Big medical data analytics is a new and unique opportunity for national health systems to reduce costs and improve population health management. The processing of vast amounts of medical histories from electronic patient records can provide researchers, clinicians, policy makers and private health companies with invaluable insights into all aspects of health and illness. New treatments, medication regimens and medical technologies can then be developed based on more accurate cost/benefit analyses. Importantly, it constitutes national health systems engines of economic growth. The European Commission is actively promoting a ‘Digital Agenda for Europe’, where more ‘Open (Government) Data’ will support and accelerate the development of ‘A Thriving Data-Driven Economy’. However, the European Agency for Fundamental Rights is working to address social, legal and ethical implications from surveillance activities and data protection mishaps, particularly for personal health information.

The aim of the BIMEDA project is to elaborate a theoretical framework for critically analysing social, technical and ethical challenges from big medical data analytics, through the mapping of the data protection controversy of the Care.data programme and the qualitative study of organisations that perform big primary care data analytics as well as of GPs and citizens who decide to opt out from big medical databases. It brings together a talented researcher with background in qualitative research of clinical information systems’ implementation and use from a Science and Technology Studies perspective to work with an internationally renowned host institution (University of Nottingham) in big primary care data analytics and, healthcare organisations and (Horizon) Digital Economy research in order to identify and clarify, for policy-makers and the public, possibilities, limitations, assumptions and biases in research, knowledge production and ethical conduct.

Big medical data offers new opportunities and conditions of ‘learning’. Healthcare professionals can use the data they already collect about their patients and services and make better clinical and managerial decisions without having to wait for the results of other studies to apply new knowledge [1]. In Europe, several EC and EPSRC funded projects are already demonstrating the power of big, integrated, data repositories in developing ICT platforms for reducing unhealthy lifestyles (daphne-fp7.eu), sharing electronic medical histories (linked2safety-project.eu), managing traumatic brain injuries (tbicare.eu), personalising medicine in paediatrics (md-paedigree.eu, health-e-child.org, sim-e-child.org) and improving the monitoring of patients after kidney transplantation [2]. 

However, big data in healthcare is a relatively new field of scientific research. While they hold great promise to transform healthcare and benefit patients, they have not yet demonstrated cost-benefit value. The actual big datasets are anything but comprehensive, and are even more prone to statistical errors. We cannot overcome sampling bias by simply sampling everything, particularly as statisticians are still scrambling to develop new methods for big data analytics [3].

Importantly, several technical, social, privacy and consent challenges remain. They must be addressed before they can fully influence health and social care [4], particularly via national and federal regulations around research on human subjects and the protection of health information [5]. 

References

1. Sebastian S. Learning from Big Health Care Data. N Engl J Med 2014; 370:2161-2163.
   
2. Krivov SV, Fenton H, Goldsmith PJ, et al. (2014) Optimal Reaction Coordinate as a Biomarker for the Dynamics of Recovery from Kidney Transplant. PLoS Comput Biol 10(6): e1003685.
   
3. Leonelli S. What difference does quantity make? On the epistemology of Big Data in biology. Big Data & Society 2014; 1(1), 2053951714534395.
   
4. Weber GM, Mandl KD, Kohane IS. Finding the Missing Link for Big Biomedical Data. JAMA 2014. doi:10.1001/jama.2014.4228
   
5. Cohen IG, Amarasingham R, Shah A, Xie B, Lo B. The Legal And Ethical Concerns That Arise From Using Complex Predictive Analytics In Health Care. Health Aff 2014, 33:71139-1147. 

General Research Question

While (predictive) big data analytics hold great promise for population health management, several technical, social, ethical and legal challenges must be addressed before they can fully influence health and social care. 

Ethnography

The application of ethnographic methods from a Science & Technology Studies’ perspective, particularly Actor-Network Theory [1], is essential to investigate the aspirations and motivations as well as the concerns of organisations involved in the development and processing of big medical datasets.

Ethnography, as a method of studying and learning about groups of people in their own environment, rather than looking for small sets of variables across a large number of people, can lead the empirical researcher to results that are scientific and uncover complexities and unintended consequences particularly of technology implementation and use [2] as part of health IT projects’ evaluations [3].

