‘Pushed’ self-tracking using digital technologies for chronic health condition management: a critical interpretive synthesis

Abstract

Introduction

Health policies internationally advocate health services provider support for health services users’ ‘self-management’ of chronic health conditions. Digital technologies are beginning to have a role in delivering such support. ‘Pushed’ self-tracking of health-related information, including imposed measurement of biomedical and behavioural data, is one approach; however, there is little systematic or discursive research. The aim of this research was to explore factors relevant to the implementation of ‘pushed’ self-tracking technologies into support for self-management of chronic health conditions interventions.

Methods

This paper reports a critical interpretive synthesis of studies involving ‘pushed’ self-tracking using digital technologies to support the self-management of chronic health conditions. The review systematically identified relevant literature, characterised the technologies and discursively explored their implementation and impacts, and human technology interactions.

Findings

The literature (n = 83), including ‘simple’ (n = 51) and ‘complex’ (n = 32) interventions, perhaps unsurprisingly, concentrates on technical and clinical rather than sociological and behavioural perspectives, which limits understanding. Some attention is paid to experiences and views of providers and users about digital technologies implementation and impacts on the delivery of care, for example: consequences of having increased information; compatibility with current systems; implications for personnel; and human–technology negotiations.

Conclusions

This is a rapidly developing field and early technical and clinical insights are useful. There are opportunities for researchers to explore the sociological and behavioural aspects, and ethical challenges, of implementing ‘pushed’ self-tracking support programmes too. Detailed multidisciplinary research is needed to understand and guide technical and medical developments that integrate digital technologies into the delivery of care.

Keywords

Digital technologies chronic health conditions self-management self-tracking health monitoring

Introduction

Health policies internationally advocate health services provider (health professional) support for health services users’ (patients’) ‘self-management’ of chronic health conditions.¹ Finding better ways to deliver healthcare is becoming critical as pressures on health service providers to support people are increasing as populations grow,² live longer and more people have one or more chronic health condition(s). Chronic health conditions somehow have to be managed over the longer term, but the sustainability of services is uncertain and makes this a challenging area for service organisations and providers. Supporting people to self-manage can reduce pressures on health services at the same time as empowering and working with service users as partners.¹

Digital technologies are beginning to have a role in delivering or facilitating such support. Digital technologies for health (e.g. mobile health interventions, such as short messaging service interactions; electronic health records and systems; smartphone apps to manage conditions; and wearable devices to monitor lifestyle) are rapidly proliferating and show wide-ranging promise for health and disease management.^3,4 The array of available and emerging digital technologies can be useful for health services providers in the delivery of care across a variety of medical domains: for supporting health service users to self-manage specific conditions, as well as for promoting healthy lifestyles. They may help people to achieve and sustain healthier behaviours through increased access to and awareness of personal health-related data. Many of these technologies allow individuals to self-track, make records of and respond to a range of previously invisible biomedical and behavioural data.⁵ In addition to personal benefits of use, they offer new platforms for health service organisations and providers to observe health service users' signs and symptoms through “pushed” self-tracking.⁶

‘Pushed’ self-tracking, i.e. when a person is asked to self-track and the self-tracking is imposed,⁷ is one approach to supporting the self-management of chronic health conditions. Technologies are now being piloted in intervention programmes in clinical practice and early studies have started to show health service providers requesting that health service users employ them in order for them to supply detailed data as part of their care package. This is more visible in the area of supporting the self-management of chronic health conditions than in preventive care at present, but there is a strong and growing commitment to using digital technologies across health and social care services, which has been signalled globally.^8–12 Like the self-management approach, technologies are appealing because they may also offer innovative means for engaging and empowering health service users in their health and care.¹³

There is little systematic or discursive applied health research that investigates how acts of ‘pushed’ electronic self-tracking are assimilated into existing medical models, or how they impact the delivery of care and daily life for users. Building on previous work that explored support for the self-management of chronic health conditions more generally,¹ the aim of this research was to explore factors relevant to the implementation of ‘pushed’ self-tracking technologies into support for self-management of chronic health conditions programmes.

Methods

This paper reports a critical interpretive synthesis of published health services research/medical literature involving service-provided digital technologies used in the context of supporting the self-management of chronic health conditions, i.e. support provided or facilitated through ‘pushed’ self-tracking. This literature was drawn upon as a subset from within a larger body, which was originally identified for a review on the breadth of approaches to health and social care support for self-managing chronic conditions. For that review, support was broadly defined and included interventions involving ‘pushed’ self-tracking.¹ For this more specific review, the focus was on ‘pushed’ self-tracking technologies used to deliver or facilitate support only. The studies reflected on in this review were systematically identified in a new and independent process of determining inclusion/exclusion criteria for titles/abstracts and full text papers, and a fresh approach to the appraisal of included studies.

Search, review and analysis proceeded in sequence. Potential papers were identified by an Information Specialist who designed and executed searches for papers indexed on Medline, CiNAHL, SCI and ASSIA databases. Search strategies combined terms relating to chronic conditions with self-management, patient involvement or provider–user relationships and practitioners' perspectives. They covered internationally published literature between 2000 and 2014 (please see Appendix 1 for full details). Conventional systematic reviewing techniques were first re-applied to the entire selection (n = 5246) by one researcher. A systematic two-stage process of inclusion/exclusion of titles/abstracts and full-text papers was undertaken to identify literature relevant for this review and critical interpretive synthesis. Checking of decision making was undertaken by two senior colleagues and queries were resolved through regular discussion.

