Personalized support for chronic conditions. A novel approach for enhancing self-management and improving lifestyle

Toward Shared Decision-Making in Degenerative Cervical Myelopathy: Protocol for a Mixed Methods Study

BACKGROUND

Health care decisions are a critical determinant in the evolution of chronic illness. In shared decision-making (SDM), patients and clinicians work collaboratively to reach evidence-based health decisions that align with individual circumstances, values, and preferences. This personalized approach to clinical care likely has substantial benefits in the oversight of degenerative cervical myelopathy (DCM), a type of nontraumatic spinal cord injury. Its chronicity, heterogeneous clinical presentation, complex management, and variable disease course engenders an imperative for a patient-centric approach that accounts for each patient's unique needs and priorities. Inadequate patient knowledge about the condition and an incomplete understanding of the critical decision points that arise during the course of care currently hinder the fruitful participation of health care providers and patients in SDM. This study protocol presents the rationale for deploying SDM for DCM and delineates the groundwork required to achieve this.

OBJECTIVE

The study's primary outcome is the development of a comprehensive checklist to be implemented upon diagnosis that provides patients with essential information necessary to support their informed decision-making. This is known as a core information set (CIS). The secondary outcome is the creation of a detailed process map that provides a diagrammatic representation of the global care workflows and cognitive processes involved in DCM care. Characterizing the critical decision points along a patient's journey will allow for an effective exploration of SDM tools for routine clinical practice to enhance patient-centered care and improve clinical outcomes.

METHODS

Both CISs and process maps are coproduced iteratively through a collaborative process involving the input and consensus of key stakeholders. This will be facilitated by Myelopathy.org, a global DCM charity, through its Research Objectives and Common Data Elements for Degenerative Cervical Myelopathy community. To develop the CIS, a 3-round, web-based Delphi process will be used, starting with a baseline list of information items derived from a recent scoping review of educational materials in DCM, patient interviews, and a qualitative survey of professionals. A priori criteria for achieving consensus are specified. The process map will be developed iteratively using semistructured interviews with patients and professionals and validated by key stakeholders.

RESULTS

Recruitment for the Delphi consensus study began in April 2023. The pilot-testing of process map interview participants started simultaneously, with the formulation of an initial baseline map underway.

CONCLUSIONS

This protocol marks the first attempt to provide a starting point for investigating SDM in DCM. The primary work centers on developing an educational tool for use in diagnosis to enable enhanced onward decision-making. The wider objective is to aid stakeholders in developing SDM tools by identifying critical decision junctures in DCM care. Through these approaches, we aim to provide an exhaustive launchpad for formulating SDM tools in the wider DCM community.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/46809.

Inertial sensors-based assessment to detect hallmarks of chronic ankle instability during single-leg standing: Is the healthy limb "healthy"?

BACKGROUND

Chronic ankle instability can be common in sportsmen and can increase the risk of damaging the articular surfaces and result in negative consequences to joint health. Balance assessment is often used to evaluate ankle instability characteristics and guide rehabilitation protocols. This study aims to investigate balance-related parameters in people with chronic ankle instability and healthy-matched controls, using inertial sensors.

METHODS

Ten young adults with a history of multiple ankle sprains (30 y, 25-34, 5 females) and ten matched healthy controls (30 y, 23-39, 5 females) were invited to participate in the study. Inertial sensors were placed on the head of the astragalus and on the chest to collect kinematic parameters during a 20-s single-leg stance performed on the leg with ankle instability (and corresponding for the healthy controls) and on the contralateral leg, randomly. Outcomes were calculated with MATLAB and subsequently analyzed.

FINDINGS

A significant group effect was found only for the inversion angle (F_1,15 = 12.514, p = 0.003, pη² = 0.455), consisting of individuals with ankle instability being characterized by higher inversion angles (4.999 degrees, 95% CI: 1.987-8.011, p = 0.003) without significant side differences. No significant side x group effects were found for the assessed parameters.

INTERPRETATION

Results from this study suggest that young adults with chronic ankle instability might be characterized by worse single-stance control in terms of inversion angle, and such worse performance could also be found in the contralateral leg. As such, inertial sensors could be used to assess kinematic parameters during balance tasks in people with chronic ankle instability.

