Emerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-tracking

The role of blood testing in prevention, diagnosis, and management of chronic diseases: A review

Blood tests are vital to prevention, diagnosis, and management of chronic diseases. Despite this, it can be challenging to construct a comprehensive view of the clinical importance of blood testing because relevant literature is typically fragmented across different disease areas and patient populations. This lack of collated evidence can also make it difficult for primary care providers to adhere to best practices for blood testing across different diseases and guidelines. Thus, this review article synthesizes the recommendations for, and importance of, blood testing across several common chronic conditions encountered in primary care and internal medicine, including cardiovascular diseases, diabetes mellitus, chronic kidney disease, vitamin D deficiency, iron deficiency, and rheumatoid arthritis. Future research is needed to continue improving chronic disease management through clearer dissemination and awareness of clinical guidelines among providers, and better access to blood testing for patients (e.g., via pre-visit laboratory testing).

Developing effective communication skills in audiology using anonymous patient feedback

OBJECTIVE

To explore the value of anonymous patient feedback for audiology students, examining alignment between student and patient judgments on communication skills and assessing how students utilise the feedback.

DESIGN

This study utilised a mixed methods design, employing a Likert survey to collect patient and student ratings on professionalism, compassion, and listening and talking skills in clinical encounters. Semi-structured interviews investigated the student perspective of receiving patient feedback.

STUDY SAMPLE

13 Audiology students and 31 patients who were placed at, or received care at an Audiology teaching clinic.

RESULTS

Patients' ratings across all measures were higher on average when compared to students' self-ratings, only correlating significantly for the measure concerning students' talking skills. Five themes and one subtheme were identified: Emotional impacts, A worthwhile experience, Contrasting priorities, Patients retake centre stage, and Self-reflective learners (subtheme Self-doubt).

CONCLUSIONS

This study reveals that patient feedback led student Audiologists to report heightened seriousness in their interactions and increased attention on skills vital for patient-centred care. The process boosted students' confidence and reinforced awareness of the patient's perspective. Further research is needed to gauge the extent of these effects and explore the feasibility of implementing a large-scale patient feedback program in audiology training settings.

Relationship between classic indicators of health behaviour and contraceptive choices in women in Flanders

BACKGROUND

In this study we shed light on ongoing trends in contraceptive use in Flanders (Belgium). Building on the fundamental cause theory and social diffusion of innovation theory, we examine socio-economic gradients in contraceptive use and the relationship to health behaviours.

METHODS

Using the unique and recently collected (2020) ISALA data, we used multinomial logistic regression to model the uptake of contraceptives and its association to educational level and health behaviour (N:4316 women).

RESULTS

Higher educated women, and women with a healthy lifestyle especially, tend to use non-hormonal contraceptives or perceived lower-dosage hormonal contraceptives that are still trustworthy from a medical point of view. Moreover, we identified a potentially vulnerable group in terms of health as our results indicate that women who do not engage in preventive health behaviours are more likely to use no, or no modern, contraceptive method.

DISCUSSION

The fact that higher educated women and women with a healthy lifestyle are less likely to use hormonal contraceptive methods is in line with patient empowerment, as women no longer necessarily follow recommendations by healthcare professionals, and there is a growing demand for naturalness in Western societies.

CONCLUSION

The results of this study can therefore be used to inform policy makers and reproductive healthcare professionals, since up-to-date understanding of women's contraceptive choices is clearly needed in order to develop effective strategies to prevent sexually transmitted infections and unplanned pregnancies, and in which women can take control over their sexuality and fertility in a comfortable and pleasurable way.

Patient-related barriers and enablers to the implementation of high-value physiotherapy for chronic pain: a systematic review

OBJECTIVE

To identify and synthesize patient-related barriers to and enablers of the implementation of high-value physiotherapy (HVP) for chronic pain. Furthermore, to review what patient-related interventions have been used to facilitate the implementation of HVP for chronic pain, as well as their efficacy.

METHODS

We systematically searched the APA PsycInfo, Embase, CINAHL, Medline, Scopus, and PEDro databases for peer-reviewed studies (published in English) of adults with chronic pain. We used the Theoretical Domains Framework of behavior change to synthesize identified themes relating to barriers and enablers. Outcomes from studies reporting on interventions were also qualitatively synthesized.

RESULTS

Fourteen studies reported on barriers and enablers, 8 of which related to exercise adherence. Themes common to barriers and enablers included perceived efficacy of treatment, interrelationship with the physiotherapist, exercise burden, and the patient's understanding of exercise benefits. Other barriers included fear of movement, fragmented care, and cost. Ten studies explored interventions, 9 of which aimed to improve exercise adherence. Of these, evidence from 4 randomized controlled trials of technology-based interventions demonstrated improved exercise adherence among intervention groups compared with controls.

CONCLUSION

Patients with chronic pain experience barriers to HVP, including their beliefs, the nature of their interaction with their physiotherapist, perceived treatment efficacy, and cost. Enablers include rapport with their physiotherapist, achievable exercises, and seamless cost-effective care. Technology-based interventions have demonstrated effectiveness at increasing exercise adherence. Our findings suggest that interventions seeking to enhance implementation of HVP need to consider the multifactorial barriers experienced by patients with chronic pain.

STUDY REGISTRATION

Open Science Framework (https://doi.org/10.17605/OSF.IO/AYGZV).

Now What? Collective Sensemaking and Sensegiving in the Cystic Fibrosis Community in Sweden During the Initial Phase of the COVID-19 Pandemic

The COVID-19 pandemic's effects on people's lives and society induced a need for rapid individual and collective sensemaking, including communication forums enabling stakeholders in the health ecosystem to share information, solve problems, and learn. This study specifically focused on the needs of the patients and family caregivers living with cystic fibrosis (CF) or primary ciliary dyskinesia (PCD), conditions that lead to chronic infections and inflammation in the airways. We explored how CF and PCD patients, family caregivers, and clinicians collectively received, processed, and used information about COVID-19 to facilitate self-care and health care decisions at the beginning of the pandemic. We applied macrocognitive theory to analyze qualitatively the questions and answers exchanged in a series of six webinars facilitated by a CF learning network at the beginning of the pandemic (March - April 2020). We identified three macrocognitive functions: sensemaking, decision-making, and replanning. We further generated nine themes: (a) understanding the nature of COVID-19, (b) exploring self-care needs and possibilities, (c) understanding health care possibilities, (d) making decisions about prevention and testing, (e) managing COVID-19 within families, (f) adjusting planned care, (g) replanning chronic care management, (h) defining COVID-19 health care strategies, and (i) refining health care policies. The exchange of questions and answers played a central role in facilitating important cognitive processes, which enabled a rapid anticipation of needs and adaptation of services to support patients, family caregivers, and clinicians during the COVID-19 pandemic.

Role of Incentives in the Use of Blockchain-Based Platforms for Sharing Sensitive Health Data: Experimental Study

BACKGROUND

Blockchain is an emerging technology that enables secure and decentralized approaches to reduce technical risks and governance challenges associated with sharing data. Although blockchain-based solutions have been suggested for sharing health information, it is still unclear whether a suitable incentive mechanism (intrinsic or extrinsic) can be identified to encourage individuals to share their sensitive data for research purposes.

OBJECTIVE

This study aimed to investigate how important extrinsic incentives are and what type of incentive is the best option in blockchain-based platforms designed for sharing sensitive health information.

METHODS

In this study, we conducted 3 experiments with 493 individuals to investigate the role of extrinsic incentives (ie, cryptocurrency, money, and recognition) in data sharing with research organizations.

RESULTS

The findings highlight that offering different incentives is insufficient to encourage individuals to use blockchain technology or to change their perceptions about the technology's premise for sharing sensitive health data. The results demonstrate that individuals still attribute serious risks to blockchain-based platforms. Privacy and security concerns, trust issues, lack of knowledge about the technology, lack of public acceptance, and lack of regulations are reported as top risks. In terms of attracting people to use blockchain-based platforms for data sharing in health care, we show that the effects of extrinsic motivations (cryptoincentives, money, and status) are significantly overshadowed by inhibitors to technology use.

CONCLUSIONS

We suggest that before emphasizing the use of various types of extrinsic incentives, the users must be educated about the capabilities and benefits offered by this technology. Thus, an essential first step for shifting from an institution-based data exchange to a patient-centric data exchange (using blockchain) is addressing technology inhibitors to promote patient-driven data access control. This study shows that extrinsic incentives alone are inadequate to change users' perceptions, increase their trust, or encourage them to use technology for sharing health data.

