Commercial use of health data in the dock – results of a public “trial”

IntroductionSurveys suggest that there is a dichotomy in how citizens view research for public good and research for commercial gain. As a consequence, the idea that a research initiative, such as a learning health system, for both public and commercial benefit may be controversial and reduce public trust. Objectives and ApproachThis study aims to investigate what informed citizens considered to be appropriate uses of health data in a learning health system. Two paired four-day juries were run, with different jurors but the same purpose, expert witnesses and facilitators. Overall, 694 people applied to be jurors; 36 were selected to match criteria based on national demographics and their prior privacy views. Jurors considered whether and why eight exemplar data uses of depersonalised patient data were acceptable. The exemplars were data uses planned by the learning health system initiative to improve care pathways (planned uses), and possible unplanned data uses. ResultsAll planned uses were considered appropriate by most, but not all, jurors, as they had the potential of benefitting the public through improving care. Positive health outcomes were more acceptable than improved efficiency of services, given jurors prior beliefs about how the NHS operates raising concerns about whether improving efficiency would lead to inequitable distribution or closure of services. The potential uses were considered appropriate where there were improvements in drugs, treatments, or lower NHS costs. Some jurors became more accepting of commercial uses as they understood them better. Commercial uses that prioritised generating profit and did not produce health benefits for the public were unacceptable, regardless of any safeguards for the data. Commercial gain that occurred secondary to achieving public benefit were generally accepted. Conclusion/ImplicationsJuries elicit more informed and nuanced judgement from citizens than surveys. Jurors tended to be more accepting of data sharing to both private and public sector after the jury process. Many jurors accept commercial gain if public benefit is achieved. Some were suspicious of data sharing for efficiency gains.

Improving care for older people with long-term conditions and social care needs in Salford: the CLASSIC mixed-methods study, including RCT

Background

The Salford Integrated Care Programme (SICP) was a large-scale transformation project to improve care for older people with long-term conditions and social care needs. We report an evaluation of the ability of the SICP to deliver an enhanced experience of care, improved quality of life, reduced costs of care and improved cost-effectiveness.

Objectives

To explore the process of implementation of the SICP and the impact on patient outcomes and costs.

Design

Qualitative methods (interviews and observations) to explore implementation, a cohort multiple randomised controlled trial to assess patient outcomes through quasi-experiments and a formal trial, and an analysis of routine data sets and appropriate comparators using non-randomised methodologies.

Setting

Salford in the north-west of England.

Participants

Older people aged ≥ 65 years, carers, and health and social care professionals.

Interventions

A large-scale integrated care project with three core mechanisms of integration (community assets, multidisciplinary groups and an ‘integrated contact centre’).

Main outcome measures

Patient self-management, care experience and quality of life, and health-care utilisation and costs.

Data sources

Professional and patient interviews, patient self-report measures, and routine quantitative data on service utilisation.

Results

The SICP and subsequent developments have been sustained by strong partnerships between organisations. The SICP achieved ‘functional integration’ through the pooling of health and social care budgets, the development of the Alliance Agreement between four organisations and the development of the shared care record. ‘Service-level’ integration was slow and engagement with general practice was a challenge. We saw only minor changes in patient experience measures over the period of the evaluation (both improvements and reductions), with some increase in the use of community assets and care plans. Compared with other sites, the difference in the rates of admissions showed an increase in emergency admissions. Patient experience of health coaching was largely positive, although the effects of health coaching on activation and depression were not statistically significant. Economic analyses suggested that coaching was likely to be cost-effective, generating improvements in quality of life [mean incremental quality-adjusted life-year gain of 0.019, 95% confidence interval (CI) –0.006 to 0.043] at increased cost (mean incremental total cost increase of £150.58, 95% CI –£470.611 to £711.776).

Limitations

The Comprehensive Longitudinal Assessment of Salford Integrated Care study represents a single site evaluation, with consequent limits on external validity. Patient response rates to the cohort survey were < 40%.

Conclusions

The SICP has been implemented in a way that is consistent with the original vision. However, there has been more rapid success in establishing new integrated structures (such as a formal integrated care organisation), rather than in delivering mechanisms of integration at sufficient scale to have a large impact on patient outcomes.

