Archive for September, 2014

September 30th 2014

Wise Practitioner – Predictive Analytics Interview Series: John Cromwell, M.D., University of Iowa Hospitals & Clinics

Wise Practitioner – Predictive Analytics Interview Series: John Cromwell, M.D., University of Iowa Hospitals & Clinics

By: Jeff Deal, Program Chair, Predictive Analytics World Healthcare

In anticipation of his upcoming keynote conference presentation at Predictive Analytics World Healthcare in Boston, “Real-Time Modeling of Surgical Site Infections,” we asked John Cromwell, M.D., Associate Professor at University of Iowa Hospitals & Clinics, a few questions about his work in predictive analytics.

Q: In your work with predictive analytics, what area of healthcare are you focused on (i.e., clinical outcomes, insurance, quality improvement, etc.)?

A: Focusing is difficult given the broad array of challenges facing hospitals today. Having said that, our work has been primarily on clinical outcomes and quality improvement.

Q: What clinical outcomes do your models predict?

A: My group works on quality and performance in surgery. In the context of surgical patients, we are modeling readmissions, surgical site infections, and the development other hospital-acquired infections such Clostridium Difficile.

Q: How does predictive analytics deliver value at your organization? What is one specific way in which it actively drives decisions?

A: PA allows us to prioritize use of both institutional and community resources for improving outcomes for a large population. As an example, surgical site infections are dangerous and expensive. Being able to predict surgical site infections from the operating room before a patient’s incision has been closed allows us to change our wound management strategy up front. Targeting of resource-intensive and invasive wound management strategies to patients who will benefit the most is good for everyone.

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September 23rd 2014

Wise Practitioner – Predictive Analytics Interview Series: Linda Miner, Ph.D., Southern Nazerene University

Wise Practitioner – Predictive Analytics Interview Series: Linda Miner, Ph.D., http://www.predictiveanalyticsworld.com/patimes/wp-content/uploads/2014/08/Linda_Miner-image.jpgSouthern Nazerene University

By: Jeff Deal, Program Chair, Predictive Analytics World Healthcare

In anticipation of her upcoming conference presentation at Predictive Analytics World Healthcare in Boston, “Developing a Mortality Prediction Model for Disseminated Intravascular Coagulation (DIC),” we asked Linda Miner, Ph.D., Professor at Southern Nazerene University, a few questions about her work in predictive analytics.

Q: What clinical outcomes do your models predict?

A: We would like to be able to predict that someone is at risk of dying from DIC symptoms, based on admission variables.

Q: How does predictive analytics deliver value at your organization? What is one specific way in which it actively drives decisions?

A: If death can be predicted before symptoms of DIC then extra care can be exerted in treatment. We might even be able to figure out which of the patient entry conditions might be most predictive for an individual and more tailored counter measures taken.

Q: Can you describe a successful result, such as the predictive lift of your model or the ROI of an analytics initiative?

A: It is possible that even given the obvious benefit of having people live, hospital stays might be shortened and resources might not be wasted on ineffective treatments with the more targeted treatments.

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September 16th 2014

Wise Practitioner – Predictive Analytics Interview Series: Marty Kohn, M.D. of Jointly Health

Wise Practitioner – Predictive Analytics Interview Series: Marty Kohn, M.D. of Jointly Health

By: Jeff Deal, Program Chair, Predictive Analytics World Healthcare

In anticipation of his upcoming conference keynote at Predictive Analytics World Healthcare in Boston, “Big Data and Clinical Decision Support,” we asked Marty Kohn, M.D., Chief Medical Scientist at Jointly Health, a few questions about his work in predictive analytics.

Q: In your work with predictive analytics, what area of healthcare are you focused on (i.e., clinical outcomes, insurance, quality improvement, etc.)?

A: Jointly Health focuses on patients with complex chronic diseases to improve health, reduce avoidable hospitalizations and acute care events and, as a result of decreased need for expense acute care, reduce costs.

Q: What outcomes do your models predict?

A: We predict which patients are likely to deteriorate so that a timely intervention can avoid the problem.

Q: How does predictive analytics deliver value at your organization? What is one specific way in which it actively drives decisions?