A rocky road but worth the drive: A longitudinal qualitative study of patient innovators and researchers cocreating research

BACKGROUND

Partnership research practices involving various stakeholder groups are gaining ground. Yet, the research community is still exploring how to effectively coproduce research together. This study describes (a) key programme developments in the creation of a 6-year partnership research programme in Sweden, and (b) explores the hopes, expectations, and experiences of patient innovators (i.e., individuals with lived experience as patients or caregivers who drive health innovations) and researchers involved in the programme during the first years.

METHODS

We conducted a prospective longitudinal qualitative study spanning the first 2 years of the programme. Data consisted of meeting protocols and interviews with 14 researchers and 6 patient innovators; 39 interviews were carried out in three evenly-spaced rounds. We identified significant events and discussion themes in the meeting protocols and analyzed the interviews using thematic analysis, applying a cross-sectional recurrent approach to track changes over time.

FINDINGS

Meeting protocols revealed how several partnership practices (e.g., programme management team, task forces, role description document) were cocreated, supporting the sharing of power and responsibilities among programme members. Based on the analysis of interviews, we created three themes: (1) paving the path to a better tomorrow, reflecting programme members' high expectations; (2) going on a road trip together, reflecting experiences of finding new roles and learning how to cocreate; (3) finding the tempo: from talking to doing, reflecting experiences of managing challenges and becoming productive as a team.

CONCLUSIONS

Our findings suggest that sharing, respecting, and acknowledging each other's experiences and concerns helps build mutual trust and shape partnership practices. High expectations beyond research productivity suggest that we need to consider outcomes at different levels, from the individual to society, when evaluating the impact of partnership research.

PATIENT OR PUBLIC CONTRIBUTION

The research team included members with formal experiences as researchers and members with lived experiences of being a patient or informal caregiver. One patient innovator coauthored this paper and contributed to all aspects of the research, including the design of the study; production of data (as interviewee); interpretation of findings; and drafting the manuscript.

Evaluation of a supportive care app for coordinating caring networks: an analysis of the first 19,000 users

Background

Major illnesses such as cancer, and other traumatic life events, can lead to sudden increases in supportive care needs. This study aimed to describe engagement, acceptability and satisfaction with a supportive care networking app under real-world conditions.

Methods

A total of 10,952 individuals used the app during the study period (2018-2022). The app is designed to enable "captains" to assemble a network of friends and family members to provide timely, and individually tailored, supportive care (including assistance with tasks such as taking children to school, cooking meals, grocery shopping, and transport to appointments). Engagement was determined from server data, whilst acceptability and satisfaction were captured using purposed-designed surveys.

Results

Users were mostly female (76%) and aged between 30 and 49 years (61%). The most common reason for using the app was sudden illness (web: 81%; mobile: 64%). An average of 42 tasks were requested per network, with a 32% acceptance rate. Significantly more tasks were requested (web: 52.2 tasks per network; mobile: 31.7 tasks per network; p < 0.001) and accepted (web: 43.2%; mobile: 20.2%; p < 0.001) in the web app vs. the mobile app. Task requests in the web app most commonly related to food (43% of requested tasks), social (15% of requested tasks) and children (13% of requested tasks). The task acceptance rate differed by task categories (p < 0.001), with tasks relating to transport, medical appointments and children accepted at the highest rates (56%, 52% and 49%, respectively). Acceptability and satisfaction data suggested that the app was well received and overall, participants were satisfied with the app.

Conclusion

Findings suggested that this support care networking app achieved widespread uptake for a wide variety of supportive care tasks. Future research focused on optimizing engagement with the mobile app and examining the effectiveness of the app for improving patient and hospital outcomes is warranted.

Recent Advances with Precision Medicine Treatment for Breast Cancer including Triple-Negative Sub-Type

Breast cancer is a heterogeneous disease with different molecular subtypes. Breast cancer is the second leading cause of mortality in woman due to rapid metastasis and disease recurrence. Precision medicine remains an essential source to lower the off-target toxicities of chemotherapeutic agents and maximize the patient benefits. This is a crucial approach for a more effective treatment and prevention of disease. Precision-medicine methods are based on the selection of suitable biomarkers to envision the effectiveness of targeted therapy in a specific group of patients. Several druggable mutations have been identified in breast cancer patients. Current improvements in omics technologies have focused on more precise strategies for precision therapy. The development of next-generation sequencing technologies has raised hopes for precision-medicine treatment strategies in breast cancer (BC) and triple-negative breast cancer (TNBC). Targeted therapies utilizing immune checkpoint inhibitors (ICIs), epidermal growth factor receptor inhibitor (EGFRi), poly(ADP-ribose) polymerase inhibitor (PARPi), antibody-drug conjugates (ADCs), oncolytic viruses (OVs), glucose transporter-1 inhibitor (GLUT1i), and targeting signaling pathways are potential treatment approaches for BC and TNBC. This review emphasizes the recent progress made with the precision-medicine therapy of metastatic breast cancer and TNBC.

Liquid Health. Medicine in the age of surveillance capitalism

Digital health technologies transform practices, roles, and relationships in medicine. New possibilities for a ubiquitous and constant data collection and the processing of data in real-time enable more personalized health services. These technologies might also allow users to actively participate in health practices, thus potentially changing the role of patients from passive receivers of healthcare to active agents. The crucial driving force of this transformation is the implementation of data-intensive surveillance and monitoring as well as self-monitoring technologies. Some commentators use terms like revolution, democratization, and empowerment to describe the aforementioned transformation process in medicine. The public debate as well as most of the ethical discourse on digital health tends to focus on the technologies themselves, mostly ignoring the economic framework of their design and implementation. Analyzing the transformation process connected to digital health technologies needs an epistemic lens that also considers said economic framework, which I argue is surveillance capitalism. This paper introduces the concept of liquid health as such an epistemic lens. Liquid health is based on Zygmunt Bauman's framing of modernity as a process of liquefaction that dissolves traditional norms and standards, roles, and relations. By using liquid health as an epistemic lens, I aim to show how digital health technologies reshape concepts of health and illness, change the scope of the medical domain, and liquify roles and relationships that surround health and healthcare. The basic hypothesis is that although digital health technologies can lead to personalization of treatment and empowerment of users, their economic framework of surveillance capitalism may undermine these very goals. Using liquid health as a concept allows us to better understand and describe practices of health and healthcare that are shaped by digital technologies and the specific economic practices they are inseparably attached to.

The quality of informational social support in online health communities: A content analysis of cancer-related discussions

Objective

Informational social support is one of the main reasons for patients to visit online health communities (OHCs). Calls have been made to investigate the objective quality of such support in the light of a worrying number of inaccurate online health-related information. The main aim of this study is to conceptualize the Quality of Informational Social Support (QISS) and develop and test a measure of QISS for content analysis. A further aim is to investigate the level of QISS in cancer-related messages in the largest OHC in Slovenia and examine the differences among various types of discussion forums, namely, online consultation forums, online support group forums, and socializing forums.

Methods

A multidimensional measurement instrument was developed, which included 20 items in a coding scheme for a content analysis of cancer-related messages. On a set of almost three million posts published between 2015 and 2019, a machine-learning algorithm was used to detect cancer-related discussions in the OHC. We then identified the messages providing informational social support, and through quantitative content analysis, three experts coded a random sample of 403 cancer-related messages for the QISS.

Results

The results demonstrate a good level of interrater reliability and agreement for a QISS scale with six dimensions, each demonstrating good internal consistency. The results reveal large differences among the social support, socializing, and consultation forums, with the latter recording significantly higher quality in terms of accuracy (M = 4.48, P < .001), trustworthiness (M = 4.65, P < .001), relevance (M = 3.59, P < .001), and justification (M = 3.81, P = .05) in messages providing informational social support regarding cancer-related issues.

Conclusions

This study provides the research field with a valid tool to further investigate the factors and consequences of varying quality of information exchanged in supportive communication. From a practical perspective, OHCs should dedicate more resources and develop mechanisms for the professional moderation of health-related topics in socializing forums and thereby suppress the publication and dissemination of low-quality information among OHC users and visitors.

Evolution of discussion topics on an online depression self-help group

Purpose

This study aims to explore the evolutionary pattern of discussion topics over time in an online depression self-help community.

