Recommended Diuretic Causes More Side Effects than Similar Hypertension Drug, Per Recent LEGEND Study
Chlorthalidone, the guideline-recommended diuretic for lowering blood pressure, causes more serious side effects than hydrochlorothiazide, a similarly effective diuretic, according to a recent OHDSI study. The findings, published in JAMA Internal Medicine, contrast with current treatment guidelines recommending chlorthalidone over hydrochlorothiazide.
The researchers found that patients taking chlorthalidone had nearly three times the risk of developing dangerously low levels of potassium and a greater risk of other electrolyte imbalances and kidney problems compared with those taking hydrochlorothiazide. Information from the largest individual database studied by the team revealed that 6.3% of patients treated with chlorthalidone experienced hypokalemia (low blood potassium), compared with 1.9% of patients who were treated with hydrochlorothiazide.
“Doctors prescribing chlorthalidone should monitor for certain side effects in their patients,” says George Hripcsak, MD, MS, chair and Vivian Beaumont Allen Professor of Biomedical Informatics at Columbia University and lead author of the study.
The prevalence of electronic healthcare data allows researchers the opportunity to study the effects of medical treatments. However, confidence in the results of such observational research is typically low, for example, because different studies on the same question often produce conflicting results, even when using the same data. We need to answer the question “to what extent can we trust observational research?”
Led by Martijn Schuemie, OHDSI researchers recently published “How Confident Are We About Observational Findings in Healthcare: A Benchmark Study” in the Harvard Data Science Review to tackle this important issue. This paper presents the OHDSI Methods Benchmark to evaluate five methods commonly used in observational research (new-user cohort, self-controlled cohort, case-control, case-crossover, and self-controlled case series designs) over a network of four large databases standardized to the OMOP Common Data Model.
Using both negative and positive controls (questions where the answer is known), a set of metrics and open-source software tools developed within the OHDSI community, the research team determined that most commonly used approaches to effect-estimation observational studies are falling short of expected confidence levels. Selection bias, confounding, and misspecification are among the sources of systematic error that plagues the validity of potentially important findings within the healthcare community.
When Dani Prieto-Alhambra discussed the Oxford Study-A-Thon at the 2019 U.S. Symposium, he introduced his talk as the “conversion of himself and 30-35 colleagues to the OMOP Common Data Model and to the OHDSI way of doing things.”
After sharing the incredible research that would eventually lead to a published study in The Lancet Rheumatology, he didn’t wait long to welcome new converts to the OHDSI community. Prieto-Alhambra coordinated the 2020 Barcelona Study-A-Thon on rheumatoid arthritis (RA); you can read the OHDSI release about the event here.
He recently discussed several aspects of the study-a-thon with OHDSI.org, and he also touched on the 2020 OHDSI European Symposium, which will be held March 27-29 at Oxford. Abstracts for the Symposium are due Friday, Feb. 14; more information on abstract submission and other areas of participation is available here.
The OHDSI community has been a proud collaborator with the European Health Data & Evidence Network (EHDEN) since the EHDEN launch in 2018. An IMI 2 consortium, EHDEN looks standardize more than 100 million patient records across Europe from different geographic areas and different data sources over the coming five years. Mapping of healthcare data to the OMOP-CDM will facilitate the re-use for a variety of purposes, enhancing and accelerating research and healthcare decision-making for global benefit. To this end, EHDEN will create an SME eco-system in Europe that supports data sources and other stakeholders in mapping and using data.
EHDEN recently announced that it has launched the second open call for SMEs to apply for training and certification to convert health data from various formats to the OMOP common data model. This second open call will run throughout the month of February, concluding on the 29th (17:00 CET).
If this prospect interests you, visit the EHDEN open call for SMEs page for more details and to submit your application. The EHDEN Consortium is looking forward to your potential application and to collaborate with you.
Invested Stakeholders, OHDSI Tools/Practices Drive Successful Rheumatoid Arthritis Study-A-Thon In Barcelona
One year after a similar study-a-thon at Oxford resulted in a knee replacement study published by The Lancet Rheumatology, 40 stakeholders from across industry, academia, and health systems — representing 10 different nations and 14 observational databases — gathered to participate in a OHDSI-EHDEN Study-a-thon and run the world’s largest network studies on Rheumatoid Arthritis (RA).