Inclusion

Papers reporting ‘pushed’ self-tracking for all/any chronic health conditions and all study types were included. There were no search restrictions on country/language (although the search was restricted to English alphabet only) and the definition of ‘technology’ was kept deliberately broad to include the range of technologies that can be described as digital. This was to allow inclusion of diverse technologies, such as mobile health interventions, electronic health records and systems, smartphone apps to manage conditions and wearable devices to monitor lifestyle, and to facilitate classification of and comparisons within and across technology types. 5246 titles and abstracts were reviewed, first manually, line by line, and then by using keyword searches to ensure that no relevant articles were missed. Manual checking was supplemented with searches for the following keywords: surveillance, self-monitoring, technology, wearable, device, application, computer, web-based, virtual, mobile, digital, telehealth, telecare, electronic, self-tracking, equipment, online, smartphone, cellular, Internet, ehealth, mhealth.

Exclusion

Papers featuring technologies that were not self-administered, assistive technologies or medical devices for physical therapy (defined as ‘electrical or mechanical devices designed to help people recover movement’) were excluded.¹⁴ So were reports of shared decision making. Intervention studies where the emphasis was on health service providers performing the measurement or doing the monitoring, without the visibility of the patient (so not self-administered and/or part of a self-management promotion/scheme, i.e. to collect clinical data rather than inform/engage the patient), and studies involving health service user gathering/using data without health service provider intervention were also excluded. So were text/SMS reminder interventions. There must have been clear active data collection/input from health service users. Interventions must have provided more than decision aid advice, e.g. by email.

Process

Full texts of papers for relevant titles/abstracts were retrieved and reviewed in full by one researcher, again in discussion with two senior colleagues, to determine final inclusion of studies, which were appraised using a reviewer developed data extraction form that focused on: setting; study type; chronic condition; specific population; self-administered health monitoring technology description and/or name; self-administered health monitoring technology purpose; self-administered health monitoring technology functions; how does it work?; users involved in design?; can it be tailored/personalised by user?; key findings.

A critical interpretive synthesis approach,¹⁵ using conventional systematic review methodology combined with traditional qualitative inquiry, was applied to make sense of what is a complex body of literature. This approach is oriented to conceptual or theoretical development and allows for critical consideration of diverse studies and the research traditions and assumptions that have influenced them.¹ Included studies were coded and comparisons were made within and across studies to identify themes. Again, these were agreed through regular discussion with two senior colleagues.

An additional layer of categorisation occurred as a clear cut distinction between ‘simple’ and ‘complex’ technologies emerged. Papers that focused on self-monitoring of blood glucose (diabetes), home blood pressure monitoring (hypertension), peak flow (asthma) or equivalent, i.e. one objective outcome measure which is expected and disease-specific, were grouped as ‘simple’. Studies that included responses to self-administered data collection and focused on data/outcomes including subjective measures, not just the condition (i.e. broader lifestyle), were grouped as ‘complex’.

This process was inductive. The evidence synthesis focused on characterising the technologies and the critical interpretive synthesis considered the implementation of technologies and their impacts on the delivery of care.

This review complies with the ENTREQ statement on reporting the synthesis of qualitative health research.¹⁶

Findings

Inclusion/exclusion of papers

From a total of 5246 studies identified, a number of papers (n = 5060), i.e. those not referring to self-tracking technologies, self-management and chronic health conditions, were excluded at the title/abstract screening stage. The remaining 186 papers were reviewed in full. From the full-text papers, a further 103 were excluded. See the flow diagram in Appendix 2 for details on the review process.

Characterisation of technologies

83 papers reporting the use of digital technologies to support the self-management of chronic conditions through ‘pushed’ self-tracking were selected. 51 used objective measures related to monitoring a single biological variable/clinical marker related to a condition and were part of clinical kit and care ‘upgrade’ (e.g. self-monitoring of blood glucose in diabetes, electronic peak flow log in asthma). Analysis helped to identify these as a homogeneous category of studies as they featured condition-specific technologies incorporated into well-documented medical regimens typical for diabetes, hypertension, asthma and thromboembolic disorders, which were designed to provide or improve insights into clinically relevant information for the condition. These were labelled ‘simple’ and were only included in the initial analysis and then set aside.

The remaining 32 papers appeared heterogeneous by comparison and are the main focus for this paper because they offered new and interesting insights into a range of systems and/or complex interventions targeting multiple biomarkers and/or behaviours for a broader range of chronic health conditions, including subjectively measured data. These studies involved the use of digital technologies (e.g. telephone-linked communications system; electronic portal accessed through smart devices; various peripherals to measure vital signs) to uncover previously invisible data in supporting the self-management of diabetes, asthma, chronic heart failure, migraine, schizophrenia, cancers, COPD and chronic health conditions more generally.⁵ Similar or comparable systems appeared to be utilised for different conditions. They were labelled ‘complex’. The criteria for characteristics for categorisation of digital technologies are detailed in Table 1.

Table 1.

Characteristics of the two categories for new health technologies.

