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Welcome to OHDSI! - Please introduce yourself


(Maura Beaton) #1

Welcome to the OHDSI community! If you’re new to OHDSI (or even a seasoned OHDSI Olympian :trident:) I invite you to:

  1. Introduce yourself and tell us a bit about what you do
  2. Let us know how you’d like to help out in the community (ex. software development, run studies, write research papers, etc)

Since I started this thread, I’ll go first:

For those of you who don’t know me, my name is Maura Beaton and I’m the OHDSI project manager. My role is largely to coordinate community activities, keep on top of collaboration opportunities and help new members get acquainted with the community. Someday I hope to become all-knowing and able to answer any and every question you have about OHDSI :slight_smile:

I work out of the OHDSI Coordinating Center which is located at Columbia University in New York. When I’m not busy with OHDSI, I’m on a never-ending quest to find the best poutine in the city (because I’m also Canadian :maple_leaf:). I also enjoy traveling and discovering new cultures, so I’m very excited to hear from you and learn more about our growing international community!


Hello from Paolo Eusebi!
(Patrick Ryan) #2

This is a great idea Maura, and I hope everyone else will participate so we
can get to know each other better.

I’m Patrick Ryan. My day job is as Senior Director and Head, Epidemiology
Analytics at Janssen Research and Development. There, my job is to help
our company analyze observational data to answer questions about disease
natural history, treatment utilization, and the effects of the medical
products in our portfolio. At Janssen, we license many different
de-identified patient-level observational datasets (administrative claims,
electronic health records, national surveys, clinical registries), and our
strategy for achieving our mission is to transform every database to the
OMOP common data model and to adopt the use of OHDSI’s open-source tools as
the foundation for our evidence generation process.

In terms of how I’d like to help the OHDSI community: I really like to
design and rapidly prototype novel analytical solutions (both back-end
statistical modeling and front-end interactive visualizations) that can
meet specific evidence needs that I see within my company and across the
community. I can hack SQL and a little R, but my team will be the first to
tell you that while my ideas are occasionally good, my code is generally
always bad (even still, there’s a few lines of code lurking in some of the
OHDSI apps that I can still lay credit to:)). Increasingly, I am
motivated to see our OHDSI tools be applied directly to real and relevant
research questions, so we don’t fall into the common informatics trap of
expecting ‘if we build it, they will come’, so you’ll probably see me
encouraging us to push through more OHDSI network research studies that
leverage our OHDSI tools to generate evidence reliably and efficiently.

When I’m not OHDSI’ing, I like to hang out with my wife and cats, golf, and
search for new hoppy beverages.


(Brandon Ulrich) #3

Hi all,

I’m Brandon Ulrich, the Managing Director of B2i Healthcare. a boutique software engineering firm specialized in SNOMED CT and healthcare information standards and exchange. Our Snow Owl technology family is deployed in over 3,000 locations in 84+ countries worldwide and used by IHTSDO to release the international version of SNOMED CT. IHTSDO members have been creating SNOMED-based drug catalogs and extensions, like the Singapore Drug Dictionary, the Dictionary of Medicines and Devices (dm+d, UK), and the Australian Medicines Terminology. As their national health records are being encoded with these dictionaries, it makes it interesting to us from an analytics perspective.

We have an online OHDSI terminology browser [1] that also allows creating cohorts using OHDSI and various extensions of SNOMED. The online synthetic patient data was created from OSIM2 in the OMOP days. The tool allows publishing Spark-based analyses of CDM data using Scala and R.

In my spare time, I enjoy traveling and hiking in Austria with my wife and dog. I live mostly in Budapest, Hungary and Würzburg, Germany but come from the US state of the World’s Only Corn Palace.

Thank you all for the great work that you do. Patrick and friends, I will gladly buy a round of your favorite hoppy beverages in thanks.

[1] https://mq.b2i.sg


(Taylor Delehanty) #4

Hi everyone,

I’m Taylor Delehanty and I’m currently a rising senior at Colorado College majoring in Computer Science. I have been working for Dr. Lisa Schilling at University of Colorado - Anschutz Medical Campus this past summer, with most of my attention directed toward creating database scripts in PostgreSQL.

In the near future I hope to help out the community by helping others understand more about OHDSI. In the far future, I hope to be a programmer so that I may be able to help in any way possible with development.

So far, I’ve loved working with this community and have found it to be a very positive experience getting to learn from all of you and your work. Thank you!


(Christian Reich) #5

Friends:

I’m Christian Reich. I have been with OMOP and OHDSI since 2009, which is ages by now. I also have a day job: VP of Real World Evidence Solutions at IMS. We are building tools for pharmaceutical clients that analyze our data assets in the various countries, mostly in the commercial setting. All of them will be convereted to OMOP CDM, and hopefully at that point they can contribute directly to the OHDSI research agenda.