Design/methodology/approach

Using the Latent Dirichlet Allocation (LDA) method, the authors analyzed 17,534 posts and 138,567 comments posted over 8 years on an online depression self-help group in China and identified the major discussion topics. Based on significant changes in the frequency of posts over time, the authors identified five stages of development. Through a comparative analysis of discussion topics in the five stages, the authors identified the changes in the extent and range of topics over time. The authors discuss the influence of socio-cultural factors on depressed individuals' health information behavior.

Findings

The results illustrate an evolutionary pattern of topics in users' discussion in the online depression self-help group, including five distinct stages with a sequence of topic changes. The discussion topics of the group included self-reflection, daily record, peer diagnosis, companionship support and instrumental support. While some prominent topics were discussed frequently in each stage, some topics were short-lived.

Originality/value

While most prior research has ignored topic changes over time, the study takes an evolutionary perspective of online discussion topics among depressed individuals. The authors provide a nuanced account of the progression of topics through five distinct stages, showing that the community experienced a sequence of changes as it developed. Identifying this evolutionary pattern extends the scope of research on depression therapy in China and offers a deeper understanding of the support that individuals with depression seek, receive and provide online.

What are the ways in which social media is used in the context of complementary and alternative medicine in the health and medical scholarly literature? a scoping review

BACKGROUND

Despite the increased use of social media to share health-related information and the substantial impact that complementary and alternative medicine (CAM) can have on individuals' health and wellbeing, currently, to our knowledge, there is no review that compiles research on how social media is used in the context of CAM. The objective of this study was to summarize what are the ways in which social media is used in the context of CAM.

METHODS

A scoping review was conducted, following Arksey and O'Malley's five-stage methodological framework. MEDLINE, EMBASE, PsycINFO, AMED, and CINAHL databases were systematically searched from inception until October 3, 2020, in addition to the Canadian Agency for Drugs and Technology in Health (CADTH) website. Eligible studies had to have investigated how at least one social media platform is used in the context of a single or multiple types of CAM treatments.

RESULTS

Searches retrieved 1714 items following deduplication, of which 1687 titles and abstracts were eliminated, leaving 94 full-text articles to be considered. Of those, 65 were not eligible, leaving a total of 29 articles eligible for review. Three themes emerged from our analysis: 1) social media is used to share user/practitioner beliefs, attitudes, and experiences about CAM, 2) social media acts as a vehicle for the spread of misinformation about CAM, and 3) there are unique challenges with social media research in the context of CAM.

CONCLUSIONS

In addition to social media being a useful tool to share user/practitioner beliefs, attitudes, and experiences about CAM, it has shown to be accessible, effective, and a viable option in delivering CAM therapies and information. Social media has also been shown to spread a large amount of misleading and false information in the context of CAM. Additionally, this review highlights the challenges with conducting social media research in the context of CAM, particularly in collecting a representative sample.

Reimagining health services provision for neglected groups: The "personalization from below" phenomenon

How can data-driven citizen science activities supporting health research and services provision meet the needs of unrepresented and neglected groups through increased personalization? In this short Perspective, we explore "personalization from below" as a concept designating forms of citizen science-based data altruism that specifically push for and enact a different understanding of both health services and personalization. We develop the argument that such phenomenon taking place outside "institutionalized" health-related practices could make health services provision more inclusive of values that matter to people. We contextualize instances of "personalization from below," discuss related data governance models and alternative public health interventions, and conclude by outlining three key arguments in favor of "personalization from below" and future research avenues.

Patient lead users experience of the COVID-19 pandemic: a qualitative interview study

OBJECTIVES

Patient lead users can be defined as patients or relatives who use their knowledge and experience to improve their own or a relative's care situation and/or the healthcare system, and who are active beyond what is usually expected. The objective of this study is to explore patient lead users' experiences and engagement during the early COVID-19 pandemic.

DESIGN

Qualitative in-depth interviews with a cross-sectional time horizon.

SETTING

The early COVID-19 pandemic in Sweden, from 1 June through 14 September, 2020.

PARTICIPANTS

A total of 10 patient lead users were recruited from the Swedish patient lead users (spetspatient) network. All participants were living with different long-term conditions and matched the definition of being patient lead users.

RESULTS

We found that during the early pandemic, patient lead users experienced that they no longer knew how to best manage their own health and care situations. On an individual level, they described an initial lack of knowledge, new routines, including a change in their health and an experience of people without a disease being in the same situation as them, for a while. On a systemic level, they described a fear of imminent unmet-care backlogs and decreased opportunities for sharing patient perspectives in care organisation, but also described increased networking.

CONCLUSIONS

Patient lead users can be seen as an emerging community of practice, and as such could be a valuable resource as a complementary communication channel for an improved health system. The health systems were not able to fully acknowledge and engage with the resource of patient lead users during the pandemic.

Donating Health Data to Research: Influential Characteristics of Individuals Engaging in Self-Tracking

Health self-tracking is an ongoing trend as software and hardware evolve, making the collection of personal data not only fun for users but also increasingly interesting for public health research. In a quantitative approach we studied German health self-trackers (N = 919) for differences in their data disclosure behavior by comparing data showing and sharing behavior among peers and their willingness to donate data to research. In addition, we examined user characteristics that may positively influence willingness to make the self-tracked data available to research and propose a framework for structuring research related to self-measurement. Results show that users’ willingness to disclose data as a “donation” more than doubled compared to their “sharing” behavior (willingness to donate = 4.5/10; sharing frequency = 2.09/10). Younger men (up to 34 years), who record their vital signs daily, are less concerned about privacy, regularly donate money, and share their data with third parties because they want to receive feedback, are most likely to donate data to research and are thus a promising target audience for health data donation appeals. The paper adds to qualitative accounts of self-tracking but also engages with discussions around data sharing and privacy.

The Age of Next-Generation Therapeutic-Microbe Discovery: Exploiting Microbe-Microbe and Host-Microbe Interactions for Disease Prevention

Humans are considered "superorganisms," harboring a diverse microbial collective that outnumbers human cells 10 to 1. Complex and gravely understudied host- and microbe-microbe interactions-the product of millions of years of host-microbe coevolution-govern the superorganism in almost every aspect of life functions and overall well-being. Abruptly disrupting these interactions via extrinsic factors has undesirable consequences for the host. On the other hand, supplementing commensal or beneficial microbes may mitigate perturbed interactions or enhance the interactive relationships that ultimately benefit all parties. Hence, immense efforts have focused on dissecting the innumerable host- and microbe-microbe relationships to characterize if a "positive" or "negative" interaction is at play and to exploit such behavior for broader implications. For example, microbiome research has worked to identify and isolate naturally antipathogenic microbes that may offer therapeutic potential either in a direct, one-on-one application or by leveraging its unique metabolic properties. However, the discovery and isolation of such desired therapeutic microbes from complex microbiota have proven challenging. Currently, there is no conventional technique to universally and functionally screen for these microbes. With this said, we first describe in this review the historical (probiotics) and current (fecal microbiota or defined consortia) perspectives on therapeutic microbes, present the discoveries of therapeutic microbes through exploiting microbe-microbe and host-microbe interactions, and detail our team's efforts in discovering therapeutic microbes via our novel microbiome screening platform. We conclude this minireview by briefly discussing challenges and possible solutions with therapeutic microbes' applications and paths ahead for discovery.

Remote assessment and reinforcement of patient awareness of role of lifestyle modification and treatment adherence in polycystic ovary syndrome using an online video based educational module

Objective:

To evaluate the role of an online, video-based, structured, educational module in increasing awareness in women with polycystic ovary syndrome (PCOS).

Material and Methods:

Patients with PCOS were assessed for baseline awareness about PCOS, quantified as “awareness score”, using a validated questionnaire. Topics assessed included factual and conceptual knowledge of the disease and awareness of behaviour-related lifestyle modification and therapy compliance in PCOS. An educational video module was shown to the participants which covered normal menstrual physiology, symptomatology, pathophysiology and natural history of PCOS, a comparative animation of healthy versus unhealthy lifestyle, indications of pharmacological intervention, and role of treatment adherence. The questionnaire was re-administered after exposure to the educational module, and effectiveness of the teaching method was evaluated by comparing pre and post test scores.

Results:

The total number of subjects was 41. Baseline knowledge was “fair” in 17.1%, “moderate” in 48.8% and “good” in 34.1%. Significant increase in awareness scores was noted among participants regarding PCOS after exposure to the learning module from 15.09±4.31 to 18.60±3.85 (p<0.00001) with a large effect size (Cohen’s d=0.85). Most (48.8%) of the respondents had baseline awareness in the “moderate” range (scores between; 11-17) whereas post intervention scores improved to the “good” category for 63.4% of the women.