‘Simple’ (n = 51)	‘Complex’ (n = 32)
Single target (clinical marker)	Multiple target (clinical markers and/or lifestyle behaviours, emotions)
Clear links between clinical marker and condition management	Less clear or unclear links between clinical or behavioural markers targeted and condition management and/or lifestyle
Part of regular clinical kit	Additional kit
Incorporated into existing medical regime	New (part of) medical and lifestyle regime
Medically-oriented technology	Social aspects to technology
Provided to all as medical necessity	Experimental use
Technologies/devices	Systems
Provided through health service	Provided through health service, but commercial versions available or uses commercial device to operate (e.g. user's own mobile phone/laptop)
Health and social care professionals already familiar	New system requires health and social care professional training to implement
Developed by/for clinical use	Users involved in design and tailoring for integration into lifestyle
Clinically grounded	Theoretically diffuse
Underdeveloped theoretical basis (clinical not social)	Underdeveloped theoretical basis (technical not social or behavioural)

This ‘simple’ and ‘complex’ classification was primarily a device for distinguishing between narrowly biomedically-oriented (objectively measured) and broader complex interventions (including subjective measures), and the need to acknowledge the importance of theoretical underpinnings, use of behaviour change techniques and measures of acceptability, which are expanded on below.

Although ‘simple’ interventions using technologies may have changed usual care packages and associated clinical interactions in some ways, the conditions concerned necessitated the particular monitoring featured. By comparison, literature relating to ‘complex’ interventions appeared more diverse and reported a range of examples of various new ‘pushed’ self-tracking technologies being implemented across a number of medical domains. The analytical focus is therefore on this set of 32 papers.

These 32 papers comprised 15 evaluations, 5 feasibility studies, 4 randomised controlled trials, 3 development studies, 2 descriptions, 2 commentaries and 1 systematic review. Of these, 7 expressly used qualitative methodologies (including 1 ethnography) and a further 4 incorporated interviews within the study. See the descriptive table in Appendix 3 for further details of individual studies.^17–48

Detailed description of precise interventions and the purpose(s) of various components and functions of technologies, aside from ‘innovation’, often seemed limited, as did discussion of health services provider and user implications apart from the technical. Theoretical underpinnings tended to extend clinical, or technological, rather than behavioural or sociological, discussions, which limits understanding of these aspects.

The implementation and integration of these ‘complex’ systems into care and their impacts on the delivery of care were developed further within the analysis.

Implementation into the delivery of care

The implementation of digital technologies into the delivery of care had several impact points at multiple levels across a number of often overlapping areas. These areas did not seem related to the specific condition or technology. Key themes under which the data were organised are: consequences of having increased information; compatibility with current systems; implications for personnel; and human–technology negotiations. Included studies seemed focused on clinical (improved health outcomes) and technical (does it work?) concerns, even where social and behavioural factors were implicated. The emerging themes for health service organisations (Figure 1), health service providers (Figure 2) and health service users (Figure 3) have been visualised below as summaries of the key findings from across and within studies.

Figure 1.

Impacts of implementation for health service organisations.

Figure 2.

Impacts of implementation for health service providers.

Figure 3.

Impacts of implementation for health service users.

These categories are not neatly configured and there is a great deal of interaction, overlap and inconsistency between themes and the stakeholder groups. This is likely to be attributable to the heterogeneity of the included studies. However, they provide a useful framework for beginning to explore the impacts on the delivery of care and the critical interpretive synthesis approach is designed to make sense of a complex body of literature.

Impacts on the delivery of care

The impacts that digital technologies have on the delivery of health and social care can include what can be interpreted as both intended and unintended, positive and negative consequences. While there are broader, often overlapping and intersecting themes, the perspectives of health service organisations, providers and users can be compared and contrasted. Overall, the findings were often contradictory or inconsistent within and across categories. Some critical observations around consequences of having increased information, compatibility with current systems, implications for personnel and human–technology negotiations were noted.

Having increased information

There were often separate health service provider–user portals,^18,32 where different information was made available through different interfaces. Therefore ‘having increased information’ might not refer to the same information, meaning that organisations, providers and users were not necessarily ‘on the same page’. In addition, technologies tended to collect structured rather than unstructured information,²⁰ sometimes resulting in limitations for supporting provider-user dialogues.²³ For health service providers, having data delivered on a daily basis could enable them to ‘stay on top of things’,⁴² and some liked to review the information immediately prior to consultation.³⁷ For others, it caused tensions around how to respond compared with traditional, periodical, face-to-face appointments, where the ‘rules of engagement’ are well versed. These sparked trade-offs around distribution of time and resources.³⁴ Some providers saw additional information as a complement or extension to,^42,43 but not replacement for,³⁷ usual care practices.

For health service users, there seemed to be less provision of information than might be assumed or expected, despite interventions being self-administered and implying ‘self’-tracking. It appeared that there was little personalised feedback/interpretation of data being provided,²¹ although, where it was, being able to visualise changes was considered helpful.^28,47 Even then, having additional information did not necessarily equate with ‘progress’,²⁷ but progress was often quite narrowly defined in terms of improving quantities (metrics) rather than quality (engagement).²⁶ In one study, it was noted that having increased data increases honesty and improves clarity,³⁸ although sometimes professionals worried about patients’ ‘gaming’ by trying to create false results or data that looks better (e.g. more exercise, healthier eating).⁴⁷ This could cause problems concerning trust.

Compatibility with current systems

Embracing new ways of working as a result of the using technologies was identified as a ‘practice point’ by health service providers in one study.³³ But providers’ perceptions of integrating technologies did not always match those of the users.⁴⁵ According to one study, the technology should be offered as ‘optional’,³⁴ suggesting a perception of implementation sometimes considered ‘compulsory’ from a provider point of view. Some systems were designed to increase efficiency by preventing under-diagnosis.^17,18 In others, increased reporting of symptoms could be found.^19,29

There were also concerns about obviating the need for routine interactions and having less human contact,^18,21 although this was linked positively with preventing health service users from having to make long journeys.³⁴ There were observed reductions in regular/scheduled appointments when service users were perceived to be able to ‘manage’ better through self-tracking.³⁸ While providers may have believed that users had better self-management, however, this might not have been the case.^24,37,45 As such, these technologies bring about some confusion about how services should be delivered, which do not necessarily fit with current conventions or expectations of service providers or users.

