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characteristic of BOS or (d) parenchymal disease (PD)characteristic of infection (Figure). Spatial information isretained allowing for visualization and quantification ofdisease within individual lobes. The relative volumes foreach classification are determined by normalizing the sumof all voxels within a particular class to the total lungvolume. Using HRCT, broncho-alveolar lavage (BAL) andspirometry data, 55 SCT recipients were classified into oneof 3 groups: A) Infection, no BOS (n¼11); B) BOS, noinfection (n¼34); and C) BOS + Infection (n¼9). BAL wereperformed within 1 week of the HRCT, in all 55 patients.Mean values (�SE) for functional small airway disease(fSAD), parenchymal (infectious) disease (PD), and normallung parenchyma were determined for each group(Figure).Results: Distinct imaging profiles were identified for pa-tients with BOS and for patients with an acute infectiouspneumonitis. In particular, the %fSAD was significantlygreater in patients with BOS when compared to those withinfection alone, 38�2% vs 17�4%, p¼0.05. There was nodifference in the %fSAD for subjects with BOS, whether aconcurrent infection was present or not, 35�3% (BOS) vs38�2% (BOS + Infection), p¼31. Patients with an acute in-fectious pneumonitis had significantly higher levels of PDthan patients with BOS, 30�4% vs 17�1.5%. In 7 of the 34(21%) BOS cases, significant increases in fSAD (>30%) werepresent when radiographic features characteristic for BOS(air trapping, bronchiectasis, septal lines) were either ab-sent or minimal on HRCT. There were no differences inPRM imaging by the type of infection. PRM provides amajor advance in our ability to diagnose small airwayobstruction that characterizes BOS, even in the presence ofan active pulmonary infection. A prospective trialcomparing PRM with spirometry and standard HRCT as anearly indicator of BOS is planned.

CRA -DATA MANAGEMENT

313Transplant Center Survey of CIBMTR Internal AssessmentsNicolette Maria Minas, Kathleen Ruehle. Greenebaum CancerCenter, University of Maryland, Baltimore, MD

Background: The University of Maryland Blood and MarrowTransplant (BMT) team has firmly established a culture ofcontinuous quality improvement to assure the utmost ac-curacy of CIBMTR data. In early 2012, Minas and Ruehle

reported the significance of auditing 10 commonly useddata points. In early 2013, Minas and Ruehle set out tofurther improve CIBMTR data accuracy by combining theiroriginal set of commonly used data points with 19 addi-tional ones.Methods: To explore the internal assessments (IA) auditactivities used by other transplant centers to ensureCIBMTR data accuracy, the University of Maryland BMTteam developed an anonymous survey consisting of 6quantitative and 3 qualitative questions. One hundred andthirty seven NMDP (National Marrow Donor Program) andCIBMTR (Center for International Blood and MarrowTransplant Research) affiliated transplant centers (TC) wereinvited to participate. The survey was administered usingSurvey Monkey.Results: A total of 86 (62.8%) responses were received. Ofthese, 57% were from centers that transplanted over 100patients per year. Most TC (89%) performed some type of IAfor their CIBMTR forms. Centers reported that IA were mostoften conducted by a quality assurancemanager (46%). Of theTC that performed IA, 76% reported using FACT (Foundationfor the Accreditation of Cellular Therapy) and additional datapoints as opposed to only FACT data points. Fifty-six percentof TC that conducted IA reported that audits were performedon 10%-30% of patient data on a regular basis, while another19% reported performing IA for 100% of patient data. Internalassessments were most commonly performed on a quarterlybasis (35%).Conclusion: Most TC participate in some sort of IA. Themajority of TC perform IA using FACT and additional datapoints, which likely improves accuracy of the data. Althoughtime is a consideration, completing 100% IA assures the mostaccurate data. Surveys such as these provide us withknowledge of how all transplant centers assure qualityCIBMTR data and prepare for external audits, such as CIBMTRand FACT.

