@article{lehtonen_serres_2020,
	title = {Serres and {Foundations}},
	volume = {37},
	issn = {0263-2764, 1460-3616},
	url = {http://journals.sagepub.com/doi/10.1177/0263276419891545},
	doi = {10.1177/0263276419891545},
	abstract = {While Michel Serres’ work has become relatively well-known among social theoreticians in recent years, his explicit thematization of the foundations of human collectives has gained surprisingly little attention. This article claims that Serres’ approach to the theme of foundations can be clarified by scrutinizing the way in which he poses and answers the following three questions: How are we together? What and whom do we exclude from our togetherness and how? Who are we today? Instead of starting with a ready-made order, be it in the form of individuals or society, Serres pushes social research to take up the challenge of examining the point at which order is about to emerge out of noise and chaos, but where the outcome of the process remains uncertain. Especially relevant to the discussion are Serres’ books Rome, Statues and Geometry, all three of which bear the subtitle Book of Foundations.},
	language = {en},
	number = {3},
	urldate = {2020-07-13},
	journal = {Theory, Culture \& Society},
	author = {Lehtonen, Turo-Kimmo},
	month = may,
	year = {2020},
	pages = {3--22},
}

While Michel Serres’ work has become relatively well-known among social theoreticians in recent years, his explicit thematization of the foundations of human collectives has gained surprisingly little attention. This article claims that Serres’ approach to the theme of foundations can be clarified by scrutinizing the way in which he poses and answers the following three questions: How are we together? What and whom do we exclude from our togetherness and how? Who are we today? Instead of starting with a ready-made order, be it in the form of individuals or society, Serres pushes social research to take up the challenge of examining the point at which order is about to emerge out of noise and chaos, but where the outcome of the process remains uncertain. Especially relevant to the discussion are Serres’ books Rome, Statues and Geometry, all three of which bear the subtitle Book of Foundations.

@article{rettberg_situated_2020,
	title = {Situated data analysis: a new method for analysing encoded power relationships in social media platforms and apps},
	volume = {7},
	issn = {2662-9992},
	shorttitle = {Situated data analysis},
	url = {http://www.nature.com/articles/s41599-020-0495-3},
	doi = {10.1057/s41599-020-0495-3},
	language = {en},
	number = {1},
	urldate = {2020-07-13},
	journal = {Humanities and Social Sciences Communications},
	author = {Rettberg, Jill Walker},
	month = dec,
	year = {2020},
	pages = {5},
}

@article{liang_physician_2020,
	title = {Physician code creep after the initiation of outpatient volume control program and implications for appropriate {ICD}-10-{CM} coding},
	volume = {20},
	issn = {1472-6963},
	url = {https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-020-5001-5},
	doi = {10.1186/s12913-020-5001-5},
	language = {en},
	number = {1},
	urldate = {2020-07-13},
	journal = {BMC Health Services Research},
	author = {Liang, Fu-Wen and Wang, Liang-Yi and Liu, Lin-Yi and Li, Chung Yi and Lu, Tsung-Hsueh},
	month = dec,
	year = {2020},
	pages = {127},
}

@article{weiner_how_2020,
	title = {How accurate is the medical record? {A} comparison of the physician’s note with a concealed audio recording in unannounced standardized patient encounters},
	volume = {27},
	issn = {1527-974X},
	shorttitle = {How accurate is the medical record?},
	url = {https://academic.oup.com/jamia/article/27/5/770/5824779},
	doi = {10.1093/jamia/ocaa027},
	abstract = {Abstract
            
              Objectives
              Accurate documentation in the medical record is essential for quality care; extensive documentation is required for reimbursement. At times, these 2 imperatives conflict. We explored the concordance of information documented in the medical record with a gold standard measure.
            
            
              Materials and Methods
              We compared 105 encounter notes to audio recordings covertly collected by unannounced standardized patients from 36 physicians, to identify discrepancies and estimate the reimbursement implications of billing the visit based on the note vs the care actually delivered.
            
            
              Results
              There were 636 documentation errors, including 181 charted findings that did not take place, and 455 findings that were not charted. Ninety percent of notes contained at least 1 error. In 21 instances, the note justified a higher billing level than the gold standard audio recording, and in 4, it underrepresented the level of service (P = .005), resulting in 40 level 4 notes instead of the 23 justified based on the audio, a 74\% inflated misrepresentation.
            
            
              Discussion
              While one cannot generalize about specific error rates based on a relatively small sample of physicians exclusively within the Department of Veterans Affairs Health System, the magnitude of the findings raise fundamental concerns about the integrity of the current medical record documentation process as an actual representation of care, with implications for determining both quality and resource utilization.
            
            
              Conclusion
              The medical record should not be assumed to reflect care delivered. Furthermore, errors of commission—documentation of services not actually provided—may inflate estimates of resource utilization.},
	language = {en},
	number = {5},
	urldate = {2020-07-13},
	journal = {Journal of the American Medical Informatics Association},
	author = {Weiner, Saul J and Wang, Shiyuan and Kelly, Brendan and Sharma, Gunjan and Schwartz, Alan},
	month = may,
	year = {2020},
	pages = {770--775},
}

Abstract Objectives Accurate documentation in the medical record is essential for quality care; extensive documentation is required for reimbursement. At times, these 2 imperatives conflict. We explored the concordance of information documented in the medical record with a gold standard measure. Materials and Methods We compared 105 encounter notes to audio recordings covertly collected by unannounced standardized patients from 36 physicians, to identify discrepancies and estimate the reimbursement implications of billing the visit based on the note vs the care actually delivered. Results There were 636 documentation errors, including 181 charted findings that did not take place, and 455 findings that were not charted. Ninety percent of notes contained at least 1 error. In 21 instances, the note justified a higher billing level than the gold standard audio recording, and in 4, it underrepresented the level of service (P = .005), resulting in 40 level 4 notes instead of the 23 justified based on the audio, a 74% inflated misrepresentation. Discussion While one cannot generalize about specific error rates based on a relatively small sample of physicians exclusively within the Department of Veterans Affairs Health System, the magnitude of the findings raise fundamental concerns about the integrity of the current medical record documentation process as an actual representation of care, with implications for determining both quality and resource utilization. Conclusion The medical record should not be assumed to reflect care delivered. Furthermore, errors of commission—documentation of services not actually provided—may inflate estimates of resource utilization.

@article{odonnell_impact_2020,
	title = {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},
	volume = {115},
	issn = {0965-2140, 1360-0443},
	shorttitle = {Impact of the introduction and withdrawal of financial incentives on the delivery of alcohol screening and brief advice in {English} primary health care},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/add.14778},
	doi = {10.1111/add.14778},
	language = {en},
	number = {1},
	urldate = {2020-07-13},
	journal = {Addiction},
	author = {O'Donnell, Amy and Angus, Colin and Hanratty, Barbara and Hamilton, Fiona L. and Petersen, Irene and Kaner, Eileen},
	month = jan,
	year = {2020},
	pages = {49--60},
}

@article{callahan_research_2020,
	title = {Research and {Reporting} {Considerations} for {Observational} {Studies} {Using} {Electronic} {Health} {Record} {Data}},
	volume = {172},
	issn = {0003-4819, 1539-3704},
	url = {https://www.acpjournals.org/doi/10.7326/M19-0873},
	doi = {10.7326/M19-0873},
	language = {en},
	number = {11\_Supplement},
	urldate = {2020-07-13},
	journal = {Annals of Internal Medicine},
	author = {Callahan, Alison and Shah, Nigam H. and Chen, Jonathan H.},
	month = jun,
	year = {2020},
	pages = {S79--S84},
}

@article{slota_prospecting_2020,
	title = {Prospecting (in) the data sciences},
	volume = {7},
	issn = {2053-9517, 2053-9517},
	url = {http://journals.sagepub.com/doi/10.1177/2053951720906849},
	doi = {10.1177/2053951720906849},
	language = {en},
	number = {1},
	urldate = {2020-07-13},
	journal = {Big Data \& Society},
	author = {Slota, Stephen C and Hoffman, Andrew S and Ribes, David and Bowker, Geoffrey C},
	month = jan,
	year = {2020},
	pages = {205395172090684},
}

@article{rettberg_book_2020,
	title = {Book {Review}: {Automated} {Media}},
	issn = {1354-8565, 1748-7382},
	shorttitle = {Book {Review}},
	url = {http://journals.sagepub.com/doi/10.1177/1354856520906610},
	doi = {10.1177/1354856520906610},
	language = {en},
	urldate = {2020-07-13},
	journal = {Convergence: The International Journal of Research into New Media Technologies},
	author = {Rettberg, Jill Walker},
	month = feb,
	year = {2020},
	pages = {135485652090661},
}

@article{doorn_platform_2020,
	title = {Platform {Capitalism}’s {Hidden} {Abode}: {Producing} {Data} {Assets} in the {Gig} {Economy}},
	issn = {0066-4812, 1467-8330},
	shorttitle = {Platform {Capitalism}’s {Hidden} {Abode}},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/anti.12641},
	doi = {10.1111/anti.12641},
	language = {en},
	urldate = {2020-07-13},
	journal = {Antipode},
	author = {Doorn, Niels and Badger, Adam},
	month = jun,
	year = {2020},
	pages = {anti.12641},
}

@article{weiner_everyday_2020,
	title = {Everyday curation? {Attending} to data, records and record keeping in the practices of self-monitoring},
	volume = {7},
	issn = {2053-9517, 2053-9517},
	shorttitle = {Everyday curation?},
	url = {http://journals.sagepub.com/doi/10.1177/2053951720918275},
	doi = {10.1177/2053951720918275},
	abstract = {This paper is concerned with everyday data practices, considering how people record data produced through self-monitoring. The analysis unpacks the relationships between taking a measure, and making and reviewing records. The paper is based on an interview study with people who monitor their blood pressure and/or body mass index/weight. Animated by discussions of ‘data power’ which are, in part, predicated on the flow and aggregation of data, we aim to extend important work concerning the everyday constitution of digital data. In the paper, we adopt and develop the idea of curation as a theory of attention. We introduce the idea of discerning work to characterise the skilful judgements people make about which readings they record, how readings are presented, and about the records they retain and those they discard. We suggest self-monitoring produces partial data, both in the sense that it embodies these judgements, and also because monitoring might be conducted intermittently. We also extend previous analyses by exploring the broad set of materials, digital and analogue, networked and not networked, involved in record keeping to consider the different ways these contributed to regulating attention to self-monitoring. By paying attention to which data is recorded and the occasions when data is not recorded, as well as the ways data is recorded, the research provides specificity to the different ways in which self-monitoring data may or may not flow or contribute to big data sets. We argue that ultimately our analysis contributes to nuancing our understanding of ‘data power’.},
	language = {en},
	number = {1},
	urldate = {2020-07-13},
	journal = {Big Data \& Society},
	author = {Weiner, Kate and Will, Catherine and Henwood, Flis and Williams, Rosalind},
	month = jan,
	year = {2020},
	pages = {205395172091827},
}