Implications for personnel

The changes technologies instigate challenge understandings of identity in provider-user relationships. Technologies alter the ways that service providers work in teams. In one study, a nurse reported that patients were more likely to approach her than a doctor, which she perceived to be a good thing, although it was not clear whether this was personal preference, better for service delivery or better for patients.³⁰ Some doctors thought that they, rather than nurses, should receive data,³⁷ perhaps creating power struggles within teams. Service providers identified using digital technologies as offering potential for professional and career development,³⁴ but whether this was for career progression or patient benefit was unclear.

In terms of changing roles and responsibilities, and their transfer from organisations and providers to users, technologies seemed to cause increased burden for health service users.²⁵ The perceived ability to manage symptoms using the technology,³⁵ however, suggested that tracking multiple behaviours was not actually as effortful as some seemed to imply (through their delivery of a ‘complex intervention’ implicating a number of biomedical and behavioural targets).

Technologies were perceived to have improved health service provider-user time together and could improve contacts between parties.^38,39 Conversely, as noted, interactions between health service providers and health service users could become more limited and a decrease in contact time was found elsewhere.^26,47 Indeed, use of technologies did not correspond with ‘real’ support, which might have meant reduced burden on and for health services organisations and providers. For instance, where an automated technology initiated a call if the patient failed to register,¹⁷ the division of labour would have been delegation to a system rather than a person. However, some service users felt and liked what they perceived to be additional monitoring as they interpreted follow up calls as someone actively monitoring them and considered it a ‘confidence booster’.⁴² Providers suggested that they wanted service users to be more engaged, feel listened to, perceive that what they had to say was important, and to seek help.²⁴ But they could also become judgemental when they felt that patients’ attitudes had not changed (e.g. no greater motivation to take on more responsibility) as a result of using the technology,³¹ thus causing some tensions. Technologies could allow more trust by the provider of the user, however, and in some cases service users may have been able to go home rather than remain in hospital.²⁷ This can bring about benefits for all stakeholders: when hospital beds are in short supply and patients wish to return home, using technologies can be mutually beneficial. Elsewhere, it seemed, however, that service users were often being monitored through a form of increased health surveillance, although they might place faith in this approach.²³

Recording symptoms might lead to enhanced communication, particularly between professionals and young people,²⁴ but it often seemed unidirectional, focused on tracking/checking rather than responding to/being interactive or responsive,^25,27 or related to increased demand for support.²⁴ This may have had implications for perceptions of privacy, particularly if patients were concerned about increased monitoring and confidentiality,^24,42 or feeling constantly watched.⁴⁷ However, they did not always seem to negatively affect patient dignity, but social (impacts on services and resources) and ethical (data protection) consequences were inevitably caused by the implementation of digital technologies. Care and relationships are transformed and provoke new questions about best practice, quality and safety. Medicolegal implications are initiated through the creation and communication of new forms of medical data,⁴³ bringing about security, storage, transmission, ownership concerns, although these were not discussed critically or in great depth.

Differences between health service users in terms of their personal characteristics and digital inclusion (i.e. equality of access to relevant technologies and equity in use) were mixed and unpredictable – there seemed to be no specific correlations.

Human–technology negotiations

Technical issues Studies tended to report interventions that aimed to deliver care through a technology, either thus reducing or in order to reduce face-to-face time. In one study, the introduction of new technologies into the care relationship increased dependence through the need for greater support,²⁴ rather than creating greater independence, although it was not clear whether the support required was technical or clinical (through increased awareness of health-related data). In another study, health service users felt more cared for and safer – but as a result of the technology, not their connection with healthcare provider(s).²³ Some patients may have preferred having access to their existing GP and to feel that there was continuity of care,²³ or more clinical expertise inputted into the technology.⁴⁷ Most patient interest was in the ‘ask the expert’ feature in one study,²² and so traditional medical expertise was valued. From the perspectives of GPs, however, the investment required to input into or support technologies’ use might have outweighed the benefits. A number of GPs ended up not using the technology in one study because they were disappointed that patients had failed to stay connected.³¹

Discussion

This paper offers a characterisation and critical interpretation of a range of illustrative literature on digital technologies used, through ‘pushed’ self-tracking, for supporting the self-management of chronic health conditions, paying particular attention to implementation and integration of technologies into the delivery of care from a health services research perspective. It focused on the consequences of having increased information, compatibility with current systems, implications for personnel and human–technology negotiations.

Perhaps unsurprisingly, the literature concentrates on technical and clinical rather than sociological and behavioural perspectives, which limits understanding. However, for the purposes of this review and to generate richer insights, the technologies examined were categorised as ‘simple’ or ‘complex’ because of key differences regarding their purpose in relation to existing medical models. Questions arose around ‘complex’ technologies, particularly the implementation and integration of technologies into the delivery of care. These were investigated in more detail. Although traditional approaches do not always appear to work well, e.g. peak flow consistently causes problems,^17,25 and new technologies show promise, e.g. a Personal Digital Assistant (PDA) works better than paper,²⁵ it seems that there is little meaningful integration (e.g. shared interpretation of data, shared decision making based on data) and a great deal of contradictions and inconsistencies in implementation at this early stage in the field of digital technologies for ‘pushed’ self-tracking of health-related data, particularly in the context of supporting self-management of chronic health conditions.

