Who Owns the Data? Open Data for Healthcare.

Research on large shared medical datasets and data-driven research are gaining fast momentum and provide major opportunities for improving health systems as well as individual care. Such open data can shed light on the causes of disease and effects of treatment, including adverse reactions side-effects of treatments, while also facilitating analyses tailored to an individual's characteristics, known as personalized or "stratified medicine." Developments, such as crowdsourcing, participatory surveillance, and individuals pledging to become "data donors" and the "quantified self" movement (where citizens share data through mobile device-connected technologies), have great potential to contribute to our knowledge of disease, improving diagnostics, and delivery of -healthcare and treatment. There is not only a great potential but also major concerns over privacy, confidentiality, and control of data about individuals once it is shared. Issues, such as user trust, data privacy, transparency over the control of data ownership, and the implications of data analytics for personal privacy with potentially intrusive inferences, are becoming increasingly scrutinized at national and international levels. This can be seen in the recent backlash over the proposed implementation of care.data, which enables individuals' NHS data to be linked, retained, and shared for other uses, such as research and, more controversially, with businesses for commercial exploitation. By way of contrast, through increasing popularity of social media, GPS-enabled mobile apps and tracking/wearable devices, the IT industry and MedTech giants are pursuing new projects without clear public and policy discussion about ownership and responsibility for user-generated data. In the absence of transparent regulation, this paper addresses the opportunities of Big Data in healthcare together with issues of responsibility and accountability. It also aims to pave the way for public policy to support a balanced agenda that safeguards personal information while enabling the use of data to improve public health.

Understanding quality improvement at scale in general practice: a qualitative evaluation of a COPD improvement programme.

BACKGROUND: A growing body of knowledge exists to guide efforts to improve the organisation and delivery of health care, most of which is based on work carried out in hospitals. It is uncertain how transferable this knowledge is to primary care. AIM: To understand the enablers and constraints to implementing a large-scale quality improvement programme in general practice, designed to improve care for people with chronic obstructive pulmonary disease. DESIGN AND SETTING: A qualitative study of 189 general practices in a socioeconomically and ethnically-mixed, urban area in east London, UK. METHOD: Twelve semi-structured interviews were conducted with people leading the programme and 17 in-depth interviews with those participating in it. Participants were local health system leaders, clinicians, and managers. A theoretical framework derived from evidence-based guidance for improvement programmes was used to interpret the findings. A complex improvement intervention took place with social and technical elements including training and mentorship, guidance, analytical tools, and data feedback. RESULTS: Practice staff wanted to participate in and learn from well-designed collaborative improvement projects. Nevertheless, there were limitations in the capacities and capabilities of the workforce to undertake systematic improvement, significant problems with access to and the quality of data, and tensions between the narrative-based generalist orientation of many primary care clinicians and the quantitative single-disease orientation that has characterised much of the quality improvement movement to date. CONCLUSION: Improvement guidance derived largely from hospital-based studies is, for the most part, applicable to improvement efforts in primary care settings, although large-scale change in general practice presents some particular challenges. These need to be better understood and addressed if improvement initiatives are to be effective.

Patients' online access to their electronic health records and linked online services: a systematic interpretative review.

OBJECTIVES: To investigate the effect of providing patients online access to their electronic health record (EHR) and linked transactional services on the provision, quality and safety of healthcare. The objectives are also to identify and understand: barriers and facilitators for providing online access to their records and services for primary care workers; and their association with organisational/IT system issues. SETTING: Primary care. PARTICIPANTS: A total of 143 studies were included. 17 were experimental in design and subject to risk of bias assessment, which is reported in a separate paper. Detailed inclusion and exclusion criteria have also been published elsewhere in the protocol. PRIMARY AND SECONDARY OUTCOME MEASURES: Our primary outcome measure was change in quality or safety as a result of implementation or utilisation of online records/transactional services. RESULTS: No studies reported changes in health outcomes; though eight detected medication errors and seven reported improved uptake of preventative care. Professional concerns over privacy were reported in 14 studies. 18 studies reported concern over potential increased workload; with some showing an increase workload in email or online messaging; telephone contact remaining unchanged, and face-to face contact staying the same or falling. Owing to heterogeneity in reporting overall workload change was hard to predict. 10 studies reported how online access offered convenience, primarily for more advantaged patients, who were largely highly satisfied with the process when clinician responses were prompt. CONCLUSIONS: Patient online access and services offer increased convenience and satisfaction. However, professionals were concerned about impact on workload and risk to privacy. Studies correcting medication errors may improve patient safety. There may need to be a redesign of the business process to engage health professionals in online access and of the EHR to make it friendlier and provide equity of access to a wider group of patients. A1 SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42012003091.