Conclusion:

The educational module was effective in significantly increasing knowledge about PCOS. Patient education is likely to help reinforce the message about lifestyle modification and continued compliance and may aid in promoting a patient-driven healthcare model in PCOS.

Chronicity and the patient's decision-making work. The case of an advanced cancer patient

This paper focuses on the particular situation of an advanced cancer patient whose condition has taken a chronic turn. We argue that chronicity of this kind sometimes falls at the frontier of Evidence Based Medicine because the uncertainty about the patient's condition can lead physicians to resort to clinical trials or non-licensed drugs to prevent the disease from progressing. This situation leaves plenty of scope for individual adjustments between patients and their doctors. Advanced cancer is regarded here not just as a biological event but as a chronic illness and a 'negotiated reality'. We argue that the chronicity of advanced cancer patients' situation broadens the patients' scope for 'work', and we have called this specific type of patient's work 'decision-making work'. This paper is based on a case study focusing on Patrick, a middle-aged Frenchman with metastatic lung cancer who underwent oncological treatment for seven years and was strongly determined to find new therapeutic options even if this meant having to go abroad. He actively orchestrated his therapeutic itinerary by reorganising his relationships with the medical world and coordinating the physicians' work. His particular social position enabled Patrick to bypass some of the current medical rules and to reorganise the usual pattern of distribution of medical responsibilities. The chronicity of his condition placed him at the very frontier of the health care system.

Remote Monitoring of Chronic Critically Ill Patients after Hospital Discharge: A Systematic Review

Background: Over the past few decades, critical care has seen many advancements. These advancements resulted in a considerable increase in the prevalence of chronically critically ill patients requiring prolonged medical care, which led to a massive increase in healthcare utilization. Methods: We performed a search for suitable articles using PubMed and Google Scholar from the inception of these databases to 15 May 2021. Results: Thirty-four articles were included in the review and analyzed. We described the following characteristics and problems with chronic critically ill patient management: the patient population, remote monitoring, the monitoring of physiological parameters in chronic critically ill patients, the anatomical location of sensors, the barriers to implementation, and the main technology-related issues. The main challenges in the management of these patients are (1) the shortage of caretakers, (2) the periodicity of vital function monitoring (e.g., episodic measuring of blood pressure leads to missing important critical events such as hypertension, hypotension, and hypoxia), and (3) failure to catch and manage critical physiological events at the right time, which can result in poor outcomes. Conclusions: The prevalence of critically ill patients is expected to grow. Technical solutions can greatly assist medical personnel and caregivers. Wearable devices can be used to monitor blood pressure, heart rate, pulse, respiratory rate, blood oxygen saturation, metabolism, and central nervous system function. The most important points that should be addressed in future studies are the performance of the remote monitoring systems, safety, clinical and economic outcomes, as well as the acceptance of the devices by patients, caretakers, and healthcare professionals.

Effects of physical activity interventions using wearables to improve objectively-measured and patient-reported outcomes in adults following orthopaedic surgical procedures: A systematic review

OBJECTIVE

To synthesize evidence on physical activity interventions that used wearables, either alone or in combination with education or rehabilitation, in adults following orthopaedic surgical procedures.

METHODS

PubMed, CINAHL, PsycINFO and EMBASE were searched for randomized controlled trials of wearable-based interventions from each database's inception to August 2021 in patients undergoing orthopaedic surgery. Relevant outcomes included physical activity, physical function, pain, psychological distress, or general health. PEDro scale scoring ranges from 0 to 10 and was used to appraise studies as high (≥7), moderate (5-6), or poor (<5) quality.

RESULTS

Of 335 articles identified, 6 articles met eligibility criteria. PEDro scores ranged from 2 to 6, with 3 studies of moderate quality and 3 of poor quality. Studies included patients undergoing total knee (number; n = 4) or total knee or hip (n = 1) arthroplasty and lumbar disc herniation surgery (n = 1). In addition to wearables, intervention components included step diary (n = 2), motivational interviewing (n = 1), goal setting (n = 2), tailored exercise program (n = 2), or financial incentives (n = 1). Interventions were delivered in-person (n = 2), remotely (n = 3) or in a hybrid format (n = 1). Intervention duration ranged from 6 weeks to 6 months. Compared to controls, 3 moderate quality studies reported greater improvement in steps/day; however, 1 moderate and 2 poor quality studies showed no between-group difference in physical function, pain, or quality of life. No serious adverse events related to the use of wearable were reported.

CONCLUSIONS

The effects of physical activity interventions using wearables, either delivered in-person or remotely, appear promising for increasing steps per day after joint arthroplasty; however, this finding should be viewed with caution since it is based on 3 moderate quality studies. Further research is needed to determine the therapeutic effects of using wearables as an intervention component in patients undergoing other orthopaedic surgical procedures.

TRIAL REGISTRATION

PROSPERO Registration Number: CRD42020186103.

Research on the Connotation and Dimension of Consumers’ Quantified-Self Consciousness

Quantified-self practice has penetrated into people’s daily life. Academic circles have begun to study it, but at present, scholars have not raised quantified-self practice to the level of consciousness. In order to explore the structural connotation of quantified-self consciousness and then provide management reference for enterprises offering quantified-self services, this study conducted in-depth interviews with self-trackers with the method of grounded theory. The conceptual model of quantified-self consciousness is formed through step-by-step coding, and the theoretical saturation is tested by reserving original sentences and crawling relevant online comments. The model shows that quantified-self consciousness can be divided into three dimensions: individual thinking, social projection, and data sensitivity.

Digital health transformation in Saudi Arabia: A cross-sectional analysis using Healthcare Information and Management Systems Society’ digital health indicators

Background

The digital revolution has had a huge impact on healthcare around the world. Digital technology could dramatically improve the accuracy of diagnosis, treatment, health outcomes, efficiency of care, and workflow of healthcare operations. Using health information technology will bring major improvements in patient outcomes.

Purpose

This study aims to measure the readiness for digital health transformation at different hospitals in the Eastern Province, Saudi Arabia in relation to Saudi Vision 2030 based on the four dimensions adopted by the Healthcare Information and Management Systems Society: person-enabled health, predictive analytics, governance and workforce, and interoperability.

Methods

The study was conducted with a cross-sectional design using data collected through an online questionnaire from 10 healthcare settings, the questionnaire consists of the four digital health indicators. The survey was developed by Healthcare Information and Management Systems Society for the purpose of assessing the level of digital maturity in healthcare settings.

Results

Ten healthcare facilities in the Eastern Province, both private and governmental, were included in the study. The highest total scores for digital health transformation were reported in private healthcare facilities (median score for private facilities = 77, public facilities = 71). The ‘governance and workforce’ was the most implemented dimension among the healthcare facilities in the study (median = 80), while the dimension that was least frequently implemented was predictive analytics (median score = 70). In addition, tertiary hospitals scored the least in digital transformation readiness (median = 74) compared to primary and secondary healthcare facilities in the study.

Conclusion

The results of the study show that private healthcare facilities scored higher in digital health transformation indicators. These results will be useful for promoting policymakers’ understanding of the level of digital health transformation in the Eastern Province and for the creation of a strategic action plan.

Clinicians and Older Adults' Perceptions of the Utility of Patient-Generated Health Data in Caring for Older Adults: Exploratory Mixed Methods Study

Background

Many people are motivated to self-track their health and optimize their well-being through mobile health apps and wearable devices. The diversity and complexity of these systems have evolved over time, resulting in a large amount of data referred to as patient-generated health data (PGHD), which has recently emerged as a useful set of data elements in health care systems around the world. Despite the increased interest in PGHD, clinicians and older adults’ perceptions of PGHD are poorly understood. In particular, although some clinician barriers to using PGHD have been identified, such as concerns about data quality, ease of use, reliability, privacy, and regulatory issues, little is known from the perspectives of older adults.

Objective

This study aims to explore the similarities and differences in the perceptions of older adults and clinicians with regard to how various types of PGHD can be used to care for older adults.

Methods

A mixed methods study was conducted to explore clinicians and older adults’ perceptions of PGHD. Focus groups were conducted with older adults and health care providers from the Greater Toronto area and the Kitchener-Waterloo region. The participants were asked to discuss their perceptions of PGHD, including facilitators and barriers. A questionnaire aimed at exploring the perceived usefulness of a range of different PGHD was also embedded in the study design. Focus group interviews were transcribed for thematic analysis, whereas the questionnaire results were analyzed using descriptive statistics.

