Data standards in diabetes patient registries

Journal of Diabetes Science and Technology

Volumn 5, Issue 3, 2011, Pages 476-485

  Richesson, Rachel L ^a  

^a UNIVERSITY OF SOUTH FLORIDA   (United States)

Author keywords

Chronic disease; Controlled vocabularies; Data standards; Diabetes; Disease management (systems); Medical informatics; Patient care management; Registries

Indexed keywords

CLINICAL RESEARCH; CLINICAL TRIAL (TOPIC); CONFERENCE PAPER; CONSENSUS; DIABETES MELLITUS; DIABETIC PATIENT; DISEASE REGISTRY; ELECTRONIC MEDICAL RECORD; HEALTH CARE POLICY; HUMAN; INFORMATION PROCESSING; MEDICAL INFORMATICS; PATIENT CARE; PATIENT SAFETY; PRIMARY HEALTH CARE; STANDARDIZATION; SYSTEMATIZED NOMENCLATURE OF MEDICINE; TOTAL QUALITY MANAGEMENT; ARTICLE; INFORMATION SYSTEM; METHODOLOGY; ORGANIZATION AND MANAGEMENT; PATHOLOGY; PROGRAM DEVELOPMENT; QUALITY CONTROL; RANDOMIZED CONTROLLED TRIAL (TOPIC); REGISTER; STANDARD; TRANSLATIONAL RESEARCH; UNITED STATES;

DATA COLLECTION; DIABETES MELLITUS; HUMANS; INFORMATION SYSTEMS; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; PROGRAM DEVELOPMENT; QUALITY CONTROL; RANDOMIZED CONTROLLED TRIALS AS TOPIC; REGISTRIES; TRANSLATIONAL MEDICAL RESEARCH; UNITED STATES;

EID: 84858755780     PISSN: None     EISSN: 19322968     Source Type: Journal    
DOI: 10.1177/193229681100500302     Document Type: Conference Paper

References (57)

