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  2020 (11)
Serres and Foundations. Lehtonen, T. Theory, Culture & Society, 37(3): 3–22. May 2020.
Serres and Foundations [link]Paper   doi   bibtex   abstract  
Situated data analysis: a new method for analysing encoded power relationships in social media platforms and apps. Rettberg, J. W. Humanities and Social Sciences Communications, 7(1): 5. December 2020.
Situated data analysis: a new method for analysing encoded power relationships in social media platforms and apps [link]Paper   doi   bibtex  
Physician code creep after the initiation of outpatient volume control program and implications for appropriate ICD-10-CM coding. Liang, F.; Wang, L.; Liu, L.; Li, C. Y.; and Lu, T. BMC Health Services Research, 20(1): 127. December 2020.
Physician code creep after the initiation of outpatient volume control program and implications for appropriate ICD-10-CM coding [link]Paper   doi   bibtex  
How accurate is the medical record? A comparison of the physician’s note with a concealed audio recording in unannounced standardized patient encounters. Weiner, S. J; Wang, S.; Kelly, B.; Sharma, G.; and Schwartz, A. Journal of the American Medical Informatics Association, 27(5): 770–775. May 2020.
How accurate is the medical record? A comparison of the physician’s note with a concealed audio recording in unannounced standardized patient encounters [link]Paper   doi   bibtex   abstract  
Impact of the introduction and withdrawal of financial incentives on the delivery of alcohol screening and brief advice in English primary health care: an interrupted time–series analysis. O'Donnell, A.; Angus, C.; Hanratty, B.; Hamilton, F. L.; Petersen, I.; and Kaner, E. Addiction, 115(1): 49–60. January 2020.
Impact of the introduction and withdrawal of financial incentives on the delivery of alcohol screening and brief advice in English primary health care: an interrupted time–series analysis [link]Paper   doi   bibtex  
Research and Reporting Considerations for Observational Studies Using Electronic Health Record Data. Callahan, A.; Shah, N. H.; and Chen, J. H. Annals of Internal Medicine, 172(11_Supplement): S79–S84. June 2020.
Research and Reporting Considerations for Observational Studies Using Electronic Health Record Data [link]Paper   doi   bibtex  
Prospecting (in) the data sciences. Slota, S. C; Hoffman, A. S; Ribes, D.; and Bowker, G. C Big Data & Society, 7(1): 205395172090684. January 2020.
Prospecting (in) the data sciences [link]Paper   doi   bibtex  
Book Review: Automated Media. Rettberg, J. W. Convergence: The International Journal of Research into New Media Technologies,135485652090661. February 2020.
Book Review: Automated Media [link]Paper   doi   bibtex  
Platform Capitalism’s Hidden Abode: Producing Data Assets in the Gig Economy. Doorn, N.; and Badger, A. Antipode,anti.12641. June 2020.
Platform Capitalism’s Hidden Abode: Producing Data Assets in the Gig Economy [link]Paper   doi   bibtex  
Everyday curation? Attending to data, records and record keeping in the practices of self-monitoring. Weiner, K.; Will, C.; Henwood, F.; and Williams, R. Big Data & Society, 7(1): 205395172091827. January 2020.
Everyday curation? Attending to data, records and record keeping in the practices of self-monitoring [link]Paper   doi   bibtex   abstract  
Wild data: how front‐line hospital staff make sense of patients’ experiences. Montgomery, C. M.; Chisholm, A.; Parkin, S.; and Locock, L. Sociology of Health & Illness, 42(6): 1424–1440. July 2020.
Wild data: how front‐line hospital staff make sense of patients’ experiences [link]Paper   doi   bibtex  
  2019 (6)
How precision medicine and screening with big data could increase overdiagnosis. Vogt, H.; Green, S.; Ekstrøm, C. T.; and Brodersen, J. BMJ,l5270. September 2019.