Results

Of the 9 participants, 4 (44%) were clinicians (average age 38.3 years, SD 7 years), and 5 (56%) were older adults (average age 81.0 years, SD 9.1 years). Four main themes were identified from the focus group interviews: influence of PGHD on patient-provider trust, reliability of PGHD, meaningful use of PGHD and PGHD-based decision support systems, and perceived clinical benefits and intrusiveness of PGHD. The questionnaire results were significantly correlated with the frequency of PGHD mentioned in the focus group interviews (r=0.42; P=.03) and demonstrated that older adults and clinicians perceived blood glucose, step count, physical activity, sleep, blood pressure, and stress level as the most useful data for managing health and delivering high-quality care.

Conclusions

This embedded mixed methods study generated several important findings about older adults and clinicians’ perceptions and perceived usefulness of a range of PGHD. Owing to the exploratory nature of this study, further research is needed to understand the concerns about data privacy, potential negative impact on the trust between older adults and clinicians, data quality and quantity, and usability of PGHD-related technologies for older adults.

Comprehension, Perception, and Projection

Health social networks (HSNs) allow individuals with health information needs to connect and discuss health-related issues online. Political-technology intertwinement (e.g. GDPR and Digital Technology) highlights that users need to be aware, understand, and willing to provide electronic consent (eConsent) when sharing personal information online. The objective of this study is to explore the ‘As-Is’ factors which impact individuals’ decisional autonomy when consenting to the privacy policy (PP) and Terms and Conditions (T&Cs) on a HSN. We use a Situational Awareness (SA) lens to examine decision autonomy when providing eConsent. A mixed-methods approach reveals that technical and privacy comprehension, user perceptions, and projection of future consequences impact participants’ decision autonomy in providing eConsent. Without dealing with the privacy paradox at the outset, decision awareness and latterly decision satisfaction is negatively impacted. Movement away from clickwrap online consent to customised two-way engagement is the way forward for the design of eConsent.

Implementation and evaluation of a multivariate abstraction-based, interval-based dynamic time-warping method as a similarity measure for longitudinal medical records

OBJECTIVES

A common prerequisite for tasks such as classification, prediction, clustering and retrieval of longitudinal medical records is a clinically meaningful similarity measure that considers both [multiple] variable (concept) values and their time. Currently, most similarity measures focus on raw, time-stamped data as these are stored in a medical record. However, clinicians think in terms of clinically meaningful temporal abstractions, such as "decreasing renal functions", enabling them to ignore minor time and value variations and focus on similarities among the clinical trajectories of different patients. Our objective was to define an abstraction- and interval-based methodology for matching longitudinal, multivariate medical records, and rigorously assess its value, versus the option of using just the raw, time-stamped data.

METHODS

We have developed a new methodology for determination of the relative distance between a pair of longitudinal records, by extending the known dynamic time warping (DTW) method into an interval-based dynamic time warping (iDTW) methodology. The iDTW methodology includes (A): A three-steps interval-based representation (iRep) method: [1] abstracting the raw, time-stamped data of the longitudinal records into clinically meaningful interval-based abstractions, using a domain-specific knowledge base, [2] scoping the period of comparison of the records, [3] creating from the intervals a symbolic time series, by partitioning them into a predetermined temporal granularity; (B) An interval-based matching (iMatch) method to match each relevant pair of multivariate longitudinal records, each represented as multiple series of short symbolic intervals in the determined temporal granularity, using a modified DTW version.

EVALUATION

Three classification or prediction tasks were defined: (1) classifying 161 records of oncology patients as having had autologous versus allogenic bone-marrow transplantation; (2) classifying the longitudinal records of 125 hepatitis patients as having B or C hepatitis; and (3) predicting micro- or macro-albuminuria in the second year, for 151 diabetes patients who were followed for five years. The raw, time-stamped, multivariate data within each medical record, for one, two, or three concepts out of four or five concepts judged as relevant in each medical domain, were abstracted into clinically meaningful intervals using the Knowledge-Based Temporal-Abstraction method, using previously acquired knowledge. We focused on two temporal-abstraction types: (1) State abstractions, which discretize a concept's raw value into a predetermined range (e.g., LOW or HIGH Hemoglobin); and (2) Gradient abstractions, which indicate the trend of the concept's value (e.g., INCREASING, DECREASING Hemoglobin value). We created all of the combinations of either uni-dimensional (State or Gradient) or multi-dimensional (State and Gradient) abstractions, of all of the concepts used. Classification of a record was determined by using a majority of the k-Nearest-Neighbors (KNN) of the given record, k ranging over the odd numbers (to break ties) from 1 to N, N being the size of the training set. We have experimented with all possible configurations of the parameters that our method uses. Overall, a total of 75,936 experiments were performed: 33,600 in the Oncology domain, 28,800 in the Hepatitis domain, and 13,536 in the Diabetes domain. Each experiment involved the performance of a 10-fold Cross Validation to compute the mean performance of a particular iDTW method-configuration set of settings, for a specific subset of one, two, or three concepts out of all of the domain-specific concepts relevant to the classification or prediction task on which the experiment focuses. We measured for each such experimental combination the Area Under the Curve (AUC) and the optimal Specificity/Sensitivity ratio using Youden's Index. We then aggregated the experiments by the types of unidimensional or multidimensional abstractions used in them (including the use of only raw concepts as a special case); for example, two state abstractions of different concepts, and one gradient abstraction of a third concept. We compared the mean AUC when using each such feature representation, or combination of abstractions, across all possible method-setting configurations, to the mean AUC when using as a feature representation, for the same task, only raw concepts, also across all possible method-setting configurations. Finally, we applied a paired t-test, to determine whether the mean difference between the accuracy of each temporal-abstraction representation, across all concept and configuration combinations, and the respective raw-concept combinations, across all concept subset and configuration combinations, is significant (P < 0.05).

RESULTS

The mean performance of the classification and prediction tasks when using, as a feature representation, the various temporal-abstraction combinations, was significantly higher than that performance when using only raw data. Furthermore, in each domain and task, there existed at least one representation using interval-based abstractions whose use led, on average (over all concept subset combinations and method configurations) to a significantly better performance than the use of only subsets of the raw time-stamped data. In seven of nine combinations of domain type (out of three) and number of concepts used (one, two, or three), the variance of the AUCs (for all representations and configurations) was considerably higher across all raw-concept subsets, compared to all abstract combinations. Increasing the number of features used by the matching task enhanced performance. Using multi-dimensional abstractions of the same concept further enhanced the performance. When using only raw data, increasing the number of neighbors monotonically increased the mean performance (over all concept combinations and method configurations) until reaching an optimal saddle-point aroundN; when using abstractions, however, optimal mean performance was often reached after matching only five nearest neighbors.

CONCLUSIONS

Using multivariate and multidimensional interval-based, abstraction-based similarity measures is feasible, and consistently and significantly improved the mean classification and prediction performance in time-oriented domains, using DTW-inspired methods, compared to the use of only raw, time-stamped data. It also made the KNN classification more effective. Nevertheless, although the mean performance for the abstract representations was higher than the mean performance when using only raw-data concepts, the actual optimal classification performance in each domain and task depends on the choice of the specific raw or abstract concepts used as features.

Evolution of Wearable Devices in Health Coaching: Challenges and Opportunities

Wearable devices hold an enormous potential in contributing to an improved global health. The availability, non-invasiveness, and affordability of those systems make them promising candidates to transform the standard of care for health coaching. These wearable devices are now considered as versatile coaching systems. Patients who wish to improve their health and well-being refer to wearables for tracking and quantifying their improvement. The timeliness of the “wearable device as a health coaching enabler” field of research will inevitably know a prominent growth in the upcoming years. This growth is expected to stem from both the computing and the medical fields. In this perspective article, we list the potential challenges as well as the opportunities of this newly born field from an interdisciplinary perspective. We mainly focus on both the computing and healthcare perspectives. We also chart guidelines for the healthcare research community that is willing to get involved in the computing field to harness the benefits of wearable devices.