This paper is concerned with everyday data practices, considering how people record data produced through self-monitoring. The analysis unpacks the relationships between taking a measure, and making and reviewing records. The paper is based on an interview study with people who monitor their blood pressure and/or body mass index/weight. Animated by discussions of ‘data power’ which are, in part, predicated on the flow and aggregation of data, we aim to extend important work concerning the everyday constitution of digital data. In the paper, we adopt and develop the idea of curation as a theory of attention. We introduce the idea of discerning work to characterise the skilful judgements people make about which readings they record, how readings are presented, and about the records they retain and those they discard. We suggest self-monitoring produces partial data, both in the sense that it embodies these judgements, and also because monitoring might be conducted intermittently. We also extend previous analyses by exploring the broad set of materials, digital and analogue, networked and not networked, involved in record keeping to consider the different ways these contributed to regulating attention to self-monitoring. By paying attention to which data is recorded and the occasions when data is not recorded, as well as the ways data is recorded, the research provides specificity to the different ways in which self-monitoring data may or may not flow or contribute to big data sets. We argue that ultimately our analysis contributes to nuancing our understanding of ‘data power’.

@article{montgomery_wild_2020,
	title = {Wild data: how front‐line hospital staff make sense of patients’ experiences},
	volume = {42},
	issn = {0141-9889, 1467-9566},
	shorttitle = {Wild data},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/1467-9566.13115},
	doi = {10.1111/1467-9566.13115},
	language = {en},
	number = {6},
	urldate = {2020-07-13},
	journal = {Sociology of Health \& Illness},
	author = {Montgomery, Catherine M. and Chisholm, Alison and Parkin, Stephen and Locock, Louise},
	month = jul,
	year = {2020},
	pages = {1424--1440},
}

@article{vogt_how_2019,
	title = {How precision medicine and screening with big data could increase overdiagnosis},
	issn = {0959-8138, 1756-1833},
	url = {http://www.bmj.com/lookup/doi/10.1136/bmj.l5270},
	doi = {10.1136/bmj.l5270},
	language = {en},
	urldate = {2020-07-13},
	journal = {BMJ},
	author = {Vogt, Henrik and Green, Sara and Ekstrøm, Claus Thorn and Brodersen, John},
	month = sep,
	year = {2019},
	pages = {l5270},
}

@article{erlingsdottir_theoretical_2019,
	title = {A {Theoretical} {Twist} on the {Transparency} of {Open} {Notes}: {Qualitative} {Analysis} of {Health} {Care} {Professionals}’ {Free}-{Text} {Answers}},
	volume = {21},
	issn = {1438-8871},
	shorttitle = {A {Theoretical} {Twist} on the {Transparency} of {Open} {Notes}},
	url = {https://www.jmir.org/2019/9/e14347},
	doi = {10.2196/14347},
	abstract = {Background
              The New Public Management movement strove for transparency so that policy makers and citizens could gain insight into the work and performance of health care. As the use of the electronic health record (EHR) started to diffuse, a foundation was laid for enhanced transparency within and between health care organizations. Now we appear to be experiencing a new kind of transparency in the health care sector. Many health care providers offer their patients online access to their EHRs (here referred to as Open Notes). The Open Notes system enables and strives for transparency between the health care organization and the patient. Hence, this study investigates health care professional (HCP) perceptions of Open Notes and deepens the understanding of the transparency that Open Notes implies.
            
            
              Objective
              Based on two survey studies of HCP perceptions of Open Notes, this paper aims to deepen the academic writing on the type of transparency that is connected to Open Notes.
            
            
              Methods
              HCPs in adult psychiatry in Region Skåne, Sweden, were surveyed before and after implementation of Open Notes. The empirical material presented consists of 1554 free-text answers from two Web surveys. A qualitative content analysis was performed.
            
            
              Results
              The theoretically informed analysis pivots around the following factors connected to transparency: effectiveness; trust; accountability; autonomy and control; confidentiality, privacy, and anonymity; fairness; and legitimacy. The results show that free-text answers can be sorted under these factors as trade-offs with transparency. According to HCPs, trade-offs affect their work, their relationship with patients, and not least, their work tool, the EHR. However, since many HCPs also state that they have not met many patients, and in some cases none, who have read their EHRs, these effects seem to be more connected to the possibility (or threat) of transparency than to the actual effectuated transparency.
            
            
              Conclusions
              The implementation (or reform) of Open Notes is policy driven while demanding real-time transparency on behalf of citizens/patients and not the authorities, which makes this particular form of transparency quite unique and interesting. We have chosen to call it governed individual real-time transparency. The effects of Open Notes may vary between different medical specialties relative to their sensitivity to both total and real-time transparency. When HCPs react by changing their ways of writing notes, Open Notes can affect the efficiency of the work of HCPs and the service itself in a negative manner. HCP reactions are aimed primarily at protecting patients and their relatives as well as their own relationship with the patients and secondly at protecting themselves. Thus, governed individual real-time transparency that provides full transparency of an actual practice in health care may have the intended positive effects but can also result in negative trade-offs between transparency and efficiency of the actual practice. This may imply that full transparency is not always most desirable but that other options can be considered on a scale between none and full transparency.},
	language = {en},
	number = {9},
	urldate = {2020-07-13},
	journal = {Journal of Medical Internet Research},
	author = {Erlingsdóttir, Gudbjörg and Petersson, Lena and Jonnergård, Karin},
	month = sep,
	year = {2019},
	pages = {e14347},
}

Background The New Public Management movement strove for transparency so that policy makers and citizens could gain insight into the work and performance of health care. As the use of the electronic health record (EHR) started to diffuse, a foundation was laid for enhanced transparency within and between health care organizations. Now we appear to be experiencing a new kind of transparency in the health care sector. Many health care providers offer their patients online access to their EHRs (here referred to as Open Notes). The Open Notes system enables and strives for transparency between the health care organization and the patient. Hence, this study investigates health care professional (HCP) perceptions of Open Notes and deepens the understanding of the transparency that Open Notes implies. Objective Based on two survey studies of HCP perceptions of Open Notes, this paper aims to deepen the academic writing on the type of transparency that is connected to Open Notes. Methods HCPs in adult psychiatry in Region Skåne, Sweden, were surveyed before and after implementation of Open Notes. The empirical material presented consists of 1554 free-text answers from two Web surveys. A qualitative content analysis was performed. Results The theoretically informed analysis pivots around the following factors connected to transparency: effectiveness; trust; accountability; autonomy and control; confidentiality, privacy, and anonymity; fairness; and legitimacy. The results show that free-text answers can be sorted under these factors as trade-offs with transparency. According to HCPs, trade-offs affect their work, their relationship with patients, and not least, their work tool, the EHR. However, since many HCPs also state that they have not met many patients, and in some cases none, who have read their EHRs, these effects seem to be more connected to the possibility (or threat) of transparency than to the actual effectuated transparency. Conclusions The implementation (or reform) of Open Notes is policy driven while demanding real-time transparency on behalf of citizens/patients and not the authorities, which makes this particular form of transparency quite unique and interesting. We have chosen to call it governed individual real-time transparency. The effects of Open Notes may vary between different medical specialties relative to their sensitivity to both total and real-time transparency. When HCPs react by changing their ways of writing notes, Open Notes can affect the efficiency of the work of HCPs and the service itself in a negative manner. HCP reactions are aimed primarily at protecting patients and their relatives as well as their own relationship with the patients and secondly at protecting themselves. Thus, governed individual real-time transparency that provides full transparency of an actual practice in health care may have the intended positive effects but can also result in negative trade-offs between transparency and efficiency of the actual practice. This may imply that full transparency is not always most desirable but that other options can be considered on a scale between none and full transparency.

@article{ni_barriers_2019,
	title = {Barriers and facilitators to data quality of electronic health records used for clinical research in {China}: a qualitative study},
	volume = {9},
	issn = {2044-6055, 2044-6055},
	shorttitle = {Barriers and facilitators to data quality of electronic health records used for clinical research in {China}},
	url = {http://bmjopen.bmj.com/lookup/doi/10.1136/bmjopen-2019-029314},
	doi = {10.1136/bmjopen-2019-029314},
	abstract = {Objectives
              There is an increasing trend in the use of electronic health records (EHRs) for clinical research. However, more knowledge is needed on how to assure and improve data quality. This study aimed to explore healthcare professionals’ experiences and perceptions of barriers and facilitators of data quality of EHR-based studies in the Chinese context.
            
            
              Setting
              Four tertiary hospitals in Beijing, China.
            
            
              Participants
              Nineteen healthcare professionals with experience in using EHR data for clinical research participated in the study.
            
            
              Methods
              A qualitative study based on face-to-face semistructured interviews was conducted from March to July 2018. The interviews were audiorecorded and transcribed verbatim. Data analysis was performed using the inductive thematic analysis approach.
            
            
              Results
              The main themes included factors related to healthcare systems, clinical documentation, EHR systems and researchers. The perceived barriers to data quality included heavy workload, staff rotations, lack of detailed information for specific research, variations in terminology, limited retrieval capabilities, large amounts of unstructured data, challenges with patient identification and matching, problems with data extraction and unfamiliar with data quality assessment. To improve data quality, suggestions from participants included: better staff training, providing monetary incentives, performing daily data verification, improving software functionality and coding structures as well as enhancing multidisciplinary cooperation.
            