How precision medicine and screening with big data could increase overdiagnosis [link]Paper   doi   bibtex  
A Theoretical Twist on the Transparency of Open Notes: Qualitative Analysis of Health Care Professionals’ Free-Text Answers. Erlingsdóttir, G.; Petersson, L.; and Jonnergård, K. Journal of Medical Internet Research, 21(9): e14347. September 2019.
A Theoretical Twist on the Transparency of Open Notes: Qualitative Analysis of Health Care Professionals’ Free-Text Answers [link]Paper   doi   bibtex   abstract  
Barriers and facilitators to data quality of electronic health records used for clinical research in China: a qualitative study. Ni, K.; Chu, H.; Zeng, L.; Li, N.; and Zhao, Y. BMJ Open, 9(7): e029314. July 2019.
Barriers and facilitators to data quality of electronic health records used for clinical research in China: a qualitative study [link]Paper   doi   bibtex   abstract  
Markets from meaning: quality uncertainty and the intersubjective construction of value. Beckert, J. Cambridge Journal of Economics,bez035. August 2019.
Markets from meaning: quality uncertainty and the intersubjective construction of value [link]Paper   doi   bibtex   abstract  
How precision medicine and screening with big data could increase overdiagnosis. Vogt, H.; Green, S.; Ekstrøm, C. T.; and Brodersen, J. BMJ,l5270. September 2019.
How precision medicine and screening with big data could increase overdiagnosis [link]Paper   doi   bibtex  
Data-driven discovery of changes in clinical code usage over time: a case-study on changes in cardiovascular disease recording in two English electronic health records databases (2001-2015). Rockenschaub, P.; Nguyen, V.; Aldridge, R. M; Acosta, D.; Garcia-Gomez, J. M; and Sáez, C. Technical Report Health Systems and Quality Improvement, September 2019.
Data-driven discovery of changes in clinical code usage over time: a case-study on changes in cardiovascular disease recording in two English electronic health records databases (2001-2015) [link]Paper   doi   bibtex   abstract  
  2018 (3)
Triangular Relations. Pyyhtinen, O. In Dépelteau, F., editor(s), The Palgrave Handbook of Relational Sociology, pages 161–182. Springer International Publishing, Cham, 2018.
Triangular Relations [link]Paper   doi   bibtex  
Possible Sources of Bias in Primary Care Electronic Health Record Data Use and Reuse. Verheij, R. A; Curcin, V.; Delaney, B. C; and McGilchrist, M. M Journal of Medical Internet Research, 20(5): e185. May 2018.
Possible Sources of Bias in Primary Care Electronic Health Record Data Use and Reuse [link]Paper   doi   bibtex  
Quantitative care: Caring for the aggregate in US academic population health sciences: Quantitative care. Mason, K. A. American Ethnologist, 45(2): 201–213. May 2018.
Quantitative care: Caring for the aggregate in US academic population health sciences: Quantitative care [link]Paper   doi   bibtex  
  2017 (6)
The fly and the cookie: alignment and unhingement in 21st-century capitalism. Fourcade, M. Socio-Economic Review, 15(3): 661–678. July 2017.
The fly and the cookie: alignment and unhingement in 21st-century capitalism [link]Paper   doi   bibtex  
Towards a broader conceptualisation of ‘public trust’ in the health care system. Gille, F.; Smith, S.; and Mays, N. Social Theory & Health, 15(1): 25–43. February 2017.
Towards a broader conceptualisation of ‘public trust’ in the health care system [link]Paper   doi   bibtex  
Realizing the Value (and Profitability) of Digital Health Data. Blumenthal, D. Annals of Internal Medicine, 166(11): 842. June 2017.
Realizing the Value (and Profitability) of Digital Health Data [link]Paper   doi   bibtex  
Quality of recording of diabetes in the UK: how does the GP's method of coding clinical data affect incidence estimates? Cross-sectional study using the CPRD database. Tate, A. R.; Dungey, S.; Glew, S.; Beloff, N.; Williams, R.; and Williams, T. BMJ open, 7(1): e012905. January 2017.
doi   bibtex   abstract  
Health Data for Common Good: Defining the Boundaries and Social Dilemmas of Data Commons. Purtova, N. In Under Observation: The Interplay Between eHealth and Surveillance, pages 177–210. Springer, 2017.
