A vision for the systematic monitoring and improvement of the quality of electronic health data

Studies in Health Technology and Informatics

Volumn 192, Issue 1-2, 2013, Pages 884-888

  Dixon, Brian E ^a,b,c   Rosenman, Marc ^b,d   Xia, Yuni ^e   Grannis, Shaun J ^b,d  

^a Indiana University   (United States)

^b REGENSTRIEF INSTITUTE   (United States)

^c VETERANS AFFAIRS MEDICAL CENTER   (United States)

^d INDIANA UNIVERSITY   (United States)

^e PURDUE UNIVERSITY   (United States)

Author keywords

Information Storage and Retrieval; Medical Informatics; Medical Records Systems, Computerized; Quality Control; Quality Improvement

Indexed keywords

CONTROLLED DRUG DELIVERY; DATA REDUCTION; DIGITAL STORAGE; MEDICAL INFORMATION SYSTEMS; POPULATION STATISTICS; QUALITY CONTROL;

BIOMEDICAL INFORMATICS; HEALTHCARE ORGANIZATIONS; INFORMATION AND COMMUNICATION; INFORMATION STORAGE AND RETRIEVAL; LARGE SCALE REPOSITORIES; MEDICAL INFORMATICS; MEDICAL RECORDS SYSTEMS , COMPUTERIZED; QUALITY IMPROVEMENT;

SEARCH ENGINES;

ELECTRONIC MEDICAL RECORD; HEALTH CARE QUALITY; INFORMATION RETRIEVAL; PROCEDURES; STANDARDS; TOTAL QUALITY MANAGEMENT; UNITED STATES;

INFORMATION STORAGE AND RETRIEVAL; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; QUALITY ASSURANCE, HEALTH CARE; QUALITY IMPROVEMENT; UNITED STATES;

EID: 84894380909     PISSN: 09269630     EISSN: 18798365     Source Type: Book Series    
DOI: 10.3233/978-1-61499-289-9-884     Document Type: Conference Paper

References (30)