Actor-Network Theory 

ANT offers a researcher a set of methodological principles for more detached, objective, value-free but also rich descriptions of rationales behind technological innovations as they attempt to become part of everyday life. It specifically focuses on three issues: (a) the network of the users and the technology, (b) the content of the technology, and (c) the trajectory of the technology’s historical development [4]. It is also informed by the concept of translation to emphasise the focus on tracing and describing the process by which a set of actors (research subjects) attempt to form a strong network of use around that particular technology. This process, during which actors, interactions, interests, controversies, negotiations, associations and behaviours are identified, resolved and agreed, is the fundamental focus of an ANT researcher who strives to understand how power, a theory or truth is performed and, then, sustained through these durable networks. For this, the ANT researcher also has to adopt three methodological principles [5]. The first deals with the nature of the actor, which can be either human (users) or non-human (technologies), asserting that this is[irrelevant to the inquiry (agnosticism). 

ETHICS COMMITTEE AND REGULATORY APPROVALS

The study will not be initiated before the protocol, consent forms and participant information sheets have received approval / favourable opinion from the Nottingham University Business School Research Ethics Committee (NUBS REC), and the respective National Health Service (NHS) Research & Development (R&D) department. Should a protocol amendment be made that requires REC approval, the changes in the protocol will not be instituted until the amendment and revised informed consent forms and participant information sheets have been reviewed and received approval / favourable opinion from the REC and R&D departments. A protocol amendment intended to eliminate an apparent immediate hazard to participants may be implemented immediately providing that the REC are notified as soon as possible and an approval is requested. Minor protocol amendments only for logistical or administrative changes may be implemented immediately; and the REC will be informed.

The study will be conducted in accordance with the ethical principles that have their origin in the Declaration of Helsinki, 1996; the principles of Good Clinical Practice, and the Department of Health Research Governance Framework for Health and Social care, 2005.

INFORMED CONSENT AND PARTICIPANT INFORMATION

The process for obtaining participant informed consent will be in accordance with the REC guidance, and Good Clinical Practice (GCP) and any other regulatory requirements that might be introduced. The investigator and the participant shall both sign and date the Consent Form before the person can participate in the study.

The participant will receive a copy of the signed and dated forms and the original will be retained in the Study records.

The decision regarding participation in the study is entirely voluntary. The investigator shall emphasize to them that consent regarding study participation may be withdrawn at any time without penalty or affecting their employment status, or loss of benefits to which the participant is otherwise entitled. No interviews will be conducted before informed consent has been obtained.

The investigator will inform the participant of any relevant information that becomes available during the course of the study, and will discuss with them, whether they wish to continue with the study. If applicable they will be asked to sign revised consent forms.

If the Consent Form is amended during the study, the investigator shall follow all applicable regulatory requirements pertaining to approval of the amended Consent Form by the REC and use of the amended form (including for ongoing participants).

RECORDS

Interview Transcripts

Each participant will be assigned a study identity code number, for use on study documents. The documents will also use their initials (of first and last names separated by a hyphen or a middle name initial when available).

Interview transcripts will be treated as confidential documents and held securely in accordance with regulations. The investigator will make a separate confidential record of the participant’s name and Participant Study Number, to permit identification of all participants enrolled in the study, in case additional follow-up is required.

Interview transcripts shall be restricted to those personnel approved by the Chief Investigator and recorded as such in the study records.

All paper forms shall be filled in using black ballpoint pen. Errors shall be lined out but not obliterated by using correction fluid and the correction inserted, initialled and dated.

Source documents

Source documents shall be filed at the investigator’s site and may include but are not limited to, consent forms, study records, field notes, interview transcriptions and audio records. Only study staff shall have access to study documentation other than the regulatory requirements listed below.

Direct access to source data / documents

All source documents shall made be available at all times for review by the Chief Investigator (CI), Sponsor’s designee and inspection by relevant regulatory authorities.

DATA PROTECTION

The CI will endeavour to protect the rights of the study’s participants to privacy and informed consent, and will adhere to the Data Protection Act, 1998. The CI will only collect the minimum required information for the purposes of the study. Interview transcripts and audio files will be held securely, in a locked room, or locked cupboard or cabinet. Access to the information will be limited to the CI and any relevant regulatory authorities (see above). Computer held data will be held securely and password protected. All data will be stored on a secure dedicated web server. Access will be restricted by user identifiers and passwords (encrypted using a one way encryption method).

Information about the study in the participant’s interview record will be treated confidentially in the same way as all other confidential information.

Electronic data will be backed up every 24 hours to both local and remote media in encrypted format.

Communication and public engagement strategy of the action

Dissemination and exploitation of the research results, and intellectual property