Health Data for Common Good: Defining the Boundaries and Social Dilemmas of Data Commons [link]Paper   bibtex  
Elite Power under Advanced Neoliberalism. Davies, W. Theory, Culture & Society,026327641771507. June 2017.
Elite Power under Advanced Neoliberalism [link]Paper   doi   bibtex  
  2016 (10)
The correct secret. Mason, K. A. Focaal, 2016(75): 45–58. June 2016.
The correct secret [link]Paper   doi   bibtex   abstract  
Seeing like a market. Fourcade, M.; and Healy, K. Socio-Economic Review,mww033. December 2016.
Seeing like a market [link]Paper   doi   bibtex  
Achievements and Limitations of Evidence-Based Medicine. Sheridan, D. J.; and Julian, D. G. Journal of the American College of Cardiology, 68(2): 204–213. July 2016.
Achievements and Limitations of Evidence-Based Medicine [link]Paper   doi   bibtex  
Young people’s views about consenting to data linkage: findings from the PEARL qualitative study. Audrey, S.; Brown, L.; Campbell, R.; Boyd, A.; and Macleod, J. BMC Medical Research Methodology, 16(1). December 2016.
Young people’s views about consenting to data linkage: findings from the PEARL qualitative study [link]Paper   doi   bibtex  
Towards data justice? The ambiguity of anti-surveillance resistance in political activism. Dencik, L.; Hintz, A.; and Cable, J. Big Data & Society, 3(2): 205395171667967. November 2016.
Towards data justice? The ambiguity of anti-surveillance resistance in political activism [link]Paper   doi   bibtex  
The New Era of Informed Consent: Getting to a Reasonable-Patient Standard Through Shared Decision Making. Spatz, E. S.; Krumholz, H. M.; and Moulton, B. W. JAMA, 315(19): 2063. May 2016.
The New Era of Informed Consent: Getting to a Reasonable-Patient Standard Through Shared Decision Making [link]Paper   doi   bibtex  
The Ethics of Biomedical Big Data. Mittelstadt, B. D.; and Floridi, L., editors. Volume 29 of Law, Governance and Technology SeriesSpringer International Publishing, Cham, 2016.
The Ethics of Biomedical Big Data [link]Paper   doi   bibtex  
The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts. Mittelstadt, B. D.; and Floridi, L. Science and Engineering Ethics, 22(2): 303–341. April 2016.
The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts [link]Paper   doi   bibtex  
Patient Perspectives on Sharing Anonymized Personal Health Data Using a Digital System for Dynamic Consent and Research Feedback: A Qualitative Study. Spencer, K.; Sanders, C.; Whitley, E. A; Lund, D.; Kaye, J.; and Dixon, W. G. Journal of Medical Internet Research, 18(4): e66. April 2016.
Patient Perspectives on Sharing Anonymized Personal Health Data Using a Digital System for Dynamic Consent and Research Feedback: A Qualitative Study [link]Paper   doi   bibtex  
On Human Dignity as a Foundation for the Right to Privacy. Floridi, L. Philosophy & Technology, 29(4): 307–312. December 2016.
On Human Dignity as a Foundation for the Right to Privacy [link]Paper   doi   bibtex  
  2015 (7)
Views of Ethical Best Practices in Sharing Individual-Level Data From Medical and Public Health Research: A Systematic Scoping Review. Bull, S.; Roberts, N.; and Parker, M. Journal of Empirical Research on Human Research Ethics, 10(3): 225–238. July 2015.
Views of Ethical Best Practices in Sharing Individual-Level Data From Medical and Public Health Research: A Systematic Scoping Review [link]Paper   doi   bibtex  
Sharing Research Data and Intellectual Property Law: A Primer. Carroll, M. W. PLOS Biology, 13(8): e1002235. August 2015.