The Study-a-thon was held at the Barcelona Biomedical Research Park Jan. 13-17 and focused on three areas during the five-day gathering: (1) characterizing drug treatment patterns; (2) developing a population-level effect estimation, examining the comparative safety of first-line Disease Modifying Anti Rheumatic Drugs (DMARDs) for safety profiles and multiple adverse outcomes; and (3) creating a patient-level prediction analysis to determine high-risk RA patients for specific adverse outcomes. The OHDSI-EHDEN community conducted observational analyses across a secure, distributed network of electronic health records and insurance claims data, collectively representing more than 1.1 million patients with RA.
“It was an honor to collaborate with so many leaders in the battle against RA, and I truly believe we made a meaningful difference within one week,” said Patrick Ryan. “I am continually amazed at what can be accomplished when you combine invested stakeholders and high-level analytic tools in an open-science setting.”
As an associate professor at Erasmus Medical Center, Peter Rijnbeek appreciates the importance of a strong, effective educational program. He has been pleased with the early progress of the EHDEN Academy, a program that should provide a broad impact for the OHDSI community once it becomes publicly available in early 2020.
The EHDEN Academy, an E-learning environment developed by the EHDEN (European Health Data & Evidence Network) Consortium, was initially developed to educate SMEs (Small and Medium Enterprises) about the tools and best practices used by both EHDEN and OHDSI. There are five training courses Rijnbeek and his EHDEN colleagues felt would provide a baseline of knowledge needed to certify a support network to map a growing set of European databases to the OMOP common data model.
Book Of OHDSI, Now Available In English/Korean Versions, Provides Central Knowledge Repository For Collaborators
One memorable moment (during a day full of them) at the 2019 OHDSI U.S. Symposium came during Martijn Schuemie’s talk on best practices within the community. With a significant number of first-timers in the Bethesda North Marriott ballroom that day, Schuemie may have caused a moment of panic for some by noting all the different locations collaborators could search to follow the preferred OHDSI methods. The panic quickly turned to celebration.
The unveiling of The Book of OHDSI at the 2019 U.S. Symposium was the culmination of months of community work, and it serves to provide the community with a central knowledge repository for all aspects of OHDSI. Twenty chapters within five sections (the OHDSI Community, Uniform Data Representation, Data Analytics, Evidence Quality, and OHDSI Studies) were written to empower any new researcher with the ability to generate real-world evidence to improve the healthcare community.
While OHDSI collaborators continue to seek new and innovative ways to train the growing community in the tools and best practices of the network, face-to-face tutorials remain an effective method for educating both newcomers and veterans. During the 2019 OHDSI U.S. Symposium, there were six tutorials held, and you can watch any or all of them now on the OHDSI YouTube channel.
Use the headline link to get access to all six tutorials, including videos, materials, information and more.
First Korea Tutorial, OHDSI Japan Formation Highlight Exciting Asian Progress Before Korea Symposium
The first official OHDSI Korea tutorial was held Oct. 23 in the Grand Ambassador Seoul, and it served as an important lead event for the upcoming OHDSI Korea Symposium, which takes place Dec. 12-14 at the Konjiam Resort in Gyeonggi-Do, Korea. The enthusiasm in the room was palpable, and the energy that has been building in Korea should lead to an exciting Symposium.
While Korea first started working with OHDSI and the OMOP Common Data Model in 2014, workshops in the country had been limited to smaller Ajou University-sessions within hospitals. This was the first event that was formalized by OHDSI collaborators and open to all. There was a heavy morning focus on how to run a network study, which followed an OHDSI Introduction by Mui Van Zandt.
The first-ever OHDSI block of the CS6440 course at Georgia Tech, held over a six-week span this past fall, was both educational and inspiring, and it reinforced the strengths that have carried OHDSI from concept to major player in the real-world analytics ecosystem.
The professor felt it from the students, but he felt it himself as well.