1. Health Information Technology for Economic and Clinical Health (HITECH) Act, title XIII of division A and title IV of division B of the American Recovery and Reinvestment Act of 2009 (ARRA), Pub. L. No. 111-5 (Feb. 17, 2009).
2. Agency for Healthcare Research and Quality. Registries for evaluating patient outcomes: a user's guide. Rockville: Agency for Healthcare Research and Quality; 2010.
3. California HealthCare Foundation. Using computerized registries in chronic disease care. http://www.chcf.org/publications/2004/02/using- computerized-registries-in-chronic-disease- care. Accessed April 22, 2011.
4. Dreyer NA, Garner S. Registries for robust evidence. JAMA. 2009;302(7):790-1.
5. Stroebel RJ, Scheitel SM, Fitz JS, Herman RA, Naessens JM, Scott CG, Zill DA, Muller L. A randomized trial of three diabetes registry implementation strategies in a community internal medicine practice. Jt Comm J Qual Improv. 2002;28(8):441-50.
6. Montori VM, Dinneen SF, Gorman CA, Zimmerman BR, Rizza RA, Bjornsen SS, Green EM, Bryant SC, Smith SA; Translation Project Investigator Group. The impact of planned care and a diabetes electronic management system on community-based diabetes care: the Mayo Health System Diabetes Translation Project. Diabetes Care. 2002;25(11):1952-7. (Pubitemid 41071050)
7. F O Kern E, Beischel S, Stalnaker R, Aron DC, Kirsh SR, Watts SA. Building a diabetes registry from the Veterans Health Administration's computerized patient record system. J Diabetes Sci Technol. 2008;2(1):7-14.
8. Brooke EM. The current and future use of registers in health information systems. Geneva: World Health Organization; 1974. http://whqlibdoc.who.int/ offset/WHO-OFFSET-8.pdf. Accessed April 22, 2011.
9. Richesson RL, Lee HS, Cuthbertson D, Lloyd J, Young K, Krischer JP. An automated communication system in a contact registry for persons with rare diseases: scalable tools for identifying and recruiting clinical research participants. Contemp Clin Trials. 2009;30(1):55-62.
10. DIAMOND Project Group. Incidence and trends of childhood type 1 diabetes worldwide 1990-1999. Diabet Med. 2006;23(8):857-66.
11. EURODIAB ACE Study Group. Variation and trends in incidence of childhood diabetes in Europe. Lancet. 2000;355(9207):873-6.
12. Mayer-Davis EJ, Bell RA, Dabelea D, D'Agostino R Jr, Imperatore G, Lawrence JM, Liu L, Marcovina S; SEARCH for Diabetes in Youth Study Group. The many faces of diabetes in American youth: type 1 and type 2 diabetes in five race and ethnic populations: the SEARCH for Diabetes in Youth Study. Diabetes Care. 2009;32 Suppl 2:S99-101.
13. Green SB, Byar DP. Using observational data from registries to compare treatments: the fallacy of omnimetrics. Stat Med. 1984;3(4):361-73.
14. Miettinen OS. The need for randomization in the study of intended effects. Stat Med. 1983;2(2):267-71. (Pubitemid 13020139)
15. Goldberg J, Gelfand HM, Levy PS. Registry evaluation methods: a review and case study. Epidemiol Rev. 1980;2:210-20. (Pubitemid 11254914)
16. Bagheri A, Sadek A, Chan T, Khunti K, de Lusignan S. Using surrogate markers in primary electronic patient record systems to confirm or refute the diagnosis of diabetes. Inform Prim Care. 2009;17(2):121-9.
17. Morris AD, Boyle DI, MacAlpine R, Emslie-Smith A, Jung RT, Newton RW, MacDonald TM. The diabetes audit and research in Tayside Scotland (DARTS) study: electronic record linkage to create a diabetes register. DARTS/MEMO Collaboration. BMJ. 1997;315(7107):524-8. (Pubitemid 27359106)
18. Tang PC, Ralston M, Arrigotti MF, Qureshi L, Graham J. Comparison of methodologies for calculating quality measures based on administrative data versus clinical data from an electronic health record system: implications for performance measures. J Am Med Inform Assoc. 2007;14(1):10-5. (Pubitemid 44909490)
19. Harris SB, Glazier RH, Tompkins JW, Wilton AS, Chevendra V, Stewart MA, Thind A. Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study. BMC Health Serv Res. 2010;10:347.
20. Cronenwett JL, Likosky DS, Russell MT, Eldrup-Jorgensen J, Stanley AC, Nolan BW; VSGNNE. A regional registry for quality assurance and improvement: the Vascular Study Group of Northern New England (VSGNNE). J Vasc Surg. 2007;46(6):1093-2.
21. California HealthCare Foundation. Chronic disease registries: a product review. http://www.chcf.org/publications/2004/05/chronic-disease-registries-a- product-review. Accessed April 22, 2011.
22. Lester WT, Zai AH, Chueh HC, Grant RW. Diabetes information technology: designing informatics systems to catalyze change in clinical care. J Diabetes Sci Technol. 2008;2(2):275-83.
23. Crosson JC, Ohman-Strickland PA, Hahn KA, DiCicco-Bloom B, Shaw E, Orzano AJ, Crabtree BF. Electronic medical records and diabetes quality of care: results from a sample of family medicine practices. Ann Fam Med. 2007;5(3):209-15. (Pubitemid 46889997)
24. Richesson RL, Vehik K. Patient registries: utility, validity and inference. In: de la Paz MP, Groft SC, eds. Rare diseases epidemiology. Dordrecht: Springer; 2010, 87-140.