The review showed the use of technologies as ultimately still focused on compliance and the construction of ‘health threats’,^23,49 i.e. ‘red flags’ for professionals to respond to user risk factors when they are indicated by specific data, rather than user experiences or allowing patients to genuinely take control or participate more actively in their (self-)care,³ although this is not always welcomed by health service providers or users.⁵⁰ Language of non-compliance will need to adapt, however, if the focus becomes less on single time points and more on a continuum, particularly if there is a growth of non-disease specific programmes (e.g. focus on lifestyle behaviours), it will mean that new and more flexible approaches are required. We will need to take care in how more directive approaches concentrating on ‘good’ habit formation are framed and fit with everyday life.⁵¹ In keeping with the findings of a review of support for self-management of chronic health conditions,¹ which looked more generally at provision of support for self-management, purpose can underpin more hierarchical practitioner-patient communication and more limited views of patient empowerment. These are often associated with experiences of failure and frustration. Broader approaches support people to manage well with their condition(s). They can keep work on disease control in perspective as attention focuses on what matters to people and how they can be supported to shape their own lives. Like other interventions, technologies tend to offer new ways of managing conditions, rather than managing or living (well) with conditions.¹ This, of course, depends on how we as developers, researchers, users (organisations, professionals and patients) collaborate to harness technologies; it's not a fault of technology itself, but it is important to attend to the nuanced and subtle difference between the two approaches and to attend to the conceptualisation of healthcare delivery.⁵²

There was limited consideration of long-term use or implications for medical education and professional training, guidelines and regulation.^53–55 The personal, relational, social and ethical intended and unintended positive and negative consequences of use will also need more careful attention as availability, use and possibilities expand.⁵⁶ There was little detailed description of how clinical interactions changed (or not) or of how any changes were managed when technologies were integrated.²³ What appeared as implementation factors (i.e. adding information, compatibility with current service, personnel and technical aspects) were reframed as different ways of enacting the technology or the clinic.³¹ This contrasts with previous research that has found a focus on the micro level impacts of ‘quantified self’ activities.⁵⁷ ‘Interactions or interviews between doctors and patients are the cornerstone of medical practice’,⁵⁸ but this notion was not directly addressed. As such, the personal, relational, social and ethical aspects of introducing new technologies into care packages, particularly those grounded in tenets of empathy and trust, seemed to be overlooked and the prevailing models involved ‘transactional medicine’ that appears standardised rather than context dependent.⁴⁹ This does not align easily with discourses of genuine patient empowerment and seems more Foucauldian, where the aim is to instil discipline through the introduction of technological regimens in order that they breed self-discipline;⁶ the technologies are not necessarily being implemented to improve relationships. A recent review found that upfront consideration should be given to how technologies may enable or limit relationships between health service providers and health service users.⁵⁹ Mitigation of changes to, or the demise of, such relationships,⁶⁰ and organisation of services, is recommended.

Relational aspects of care are distinguishable from clinical and technical aspects and need to be explored in more depth. While clinical/technical evaluations are important in terms of improving outcomes and service development, we need to know more about the behavioural/sociological theories that underpin the phenomenon of ‘pushed’ self-tracking, as well as understanding derived through social scientific understandings of human experiences of it and their meaning. These analyses would offer explanations of the mechanisms of action, help to identify and possibly resolve ethical tensions and provide insights into digital human being, as well as uncovering directions for improving acceptability and usefulness. In terms of how these impacts of implementation affect the delivery of care, at this early stage in the development of the ‘digital health’ field within medicine, and in the absence of detailed data that goes beyond investigating clinical or technical factors, it seems that it may be more beneficial to focus on the collaborative construction and making sense of using digital technologies through applying and developing sociological theories within a health services research context. There may be more useful ways in which to think about and conceptualise the implementation of digital technologies in this multidisciplinary field. It will be important to look beyond the medical literature to develop understandings of the emerging application of new technologies within health services going forward.

Strengths and limitations

The strengths of this paper include the development of categories for classifying digital technologies – as ‘simple’ or ‘complex’. To date, categorisation has been diffuse and so these may be helpful for practice and research. The detailed exploration of those considered ‘complex’, which has not previously been a focus of systematic research, may also be useful. A new focus on how ‘pushed’ self-tracking transforms the delivery of care, where previous applied research has been more concerned with efficiency, is novel. This is an emerging area and very topical as the increased use of self-tracking technologies is indicated, particularly for managing chronic health conditions, multi-morbidities and lifestyles.

The limitations include the inclusion of a broad range of applied health services literature, which was concerned with self-management of chronic conditions. The focus on chronic health conditions and health service provided technologies – ‘pushed’ self-tracking – not technologies for use in relation to health in general, means that insights may be restricted to specific groups of technologies and/or conditions rather than digital technologies more generally, including those commercially available outside of health services. The variation and diversity of technologies included here, however, may mean that the findings are still too broad in terms of classification and this research may have raised more questions than answers. Clearly, another limitation is that by undertaking this research following a strict health services systematic reviewing methodology, potentially relevant research papers from other fields were not included in the review.

