A mobile health monitoring-and-treatment system based on integration of the SSN sensor ontology and the HL7 FHIR standard

HL7 Fast Healthcare Interoperability Resources (HL7 FHIR) in digital healthcare ecosystems for chronic disease management: Scoping review

BACKGROUND

The prevalence of chronic diseases has shifted the burden of disease from incidental acute inpatient admissions to long-term coordinated care across healthcare institutions and the patient's home. Digital healthcare ecosystems emerge to target increasing healthcare costs and invest in standard Application Programming Interfaces (API), such as HL7 Fast Healthcare Interoperability Resources (HL7 FHIR) for trusted data flows.

OBJECTIVES

This scoping review assessed the role and impact of HL7 FHIR and associated Implementation Guides (IGs) in digital healthcare ecosystems focusing on chronic disease management.

METHODS

To study trends and developments relevant to HL7 FHIR, a scoping review of the scientific and gray English literature from 2017 to 2023 was used.

RESULTS

The selection of 93 of 524 scientific papers reviewed in English indicates that the popularity of HL7 FHIR as a robust technical interface standard for the health sector has been steadily rising since its inception in 2010, reaching a peak in 2021. Digital Health applications use HL7 FHIR in cancer (45 %), cardiovascular disease (CVD) (more than 15 %), and diabetes (almost 15 %). The scoping review revealed that references to HL7 FHIR IGs are limited to ∼ 20 % of articles reviewed. HL7 FHIR R4 was most frequently referenced when the HL7 FHIR version was mentioned. In HL7 FHIR IGs registries and the internet, we found 35 HL7 FHIR IGs addressing chronic disease management, i.e., cancer (40 %), chronic disease management (25 %), and diabetes (20 %). HL7 FHIR IGs frequently complement the information in the article.

CONCLUSIONS

HL7 FHIR matures with each revision of the standard as HL7 FHIR IGs are developed with validated data sets, common shared HL7 FHIR resources, and supporting tools. Referencing HL7 FHIR IGs cataloged in official registries and in scientific publications is recommended to advance data quality and facilitate mutual learning in growing digital healthcare ecosystems that nurture interoperability in digital health innovation.

Ontology-based decision support systems for diabetes nutrition therapy: A systematic literature review

Diabetes is a non-communicable disease that has reached epidemic proportions, affecting 537 million people globally. Artificial Intelligence can support patients or clinicians in diabetes nutrition therapy - the first medical therapy in most cases of Type 1 and Type 2 diabetes. In particular, ontology-based recommender and decision support systems can deliver a computable representation of experts' knowledge, thus delivering patient-tailored nutritional recommendations or supporting clinical personnel in identifying the most suitable diet. This work proposes a systematic literature review of the domain ontologies describing diabetes in such systems, identifying their underlying conceptualizations, the users targeted by the systems, the type(s) of diabetes tackled, and the nutritional recommendations provided. This review also delves into the structure of the domain ontologies, highlighting several aspects that may hinder (or foster) their adoption in recommender and decision support systems for diabetes nutrition therapy. The results of this review process allow to underline how recommendations are formulated and the role of clinical experts in developing domain ontologies, outlining the research trends characterizing this research area. The results also allow for identifying research directions that can foster a preeminent role for clinical experts and clinical guidelines in a cooperative effort to make ontologies more interoperable - thus enabling them to play a significant role in the decision-making processes about diabetes nutrition therapy.

Semantic Interoperability of Electronic Health Records: Systematic Review of Alternative Approaches for Enhancing Patient Information Availability

Background

Semantic interoperability facilitates the exchange of and access to health data that are being documented in electronic health records (EHRs) with various semantic features. The main goals of semantic interoperability development entail patient data availability and use in diverse EHRs without a loss of meaning. Internationally, current initiatives aim to enhance semantic development of EHR data and, consequently, the availability of patient data. Interoperability between health information systems is among the core goals of the European Health Data Space regulation proposal and the World Health Organization's Global Strategy on Digital Health 2020-2025.

Objective

To achieve integrated health data ecosystems, stakeholders need to overcome challenges of implementing semantic interoperability elements. To research the available scientific evidence on semantic interoperability development, we defined the following research questions: What are the key elements of and approaches for building semantic interoperability integrated in EHRs? What kinds of goals are driving the development? and What kinds of clinical benefits are perceived following this development?

Methods

Our research questions focused on key aspects and approaches for semantic interoperability and on possible clinical and semantic benefits of these choices in the context of EHRs. Therefore, we performed a systematic literature review in PubMed by defining our study framework based on previous research.

Results

Our analysis consisted of 14 studies where data models, ontologies, terminologies, classifications, and standards were applied for building interoperability. All articles reported clinical benefits of the selected approach to enhancing semantic interoperability. We identified 3 main categories: increasing the availability of data for clinicians (n=6, 43%), increasing the quality of care (n=4, 29%), and enhancing clinical data use and reuse for varied purposes (n=4, 29%). Regarding semantic development goals, data harmonization and developing semantic interoperability between different EHRs was the largest category (n=8, 57%). Enhancing health data quality through standardization (n=5, 36%) and developing EHR-integrated tools based on interoperable data (n=1, 7%) were the other identified categories. The results were closely coupled with the need to build usable and computable data out of heterogeneous medical information that is accessible through various EHRs and databases (eg, registers).

Conclusions

When heading toward semantic harmonization of clinical data, more experiences and analyses are needed to assess how applicable the chosen solutions are for semantic interoperability of health care data. Instead of promoting a single approach, semantic interoperability should be assessed through several levels of semantic requirements A dual model or multimodel approach is possibly usable to address different semantic interoperability issues during development. The objectives of semantic interoperability are to be achieved in diffuse and disconnected clinical care environments. Therefore, approaches for enhancing clinical data availability should be well prepared, thought out, and justified to meet economically sustainable and long-term outcomes.