25. Richesson RL, Krischer J. Data standards in clinical research: gaps, overlaps, challenges and future directions. J Am Med Inform Assoc. 2007;14(6):687-96. (Pubitemid 350026419)
26. Chalmers RJ . Health care terminology for the electronic era. Mayo Clin Proc. 2006;81(6):729-31. (Pubitemid 43839486)
27. Dudeck J. Aspects of implementing and harmonizing healthcare communication standards. Int J Med Inform. 1998;48(1-3):163-71. (Pubitemid 28172024)
28. American Medical Informatics Association; American Health Information Management Association Terminology and Classification Policy Task Force. Healthcare terminologies and classifications: an action agenda for the United States. http://www.ncvhs.hhs.gov/080221p4.pdf.
29. Institute of Medicine of the National Academies. To err is human: building a safer health system. Washington DC: Institute of Medicine, National Academy of Sciences; 1999. http://www.iom.edu/Reports/1999/To-Err-is-Human- Building-A-Safer-Health-System. aspx. Accessed April 22, 2011.
30. Hammond WE, Cimino JJ. Standards in biomedical informatics. In: Shortliffe EH, Cimino JJ, eds. Biomedical informatics: computer applications in health care and biomedicine. New York: Springer; 2006, 265-311.
31. Rollason W, Khunti K, de Lusignan S. Variation in the recording of diabetes diagnostic data in primary care computer systems: implications for the quality of care. Inform Prim Care. 2009;17(2):113-9.
32. Office of Management and Budget. Revisions to the standards for the classification of federal data on race and ethnicity. Federal Register 1997. http://www.whitehouse.gov/omb/fedreg- 1997standards. Accessed April 22, 2011.
33. U.S. Food and Drug Administration. FDA resources for data standards. http://www.fda.gov/forindustry/datastandards/default.htm. Accessed December 6, 2010.
34. Healthcare Information Technology Standards Panel (HITSP); American National Standards Institute. http://www.hitsp.org/. Accessed November 23, 2010.
35. Clinical Data Standards Interchange Consortium. http://www.cdisc.org/. Accessed December 13, 2005.
36. McDonald CJ, Huff SM, Suico JG, Hill G, Leavelle D, Aller R, Forrey A, Mercer K, DeMoor G, Hook J, Williams W, Case J, Maloney P. LOINC, a universal standard for identifying laboratory observations: a 5-year update. Clin Chem. 2003;49(4):624-33. (Pubitemid 36382924)
37. Chute CG. Medical concept representation. In: Chen HC, Fuller SS, Friedman C, Hersh W, eds. Medical informatics: knowledge management and data mining in biomedicine. New York: Springer; 2005, 163-82.
38. Healthcare Information Technology Standards Panel. Clinical research interoperability specification. HITSP/IS158. http://hitsp.org/ConstructSet- Details.aspx?&PrefixAlpha=1&PrefixNumeric= 158 . Accessed April 22, 2011.
39. Public Health Data Standards Consortium. Standards for public health data exchange: functional requirements standard for diabetes care management and surveillance. http://www.phdsc.org/health-info/pdfs/Standards-for-Public-Health- PHDSC-FINAL-Report.pdf. Accessed April 22, 2011.
40. Bhatt DL. Advancing the care of cardiac patients using registry data: going where randomized clinical trials dare not. JAMA. 2010;303(21):2188-9.
41. Hendel RC, Budoff MJ, Cardella JF, Chambers CE, Dent JM, Fitzgerald DM, Hodgson JM, Klodas E, Kramer CM, Stillman AE, Tilkemeier PL, Ward RP, Weigold WG, White RD, Woodard PK; American College of Cardiology (ACC); American Heart Association (AHA). ACC/AHA/ACR/ASE/ASNC/HRS/NASCI/RSNA/SAIP/SCAI/SCCT/SCMR/SIR 2008 Key data elements and definitions for cardiac imaging a report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Clinical Data Standards for Cardiac Imaging). J Am Coll Cardiol. 2009;53(1):91-124.
42. Buxton AE, Calkins H, Callans DJ, DiMarco JP, Fisher JD, Greene HL, Haines DE, Hayes DL, Heidenreich PA, Miller JM, Poppas A, Prystowsky EN, Schoenfeld MH, Zimetbaum PJ, Heidenreich PA, Goff DC, Grover FL, Malenka DJ, Peterson ED, Radford MJ, Redberg RF; American College of Cardiology; American Heart Association Task Force on Clinical Data Standards; (ACC/AHA/HRS Writing Committee to Develop Data Standards on Electrophysiology). ACC/AHA/HRS 2006 key data elements and definitions for electrophysiological studies and procedures: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (ACC/AHA/HRS Writing Committee to Develop Data Standards on Electrophysiology). J Am Coll Cardiol. 2006;48(11):2360-96. (Pubitemid 44856764)
