Big Bad Data: Law,Public Health,and Biomedical Databases

See, e.g., Lee L. M. and Gostin L. O. “Ethical Collection, Storage, and Use of Public Health Data: A Proposal for a National Privacy Protection” JAMA 302, no. 1(2009):82–84; O'Connor J. and Matthews G. “Informational Privacy, Public Health, and State Laws” American Journal of Public Health 101, no. 10(2011):1845–1850; Wilson A. , Note, “Missing the Mark: The Public Health Exception to the HIPAA Privacy Rule and Its Impact on Surveillance Activity” Houston Journal of Health Law & Policy 9, no. 1(2008): 131–156.

Chretien J. Tomich N. E. Gaydos J. C. and Kelley P. W. “RealTime Public Health Surveillance for Emergency Preparedness” American Journal of Public Health 99, no. 8(2009):1360–1363; Smith P. F. Hadler J. L. Stanbury M. Rolfs R. T. Hopkins R. S. , and the CSTE Surveillance Strategy Group, “Blueprint Version 2.0': Updating Public Health Surveillance for the 21st Century” Journal of Public Health Management Practice (2012) (Epub ahead of print), at 5; Klompas M. Murphy M. Lankiewicz J. McVetta J. Lazarus R. Eggleston E. Daly P. Oppendisano P. Beagan B. Kirby C. and Platt R. “Harnessing Electronic Health Records for Public Health Surveillance” Online Journal of Public Health Informatics 3, no. 3(2011): 1–7.

45 C.F.R. §170.205(c)-(e) (2011); Public Health Information Network, Meaningful Use Fact Sheet: Syndromic Surveillance, at <http://www.cdc.gov/phin/library/PHIN_Fact_Sheets/FS_MU_SS.pdf> (last visited January 9, 2013).

Cousens S. Hargreaves J. Bonell C. Armstrong B. Thomas J. Kirkwood B. R. and Hayes R. “Alternatives to Randomisation in the Evaluation of Public-Health Interventions: Statistical Analysis and Causal Inference” Journal of Epidemiology and Community Health 65, no. 7(2011):576–581; Guilbert T. W. Arndt B. Temte J. Adams A. Buckingham W. Tandias A. Tomasallo C. Anderson H. A. and Hanrahan L. P. “The Theory and Application of UW e-Health-Phinex, A Clinical Electronic Health Record-Public Health Information Exchange” Wisconsin Medical Journal 111, no. 3(2012):124–133, at 124–125; Hoffman S. and Podgurski A. “Balancing Privacy, Autonomy, and Scientific Needs in Electronic Health Records Research” SMU Law Review 65, no. 1(2012):85–144, at 97–102. The latter article discusses the benefits of observational research and its limitations compared to randomized clinical studies. See also 42 U.S.C. §1320e (2010).

Brown S. H. Fischetti L. F. Graham G. Bates J. Lancaster A. E. McDaniel D. Gillon J. Darbe M. and Kolodner R. M. “Use of Electronic Health Records in Disaster Response: The Experience of Department of Veterans Affairs After Hurricane Katrina” American Journal of Public Health 97, Supp. no. 1 (2007): S136–S141.

DeMers G. Kah C. Buono C. Chan T. Blair P. Griswold W. Johansson P. Chipara O. and Nilsson A. “Secure Scalable Disaster Electronic Medical Record and Tracking System” 2011 IEEE International Conference on Technologies for Homeland Security (HST) (2011):402–406; Levy G. Blumberg N. Kreiss Y. Ash N. and Merin O. “Application of Information Technology within a Field Hospital Deployment Following the January 2010 Haiti Earthquake Disaster” Journal of the American Medical Informatics Association 17, no. 6(2010): 626–630.

Garrett N. Mishra N. Nichols B. Staes C. Akin C. and Safran C. “Characterization of Public Health Alerts and Their Suitability for Alerting in Electronic Health Record Systems,”Journal of Public Health Management Practice 17, no. 1(2011):77–83; Lurio J. Morrison F. P. Pichardo M. Berg R. Buck M. D. Wu W. Kitson K. Mostashari F. and Calman N. “Using Electronic Health Record Alerts to Provide Public Health Situational Awareness to Clinicians” Journal of the American Medical Informatics Association 17, no. 2(2010): 217–219.

Botsis T. Hartvigsen G. Chen F. and Weng C. “Secondary Use of EHR: Data Quality Issues and Informatics Opportunities” AMIA Summits on Translational Science Proceedings 2010 (2010): 1–5.

Liaw S. T. Taggart J. Dennis S. and Yeo A. “Data Quality and Fitness for Purpose of Routinely Collected Data – A General Practice Case Study from an Electronic Practice-Based Research Network (ePBRN)” AMIA Annual Symposium Proceedings 2011 (2011):785–794, at 789; see Botsis (id.)

Kukafka R. Ancker J. S. Chan C. Chelico J. Khan S. Mortoti S. Natarajan K. Presley K. and Stephens K. “Redesigning Electronic Health Record Systems to Support Public Health” Journal of Biomedical Informatics 40, no. 4(2007): 398–409, at 405.