Regulatory Standards and Guidance for the Use of Health Apps for Self-Management in Sub-Saharan Africa: Scoping Review

BACKGROUND

Health apps are increasingly recognized as crucial tools for enhancing health care delivery. Many countries, particularly those in sub-Saharan Africa, can substantially benefit from using health apps to support self-management and thus help to achieve universal health coverage and the third sustainable development goal. However, most health apps published in app stores are of unknown or poor quality, which poses a risk to patient safety. Regulatory standards and guidance can help address this risk and promote patient safety.

OBJECTIVE

This review aims to assess the regulatory standards and guidance for health apps supporting evidence-based best practices in sub-Saharan Africa with a focus on self-management.

METHODS

A methodological framework for scoping reviews was applied. A search strategy was built and applied across the following databases, gray literature sources, and institutional websites: PubMed, Scopus, World Health Organization (WHO) African Index Medicus, OpenGrey, WHO Regional Office for Africa Library, ICTworks, WHO Directory of eHealth policies, HIS Strengthening Resource Center, International Telecommunication Union, Ministry of Health websites, and Google. The search covered the period between January 2005 and January 2024. The findings were analyzed using a deductive descriptive content analysis. The policy analysis framework was adapted and used to organize the findings. The Reporting Items for Stakeholder Analysis tool guided the identification and mapping of key stakeholders based on their roles in regulating health apps for self-management.

RESULTS

The study included 49 documents from 31 sub-Saharan African countries. While all the documents were relevant for stakeholder identification and mapping, only 3 regulatory standards and guidance contained relevant information on regulation of health apps. These standards and guidance primarily aimed to build mutual trust; promote integration, inclusion, and equitable access to services; and address implementation issues and poor coordination. They provided guidance on systems quality, software acquisition and maintenance, security measures, data exchange, interoperability and integration, involvement of relevant stakeholders, and equitable access to services. To enhance implementation, the standards highlight that legal authority, coordination of activities, building capacity, and monitoring and evaluation are required. A number of stakeholders, including governments, regulatory bodies, funders, intergovernmental and nongovernmental organizations, academia, and the health care community, were identified to play key roles in regulating health apps.

CONCLUSIONS

Health apps have huge potential to support self-management in sub-Saharan Africa, but the lack of regulatory standards and guidance constitutes a major barrier. Hence, for these apps to be safely and effectively integrated into health care, more attention should be given to regulation. Learning from countries with effective regulations can help sub-Saharan Africa build a more robust and responsive regulatory system, ensuring the safe and beneficial use of health apps across the region.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2018-025714.

Electronic Health Record and Semantic Issues Using Fast Healthcare Interoperability Resources: Systematic Mapping Review

BACKGROUND

The increasing use of electronic health records and the Internet of Things has led to interoperability issues at different levels (structural and semantic). Standards are important not only for successfully exchanging data but also for appropriately interpreting them (semantic interoperability). Thus, to facilitate the semantic interoperability of data exchanged in health care, considerable resources have been deployed to improve the quality of shared clinical data by structuring and mapping them to the Fast Healthcare Interoperability Resources (FHIR) standard.

OBJECTIVE

The aims of this study are 2-fold: to inventory the studies on FHIR semantic interoperability resources and terminologies and to identify and classify the approaches and contributions proposed in these studies.

METHODS

A systematic mapping review (SMR) was conducted using 10 electronic databases as sources of information for inventory and review studies published during 2012 to 2022 on the development and improvement of semantic interoperability using the FHIR standard.

RESULTS

A total of 70 FHIR studies were selected and analyzed to identify FHIR resource types and terminologies from a semantic perspective. The proposed semantic approaches were classified into 6 categories, namely mapping (31/126, 24.6%), terminology services (18/126, 14.3%), resource description framework or web ontology language-based proposals (24/126, 19%), annotation proposals (18/126, 14.3%), machine learning (ML) and natural language processing (NLP) proposals (20/126, 15.9%), and ontology-based proposals (15/126, 11.9%). From 2012 to 2022, there has been continued research in 6 categories of approaches as well as in new and emerging annotations and ML and NLP proposals. This SMR also classifies the contributions of the selected studies into 5 categories: framework or architecture proposals, model proposals, technique proposals, comparison services, and tool proposals. The most frequent type of contribution is the proposal of a framework or architecture to enable semantic interoperability.

CONCLUSIONS

This SMR provides a classification of the different solutions proposed to address semantic interoperability using FHIR at different levels: collecting, extracting and annotating data, modeling electronic health record data from legacy systems, and applying transformation and mapping to FHIR models and terminologies. The use of ML and NLP for unstructured data is promising and has been applied to specific use case scenarios. In addition, terminology services are needed to accelerate their use and adoption; furthermore, techniques and tools to automate annotation and ontology comparison should help reduce human interaction.

Evaluating the Feasibility and Acceptance of a Mobile Clinical Decision Support System in a Resource-Limited Country: Exploratory Study

BACKGROUND

In resource-limited countries, access to specialized health care services such as dermatology is limited. Clinical decision support systems (CDSSs) offer innovative solutions to address this challenge. However, the implementation of CDSSs is commonly associated with unique challenges. VisualDx-an exemplar CDSS-was recently implemented in Botswana to provide reference materials in support of the diagnosis and management of dermatological conditions. To inform the sustainable implementation of VisualDx in Botswana, it is important to evaluate the intended users' perceptions about the technology.

OBJECTIVE

This study aims to determine health care workers' acceptance of VisualDx to gauge the feasibility of future adoption in Botswana and other similar health care systems.