            
              Conclusions
              These results provide a basis to begin to address current barriers and ultimately to improve validity and generalisability of research findings in China.},
	language = {en},
	number = {7},
	urldate = {2020-07-13},
	journal = {BMJ Open},
	author = {Ni, Kaiwen and Chu, Hongling and Zeng, Lin and Li, Nan and Zhao, Yiming},
	month = jul,
	year = {2019},
	pages = {e029314},
}

Objectives There is an increasing trend in the use of electronic health records (EHRs) for clinical research. However, more knowledge is needed on how to assure and improve data quality. This study aimed to explore healthcare professionals’ experiences and perceptions of barriers and facilitators of data quality of EHR-based studies in the Chinese context. Setting Four tertiary hospitals in Beijing, China. Participants Nineteen healthcare professionals with experience in using EHR data for clinical research participated in the study. Methods A qualitative study based on face-to-face semistructured interviews was conducted from March to July 2018. The interviews were audiorecorded and transcribed verbatim. Data analysis was performed using the inductive thematic analysis approach. Results The main themes included factors related to healthcare systems, clinical documentation, EHR systems and researchers. The perceived barriers to data quality included heavy workload, staff rotations, lack of detailed information for specific research, variations in terminology, limited retrieval capabilities, large amounts of unstructured data, challenges with patient identification and matching, problems with data extraction and unfamiliar with data quality assessment. To improve data quality, suggestions from participants included: better staff training, providing monetary incentives, performing daily data verification, improving software functionality and coding structures as well as enhancing multidisciplinary cooperation. Conclusions These results provide a basis to begin to address current barriers and ultimately to improve validity and generalisability of research findings in China.

@article{beckert_markets_2019,
	title = {Markets from meaning: quality uncertainty and the intersubjective construction of value},
	issn = {0309-166X, 1464-3545},
	shorttitle = {Markets from meaning},
	url = {https://academic.oup.com/cje/advance-article/doi/10.1093/cje/bez035/5550612},
	doi = {10.1093/cje/bez035},
	abstract = {Abstract
            This article explores price formation in markets where quality cannot be based on intrinsic characteristics of the good exchanged. In such markets, quality uncertainty is not an information problem as described by Akerlof in the market for lemons model. Instead, defining quality is a problem of contingent assessments that are arrived at intersubjectively through discursive practices and mutual observation of market participants. Quality is endogenous to the market process. Institutions and conventions play an important role, much as they do in the market for lemons model, but their function is to generate confidence rather than trust. Prices emerge in such markets from a combination of intersubjectively established quality assessments, institutions and existing structural characteristics of the market. I call this the markets from meaning model, which I develop based on the art market and expand to capital investments and financial speculation.},
	language = {en},
	urldate = {2020-07-13},
	journal = {Cambridge Journal of Economics},
	author = {Beckert, Jens},
	month = aug,
	year = {2019},
	pages = {bez035},
}

Abstract This article explores price formation in markets where quality cannot be based on intrinsic characteristics of the good exchanged. In such markets, quality uncertainty is not an information problem as described by Akerlof in the market for lemons model. Instead, defining quality is a problem of contingent assessments that are arrived at intersubjectively through discursive practices and mutual observation of market participants. Quality is endogenous to the market process. Institutions and conventions play an important role, much as they do in the market for lemons model, but their function is to generate confidence rather than trust. Prices emerge in such markets from a combination of intersubjectively established quality assessments, institutions and existing structural characteristics of the market. I call this the markets from meaning model, which I develop based on the art market and expand to capital investments and financial speculation.

@article{vogt_how_2019-1,
	title = {How precision medicine and screening with big data could increase overdiagnosis},
	issn = {0959-8138, 1756-1833},
	url = {http://www.bmj.com/lookup/doi/10.1136/bmj.l5270},
	doi = {10.1136/bmj.l5270},
	language = {en},
	urldate = {2020-07-13},
	journal = {BMJ},
	author = {Vogt, Henrik and Green, Sara and Ekstrøm, Claus Thorn and Brodersen, John},
	month = sep,
	year = {2019},
	pages = {l5270},
}

@techreport{rockenschaub_data-driven_2019,
	type = {preprint},
	title = {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)},
	shorttitle = {Data-driven discovery of changes in clinical code usage over time},
	url = {http://medrxiv.org/lookup/doi/10.1101/19006098},
	abstract = {Objectives: To demonstrate how data-driven variability methods can be used to identify changes in disease recording in two English electronic health records databases between 2001-2015. Design: Repeated cross-sectional analysis that applied data-driven temporal variability methods to assess month-by-month changes in routinely-collected medical data. A measure of difference between months was calculated based on joint distributions of age, gender, socio-economic status and recorded cardiovascular diseases. Distances between months were used to identify temporal trends in data recording. Setting: 400 English primary care practices from the Clinical Practice Research Datalink (CPRD GOLD) and 451 hospital trusts from the Hospital Episode Statistics (HES). Main outcomes: The proportion of patients (CPRD GOLD) and hospital admissions (HES) with a recorded cardiovascular disease (CPRD GOLD: coronary heart disease, heart failure, peripheral arterial disease, stroke; HES: International Classification of Disease ICD codes I20-I69/G45). Results: Both databases showed gradual changes in cardiovascular disease recording between 2001 and 2008. The recorded prevalence of included cardiovascular diseases in CPRD GOLD increased by 47\%-62\%, which partially reversed after 2008. For hospital records in HES, there was a relative decrease in angina pectoris (-34.4\%) and unspecified stroke (-42.3\%) over the same time period, with a concomitant increase in chronic coronary heart disease (+14.3\%). Multiple abrupt changes in the use of myocardial infarction codes in hospital were found in March/April 2010, 2012 and 2014, possibly linked to updates of clinical coding guidelines. Conclusions: Identified temporal variability could be related to potentially non-medical causes such as updated coding guidelines. These artificial changes may introduce temporal correlation among diagnoses inferred from routine data, violating the assumptions of frequently used statistical methods. Temporal variability measures provided an objective and robust technique to identify, and subsequently account for, those changes in electronic health records studies without any prior knowledge of the data collection process.},
	language = {en},
	urldate = {2020-07-13},
	institution = {Health Systems and Quality Improvement},
	author = {Rockenschaub, Patrick and Nguyen, Vincent and Aldridge, Robert M and Acosta, Dionisio and Garcia-Gomez, Juan M and Sáez, Carlos},
	month = sep,
	year = {2019},
	doi = {10.1101/19006098},
}

Objectives: To demonstrate how data-driven variability methods can be used to identify changes in disease recording in two English electronic health records databases between 2001-2015. Design: Repeated cross-sectional analysis that applied data-driven temporal variability methods to assess month-by-month changes in routinely-collected medical data. A measure of difference between months was calculated based on joint distributions of age, gender, socio-economic status and recorded cardiovascular diseases. Distances between months were used to identify temporal trends in data recording. Setting: 400 English primary care practices from the Clinical Practice Research Datalink (CPRD GOLD) and 451 hospital trusts from the Hospital Episode Statistics (HES). Main outcomes: The proportion of patients (CPRD GOLD) and hospital admissions (HES) with a recorded cardiovascular disease (CPRD GOLD: coronary heart disease, heart failure, peripheral arterial disease, stroke; HES: International Classification of Disease ICD codes I20-I69/G45). Results: Both databases showed gradual changes in cardiovascular disease recording between 2001 and 2008. The recorded prevalence of included cardiovascular diseases in CPRD GOLD increased by 47%-62%, which partially reversed after 2008. For hospital records in HES, there was a relative decrease in angina pectoris (-34.4%) and unspecified stroke (-42.3%) over the same time period, with a concomitant increase in chronic coronary heart disease (+14.3%). Multiple abrupt changes in the use of myocardial infarction codes in hospital were found in March/April 2010, 2012 and 2014, possibly linked to updates of clinical coding guidelines. Conclusions: Identified temporal variability could be related to potentially non-medical causes such as updated coding guidelines. These artificial changes may introduce temporal correlation among diagnoses inferred from routine data, violating the assumptions of frequently used statistical methods. Temporal variability measures provided an objective and robust technique to identify, and subsequently account for, those changes in electronic health records studies without any prior knowledge of the data collection process.

@incollection{depelteau_triangular_2018,
	address = {Cham},
	title = {Triangular {Relations}},
	isbn = {978-3-319-66004-2 978-3-319-66005-9},
	url = {http://link.springer.com/10.1007/978-3-319-66005-9_8},
	language = {en},
	urldate = {2020-07-15},
	booktitle = {The {Palgrave} {Handbook} of {Relational} {Sociology}},
	publisher = {Springer International Publishing},
	author = {Pyyhtinen, Olli},
	editor = {Dépelteau, François},
	year = {2018},
	doi = {10.1007/978-3-319-66005-9_8},
	pages = {161--182},
}

@article{verheij_possible_2018,
	title = {Possible {Sources} of {Bias} in {Primary} {Care} {Electronic} {Health} {Record} {Data} {Use} and {Reuse}},
	volume = {20},
	issn = {1438-8871},
	url = {http://www.jmir.org/2018/5/e185/},
	doi = {10.2196/jmir.9134},
	language = {en},
	number = {5},
	urldate = {2020-07-13},
	journal = {Journal of Medical Internet Research},
	author = {Verheij, Robert A and Curcin, Vasa and Delaney, Brendan C and McGilchrist, Mark M},
	month = may,
	year = {2018},
	pages = {e185},
}

@article{mason_quantitative_2018,
	title = {Quantitative care: {Caring} for the aggregate in {US} academic population health sciences: {Quantitative} care},
	volume = {45},
	issn = {00940496},
	shorttitle = {Quantitative care},
	url = {http://doi.wiley.com/10.1111/amet.12632},
	doi = {10.1111/amet.12632},
	language = {en},
	number = {2},
	urldate = {2020-07-13},
	journal = {American Ethnologist},
	author = {Mason, Katherine A.},
	month = may,
	year = {2018},
	pages = {201--213},
}