Jon Duke, MD, MS, an OHDSI veteran who collaborated on the LEGEND hypertension study published recently in Lancet, is Director of Health Informatics at Georgia Tech, home of the largest computer science graduate program in the nation. When he took over the Intro to Health Informatics course in 2018, he decided to introduce population-level analytics to a rising generation of data scientists.
EHDEN Knee Replacement Study Results Published In Lancet Rheumatology; OHDSI Tools, Collaborators Helped Lead Important Study
The IMI European Health Data & Evidence Network (EHDEN) project is pleased to announce the publication of the results of its first ‘study-a-thon’ in Lancet Rheumatology the effectiveness and safety associated with unicompartmental versus total knee replacement, a milestone after its first year.1
The choice of which type of knee replacement to recommend remains difficult for surgeons, and there remains insufficient information to inform them and patients of the best approach, dependent on the patient’s personal context.
Researchers associated with the Observational Health Data Sciences and Informatics (OHDSI) network and EHDEN met in Oxford for five days in December 2018 to design, analyze and draft a report of the study results. The resulting study emulated to the extent possible, the design of the five year Total or Partial Knee Arthroplasty Trial (TOPKAT). The study-a-thon assessed whether the efficacy results seen in the trial translated into effectiveness in real-world settings and provided further consideration of safety outcomes that were too uncommon to assess in TOPKAT.
Thiazide diuretics demonstrate better effectiveness and cause fewer side effects than ACE inhibitors as first-line antihypertensive drugs, according to a report published Oct. 24 in The Lancet. The study factors insurance claim data and electronic health records from 4.9 million patients across nine observational databases, making it the most comprehensive one ever on first-line antihypertensives, and it provides additional context to the 2017 guidelines for high blood pressure treatment developed by the American College of Cardiology (ACC) and American Heart Association (AHA).
Collaborators in the Observational Health Data Sciences and Informatics (OHDSI) network produced the paper “Comprehensive comparative effectiveness and safety of first-line antihypertensive drug classes: a systematic, multinational, large-scale analysis” as part of the collaborative’s ongoing Large-Scale Evidence Generation and Evaluation across a Network of Databases (LEGEND) project, which applies high-level analytics to perform observational research on hundreds of millions of patient records within OHDSI’s international database network.
OHDSI researchers believe LEGEND will continue to significantly enhance how real-world evidence is used to study important healthcare questions that impact millions of patients worldwide.
There were more than 80 research highlights presented during the Collaborator Showcase at the 2019 OHDSI U.S. Symposium. For those who couldn’t attend, or who want to check out all the OHDSI innovations over the last year, you’ll have your chance on the OHDSI Twitter and LinkedIn platforms. Each weekday, a different poster will be highlighted with an individual URL. You’ll be able to check out the poster, as well as other materials the author may have included (abstract, software demo, lightning talk, etc.).
Martijn Schuemie, PhD, took the stage at the 2019 OHDSI U.S. Symposium and laid out a collection of internet locations where potential collaborators could learn about the tools and best practices developed within the community. To an audience that included about 200 first-time attendees, it must have been a daunting moment.
That feeling wouldn’t last long, as Schuemie followed by reaching under a white cover and pulling out the first version of the Book of OHDSI, the product of a year-long collaborative effort within the community to provide the best documentation for all aspects of OHDSI. Twenty chapters within five sections (the OHDSI Community, Uniform Data Representation, Data Analytics, Evidence Quality, and OHDSI Studies) were written to empower any new researcher with the ability to generate real-world evidence to improve the healthcare community.
For those who didn’t attend the Symposium, the Book of OHDSI is available here as HTML, as well as EPUB and PDF (click the small download icon at the top). Anybody who wants an actual copy of the book can order it through Amazon at cost price.
The fifth annual OHDSI Symposium was a tremendous success. From the insightful talks and impressive poster presentations on Monday to the spectacular Women in Real-World Analytics Leadership Forum and the six tutorials, there is no shortage of important material that is now available from this event (including videos of all speeches and tutorials, as well as slides from the presentations). The page also includes video and photo recaps from the weekend, as well as the virtual collaborator showcase, which highlights more than 80 posters and software demos from the event.