Other than that: I have been involved in defining the CDM and building the Vocabularies and Code Mappings from the beginning. It’s not glamourous work, but it is the necessary foundation for everything else. So, I am still very enthusiastic in doing it. OMOP, and now OHDSI, is a rare example of an intitiative where everybody comes together purely for the joy of doing something right, and cool. There is no money in it, really. That nicely separates the wheat from the chaff, and here I got to know the nicest and most impressive people in my career.

Yes, hoppy beverages are good, also grape-based ones. I have learned a lot about the former from working wtih Patrick et al. :smile:


(Nigam Shah) #6

Nigam Shah, relatively new to the fold compared to Patrick and Christian.
My day and night job is to figure out ways of learning from aggregate
patient data (hopefully at the bedside someday …
http://greenbutton.stanford.edu). For most analyses done with OHDSI data,
you’ll find me asking how does knowing the result of the analysis change
practice :-).

I know nothing about hoppy or grape beverages but can still be friends with
the OHDSI gang!


(Rkboyce) #7

Hi, Richard (Rich) Boyce here. My main research interest is on how to improve the safety of medication therapies for older adults. Older patients have a greater number of health concerns and receive much more medication therapy than younger adults. This means that there tends to be very little evidence to guide their therapy and help them avoid adverse events. I study how to take knowledge from semantic resources and evidence from aggregate patient data and put it to work for these patients. Within the OHDSI community, I lead the Knowledge Base workgroup and a network study.


(Anthony Sena) #8

Hi All - my name is Anthony Sena and I’m a new member of Patrick’s Epidemiology Anlaytics team at Janssen R&D and the OHDSI community. As Patrick mentioned, our team is focused on the transformation of data to the OMOP common data model and to ensure that the OHDSI open-source tools are capable of helping our broader team to generate the evidence they need to do their jobs.

I plan to help the OHDSI community by contributing to the open-source projects on GitHub. My goal is to make these tools capable of helping to answer the scientific questions posed by the contributors in this network.I’m very excited to have the opportunity to work and learn with all of you through this journey.

When I’m not hacking code, I like to spend time with my wife, twin girls and our cats (although the cats aren’t always eager to spend time with me). I enjoy golfing and watching football (Go Giants) - with or without a hoppy beverage.


(Erica Voss) #9

Hi, I’m Erica Voss and I work for @Patrick_Ryan at Janssen R&D. As he already mentioned above our roles are to help the organization use observational data to understand our medical products both pre and post market. I am also a PhD student at Erasmus MC working with @Rijnbeek, @schuemie, and Johan van der Lei. I’ve worked on taking Erasmus MC’s IPCI medical record data and converting it to the CDM with @mdewilde. For my PhD I’m also working on LAERTES with @rkboyce (an many other OHDSI collaborators) which pulls evidence about adverse events of drugs from a variety of sources together and standardizes them on the OMOP Vocabulary standard terminologies (RxNorm/SNOMED). Through my research I hope to continue to look for ways to pull expert knowledge together in order to inform epidemiology/observational research.

When not busy with Janssen, Erasmus, or OHDSI, I have a husband, 2-year-old son, and 2 cats to attend to, I pretend that I do crossfit, and enjoy a good cup of coffee or great glass of wine.


(Jon Duke) #10

Great idea, Maura! I have seen interest in OHDSI from so many different corners that it helps to hear what has brought everyone to the table.

So first, hello to everyone I haven’t met. My name is Jon Duke and I am an internal medicine physician and researcher in medical informatics at a not-for-profit healthcare research organization called the Regenstrief Institute in Indianapolis. Note, there is no correct pronunciation for Regenstrief. Long e, short e, hard g, soft g, you can’t go wrong. So don’t hesitate to come visit for fear of pronunciation challenges.

Regenstrief does a lot of cool stuff that I sadly cannot take credit for-- such as LOINC and OpenMRS. We spend a lot of time thinking about health care data, how to make it better and how to deliver it to healthcare providers in useful ways.

My particular work centers around drug safety, which requires something of a holistic approach. By that I mean, even good evidence usually has minimal impact on provider decision-making due to longstanding challenges of information overload, poor specificity of recommendations, opaque outcome definitions, UI/UX problems, and other stuff that keeps informaticians busy at conferences. I’ve tried to come at these issues from both the data side (modeling, phenotypes, NLP) and the human side (HCI, provider behavior). Still have a long way to go on both, but OHDSI reflects the amazing potential of diverse talents to tackle big, seemingly intractable problems in healthcare through a strong common foundation.