Comprehensive telemedicine solution for remote monitoring of Parkinson's disease patients with orthostatic hypotension during COVID-19 pandemic

OBJECTIVE

Orthostatic hypotension (OH) represents a frequent but under-recognized phenomenon in Parkinson's disease (PD). During COVID-19 pandemic, Information and Communication Technologies (ICT) have become pivotal in the management of chronic diseases like PD, not only to assess motor impairment, but also for vital signs monitoring. This pilot study aimed to propose a real-time remote home-monitoring system and protocol for PD patients with OH.

METHODS

Vital parameters were acquired by wireless devices and transmitted to an ICT platform, providing data and smart notifications to the healthcare provider through an interactive web portal. Eight patients with idiopathic PD and OH underwent 5-day monitoring. Data about OH episodes, therapeutic interventions, impact on daily activities, and patient satisfaction were collected and analyzed.

RESULTS

The proposed solution allowed the identification of 65 OH episodes and subsequent medical interventions. Thirty-five episodes were asymptomatic, especially in the postprandial and in the afternoon recordings. Systolic-blood-pressure (SBP) and diastolic-blood-pressure (DBP) were significantly lower in symptomatic episodes, while the pressure drops resulted significantly higher in presence of symptoms. High usability and patient satisfaction scores were observed.

CONCLUSION

The proposed home-monitoring system and protocol have proved to provide useful information and to allow prompt interventions in the management of PD patients with OH during COVID-19 pandemic.

Personalized Approach for the Management of Exercise-Related Glycemic Imbalances in Type 1 Diabetes: Comparison with Reference Method

BACKGROUND

One of the most frequently adopted strategies to counterbalance the risk of exercise-induced hypoglycemia in patients with type 1 diabetes is carbohydrates supplement. Nevertheless, the estimation of its amount is still challenging. We investigated the efficacy of the personalized Exercise Carbohydrate Requirement Estimation System (ECRES) method compared to a tabular approach to estimate the glucose supplement needed for the prevention of exercise-related glycemic imbalances.

METHOD

Twenty-six patients performed two one-hour constant intensity exercises one week apart; the amount of extra carbohydrates was estimated, in random order, by the personalized ECRES method or through the tabular approach; glycemia was determined every 30 minutes. Continuous glucose monitoring (CGM) metrics were calculated over the 48 hours preceding, and the afternoon and night following the trials.

RESULTS

Applying the personalized ECRES method, a significantly lower amount of carbohydrates was administered to the active patients compared to the tabular approach, median (interquartile range): 9.0 (0.5-21.0) g vs 23.0 (21.0-25.0) g; P < .01; the two methods were similar for the sedentary patients, 18 (13.5-36.0) g vs 23.0 (21.0-27.0) g; P = NS. After overlapping CGM metrics before the exercises, both methods avoided hypoglycemia and resulted in similar glucose levels throughout them. The ECRES method led to CGM metrics within the guidelines for either the afternoon and the night just following the trials, whereas the tabular approach resulted in a significantly greater time below range in the afternoon (11.8% ± 18.2%; P < .05) and time above range during the night (39.3% ± 29.8%; P < .05).

CONCLUSIONS

The results support the validity of the personalized ECRES method: although the estimated amounts of carbohydrates were lower, patients' glycemia was maintained within safe clinical limits.

Mobile Health in Chronic Disease Management and Patient Empowerment: Exploratory Qualitative Investigation Into Patient-Physician Consultations

Background

Chronic diseases often present severe consequences for those affected. The management and treatment of chronic diseases largely depend on patients’ lifestyle choices and how they cope with the disease in their everyday lives. Accordingly, the ability of patients to self-manage diseases is a highly relevant topic. In relation to self-management, studies refer to patient empowerment as strengthening patients’ voices and enabling them to assert control over their health and treatment. Mobile health (mHealth) provides cost-efficient means to support self-management and foster empowerment.