@article{fourcade_fly_2017,
	title = {The fly and the cookie: alignment and unhingement in 21st-century capitalism},
	volume = {15},
	issn = {1475-1461, 1475-147X},
	shorttitle = {The fly and the cookie},
	url = {http://academic.oup.com/ser/article/15/3/661/4110371/The-fly-and-the-cookie-alignment-and-unhingement},
	doi = {10.1093/ser/mwx032},
	language = {en},
	number = {3},
	urldate = {2020-07-13},
	journal = {Socio-Economic Review},
	author = {Fourcade, Marion},
	month = jul,
	year = {2017},
	pages = {661--678},
}

@article{gille_towards_2017,
	title = {Towards a broader conceptualisation of ‘public trust’ in the health care system},
	volume = {15},
	issn = {1477-8211, 1477-822X},
	url = {http://link.springer.com/10.1057/s41285-016-0017-y},
	doi = {10.1057/s41285-016-0017-y},
	language = {en},
	number = {1},
	urldate = {2017-08-14},
	journal = {Social Theory \& Health},
	author = {Gille, Felix and Smith, Sarah and Mays, Nicholas},
	month = feb,
	year = {2017},
	pages = {25--43},
}

@article{blumenthal_realizing_2017,
	title = {Realizing the {Value} (and {Profitability}) of {Digital} {Health} {Data}},
	volume = {166},
	issn = {0003-4819},
	url = {http://annals.org/article.aspx?doi=10.7326/M17-0511},
	doi = {10.7326/M17-0511},
	language = {en},
	number = {11},
	urldate = {2017-08-14},
	journal = {Annals of Internal Medicine},
	author = {Blumenthal, David},
	month = jun,
	year = {2017},
	pages = {842},
}

@article{tate_quality_2017,
	title = {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},
	volume = {7},
	issn = {2044-6055},
	shorttitle = {Quality of recording of diabetes in the {UK}},
	doi = {10.1136/bmjopen-2016-012905},
	abstract = {OBJECTIVE: To assess the effect of coding quality on estimates of the incidence of diabetes in the UK between 1995 and 2014.
DESIGN: A cross-sectional analysis examining diabetes coding from 1995 to 2014 and how the choice of codes (diagnosis codes vs codes which suggest diagnosis) and quality of coding affect estimated incidence.
SETTING: Routine primary care data from 684 practices contributing to the UK Clinical Practice Research Datalink (data contributed from Vision (INPS) practices).
MAIN OUTCOME MEASURE: Incidence rates of diabetes and how they are affected by (1) GP coding and (2) excluding 'poor' quality practices with at least 10\% incident patients inaccurately coded between 2004 and 2014.
RESULTS: Incidence rates and accuracy of coding varied widely between practices and the trends differed according to selected category of code. If diagnosis codes were used, the incidence of type 2 increased sharply until 2004 (when the UK Quality Outcomes Framework was introduced), and then flattened off, until 2009, after which they decreased. If non-diagnosis codes were included, the numbers continued to increase until 2012. Although coding quality improved over time, 15\% of the 666 practices that contributed data between 2004 and 2014 were labelled 'poor' quality. When these practices were dropped from the analyses, the downward trend in the incidence of type 2 after 2009 became less marked and incidence rates were higher.
CONCLUSIONS: In contrast to some previous reports, diabetes incidence (based on diagnostic codes) appears not to have increased since 2004 in the UK. Choice of codes can make a significant difference to incidence estimates, as can quality of recording. Codes and data quality should be checked when assessing incidence rates using GP data.},
	language = {eng},
	number = {1},
	journal = {BMJ open},
	author = {Tate, A. Rosemary and Dungey, Sheena and Glew, Simon and Beloff, Natalia and Williams, Rachael and Williams, Tim},
	month = jan,
	year = {2017},
	pmid = {28122831},
	pmcid = {PMC5278252},
	keywords = {Data quality, Misclassification, primary care},
	pages = {e012905},
}

OBJECTIVE: To assess the effect of coding quality on estimates of the incidence of diabetes in the UK between 1995 and 2014. DESIGN: A cross-sectional analysis examining diabetes coding from 1995 to 2014 and how the choice of codes (diagnosis codes vs codes which suggest diagnosis) and quality of coding affect estimated incidence. SETTING: Routine primary care data from 684 practices contributing to the UK Clinical Practice Research Datalink (data contributed from Vision (INPS) practices). MAIN OUTCOME MEASURE: Incidence rates of diabetes and how they are affected by (1) GP coding and (2) excluding 'poor' quality practices with at least 10% incident patients inaccurately coded between 2004 and 2014. RESULTS: Incidence rates and accuracy of coding varied widely between practices and the trends differed according to selected category of code. If diagnosis codes were used, the incidence of type 2 increased sharply until 2004 (when the UK Quality Outcomes Framework was introduced), and then flattened off, until 2009, after which they decreased. If non-diagnosis codes were included, the numbers continued to increase until 2012. Although coding quality improved over time, 15% of the 666 practices that contributed data between 2004 and 2014 were labelled 'poor' quality. When these practices were dropped from the analyses, the downward trend in the incidence of type 2 after 2009 became less marked and incidence rates were higher. CONCLUSIONS: In contrast to some previous reports, diabetes incidence (based on diagnostic codes) appears not to have increased since 2004 in the UK. Choice of codes can make a significant difference to incidence estimates, as can quality of recording. Codes and data quality should be checked when assessing incidence rates using GP data.

@incollection{purtova_health_2017,
	title = {Health {Data} for {Common} {Good}: {Defining} the {Boundaries} and {Social} {Dilemmas} of {Data} {Commons}},
	shorttitle = {Health {Data} for {Common} {Good}},
	url = {http://link.springer.com/chapter/10.1007/978-3-319-48342-9_10},
	urldate = {2017-08-14},
	booktitle = {Under {Observation}: {The} {Interplay} {Between} {eHealth} and {Surveillance}},
	publisher = {Springer},
	author = {Purtova, Nadezhda},
	year = {2017},
	pages = {177--210},
}

@article{davies_elite_2017,
	title = {Elite {Power} under {Advanced} {Neoliberalism}},
	issn = {0263-2764, 1460-3616},
	url = {http://journals.sagepub.com/doi/10.1177/0263276417715072},
	doi = {10.1177/0263276417715072},
	language = {en},
	urldate = {2017-08-14},
	journal = {Theory, Culture \& Society},
	author = {Davies, William},
	month = jun,
	year = {2017},
	pages = {026327641771507},
}

@article{ajana_digital_2017,
	title = {Digital health and the biopolitics of the {Quantified} {Self}},
	volume = {3},
	issn = {2055-2076, 2055-2076},
	url = {http://journals.sagepub.com/doi/10.1177/2055207616689509},
	doi = {10.1177/2055207616689509},
	language = {en},
	urldate = {2017-08-14},
	journal = {DIGITAL HEALTH},
	author = {Ajana, Btihaj},
	month = jan,
	year = {2017},
	pages = {205520761668950},
}

@article{ravi_deep_2017,
	title = {Deep {Learning} for {Health} {Informatics}},
	volume = {21},
	issn = {2168-2194, 2168-2208},
	url = {http://ieeexplore.ieee.org/document/7801947/},
	doi = {10.1109/JBHI.2016.2636665},
	number = {1},
	urldate = {2017-08-14},
	journal = {IEEE Journal of Biomedical and Health Informatics},
	author = {Ravi, Daniele and Wong, Charence and Deligianni, Fani and Berthelot, Melissa and Andreu-Perez, Javier and Lo, Benny and Yang, Guang-Zhong},
	month = jan,
	year = {2017},
	pages = {4--21},
}

@article{mason_correct_2016,
	title = {The correct secret},
	volume = {2016},
	issn = {0920-1297, 1558-5263},
	url = {http://berghahnjournals.com/view/journals/focaal/2016/75/focaal750104.xml},
	doi = {10.3167/fcl.2016.750104},
	abstract = {In this article I argue that the global biosecurity project that arose out
of the events of the SARS epidemic of 2003 created a new balance of secrecy and
transparency within the public health arm of the Chinese state. In an effort to meet
national and international demands for greater transparency in support of a “common
good,” local public health officials engaged in what I call hypertransparency.
This hypertransparency took two forms: the real-time online sharing of disease
incidence data within the public health bureaucracy, and the over-performance
of disease fighting strategies in front of a wider local and global public. Because
local Chinese officials interpreted the “common good” differently from their international
partners, neither of these efforts succeeded in erasing the crucial role
that local officials continued to play in determining what should and should not
be shared, and with whom. Secrecy continued to be an important component of
China’s securitization efforts, with hypertransparency ultimately concealing more
than it revealed.},
	number = {75},
	urldate = {2020-07-13},
	journal = {Focaal},
	author = {Mason, Katherine A.},
	month = jun,
	year = {2016},
	pages = {45--58},
}

In this article I argue that the global biosecurity project that arose out of the events of the SARS epidemic of 2003 created a new balance of secrecy and transparency within the public health arm of the Chinese state. In an effort to meet national and international demands for greater transparency in support of a “common good,” local public health officials engaged in what I call hypertransparency. This hypertransparency took two forms: the real-time online sharing of disease incidence data within the public health bureaucracy, and the over-performance of disease fighting strategies in front of a wider local and global public. Because local Chinese officials interpreted the “common good” differently from their international partners, neither of these efforts succeeded in erasing the crucial role that local officials continued to play in determining what should and should not be shared, and with whom. Secrecy continued to be an important component of China’s securitization efforts, with hypertransparency ultimately concealing more than it revealed.