So yes, I’d be ultimately psyched to see OHDSI be a standard for generating transparent, reproducible, high-quality evidence that actually succeeds in influencing decision-making around drug prescribing. But I also look forward to the many smaller steps along the way that will help people better capture, understand, and apply their healthcare data towards important problems.

Thanks,

Jon


(Martijn Schuemie) #11

Hi all, I’m Martijn Schuemie (I have zero expectations of correct pronounciation of my name). I’m in the team of @Patrick_Ryan at Janssen R&D, and I’m currently on assignment at the University of Hong Kong. My main interest is in developing (statistical) methods for learning from observational data. Together with @msuchard I ‘lead’ the OHDSI estimation methods workgroup, and write a lot of the OHDSI Methods Library. But to enable methods research we need a good foundation, so I often find myself working on converting data to the Common Data Model as well.

OHDSI for me means working together with clever people on hard problems that make a difference. I hope that my contributions help get real value out of observational data and helps improve health care and health in general. (I must confess I’m a bit of a sceptic when it comes to the current value coming out of observational research).

When not working I hang out with wife and 2-year-old daughter (who currently claims to be a space ranger), and like to sail. I sometimes pretend to play golf.


(Brian S) #12

Hi everyone, I’m Brian Sauer, and I self identify as a pharmacoepidemiologist with some training in informatics and a special affinity for theoretical foundations of causal inference. I was involved in the original OMOP methods development but we unfortunately didn’t get our method to scale up in time to participate in the primary evaluation. I want to find my place in OHDSI but am a couple paces behind and slightly out of synch but remain persistent.

Most of my work is at the SLC VA where I am involved in some of the OMOP data conversion and development of our own interpretation of drug safety and CER database analytic workflows that we call Transparent ReUsable Statistical Tools (TRUST). Redirecting inertia from our original TRUST plans has not been easy for my team but we are trying to find our place within OHDSI.

We have develop deep appreciate for Patrick, Martijn and others who work in the community and look forward to a more complementary relationship. We are specifically interested in weighting techniques to deal with confounding and selection bias for fixed and time-varying treatment effects. We hope to work with Martijn and others on these issues once we complete our obligations to review and improve the data quality problems around VHA CDW transformation to the OMOP CDM.

Wonderful advancements are happening in this community and I would enjoy participating in more theoretical work (journal clubs and simulation) that are directly translated into applied technology, such as the cohort method and other inference and prediction technology. I would also like to participate in more training on how to effectively use OMOP vocabulary tools for applied research. Our OMOP/OHDSI work is coming together at the VA thanks to folks like Michael Matheny, Fern Fitzhenry and Scott DuVall and I look forward to deep integration with VA operations and research.

When not working I enjoy recreational activities typical of the mountain west with my wife and 2 young ones.

Some of our work is available on Research Gate: https://www.researchgate.net/profile/Brian_Sauer2

This may be a bad idea but for those who really want to know who I am you can find me on FB - maybe we need an OHDSI FB page: https://www.facebook.com/brian.sauer.520


(Mark Danese) #13

I am Mark Danese. My background is in Biostatistics (MHS) and Epidemiology (PhD) from Johns Hopkins University. I run a small consulting company called Outcomes Insights based on Southern California. @aguynamedryan, @jenniferduryea, @mlgleeson are all part of OI. We do a lot of observational data analyses. We also simulation modeling for health economics, and epidemiological simulations (e.g., estimating fractures prevented in the US if we could achieve perfect compliance with bisphosphonates).

About 2 years ago, we decided to improve the process of conducting studies using observational data, and started developing an tool for building entire studies that we call Jigsaw, where one could choose from stored algorithms to identify research concepts of interest (e.g., defining an MI using claims data) and incorporate them directly into a study using a very flexible framework. To really make that work, we needed a common data model, and the OMOP model really fit the bill. While our approach to building studies is slightly different from the OHDSI approach, we share the same desire to create tools to abstract away the tedious, repetitive tasks with building studies, and making things better for researchers.

To this end, we are leading the Medicare ETL working group (v5) and have contributed to some of the recent updates to Rabbit-in-a-Hat. Like Christian says, some of this stuff is boring, but somebody has to do it to make the world a better place. (Though I have to say that Christian’s job with the vocab is infinitely more complicated.)

We are also developing the ETL for SEER data with the National Cancer Institute. Eventually, we will have the ETL ready for the SEER Medicare merged data.

Being in California, I tend to favor red wine. And I am a runner who might try a marathon early next year in Napa.