METHODS

The study's design was informed by constructs of the Technology Acceptance Model. An explanatory, sequential, mixed methods study involving surveys and semistructured interviews was conducted. The REDCap (Research Electronic Data Capture; Vanderbilt University) platform supported web-based data capture from March 2021 through August 2021. In total, 28 health care workers participated in the study. Descriptive statistics were generated and analyzed using Excel (Microsoft Corp), and thematic analysis of interview transcripts was performed using Delve software.

RESULTS

All survey respondents (N=28) expressed interest in using mobile health technology to support their work. Before VisualDx, participants referenced textbooks, journal articles, and Google search engines. Overall, participants' survey responses showed their confidence in VisualDx (18/19, 95%); however, some barriers were noted. Frequently used VisualDx features included generating a differential diagnosis through manual entry of patient symptoms (330/681, 48.5% of total uses) or using the artificial intelligence feature to analyze skin conditions (150/681, 22% of total uses). Overall, 61% (17/28) of the survey respondents were also interviewed, and 4 thematic areas were derived.

CONCLUSIONS

Participants' responses indicated their willingness to accept VisualDx. The ability to access information quickly without internet connection is crucial in resource-constrained environments. Selected enhancements to VisualDx may further increase its feasibility in Botswana. Study findings can serve as the basis for improving future CDSS studies and innovations in Botswana and similar resource-limited countries.

Machine Learning-Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review

Background

Machine learning-enabled clinical information systems (ML-CISs) have the potential to drive health care delivery and research. The Fast Healthcare Interoperability Resources (FHIR) data standard has been increasingly applied in developing these systems. However, methods for applying FHIR to ML-CISs are variable.

Objective

This study evaluates and compares the functionalities, strengths, and weaknesses of existing systems and proposes guidelines for optimizing future work with ML-CISs.

Methods

Embase, PubMed, and Web of Science were searched for articles describing machine learning systems that were used for clinical data analytics or decision support in compliance with FHIR standards. Information regarding each system's functionality, data sources, formats, security, performance, resource requirements, scalability, strengths, and limitations was compared across systems.

Results

A total of 39 articles describing FHIR-based ML-CISs were divided into the following three categories according to their primary focus: clinical decision support systems (n=18), data management and analytic platforms (n=10), or auxiliary modules and application programming interfaces (n=11). Model strengths included novel use of cloud systems, Bayesian networks, visualization strategies, and techniques for translating unstructured or free-text data to FHIR frameworks. Many intelligent systems lacked electronic health record interoperability and externally validated evidence of clinical efficacy.

Conclusions

Shortcomings in current ML-CISs can be addressed by incorporating modular and interoperable data management, analytic platforms, secure interinstitutional data exchange, and application programming interfaces with adequate scalability to support both real-time and prospective clinical applications that use electronic health record platforms with diverse implementations.

Content and quality of physical activity ontologies: a systematic review

INTRODUCTION

Ontologies are a formal way to represent knowledge in a particular field and have the potential to transform the field of health promotion and digital interventions. However, few researchers in physical activity (PA) are familiar with ontologies, and the field can be difficult to navigate. This systematic review aims to (1) identify ontologies in the field of PA, (2) assess their content and (3) assess their quality.

METHODS

Databases were searched for ontologies on PA. Ontologies were included if they described PA or sedentary behavior, and were available in English language. We coded whether ontologies covered the user profile, activity, or context domain. For the assessment of quality, we used 12 criteria informed by the Open Biological and Biomedical Ontology (OBO) Foundry principles of good ontology practice.

RESULTS

Twenty-eight ontologies met the inclusion criteria. All ontologies covered PA, and 19 included information on the user profile. Context was covered by 17 ontologies (physical context, n = 12; temporal context, n = 14; social context: n = 5). Ontologies met an average of 4.3 out of 12 quality criteria. No ontology met all quality criteria.

DISCUSSION

This review did not identify a single comprehensive ontology of PA that allowed reuse. Nonetheless, several ontologies may serve as a good starting point for the promotion of PA. We provide several recommendations about the identification, evaluation, and adaptation of ontologies for their further development and use.

Assessment of Stakeholder Perceptions and Attitudes Toward Health Data Governance Principles in Botswana: Web-Based Survey

BACKGROUND

The use of information and communication technologies for health-eHealth-is described as having potential to improve the quality of health care service delivery. Consequently, there is an increased global trend toward adoption of eHealth interventions by health care systems worldwide. Despite the proliferation of eHealth solutions, many health care institutions especially in transitioning countries are struggling to attain effective data governance approaches. The Ministry of Health in Botswana is an exemplar institution continually seeking better approaches to strengthen health data governance (HDG) approaches following the adoption of eHealth solutions. Recognizing the need for a global HDG framework, the Transform Health coalition conceptualized HDG principles that are structured around 3 interconnected objectives: protecting people, promoting the value of health, and prioritizing equity.

OBJECTIVE

The aim of the study is to solicit and evaluate perceptions and attitudes of health sector workers in Botswana toward the HDG principles by Transform Health and derive any future guidance.

METHODS

Purposive sampling was used to select participants. A total of 23 participants from various health care organizations in Botswana completed a web-based survey and 10 participated in a follow-up remote round-table discussion. The aim of the round-table discussion was to gain further insight into participants' responses from the web-based survey. Participants were from the following health care cadres: nurses, doctors, information technology professionals, and health informaticians. Both validity and reliability testing were performed for the survey tool before sharing it with study participants. An analysis of participants' close-ended responses from the survey was performed using descriptive statistics. Thematic analysis of open-ended responses from the questionnaire and the round-table discussion was achieved using the Delve software and the widely accepted principles of thematic analysis.

RESULTS

Although some participants highlighted having measures in place similar to the HDG principles, there were some who either did not know or disagreed that their organizations already had in place mechanisms similar to the proposed HDG principles. Participants further expressed relevance and importance of the HDG principles in the context of Botswana. However, some modifications to the principles were also suggested.