@article{fourcade_seeing_2016,
	title = {Seeing like a market},
	issn = {1475-1461, 1475-147X},
	url = {https://academic.oup.com/ser/article-lookup/doi/10.1093/ser/mww033},
	doi = {10.1093/ser/mww033},
	language = {en},
	urldate = {2020-07-13},
	journal = {Socio-Economic Review},
	author = {Fourcade, Marion and Healy, Kieran},
	month = dec,
	year = {2016},
	pages = {mww033},
}

@article{sheridan_achievements_2016,
	title = {Achievements and {Limitations} of {Evidence}-{Based} {Medicine}},
	volume = {68},
	issn = {07351097},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0735109716331370},
	doi = {10.1016/j.jacc.2016.03.600},
	language = {en},
	number = {2},
	urldate = {2020-07-13},
	journal = {Journal of the American College of Cardiology},
	author = {Sheridan, Desmond J. and Julian, Desmond G.},
	month = jul,
	year = {2016},
	pages = {204--213},
}

@article{audrey_young_2016,
	title = {Young people’s views about consenting to data linkage: findings from the {PEARL} qualitative study},
	volume = {16},
	issn = {1471-2288},
	shorttitle = {Young people’s views about consenting to data linkage},
	url = {http://www.biomedcentral.com/1471-2288/16/34},
	doi = {10.1186/s12874-016-0132-4},
	language = {en},
	number = {1},
	urldate = {2017-08-14},
	journal = {BMC Medical Research Methodology},
	author = {Audrey, Suzanne and Brown, Lindsey and Campbell, Rona and Boyd, Andy and Macleod, John},
	month = dec,
	year = {2016},
}

@article{dencik_towards_2016,
	title = {Towards data justice? {The} ambiguity of anti-surveillance resistance in political activism},
	volume = {3},
	issn = {2053-9517, 2053-9517},
	shorttitle = {Towards data justice?},
	url = {http://journals.sagepub.com/doi/10.1177/2053951716679678},
	doi = {10.1177/2053951716679678},
	language = {en},
	number = {2},
	urldate = {2017-08-14},
	journal = {Big Data \& Society},
	author = {Dencik, Lina and Hintz, Arne and Cable, Jonathan},
	month = nov,
	year = {2016},
	pages = {205395171667967},
}

@article{spatz_new_2016,
	title = {The {New} {Era} of {Informed} {Consent}: {Getting} to a {Reasonable}-{Patient} {Standard} {Through} {Shared} {Decision} {Making}},
	volume = {315},
	issn = {0098-7484},
	shorttitle = {The {New} {Era} of {Informed} {Consent}},
	url = {http://jama.jamanetwork.com/article.aspx?doi=10.1001/jama.2016.3070},
	doi = {10.1001/jama.2016.3070},
	language = {en},
	number = {19},
	urldate = {2017-08-15},
	journal = {JAMA},
	author = {Spatz, Erica S. and Krumholz, Harlan M. and Moulton, Benjamin W.},
	month = may,
	year = {2016},
	pages = {2063},
}

@book{mittelstadt_ethics_2016,
	address = {Cham},
	series = {Law, {Governance} and {Technology} {Series}},
	title = {The {Ethics} of {Biomedical} {Big} {Data}},
	volume = {29},
	isbn = {978-3-319-33523-0 978-3-319-33525-4},
	url = {http://link.springer.com/10.1007/978-3-319-33525-4},
	urldate = {2017-08-14},
	publisher = {Springer International Publishing},
	editor = {Mittelstadt, Brent Daniel and Floridi, Luciano},
	year = {2016},
	doi = {10.1007/978-3-319-33525-4},
}

@article{mittelstadt_ethics_2016-1,
	title = {The {Ethics} of {Big} {Data}: {Current} and {Foreseeable} {Issues} in {Biomedical} {Contexts}},
	volume = {22},
	issn = {1353-3452, 1471-5546},
	shorttitle = {The {Ethics} of {Big} {Data}},
	url = {http://link.springer.com/10.1007/s11948-015-9652-2},
	doi = {10.1007/s11948-015-9652-2},
	language = {en},
	number = {2},
	urldate = {2017-08-14},
	journal = {Science and Engineering Ethics},
	author = {Mittelstadt, Brent Daniel and Floridi, Luciano},
	month = apr,
	year = {2016},
	pages = {303--341},
}

@article{spencer_patient_2016,
	title = {Patient {Perspectives} on {Sharing} {Anonymized} {Personal} {Health} {Data} {Using} a {Digital} {System} for {Dynamic} {Consent} and {Research} {Feedback}: {A} {Qualitative} {Study}},
	volume = {18},
	issn = {1438-8871},
	shorttitle = {Patient {Perspectives} on {Sharing} {Anonymized} {Personal} {Health} {Data} {Using} a {Digital} {System} for {Dynamic} {Consent} and {Research} {Feedback}},
	url = {http://www.jmir.org/2016/4/e66/},
	doi = {10.2196/jmir.5011},
	language = {en},
	number = {4},
	urldate = {2017-08-14},
	journal = {Journal of Medical Internet Research},
	author = {Spencer, Karen and Sanders, Caroline and Whitley, Edgar A and Lund, David and Kaye, Jane and Dixon, William Gregory},
	month = apr,
	year = {2016},
	pages = {e66},
}

@article{floridi_human_2016,
	title = {On {Human} {Dignity} as a {Foundation} for the {Right} to {Privacy}},
	volume = {29},
	issn = {2210-5433, 2210-5441},
	url = {http://link.springer.com/10.1007/s13347-016-0220-8},
	doi = {10.1007/s13347-016-0220-8},
	language = {en},
	number = {4},
	urldate = {2017-08-14},
	journal = {Philosophy \& Technology},
	author = {Floridi, Luciano},
	month = dec,
	year = {2016},
	pages = {307--312},
}

@article{thatcher_data_2016,
	title = {Data colonialism through accumulation by dispossession: {New} metaphors for daily data},
	volume = {34},
	shorttitle = {Data colonialism through accumulation by dispossession},
	url = {http://journals.sagepub.com/doi/abs/10.1177/0263775816633195},
	number = {6},
	urldate = {2017-08-14},
	journal = {Environment and Planning D: Society and Space},
	author = {Thatcher, Jim and O’Sullivan, David and Mahmoudi, Dillon},
	year = {2016},
	pages = {990--1006},
}

@article{bull_views_2015,
	title = {Views of {Ethical} {Best} {Practices} in {Sharing} {Individual}-{Level} {Data} {From} {Medical} and {Public} {Health} {Research}: {A} {Systematic} {Scoping} {Review}},
	volume = {10},
	issn = {1556-2646, 1556-2654},
	shorttitle = {Views of {Ethical} {Best} {Practices} in {Sharing} {Individual}-{Level} {Data} {From} {Medical} and {Public} {Health} {Research}},
	url = {http://jre.sagepub.com/lookup/doi/10.1177/1556264615594767},
	doi = {10.1177/1556264615594767},
	language = {en},
	number = {3},
	urldate = {2017-02-22},
	journal = {Journal of Empirical Research on Human Research Ethics},
	author = {Bull, S. and Roberts, N. and Parker, M.},
	month = jul,
	year = {2015},
	pages = {225--238},
}

@article{carroll_sharing_2015,
	title = {Sharing {Research} {Data} and {Intellectual} {Property} {Law}: {A} {Primer}},
	volume = {13},
	issn = {1545-7885},
	shorttitle = {Sharing {Research} {Data} and {Intellectual} {Property} {Law}},
	url = {http://dx.plos.org/10.1371/journal.pbio.1002235},
	doi = {10.1371/journal.pbio.1002235},
	language = {en},
	number = {8},
	urldate = {2017-08-14},
	journal = {PLOS Biology},
	author = {Carroll, Michael W.},
	month = aug,
	year = {2015},
	pages = {e1002235},
}

@article{huang_promises_2015,
	title = {Promises and {Challenges} of {Big} {Data} {Computing} in {Health} {Sciences}},
	volume = {2},
	issn = {22145796},
	url = {http://linkinghub.elsevier.com/retrieve/pii/S2214579615000118},
	doi = {10.1016/j.bdr.2015.02.002},
	language = {en},
	number = {1},
	urldate = {2017-08-14},
	journal = {Big Data Research},
	author = {Huang, Tao and Lan, Liang and Fang, Xuexian and An, Peng and Min, Junxia and Wang, Fudi},
	month = mar,
	year = {2015},
	pages = {2--11},
}

@article{joshi_new_2015,
	title = {New {Big} {Things} in {Era} of {Digital} {Data}:‘{Big} {Data}’\& {Big} {Data} {Challenges} with its {Solution} {Using} {Different} {Tools}},
	shorttitle = {New {Big} {Things} in {Era} of {Digital} {Data}},
	url = {https://www.researchgate.net/profile/Tapan_Gondaliya/publication/273695685_New_Big_Things_in_Era_of_Digital_Data_'Big_Data'_Big_Data_Challenges_with_its_Solution_Using_Different_Tools/links/550bf9610cf2063799393325/New-Big-Things-in-Era-of-Digital-Data-Big-Data-Big-Data-Challenges-with-its-Solution-Using-Different-Tools.pdf},
	urldate = {2017-08-14},
	author = {Joshi, Hiren D. and Gondaliya, Tapan P. and Joshi, Hardik J.},
	year = {2015},
}

@article{taylor_legal_2015,
	title = {{LEGAL} {BASES} {FOR} {DISCLOSING} {CONFIDENTIAL} {PATIENT} {INFORMATION} {FOR} {PUBLIC} {HEALTH}: {DISTINGUISHING} {BETWEEN} {HEALTH} {PROTECTION} {AND} {HEALTH} {IMPROVEMENT}:},
	volume = {23},
	issn = {0967-0742, 1464-3790},
	shorttitle = {{LEGAL} {BASES} {FOR} {DISCLOSING} {CONFIDENTIAL} {PATIENT} {INFORMATION} {FOR} {PUBLIC} {HEALTH}},
	url = {https://academic.oup.com/medlaw/article-lookup/doi/10.1093/medlaw/fwv018},
	doi = {10.1093/medlaw/fwv018},
	language = {en},
	number = {3},
	urldate = {2017-08-14},
	journal = {Medical Law Review},
	author = {Taylor, Mark J.},
	month = sep,
	year = {2015},
	pages = {348--374},
}

@article{vayena_ethical_2015,
	title = {Ethical {Challenges} of {Big} {Data} in {Public} {Health}},
	volume = {11},
	issn = {1553-7358},
	url = {http://dx.plos.org/10.1371/journal.pcbi.1003904},
	doi = {10.1371/journal.pcbi.1003904},
	language = {en},
	number = {2},
	urldate = {2017-08-14},
	journal = {PLOS Computational Biology},
	author = {Vayena, Effy and Salathé, Marcel and Madoff, Lawrence C. and Brownstein, John S.},
	editor = {Bourne, Philip E.},
	month = feb,
	year = {2015},
	pages = {e1003904},
}