Objective

There is a scarcity of research investigating how mHealth affects patient empowerment during patient-physician consultations. The objective of this study is to address this knowledge gap by investigating how mHealth affects consultations and patient empowerment.

Methods

We relied on data from an ethnographic field study of 6 children and adolescents diagnosed with juvenile idiopathic arthritis. We analyzed 6 patient-physician consultations and drew on Michel Foucault’s concepts of power and power technology.

Results

Our results suggest that the use of mHealth constitutes practices that structure the consultations around deviations and noncompliant patient behavior. Our analysis shows how mHealth is used to discipline patients and correct their behavior. We argue that the use of mHealth during consultations may unintentionally lead to relevant aspects of patients’ lives related to the disease being ignored; thus, inadvertently, patients’ voices may be silenced.

Conclusions

Our results show that concrete uses of mHealth may conflict with extant literature on empowerment, which emphasizes the importance of strengthening the patients’ voices and enabling patients to take more control of their health and treatment. We contribute to the state-of-the-art knowledge by showing that the use of mHealth may have unintended consequences that do not lead to empowerment. Our analysis underscores the need for further research to investigate how mHealth impacts patient empowerment during consultations.

e-Health solution for home patient telemonitoring in early post-acute TIA/Minor stroke during COVID-19 pandemic

Background

When it comes to critical early post-acute TIA/stroke phase, there is a lack of a comprehensive multi-parametric telemonitoring system. The COVID-19 emergency, its related global mobility restrictions and fear of hospitalization further highlighted the need of a comprehensive solution.

Objective

We aimed to design and test a pragmatic e-Health system based on multiparametric telemonitoring to support of TIA/stroke patients in sub-acute phase during the COVID-19 pandemic.

Methods

We proposed a telemonitoring system and protocol for TIA/minor stroke patients during COVID-19 pandemic for patients at risk of stroke recurrence. This system involves the use of portable devices for BP/HR/SpO₂/temperature sensing, panic-button, gateway, and a dedicated ICT platform. The protocol is a 14-day multiparametric telemonitoring, therapy, and emergency intervention based on vital sign alteration notifications. We conducted a proof-of-concept validation test on 8 TIA/minor stroke patients in the early post-acute phase (< 14 days from ischemic event).

Results

The proposed solution allowed to promptly and remotely identify vital sign alterations at home during the early post-acute phase, allowing therapy and behavioral intervention adjustments. Also, we observed a significant improvement of quality of life, as well as a significant reduction of anxiety and depression status. TUQ showed ease of use, good interface quality and high user satisfaction of the proposed solution. The 3-month follow-up showed total adherence of prescribed therapy and no stroke/TIA recurrence or other emergency department admissions.

Conclusion

The proposed e-Health solution and telemonitoring protocol may be highly useful for early post-acute remote patient management, thus supporting constant monitoring and patient adherence to the treatment pathway, especially during the COVID-19 emergency.

Carbohydrate Requirement for Exercise in Type 1 Diabetes: Effects of Insulin Concentration

Physical activity is a keystone of a healthy lifestyle as well as of management of patients with type 1 diabetes. The risk of exercise-induced hypoglycemia, however, is a great challenge for these patients. The glycemic response to exercise depends upon several factors concerning the patient him/herself (eg, therapy, glycemic control, training level) and the characteristics of the exercise performed. Only in-depth knowledge of these factors will allow to develop individualized strategies minimizing the risk of hypoglycemia. The main factors affecting the exercise-induced hypoglycemia in patients with T1D have been analyzed, including the effects of insulin concentration. A model is discussed, which has the potential to become the basis for providing patients with individualized suggestions to keep constant glucose levels on each exercise occasion.

Smart technology for physical activity and health assessment during COVID-19 lockdown

BACKGROUND

The worldwide lockdown in response to COVID-19 pandemics has often led to physical inactivity and social distancing. When combined, these factors may affect quality and life and increase the risk of different diseases. Therefore, assessment of physical activity levels should be encouraged to monitor and identify those at a higher risk of inactivity. Smart technology is a promising tool to assess physical activity and health and may be particularly useful during a period of general lockdown.