N.M. Minas, K. Ruehle. CIBMTR Monthly Internal Assess-ment Improves Quality of Registry Data. Biology of Bloodand Marrow Transplantation. Volume 18, Issue 2, Supple-ment, Page S239, February 2012 [abstract].

N.M. Minas, K. Ruehle. A Culture of Continuous QualityImprovement Improves Registry Data. Biology of Blood andMarrow Transplantation. Volume 19, Issue 2, Supplement,Pages S169-S170, February 2013 [abstract].

314Extending the Bridg Model with Hematopoietic CellTransplant ConceptsJane Pollack 1, Kirt Schaper 2, Robinette Renner 3,Charles Martinez 4, Sandra Sorensen 5, Bob Milius 6,Colleen O’Neill 7, Roy B. Jones 8, J. Douglas Rizzo 9.1 Bioinformatics Research, CIBMTR/Minneapolis Campus,Minneapolis, MN; 2 CIBMTR - Minneapolis, Minneapolis, MN;3 CIBMTR IT, CIBMTR/Minneapolis Campus, Minneapolis, MN;4M.D. Anderson Cancer Center, Houston, Texas; 5 ResearchOperations, CIBMTR - Minneapolis, Minneapolis, MN;6 Bioinformatics Research, NMDP, Minneapolis, MN; 7NationalMarrow Donor Program, CIBMTR/Minneapolis Campus,Minneapolis, MN; 8 Stem Cell Transplantation & CellularTherapy, UT M.D. Anderson Cancer Center, Houston, TX;9 CIBMTR, CIBMTR/Medical College of Wisconsin, Milwaukee,WI

Organizing data into coherent groups, i.e. data domains, iskey to understanding relations between complex subjectareas such as information collected around one simple

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hematopoietic cell transplant (HCT) event. Multiplying thisby the number of transplants that are part of the CIBMTROutcomes Research Database underlines the need forstructures that document this ’data about data’ (Metadata).The difficulty is showing how the complete set of dataaround a transplant event is connected in a way thattranscends the collection method, i.e. form. Our aim was todemonstrate that a domain-driven architecture aligns withthe forms-based model, and eases the introduction ofcollecting more data about HCT transplant events. TheBiomedical Research Integrated Domain Group (BRIDG)model is publically available. The goal of BRIDG group is tohave a common view of the data exchanged for semanticinteroperability. The BRIDG model is intended to balancethe concerns of the larger health care community, whilebeing specific enough to apply to a particular subject areasuch as HCT. We extracted all Common Data Elements(CDEs) for all CIBMTR-mandated forms and associated eachelement to one of three contexts, Recipient, Donor andstem-cell product; most elements were in the Recipientcontext. Because no element could be described in isola-tion, instance diagrams were created to describe how onesimple concept needed multiple BRIDG entities to be fullydescribed. Some CDEs were described as relationshipsbetween entities rather than an attribute of an entity. Weextended the generic BRIDG model to contain all identifiedelements. To this end, we requested the expansion of theBRIDG model to include a ’PerformedSubstanceExtraction’entity at the same level of inheritance as ’Perform-edSubstanceAdministration’. While the collection of astem-cell product could have been described in the contextof a ’Product’ and a ’SpecimenCollection’, the richness ofthe relationship between a Donor and a Recipient wouldnot have been as obvious. This as well as other enhance-ments to the BRIDG model were included in BRIDG version3.2. With this effort, we have documented each data point(CDE) collected on all the CIBMTR-mandated forms and therelationships between them. We intend to use the UMLBRIDG model with the added HCT content as the specifi-cation for a physical database model. This physical modelwill help remove barriers that transplant centers experi-ence in electronic transfer of HCT data to the Stem CellTransplant Outcomes Database by providing a foundationupon which to develop their own in-house data systems,and eventual development of Electronic Medical Record(EMR) integration engines to submit data to the OutcomesDatabase.