Robotic-Based Well-Being Monitoring and Coaching System for the Elderly in Their Daily Activities

The increasingly ageing population and the tendency to live alone have led science and engineering researchers to search for health care solutions. In the COVID 19 pandemic, the elderly have been seriously affected in addition to suffering from isolation and its associated and psychological consequences. This paper provides an overview of the RobWell (Robotic-based Well-Being Monitoring and Coaching System for the Elderly in their Daily Activities) system. It is a system focused on the field of artificial intelligence for mood prediction and coaching. This paper presents a general overview of the initially proposed system as well as the preliminary results related to the home automation subsystem, autonomous robot navigation and mood estimation through machine learning prior to the final system integration, which will be discussed in future works. The main goal is to improve their mental well-being during their daily household activities. The system is composed of ambient intelligence with intelligent sensors, actuators and a robotic platform that interacts with the user. A test smart home system was set up in which the sensors, actuators and robotic platform were integrated and tested. For artificial intelligence applied to mood prediction, we used machine learning to classify several physiological signals into different moods. In robotics, it was concluded that the ROS autonomous navigation stack and its autodocking algorithm were not reliable enough for this task, while the robot’s autonomy was sufficient. Semantic navigation, artificial intelligence and computer vision alternatives are being sought.

How Self-tracking and the Quantified Self Promote Health and Well-being: Systematic Review

BACKGROUND

Self-tracking technologies are widely used in people's daily lives and health care. Academic research on self-tracking and the quantified self has also accumulated rapidly in recent years. Surprisingly, there is a paucity of research that reviews, classifies, and synthesizes the state of the art with respect to self-tracking and the quantified self.

OBJECTIVE

Our objective was to identify the state of the art of self-tracking and the quantified self in terms of health and well-being.

METHODS

We have undertaken a systematic literature review on self-tracking and the quantified self in promoting health and well-being. After a rigorous literature search, followed by inclusions, exclusions, and the application of article quality assessment protocols, 67 empirical studies qualified for the review.

RESULTS

Our results demonstrate that prior research has focused on 3 stakeholders with respect to self-tracking and the quantified self, namely end users, patients and people with illnesses, and health care professionals and caregivers. We used these stakeholder groups to cluster the research themes of the reviewed studies. We identified 11 research themes. There are 6 themes under the end-user cluster: user motivation and goal setting, usage and effects of self-tracking, continuance intention and long-term usage, management of personal data, rejection and discontinuance, and user characteristics. The patient and people with illnesses cluster contains three themes: usage experience of patients and people with illnesses, management of patient-generated data, and advantages and disadvantages in the clinical context. The health care professional and caregiver cluster contains two themes: collaboration among patients, health care professionals, and caregivers, and changes in the roles of patients and professionals. Moreover, we classified the future research suggestions given in the literature into 5 directions in terms of research designs and research topics. Finally, based on our reflections on the observations from the review, we suggest four future research directions: (1) users' cognitions and emotions related to processing and interpreting the information produced by tracking devices and apps; (2) the dark side of self-tracking (eg, its adverse psychosocial consequences); (3) self-tracking as a societal phenomenon; and (4) systemic impacts of self-tracking on health care and the actors involved.

CONCLUSIONS

This systematic literature review contributes to research and practice by assisting future research activities and providing practitioners with a concise overview of the state of the art of self-tracking and the quantified self.

A qualitative study of clinician perceptions regarding the potential role for digital health interventions for the management of COPD

Effective self-management of chronic obstructive pulmonary disease (COPD) can lead to increased patient control and reduced health care costs. However, both patients and healthcare professionals encounter significant challenges. Digital health interventions, such as smart oximeters and COPD self-management applications, promise to enhance the management of COPD, yet, there is little evidence to support their use and user-experience issues are still common. Understanding the needs of healthcare professionals is central for increasing adoption and engagement with digital health interventions but little is known about their perceptions of digital health interventions in COPD. This paper explored the perceptions of healthcare professionals regarding the potential role for DHI in the management of COPD. Snowball sampling was used to recruit the participants (n = 32). Each participant underwent a semi-structured interview. Using NVivo 12 software, thematic analysis was completed. Healthcare professionals perceive digital health interventions providing several potential benefits to the management of COPD including the capture of patient status indicators during the interappointment period, providing new patient data to support the consultation process and perceived digital health interventions as a potential means to improve patient engagement. The findings offer new insights regarding potential future use-cases for digital health interventions in COPD, which can help ease user-experience issues as they align with the needs of healthcare professionals.

The Exposome in the Era of the Quantified Self

Human health is regulated by complex interactions among the genome, the microbiome, and the environment. While extensive research has been conducted on the human genome and microbiome, little is known about the human exposome. The exposome comprises the totality of chemical, biological, and physical exposures that individuals encounter over their lifetimes. Traditional environmental and biological monitoring only targets specific substances, whereas exposomic approaches identify and quantify thousands of substances simultaneously using nontargeted high-throughput and high-resolution analyses. The quantified self (QS) aims at enhancing our understanding of human health and disease through self-tracking. QS measurements are critical in exposome research, as external exposures impact an individual's health, behavior, and biology. This review discusses both the achievements and the shortcomings of current research and methodologies on the QS and the exposome and proposes future research directions.

The work of having a chronic condition: development and psychometric evaluation of the distribution of co-care activities (DoCCA) scale

BACKGROUND

Chronic care involves multiple activities that can be performed by individuals and healthcare staff as well as by other actors and artifacts, such as eHealth services. Thus, chronic care management can be viewed as a system where the individual interacts with people and eHealth services performing activities to maintain or improve health and functioning, called co-care. Yet, the system perspective is not reflected in concepts such as person-centered care and shared decision making. This limits the understanding of individuals' global experience of chronic care management and subsequently the ability to optimize chronic care. The aim of this study was threefold: (1) to propose a theory-based operationalization of co-care for chronic care management, (2) to develop a scale to measure co-care as a distributed system of activities, and (3) to evaluate the scale's psychometric properties. With the theory of distributed cognition as a theoretical underpinning, co-care was operationalized along three dimensions: experience of activities, needs support, and goal orientation.

METHODS

Informed by the literature on patient experiences and work psychology, a scale denoted Distribution of Co-Care Activities (DoCCA) was developed with the three conceptualized dimensions, the activities dimension consisting of three sub-factors: demands, unnecessary tasks, and role clarity. It was tested with 113 primary care patients with chronic conditions in Sweden at two time points.

RESULTS

A confirmatory factor analysis showed support for a second-order model with the three conceptualized dimensions, with activities further divided into the three sub-factors. Cronbach's alpha values indicated a good to excellent reliability of the subscales, and correlations across time points with panel data indicated satisfactory test-retest reliability. Convergent, concurrent and predictive validity of the scale were, overall, satisfactory.

CONCLUSIONS

The psychometric evaluation supports a model consisting of activities (demands, unnecessary tasks, and role clarity), needs support and goal orientation that can be reliably measured with the DoCCA scale. The scale provides a way to assess chronic care management as a system, considering the perspective of the individuals with the chronic condition and how they perceive the work that must be done, across situations, either by themselves or through healthcare, eHealth, or other means.

2021 ISHNE/HRS/EHRA/APHRS collaborative statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

2021 ISHNE/ HRS/ EHRA/ APHRS collaborative statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/ Heart Rhythm Society/ European Heart Rhythm Association/ Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

2021 ISHNE / HRS / EHRA / APHRS Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology / Heart Rhythm Society / European Heart Rhythm Association / Asia Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology / Heart Rhythm Society / European Heart Rhythm Association / Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

Using Consumer-Grade Physical Activity Trackers to Measure Frailty Transitions in Older Critical Care Survivors: Exploratory Observational Study

Background

Critical illness has been suggested as a sentinel event for frailty development in at-risk older adults. Frail critical illness survivors are affected by increased adverse health outcomes, but monitoring the recovery after intensive care unit (ICU) discharge is challenging. Clinicians and funders of health care systems envision an increased role of wearable devices in monitoring clinically relevant measures, as sensor technology is advancing rapidly. The use of wearable devices has also generated great interest among older patients, and they are the fastest growing group of consumer-grade wearable device users. Recent research studies indicate that consumer-grade wearable devices offer the possibility of measuring frailty.

Objective

This study aims to examine the data collected from wearable devices for the progression of frailty among critical illness survivors.

Methods

An observational study was conducted with 12 older survivors of critical illness from Kingston General Hospital in Canada. Frailty was measured using the Clinical Frailty Scale (CFS) at ICU admission, hospital discharge, and 4-week follow-up. A wearable device was worn between hospital discharge and 4-week follow-up. The wearable device collected data on step count, physical activity, sleep, and heart rate (HR). Patient assessments were reviewed, including the severity of illness, cognition level, delirium, activities of daily living, and comorbidity.