CONCLUSIONS

This study highlights the necessity of data governance in health care particularly toward meeting the requirements for Universal Health Coverage. The existence of other health data governance frameworks calls for a critical analysis to assess the most appropriate and applicable framework in the context of Botswana and similar transitioning countries. An organization-centered approach may be most appropriate, as well as strengthening of existing organizations' HDG practices with the Transform Health principles.

An Ostensive Information Architecture to Enhance Semantic Interoperability for Healthcare Information Systems

Semantic interoperability establishes intercommunications and enables data sharing across disparate systems. In this study, we propose an ostensive information architecture for healthcare information systems to decrease ambiguity caused by using signs in different contexts for different purposes. The ostensive information architecture adopts a consensus-based approach initiated from the perspective of information systems re-design and can be applied to other domains where information exchange is required between heterogeneous systems. Driven by the issues in FHIR (Fast Health Interoperability Resources) implementation, an ostensive approach that supplements the current lexical approach in semantic exchange is proposed. A Semantic Engine with an FHIR knowledge graph as the core is constructed using Neo4j to provide semantic interpretation and examples. The MIMIC III (Medical Information Mart for Intensive Care) datasets and diabetes datasets have been employed to demonstrate the effectiveness of the proposed information architecture. We further discuss the benefits of the separation of semantic interpretation and data storage from the perspective of information system design, and the semantic reasoning towards patient-centric care underpinned by the Semantic Engine.

Ontologies Applied in Clinical Decision Support System Rules: Systematic Review

BACKGROUND

Clinical decision support systems (CDSSs) are important for the quality and safety of health care delivery. Although CDSS rules guide CDSS behavior, they are not routinely shared and reused.

OBJECTIVE

Ontologies have the potential to promote the reuse of CDSS rules. Therefore, we systematically screened the literature to elaborate on the current status of ontologies applied in CDSS rules, such as rule management, which uses captured CDSS rule usage data and user feedback data to tailor CDSS services to be more accurate, and maintenance, which updates CDSS rules. Through this systematic literature review, we aim to identify the frontiers of ontologies used in CDSS rules.

METHODS

The literature search was focused on the intersection of ontologies; clinical decision support; and rules in PubMed, the Association for Computing Machinery (ACM) Digital Library, and the Nursing & Allied Health Database. Grounded theory and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines were followed. One author initiated the screening and literature review, while 2 authors validated the processes and results independently. The inclusion and exclusion criteria were developed and refined iteratively.

RESULTS

CDSSs were primarily used to manage chronic conditions, alerts for medication prescriptions, reminders for immunizations and preventive services, diagnoses, and treatment recommendations among 81 included publications. The CDSS rules were presented in Semantic Web Rule Language, Jess, or Jena formats. Despite the fact that ontologies have been used to provide medical knowledge, CDSS rules, and terminologies, they have not been used in CDSS rule management or to facilitate the reuse of CDSS rules.

CONCLUSIONS

Ontologies have been used to organize and represent medical knowledge, controlled vocabularies, and the content of CDSS rules. So far, there has been little reuse of CDSS rules. More work is needed to improve the reusability and interoperability of CDSS rules. This review identified and described the ontologies that, despite their limitations, enable Semantic Web technologies and their applications in CDSS rules.

Customer-centric product presentations for monoclonal antibodies

Delivering customer-centric product presentations for biotherapeutics, such as monoclonal antibodies (mAbs), represents a long-standing and paramount area of engagement for pharmaceutical scientists. Activities include improving experience with the dosing procedure, reducing drug administration-related expenditures, and ultimately shifting parenteral treatments outside of a controlled healthcare institutional setting. In times of increasingly cost-constrained markets and reinforced with the coronavirus pandemic, this discipline of "Product Optimization" in healthcare has gained momentum and changed from a nice-to-have into a must. This review summarizes latest trends in the healthcare ecosystem that inform key strategies for developing customer-centric products, including the availability of a wider array of sustainable drug delivery options and treatment management plans that support dosing in a flexible care setting. Three disease area archetypes with varying degree of implementation of customer-centric concepts are introduced to highlight relevant market differences and similarities. Namely, rheumatoid arthritis and inflammatory bowel disease, multiple sclerosis, and oncology have been chosen due to differences in the availability of subcutaneously dosed and ready-to-use self-administration products for mAb medicines and their follow-on biologics. Different launch scenarios are described from a manufacturer's perspective highlighting the necessity of platform approaches. To unfold the full potential of customer-centric care, value-based healthcare provider reimbursement schemes that incentivize the efficiency of care need to be broadly implemented.

[Ontologies Applied in Clinical Decision Support Systems for Diabetes]

A clinical decision support system (CDSS) integrated with electronic health records helps physicians at the grassroots make patient-appropriate and evidence-based treatment decisions and improves the efficiency of diagnosis and treatment. Furthermore, using ontologies to build up the medical knowledge base and patient data for CDSS enhances the automation and transparency of the reasoning process of CDSS and helps generate interpretable and accurate treatment recommendations. Herein, we reviewed the relevant ontologies in the field of diabetes treatment and the progress and challenges concerning ontology-based CDSSs. Firstly, we elaborated on the current status and challenges of diabetes treatment in China, highlighting the urgent need to improve the efficiency and quality of medical services. Then, we presented background information about ontologies and gave an overview of the framework, methodology, and features of using ontologies to construct CDSS. After that, we reviewed the ontologies and instances of ontology-based CDSS in the field of diabetes treatment in China and abroad and summarized their construction methods and features. Last but not the least, we discussed the future prospects of the field, suggesting that integrating evidence-based medicine with ontologies to build a reliable clinical recommendation system should be the current focus of CDSS development.

Telehealth System Based on the Ontology Design of a Diabetes Management Pathway Model in China: Development and Usability Study

BACKGROUND

Diabetes needs to be under control through management and intervention. Management of diabetes through mobile health is a practical approach; however, most diabetes mobile health management systems do not meet expectations, which may be because of the lack of standardized management processes in the systems and the lack of intervention implementation recommendations in the management knowledge base.