Future work

Further research could focus on each of the mechanisms of integration. The multidisciplinary groups may require improved targeting of patients or disease subgroups to demonstrate effectiveness. Development of a proven model of health coaching that can be implemented at scale is required, especially one that would provide cost savings for commissioners or providers. Similarly, further exploration is required to assess the longer-term benefits of community assets and whether or not health impacts translate to reductions in care use.

Trial registration

Current Controlled Trials ISRCTN12286422.

Funding

This project was funded by the NIHR Health Services and Delivery Research programme and will be published in full inHealth Services and Delivery Research; Vol. 6, No. 31. See the NIHR Journals Library website for further project information.

Actissist: Proof-of-Concept Trial of a Theory-Driven Digital Intervention for Psychosis

BACKGROUND

Timely access to intervention for psychosis is crucial yet problematic. As such, health care providers are forming digital strategies for addressing mental health challenges. A theory-driven digital intervention that monitors distressing experiences and provides real-time active management strategies could improve the speed and quality of recovery in psychosis, over and above conventional treatments. This study assesses the feasibility and acceptability of Actissist, a digital health intervention grounded in the cognitive model of psychosis that targets key early psychosis domains.

METHODS

A proof-of-concept, single, blind, randomized controlled trial of Actissist, compared to a symptom-monitoring control. Thirty-six early psychosis patients were randomized on a 2:1 ratio to each arm of the trial. Actissist was delivered via a smartphone app over 12-weeks; clinical and functional assessment time-points were baseline, post-treatment and 22-weeks. Assessors' blind to treatment condition conducted the assessments. Acceptability was examined using qualitative methods.

RESULTS

Actissist was feasible (75% participants used Actissist at least once/day; uptake was high, 97% participants remained in the trial; high follow-up rates), acceptable (90% participants recommend Actissist), and safe (0 serious adverse events), with high levels of user satisfaction. Treatment effects were large on negative symptoms, general psychotic symptoms and mood. The addition of Actissist conferred benefit at post-treatment assessment over routine symptom-monitoring and treatment as usual.

CONCLUSIONS

This is the first controlled proof-of-concept trial of a theory-driven digital health intervention for early psychosis. Actissist is feasible and acceptable to early psychosis patients, with a strong signal for treatment efficacy. Trial Registration: ISRCTN: 34966555.

Addressing the Socio-Technical Challenges of Health Information Exchange Adoption: DataWell in Greater Manchester

Several high profile, problematic UK health data-sharing projects have shaped NHS professionals' and the public's opinion about NHS data-sharing projects, and there is a substantial body of evidence identifying barriers to Health Information Exchange (HIE) adoption. Socio-technical factors are a significant consideration and this paper describes the approach taken to address these concerns in the design and implementation of a HIE for Greater Manchester.

Patient understanding of genetic information influences reproductive decision making in retinoblastoma

BACKGROUND

Retinoblastoma is the most common malignant tumour of the eye in childhood, with nearly all bilateral tumours and around 17% to 18% of unilateral tumours due to an oncogenic mutation in the RB1 gene in the germline. Genetic testing enables accurate risk assessment and optimal clinical management for the affected individual, siblings, and future offspring.

MATERIAL AND METHODS

We carried out the first UK-wide audit of understanding of genetic testing in individuals with retinoblastoma. A total of 292 individuals aged 16 to 45 years were included.

RESULTS

Patients with bilateral disease were significantly more likely to understand the implications of retinoblastoma for siblings and children. There was a significant association between not knowing the results of genetic testing or not understanding the implications and not having children, particularly in women. Surprisingly, this was also true for individuals treated for unilateral disease with a low risk of retinoblastoma for their offspring.

CONCLUSION

We are concerned that individuals may be making life choices based on insufficient information regarding risks of retinoblastoma and reproductive options. We suggest that improvement in transition care is needed to enable individuals to make informed reproductive decisions and to ensure optimal care for children born at risk of retinoblastoma.