Sharing Research Data and Intellectual Property Law: A Primer [link]Paper   doi   bibtex  
Promises and Challenges of Big Data Computing in Health Sciences. Huang, T.; Lan, L.; Fang, X.; An, P.; Min, J.; and Wang, F. Big Data Research, 2(1): 2–11. March 2015.
Promises and Challenges of Big Data Computing in Health Sciences [link]Paper   doi   bibtex  
New Big Things in Era of Digital Data:‘Big Data’& Big Data Challenges with its Solution Using Different Tools. Joshi, H. D.; Gondaliya, T. P.; and Joshi, H. J. . 2015.
New Big Things in Era of Digital Data:‘Big Data’& Big Data Challenges with its Solution Using Different Tools [pdf]Paper   bibtex  
LEGAL BASES FOR DISCLOSING CONFIDENTIAL PATIENT INFORMATION FOR PUBLIC HEALTH: DISTINGUISHING BETWEEN HEALTH PROTECTION AND HEALTH IMPROVEMENT:. Taylor, M. J. Medical Law Review, 23(3): 348–374. September 2015.
LEGAL BASES FOR DISCLOSING CONFIDENTIAL PATIENT INFORMATION FOR PUBLIC HEALTH: DISTINGUISHING BETWEEN HEALTH PROTECTION AND HEALTH IMPROVEMENT: [link]Paper   doi   bibtex  
Ethical Challenges of Big Data in Public Health. Vayena, E.; Salathé, M.; Madoff, L. C.; and Brownstein, J. S. PLOS Computational Biology, 11(2): e1003904. February 2015.
Ethical Challenges of Big Data in Public Health [link]Paper   doi   bibtex  
Discussion of “Combining Health Data Uses to Ignite Health System Learning”:. Denaxas, S.; Friedman, C. P.; Geissbuhler, A.; Hemingway, H.; Kalra, D.; Kimura, M.; Kuhn, K. A.; Payne, H. A.; de Quiros, F. G. B.; and Wyatt, J. C. Methods of Information in Medicine, 54(6): 488–499. November 2015.
Discussion of “Combining Health Data Uses to Ignite Health System Learning”: [link]Paper   doi   bibtex  
  2014 (14)
What’s the big fuss about ‘big data’?. Pope, C.; Halford, S.; Tinati, R.; and Weal, M. Journal of Health Services Research & Policy, 19(2): 67–68. April 2014.
What’s the big fuss about ‘big data’? [link]Paper   doi   bibtex  
What Big Data means to me. Bourne, P. E Journal of the American Medical Informatics Association, 21(2): 194–194. March 2014.
What Big Data means to me [link]Paper   doi   bibtex  
UK Biobank is an opt-in model for the sharing of medical records. Davis, J. Nursing Standard, 28(27): 35–35. 2014.
UK Biobank is an opt-in model for the sharing of medical records [link]Paper   bibtex  
Trends in big data analytics. Kambatla, K.; Kollias, G.; Kumar, V.; and Grama, A. Journal of Parallel and Distributed Computing, 74(7): 2561–2573. July 2014.
Trends in big data analytics [link]Paper   doi   bibtex  
The role of big data in health care decision making: an Italian experience. De Rosa, M.; Rossi, E.; and Cataudella, S. Value in Health, 17(3): A20. 2014.
The role of big data in health care decision making: an Italian experience [link]Paper   bibtex  
The Parable of Google Flu: Traps in Big Data Analysis. Lazer, D.; Kennedy, R.; King, G.; and Vespignani, A. Science, 343(6176): 1203–1205. March 2014.
The Parable of Google Flu: Traps in Big Data Analysis [link]Paper   doi   bibtex  
The NHS's care.data scheme: what are the risks to privacy?. Hoeksma, J. BMJ, 348(feb17 10): g1547–g1547. February 2014.
The NHS's care.data scheme: what are the risks to privacy? [link]Paper   doi   bibtex  
The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data. Margolis, R.; Derr, L.; Dunn, M.; Huerta, M.; Larkin, J.; Sheehan, J.; Guyer, M.; and Green, E. D Journal of the American Medical Informatics Association, 21(6): 957–958. November 2014.