METHODS

An online survey was developed and shared among the Italian general population to collect data about physical activity and daily routine changes between January 2020 and the lockdown period from March 23 to March 29. Participants were asked to provide data such as daily step count (Steps) or heart rate (HR) measured and collected by their smart technology devices.

RESULTS

Four hundred participants were included in the final analysis. During the lockdown, the number of steps dropped from 8284±4390 to 3294±3994 steps (P<0.001), while mean peak HR decreased from 61.3±18.2% to 55.9±17.3% (P<0.001).

CONCLUSIONS

These findings provide objective data about the effects of the COVID-19 lockdown on physical activity, thus encouraging the use of smart devices to monitor and promote healthy lifestyles while faced with a confinement condition.

Adapting the stage-based model of personal informatics for low-resource communities in the context of type 2 diabetes

Growing availability of self-monitoring technologies creates new opportunities for collection of personal health data and their use in personalized health informatics interventions. However, much of the previous empirical research and existing theories of individuals' engagement with personal data focused on early adopters and data enthusiasts. Less is understood regarding ways individuals from medically underserved low-income communities who live with chronic diseases engage with self-monitoring in health. In this research, we adapted a widely used theoretical framework, the stage-based model of personal informatics, to the unique attitudes, needs, and constraints of low-income communities. We conducted a qualitative study of attitudes and perceptions regarding tracking and planning in health and other contexts (e.g., finances) among low-income adults living with type 2 diabetes. This study showed distinct differences in participants' attitudes and behaviors around tracking and planning, as well as wide variability in their sense of being in charge of different areas of one's life. Ultimately, we found a strong connection between these two: perceptions of being in charge seems to be strongly connected to an individual's proactive or reactive tracking and planning in that area. Whereas individuals with a greater sense of being in charge of their health were more proactive, meaning they were likely to engage with all the stages of personal informatics model on their own, those with less of a sense of being in charge were more likely to be reactive-relying on their healthcare providers for several critical stages of self-monitoring (deciding what data to collect, integrating data from multiple sources, reflecting over patterns in collected data, and arriving at conclusions and implications for action). Perhaps as a result, these individuals were less likely to experience increases in self-awareness and self-knowledge, common motivating factors to engaging in self-monitoring in the future. We argue that adapting this framework in a way that highlights gaps in individuals' engagement has a number of important implications for future research in biomedical informatics and for the design of new interventions that promote engagement with self-monitoring, and that are robust in light of fragmented engagement.

Mapping Patient Data to Colorectal Cancer Clinical Algorithms for Personalized Guideline-Based Treatment

BACKGROUND

Colorectal cancer is the most commonly occurring cancer in Germany, and the second and third most commonly diagnosed cancer in women and men, respectively. In this context, evidence-based guidelines positively impact the quality of treatment processes for cancer patients. However, evidence of their impact on real-world patient care remains unclear. To ensure the success of clinical guidelines, a fast and clear provision of knowledge at the point of care is essential.

OBJECTIVES

The objectives of this study are to model machine-readable clinical algorithms for colon carcinoma and rectal carcinoma annotated by Unified Medical Language System (UMLS) based on clinical guidelines and the development of an open-source workflow system for mapping clinical algorithms with patient-specific information to identify patient's position on the treatment algorithm for guideline-based therapy recommendations.

METHODS

This study qualitatively assesses the therapy decision of clinical algorithms as part of a clinical pathway. The solution uses rule-based clinical algorithms, which were developed based on the corresponding guidelines. These algorithms are executed on a newly developed open-source workflow system and are visualized at the point of care. The aim of this approach is to create clinical algorithms based on an established business process standard, the Business Process Model and Notation (BPMN), which is annotated by UMLS terminologies. The gold standard for the validation process was set by manual extraction of clinical datasets from 86 rectal cancer patients and 89 colon cancer patients.

RESULTS

Using this approach, the algorithm achieved a precision value of 87.64% for colon cancer and 84.70% for rectal cancer with recall values of 87.64 and 83.72%, respectively.

CONCLUSION

The results indicate that the automatic positioning of a patient on the decision pathway is possible with tumor stages that have a less complex clinical algorithm with fewer decision points reaching a higher accuracy than complex stages.