Tea, talk and technology: patient and public involvement to improve connected health 'wearables' research in dementia

PLAIN ENGLISH SUMMARY

There are a growing number of mobile phones, watches and electronic devices which can be worn on the body to track aspects of health and well-being, such as daily steps, sleep and exercise. Dementia researchers think that these devices could potentially be used as part of future research projects, for example to help spot changes in daily activity that may signal the early symptoms of dementia. We asked a range of older people, including people living with dementia and their carers, to participate in interactive discussions about how future participants might find using these devices as part of research projects. We also invited volunteers to borrow a range of devices to test at home, giving them further insights. Discussions revealed that people were generally supportive of this type of research, provided they gave informed consent and that devices were discreet, comfortable and easy to use. They also valued technical support and regular feedback on study progress to encourage ongoing participation. These findings were used to develop a pool of devices for researchers, with computer software and written guidance to help plan, design and support studies. Our work shows that when given the right opportunities, people who are affected by dementia can provide valuable insights that can enhance the design, delivery and quality of future research.

ABSTRACT

Background Increasingly, researchers are recognising the potential for connected health devices, including smartphones and smartwatches, to generate high resolution data about patterns of daily activity and health outcomes. One aim of the Dementias Platform UK (DPUK) project is to provide researchers with a secure means to collect, collate and link data generated by such devices, thereby accelerating this type of research in the field of dementia. We aimed to involve members of the public in discussions about the acceptability and feasibility of different devices and research designs to inform the development of a device pool, software platform and written guidance to support future studies. Methods Over 30 people attended a series of interactive workshops, drop-in sessions and meetings in Greater Manchester. This included people living with dementia and cognitive impairments, carers and people without memory problems. Discussions were tailored to suit different audiences and focused on the feasibility and acceptability of a range of different wearable devices and research designs. We also invited volunteers to borrow a device to test at home, enabling further insights from hands-on interactions with devices. Results Discussions revealed that people were supportive of connected health dementia research in principle, provided they gave informed consent and that devices were discreet, comfortable and easy to use. Moreover, they recommended technical support and regular feedback on study progress to encourage ongoing participation. Conclusion By using a range of discussion-based and practical activities, we found it was feasible to involve people affected by dementia and use their insights to shape the development of a software platform and device pool to support future connected health dementia research. We recommend that researchers planning such studies in future pay adequate attention to designing suitable participant information, technical support and mechanisms of providing study progress updates to support sustained engagement from participants.

Derivation and validation of a universal vital assessment (UVA) score: a tool for predicting mortality in adult hospitalised patients in sub-Saharan Africa

Background

Critical illness is a leading cause of morbidity and mortality in sub-Saharan Africa (SSA). Identifying patients with the highest risk of death could help with resource allocation and clinical decision making. Accordingly, we derived and validated a universal vital assessment (UVA) score for use in SSA.

Methods

We pooled data from hospital-based cohort studies conducted in six countries in SSA spanning the years 2009–2015. We derived and internally validated a UVA score using decision trees and linear regression and compared its performance with the modified early warning score (MEWS) and the quick sepsis-related organ failure assessment (qSOFA) score.

Results

Of 5573 patients included in the analysis, 2829 (50.8%) were female, the median (IQR) age was 36 (27–49) years, 2122 (38.1%) were HIV-infected and 996 (17.3%) died in-hospital. The UVA score included points for temperature, heart and respiratory rates, systolic blood pressure, oxygen saturation, Glasgow Coma Scale score and HIV serostatus, and had an area under the receiver operating characteristic curve (AUC) of 0.77 (95% CI 0.75 to 0.79), which outperformed MEWS (AUC 0.70 (95% CI 0.67 to 0.71)) and qSOFA (AUC 0.69 (95% CI 0.67 to 0.72)).

Conclusion

We identified predictors of in-hospital mortality irrespective of the underlying condition(s) in a large population of hospitalised patients in SSA and derived and internally validated a UVA score to assist clinicians in risk-stratifying patients for in-hospital mortality. The UVA score could help improve patient triage in resource-limited environments and serve as a standard for mortality risk in future studies.