A: By identifying patterns in home monitoring physiologic data, coupled with interaction with the patient and the patient’s caregivers, we can give the care team early warning of a worsening of the patient’s clinical status. We develop such patterns in a way that is unique for each patient, allowing the care team sufficient warning to treat the problem when it is more likely to be successful.

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September 9th 2014

Wise Practitioner – Predictive Analytics Interview Series: John Foreman of MailChimp

Wise Practitioner – Predictive Analytics Interview Series: John Foreman of MailChimp

By: Eric Siegel, Founder, Predictive Analytics World

In anticipation of his upcoming conference keynote at Predictive Analytics World Boston, “Problems, then Techniques, then Toys. Keeping Your Predictive Analytics Right-side Up,” we asked John Foreman, Chief Scientist at MailChimp, a few questions about his work in predictive analytics.

Q: In your work with predictive analytics, what behavior do your models predict?

A: At MailChimp, we use predictive modeling across the application to improve the experiences of our users. Some examples:

  • We predict users who are unlikely to send spam, and we allow them to begin sending email through the system without manual account vetting (manual vetting slows people down by a day)
  • We predict users who are likely to send spam, and we shut them down before they send in order to protect our email-sending ecosystem
  • We predict users who are on a free account but who are likely to pay in the future. We then give them the same customer support given to currently paid users
  • We predict users who are most certainly not bots and we remove reCAPTCHA entirely from the app for them
  • We predict the knowledge base articles that a user is most likely interested in when they contact customer support
  • We predict the best time to send an email address marketing content and provide that to users in our Send Time Optimization (STO) system
  • Given a small segment of email addresses, we predict other email addresses on a user’s list that have the same interests to facilitate better segmentation and targeting
  • We predict demographic data on email addresses

These are just some examples of the different models in play.

Q: How does predictive analytics deliver value at your organization? What is one specific way in which it actively drives decisions?

A: Predictive analytics is a key part of our user on-boarding and compliance process. MailChimp has over 6 million customers, and without predictive modeling, the company would be left linearly scaling the headcount of customer support and compliance. Predictive models enable us to automate the easy jobs, allowing our compliance personnel to hunt down the worst of worst in terms of bad actors. This lowers our headcount, saving us a great deal of money. We are able to manage 6 million customers with less than 300 people total at the company.

Furthermore, our user-facing predictive products (Send Time Optimization & Segment

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September 2nd 2014

Wise Practitioner – Predictive Analytics Interview Series: Jack Levis of UPS

Wise Practitioner – Predictive Analytics Interview Series:

Jack Levis of UPS

By: Eric Siegel, Founder, Predictive Analytics World

In anticipation of his upcoming conference keynote at Predictive Analytics World Boston, “UPS Analytics – The Road to Optimization,” we asked Jack Levis – Senior Director, Process Management at UPS, a few questions about his work in predictive analytics.

Q: In your work with predictive analytics, what behavior do your models predict?

A: We use a tremendous number of predictive and prescriptive models at UPS. They are used to help make decisions, which range from where to build a facility and what type of aircraft to purchase to which packages go in each trailer and how to maintain our delivery fleet.

We currently have 700 dedicated resources working on a system called ORION, which has been called “arguably the world’s largest Operations Research Project.” With ORION, we are using analytics to determine the best way for a driver to serve our customers at the lowest cost.

Q: How does predictive analytics deliver value at your organization? What is one specific way in which it actively drives decisions?

A: We do not do anything by the “seat of our pants.” Analytics is engrained so deep in our culture, it is difficult to separate analytics driven decisions from normal business processes.

In 1954, our CEO said, “If we did not have operations research, our rate of growth might have been affected. As we grow in size, our problems increase geometrically. Without Operations Research, we would be analyzing our problems intuitively only, and we would miss many opportunities to get maximum efficiency out of our operations.”

Analytics has helped UPS make better decisions in all parts of our business.

Q: Can you describe a successful result, such as the predictive lift of your model or the ROI of an analytics initiative?

A: In 2003, UPS began using predictive models to better plan our delivery operations. This suite of tools called Package Flow Technologies along with Telematics has been responsible for a yearly reduction of 85 million miles driven per year. This reduced our fuel needs by over 8 million gallons and reduced carbon emissions by 8,500 metric tons.

In addition, because the analytics and business processes are fully aligned we have been able to deploy new products for customers. UPS’ MyChoice is a prime example of that.

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