315BMT Physician-Research Coordinator Relationships:Fostering Reciprocal CommunicationJason D. Sabo 1, Joshua Workman 1, Melissa Yurch 1,Donna Abounader 1, Patti Baucco 1, Sharisa Cross 1,Tanya Rodela 1, Andrea Urbanek 1, Matt E. Kalaycio 2.1 Department of Hematologic Oncology and Blood Disorders,Cleveland Clinic Taussig Cancer Institute, Cleveland, OH; 2 BMTProgram, Cleveland Clinic Foundation, Cleveland, OH

Background: Interpersonal communication is an intangible- and often overlooked - barrier to data management anderror reduction. Reporting to the Center for InternationalBlood and Marrow Transplant Research (CIBMTR) and in-ternal databases requires comprehensive data manage-ment techniques e including communication processes.Facilitation of interpersonal communication among clinicalteams has become increasingly important in healthcaredue to potentially adverse outcomes of a communication

failure (see Leonard, Graham, & Bonacum, 2004; Marshal,Harrison, & Flanagan, 2009; Propp et. al, 2010) Sutcliffe,Lewton, & Rosenthal, 2004). A poor BMT Physician-research coordinator relationship may result in closedcommunication, a lack of transparency throughout theclinical team, and insufficient data collection and reportingto CIBMTR. Thus, we recommend actions targeted atremoving barriers to reciprocal physician-coordinatorcommunication.Methods targeting improved communication: (a.) Physi-cian Sign-off: physician-reviewed data verification encour-ages open discussion and review of essential CIBMTR dataprior to transplant; (b.) Rounding: opportunities to attend in-patient rounds with the entire clinical team increases coor-dinator knowledge base and permits a transparent view ofthe continuum of care. (c.) Research Nurse Relationships:highly-accessible and responsive nurses serve as key liaisonsbetween coordinators and the clinical team; (d.) DiseaseIn-service & Education: small group continuing educationsessions allow teaching moments between physicians andcoordinators; (e.) Direct and Real-Time communication:reducing hierarchical barriers allows any team member todirectly contact/speak to a physician or use electroniccommunication to share patient status updates (e.g., re-lapses, deaths); (f.) Team Engagement Events: social eventsencourage networking and relationship development (e.g.,NMDP Be the Match - Toss the boss, Leukemia & LymphomaSociety, and after work events).Future: Interpersonal communication is essential to ourgood clinical practices and embedded in our standardoperating procedures. Removing communication barriersand improving relationships has been a critical successfactor for our team. Our objective is to continue identifyingcommunication failures while maintaining reciprocal re-lationships e particularly during times of turnover andtransition.

316Novel Electronic Data Capture Tool Is More Time Efficientfor Adverse Event (AE) Capture and ReportingHannah E. Spencer 1, Sean Graves 2, Amy Lankford 3,Diana Farrell 3, Theresa Altherr 4, Carlos G. Lee 5,Amer Beitinjaneh 1, Leonid Volodin 4, Amy K. Camblos 6,Tamila L. Kindwall-Keller 1. 1 Hematology Oncology, Universityof Virginia School of Medicine, Charlottesville, VA; 2 PublicHealth Sciences, University of Virginia, Charlottesville, VA;3 Cancer Center Office of Clinical Research, University ofVirginia, Charlottesville, VA; 4 Hematology Oncology,University of Virginia, Charlottesville, VA; 5 Stem CellTransplant Program, University of Virginia, Charlottesville, VA;6 School of Medicine Clinical Trials Office, University ofVirginia, Charlottesville, VA

Background: AE capture and reporting is one of the mosttime-consuming activities related to the conduct of he-matopoietic stem cell transplant (HSCT) clinical trials, withsome trials requiring hundreds of AEs to be captured andsummarized for reporting. To improve the AE reportingprocess, our HSCT Program collaborated with the Univer-sity of Virginia Biomedical Informatics Division of thePublic Health Sciences Department to develop a novelelectronic data capture tool. The purpose of this study wasto evaluate the tool’s efficiency and identify areas forimprovement.Methods: The electronic tool was designed to be quick,simple to use, and easy to deploy. Microsoft Excel array for-mulas were used, allowing a calculation to be carried out