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Get the Data You Need Via Cross -Disciplinary Conversation Alignment

Get the Data You Need Via Cross -Disciplinary Conversation Alignment. Chunhua Weng 1 , Gregory W. Hruby 1 , Sunmoo Yoon 2 , Alla Babina 1 , Feng Liu 1 , Jianhua Li 1 , David Hanauer 3

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Get the Data You Need Via Cross -Disciplinary Conversation Alignment

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  1. Get the Data You Need Via Cross-Disciplinary Conversation Alignment Chunhua Weng1, Gregory W. Hruby1, Sunmoo Yoon2, AllaBabina1, FengLiu1, JianhuaLi1, David Hanauer3 1Department of Biomedical Informatics, Columbia University, New York, NY2School of Nursing, Columbia University, New York, NY 3Department of Pediatrics, University of Michigan, Ann Arbor, MI

  2. Big Health Data

  3. Data Access for Life Scientists • Patient Privacy • Data Governance • Knowledge Gaps Data

  4. Example Data Request Forms

  5. Data Access for Life Scientists…Hard! • Vocabulary Differences • Conceptualization Discrepancies • Tacit Knowledge Gaps

  6. Related Work Hruby GW, Cimino JJ, Patel V, Weng C, Toward a Cognitive Task Analysis for Biomedical Query Mediation, Proc of 2014 AMIA Joint Summits on Translational Science, 7-11 April 2014, San Francisco, CA, in press. Hruby GW, Boland MR, Cimino JJ, Gao J, Wilcox AB, Hirschberg J, Weng C, Characterization of the Biomedical Query Mediation Process, Procof 2013 AMIA Joint Summits on Translational Science, 18-22 March 2013, San Francisco, CA, 89-93.

  7. How do researchers and query analysts negotiate data needs via email?

  8. Methods • Participants: query analysts from CUMC • A: > 10 years of experience, no MD • B: novice analyst with a non-US MD • C: 2 years of experience, no MD • Eight user-reported critical incidents, including 150 email messages • Message de-identification • Thematic analysis of dialog acts

  9. Results

  10. Themes in Dialogue Acts

  11. Top Themes Q: Query Analyst; R: Researcher; M: Manager

  12. Example Communication Patterns

  13. Aggregated Activity Transition Graph

  14. Need Clarification Example 1 Hi A…………. ………………. ……………….. ……………….. Hi Alice, Thank you very much for your help. I just want to make sure I get it right. About the code 531.9 from your list - there are fifth digits with 531.9 code (0 and 1) and non of them match your description in the list. Please look at the icd9 codes below and let me know the right ones. 531.90 GASTRIC ULCER 531.30 ACUTE GASTRIC ULCER 531.00 ACUTE GASTRIC ULCER WITH HEMORRHAGE, WITHOUT MENTION OF OBSTRUCTION 531.10 ACUTE GASTRIC ULCER WITH PERFORATION, WITHOUT MENTION OF OBSTRUCTION 531.20 ACUTE GASTRIC ULCER WITH HEMORRHAGE AND PERFORATION 531.70 CHRONIC GASTRIC ULCER 531.40 CHRONIC GASTRIC ULCER WITH HEMORRHAGE 531.50 CHRONIC GASTRIC ULCER WITH PERFORATION 531.60 CHRONIC GASTRIC ULCER WITH HEMORRHAGE AND PERFORATION 531.91 GASTRIC ULCER WITH OBSTRUCTION 531.31 ACUTE GASTRIC ULCER WITH OBSTRUCTION 531.01 AC STOMAC ULC W HEM-OBST 531.11 AC STOM ULC W PERF-OBST 531.21 AC STOM ULC HEM/PERF-OBS 531.71 CHRONIC GASTRIC ULCER WITH OBSTRUCTION 531.41 CHRONIC OR UNSPECIFIED GASTRIC ULCER WITH HEMORRHAGE, WITH OBSTRUCTION 531.51 CHRONIC OR UNSPECIFIED GASTRIC ULCER WITH PERFORATION, WITH OBSTRUCTION 531.61 CHRONIC GASTRIC ULCER WITH HEMORRHAGE, PERFORATION, AND OBSTRUCTION Thank you again. A Hi A, These are relevant codes pasted below: ICD9 codes 041.86 Helicobacter pylori 151.0-151.9 Malignant neoplasm of stomach 209.23 Malignant Carcinoid Tumor of the Stomach 211.1 Benign neoplasm of stomach 230.2 Carcinoma in situ of stomach 235.2 Neoplasm of uncertain behavior of stomach, intestines, and rectum 531.9 Gastric ulcer unspecified 536.8 Unspecified functional disorder of stomach 537.9 Unspecified disorder of stomach and duodenum These are the CPT codes we need: 43620 43621 43622 43631 43632 43633 43634 43999 44238 49329

  15. Need Clarification Example 2 Hi A…………. ………………. ……………….. ……………….. Hi, >> Age 18 is the current age or diagnosis age? >> Do you care about which diagnosis is made first? I filed the discovery request today. I am requesting 2 lists of MRNs that meet the criteria below. LIST 1 Population: adults aged 18 years or older Date range: 1992-present Inclusion criteria: ICD 079.5, OR 079.53, OR 795.71, OR 042, OR 043, OR 044, AND ICD 155.0, OR 230 Data elements requested: Date of birth Age sex race/ethnicity

  16. Need Clarification Example 3 Hi A…………. ………………. ……………….. ……………….. I will double check. It is not 'primary', I will correct it. Then exclude V24.6 and <15. Then exclude ICU only patients, if I can find a way. By the way, I used 'age<18' according to your request doc. You prefer 15 instead? Hi A, Thanks for the data. It does seem strange to me that the numbers increase so much in 2013. Can you confirm that the numbers are indeed correct? Also, can you tell me if the diagnosis is the "primary” diagnosis or not? We are most interested in those with a primary admitting diagnosis that is one of these variables. Please also confirm that those with concomitant V24.6 are excluded and those age <15 are excluded. Thanks, Researcher

  17. Iterative Need Clarification Data Verification Sample patients Data Requests Data sample …. ….. ….. Concept Clarification Codes

  18. Length of Query Processing Time Medical knowledge may be associated with more efficient query processing

  19. Discussion

  20. Conclusions Decision support should not be just about user augmentation, but enable user engagement and shared decision making Besides alerts, reminders, information filters or summarizers, we also need better dialog-based decision support to bridge the gap between clinical researchers and Big Data

  21. Towards Dialog-based Query Support

  22. Limitations One institution Small sample Communication outside emails

  23. Thank you cw2384@columbia.edu http://people.dbmi.columbia.edu/~chw7007/ NLM R01LM009886 (Bridging the semantic gap between clinical research eligibility criteria and clinical data, PI: Weng)

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