The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data [link]Paper   doi   bibtex  
The commodification of patient opinion: the digital patient experience economy in the age of big data. Lupton, D. Sociology of Health & Illness, 36(6): 856–869. July 2014.
The commodification of patient opinion: the digital patient experience economy in the age of big data [link]Paper   doi   bibtex  
The case of the “Big Data” revolution. Worst, J.; and others Working Papers, 30(35): 119–141. 2014.
The case of the “Big Data” revolution [pdf]Paper   bibtex  
Harnessing the power of big data in healthcare. Nash, D. B. American health & drug benefits, 7(2): 69. 2014.
Harnessing the power of big data in healthcare [link]Paper   bibtex  
Ethics of Care.Data. Herbert, I. ITNOW, 56(3): 46–47. September 2014.
Ethics of Care.Data [link]Paper   doi   bibtex  
Ethics for big data and analytics. Chessell, M. Somers: IBM Corporation. 2014.
Ethics for big data and analytics [pdf]Paper   bibtex  
Effective pseudonymisation and explicit statements of public interest to ensure the benefits of sharing health data for research, quality improvement and health service management outweigh the risks. De Lusignan, S. Journal of Innovation in Health Informatics, 21(2): 61–63. May 2014.
Effective pseudonymisation and explicit statements of public interest to ensure the benefits of sharing health data for research, quality improvement and health service management outweigh the risks [link]Paper   doi   bibtex  
  2013 (8)
Why Big Data Won't Cure Us. Neff, G. Big Data, 1(3): 117–123. September 2013.
Why Big Data Won't Cure Us [link]Paper   doi   bibtex  
The NHS Information Revolution: ‘Choice of Control’ to ‘Choice’ and ‘Control’. Munns, C.; and Basu, S. International Review of Law, Computers & Technology, 27(1-2): 124–160. July 2013.
The NHS Information Revolution: ‘Choice of Control’ to ‘Choice’ <i>and</i> ‘Control’ [link]Paper   doi   bibtex  
Reforming the regulation of health research in England and Wales: new challenges: new pitfalls. McHale, J. Journal of Medical Law and Ethics, 1(1): 23–42. 2013.
Reforming the regulation of health research in England and Wales: new challenges: new pitfalls [link]Paper   bibtex  
Protecting health privacy in an era of big data processing and cloud computing. Pasquale, F.; and Ragone, T. A. Stan. Tech. L. Rev., 17: 595. 2013.
Protecting health privacy in an era of big data processing and cloud computing [link]Paper   bibtex  
On the Ethical Implications of Personal Health Monitoring. Mittelstadt, B. . 2013.
On the Ethical Implications of Personal Health Monitoring [link]Paper   bibtex  
Identifying Personal Genomes by Surname Inference. Gymrek, M.; McGuire, A. L.; Golan, D.; Halperin, E.; and Erlich, Y. Science, 339(6117): 321–324. January 2013.
Identifying Personal Genomes by Surname Inference [link]Paper   doi   bibtex  
Ethical, legal, and social implications of incorporating genomic information into electronic health records. Hazin, R.; Brothers, K. B.; Malin, B. A.; Koenig, B. A.; Sanderson, S. C.; Rothstein, M. A.; Williams, M. S.; Clayton, E. W.; and Kullo, I. J. Genetics in Medicine, 15(10): 810–816. October 2013.
Ethical, legal, and social implications of incorporating genomic information into electronic health records [link]Paper   doi   bibtex  
Electronic health records-driven phenotyping: challenges, recent advances, and perspectives. Pathak, J.; Kho, A. N; and Denny, J. C Journal of the American Medical Informatics Association, 20(e2): e206–e211. December 2013.
Electronic health records-driven phenotyping: challenges, recent advances, and perspectives [link]Paper   doi   bibtex  
  2012 (3)
Computer templates in chronic disease management: ethnographic case study in general practice. Swinglehurst, D.; Greenhalgh, T.; and Roberts, C. BMJ Open, 2(6): e001754. 2012.