OBJECTIVE

In this study, we aimed to construct a diabetes management care pathway suitable for the actual situation in China to express the diabetes management care pathway using ontology and develop a diabetes closed-loop system based on the construction results of the diabetes management pathway and apply it practically.

METHODS

This study proposes a diabetes management care pathway model in which the management process of diabetes is divided into 9 management tasks, and the Diabetes Care Pathway Ontology (DCPO) is constructed to represent the knowledge contained in this pathway model. A telehealth system, which can support the comprehensive management of patients with diabetes while providing active intervention by physicians, was designed and developed based on the DCPO. A retrospective study was performed based on the data records extracted from the system to analyze the usability and treatment effects of the DCPO.

RESULTS

The diabetes management pathway ontology constructed in this study contains 119 newly added classes, 28 object properties, 58 data properties, 81 individuals, 426 axioms, and 192 Semantic Web Rule Language rules. The developed mobile medical system was applied to 272 patients with diabetes. Within 3 months, the average fasting blood glucose of the patients decreased by 1.34 mmol/L (P=.003), and the average 2-hour postprandial blood glucose decreased by 2.63 mmol/L (P=.003); the average systolic and diastolic blood pressures decreased by 11.84 mmHg (P=.02) and 8.8 mmHg (P=.02), respectively. In patients who received physician interventions owing to abnormal attention or low-compliance warnings, the average fasting blood glucose decreased by 2.45 mmol/L (P=.003), and the average 2-hour postprandial blood glucose decreased by 2.89 mmol/L (P=.003) in all patients with diabetes; the average systolic and diastolic blood pressure decreased by 20.06 mmHg (P=.02) and 17.37 mmHg (P=.02), respectively, in patients with both hypertension and diabetes during the 3-month management period.

CONCLUSIONS

This study helps guide the timing and content of interactive interventions between physicians and patients and regulates physicians' medical service behavior. Different management plans are formulated for physicians and patients according to different characteristics to comprehensively manage various cardiovascular risk factors. The application of the DCPO in the diabetes management system can provide effective and adequate management support for patients with diabetes and those with both diabetes and hypertension.

My Real Avatar has a Doctor Appointment in the Wepital: A System for Persistent, Efficient, and Ubiquitous Medical Care

COVID-19 created a great deal of personal, social, and economic anxiety in the USA and across the globe and exposed the inadequacy of traditional medical systems in handling large-scale emergencies. While telemedicine and virtual visits have become popular as a result, they end once a visit is over, hence lacking data persistence and continuity in caring for patients. Using the design science research approach with support from the theory of affordances, this paper proposes the design of a medical system (called wepital) in which patients receive care through their real avatars, enabling hospitals and other medical centers to provide immediate care that can continue for as long as a patient needs it. Real avatars are digital representations of patients that embody their real-time vital signs and health information. We have created a functional prototype to demonstrate how the proposed design can work. To assess the usability of the design, we have used the prototype in an experiment to provide medical advice to patient volunteers. Based on a theory-based conceptual model, we collected survey data after the experiment to identify factors contributing to the success of such a system, as measured by patient satisfaction. We report the factors that significantly contribute to the patients’ satisfaction. As part of the application and policy implications of our work, we propose a nationwide system that could supplement and expand the capacity of medical systems at the national or even global level.

Process quality of type 2 diabetes mellitus care and association with patient perceived attributes of family doctor service in urban general practices, Beijing, China

Background

Family doctor service (FDS) is a scheme oriented to improving the access and continuity of primary care in China. Type 2 diabetes mellitus (T2DM) management is a core component of FDS. However, evidence on the quality of T2DM care is lacking and the potential association between FDS attributes and T2DM care is largely unknown. This study attempted to assess the process quality of T2DM care in general practice and explore the association between patient perceived FDS attributes and process quality of T2DM care.

Methods

Total 400 patients were recruited from 5 community health service centers in two urban districts in Beijing. Questionnaire survey and extraction of data from electronic health record (EHR) were conducted to collect patient characteristics, patient perceived FDS attributes (accessibility, continuity and team-based care) and process quality indicators (monitoring and health counseling indicators). Chi-square test and a two-level generalized linear mixed model (GLMM) were used to explore the association between FDS attributes and process quality.

Results

The utilization rate of all the 12 indicators in monitoring, 6 indicators in health counseling and all the 18 process indicators, was 12.8%, 23.8% and 6.0% respectively. Over half of the patients (56.8%) perceived all the 3 FDS attributes. There were statistically significant associations between accessibility of care and lipid (p = 0.008), electrocardiogram (p = 0.016), retinopathy (p = 0.037) and peripheral neuropathy (p = 0.006) monitoring and each of the 6 health counseling indicators (all the p values < 0.05). Regular follow up (p = 0.039), plasma blood glucose (p = 0.020), blood pressure (p = 0.026), body mass index (p = 0.044) and foot (p = 0.005) monitoring as well as each of the 6 health counseling indicators (all the p values < 0.05) were more likely to be received by patients when continuity of care was ensured. Patients who were managed by a GP team had higher utilization rate of glycosylated hemoglobin monitoring (p = 0.026) and each of the 6 health counseling indicators (all the p values < 0.05). When the patients perceived one more FDS attribute, the indicators they received significantly increased by 1.50 (coefficient = 1.50, p < 0.001). Patients between the age of 65 and 74 years received 1.15 more indicators than those under 65 (coefficient = 1.15, p = 0.003). Patients with more than ten years duration of T2DM received 0.74 more indicators (coefficient = 0.74, p = 0.028). Patients taking both insulin and oral medicine received 0.97 more indicators than those taking oral medication only (coefficient = 0.97, p = 0.027). Patients who were managed by GPs with on-job training experience received 1.19 more indicators (coefficient = 1.19, p = 0.040). Among the patients who had completed junior high school or below, having better self-report health status (≥ 60) received 2.40 less indicators (coefficient = -2.40, p = 0.004).

