A survey of informatics platforms that enable distributed comparative effectiveness research using multi-institutional heterogenous clinical data

Medical Care

Volumn 50, Issue SUPPL. 1, 2012, Pages

  Sittig, Dean F ^a   Hazlehurst, Brian L ^b   Brown, Jeffrey ^c   Murphy, Shawn ^d   Rosenman, Marc ^e   Tarczy Hornoch, Peter ^f   Wilcox, Adam B ^g  

^a UNIVERSITY OF TEXAS   (United States)

^b CENTER FOR HEALTH RESEARCH   (United States)

^c HARVARD PILGRIM HEALTH CARE INSTITUTE   (United States)

^d PARTNERS HEALTHCARE   (United States)

^e INDIANA UNIVERSITY SCHOOL OF MEDICINE   (United States)

^f UNIVERSITY OF WASHINGTON   (United States)

^g Och Spine at New York Presbyterian Hospitals   (United States)

Author keywords

Comparative effectiveness research; Medical informatics; Methods; Organization and administration

Indexed keywords

ARTICLE; CLINICAL STUDY; COMPARATIVE EFFECTIVENESS; CONTROLLED STUDY; DATA ANALYSIS; DATA EXTRACTION; ELECTRONIC MEDICAL RECORD; HEALTH CARE; HEALTH CARE QUALITY; HEALTH SURVEY; HUMAN; INFORMATION DISSEMINATION; INFORMATION PROCESSING; INFORMATION TECHNOLOGY; INTEGRATED HEALTH CARE SYSTEM; MEDICAL INFORMATICS; MEDICAL INFORMATION; MULTIHOSPITAL SYSTEM; ORGANIZATION AND MANAGEMENT; PRIORITY JOURNAL;

COMPARATIVE EFFECTIVENESS RESEARCH; DATA COLLECTION; HUMANS; MEDICAL INFORMATICS; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; OUTCOME AND PROCESS ASSESSMENT (HEALTH CARE); QUALITY ASSURANCE, HEALTH CARE; QUALITY IMPROVEMENT; REGISTRIES; UNITED STATES;

EID: 84862279410     PISSN: 00257079     EISSN: 15371948     Source Type: Journal    
DOI: 10.1097/MLR.0b013e318259c02b     Document Type: Article

References (34)