@article{denaxas_discussion_2015,
	title = {Discussion of “{Combining} {Health} {Data} {Uses} to {Ignite} {Health} {System} {Learning}”:},
	volume = {54},
	issn = {0026-1270},
	shorttitle = {Discussion of “{Combining} {Health} {Data} {Uses} to {Ignite} {Health} {System} {Learning}”},
	url = {http://www.schattauer.de/index.php?id=1214&doi=10.3414/ME15-12-0004},
	doi = {10.3414/ME15-12-0004},
	language = {en},
	number = {6},
	urldate = {2017-08-14},
	journal = {Methods of Information in Medicine},
	author = {Denaxas, S. and Friedman, C. P. and Geissbuhler, A. and Hemingway, H. and Kalra, D. and Kimura, M. and Kuhn, K. A. and Payne, H. A. and de Quiros, F. G. B. and Wyatt, J. C.},
	month = nov,
	year = {2015},
	pages = {488--499},
}

@article{bourne_confronting_2015,
	title = {Confronting the ethical challenges of big data in public health},
	volume = {11},
	url = {http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004073},
	number = {2},
	urldate = {2017-08-14},
	journal = {PLoS computational biology},
	author = {Bourne, Philip E.},
	year = {2015},
	pages = {e1004073},
}

@article{martin_commercialising_2015,
	title = {Commercialising neurofutures: {Promissory} economies, value creation and the making of a new industry},
	volume = {10},
	issn = {1745-8552, 1745-8560},
	shorttitle = {Commercialising neurofutures},
	url = {http://link.springer.com/10.1057/biosoc.2014.40},
	doi = {10.1057/biosoc.2014.40},
	language = {en},
	number = {4},
	urldate = {2017-02-08},
	journal = {BioSocieties},
	author = {Martin, Paul},
	month = dec,
	year = {2015},
	pages = {422--443},
}

@book{dove_biobanks_2015,
	title = {Biobanks, data sharing, and the drive for a global privacy governance framework},
	url = {http://journals.sagepub.com/doi/abs/10.1111/jlme.12311},
	urldate = {2017-08-14},
	publisher = {SAGE Publications Sage CA: Los Angeles, CA},
	author = {Dove, Edward S.},
	year = {2015},
}

@article{pope_whats_2014,
	title = {What’s the big fuss about ‘big data’?},
	volume = {19},
	issn = {1355-8196, 1758-1060},
	url = {http://journals.sagepub.com/doi/10.1177/1355819614521181},
	doi = {10.1177/1355819614521181},
	language = {en},
	number = {2},
	urldate = {2017-08-14},
	journal = {Journal of Health Services Research \& Policy},
	author = {Pope, Catherine and Halford, Susan and Tinati, Ramine and Weal, Mark},
	month = apr,
	year = {2014},
	pages = {67--68},
}

@article{bourne_what_2014,
	title = {What {Big} {Data} means to me},
	volume = {21},
	issn = {1067-5027, 1527-974X},
	url = {https://academic.oup.com/jamia/article-lookup/doi/10.1136/amiajnl-2014-002651},
	doi = {10.1136/amiajnl-2014-002651},
	language = {en},
	number = {2},
	urldate = {2017-08-14},
	journal = {Journal of the American Medical Informatics Association},
	author = {Bourne, Philip E},
	month = mar,
	year = {2014},
	pages = {194--194},
}

@article{davis_uk_2014,
	title = {{UK} {Biobank} is an opt-in model for the sharing of medical records},
	volume = {28},
	url = {http://journals.rcni.com/doi/pdfplus/10.7748/ns2014.03.28.27.35.s46},
	number = {27},
	urldate = {2017-08-14},
	journal = {Nursing Standard},
	author = {Davis, Joy},
	year = {2014},
	pages = {35--35},
}

@article{kambatla_trends_2014,
	title = {Trends in big data analytics},
	volume = {74},
	issn = {07437315},
	url = {http://linkinghub.elsevier.com/retrieve/pii/S0743731514000057},
	doi = {10.1016/j.jpdc.2014.01.003},
	language = {en},
	number = {7},
	urldate = {2017-08-14},
	journal = {Journal of Parallel and Distributed Computing},
	author = {Kambatla, Karthik and Kollias, Giorgos and Kumar, Vipin and Grama, Ananth},
	month = jul,
	year = {2014},
	pages = {2561--2573},
}

@article{de_rosa_role_2014,
	title = {The role of big data in health care decision making: an {Italian} experience},
	volume = {17},
	shorttitle = {The role of big data in health care decision making},
	url = {http://www.valueinhealthjournal.com/article/S1098-3015(14)00178-8/abstract},
	number = {3},
	urldate = {2017-08-14},
	journal = {Value in Health},
	author = {De Rosa, M. and Rossi, E. and Cataudella, S.},
	year = {2014},
	pages = {A20},
}

@article{lazer_parable_2014,
	title = {The {Parable} of {Google} {Flu}: {Traps} in {Big} {Data} {Analysis}},
	volume = {343},
	issn = {0036-8075, 1095-9203},
	shorttitle = {The {Parable} of {Google} {Flu}},
	url = {http://www.sciencemag.org/cgi/doi/10.1126/science.1248506},
	doi = {10.1126/science.1248506},
	language = {en},
	number = {6176},
	urldate = {2017-08-14},
	journal = {Science},
	author = {Lazer, D. and Kennedy, R. and King, G. and Vespignani, A.},
	month = mar,
	year = {2014},
	pages = {1203--1205},
}

@article{hoeksma_nhss_2014,
	title = {The {NHS}'s care.data scheme: what are the risks to privacy?},
	volume = {348},
	issn = {1756-1833},
	shorttitle = {The {NHS}'s care.data scheme},
	url = {http://www.bmj.com/cgi/doi/10.1136/bmj.g1547},
	doi = {10.1136/bmj.g1547},
	language = {en},
	number = {feb17 10},
	urldate = {2016-01-16},
	journal = {BMJ},
	author = {Hoeksma, J.},
	month = feb,
	year = {2014},
	pages = {g1547--g1547},
}

@article{margolis_national_2014,
	title = {The {National} {Institutes} of {Health}'s {Big} {Data} to {Knowledge} ({BD2K}) initiative: capitalizing on biomedical big data},
	volume = {21},
	issn = {1067-5027, 1527-974X},
	shorttitle = {The {National} {Institutes} of {Health}'s {Big} {Data} to {Knowledge} ({BD2K}) initiative},
	url = {https://academic.oup.com/jamia/article-lookup/doi/10.1136/amiajnl-2014-002974},
	doi = {10.1136/amiajnl-2014-002974},
	language = {en},
	number = {6},
	urldate = {2017-08-15},
	journal = {Journal of the American Medical Informatics Association},
	author = {Margolis, Ronald and Derr, Leslie and Dunn, Michelle and Huerta, Michael and Larkin, Jennie and Sheehan, Jerry and Guyer, Mark and Green, Eric D},
	month = nov,
	year = {2014},
	pages = {957--958},
}

@article{lupton_commodification_2014,
	title = {The commodification of patient opinion: the digital patient experience economy in the age of big data},
	volume = {36},
	issn = {01419889},
	shorttitle = {The commodification of patient opinion},
	url = {http://doi.wiley.com/10.1111/1467-9566.12109},
	doi = {10.1111/1467-9566.12109},
	language = {en},
	number = {6},
	urldate = {2017-08-14},
	journal = {Sociology of Health \& Illness},
	author = {Lupton, Deborah},
	month = jul,
	year = {2014},
	pages = {856--869},
}

@article{worst_case_2014,
	title = {The case of the “{Big} {Data}” revolution},
	volume = {30},
	url = {http://www.msm.nl/resources/uploads/2014/09/MSM-WP2014-34.pdf},
	number = {35},
	urldate = {2017-08-14},
	journal = {Working Papers},
	author = {Worst, Jan and {others}},
	year = {2014},
	pages = {119--141},
}

@article{nash_harnessing_2014,
	title = {Harnessing the power of big data in healthcare},
	volume = {7},
	url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4049118/},
	number = {2},
	urldate = {2017-08-14},
	journal = {American health \& drug benefits},
	author = {Nash, David B.},
	year = {2014},
	pages = {69},
}

@article{herbert_ethics_2014,
	title = {Ethics of {Care}.{Data}},
	volume = {56},
	issn = {1746-5702, 1746-5710},
	url = {https://academic.oup.com/itnow/article-lookup/doi/10.1093/itnow/bwu079},
	doi = {10.1093/itnow/bwu079},
	language = {en},
	number = {3},
	urldate = {2017-08-14},
	journal = {ITNOW},
	author = {Herbert, I.},
	month = sep,
	year = {2014},
	pages = {46--47},
}

@article{chessell_ethics_2014,
	title = {Ethics for big data and analytics},
	url = {http://www.ibmbigdatahub.com/sites/default/files/whitepapers_reports_file/TCG%20Study%20Report%20-%20Ethics%20for%20BD&A.pdf},
	urldate = {2017-08-14},
	journal = {Somers: IBM Corporation},
	author = {Chessell, Mandy},
	year = {2014},
}

@article{de_lusignan_effective_2014,
	title = {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},
	volume = {21},
	issn = {2058-4563, 2058-4555},
	url = {http://hijournal.bcs.org/index.php/jhi/article/view/68},
	doi = {10.14236/jhi.v21i2.68},
	number = {2},
	urldate = {2017-08-14},
	journal = {Journal of Innovation in Health Informatics},
	author = {De Lusignan, Simon},
	month = may,
	year = {2014},
	pages = {61--63},
}

@article{crawford_critiquing_2014,
	title = {Critiquing {Big} {Data}: {Politics}, {Ethics}, {Epistemology}.},
	volume = {8},
	shorttitle = {Critiquing {Big} {Data}},
	url = {http://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=19328036&AN=97249722&h=CClQlsBrwQw3w%2FnL%2BOsc1EYeMRncDQ9MJGwQxbjCbJ3%2BMtmkoCncSZpSzuVf1SmNzdHZ3NFUoErUAXZAv4tRXg%3D%3D&crl=c},
	urldate = {2017-08-14},
	journal = {International Journal of Communication (19328036)},
	author = {Crawford, Kate and Miltner, Kate and Gray, Mary L.},
	year = {2014},
}