Conclusions

Improvement of key monitoring and health counseling indicators might be needed in T2DM care in general practice in Beijing, China. Policies for improving process quality of T2DM care should be considered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-022-01838-0.

A scoping review of semantic integration of health data and information

OBJECTIVE

We summarized a decade of new research focusing on semantic data integration (SDI) since 2009, and we aim to: (1) summarize the state-of-art approaches on integrating health data and information; and (2) identify the main gaps and challenges of integrating health data and information from multiple levels and domains.

MATERIALS AND METHODS

We used PubMed as our focus is applications of SDI in biomedical domains and followed the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) to search and report for relevant studies published between January 1, 2009 and December 31, 2021. We used Covidence-a systematic review management system-to carry out this scoping review.

RESULTS

The initial search from PubMed resulted in 5,326 articles using the two sets of keywords. We then removed 44 duplicates and 5,282 articles were retained for abstract screening. After abstract screening, we included 246 articles for full-text screening, among which 87 articles were deemed eligible for full-text extraction. We summarized the 87 articles from four aspects: (1) methods for the global schema; (2) data integration strategies (i.e., federated system vs. data warehousing); (3) the sources of the data; and (4) downstream applications.

CONCLUSION

SDI approach can effectively resolve the semantic heterogeneities across different data sources. We identified two key gaps and challenges in existing SDI studies that (1) many of the existing SDI studies used data from only single-level data sources (e.g., integrating individual-level patient records from different hospital systems), and (2) documentation of the data integration processes is sparse, threatening the reproducibility of SDI studies.

Acceptance of the District Health Information System Version 2 Platform for Malaria Case-Based Surveillance By Health Care Workers in Botswana: Web-Based Survey

Background

Similar to many low- and middle-income countries, Botswana has identified eHealth as a means of improving health care service provision and delivery. The National Malaria Programme (NMP) in Botswana has implemented the District Health Information System version 2 (DHIS2) to support timely malaria case reporting across its 27 health districts; however, the implementation of an eHealth system is never without challenges. Barriers to the implementation of eHealth innovations within health care settings may arise at the individual or organizational levels. As such, the evaluation of user perceptions of the technology is an important step that can inform its sustainable implementation. The DHIS2 was implemented without evaluating user perceptions beforehand; therefore, the Botswana Ministry of Health and Wellness was uncertain about the likelihood of acceptance and use of the platform.

Objective

We aimed to determine the acceptance of the DHIS2 platform by the NMP in Botswana to gauge whether adoption would be successful.

Methods

The study’s design was informed by constructs of the technology acceptance model. A survey, with items assessed using a 7-point Likert scale, and focus group discussions were undertaken with DHIS2 core users from 27 health districts and NMP personnel at the Ministry of Health and Wellness. The web-based survey was administered from August 3, 2020 to September 30, 2020.

Results

Survey participants were core users (n=27). Focus group participants were NMP personnel (n=5). Overall, participants’ survey responses (frequently occurring scores of 7) showed their confidence in the DHIS2 platform for case-based surveillance of malaria; however, participants also noted some organizational issues that could compromise user acceptance of the DHIS2 platform.

Conclusions

Participants’ responses indicated their acceptance of the DHIS2 platform; however, the consideration of factors related to organizational readiness could further enhance successful acceptance, and consequently, successful adoption of the platform by the malaria program in Botswana.

Impact of Electronic Health Records Interoperability on Telehealth Service Outcomes

This paper aims to develop a telehealth success model and discusses three critical components: (1) health information quality, (2) electronic health record system quality, and (3) telehealth service quality to ensure effective telehealth service delivery, reduce professional burnout, and enhance access to care. The paper applied a policy analysis method and discussed telehealth applications in rural health, mental health, and veterans health services. The results pointed out the fact that, although telehealth paired with semantic/organizational interoperability facilitates value-based and team-based care, challenges remain to enhance user (both patients and clinicians) experience and satisfaction. The conclusion indicates that approaches at systemic and physician levels are needed to reduce disparities in health technology adoption and improve access to telehealth care.

Development of a conceptual framework for linking mHealth applications to eRecord systems in Botswana

BACKGROUND

The proliferation of mHealth solutions and eRecord systems is inevitable in developing countries, and ensuring their bi-directional interoperability is essential. Interoperability has been described as the ability for two or more systems or components to exchange information and use the information that has been exchanged. Given the importance of linking mHealth solutions to eRecord systems in the developing world, a suitable interoperability framework is required to provide an agreed approach to interoperability and specify common elements. Although eHealth interoperability frameworks exist in the literature, none meet all the requirements for linking mHealth solutions to eRecord systems in developing countries. The aim of this paper was to describe the design and development of a conceptual framework for linking mHealth solutions to eRecord systems in Botswana, as an exemplar.

METHODS

An iterative and reflective process was adopted, supported by existing literature and research including consultations with eHealth experts, and guidance from existing frameworks. These collectively identified key elements, concepts, and standards relevant and essential for framework design and development.

RESULTS

The mHealth-eRecord Interoperability Framework (mHeRIF) was developed which highlights the need for: governance and regulation of mHealth and eRecord systems, a national health information exchange, and which interoperability levels to achieve. Each of these are supported by integral themes and concepts. It also addresses the need for regular review, accreditation, and alignment of framework concepts and themes with a National eHealth Strategy Interoperability Development Process. To demonstrate the framework's applicability, a proposed architecture for the Kgonafalo mobile telemedicine programme is presented.