1. Rao SR, Desroches CM, Donelan K, Campbell EG, Miralles PD, Jha AK. Electronic health records in small physician practices: Availability, use, and perceived benefits. J Am Med Inform Assoc. 2011;18(3):271-5.
2. Jha AK, Burke MF, DesRoches C, Joshi MS, Kralovec PD, Campbell EG, et al. Progress toward meaningful use: Hospitals' adoption of electronic health records. Am J Manag Care. 2011;17(12 Spec No.):SP117-24.
3. Lewis T, Synowiec C, Lagomarsino G, Schweitzer J. E-health in low-and middle-income countries: Findings from the center for health market innovations. Bull World Health Organ. 2012;90(5):332-40.
4. Schoen C, Osborn R, Squires D, Doty M, Rasmussen P, Pierson R, et al. A survey of primary care doctors in ten countries shows progress in use of health information technology, less in other areas. Health Aff. 2012.
5. Kaelber DC, Foster W, Gilder J, Love TE, Jain AK. Patient characteristics associated with venous thromboembolic events: A cohort study using pooled electronic health record data. J Am Med Inform Assoc. 2012;19(6):965-72.
6. Comer KF, Grannis S, Dixon BE, Bodenhamer DJ, Wiehe SE. Incorporating geospatial capacity within clinical data systems to address social determinants of health. Public Health Rep. 2011;126 Suppl 3:54-61.
7. Shah NH. Translational bioinformatics embraces big data. Yearb Med Inform. 2012;7(1):130-4.
8. Ohno-Machado L. Big science, big data, and a big role for biomedical informatics. J Am Med Inform Assoc. 2012;19(e1):e1.
9. Institute of Medicine. Digital infrastructure for the learning health system: The foundation for continuous improvement in health and health care: Workshop series summary. Washington, D.C.: The National Academies Press; 2011.
10. Wang RY, Strong DM. Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems. 1996;12(4):5-34.
11. Batini C, Cappiello C, Francalanci C, Maurino A. Methodologies for data quality assessment and improvement. ACM Comput Surv. 2009;41(3).
12. Kerr KA, Norris T, Stockdale R. The strategic management of data quality in healthcare. Health Informatics J. 2008;14(4):259-66.
13. Redman TC. The impact of poor data quality on the typical enterprise. Communications of the ACM. 1998;41(2):79-82.
14. Kaboli PJ, McClimon BJ, Hoth AB, Barnett MJ. Assessing the accuracy of computerized medication histories. Am J Manag Care. 2004;10(11 Pt 2):872-7.
15. Liaw ST, Chen HY, Maneze D, Taggart J, Dennis S, Vagholkar S, et al. Health reform: Is routinely collected electronic information fit for purpose? Emergency medicine Australasia : EMA. 2012;24(1):57-63.
16. Dixon BE, McGowan JJ, Grannis SJ. Electronic laboratory data quality and the value of a health information exchange to support public health reporting processes. AMIA Annu Symp Proc. 2011;2011:322-30.
17. McGinnis KA, Skanderson M, Levin FL, Brandt C, Erdos J, Justice AC. Comparison of two va laboratory data repositories indicates that missing data vary despite originating from the same source. Med Care. 2009;47(1):121-4.
18. Chan KS, Fowles JB, Weiner JP. Review: Electronic health records and the reliability and validity of quality measures: A review of the literature. Med Care Res Rev. 2010;67(5):503-27.
19. Wang RY. A product perspective on total data quality management. Communications of the ACM. 1998;41(2):58-65.
20. Batini C, Barone D, Cabitza F, Grega S. A data quality metholodology for heterogeneous data. International Journal of Database Management Systems. 2011;3(1):60-79.
21. Dixon BE, Zafar A, Overhage JM. A framework for evaluating the costs, effort, and value of nationwide health information exchange. J Am Med Inform Assoc. 2010;17(3):295-301.
22. Cadieux G, Buckeridge DL, Jacques A, Libman M, Dendukuri N, Tamblyn R. Patient, physician, encounter, and billing characteristics predict the accuracy of syndromic surveillance case definitions. BMC Public Health. 2012;12:166.
23. Kirbiyik U, Gamache RE, Dixon BE, Grannis SJ, editors. Evaluating the variation on public health's perceived field need of communicable disease reports. ISDS Annual Conference; 2012; San Diego, CA: International Society for Disease Surveillance.
24. Dixon BE, Grannis S. Why asking questions about data and their sources is important to public health informatics practice and research. Online Journal of Public Health Informatics. 2011;3(3).
25. Overhage JM, Grannis S, McDonald CJ. A comparison of the completeness and timeliness of automated electronic laboratory reporting and spontaneous reporting of notifiable conditions. Am J Public Health. 2008;98(2):344-50.
26. Buehler JW, Hopkins RS, Overhage JM, Sosin DM, Tong V. Framework for evaluating public health surveillance systems for early detection of outbreaks: Recommendations from the cdc working group. MMWR Recomm Rep. 2004;53(RR-5):1-11.
27. Kass-Hout TA, Xu Z, McMurray P, Park S, Buckeridge DL, Brownstein JS, Finelli L, Groseclose SL. Application of change point analysis to daily influenza-like illness emergency department visits. J Am Med Inform Assoc. 2012;19(6):1075-81.
28. Grannis SJ, Dixon BE, Xia Y, Wu J. Using information entropy to monitor chief complaint characteristics and quality. In: Ising A, editor. ISDS Annual Conference Proceedings; San Diego, CA. 2012. p. 90.
29. Sell J, Mathes R, Paladini M. Detecting changes in chief complaint word count: Effects on syndromic surveillance. In: Ising A, editor. ISDS Annual Conference Proceedings; San Diego, CA. 2012. p. 191.
30. Painter I, Eaton J, Lober B, editors. Using change point detection for monitoring the quality of aggregate data. ISDS 2012 Conference Proceedings; 2012; San Diego, CA. p. 169.