@article {1229, title = {Data model harmonization for the All Of Us Research Program: Transforming i2b2 data into the OMOP common data model.}, journal = {PLoS One}, volume = {14}, year = {2019}, month = {2019}, pages = {e0212463}, abstract = {

BACKGROUND: The All Of Us Research Program (AOU) is building a nationwide cohort of one million patients{\textquoteright} EHR and genomic data. Data interoperability is paramount to the program{\textquoteright}s success. AOU is standardizing its EHR data around the Observational Medical Outcomes Partnership (OMOP) data model. OMOP is one of several standard data models presently used in national-scale initiatives. Each model is unique enough to make interoperability difficult. The i2b2 data warehousing and analytics platform is used at over 200 sites worldwide, which uses a flexible ontology-driven approach for data storage. We previously demonstrated this ontology system can drive data reconfiguration, to transform data into new formats without site-specific programming. We previously implemented this on our 12-site Accessible Research Commons for Health (ARCH) network to transform i2b2 into the Patient Centered Outcomes Research Network model.

METHODS AND RESULTS: Here, we leverage our investment in i2b2 high-performance transformations to support the AOU OMOP data pipeline. Because the ARCH ontology has gained widespread national interest (through the Accrual to Clinical Trials network, other PCORnet networks, and the Nebraska Lexicon), we leveraged sites{\textquoteright} existing investments into this standard ontology. We developed an i2b2-to-OMOP transformation, driven by the ARCH-OMOP ontology and the OMOP concept mapping dictionary. We demonstrated and validated our approach in the AOU New England HPO (NEHPO). First, we transformed into OMOP a fake patient dataset in i2b2 and verified through AOU tools that the data was structurally compliant with OMOP. We then transformed a subset of data in the Partners Healthcare data warehouse into OMOP. We developed a checklist of assessments to ensure the transformed data had self-integrity (e.g., the distributions have an expected shape and required fields are populated), using OMOP{\textquoteright}s visual Achilles data quality tool. This i2b2-to-OMOP transformation is being used to send NEHPO production data to AOU. It is open-source and ready for use by other research projects.

}, issn = {1932-6203}, doi = {10.1371/journal.pone.0212463}, author = {Klann, Jeffrey G and Joss, Matthew A H and Embree, Kevin and Murphy, Shawn N} } @article {986, title = {Taking advantage of continuity of care documents to populate a research repository.}, journal = {J Am Med Inform Assoc}, volume = {22}, year = {2015}, month = {2015 Mar}, pages = {370-9}, abstract = {

OBJECTIVE: Clinical data warehouses have accelerated clinical research, but even with available open source tools, there is a high barrier to entry due to the complexity of normalizing and importing data. The Office of the National Coordinator for Health Information Technology{\textquoteright}s Meaningful Use Incentive Program now requires that electronic health record systems produce standardized consolidated clinical document architecture (C-CDA) documents. Here, we leverage this data source to create a low volume standards based import pipeline for the Informatics for Integrating Biology and the Bedside (i2b2) clinical research platform. We validate this approach by creating a small repository at Partners Healthcare automatically from C-CDA documents.

MATERIALS AND METHODS: We designed an i2b2 extension to import C-CDAs into i2b2. It is extensible to other sites with variances in C-CDA format without requiring custom code. We also designed new ontology structures for querying the imported data.

RESULTS: We implemented our methodology at Partners Healthcare, where we developed an adapter to retrieve C-CDAs from Enterprise Services. Our current implementation supports demographics, encounters, problems, and medications. We imported approximately 17 000 clinical observations on 145 patients into i2b2 in about 24 min. We were able to perform i2b2 cohort finding queries and view patient information through SMART apps on the imported data.

DISCUSSION: This low volume import approach can serve small practices with local access to C-CDAs and will allow patient registries to import patient supplied C-CDAs. These components will soon be available open source on the i2b2 wiki.

CONCLUSIONS: Our approach will lower barriers to entry in implementing i2b2 where informatics expertise or data access are limited.

}, keywords = {Biomedical Research, Continuity of Patient Care, Database Management Systems, Databases as Topic, Humans, Information Storage and Retrieval, Meaningful Use, Systems Integration}, issn = {1527-974X}, doi = {10.1136/amiajnl-2014-003040}, author = {Klann, Jeffrey G and Mendis, Michael and Phillips, Lori C and Goodson, Alyssa P and Rocha, Beatriz H and Goldberg, Howard S and Wattanasin, Nich and Murphy, Shawn N} } @article {855, title = {Health care transformation through collaboration on open-source informatics projects: integrating a medical applications platform, research data repository, and patient summarization.}, journal = {Interact J Med Res}, volume = {2}, year = {2013}, month = {2013}, pages = {e11}, abstract = {

BACKGROUND: The Strategic Health IT Advanced Research Projects (SHARP) program seeks to conquer well-understood challenges in medical informatics through breakthrough research. Two SHARP centers have found alignment in their methodological needs: (1) members of the National Center for Cognitive Informatics and Decision-making (NCCD) have developed knowledge bases to support problem-oriented summarizations of patient data, and (2) Substitutable Medical Apps, Reusable Technologies (SMART), which is a platform for reusable medical apps that can run on participating platforms connected to various electronic health records (EHR). Combining the work of these two centers will ensure wide dissemination of new methods for synthesized views of patient data. Informatics for Integrating Biology and the Bedside (i2b2) is an NIH-funded clinical research data repository platform in use at over 100 sites worldwide. By also working with a co-occurring initiative to SMART-enabling i2b2, we can confidently write one app that can be used extremely broadly.

OBJECTIVE: Our goal was to facilitate development of intuitive, problem-oriented views of the patient record using NCCD knowledge bases that would run in any EHR. To do this, we developed a collaboration between the two SHARPs and an NIH center, i2b2.

METHODS: First, we implemented collaborative tools to connect researchers at three institutions. Next, we developed a patient summarization app using the SMART platform and a previously validated NCCD problem-medication linkage knowledge base derived from the National Drug File-Reference Terminology (NDF-RT). Finally, to SMART-enable i2b2, we implemented two new Web service "cells" that expose the SMART application programming interface (API), and we made changes to the Web interface of i2b2 to host a "carousel" of SMART apps.

RESULTS: We deployed our SMART-based, NDF-RT-derived patient summarization app in this SMART-i2b2 container. It displays a problem-oriented view of medications and presents a line-graph display of laboratory results.

CONCLUSIONS: This summarization app can be run in any EHR environment that either supports SMART or runs SMART-enabled i2b2. This i2b2 "clinical bridge" demonstrates a pathway for reusable app development that does not require EHR vendors to immediately adopt the SMART API. Apps can be developed in SMART and run by clinicians in the i2b2 repository, reusing clinical data extracted from EHRs. This may encourage the adoption of SMART by supporting SMART app development until EHRs adopt the platform. It also allows a new variety of clinical SMART apps, fueled by the broad aggregation of data types available in research repositories. The app (including its knowledge base) and SMART-i2b2 are open-source and freely available for download.

}, issn = {1929-073X}, doi = {10.2196/ijmr.2454}, author = {Klann, Jeffrey G and McCoy, Allison B and Wright, Adam and Wattanasin, Nich and Sittig, Dean F and Murphy, Shawn N} }