The provision and impact of online patient access to their electronic health records (EHR) and transactional services on the quality and safety of health care: systematic review protocol.

BACKGROUND: Innovators have piloted improvements in communication, changed patterns of practice and patient empowerment from online access to electronic health records (EHR). International studies of online services, such as prescription ordering, online appointment booking and secure communications with primary care, show good uptake of email consultations, accessing test results and booking appointments; when technologies and business process are in place. Online access and transactional services are due to be rolled out across England by 2015; this review seeks to explore the impact of online access to health records and other online services on the quality and safety of primary health care. OBJECTIVE: To assess the factors that may affect the provision of online patient access to their EHR and transactional services, and the impact of such access on the quality and safety of health care. METHOD: Two reviewers independently searched 11 international databases during the period 1999-2012. A range of papers including descriptive studies using qualitative or quantitative methods, hypothesis-testing studies and systematic reviews were included. A detailed eligibility criterion will be used to shape study inclusion. A team of experts will review these papers for eligibility, extract data using a customised extraction form and use the Grading of Recommendations Assessment, Development and Evaluation (GRADE) instrument to determine the quality of the evidence and the strengths of any recommendation. Data will then be descriptively summarised and thematically synthesised. Where feasible, we will perform a quantitative meta-analysis. Prospero (International Prospective Register of Systematic Reviews) registration number: crd42012003091.

Low-cost three-channel video for assessment of the clinical consultation.

Single-channel video is an established method for assessing the clinical consultation; however, it has limitations. While previous research has concluded that three-channel video recording of clinical consultations offers advantages, using professional equipment made costs prohibitive. In this study we set out to establish whether the benefits of three-channel video could be achieved using low-budget consumer-level equipment. Using a kit assembled for around euro 1000, we produced three-channel video recordings of simulated consultations. We then showed single- and three-channel versions of the videos to a panel of health professionals and recorded their opinions regarding the quality of the material and the level of information presented. We found that our budget three-channel set-up provided the same advantages as professional three-channel video, while the cost and complexity of the process was minimal. It is now affordable as well as feasible to use a budget set-up three-channel video system for training clinicians and assessing the impact of the computer on the consultation.

The feasibility of using UML to compare the impact of different brands of computer system on the clinical consultation.

BACKGROUND: UK general practice is universally computerised, with computers used in the consulting room at the point of care. Practices use a range of different brands of computer system, which have developed organically to meet the needs of general practitioners and health service managers. Unified Modelling Language (UML) is a standard modelling and specification notation widely used in software engineering. OBJECTIVE: To examine the feasibility of UML notation to compare the impact of different brands of general practice computer system on the clinical consultation. METHOD: Multi-channel video recordings of simulated consultation sessions were recorded on three different clinical computer systems in common use (EMIS, iSOFT Synergy and IPS Vision). User action recorder software recorded time logs of keyboard and mouse use, and pattern recognition software captured non-verbal communication. The outputs of these were used to create UML class and sequence diagrams for each consultation. We compared 'definition of the presenting problem' and 'prescribing', as these tasks were present in all the consultations analysed. RESULTS: Class diagrams identified the entities involved in the clinical consultation. Sequence diagrams identified common elements of the consultation (such as prescribing) and enabled comparisons to be made between the different brands of computer system. The clinician and computer system interaction varied greatly between the different brands. CONCLUSIONS: UML sequence diagrams are useful in identifying common tasks in the clinical consultation, and for contrasting the impact of the different brands of computer system on the clinical consultation. Further research is needed to see if patterns demonstrated in this pilot study are consistently displayed.