See Smith , supra note 2, at 5; Brunt C. S. “CPT Fee Differentials and Visit Upcoding Under Medicare Part B” Health Economics 20, no. 7(2011): 831–841.

Newgard C. D. Zive D. Jui J. Weathers C. and Daya M. “Electronic Versus Manual Data Processing: Evaluating the Use of Electronic Health Records in Out-of-Hospital Clinical Research” Academic Emergency Medicine 19, no. 2(2012): 217–227, at 225.

Diamond C. C. Mostashari F. and Shirky C. “Collecting and Sharing Data for Population Health: A New Paradigm” Health Affairs 28, no. 2(2009):454–66, at 456–457; Beasley J. W. Wetterneck T. B. Temte J. Lapin J. A. Smith P. Rivera-Rodriguez J. and Karsh B. T. “Information Chaos in Primary Care: Implications for Physician Performance and Patient Safety” Journal of the American Board of Family Medicine 24, no. 6(2011): 745–751, at 747.

Terhune C. “U.S. Pushes Healthcare Providers to Share Records Electronically” Los Angeles Times, March 10, 2012, available at <http://articles.latimes.com/2012/mar/10/business/la-fi-health-tech-20120310> (last visited January 9, 2013). Shortliffe E. H. and Cimino J. J. , eds., Biomedical Informatics: Computer Applications in Health Care and Biomedicine (New York: Springer, 2006): at 952 (defining interoperability).

Chute C. G. “Medical Concept Representation” in Chen H. Fuller S. S. Friedman C. and Hersh W. , eds., Medical Informatics: Knowledge Management and Data Mining in Biomedicine (New York: Springer-Verlag 2005): at 170; Gold M. R. McLaughlin C. G. Devers K. J. Berenson R. A. and Bovbjerg R. R. “Obtaining Providers'‘Buy-In’ and Establishing Effective Means of Information Exchange Will Be Critical to HITECH's Success” Health Affairs 31, no. 3(2012): 514–526, at 519.

Ahern J. Hubbard A. and Galea S. “Estimating the Effects of Potential Public Health Interventions on Population Disease Burden: A Step-by-Step Illustration of Causal Inference Methods” American Journal of Epidemiology 169, no. 9(2009):1140–1147; see Cousens , supra note 4.

Faigman D. Blumenthal J. Cheng E. K. Mnookin J. L. Murphy E. E. and Sanders J. , Modern Scientific Evidence: The Law and Science of Expert Testimony (Minnesota: Thomson Reuters/West, 2011): at §5:16, pp, 281–282.

Greenland S. “Quantifying Biases in Causal Models: Classical Confounding vs. Collider-Stratification Bias” Epidemiology 14, no. 3(2003): 300–306, at 306.

See Beasley , supra note 13, at 747; Faigman , supra note 17, at §5:10, at 277; Hammer G. P. Prel J. B. du and Blettner M. “Avoiding Bias in Observational Studies” Deutsches Ärzteblatt International 106, no. 41(2009): 664–668, at 665.

Turner K. and Ferland L. “State Electronic Disease Surveillance Systems – United States, 2007 and 2010” Morbidity and Mortality Weekly Report 60, no. 41(2011):1421–1423, at 1421; Rolka H. Walker D. W. English R. Katzoff M. Scogin G. and Neuhaus E. “Analytical Challenges for Emerging Public Health Surveillance” Morbidity and Mortality Weekly Report 61, Supp. (2012): 35–39, at 36.

Sachdeva S. and Bhalla S. “Semantic Interoperability in Standardized Electronic Health Record Databases” Association for Computing Machinery Journal of Data and Information Quality 3, no. 1(2012):1–1:37, at 1:5.

Optum, A CIO Survey of HIT Adoption Trends, An Optum Institute Survey Brief (2012), available at <http://institute.optum.com/research/featured-publications/cio-survey-of-hit-adoptiontrends/∼/media/OptumInstitute/Page_Elements/Articles/OPTUM_CIO_HIT_Survey_Feb2012.pdf> (last visited January 9, 2013).

Klompas M. McVetta J. Lazarus R. Eggleston E. Haney G. Kruskal B. A. Yih W. K. Daly P. Oppendisano P. Beagan B. Lee M. Kirby C. Heisey-Grove D. DeMaria A. and Platt R. “Integrating Clinical Practice and Public Health Surveillance Using Electronic Medical Record Systems” American Journal of Preventive Medicine 42, no. 6, Supp. 2 (2012): S154–S162. The ESP platform “automatically execute[s] complex disease-detection algorithms to provide meaningful surveillance without requiring clinicians to manually parse potential cases.” Id., at S154.

Kahn M. G. Raebel M. A. Glanz J. M. Riedlinger K. and Steiner J. F. “A Pragmatic Framework for Single-Site and Multisite Data Quality Assessment in Electronic Health Record-Based Clinical Research” Medical Care 50, Supp. (2012): S21–S29.

Pearl J. , Causality, 2d ed. (New York: Cambridge University Press, 2009): at 65–68; VanderWeele T. J. and Staudt N. C. “Causal Diagrams for Empirical Legal Research: Methodology for Identifying Causation, Avoiding Bias, and Interpreting Results” Law, Probability and Risk 10, no. 4(2011): 329–354.