@article{lloyd_consent_2014,
	title = {Consent for release of confidential information–ethics in context?},
	volume = {64},
	issn = {0962-7480, 1471-8405},
	url = {https://academic.oup.com/occmed/article-lookup/doi/10.1093/occmed/kqu067},
	doi = {10.1093/occmed/kqu067},
	language = {en},
	number = {6},
	urldate = {2017-08-14},
	journal = {Occupational Medicine},
	author = {Lloyd, S.},
	month = sep,
	year = {2014},
	pages = {398--399},
}

@article{harford_big_2014,
	title = {Big data: {A} big mistake?},
	volume = {11},
	shorttitle = {Big data},
	url = {http://onlinelibrary.wiley.com/doi/10.1111/j.1740-9713.2014.00778.x/full},
	number = {5},
	urldate = {2017-08-14},
	journal = {Significance},
	author = {Harford, Tim},
	year = {2014},
	pages = {14--19},
}

@article{khoury_big_2014,
	title = {Big data meets public health},
	volume = {346},
	issn = {0036-8075, 1095-9203},
	url = {http://www.sciencemag.org/cgi/doi/10.1126/science.aaa2709},
	doi = {10.1126/science.aaa2709},
	language = {en},
	number = {6213},
	urldate = {2017-08-14},
	journal = {Science},
	author = {Khoury, M. J. and Ioannidis, J. P. A.},
	month = nov,
	year = {2014},
	pages = {1054--1055},
}

@article{martin-sanchez_big_2014,
	title = {Big {Data} in {Medicine} {Is} {Driving} {Big} {Changes}:},
	volume = {9},
	issn = {0943-4747},
	shorttitle = {Big {Data} in {Medicine} {Is} {Driving} {Big} {Changes}},
	url = {http://www.schattauer.de/index.php?id=1214&doi=10.15265/IY-2014-0020},
	doi = {10.15265/IY-2014-0020},
	language = {en},
	number = {1},
	urldate = {2017-08-14},
	journal = {IMIA Yearbook},
	author = {Martin-Sanchez, F. and Verspoor, K.},
	year = {2014},
	pages = {14--20},
}

@article{weil_big_2014,
	title = {Big {Data} {In} {Health}: {A} {New} {Era} {For} {Research} {And} {Patient} {Care}},
	volume = {33},
	issn = {0278-2715, 1544-5208},
	shorttitle = {Big {Data} {In} {Health}},
	url = {http://content.healthaffairs.org/cgi/doi/10.1377/hlthaff.2014.0689},
	doi = {10.1377/hlthaff.2014.0689},
	language = {en},
	number = {7},
	urldate = {2017-08-14},
	journal = {Health Affairs},
	author = {Weil, A. R.},
	month = jul,
	year = {2014},
	pages = {1110--1110},
}

@article{bates_big_2014,
	title = {Big {Data} {In} {Health} {Care}: {Using} {Analytics} {To} {Identify} {And} {Manage} {High}-{Risk} {And} {High}-{Cost} {Patients}},
	volume = {33},
	issn = {0278-2715, 1544-5208},
	shorttitle = {Big {Data} {In} {Health} {Care}},
	url = {http://content.healthaffairs.org/cgi/doi/10.1377/hlthaff.2014.0041},
	doi = {10.1377/hlthaff.2014.0041},
	language = {en},
	number = {7},
	urldate = {2017-08-14},
	journal = {Health Affairs},
	author = {Bates, D. W. and Saria, S. and Ohno-Machado, L. and Shah, A. and Escobar, G.},
	month = jul,
	year = {2014},
	pages = {1123--1131},
}

@article{dhar_big_2014,
	title = {Big {Data} and {Predictive} {Analytics} in {Health} {Care}},
	volume = {2},
	issn = {2167-6461, 2167-647X},
	url = {http://online.liebertpub.com/doi/abs/10.1089/big.2014.1525},
	doi = {10.1089/big.2014.1525},
	language = {en},
	number = {3},
	urldate = {2017-08-14},
	journal = {Big Data},
	author = {Dhar, Vasant},
	month = sep,
	year = {2014},
	pages = {113--116},
}

@article{jagadish_big_2014,
	title = {Big data and its technical challenges},
	volume = {57},
	issn = {00010782},
	url = {http://dl.acm.org/citation.cfm?doid=2622628.2611567},
	doi = {10.1145/2611567},
	language = {en},
	number = {7},
	urldate = {2017-08-14},
	journal = {Communications of the ACM},
	author = {Jagadish, H. V. and Gehrke, Johannes and Labrinidis, Alexandros and Papakonstantinou, Yannis and Patel, Jignesh M. and Ramakrishnan, Raghu and Shahabi, Cyrus},
	month = jul,
	year = {2014},
	pages = {86--94},
}

@article{cavoukian_big_2014,
	title = {Big {Data} and innovation, setting the record straight: {De}-identification does {Work}},
	shorttitle = {Big {Data} and innovation, setting the record straight},
	url = {https://ecfsapi.fcc.gov/file/102058078475/2014-big-data-deidentification.pdf},
	urldate = {2017-08-14},
	journal = {White Paper, Jun},
	author = {Cavoukian, Ann and Castro, Daniel},
	year = {2014},
	pages = {20},
}

@article{neff_why_2013,
	title = {Why {Big} {Data} {Won}'t {Cure} {Us}},
	volume = {1},
	issn = {2167-6461, 2167-647X},
	url = {http://online.liebertpub.com/doi/abs/10.1089/big.2013.0029},
	doi = {10.1089/big.2013.0029},
	language = {en},
	number = {3},
	urldate = {2017-07-24},
	journal = {Big Data},
	author = {Neff, Gina},
	month = sep,
	year = {2013},
	pages = {117--123},
}

@article{munns_nhs_2013,
	title = {The {NHS} {Information} {Revolution}: ‘{Choice} of {Control}’ to ‘{Choice}’ \textit{and} ‘{Control}’},
	volume = {27},
	issn = {1360-0869, 1364-6885},
	shorttitle = {The {NHS} {Information} {Revolution}},
	url = {http://www.tandfonline.com/doi/abs/10.1080/13600869.2013.764132},
	doi = {10.1080/13600869.2013.764132},
	language = {en},
	number = {1-2},
	urldate = {2017-08-14},
	journal = {International Review of Law, Computers \& Technology},
	author = {Munns, Christina and Basu, Subhajit},
	month = jul,
	year = {2013},
	pages = {124--160},
}

@article{mchale_reforming_2013,
	title = {Reforming the regulation of health research in {England} and {Wales}: new challenges: new pitfalls},
	volume = {1},
	shorttitle = {Reforming the regulation of health research in {England} and {Wales}},
	url = {http://www.ingentaconnect.com/content/plp/jmle/2013/00000001/00000001/art00003},
	number = {1},
	urldate = {2017-08-14},
	journal = {Journal of Medical Law and Ethics},
	author = {McHale, Jean},
	year = {2013},
	pages = {23--42},
}

@article{pasquale_protecting_2013,
	title = {Protecting health privacy in an era of big data processing and cloud computing},
	volume = {17},
	url = {http://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/stantlr17&section=16},
	urldate = {2017-08-14},
	journal = {Stan. Tech. L. Rev.},
	author = {Pasquale, Frank and Ragone, Tara Adams},
	year = {2013},
	pages = {595},
}

@article{mittelstadt_ethical_2013,
	title = {On the {Ethical} {Implications} of {Personal} {Health} {Monitoring}},
	url = {https://www.dora.dmu.ac.uk/handle/2086/10101},
	urldate = {2017-08-14},
	author = {Mittelstadt, Brent},
	year = {2013},
}

@article{gymrek_identifying_2013,
	title = {Identifying {Personal} {Genomes} by {Surname} {Inference}},
	volume = {339},
	issn = {0036-8075, 1095-9203},
	url = {http://www.sciencemag.org/cgi/doi/10.1126/science.1229566},
	doi = {10.1126/science.1229566},
	language = {en},
	number = {6117},
	urldate = {2017-08-14},
	journal = {Science},
	author = {Gymrek, M. and McGuire, A. L. and Golan, D. and Halperin, E. and Erlich, Y.},
	month = jan,
	year = {2013},
	pages = {321--324},
}

@article{hazin_ethical_2013,
	title = {Ethical, legal, and social implications of incorporating genomic information into electronic health records},
	volume = {15},
	issn = {1098-3600, 1530-0366},
	url = {http://www.nature.com/doifinder/10.1038/gim.2013.117},
	doi = {10.1038/gim.2013.117},
	number = {10},
	urldate = {2017-08-14},
	journal = {Genetics in Medicine},
	author = {Hazin, Ribhi and Brothers, Kyle B. and Malin, Bradley A. and Koenig, Barbara A. and Sanderson, Saskia C. and Rothstein, Mark A. and Williams, Marc S. and Clayton, Ellen W. and Kullo, Iftikhar J.},
	month = oct,
	year = {2013},
	pages = {810--816},
}

@article{pathak_electronic_2013,
	title = {Electronic health records-driven phenotyping: challenges, recent advances, and perspectives},
	volume = {20},
	issn = {1067-5027, 1527-974X},
	shorttitle = {Electronic health records-driven phenotyping},
	url = {http://jamia.oxfordjournals.org/lookup/doi/10.1136/amiajnl-2013-002428},
	doi = {10.1136/amiajnl-2013-002428},
	language = {en},
	number = {e2},
	urldate = {2016-01-12},
	journal = {Journal of the American Medical Informatics Association},
	author = {Pathak, Jyotishman and Kho, Abel N and Denny, Joshua C},
	month = dec,
	year = {2013},
	pages = {e206--e211},
}

@article{halford_digital_2013,
	title = {Digital futures? {Sociological} challenges and opportunities in the emergent semantic web},
	volume = {47},
	shorttitle = {Digital futures?},
	url = {http://journals.sagepub.com/doi/abs/10.1177/0038038512453798},
	number = {1},
	urldate = {2017-08-14},
	journal = {Sociology},
	author = {Halford, Susan and Pope, Catherine and Weal, Mark},
	year = {2013},
	pages = {173--189},
}