High resolution data from everyday life: coproducing a technically robust and engaging sensing platform

ABSTRACTObjectives Researchers are increasingly recognising the potential for connected health devices – in particular, wearables and smartphones - to capture high-resolution, multi-dimensional data from everyday life. The Dementias Platform UK project aims to develop research capacity in this emerging area by providing a combination of hardware and software: a pool of devices capable of generating data supported by a ‘sensing platform’ designed to securely receive, store and link these data with sources, including clinical records and cohort data. We collected feedback from researchers and patients to (i) develop requirements for the sensing platform and (ii) inform procurement of a device pool. ApproachSeparate workshops were held to involve (i) researchers (public and private sector) and (ii) over 30 patients from four potential user groups, including people with dementia. Both groups gave feedback on the suitability and acceptability of a range of wearable devices for capturing data for different study purposes. Additionally, researchers commented on the platform functionality. Patients were provided opportunities to handle multiple devices and test them at home. We captured feedback at workshops using notes, which were collated, shared and discussed among the team. An agile software development methodology was used to respond rapidly to changing requirements. ResultsPatients supported plans for connected health dementia research and, in principle, were willing to wear devices, provided they consented voluntarily and data were stored securely and confidentially. Many patients were prepared to undergo some level of inconvenience, for example wearing devices for longer periods, particularly if given ongoing feedback about research progress, findings and benefits. Researchers and patients agreed the platform should be open to a wide range of devices, available currently and in future. Researchers envisaged using the platform for a range of projects and data types. As a result, we established a device pool (including wearables, smartphones and tablets) and developed a generic, ‘device-agnostic’ platform to receive and store data. Platform architecture was designed to be as flexible as possible to allow for future modifications. ConclusionWe found it was feasible to integrate requirements from both researchers and patients when developing a sensing platform for dementia research. By seeking feedback from both user groups, we were better able to attend to device linkage requirements, platform functionality and acceptability, integrating these within development and procurement processes. Furthermore, we identified aspects of research setup and design that could support sustained engagement from participants, thereby improving data completeness and quality.

Cloudy with a Chance of Pain: Engagement and Subsequent Attrition of Daily Data Entry in a Smartphone Pilot Study Tracking Weather, Disease Severity, and Physical Activity in Patients With Rheumatoid Arthritis

BACKGROUND

The increasing ownership of smartphones provides major opportunities for epidemiological research through self-reported and passively collected data.

OBJECTIVE

This pilot study aimed to codesign a smartphone app to assess associations between weather and joint pain in patients with rheumatoid arthritis (RA) and to study the success of daily self-reported data entry over a 60-day period and the enablers of and barriers to data collection.

METHODS

A patient and public involvement group (n=5) and 2 focus groups of patients with RA (n=9) supported the codesign of the app collecting self-reported symptoms. A separate "capture app" was designed to collect global positioning system (GPS) and continuous raw accelerometer data, with the GPS-linking providing local weather data. A total of 20 patients with RA were then recruited to collect daily data for 60 days, with entry and exit interviews. Of these, 17 were loaned an Android smartphone, whereas 3 used their own Android smartphones.

RESULTS

Of the 20 patients, 6 (30%) withdrew from the study: 4 because of technical challenges and 2 for health reasons. The mean completion of daily entries was 68% over 2 months. Patients entered data at least five times per week 65% of the time. Reasons for successful engagement included a simple graphical user interface, automated reminders, visualization of data, and eagerness to contribute to this easily understood research question. The main barrier to continuing engagement was impaired battery life due to the accelerometer data capture app. For some, successful engagement required ongoing support in using the smartphones.

CONCLUSIONS

This successful pilot study has demonstrated that daily data collection using smartphones for health research is feasible and achievable with high levels of ongoing engagement over 2 months. This result opens important opportunities for large-scale longitudinal epidemiological research.

Use of plasma human herpesvirus-8 viral load measurement: evaluation of practice in three UK HIV treatment centres

A retrospective audit of plasma human herpesvirus-8 (HHV-8) viral load testing was performed in three HIV treatment centres over 24 months. Reasons for testing (360 tests) were: symptoms of systemic inflammatory response syndrome (SIRS) (fever, lymphadenopathy and raised inflammatory markers); monitoring in known HHV-8 pathology other than Kaposi sarcoma (KS); investigation of known/suspected KS, and other/no reason. Of patients with multicentric Castleman disease (MCD), 14/16 (88%) had detectable plasma HHV-8, as did 27/45 (60%) with biopsy proven or clinically confirmed KS, and 6/19 (32%) with lymphoma. Neither of the two patients with MCD and no detectable HHV-8 had SIRS symptoms at the time of the test. There was wide variation between centres in the indications prompting HHV-8 testing, with a more conservative approach resulting in a higher proportion of positive results. Measuring plasma HHV-8 in the absence of SIRS symptoms, established HHV-8 disease monitoring, or confirmed/suspected KS is unlikely to yield detectable HHV-8 thus allowing potential cost savings.

