition of “big data” — noting that people had supplied at least twenty different definitions in response to his question on Twitter. The popularity of the term has been driven by the rise of new open-source technology technology such as Hadoop, but it is now typically used to refer to what Gartner calls “extreme data”.
Extreme data is on the high end of one or more of the ‘3Vs’: Volume, Velocity, and Variety (and some note that there’s a fourth V, validity, that must be taken account of: data quality remains the #1 struggle for organizations trying to implement successful analytic projects).
To address all of these effectively, any “big data solution” has to encompass a wide range of different technologies. SAP is proposing a new “Big Data Processing Framework” that includes integration to new tools such as Hadoop, but also addresses the need for the other ‘V’s for a global approach to ingesting, storing, processing, and presenting data from both structured and less-structured sources. Many more details about this framework will be available in the coming months.
The keynote session went on to talk about how big data is related to other technologies, such as real time, mobile, cloud, virtualization, and social, with highlight demonstrations of some of the latest SAP technology. These included: in-memory smart meter analytics, SAP BusinessObjects 4.0 running on Sybase IQ, BI On-Demand powered by HANA, SAP NetWeaver Landscape Virtualization Management, a mobile Hospital Oncology analytics application, and two new mobile consumer applications from SAP: Recalls Plus, and an upcoming project called iLike
Dave Rathburn put together a nice overview of the session, and Matthias Wild wrote up a post on the SDN site.
A reply of the session is now available, and here’s a copy of the presentation available for download:
Just Add Analytics – Even to Toothbrushes
I recently saw a presentation mentioning that there “are more mobile phones than toothbrushes in the world”, and according to some research by the 60 second marketer, it seems that in all likelihood, this is absolutely true:
My next thought was “why not combine the two?!”. Here’s my quick mockup of an iPhone case of the future:
But as usual, truth is stranger than fiction. Just when you think you’ve seen every use of analytics possible, along comes a real “iPhone toothbrush”. The Beam Toothbrush is a bluetooth-enabled toothbrush and associated iphone application:
It provides detailed analytics, recording how long each person brushes their teeth:
And like any good performance management tool, it uses gamification techniques to encourage the right behavior…
It seems as if analytics is being embedded in every device possible, such as the new Nike Hyperdunk+ basketball shoes and associated application:
Anybody else have any favorite examples of how analytics are taking over the world of consumer products?
Business Intelligence Best Practice Twitter #SAPChat
I will be the host of the next #SAPChat, an interactive panel discussion carried out entirely over Twitter. It’s scheduled for 9am PST / 18:00 CET on Wednesday February 29th, and the subject will be “Business Intelligence Best Practice”. We will be discussing how best to implement business intelligence projects successfully, with an emphasis on people-focused hints and tips rather than technical discussions. And with only 140 characters available, the advice is guaranteed to be succinct!
You can participate in the discussion by asking your question over twitter, by including the hashtag #SAPChat, or just tune in on the day to watch the information flow. You can use your favorite Twitter tool, or join the action at http://tweetchat.com/room/SAPChat. The goal is to make the discussion as interactive as possible – don’t hesitate to answer questions from other people, or expand on the points made.
If you’d like an idea of what the chats look like, take a look at the transcripts from previous sessions such as SAP’s CIO Oliver Bussmann on the Consumerization of IT and a deluge of questions around SAP HANA.
For the session, I will be accompanied by two world experts on the topic of successfully deploying business intelligence projects:
Alys Woodward
Alys Woodward is program manger for European Business Analytics, Enterprise Collaboration and Social Solutions at IDC. Alys has been in the business analytics space since 1995, and an analyst since 2003. I’ve shared many stages with her over the years, most recently in Russia, and I have been consistently impressed with how much I’ve learned in each presentation. You can find out more about IDC’s research on making BI more pervasive with this research sponsored by SAP:
Improving Organizational Performance Through Pervasive Business Intelligence:
An increasing number of organizations are making BI and analytics functionality more broadly available to all decision makers inside and outside the organization. Internally, more pervasively available BI solutions lead to greater accountability by all employees and greater consistency in performance management. Externally, relationships with supplier and partners can be strengthened through effective sharing of key performance indicators (KPIs). However, having pervasive BI means more than having the appropriate BI tools distributed to all stakeholders. In pursuit of pervasive BI, organizations should focus on the five key factors that can be directly influenced to increase diffusion of BI. They are:
- Degree of training on the data, tools, and analytic techniques
- Design quality of the BI solution
- Prominence of data governance
- Nonexecutive involvement in promoting the design and use of BI solutions
- Prominence of a performance management methodology
You should follow Alys on Twitter: http://twitter.com/alyswoodward
Cindi Howson
Cindi Howson is the founder of BI Scorecard, a resource for in-depth BI product reviews, based on exclusive hands-on testing. I have known Cindi ever since she was the manager responsible for rolling out business intelligence at one of Business Objects’ largest customers, many years ago. Cindi carries out a key industry survey each year which gives insights into how successful organizations are with their business intelligence efforts. Cindi is a TDWI (The Data Warehousing Institute) faculty member and a contributing expert to Information Week. She has been now been advising clients on BI tool strategies and selections for more than 15 years, and wrote my favorite BI book:
Successful Business Intelligence: Secrets to Making BI a Killer App.
Business intelligence has the power to change people’s way of working, to enable businesses to compete more effectively and efficiently, and to help non-profits stretch their dollars further. The book draws on exclusive survey data and real-world case studies of BI success stories to identify proven BI best practices you can put to use in your organization, including:
- Gaining executive support and aligning your BI strategy with business goals
- Organizing BI teams and experts for success
- Choosing the best BI tools to meet user and business needs
- Improving data quality so decision-makers trust the BI solution
- Finding the relevance of BI to all employees, including front-line workers
- Using agile development processes to deliver BI capabilities and improvements at the speed of business
- Measuring success in multiple ways
You should follow Cindi on Twitter: http://twitter.com/BIScorecard
As you’re thinking of questions to ask, take a look at some of the great blog posts on the SAP Analytics blog and the Decision Factor blog.
Finally, if you’re interested in this session, you’ll be interested in this presentation I did late last year called “Why BI Products Fail and What To Do About It” (also available as slides: Why BI Projects Fail — PowerPoint Version)
I was the eighth employee of 