Results

The CFS scores increased significantly following critical illness compared with the pre-ICU frailty level (P=.02; d=−0.53). Survivors who were frail over the 4-week follow-up period had significantly lower daily step counts than survivors who were not frail (P=.02; d=1.81). There was no difference in sleep and HR measures. Daily step count was strongly correlated with the CFS at 4-week follow-up (r=−0.72; P=.04). The average HR was strongly correlated with the CFS at hospital discharge (r=−0.72; P=.046). The HR SD was strongly correlated (r=0.78; P=.02) with the change in CFS from ICU admission to 4-week follow-up. No association was found between the CFS and sleep measures. The pattern of increasing step count over the 4-week follow-up period was correlated with worsening of frailty (r=.62; P=.03).

Conclusions

This study demonstrated an association between frailty and data generated from a consumer-grade wearable device. Daily step count and HR showed a strong association with the frailty progression of the survivors of critical illness over time. Understanding this association could unlock a new avenue for clinicians to monitor and identify a vulnerable subset of the older adult population that might benefit from an early intervention.

2021 ISHNE/HRS/EHRA/APHRS Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

2021 ISHNE/HRS/EHRA/APHRS Expert Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society describes the current status of mobile health technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mobile health. The promises of predictive analytics but also operational challenges in embedding mobile health into routine clinical care are explored.

Postcode based participatory disease surveillance systems : a comparison with traditional risk-based surveillance and its application in the COVID-19 pandemic

BACKGROUND

Background: The SARS-Cov-2 infection has rapidly saturated health systems and traditional surveillance networks are finding hard to keep pace with its spread. We designed a participatory disease surveillance (PDS) system, to capture symptoms of Influenza-like illness (ILI) to estimate SARS-CoV-2 infection in the community. While data generated by these platforms can help public health organisations find community hotspots and effectively direct control measures, it has never been compared to traditional systems.

OBJECTIVE

Methods and Objectives: A completely anonymised web based PDS system, www.trackcovid-19.org was developed. We evaluated the symptomatic responses received form the PDS system to the traditional risk based surveillance carried out by the Bruhat Bengaluru Mahanagara Palike over a period of 45 days in the South Indian city of Bengaluru.

METHODS

Methods and Objectives: A completely anonymised web based PDS system, www.trackcovid-19.org was developed. We evaluated the symptomatic responses received form the PDS system to the traditional risk based surveillance carried out by the Bruhat Bengaluru Mahanagara Palike over a period of 45 days in the South Indian city of Bengaluru.

RESULTS

Results: The PDS system recorded 11062 entries from 106 Postal codes. A healthy response was obtained from 10863 users while 199 (1.8%) reported symptomatic. Subgroup analysis of a 14 day symptomatic window recorded 33 (0.29%) responses. Risk based surveillance was carried out covering a population of 605,284 with 209 (0.03%) individuals identified symptomatic.

CONCLUSIONS

Conclusion: Web PDS platforms provide better visualisation of community infection when compared to traditional risk based surveillance systems. They are extremely useful by providing real time information in the extended battle against this pandemic. When integrated into national disease surveillance systems, they can provide long term community surveillance adding an important cost-effective layer to already available data sources.

Ethical Challenges With Smartwatch-Based Screening for Atrial Fibrillation: Putting Users at Risk for Marketing Purposes?

Background: Atrial fibrillation is the most common persistent arrhythmia. It is associated with increased mortality and morbidity such as stroke. The early detection of atrial fibrillation can significantly reduce the risk of stroke through preventive anticoagulation. Smartwatches offer the opportunity to screen for atrial fibrillation in the general population. This paper aims to analyze the ethical challenges associated with screening for atrial fibrillation using smartwatches. Methods: This is an ethical analysis. The methodology is based on the principle-orientated approach of Beauchamp and Childress. The principles of beneficence, non-maleficence, justice, and autonomy have to be guaranteed given the influence of private companies, privacy protection, liability and doctor-patient-relationship. The work is based on a systematic literature research. Results: There is currently no evidence that screening for atrial fibrillation with smartwatches improves the outcome and reduces the number of adverse events. The high number of false-positive results can lead to harm. The principle of non-maleficence is violated. The over-reliance on and the lack of adequate education by smartwatches can worsen the doctor-patient relationship. However, the relationship can also be improved by the proactive participation of the patient, which leads to greater autonomy, compliance and in the end beneficence. Since smartwatches are consumer goods, there is a risk for greater disparities in the poor and rich population. There is also a risk of discrimination against ethnic minorities due to underrepresentation in training data and study cohorts. The principle of justice is violated. The storage of sensitive medical data by private companies also raises many ethical and legal concerns. Conclusion: This analysis has shown that the use of smartwatches to detect atrial fibrillation is currently in an ethical perspective problematic. The lack of evidence and the high number of false-positive results can lead to harm. As smartwatches provide only little information about the possible consequences, informed consent cannot be assumed. Ethical implementation could be archived if doctors provide smartwatches to patients who have been shown to benefit from them. The implementation and education should be managed by the doctor.

Development of Social Support Networks by Patients With Depression Through Online Health Communities: Social Network Analysis

BACKGROUND

In recent years, people with mental health problems are increasingly using online social networks to receive social support. For example, in online depression communities, patients can share their experiences, exchange valuable information, and receive emotional support to help them cope with their disease. Therefore, it is critical to understand how patients with depression develop online social support networks to exchange informational and emotional support.

OBJECTIVE

Our aim in this study was to investigate which user attributes have significant effects on the formation of informational and emotional support networks in online depression communities and to further examine whether there is an association between the two social networks.

METHODS

We used social network theory and constructed exponential random graph models to help understand the informational and emotional support networks in online depression communities. A total of 74,986 original posts were retrieved from 1077 members in an online depression community in China from April 2003 to September 2017 and the available data were extracted. An informational support network of 1077 participant nodes and 6557 arcs and an emotional support network of 1077 participant nodes and 6430 arcs were constructed to examine the endogenous (purely structural) effects and exogenous (actor-relation) effects on each support network separately, as well as the cross-network effects between the two networks.

RESULTS

We found significant effects of two important structural features, reciprocity and transitivity, on the formation of both the informational support network (r=3.6247, P<.001, and r=1.6232, P<.001, respectively) and the emotional support network (r=4.4111, P<.001, and r=0.0177, P<.001, respectively). The results also showed significant effects of some individual factors on the formation of the two networks. No significant effects of homophily were found for gender (r=0.0783, P=.20, and r=0.1122, P=.25, respectively) in the informational or emotional support networks. There was no tendency for users who had great influence (r=0.3253, P=.05) or wrote more posts (r=0.3896, P=.07) or newcomers (r=-0.0452, P=.66) to form informational support ties more easily. However, users who spent more time online (r=0.6680, P<.001) or provided more replies to other posts (r=0.5026, P<.001) were more likely to form informational support ties. Users who had a big influence (r=0.8325, P<.001), spent more time online (r=0.5839, P<.001), wrote more posts (r=2.4025, P<.001), or provided more replies to other posts (r=0.2259, P<.001) were more likely to form emotional support ties, and newcomers (r=-0.4224, P<.001) were less likely than old-timers to receive emotional support. In addition, we found that there was a significant entrainment effect (r=0.7834, P<.001) and a nonsignificant exchange effect (r=-0.2757, P=.32) between the two networks.

CONCLUSIONS

This study makes several important theoretical contributions to the research on online depression communities and has important practical implications for the managers of online depression communities and the users involved in these communities.

Self-Quantification Systems to Support Physical Activity: From Theory to Implementation Principles

Since the emergence of the quantified self movement, users aim at health behavior change, but only those who are sufficiently motivated and competent with the tools will succeed. Our literature review shows that theoretical models for quantified self exist but they are too abstract to guide the design of effective user support systems. Here, we propose principles linking theory and implementation to arrive at a hierarchical model for an adaptable and personalized self-quantification system for physical activity support. We show that such a modeling approach should include a multi-factors user model (activity, context, personality, motivation), a hierarchy of multiple time scales (week, day, hour), and a multi-criteria decision analysis (user activity preference, user measured activity, external parameters). This theoretical groundwork, which should facilitate the design of more effective solutions, has now to be validated by further empirical research.