Computable Information Governance Contracts

The risks of relinquishing control of electronic healthcare data for re-use in research are mitigated by the use of data sharing agreements and information governance procedures. These exist as legal, or quasi-legal, textual documents exchanged between data owners. Their existence outside of the digital realm leads to a situation where breaches of an agreement can only be detected and acted on post-hoc. We introduce the design of a system of computable contracts, specified formally, that can enforce the rules of data sharing agreements within the bounds of electronic health care systems.

Enabling Patient Control of Personal Electronic Health Records Through Distributed Ledger Technology

The rise of distributed ledger technology, initiated and exemplified by the Bitcoin blockchain, is having an increasing impact on information technology environments in which there is an emphasis on trust and security. Management of electronic health records, where both conformation to legislative regulations and maintenance of public trust are paramount, is an area where the impact of these new technologies may be particularly beneficial. We present a system that enables fine-grained personalized control of third-party access to patients' electronic health records, allowing individuals to specify when and how their records are accessed for research purposes. The use of the smart contract based Ethereum blockchain technology to implement this system allows it to operate in a verifiably secure, trustless, and openly auditable environment, features crucial to health information systems moving forward.

Towards an Open Infrastructure for Relating Scholarly Assets

Discovery of useful relationships between scholarly assets on the web is challenging, both in terms generating the right metadata around the assets, and in connecting all relevant digital entities in chain of provenance accessible to the whole community. This paper reports the development of a framework and tools enabling scholarly asset relationships to be expressed in a standard and open way, illustrated with use-cases of discovering new knowledge across cohort studies. The framework uses Research Objects for aggregation, distributed databases for storage, and distributed ledgers for provenance. Our proposal avoids management by a single central platform or organization, instead leveraging the use of existing resources and platforms across natural partnerships. Our proposed infrastructure will support a wide range of users from system administrators to researchers.

Data Safe Havens and Trust: Toward a Common Understanding of Trusted Research Platforms for Governing Secure and Ethical Health Research

In parallel with the advances in big data-driven clinical research, the data safe haven concept has evolved over the last decade. It has led to the development of a framework to support the secure handling of health care information used for clinical research that balances compliance with legal and regulatory controls and ethical requirements while engaging with the public as a partner in its governance. We describe the evolution of 4 separately developed clinical research platforms into services throughout the United Kingdom-wide Farr Institute and their common deployment features in practice. The Farr Institute is a case study from which we propose a common definition of data safe havens as trusted platforms for clinical academic research. We use this common definition to discuss the challenges and dilemmas faced by the clinical academic research community, to help promote a consistent understanding of them and how they might best be handled in practice. We conclude by questioning whether the common definition represents a safe and trustworthy model for conducting clinical research that can stand the test of time and ongoing technical advances while paying heed to evolving public and professional concerns.

Combining Health Data Uses to Ignite Health System Learning

OBJECTIVES

In this paper we aim to characterise the critical mass of linked data, methods and expertise required for health systems to adapt to the needs of the populations they serve - more recently known as learning health systems. The objectives are to: 1) identify opportunities to combine separate uses of common data sources in order to reduce duplication of data processing and improve information quality; 2) identify challenges in scaling-up the reuse of health data sufficiently to support health system learning.

METHODS

The challenges and opportunities were identified through a series of e-health stakeholder consultations and workshops in Northern England from 2011 to 2014. From 2013 the concepts presented here have been refined through feedback to collaborators, including patient/citizen representatives, in a regional health informatics research network (www.herc.ac.uk).

RESULTS

Health systems typically have separate information pipelines for: 1) commissioning services; 2) auditing service performance; 3) managing finances; 4) monitoring public health; and 5) research. These pipelines share common data sources but usually duplicate data extraction, aggregation, cleaning/preparation and analytics. Suboptimal analyses may be performed due to a lack of expertise, which may exist elsewhere in the health system but is fully committed to a different pipeline. Contextual knowledge that is essential for proper data analysis and interpretation may be needed in one pipeline but accessible only in another. The lack of capable health and care intelligence systems for populations can be attributed to a legacy of three flawed assumptions: 1) universality: the generalizability of evidence across populations; 2) time-invariance: the stability of evidence over time; and 3) reducibility: the reduction of evidence into specialised sub-systems that may be recombined.