CONCLUSION

Interoperable mHealth solutions and eRecords systems have the potential to strengthen health systems. This paper reports the design and development of an evidence-based mHeRIF to align with, build upon, and expand National eHealth Strategies by guiding the linking of mHealth solutions to eRecord systems in Botswana and other developing countries facing similar circumstances.

Detection of Health-Related Events and Behaviours from Wearable Sensor Lifestyle Data Using Symbolic Intelligence: A Proof-of-Concept Application in the Care of Multiple Sclerosis

In this paper, we demonstrate the potential of a knowledge-driven framework to improve the efficiency and effectiveness of care through remote and intelligent assessment. More specifically, we present a rule-based approach to detect health related problems from wearable lifestyle sensor data that add clinical value to take informed decisions on follow-up and intervention. We use OWL 2 ontologies as the underlying knowledge representation formalism for modelling contextual information and high-level concepts and relations among them. The conceptual model of our framework is defined on top of existing modelling standards, such as SOSA and WADM, promoting the creation of interoperable knowledge graphs. On top of the symbolic knowledge graphs, we define a rule-based framework for infusing expert knowledge in the form of SHACL constraints and rules to recognise patterns, anomalies and situations of interest based on the predefined and stored rules and conditions. A dashboard visualizes both sensor data and detected events to facilitate clinical supervision and decision making. Preliminary results on the performance and scalability are presented, while a focus group of clinicians involved in an exploratory research study revealed their preferences and perspectives to shape future clinical research using the framework.

New Standards for Clinical Decision Support: A Survey of The State of Implementation

Objectives: To review the current state of research on designing and implementing clinical decision support (CDS) using four current interoperability standards: Fast Healthcare Interoperability Resources (FHIR); Substitutable Medical Applications and Reusable Technologies (SMART); Clinical Quality Language (CQL); and CDS Hooks.

Methods: We conducted a review of original studies describing development of specific CDS tools or infrastructures using one of the four targeted standards, regardless of implementation stage. Citations published any time before the literature search was executed on October 21, 2020 were retrieved from PubMed. Two reviewers independently screened articles and abstracted data according to a protocol designed by team consensus.

Results: Of 290 articles identified via PubMed search, 44 were included in this study. More than three quarters were published since 2018. Forty-three (98%) used FHIR; 22 (50%) used SMART; two (5%) used CQL; and eight (18%) used CDS Hooks. Twenty-four (55%) were in the design stage, 15 (34%) in the piloting stage, and five (11%) were deployed in a real-world setting. Only 12 (27%) of the articles reported an evaluation of the technology under development. Three of the four articles describing a deployed technology reported an evaluation. Only two evaluations with randomized study components were identified.

Conclusion: The diversity of topics and approaches identified in the literature highlights the utility of these standards. The infrequency of reported evaluations, as well as the high number of studies in the design or piloting stage, indicate that these technologies are still early in their life cycles. Informaticists will require a stronger evidence base to understand the implications of using these standards in CDS design and implementation.

Interoperability opportunities and challenges in linking mhealth applications and eRecord systems: Botswana as an exemplar

Background

Significant investments have been made towards the implementation of mHealth applications and eRecord systems globally. However, fragmentation of these technologies remains a big challenge, often unresolved in developing countries. In particular, evidence shows little consideration for linking mHealth applications and eRecord systems. Botswana is a typical developing country in sub-Saharan Africa that has explored mHealth applications, but the solutions are not interoperable with existing eRecord systems. This paper describes Botswana’s eRecord systems interoperability landscape and provides guidance for linking mHealth applications to eRecord systems, both for Botswana and for developing countries using Botswana as an exemplar.

Methods

A survey and interviews of health ICT workers and a review of the Botswana National eHealth Strategy were completed. Perceived interoperability benefits, opportunities and challenges were charted and analysed, and future guidance derived.

Results

Survey and interview responses showed the need for interoperable mHealth applications and eRecord systems within the health sector of Botswana and within the context of the National eHealth Strategy. However, the current Strategy does not address linking mHealth applications to eRecord systems. Across Botswana’s health sectors, global interoperability standards and Application Programming Interfaces are widely used, with some level of interoperability within, but not between, public and private facilities. Further, a mix of open source and commercial eRecord systems utilising relational database systems and similar data formats are supported. Challenges for linking mHealth applications and eRecord systems in Botswana were identified and categorised into themes which led to development of guidance to enhance the National eHealth Strategy.

Conclusion

Interoperability between mHealth applications and eRecord systems is needed and is feasible. Opportunities and challenges for linking mHealth applications to eRecord systems were identified, and future guidance stemming from this insight presented. Findings will aid Botswana, and other developing countries, in resolving the pervasive disconnect between mHealth applications and eRecord systems.

The Fast Health Interoperability Resources (FHIR) Standard: Systematic Literature Review of Implementations, Applications, Challenges and Opportunities

Background

Information technology has shifted paper-based documentation in the health care sector into a digital form, in which patient information is transferred electronically from one place to another. However, there remain challenges and issues to resolve in this domain owing to the lack of proper standards, the growth of new technologies (mobile devices, tablets, ubiquitous computing), and health care providers who are reluctant to share patient information. Therefore, a solid systematic literature review was performed to understand the use of this new technology in the health care sector. To the best of our knowledge, there is a lack of comprehensive systematic literature reviews that focus on Fast Health Interoperability Resources (FHIR)-based electronic health records (EHRs). In addition, FHIR is the latest standard, which is in an infancy stage of development. Therefore, this is a hot research topic with great potential for further research in this domain.

Objective

The main aim of this study was to explore and perform a systematic review of the literature related to FHIR, including the challenges, implementation, opportunities, and future FHIR applications.

Methods

In January 2020, we searched articles published from January 2012 to December 2019 via all major digital databases in the field of computer science and health care, including ACM, IEEE Explorer, Springer, Google Scholar, PubMed, and ScienceDirect. We identified 8181 scientific articles published in this field, 80 of which met our inclusion criteria for further consideration.