(George Hripcsak) #14

Hi, all. I am George Hripcsak, a professor of biomedical informatics at Columbia University. I have been working on observational research methods for over 20 years, focused on defining phenotypes and on applying machine learning methods, and I also oversee the team that runs the clinical data warehouse for my institution. I became hooked on OHDSI (then OMOP) when a new and seemingly complicated idea was implemented by Patrick Ryan, Paul Stang, and David Madigan over a weekend–data, code, visualization, everything–and I thought, wow, I need to work with these guys. I have recently been working to facilitate OHDSI’s evolution by having Columbia serve as a coordinating center, mainly for those things that cannot be done so easily on a voluntary basis. OHDSI is an amazing group of people, both during and after work.

George


(William Stephens) #15

HI all, I’m Bill Stephens. I am Director of IT for Paxata, a Silicon Valley company that provides a data preparation solution leveraging several big data technologies for SAAS or on-premises deployment. My team develops the “Library” components, which serve as the interface to all external data sources and provide data management for imported client data, 3rd party lookup data and generated data sets. I’ve performed some preliminary work using our product for medical data and intend to push for expansion into the medical domain.

In several years of previous work, I spent considerable time working on ETL and federated data sharing solutions for Ohio State and Signet Accel, much focusing on the OMOP data models.

In my “night job”, I’m pursuing my MS in Public Health specializing in Biomedical Informatics at Ohio State in order to tie together my BS Human Nutrition and BS Computer Science degrees. It is in this student role that I intend to focus most of my OHDSI efforts. My thesis activities are focused on the data elements coverage and the computation complexity of implementing NQF measures and PheKB phenotyping algorithms against a set of public Outcomes-oriented data models.

I would like to become involved in any OHDSI group involved in the implementation of measures software as well as continuing to remain involved in OMOP development, where possible.

For me time, I enjoy guitar, growing things (grapes, hops, apples…), smoking meats and providing transportation to my children.

Bill


(Clair Blacketer) #16

Hi, I’m Clair Blacketer and I am a new addition to the Janssen R&D team working for @Patrick_Ryan and @ericaVoss. Prior to joining Janssen I spent some time at a regional health system here in Virginia as well as a large national insurer in their Medicare division. I am very excited to be part of the OHDSI community because it is such a unique approach to the challenge of utilizing different datasets. My current goal is to continue to work with the CDM as much as I can so I can apply that learning back to the community in a meaningful way.

In my downtime I enjoy spending time at the beach with my husband and dog Lollipop.


(Maura Beaton) #17

(Mary Regina Boland) #18

Hi all,

In case I have not met you already, my name is Mary Regina Boland and I am a biomedical informatics PhD student at Columbia University. My work focuses on developing novel and interesting data mining methods that use electronic health records, observational health data and genetic data, and basically any data I can get my hands on. My primary interest is in integrating different types of data to find interesting results.

My current work focuses on the relationship between environment and disease, especially in the developmental setting. Because developmental environment can be hard to study in adult populations, I use birth-related data (such as birth month) as a proxy for the environment at birth (perinatal) and prior to birth (prenatal).

Because electronic health records can also be difficult and cumbersome to use my interests in the OHDSI community also involve developing methods that are shareable across the consortium and also enable data sharing.

I look forward to meeting those that I have not met and working more closely with you all.

Thanks,
~Mary


(Dino Gambone) #19

Hello everyone,

My name is Dino Gambone, and I’m a Director of Software Development within the Real-World Evidence Solutions organization at IMS Health, Inc. I’m a Director by title, but Developer by trade. I actually report to Christian Reich (introduced above) and am very new to OHDSI and OMOP. I manage the US-based development efforts around RWE and OMOP, which includes developing applications (.NET based) and performing OMOP conversions. My background is in enterprise-level web applications and very large data sets.

I’m quite new to this work of OHDSI and OMOP so right now I’m here to be a sponge, learn what I can from the wealth of knowledge this community has, and offer up any general technical support/ideas that I can. Hopefully I can offer more as I get more familiar and comfortable with the topics over time.


(Hillel R. Alpert, ScD) #20

Hello Everyone. I am delighted to join the OHDSI community. Thank you very much Maura Beaton for her most helpful orientation call. By way of introduction, I am a a public health scientist with a 20+ year career conducting studies and investigations that have supported the development of national policies and programs and advanced public health science. My aims and and interests are closely aligned with those of OHDSI, particularly with respect to maximizing the sharing, utility and value of health data to improve quality of care and medical practices, ideally within the construct of a learning health care system. I come with a solid track record of peer-reviewed publications and presentations at national / international scientific meetings with areas of scientific focus that have included health policy, medical ethics, population and social science, tobacco and other substances abuse, and regulatory science. Areas of technical specialization are study design and research methodology, surveillance and sruvey methodology, epidemiology, statistical analysis, regulatory sciences, decision sciences.


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