CONCLUSIONS

We conceptualize a population health and care intelligence system capable of supporting health system learning and we put forward a set of maturity tests of progress toward such a system. A factor common to each test is data-action latency; a mature system spawns timely actions proportionate to the information that can be derived from the data, and in doing so creates meaningful measurement about system learning. We illustrate, using future scenarios, some major opportunities to improve health systems by exchanging conventional intelligence pipelines for networked critical masses of data, methods and expertise that minimise data-action latency and ignite system-learning.

Using mobile technology to deliver a cognitive behaviour therapy-informed intervention in early psychosis (Actissist): study protocol for a randomised controlled trial

Background

Cognitive behaviour therapy (CBT) is recommended for the treatment of psychosis; however, only a small proportion of service users have access to this intervention. Smartphone technology using software applications (apps) could increase access to psychological approaches for psychosis. This paper reports the protocol development for a clinical trial of smartphone-based CBT.

Methods/Design

We present a study protocol that describes a single-blind randomised controlled trial comparing a cognitive behaviour therapy-informed software application (Actissist) plus Treatment As Usual (TAU) with a symptom monitoring software application (ClinTouch) plus TAU in early psychosis. The study consists of a 12-week intervention period. We aim to recruit and randomly assign 36 participants registered with early intervention services (EIS) across the North West of England, UK in a 2:1 ratio to each arm of the trial. Our primary objective is to determine whether in people with early psychosis the Actissist app is feasible to deliver and acceptable to use. Secondary aims are to determine whether Actissist impacts on predictors of first episode psychosis (FEP) relapse and enhances user empowerment, functioning and quality of life. Assessments will take place at baseline, 12 weeks (post-treatment) and 22-weeks (10 weeks post-treatment) by assessors blind to treatment condition. The trial will report on the feasibility and acceptability of Actissist and compare outcomes between the randomised arms. The study also incorporates semi-structured interviews about the experience of participating in the Actissist trial that will be qualitatively analysed to inform future developments of the Actissist protocol and app.

Discussion

To our knowledge, this is the first controlled trial to test the feasibility, acceptability, uptake, attrition and potential efficacy of a CBT-informed smartphone app for early psychosis. Mobile applications designed to deliver a psychologically-informed intervention offer new possibilities to extend the reach of traditional mental health service delivery across a range of serious mental health problems and provide choice about available care.

Trial registration

ISRCTN34966555. Date of first registration: 12 June 2014.

On moving targets and magic bullets: Can the UK lead the way with responsible data linkage for health research?

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We explore key elements of good governance in health linkage.

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Adaptive reflexive governance models are essential.

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Two examples illustrate how we can achieve standardisation of practice.

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Distinct elements of governance compiled in a composite fashion tend to challenges.

Purpose

To provide an overview of essential elements of good governance of data linkage for health-related research, to consider lessons learned so far and to examine key factors currently impeding the delivery of good governance in this area. Given the considerable hurdles which must be overcome and the changing landscape of health research and data linkage, a principled, proportionate, risk-based approach to governance is advocated.

Discussion

In light of the considerable value of data linkage to health and well-being, the United Kingdom aspires to design and deliver good governance in health-related research. A string of projects have been asking: what does good governance look like in data linkage for health research? It is argued here that considerable progress can and must be made in order to develop the UK’s contribution to future health and wealth economies, particularly in light of mis-start initiatives such as care.data in NHS England. Discussion centres around lessons learned from previous successful health research initiatives, identifying those governance mechanisms which are essential to achieving good governance.

Conclusion

This article suggests that a crucial element in any step-increase of research capability will be the adoption of adaptive governance models. These must recognise a range of approaches to delivering safe and effective data linkage, while remaining responsive to public and research user expectations and needs as these shift and change with time and experience. The targets are multiple and constantly moving. There is not – nor should we seek – a single magic bullet in delivering good governance in health research.