Impressions from the Undergraduate Workshop on Data-Driven Decisions in Healthcare

big group of students outside SAMSI

February 2013 Undergraduate Workshop participants.

SAMSI recently held the Undergraduate Workshop on Data-Driven Decisions in Healthcare for about 30 students. Visiting professors, postdoctoral fellows and graduate fellows who are participating in this SAMSI program led the sessions providing cutting-edge research into the lectures. Students had a chance to work with data from the SEElab at Technion in Israel, got an overview of personalized medicine and a tutorial in R and a demonstration of the ARENA software.  Here are a few of the students’ impressions from the workshop.

Eric Laber instructing students

Eric Laber, NCSU, giving lecture at the workshop.

Eric Kernfeld, Tufts University Class of 2014, Applied Mathematics

“I had a great time at the workshop on Data Driven Decisions in Health Care this past weekend. It was a nice opportunity to meet statisticians, something I don’t get the chance to do back at Tufts. I also met a lot of undergraduates majoring in statistics and mathematics. The food was good, the staff were welcoming, the accommodations were convenient, and the talks were well-pitched. I recommend SAMSI workshops to anyone who’s interested in the topics, especially to people considering graduate education down the road.”

Danielle Llanos, Georgetown University

“I thought the SAMSI workshop was wonderful. It was a great opportunity to learn from talented individuals, and a chance to expand my network. The lecture topics were incredibly interesting and were very relevant to my career goals. Probably the best part of the workshop was the graduate student panel. The ability to ask those burning questions and learn from the experiences of others was great. I would recommend any SAMSI workshop to students looking to learn more about opportunities in the sciences, and expanding their educational experiences.”

three students at table

Students networking at lunch.

Brittany Boribong, sophomore, biomathematics major at University of Scranton

“As a student with no background in statistics and programming, I found the workshop a bit overwhelming but no less interesting. Coming into this with no experience just allowed me to take that much more out of the workshop.  I was able to explore new fields of math that I never considered before and learn about topics that I had no idea even existed. As a Biomathematics major, I found the topic of using data to derive decisions in healthcare intriguing since it is an application of my major that I was not aware of. Another wonderful aspect of the workshop was the chance to speak to people in different fields. During lunch, I had the opportunity to speak to a post-doc fellow and during dinner, I spoke to one of the professors that gave a lecture earlier in the day; these opportunities don’t come along every day. It was enjoyable hearing their stories and being able to have a casual conversation with them. The panel made up of current graduate students and post-docs was also helpful in that they were able to share their experiences about graduate school and offer along any advice. I found it particularly helpful since one of the speakers was currently in a biomathematics program and I was able to ask questions I had about my major.

However, the best part of the workshop, in my opinion, was being to meet other students. Coming from a university with a smaller math department, I really enjoyed meeting students from around the country with interests similar to my own. It was great being able to make connections with students in different fields and from universities from all over. Overall, I had a wonderful time meeting new people and exploring different fields of mathematics during the workshop and found this to be a great experience.”

SAMSI DDDHC Workshop: My experience

The following blog entry is from John Olaomi, Associate Professor from the University of South Africa. He recently attended the Data-Driven Decisions in Healthcare Opening Workshop.

John Olaomi

John Olaomi, Associate Professor from U. of South Africa and guest blogger.

In my quest for knowledge and international exposures into the current trend in statistics and its applications, I first got in contact with SAMSI in 2007, responding to the 2008-2009 Postdoc position request, thanks to Google Search.  I was invited to participate in 2008-2009 Workshop on Sequential Monte Carlo Methods but could not, due to last minute funding challenges.  Since then, I have always been notified about all SAMSI programs.

The Data-Driven Decisions in Healthcare (DDDHC) opening workshop was another opportunity to participate in SAMSI programs, which I eventually succeeded with, thanks to the funding from my institution, the University of South Africa. From the organization to the execution and the forming of working groups, the workshop was a real success.  The tutorials and the technical sessions were informative, practical and posed many relevant research challenges which is really worth coming for.  Meeting erudite scholars and colleagues (both academic and professional) that can contribute to one’s academic prowess is priceless.

people looking at a poster

There was a poster session and reception held Monday night for the DDDHC opening workshop.

Technically, the expositions on Comparative Effectiveness Research (CER)- Observational Studies, Patient Flow, Personalized Healthcare and Healthcare Databases really opened my eyes to many applications and the need for statisticians to be at the forefront to achieving the healthcare goals.  Although the presentations were good, my expectations were that a lot of methodological issues (with Statistical and Operations Research perspectives) will be raised and tackled.  This was lacking, as virtually all presentations were like 80 percent healthcare issues and 20 percent (statistical or operations research) methodology, which I think should be vise-versa. This is necessary to avoid errors of the third kind: the error committed by giving the right answer to the wrong problem (Kimball, 1957).

In all, I think my trip really worth it. Thanks to SAMSI for the opportunity and the good facilitation.

Olaomi, John. O. (PhD)
Associate Professor
Department of Statistics,
University of South Africa (UNISA)
P. O. Box 392 UNISA 0003
Pretoria, South Africa

Data-Driven Decisions in Healthcare – An Overview of the Opening Workshop

The following is from Ray Falk, from OptInference LLC, who participated in the opening workshop for SAMSI’s Data-Driven Decisions in Healthcare program.

Ray Falk looking at Banafsheh Behzad’s poster as she explains the research she is doing at the Data-Driven Decisions in Healthcare Opening Workshop.

I found the kick-off workshop, Data-Driven Decisions in Healthcare, tightly focused on methodologically tractable projects with ‘shovel-ready’ data sources, primarily in the areas of operational patient, provider, and (material) resource allocation and scheduling and patient-centered (personalized) effectiveness assessment.

Avi Mandelbaum

Avi Mandelbaum of Technion gave a lecture at the opening workshop.

Inference, analysis and control of service systems were developed via extension of existing results and observations from call center management (Avi Mandelbaum), including stabilization of performance under time-varying conditions (Yunan Liu).  Prodigiously comprehensive tracking of patient flows through the ICU (Carri Chan) and the remaining non-intensive departments of a hospital (Jim Dai) were related to specific insights regarding options for intervention (including proportional and absolute threshold effects), both for providers and patients.  An interesting discussion addressed dependence of service times on (new vs. readmitted) patient status (Guodong Pang).

Bob Obenchain

Bob Obenchain at the poster session Monday evening.

Personalized medicine was addressed from several perspectives, including heterogeneous treatment effects (with a heuristic re-sampling based approaches from Bob Obenchain and Sheldon Jacobson), appropriately targeted decision analysis based on high-dimensional modeling from large populations (centered on ROC curves from validation data sequestered from model development), and availability of comprehensive data, as well as methodologies for data acquisition and alignment, inference, and modeling(OMOP) (David Madigan, Patrick Ryan) .  Assessment and prediction from retrospective observational studies and tracking data was addressed via meta-analysis, propensity matching or weighting, and spontaneous event reporting (with no identifiable population at risk) (Alan Menius)

Guidance and policy for the national initiative in patient-centered evidence-based assessment of medical effectiveness was addressed via standards elaborated via PCORI (Constantine Gatsonis, Sally Morton).  Issues and perspectives included:
Value of Information for  prioritization, Efficiency of adaptive experimental design, individually heterogeneous treatment effects, observational vs. prospective randomized trials, data infrastructure (storage of electronic records and ontologies for integrated access), and technology assessment and dissemination, hyper-inclusive access to results for review (beyond standard publications in English).  An auxiliary resource is the Society for Medical Decision Making (Turgay Ayer).

– Ray Falk