@article{swinglehurst_computer_2012,
	title = {Computer templates in chronic disease management: ethnographic case study in general practice},
	volume = {2},
	issn = {2044-6055, 2044-6055},
	shorttitle = {Computer templates in chronic disease management},
	url = {http://bmjopen.bmj.com/lookup/doi/10.1136/bmjopen-2012-001754},
	doi = {10.1136/bmjopen-2012-001754},
	language = {en},
	number = {6},
	urldate = {2020-07-13},
	journal = {BMJ Open},
	author = {Swinglehurst, Deborah and Greenhalgh, Trisha and Roberts, Celia},
	year = {2012},
	pages = {e001754},
}

@article{huzair_uk_2012,
	title = {{UK} {Biobank}: {Consequences} for commons and innovation},
	volume = {39},
	issn = {0302-3427, 1471-5430},
	shorttitle = {{UK} {Biobank}},
	url = {https://academic.oup.com/spp/article-lookup/doi/10.1093/scipol/scs036},
	doi = {10.1093/scipol/scs036},
	language = {en},
	number = {4},
	urldate = {2017-08-14},
	journal = {Science and Public Policy},
	author = {Huzair, F. and Papaioannou, T.},
	month = aug,
	year = {2012},
	pages = {500--512},
}

@article{anesi_decrepit_2012,
	title = {The “decrepit concept” of confidentiality, 30 years later},
	volume = {14},
	url = {http://journalofethics.ama-assn.org/2012/09/jdsc1-1209.html},
	number = {9},
	urldate = {2017-08-14},
	journal = {Virtual Mentor},
	author = {Anesi, George L.},
	year = {2012},
	pages = {708},
}

@article{drucker_humanities_2011,
	title = {Humanities {Approaches} to {Graphical} {Display}},
	volume = {5},
	url = {http://digitalhumanities.org/dhq/vol/5/1/000091/000091.html},
	number = {1},
	journal = {Digital Humanities Quarterly},
	author = {Drucker, J.},
	year = {2011},
}

@book{aitken_linking_2011,
	address = {"Edinburgh},
	title = {Linking social care, housing and health data: social care clients' and patients' views},
	isbn = {978-1-78045-408-5},
	shorttitle = {"{Linking} social care, housing and health data},
	url = {http://www.nls.uk/scotgov/2011},
	language = {English},
	urldate = {2016-11-11},
	publisher = {Scottish Social Government Resaearch},
	author = {Aitken, Mhari},
	year = {2011},
	note = {OCLC: 780257485},
}

@article{gottweis_connecting_2011,
	title = {Connecting the public with biobank research: reciprocity matters},
	volume = {12},
	issn = {1471-0056, 1471-0064},
	shorttitle = {Connecting the public with biobank research},
	url = {http://www.nature.com/doifinder/10.1038/nrg3083},
	doi = {10.1038/nrg3083},
	number = {11},
	urldate = {2017-08-14},
	journal = {Nature Reviews Genetics},
	author = {Gottweis, Herbert and Gaskell, George and Starkbaum, Johannes},
	month = oct,
	year = {2011},
	pages = {738--739},
}

@article{brown_using_2010,
	title = {Using {NHS} {Patient} {Data} for {Research} {Without} {Consent}},
	volume = {2},
	issn = {17579961, 1757997X},
	url = {http://www.tandfonline.com/doi/full/10.5235/175799610794046186},
	doi = {10.5235/175799610794046186},
	language = {en},
	number = {2},
	urldate = {2017-08-14},
	journal = {Law, Innovation and Technology},
	author = {Brown, Ian and Brown, Lindsey and Korff, Douwe},
	month = dec,
	year = {2010},
	pages = {219--258},
}

@article{mitchell_national_2010,
	title = {National {Biobanks}: {Clinical} {Labor}, {Risk} {Production}, and the {Creation} of {Biovalue}},
	volume = {35},
	issn = {0162-2439, 1552-8251},
	shorttitle = {National {Biobanks}},
	url = {http://journals.sagepub.com/doi/10.1177/0162243909340267},
	doi = {10.1177/0162243909340267},
	language = {en},
	number = {3},
	urldate = {2017-08-14},
	journal = {Science, Technology, \& Human Values},
	author = {Mitchell, Robert and Waldby, Catherine},
	month = may,
	year = {2010},
	pages = {330--355},
}

@article{mattison_thompson_towards_2009,
	title = {Towards a {Privacy} {Framework}},
	url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1506917},
	urldate = {2017-08-14},
	author = {Mattison Thompson, Frauke and Smith, Andrew and Winklhofer, Heidi},
	year = {2009},
}

@article{chan_free_2009,
	title = {Free riders and pious sons--why science research remains obligatory},
	volume = {23},
	issn = {1467-8519},
	doi = {10.1111/j.1467-8519.2008.00648.x},
	abstract = {John Harris has previously proposed that there is a moral duty to participate in scientific research. This concept has recently been challenged by Iain Brassington, who asserts that the principles cited by Harris in support of the duty to research fail to establish its existence. In this paper we address these criticisms and provide new arguments for the existence of a moral obligation to research participation. This obligation, we argue, arises from two separate but related principles. The principle of fairness obliges us to support the social institutions which sustain us, of which research is one; while the principle of beneficence, or the duty of rescue, imposes upon us a duty to prevent harm to others, including by supporting potentially beneficial, even life-saving research. We argue that both these lines of argument support the duty to research, and explore further aspects of this duty, such as to whom it is owed and how it might be discharged.},
	language = {eng},
	number = {3},
	journal = {Bioethics},
	author = {Chan, Sarah and Harris, John},
	month = mar,
	year = {2009},
	pmid = {18445091},
	pmcid = {PMC3579232},
	keywords = {Biomedical Research, Humans, Moral Obligations, Philosophy, Medical},
	pages = {161--171},
}

John Harris has previously proposed that there is a moral duty to participate in scientific research. This concept has recently been challenged by Iain Brassington, who asserts that the principles cited by Harris in support of the duty to research fail to establish its existence. In this paper we address these criticisms and provide new arguments for the existence of a moral obligation to research participation. This obligation, we argue, arises from two separate but related principles. The principle of fairness obliges us to support the social institutions which sustain us, of which research is one; while the principle of beneficence, or the duty of rescue, imposes upon us a duty to prevent harm to others, including by supporting potentially beneficial, even life-saving research. We argue that both these lines of argument support the duty to research, and explore further aspects of this duty, such as to whom it is owed and how it might be discharged.

@article{ohm_broken_2009,
	title = {Broken promises of privacy: {Responding} to the surprising failure of anonymization},
	shorttitle = {Broken promises of privacy},
	url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1450006},
	urldate = {2017-08-14},
	author = {Ohm, Paul},
	year = {2009},
}

@article{mcguire_dna_2008,
	title = {{DNA} data sharing: research participants' perspectives},
	volume = {10},
	issn = {1098-3600, 1530-0366},
	shorttitle = {{DNA} data sharing},
	url = {http://www.nature.com/doifinder/10.1097/GIM.0b013e31815f1e00},
	doi = {10.1097/GIM.0b013e31815f1e00},
	number = {1},
	urldate = {2017-08-14},
	journal = {Genetics in Medicine},
	author = {McGuire, Amy L and Hamilton, Jennifer A and Lunstroth, Rebecca and McCullough, Laurence B and Goldman, Alica},
	month = jan,
	year = {2008},
	pages = {46--53},
}

@article{damschroder_patients_2007,
	title = {Patients, privacy and trust: {Patients}’ willingness to allow researchers to access their medical records},
	volume = {64},
	issn = {02779536},
	shorttitle = {Patients, privacy and trust},
	url = {http://linkinghub.elsevier.com/retrieve/pii/S0277953606004448},
	doi = {10.1016/j.socscimed.2006.08.045},
	language = {en},
	number = {1},
	urldate = {2017-08-15},
	journal = {Social Science \& Medicine},
	author = {Damschroder, Laura J. and Pritts, Joy L. and Neblo, Michael A. and Kalarickal, Rosemarie J. and Creswell, John W. and Hayward, Rodney A.},
	month = jan,
	year = {2007},
	pages = {223--235},
}

@article{krieger_data_2004,
	title = {Data, "race," and politics: a commentary on the epidemiological significance of {California}'s {Proposition} 54},
	volume = {58},
	issn = {0143-005X},
	shorttitle = {Data, "race," and politics},
	url = {http://jech.bmj.com/cgi/doi/10.1136/jech.2003.018549},
	doi = {10.1136/jech.2003.018549},
	language = {en},
	number = {8},
	urldate = {2020-07-13},
	journal = {Journal of Epidemiology \& Community Health},
	author = {Krieger, N.},
	month = aug,
	year = {2004},
	pages = {632--633},
}

@article{krieger_data_2004-1,
	title = {Data, "race," and politics: a commentary on the epidemiological significance of {California}'s {Proposition} 54},
	volume = {58},
	issn = {0143-005X},
	shorttitle = {Data, "race," and politics},
	url = {http://jech.bmj.com/cgi/doi/10.1136/jech.2003.018549},
	doi = {10.1136/jech.2003.018549},
	language = {en},
	number = {8},
	urldate = {2020-07-13},
	journal = {Journal of Epidemiology \& Community Health},
	author = {Krieger, N.},
	month = aug,
	year = {2004},
	pages = {632--633},
}

@article{krieger_making_1992,
	title = {The {Making} of {Public} {Health} {Data}: {Paradigms}, {Politics}, and {Policy}},
	volume = {13},
	issn = {01975897},
	shorttitle = {The {Making} of {Public} {Health} {Data}},
	url = {https://www.jstor.org/stable/3342531?origin=crossref},
	doi = {10.2307/3342531},
	number = {4},
	urldate = {2020-07-13},
	journal = {Journal of Public Health Policy},
	author = {Krieger, Nancy},
	year = {1992},
	pages = {412},
}

@article{davis_toward_nodate,
	title = {Toward the {Elimination} of {Subjectivity}: {From} {Francis} {Bacon} to {AI}.},
	volume = {86},
	url = {https://muse.jhu.edu/article/748881},
	number = {4},
	journal = {Social Research: An International Quarterly},
	author = {Davis, L.E.},
	pages = {845--869},
}