1. The American Recovery and Reinvestment Act of 2009. Public Law 111-5. Available at: http://www.gpo.gov/fdsys/pkg/PLAW-111publ5/pdf/PLAW-111publ5.pdf. Accessed February 17, 2009.
2. VanLare JM, Conway PH, Rowe JW. Building academic health centers' capacity to shape and respond to comparative effectiveness research policy. Acad Med. 2011;86:689-694.
3. Stang PE, Ryan PB, Racoosin JA, et al. Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership. Ann Intern Med. 2010;153:600-606.
4. Ohno-Machado L, Bafna V, Boxwala AA, et al, and the iDASH team iDASH: integrating data for analysis, anonymization, and sharing. J Am Med Inform Assoc. 2012;19:196-201.
5. Behrman RE, Benner JS, Brown JS, et al. Developing the Sentinel System-a national resource for evidence development. N Engl J Med. 2011;364:498-499.
6. Payne P, Ervin D, Dhaval R, et al. TRIAD: The Translational Research Informatics and Data management grid. Appl Clin Inf. 2011;2:331-344.
7. Greene SM, Hart G, Wagner EH. Measuring and improving performance in multicenter research consortia. J Natl Cancer Inst Monogr. 2005;35:26-32.
8. Toh S, Platt R, Steiner JF, et al. Comparative-effectiveness research in distributed health data networks. Clin Pharmacol Ther. 2011;90:883-887.
9. Hornbrook MC, Hart G, Ellis JL, et al. Building a virtual cancer research organization. J Natl Cancer Inst Monogr. 2005;35:12-25.
10. Brown JS, Holmes JH, Shah K, et al. Distributed health data networks: a practical and preferred approach to multi-institutional evaluations of comparative effectiveness, safety, and quality of care. Med Care. 2010;48(suppl 1):S45-S51.
11. Hazlehurst B, Frost HR, Sittig DF, et al. MediClass: a system for detecting and classifying encounter-based clinical events in any electronic medical record. J Am Med Inform Assoc. 2005;12:517-529. (Pubitemid 41215621)
12. Murphy SN, Gainer VS, Chueh H. A visual interface designed for novice users to find research patient cohorts in a large biomedical database. AMIA Annu Symp Proc. 2003:489-493. Available at: www. ncbi.nlm.nih.gov/pmc/articles/ PMC1480150/pdf/amia2003-0489.pdf. Accessed May 4, 2012.
13. Murphy SN, Weber G, Mendis M, et al. Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2). J Am Med Inform Assoc. 2010;17:124-130.
14. Overhage JM, Tierney WM, McDonald CJ. Design and implementation of the Indianapolis Network for Patient Care and Research. Bull Med Libr Assoc. 1995;83:48-56.
15. McDonald CJ, Overhage JM, Barnes M, et al. INPC Management Committee. The Indiana network for patient care: a working local health information infrastructure. An example of a working infrastructure collaboration that links data from five health systems and hundreds of millions of entries. Health Aff (Millwood). 2005;24:1214-1220.
16. Zhu VJ, Tu W, Rosenman MB, et al. Facilitating clinical research through the health information exchange: lipid control as an example. AMIA Annu Symp Proc. 2010;2010:947-951.
17. McDonald CJ, Huff SM, Suico JG, et al. LOINC, a universal standard for identifying laboratory observations: a 5-year update. Clin Chem. 2003;49:624-633. (Pubitemid 36382924)
18. Sittig DF, Singh H. A new socio-technical model for studying health information technology in complex adaptive healthcare systems. Qual Saf Healthc. 2010;19(suppl 3):i68-i74.
19. Health & Human Services Research Awards: Use of Recovery Act and Patient Protection and Affordable Care Act Funds for Comparative Effectiveness Research. U.S. Government Accountability Office, Washington, D.C.; June 14, 2011. Available at: http://www.gao.gov/new.items/d11712r.pdf. Accessed May 4, 2012.
20. Tatonetti NP, Denny JC, Murphy SN, et al. Detecting drug interactions from adverse-event reports: interaction between paroxetine and pravastatin increases blood glucose levels. Clin Pharmacol Ther. 2011;90:133-42. doi: 10.1038/clpt.2011.83. [Epub 2011 May 25].
21. Kurreeman F, Liao K, Chibnik L, et al. Genetic basis of autoantibody positive and negative rheumatoid arthritis risk in a multi-ethnic cohort derived from electronic health records. Am J Hum Genet. 2011;88:57-69.
22. CHAPTER 4: VIRTUAL DATA WAREHOUSE (VDW) In Collaboration Toolkit: A guide to multicenter research in the HMO Research Network. 2011. Available at: www.hmoresearchnetwork.org/resources/toolkit/HMORN-CollaborationToolkit.pdf#4.
23. Friedman C, Shagina L, Lussier Y, et al. Automated encoding of clinical documents based on natural language processing. J Am Med Inform Assoc. 2004;11:392-402. (Pubitemid 39220799)
24. Baorto D, Li L, Cimino JJ. Practical experience with the maintenance and auditing of a large medical ontology. J Biomed Inform. 2009;42: 494-503.
25. Zeng QT, Goryachev S, Weiss S, et al. Extracting principal diagnosis, comorbidity and smoking status for asthma research: evaluation of a natural language processing system. BMC Med Inform Decis Mak. 2006;6:30.
26. Perlis RH, Iosifescu DV, Castro VM, et al. Using electronic medical records to enable large-scale studies in psychiatry: treatment resistant depression as a model. Psychol Med. 2012;42:41-50. [Epub 20 June 2011].
27. Friedlin J, McDonald CJ. Using a natural language processing system to extract and code family history data from admission reports. AMIA Annu Symp Proc. 2006:925.
28. HMO Research Network Collaboration Toolkit. Available at: http://www.hmoresearchnetwork.org/resources/collab-toolkit.htm.
29. CERHUB Mission and Membership Overview. Available at: http://www.cerhub.org/mission.html.
30. AHIMA, Fundamentals for Building a Master Patient Index/Enterprise Master Patient Index (Updated), J AHIMA. Available at: http://library.ahima.org/ xpedio/groups/public/documents/ahima/bok1-048389. hcsp?dDocName = bok1-048389. Accessed September 2010.
31. Adragna L. Implementing the enterprise master patient index. J AHIMA. 1998;69:46-48, 50, 52.
32. McDonald CJ, Overhage JM, Tierney WM, et al. The Regenstrief medical record system: a quarter century experience. Int J Med Inform. 1999;54:225-253. (Pubitemid 29276954)
33. Friedman CP, Wong AK, Blumenthal D. Achieving a nationwide learning health system. Sci Transl Med. 2010;2:57cm29.
34. Regulatory changes in advanced notice of proposed rulemaking: comparison of existing rules with some of the changes being considered. Available at: http://www.hhs.gov/ohrp/humansubjects/anprmchangetable. html. Accessed September 13, 2011.