Suggested directions for future research

Overall, the findings were contradictory and indicate a need for both multidisciplinary and detailed qualitative, including ethnographic, research into integration of technologies into care models and the personal, relational, social and ethical consequences of use, for example how our bodies might be integrated with or commodified by technologies, discrimination, what is acceptable and/or measured by interpretations of good and bad health behaviour, and how that impacts on health and social care. This is consistent with the conclusions of other papers within this evolving field.⁶¹ There may be a need to develop a focus on or framework for assessing/analysing how precise technologies are implemented and/or a model to guide medically-located interactions,⁶² as well as for evaluating them. This may draw on the health psychology of behaviour change,^63,64 as well as social scientific approaches. In particular, detailed work to define optimal settings, with attention to the importance of place,⁶⁵ duration of use, and consideration of power dynamics through the availability of previously unknown information, is required. Approval/regulation is also an issue: there are currently a number of technologies with FDA approval in the USA,⁵⁴ with some being available on prescription. In the UK, the NHS apps library has recently come under criticism for products leaking data,⁶⁶ although this has since been closed down.

In future research, it would be of benefit to conduct detailed exploration of use outside health services too: ‘Research could explore if there is a difference in outcomes between an individual independently deciding to use an app versus having an app recommended by his/her healthcare provider.’²⁶ More and more within the grey literature, the prevalence of commercial health technologies is reported, with much speculation about the growth of their role. The heterogeneity within this study was evident and should be unpacked and distilled to progress classification in this field. There may be individuals who prefer not to use them at all and this population should also be consulted. Similarly, issues of equity, equality of access and (the creation of new and different) health inequalities in the context of digital technologies need to be addressed. Features and designs of technologies should also be considered, especially regarding consumer vs. citizen agendas, where people, patients, might prefer to choose their own technologies. User-centred design was more common in social care than health care contexts,¹⁹ reflecting differences found between broader compared with narrower approaches to supporting the self-management of chronic conditions.¹ As found in the included studies, co-design of digital health technologies does already happen and in-depth qualitative research, conducted alongside other research designs within studies, is evident in the literature included in this review. There is a useful framework for mitigating problems of implementing and normalising technologies that outlines the value of these kinds of approaches.⁶⁷ It would be beneficial for the research community, as well as for practice, if those engaging in technology co-design and/or qualitative inquiry around implementation reported these processes in detail to uncover the detail to allow in-depth analysis. Finally, research design and conduct that is flexible to accommodate concepts of performativity, co-construction of identities and new repertoires of ‘being human’ will be crucial.

Conclusions

The technologies featured appeared largely as a conduit for the delivery of care and proxy for health care professional support for the self-management of chronic conditions, which seem to be substituted for traditional models of delivery and to impact on human contact. As such, they did not seem to be well integrated and did not align easily with other healthcare discourses around support for self-management, patient empowerment, etc. This may not be universal or the case beyond chronic condition self-management support, however, there may be wider-ranging implications for digital technologies provided by health services in other clinical areas. There is a need for detailed qualitative research to explore user perspectives, likely involving ethnographic and longitudinal work. Co-design of technologies also requires further exploration.

While this review focused on technologies, the findings imply that the focus of future work should not be on technologies or data per se, but what integration of self-tracking technologies means for the delivery of care. As pacey proliferation of technologies continues, there may be a need to look at ‘innovolution’, evolution through innovation, rather than discrete innovations.³⁸ More unpacking and conceptualisation, drawing on both health services research and sociological perspectives, is required as digital technologies transform health and care, continually raising new personal, relational, social and ethical questions, as well as technical and clinical concerns.

There are opportunities for health services researchers to focus more on the sociological and behavioural aspects, and ethical challenges, of implementing ‘pushed’ self-tracking support programmes. Detailed multidisciplinary research is needed to understand and guide technical and medical developments that integrate digital technologies into the delivery of care.

Footnotes

Acknowledgements

This review drew on a body of literature originally identified in The Health Foundation-funded project: ‘Concept: SSM – conceptualising support for self-management’, led by Professor Vikki Entwistle, University of Aberdeen. Many thanks to Professors Lorna McKee and Marion Campbell, Health Services Research Unit, University of Aberdeen, for helpful discussions regarding analysis and for commenting on earlier drafts of this paper. Thanks also to Cynthia Fraser, Information Specialist, and Lara Kemp, Secretary, Health Services Research Unit, University of Aberdeen, for their help with reference retrieval and management.

Contributorship

HM led the design and conduct of this research and wrote this paper. The literature was identified by an Information Specialist who designed and executed searches for papers indexed on Medline, CiNAHL, SCI and ASSIA databases.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical approval

This paper reports secondary research, which did not require ethical approval. This review complies with the ENTREQ statement on reporting the synthesis of qualitative health research.²⁵

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by an award made to Heather Morgan, Health Services Research Unit, University of Aberdeen, through the Wellcome Trust Institutional Strategic Support Fund (RG12724-13). The Health Services Research Unit is core funded by the Chief Scientist Office of the Scottish Government’s Health and Social Care Directorates. The author accepts full responsibility for this work.

Guarantor

Peer review

This manuscript was reviewed by Leanne Morrison, University of Southampton, Panagiotis Balatsoukas, University of Manchester & Nikki Newhouse, University of Oxford.

Appendix 1

Appendix 2

Appendix 3

References

Morgan

Entwistle

Cribb

. We need to talk about purpose: a critical interpretive synthesis of health and social care professionals' approaches to self-management support for people with long-term conditions. Health Expect. Epub ahead of print 1 March 2016. DOI: 10.1111/hex.12453.

García-Lizana

Sarría-Santamera

. New technologies for chronic disease management and control: a systematic review. J Telemed Telecare 2007; 13: 62–68.

Lupton

. Apps as artefacts: towards a critical perspective on mobile health and medical apps. Societies 2014; 4: 606–622.

Husain

Spence

. Can healthy people benefit from health apps? BMJ 2015; 350: h1887.