Using real-world evidence to meaningfully impact the healthcare community will be the prevailing theme Sept. 15-17 during the 5th annual OHDSI U.S. Symposium. Collaborators from around the world will discuss both the direction of the OHDSI community, as well as some of its most important research achievements of the past year, in the highlight event on the OHDSI calendar.
The symposium takes place at the Bethesda North Marriott Hotel & Conference Center, and for the first time, it will include a Women in Real-World Analytics Leadership Forum, hosted Sunday night by the Women of OHDSI. This free event, which is open to all symposium attendees (you can RSVP here), will feature four prominent leaders in the real-world analytics community (Noémie Elhadad, Violanda Grigorescu, Janet Woodcock, and Joanne Waldstreicher), each of whom will share thoughts on their own journey, where they see this emerging discipline headed, and how OHDSI collaborators can improve healthcare in the future.
There has been interest recently in developing new working groups within the OHDSI community, but many have wondered what it takes to actually start a new working group. This was addressed previously in an OHDSI forum post, but we wanted to share the steps with you again.
An OHDSI working group represents a group of OHDSI collaborators who hold regular meetings with the purpose of developing shared solutions to tackle a common problem or address a knowledge/technology gap. A group of collaborators aiming to complete a network research study can be considered a study working group and are encouraged to follow these guidelines.
Constructing phenotype algorithms (PAs) is a primary method for both defining diseases and identifying subjects at risk for disease in observational research. While the role of PAs is crucial for effective, reproducible research, the ability to complete detailed PA evaluations has traditionally been limited due to both cost and efficiency.
Lead author Joel Swerdel provided a potential solution to this challenge in PheValuator: Development and evaluation of a phenotype algorithm evaluator, published in the latest issue of the Journal of Biomedical Informatics. Utilizing tools within the OHDSI Network, the research team developed a method that showed promise for reliable phenotype evaluation without reliance on manual review of patient data.
Traditional methods of identifying phenotypes over varied networks of electronic health record (EHR) databases is challenging. The recently published “Facilitating Phenotype Transfer Using A Common Data Model” paper in the Journal of Biomedical Informatics demonstrated success in creating a systematic process for sharing disease definitions—known as phenotypes—across a network using the Observational Health Data Sciences and Informatics (OHDSI) OMOP Common Data Model, which could lead to dramatic improvements in the ability to study diseases in the future.
George Hripcsak, MD, MS, the co-PI of the OHDSI Coordinating Center at Columbia University, served as lead author for a paper that demonstrated an efficient alternative to phenotype sharing that allows for rapid exchange and execution across different medical centers, improving the speed and reproducibility of the research process.
The annual OHDSI China Symposium, which took place June 27-29 at Shanghai Jiaotong University, reinforced the impressive potential of the OHDSI network via the collaboration of multiple, motivated stakeholders.
Attendees of the symposium included experts and scholars from major universities in China, medical information-related practitioners of various medical and health institutions, medical-related scientific research personnel, and workers interested in big data in the pharmaceutical industry.
The symposium led off with a pair of keynote addresses, including one entitled “FEEDERNET: Evolution of Distributed Research Network in Korea” by OHDSI collaborator Rae Woong Park. Park is a top advocate for the development of OHDSI in Korea, and his presentation helped demonstrate the unique possibilities of the network.
The boundless potential to create real-world evidence through OHDSI was demonstrated for a second time in as many weeks, as collaborators from both sides of the Atlantic met in England during the Real World Epidemiology: Oxford Summer School session.
Rijnbeek and Ryan supported the mission of OHDSI collaborator and Oxford professor Dani Prieto-Alhambra. The previous week, Rijnbeek and Ryan supported OHDSI collaborators Iannis Drakos and Ismail Gögenur during a three-day seminar for the Denmark Center for Surgical Sciences (CSS).
“It was great to have OHDSI join our summer school,” Prieto-Alhambra said. “Forty people’s jaws dropped whilst learning what can be achieved through open science, community and a common data model!”