Auf dem Weg zum digitalen homo vitruvianus? Medizinisches Selftracking und digitale Gesundheitsanwendungen (DiGA) zwischen Empowerment und Kontrollverlust

Zunehmend gewinnen Health Apps an Bedeutung für eine präventive und eigenverantwortliche Ausrichtung des Gesundheitssystems. Die meisten dieser digitalen Gesundheitsanwendungen (DiGA) basieren derzeit auf sog. Selftracking-Technologien, mit deren Hilfe physiologische und psychische Daten sensorgestützt aufgezeichnet und diese zumeist um personalisierte Alltagsinformationen ergänzt werden. Die digitalen Entwicklungen dieser Art lösten in den letzten Jahren eine intensive und deutlich polarisierte Debatte über die Chancen und Gefahren von gesundheitlichem Selftracking aus. Ziel dieser Arbeit ist es, nach einem kurzen Überblick über das Feld des medizinischen Selftracking den polarisierten Diskurs zunächst anhand seiner entscheidenden individuellen und gesellschaftlichen Potenziale zu systematisieren und zu prüfen. Es stellt sich heraus, dass Selbstvermessungstechniken keineswegs ein neues Phänomen, sondern vielmehr seit langem fester Bestandteil medizinischen Wirkens in Diagnostik und Therapie sind. Als für die Implementierung von Health Apps in die medizinische Regelversorgung besonders bedeutend wird das Spannungsfeld zwischen individuellem Empowerment und potentiellem Kontrollverlust der Nutzenden herausgestellt. Abschließend werden mögliche Implikationen für die aktuelle Ausgestaltung des neuen Digitale-Versorgung-Gesetzes (DVG) aufgezeigt und auf einige bestehende „blinde Flecken“ hingewiesen.

New perspectives on person-centered care: an affordance-based account

Despite the growing interest and supporting evidence for person-centered care (PCC), there is still a fundamental disagreement about what makes healthcare person-centered. In this article, we define PCC as operating with three fundamental conditions: personal, participatory and holistic. To further understand these concepts, we develop a framework based on the theory of affordances, which we apply to the healthcare case of rehabilitation and a concrete experiment on social interactions between persons with cerebral palsy and physio- and occupational therapists. Based on the application of the theory, we argue that in order for healthcare to be considered as PCC, professionals need to adopt a personalistic attitude in their care, defined (at the how-level) in terms of mutual affordances: how the professional and the person of care acknowledges each other as a person in an interaction. In opposition, we define (at the what level) the functionalistic attitude in terms of object affordances, those related to a concrete goal. We show that PCC requires a balance of personalistic and functionalistic attitudes, since this contributes to a participatory and holistic conception of, and interaction with, the person of care.

Collecting, exploring and sharing personal data: Why, how and where

New, multi-channel personal data sources (like heart rate, sleep patterns, travel patterns, or social activities) are enabled by ever increased availability of miniaturised technologies embedded within smartphones and wearables. These data sources enable personal self-management of lifestyle choices (e.g., exercise, move to a bike-friendly area) and, on a large scale, scientific discoveries to improve health and quality of life. However, there are no simple and reliable ways for individuals to securely collect, explore and share these sources. Additionally, much data is also wasted, especially when the technology provider ceases to exist, leaving the users without any opportunity to retrieve own datasets from “dead” devices or systems. Our research reveals evidence of what we term human data bleeding and offers guidance on how to address current issues by reasoning upon five core aspects, namely technological, financial, legal, institutional and cultural factors. To this end, we present preliminary specifications of an open platform for personal data storage and quality of life research. The Open Health Archive (OHA) is a platform that would support individual, community and societal needs by facilitating collecting, exploring and sharing personal health and QoL data.

Augmenting the Clinical Data Sources for Enigmatic Diseases: A Cross-Sectional Study of Self-Tracking Data and Clinical Documentation in Endometriosis

BACKGROUND

Self-tracking through mobile health technology can augment the electronic health record (EHR) as an additional data source by providing direct patient input. This can be particularly useful in the context of enigmatic diseases and further promote patient engagement.

OBJECTIVES

This study aimed to investigate the additional information that can be gained through direct patient input on poorly understood diseases, beyond what is already documented in the EHR.

METHODS

This was an observational study including two samples with a clinically confirmed endometriosis diagnosis. We analyzed data from 6,925 women with endometriosis using a research app for tracking endometriosis to assess prevalence of self-reported pain problems, between- and within-person variability in pain over time, endometriosis-affected tasks of daily function, and self-management strategies. We analyzed data from 4,389 patients identified through a large metropolitan hospital EHR to compare pain problems with the self-tracking app and to identify unique data elements that can be contributed via patient self-tracking.

RESULTS

Pelvic pain was the most prevalent problem in the self-tracking sample (57.3%), followed by gastrointestinal-related (55.9%) and lower back (49.2%) pain. Unique problems that were captured by self-tracking included pain in ovaries (43.7%) and uterus (37.2%). Pain experience was highly variable both across and within participants over time. Within-person variation accounted for 58% of the total variance in pain scores, and was large in magnitude, based on the ratio of within- to between-person variability (0.92) and the intraclass correlation (0.42). Work was the most affected daily function task (49%), and there was significant within- and between-person variability in self-management effectiveness. Prevalence rates in the EHR were significantly lower, with abdominal pain being the most prevalent (36.5%).

CONCLUSION

For enigmatic diseases, patient self-tracking as an additional data source complementary to EHR can enable learning from the patient to more accurately and comprehensively evaluate patient health history and status.

Converting Visitors of Physicians' Personal Websites to Customers in Online Health Communities: Longitudinal Study

Background

With the dramatic development of Web 2.0, increasing numbers of patients and physicians are actively involved in online health communities. Despite extensive research on online health communities, the conversion rate from visitor to customer and its driving factors have not been discussed.

Objective

The aim of this study was to analyze the conversion rate of online health communities and to explore the effects of multisource online health community information, including physician-generated information, patient-generated information, and system-generated information.

Methods

An empirical study was conducted to examine the effects of physician-generated, patient-generated, and system-generated information on the conversion rate of physicians’ personal websites by analyzing short panel data from 2112 physicians over five time periods in a Chinese online health community.

Results

Multisource online health community information (ie, physician-generated, patient-generated, and system-generated information) positively affected the conversion rate. Physician-generated and patient-generated information showed a substitute relationship rather than a complementary relationship. In addition, the usage time of a personal website positively moderated patient-generated information, but negatively moderated physician-generated information.

Conclusions

This study contributes to the electronic health literature by investigating the conversion rate of online health communities and the effect of multisource online health community information. This study also contributes to understanding the drivers of conversion rate on service websites, which can help to successfully improve the efficiency of online health communities.

Experiences With Wearable Activity Data During Self-Care by Chronic Heart Patients: Qualitative Study

Background

Most commercial activity trackers are developed as consumer devices and not as clinical devices. The aim is to monitor and motivate sport activities, healthy living, and similar wellness purposes, and the devices are not designed to support care management in a clinical context. There are great expectations for using wearable sensor devices in health care settings, and the separate realms of wellness tracking and disease self-monitoring are increasingly becoming blurred. However, patients’ experiences with activity tracking technologies designed for use outside the clinical context have received little academic attention.

Objective

This study aimed to contribute to understanding how patients with a chronic disease experience activity data from consumer self-tracking devices related to self-care and their chronic illness. Our research question was: “How do patients with heart disease experience activity data in relation to self-care and chronic illness?”

Methods

We conducted a qualitative interview study with patients with chronic heart disease (n=27) who had an implanted cardioverter-defibrillator. Patients were invited to wear a FitBit Alta HR wearable activity tracker for 3-12 months and provide their perspectives on their experiences with step, sleep, and heart rate data. The average age was 57.2 years (25 men and 2 women), and patients used the tracker for 4-49 weeks (mean 26.1 weeks). Semistructured interviews (n=66) were conducted with patients 2–3 times and were analyzed iteratively in workshops using thematic analysis and abductive reasoning logic.

Results

Of the 27 patients, 18 related the heart rate, sleep, and step count data directly to their heart disease. Wearable activity trackers actualized patients’ experiences across 3 dimensions with a spectrum of contrasting experiences: (1) knowing, which spanned gaining insight and evoking doubts; (2) feeling, which spanned being reassured and becoming anxious; and (3) evaluating, which spanned promoting improvements and exposing failure.

Conclusions

Patients’ experiences could reside more on one end of the spectrum, could reside across all 3 dimensions, or could combine contrasting positions and even move across the spectrum over time. Activity data from wearable devices may be a resource for self-care; however, the data may simultaneously constrain and create uncertainty, fear, and anxiety. By showing how patients experience self-tracking data across dimensions of knowing, feeling, and evaluating, we point toward the richness and complexity of these data experiences in the context of chronic illness and self-care.