A Sociotechnical Systems Approach Toward Tailored Design for Personal Health Information Management

We used a sociotechnical systems approach-which conceptualizes a system of interacting people, technologies, and tasks, to identify individual differences in personal health information management (PHIM) that can inform the design for patient-friendly environments, tools and technologies. We conducted a secondary thematic analysis of data collected as part of a parent project, vizHOME. The goal of vizHOME was to improve health and health outcomes through identifying key features in the environment that will inform the design of consumer health information technology HIT. We analyzed interview data collected from 20 individuals with diabetes. We found seven dimensions of PHIM: (1) level of privacy preferred for PHIM; (2) amount of engagement in PHIM; (3) extent of guidance preferred for PHIM; (4) level of documentation preferred for PHIM; (5) degree of physical distribution of PHIM; (6) amount of flexibility in PHIM routine; and (7) use of external cues to manage PHIM. Our results suggest that each dimension exists as a continuum, which are anchored from low to high. Exploring the interaction between PHIM and the sociotechnical system in which PHIM is performed revealed key dimensions of PHIM as well as individual differences in those PHIM dimensions. Identification of individual differences in PHIM can support the creation of human-centered design considerations for tailored environments, products, processes, and technologies that support PHIM. Future research will seek to validate PHIM dimensions in a larger population and develop a PHIM-typing measure to identify PHIM types toward tailoring processes, products, and to individual needs in context.

Design for mobile mental health: Exploring the informed participation approach

Mobile applications (apps) have the potential to improve mental health services. However, there is limited evidence of efficacy or responsiveness to user needs for existing apps. A lack of design methods has contributed to this issue. Developers view mental health apps as stand-alone products and dismiss the complex context of use. Participatory design, particularly an informed participation approach, has potential to improve the design of mental health apps. In this study, we worked with young mobile users and mental health practitioners to examine the informed participation approach for designing apps. Using auto-ethnography and a set of design workshops, the project focused on eliciting design requirements as a factor for successful implementation. We compared resultant ideas and designs with existing apps. Many user requirements revealed were absent in existing apps, suggesting potential advantages to informed participation. The observation of the process, however, showed challenges in engagement that need to be overcome.

Factors Influencing Sustained Engagement with ECG Self-Monitoring: Perspectives from Patients and Health Care Providers

BACKGROUND

Patient-generated health data (PGHD) collected digitally with mobile health (mHealth) technology has garnered recent excitement for its potential to improve precision management of chronic conditions such as atrial fibrillation (AF), a common cardiac arrhythmia. However, sustained engagement is a major barrier to collection of PGHD. Little is known about barriers to sustained engagement or strategies to intervene upon engagement through application design.

OBJECTIVE

This article investigates individual patient differences in sustained engagement among individuals with a history of AF who are self-monitoring using mHealth technology.

METHODS

This qualitative study involved patients, health care providers, and research coordinators previously involved in a randomized, controlled trial involving electrocardiogram (ECG) self-monitoring of AF. Patients were adults with a history of AF randomized to the intervention arm of this trial who self-monitored using ECG mHealth technology for 6 months. Semistructured interviews and focus groups were conducted separately with health care providers and research coordinators, engaged patients, and unengaged patients. A validated model of sustained engagement, an adapted unified theory of acceptance and use of technology (UTAUT), guided data collection, and analysis through directed content analysis.

RESULTS

We interviewed 13 patients (7 engaged, 6 unengaged), 6 providers, and 2 research coordinators. In addition to finding differences between engaged and unengaged patients within each predictor in the adapted UTAUT model (perceived ease of use, perceived usefulness, facilitating conditions), four additional factors were identified as being related to sustained engagement in this population. These are: (1) internal motivation to manage health, (2) relationship with health care provider, (3) supportive environments, and (4) feedback and guidance.

CONCLUSION

Although it required some modification, the adapted UTAUT model was useful in understanding of the parameters of sustained engagement. The findings of this study provide initial requirement specifications for the design of applications that engage patients in this unique population of adults with AF.