Uotinen

. Senses, bodily knowledge, and autoethnography: unbeknown knowledge from an ICU experience. Qual Health Res 2011; 21: 1307–1315.

Foucault

. The birth of the clinic: an archaeology of medical perception, London: Routledge, 1973.

Lupton D. Self-tracking modes: reflexive self-monitoring and data practices. Social Science Research Network (SSRN). http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2483549 (2014, accessed November 2015).

European Commission. Digital agenda for Europe: EH policy eHealth, https://ec.europa.eu/digital-agenda/en/eu-policy-ehealth (2015, accessed November 2015).

UK Department of Health. Digital health: working in partnership – promotional material, www.gov.uk/government/publications/digital-health-working-in-partnership/ digital-health-working-in-partnerships (2014, accessed November 2015).

10.

US Department of Health and Human Services. Digital strategy at Health and Human Services (HHS), www.hhs.gov/web/governance/digital-strategy/index.html (2015, accessed November 2015).

11.

Australian Government Department of Health. eHealth program, www.health.gov.au/internet/main/publishing.nsf/content/ehealth (2015, accessed November 2015).

12.

NHS Scotland. eHealth strategy 2011–2017. Edinburgh: Scottish Government. www.gov.scot/resource/doc/357616/0120849.pdf (2011, accessed November 2015).

13.

Sosnowy

. Practicing patienthood online: social media, chronic illness and lay expertise. Societies 2014; 4: 316–329.

14.

Demain

Burridge

Ellis-Hill

. Assistive technologies after stroke: self-management or fending for yourself? A focus group study. BMC Health Serv Res 2013; 13: 334.

15.

Dixon-Woods

Cavers

Agarwal

. Conducting a critical interpretive synthesis of the literature on access to healthcare by vulnerable groups. BMC Med Res Methodol 2006; 6: 35.

16.

Tong

Flemming

McInnes

. Enhancing transparency in reporting the synthesis of qualitative research: ENTREQ. BMC Med Res Methodol 2012; 12: 181.

17.

Adams WG, Fuhlbrigge AL, Miller CW, et al. TLC-Asthma: an integrated information system for patient-centered monitoring, case management, and point-of-care decision support. AMIA Ann Symp Proc 2003; 1–5.

18.

Agarwal

Lau

. Remote health monitoring using mobile phones and Web services. Telemed J E-Health 2010; 16: 603–607.

19.

Ben-Zeev

Kaiser

Brenner

. Development and usability testing of FOCUS: a smartphone system for self-management of schizophrenia. Psych Rehab J 2013; 36: 289–96.47.

20.

Biswas

Maniam

Lee

. User-driven health care: answering multidimensional information needs in individual patients utilizing post-EBM approaches: an operational model. J Eval Clin Pract 2008; 14: 750–760.

21.

Brandell

Ford

. Diabetes professionals must seize the opportunity in mobile health. J Diabetes Sci Technol 2013; 7: 1616–1620.

22.

Donovan

Mehringer

Zeltzer

. Assessing the feasibility of a web-based self-management program for adolescents with migraines and their caregivers. Clin Pediatr 2013; 52: 667–670.

23.

Fairbrother

Ure

Hanley

. Telemonitoring for chronic heart failure: the views of patients and healthcare professionals – a qualitative study. J Clin Nurs 2014; 23: 132–144.

24.

Gibson

Aldiss

Taylor

. Involving health professionals in the development of an advanced symptom management system for young people: the ASyMS-YG study. Eur J Oncol Nurs 2009; 13: 187–192.

25.

Greaney

Sprunck-Harrild

Bennett

. Use of email and telephone prompts to increase self-monitoring in a web-based intervention: randomized controlled trial. J Med Internet Res 2012; 14: e96.

26.

Holtz

Lauckner

. Diabetes management via mobile phones: a systematic review. Telemed J E-Health 2012; 18: 175–184.

27.

Hopp

Hogan

Woodbridge

. The use of telehealth for diabetes management: a qualitative study of telehealth provider perceptions. Implement Sci 2007; 2: 14.

28.

Kawaguchi

Azuma

Ohta

. Development of a telenursing system for patients with chronic conditions. J Telemed Telecare 2004; 10: 239–244.

29.

Kearney

Kidd

Miller

. Utilising handheld computers to monitor and support patients receiving chemotherapy: results of a UK-based feasibility study. Support Care Cancer 2006; 14: 742–752.

30.

Kenealy

Parsons

MJG

Rouse

APB

. Telecare for diabetes, CHF or COPD: effect on quality of life, hospital use and costs. A randomised controlled trial and qualitative evaluation. PLoS One 2015; 10: e0116188.

31.

Langstrup

. Making connections through online asthma monitoring. Chron Illn 2008; 4: 118–126.

32.

Lin

Chen

Guo

. Developing a web 2.0 diabetes care support system with evaluation from care provider perspectives. J Med Syst 2012; 36: 2085–2095.

33.

Lyndon

Tyas

. Telehealth enhances self care and independence in people with long term conditions. Nurs Times 2010; 106: 12–13.

34.

MacNeill

Sanders

Fitzpatrick

. Experiences of front-line health professionals in the delivery of telehealth: a qualitative study. Br J Gen Pract 2014; 64: e401–e407.

35.

Maguire

Miller

Sage

. Results of a UK based pilot study of a mobile phone based advanced symptom management system (ASyMS) in the remote monitoring of chemotherapy related toxicity. Clin Effect Nurs 2005; 9: 202–210.

36.