Computer templates in chronic disease management: ethnographic case study in general practice [link]Paper   doi   bibtex  
UK Biobank: Consequences for commons and innovation. Huzair, F.; and Papaioannou, T. Science and Public Policy, 39(4): 500–512. August 2012.
UK Biobank: Consequences for commons and innovation [link]Paper   doi   bibtex  
The “decrepit concept” of confidentiality, 30 years later. Anesi, G. L. Virtual Mentor, 14(9): 708. 2012.
The “decrepit concept” of confidentiality, 30 years later [link]Paper   bibtex  
  2011 (2)
Humanities Approaches to Graphical Display. Drucker, J. Digital Humanities Quarterly, 5(1). 2011.
Humanities Approaches to Graphical Display [link]Paper   bibtex  
Linking social care, housing and health data: social care clients' and patients' views. Aitken, M. Scottish Social Government Resaearch, "Edinburgh, 2011. OCLC: 780257485
Linking social care, housing and health data: social care clients' and patients' views [link]Paper   bibtex  
  2010 (2)
Using NHS Patient Data for Research Without Consent. Brown, I.; Brown, L.; and Korff, D. Law, Innovation and Technology, 2(2): 219–258. December 2010.
Using NHS Patient Data for Research Without Consent [link]Paper   doi   bibtex  
National Biobanks: Clinical Labor, Risk Production, and the Creation of Biovalue. Mitchell, R.; and Waldby, C. Science, Technology, & Human Values, 35(3): 330–355. May 2010.
National Biobanks: Clinical Labor, Risk Production, and the Creation of Biovalue [link]Paper   doi   bibtex  
  2009 (2)
Towards a Privacy Framework. Mattison Thompson, F.; Smith, A.; and Winklhofer, H. . 2009.
Towards a Privacy Framework [link]Paper   bibtex  
Free riders and pious sons–why science research remains obligatory. Chan, S.; and Harris, J. Bioethics, 23(3): 161–171. March 2009.
doi   bibtex   abstract  
  2008 (1)
DNA data sharing: research participants' perspectives. McGuire, A. L; Hamilton, J. A; Lunstroth, R.; McCullough, L. B; and Goldman, A. Genetics in Medicine, 10(1): 46–53. January 2008.
DNA data sharing: research participants' perspectives [link]Paper   doi   bibtex  
  2007 (1)
Patients, privacy and trust: Patients’ willingness to allow researchers to access their medical records. Damschroder, L. J.; Pritts, J. L.; Neblo, M. A.; Kalarickal, R. J.; Creswell, J. W.; and Hayward, R. A. Social Science & Medicine, 64(1): 223–235. January 2007.
Patients, privacy and trust: Patients’ willingness to allow researchers to access their medical records [link]Paper   doi   bibtex  
  2004 (2)
Data, "race," and politics: a commentary on the epidemiological significance of California's Proposition 54. Krieger, N. Journal of Epidemiology & Community Health, 58(8): 632–633. August 2004.
Data, "race," and politics: a commentary on the epidemiological significance of California's Proposition 54 [link]Paper   doi   bibtex  
Data, "race," and politics: a commentary on the epidemiological significance of California's Proposition 54. Krieger, N. Journal of Epidemiology & Community Health, 58(8): 632–633. August 2004.
Data, "race," and politics: a commentary on the epidemiological significance of California's Proposition 54 [link]Paper   doi   bibtex  
  1992 (1)
The Making of Public Health Data: Paradigms, Politics, and Policy. Krieger, N. Journal of Public Health Policy, 13(4): 412. 1992.
The Making of Public Health Data: Paradigms, Politics, and Policy [link]Paper   doi   bibtex  
  undefined (1)
Toward the Elimination of Subjectivity: From Francis Bacon to AI. Davis, L. Social Research: An International Quarterly, 86(4): 845–869. .
Toward the Elimination of Subjectivity: From Francis Bacon to AI. [link]Paper   bibtex