43. Radford MJ, Arnold JM, Bennett SJ, Cinquegrani MP, Cleland JG, Havranek EP, Heidenreich PA, Rutherford JD, Spertus JA, Stevenson LW, Goff DC, Grover FL, Malenka DJ, Peterson ED, Redberg RF; American College of Cardiology; American Heart Association Task Force on Clinical Data Standards; American College of Chest Physicians; International Society for Heart and Lung Transplantation; Heart Failure Society of America. ACC/AHA key data elements and definitions for measuring the clinical management and outcomes of patients with chronic heart failure: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Heart Failure Clinical Data Standards): developed in collaboration with the American College of Chest Physicians and the International Society for Heart and Lung Transplantation: endorsed by the Heart Failure Society of America. Circulation. 2005;112(12):1888-916.
44. Cannon CP, Battler A, Brindis RG, Cox JL, Ellis SG, Every NR, Flaherty JT, Harrington RA, Krumholz HM, Simoons ML, Van De Werf FJ, Weintraub WS, Mitchell KR, Morrisson SL, Brindis RG, Anderson HV, Cannom DS, Chitwood WR, Cigarroa JE, Collins-Nakai RL, Ellis SG, Gibbons RJ, Grover FL, Heidenreich PA, Khandheria BK, Knoebel SB, Krumholz HL, Malenka DJ, Mark DB, Mckay CR, Passamani ER, Radford MJ, Riner RN, Schwartz JB, Shaw RE, Shemin RJ, Van Fossen DB, Verrier ED, Watkins MW, Phoubandith DR, Furnelli T. American College of Cardiology key data elements and definitions for measuring the clinical management and outcomes of patients with acute coronary syndromes. A report of the American College of Cardiology Task Force on Clinical Data Standards (Acute Coronary Syndromes Writing Committee). J Am Coll Cardiol. 2001;38(7):2114-30. (Pubitemid 33116592)
45. Ahmadian L, Cornet R, Kalkman C, de Keizer NF; NVA Working Group "Minimal Dataset for Preoperative Assessment". Development of a national core dataset for preoperative assessment. Methods Inf Med. 2009;48(2):155-61.
46. Winget MD, Baron JA, Spitz MR, Brenner DE, Warzel D, Kincaid H, Thornquist M, Feng Z. Development of common data elements: the experience of and recommendations from the Early Detection Research Network. Int J Med Inform. 2003;70(1):41-8. (Pubitemid 36434341)
47. Mohanty SK, Mistry AT, Amin W, Parwani AV, Pople AK, Schmandt L, Winters SB, Milliken E, Kim P, Whelan NB, Farhat G, Melamed J, Taioli E, Dhir R, Pass HI, Becich MJ. The development and deployment of common data elements for tissue banks for translational research in cancer - an emerging standard based approach for the Mesothelioma Virtual Tissue Bank. BMC Cancer. 2008;8:91.
48. Richesson RL, Mon D, Kallem C, Gunter P. A strategy for defining common data elements to support clinical care and secondary use in clinical research. Presented at: 2010 AMIA Clinical Research Informatics Summit. http://crisummit2010.amia.org/files/symposium2008/100-richesson.pdf. Accessed April 22, 2011.
49. Health Level 7. EHR Diabetes Data Strategy. http://wiki.hl7.org/index. php?title=EHR-Diabetes-Data- Strategy. Accessed November 23, 2010.
50. Hagopian WA, Lernmark A, Rewers MJ, Simell OG, She JX, Ziegler AG, Krischer JP, Akolkar B. TEDDY - The Environmental Determinants of Diabetes in the Young: an observational clinical trial. Ann N Y Acad Sci. 2006;1079:320-6. (Pubitemid 44968741)
51. Uusitaloa U, Kronberg-Kippilab C, Aronssonc CA, Schakeld S, Schoene S, Mattissonf I, Reinivuog H, Silvish K, Sichert-Hellerti W, Stevensj M, Norrisk JM, Virtanen SM. Food composition database harmonization for between-country comparisons of nutrient data in the TEDDY Study. J Food Comp Anal. To be published.
52. Moyers S, Richesson R, Krischer J. Trans-Atlantic data harmonization in the classification of medicines and dietary supplements: a challenge for epidemiologic study and clinical research. Int J Med Inform. 2008;77(1):58-67. (Pubitemid 350161424)
53. Weykamp C, John WG, Mosca A. A review of the challenge in measuring hemoglobin A1c. J Diabetes Sci Technol. 2009;3(3):439-45.
54. Elwyn GJ, Vaughan NJ, Stott NC. District diabetes registers: more trouble than they're worth? Diabet Med. 1998;15 Suppl 3:S44-8.
55. Kallem C, Richesson R, DuLong D, Sison L, Van Dyke P, Mon DT. Advancing secondary data uses through data standards: HL7 project advances the "collect once, use many times" paradigm. J AHIMA. 2011;82(4):38-9.
56. McNamara RL, Brass LM, Drozda JP Jr, Go AS, Halperin JL, Kerr CR, Lévy S, Malenka DJ, Mittal S, Pelosi F Jr, Rosenberg Y, Stryer D, Wyse DG, Radford MJ, Goff DC Jr, Grover FL, Heidenreich PA, Malenka DJ, Peterson ED, Redberg RF; American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Data Standards on Atrial Fibrillation); American Collage of Cardiology; American Heart Association. ACC/AHA key data elements and definitions for measuring the clinical management and outcomes of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Data Standards on Atrial Fibrillation). Circulation. 2004;109(25):3223-43.
57. Hendel RC, Budoff MJ, Cardella JF, Chambers CE, Dent JM, Fitzgerald DM, Hodgson JM, Klodas E, Kramer CM, Stillman AE, Tilkemeier PL, Ward RP, Weigold WG, White RD, Woodard PK. ACC/AHA/ACR/ASE/ASNC/HRS/NASCI/RSNA/SAIP/SCAI/SCCT/ SCMR/SIR 2008 key data elements and definitions for cardiac imaging: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Clinical Data Standards for Cardiac Imaging). Circulation. 2009;119(1):154-86.