A data flow process for confidential data and its application in a health research project

BACKGROUND

The use of linked healthcare data in research has the potential to make major contributions to knowledge generation and service improvement. However, using healthcare data for secondary purposes raises legal and ethical concerns relating to confidentiality, privacy and data protection rights. Using a linkage and anonymisation approach that processes data lawfully and in line with ethical best practice to create an anonymous (non-personal) dataset can address these concerns, yet there is no set approach for defining all of the steps involved in such data flow end-to-end. We aimed to define such an approach with clear steps for dataset creation, and to describe its utilisation in a case study linking healthcare data.

METHODS

We developed a data flow protocol that generates pseudonymous datasets that can be reversibly linked, or irreversibly linked to form an anonymous research dataset. It was designed and implemented by the Comprehensive Patient Records (CPR) study in Leeds, UK.

RESULTS

We defined a clear approach that received ethico-legal approval for use in creating an anonymous research dataset. Our approach used individual-level linkage through a mechanism that is not computer-intensive and was rendered irreversible to both data providers and processors. We successfully applied it in the CPR study to hospital and general practice and community electronic health record data from two providers, along with patient reported outcomes, for 365,193 patients. The resultant anonymous research dataset is available via DATA-CAN, the Health Data Research Hub for Cancer in the UK.

CONCLUSIONS

Through ethical, legal and academic review, we believe that we contribute a defined approach that represents a framework that exceeds current minimum standards for effective pseudonymisation and anonymisation. This paper describes our methods and provides supporting information to facilitate the use of this approach in research.

Paths to social licence for tracking-data analytics in university research and services

While tracking-data analytics can be a goldmine for institutions and companies, the inherent privacy concerns also form a legal, ethical and social minefield. We present a study that seeks to understand the extent and circumstances under which tracking-data analytics is undertaken with social licence-that is, with broad community acceptance beyond formal compliance with legal requirements. Taking a University campus environment as a case, we enquire about the social licence for Wi-Fi-based tracking-data analytics. Staff and student participants answered a questionnaire presenting hypothetical scenarios involving Wi-Fi tracking for university research and services. Our results present a Bayesian logistic mixed-effects regression of acceptability judgements as a function of participant ratings on 11 privacy dimensions. Results show widespread acceptance of tracking-data analytics on campus and suggest that trust, individual benefit, data sensitivity, risk of harm and institutional respect for privacy are the most predictive factors determining this acceptance judgement.

Developing a System for Processing Health Data of Children Using Digitalized Toys: Ethical and Privacy Concerns for the Internet of Things Paradigm

EDUCERE (Ubiquitous Detection Ecosystem to Care and Early Stimulation for Children with Developmental Disorders) is a government funded research and development project. EDUCERE objectives are to investigate, develop, and evaluate innovative solutions for society to detect changes in psychomotor development through the natural interaction of children with toys and everyday objects, and perform stimulation and early attention activities in real environments such as home and school. In the EDUCERE project, an ethical impact assessment is carried out linked to a minors' data protection rights. Using a specific methodology, the project has achieved some promising results. These include use of a prototype of smart toys to detect development difficulties in children. In addition, privacy protection measures which take into account the security concerns of health data, have been proposed and applied. This latter security framework could be useful in other Internet of Things related projects. It consists of legal and technical measures. Special attention has been placed in the transformation of bulk data such as acceleration and jitter of toys into health data when patterns of atypical development are found. The article describes the different security profiles in which users are classified.

Framework for setting up and operating biobanks

With regard to the use of bio materials, there is a great need for clarification of the legal ramifications. And since procuring and storing bio materials is becoming an increasingly important point for answering molecular-genetic questions within medical research, finding an answer soon for the related legal and organisational questions is extremely important. This article examines the modern uses of bio materials, suitable types of legal entity for biobanks as well as questions related to ownership of samples.