Maguire

Ream

Richardson

. Development of a novel remote patient monitoring system: The advanced symptom management system for radiotherapy to improve the symptom experience of patients with lung cancer receiving radiotherapy. Cancer Nurs 2015; 38: E37–E47.

37.

Nundy

CYE

Hogan

. Using patient-generated health data from mobile technologies for diabetes self-management support: provider perspectives from an academic medical center. J Diabetes Sci Technol 2014; 8: 74–82.

38.

Ovretveit

Keller

Hvitfeldt

. Continuous innovation: developing and using a clinical database with new technology for patient-centred care: the case of the Swedish quality register for arthritis. Int J Qual Health Care 2013; 25: 118–124.

39.

Prescher

Deckwart

Winkler

. Telemedical care: feasibility and perception of the patients and physicians: a survey-based acceptance analysis of the Telemedical Interventional Monitoring in Heart Failure (TIM-HF) trial. Eur J Prevent Cardiol 2013; 20(2 Suppl): 18–24.

40.

Quinn

Sareh

Shardell

. Mobile diabetes intervention for glycemic control: impact on physician prescribing. J Diabetes Sci Technol 2014; 8: 362–370.

41.

Rich

Lamola

Gordon

. Video intervention/prevention assessment: a patient-centered methodology for understanding the adolescent illness experience. J Adolesc Health 2000; 27: 155–165.

42.

Seto

Leonard

Cafazzo

. Perceptions and experiences of heart failure patients and clinicians on the use of mobile phone-based telemonitoring. J Med Internet Res 2012; 14: e25.

43.

Seto

Leonard

Masino

. Attitudes of heart failure patients and health care providers towards mobile phone-based remote monitoring. J Med Internet Res 2010; 12: e55.

44.

Shea

Chamoff

. Patient reactions to vital sign measures: comparing home monitoring technology to face-to-face delivery. Home Health Care Manag Pract 2011; 23: 454–460.

45.

Shea

Chamoff

. Telehomecare communication and self-care in chronic conditions: moving toward a shared understanding. Worldviews Evid Based Nurs 2012; 9: 109–116.

46.

Thomas

Man

O'Cathain

. Effectiveness and cost-effectiveness of a telehealth intervention to support the management of long-term conditions: study protocol for two linked randomized controlled trials. Trials 2014; 15: 36.

47.

Urowitz

Wiljer

Dupak

. Improving diabetes management with a patient portal: a qualitative study of diabetes self-management portal. J Med Internet Res 2012; 14: e158.

48.

Zamith

Cardoso

Matias

. Home telemonitoring of severe chronic respiratory insufficient and asthmatic patients. Rev Port Pneumol 2009; 15: 385–417.

49.

Cakici

. Detecting the visible: the discursive construction of health threats in a syndromic surveillance system design. Societies 2014; 4: 399–413.

50.

Protheroe

Brooks

Chew-Graham

. ‘Permission to participate?’ A qualitative study of participation in patients from differing socio-economic backgrounds. J Health Psychol 2013; 18: 1046–1055.

51.

Stawarz K, Cox AL and Blandford A. Beyond self-tracking and reminders: designing smartphone apps that support habit formation. In: Proceedings of the 33rd annual ACM conference on human factors in computing systems, Seoul, 18–23 April 2015.

52.

May

. Making sense of technology adoption in healthcare: meso-level considerations. BMC Med 2015; 13(92): 1–3.

53.

Hopia

Punna

Laitinen

. A patient as a self-manager of their personal data on health and disease with new technology – challenges for nursing education. Nurs Educ Today 2015; 35: e1–e3.

54.

US Food and Drug Administration (FDA). FDA proposes health “app” guidelines, www.fda.gov/ForConsumers/ConsumerUpdates/ucm263332.htm (2015, accessed November 2015).

55.

US Food and Drug Administration (FDA). Mobile medical applications, hwww.fda.gov/medicaldevices/digitalhealth/mobilemedicalapplications/default.htm (2015, accessed November 2015).

56.

Austen

. What could derail the wearables revolution? Nature 2015; 525: 22–24.

57.

Till

. Exercise as labour: quantified self and the transformation of exercise into labour. Societies 2014; 4: 446–462.

58.

Thompson

Anderson

. Patient preferences and the bedside manner. Med Educ 1982; 16: 17–21.

59.

Vassilev

Rowsell

Pope

. Assessing the implementability of telehealth interventions for self-management support: a realist review. Implement Sci 2015; 10: 59.

60.

Wachter

. The digital doctor, McGraw-Hill Publishing, 2015.

61.

Lupton

. Beyond techno-Utopia: critical approaches to digital health technologies, Basel: MDPI Books, 2015.

62.

Hanna

May

Fairhurst

. The place of information and communication technology-mediated consultations in primary care: GPs' perspectives. Family Pract 2011. cmr087.

63.

Michie

Richardson

Johnston

. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med 2013; 46: 81–95.

64.

Michie

West

. A guide to development and evaluation of digital behaviour change interventions in healthcare, London: Silverback Publishing, 2016.

65.

Oudshoorn

. How places matter. Telecare technologies and the changing spatial dimensions of healthcare. Soc Studies Sci 2011; 42: 121–142.

66.

Huckvale

Prieto

Tilney

. Unaddressed privacy risks in accredited health and wellness apps: a cross-sectional systematic assessment. BMC Med 2015; 13: 214.

67.

Greenhalgh

Procter

Wherton

. What is quality in assistive living technology? The ARCHIE framework for effective telehealth and telecare services. BMC Med 2015; 13: 91. .