Results

The selected 80 scientific articles were reviewed systematically, and we identified open questions, challenges, implementation models, used resources, beneficiary applications, data migration approaches, and goals of FHIR.

Conclusions

The literature analysis performed in this systematic review highlights the important role of FHIR in the health care domain in the near future.

Interoperability frameworks linking mHealth applications to electronic record systems

BACKGROUND

mHealth presents innovative approaches to enhance primary healthcare delivery in developing countries like Botswana. The impact of mHealth solutions can be improved if they are interoperable with eRecord systems such as electronic health records, electronic medical records and patient health records. eHealth interoperability frameworks exist but their availability and utility for linking mHealth solutions to eRecords in developing world settings like Botswana is unknown. The recently adopted eHealth Strategy for Botswana recognises interoperability as an issue and mHealth as a potential solution for some healthcare needs, but does not address linking the two.

AIM

This study reviewed published reviews of eHealth interoperability frameworks for linking mHealth solutions with eRecords, and assessed their relevance to informing interoperability efforts with respect to Botswana's eHealth Strategy.

METHODS

A structured literature review and analysis of published reviews of eHealth interoperability frameworks was performed to determine if any are relevant to linking mHealth with eRecords. The Botswanan eHealth Strategy was reviewed.

RESULTS

Four articles presented and reviewed eHealth interoperability frameworks that support linking of mHealth interventions to eRecords and associated implementation strategies. While the frameworks were developed for specific circumstances and therefore were based upon varying assumptions and perspectives, they entailed aspects that are relevant and could be drawn upon when developing an mHealth interoperability framework for Botswana. Common emerging themes of infrastructure, interoperability standards, data security and usability were identified and discussed; all of which are important in the developing world context such as in Botswana. The Botswana eHealth Strategy recognises interoperability, mHealth, and eRecords as distinct issues, but not linking of mHealth solutions with eRecords.

CONCLUSIONS

Delivery of healthcare is shifting from hospital-based to patient-centered primary healthcare and community-based settings, using mHealth interventions. The impact of mHealth solutions can be improved if data generated from them are converted into digital information ready for transmission and incorporation into eRecord systems. The Botswana eHealth Strategy stresses the need to have interoperable eRecords, but mHealth solutions must not be left out. Literature insight about mHealth interoperability with eRecords can inform implementation strategies for Botswana and elsewhere.

Disentangling the clinical data chaos: User-centered interface system design for trauma centers

This paper presents a year-long study of our project, aiming at (1) understanding the work practices of clinical staff in trauma intensive care units (TICUs) at a trauma center, with respect to their usage of clinical data interface systems, and (2) developing and evaluating an intuitive and user-centered clinical data interface system for their TICU environments. Based on a long-term field study in an urban trauma center that involved observation-, interview-, and survey-based studies to understand our target users and their working environment, we designed and implemented MediSenseView as a working prototype. MediSenseView is a clinical-data interface system, which was developed through the identification of three core challenges of existing interface system use in a trauma care unit-device separation, usage inefficiency, and system immobility-from the perspectives of three staff groups in our target environment (i.e., doctors, clinical nurses and research nurses), and through an iterative design study. The results from our pilot deployment of MediSenseView and a user study performed with 28 trauma center staff members highlight their work efficiency and satisfaction with MediSenseView compared to existing clinical data interface systems in the hospital.

Connected health for growth hormone treatment research and clinical practice: learnings from different sources of real-world evidence (RWE)-large electronically collected datasets, surveillance studies and individual patients' cases

Background

A range of factors can reduce the effectiveness of treatment prescribed for the long-term management of chronic health conditions, such as growth disorders. In particular, prescription medications may not achieve the positive outcomes expected because approximately half of patients adhere poorly to the prescribed treatment regimen.

Methods

Adherence to treatment has previously been assessed using relatively unreliable subjective methods, such as patient self-reporting during clinical follow-up, or counting prescriptions filled or vials returned by patients. Here, we report on a new approach, the use of electronically recorded objective evidence of date, time, and dose taken which was obtained through a comprehensive eHealth ecosystem, based around the easypod™ electromechanical auto-injection device and web-based connect software. The benefits of this eHealth approach are also illustrated here by two case studies, selected from the Finnish cohort of the easypod™ Connect Observational Study (ECOS), a 5-year, open-label, observational study that enrolled children from 24 countries who were being treated with growth hormone (GH) via the auto-injection device.

Results

Analyses of data from 9314 records from the easypod™ connect database showed that, at each time point studied, a significantly greater proportion of female patients had high adherence (≥ 85%) than male patients (2849/3867 [74%] vs 3879/5447 [71%]; P < 0.001). Furthermore, more of the younger patients (< 10 years for girls, < 12 years for boys) were in the high adherence range (P < 0.001). However, recursive partitioning of data from ECOS identified subgroups with lower adherence to GH treatment ‒ children who performed the majority of injections themselves at an early age (~ 8 years) and teenagers starting treatment aged ≥ 14 years.

Conclusions

The data and case studies presented herein illustrate the importance of adherence to GH therapy and how good growth outcomes can be achieved by following treatment as described. They also show how the device, software, and database ecosystem can complement normal clinical follow-up by providing HCPs with reliable information about patient adherence between visits and also providing researchers with real-world evidence of adherence and growth outcomes across a large population of patients with growth disorders treated with GH via the easypod™ device.

El-Bakry H, Abdelrazek S. Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges

Chronic diseases are becoming more widespread. Treatment and monitoring of these diseases require going to hospitals frequently, which increases the burdens of hospitals and patients. Presently, advancements in wearable sensors and communication protocol contribute to enriching the healthcare system in a way that will reshape healthcare services shortly. Remote patient monitoring (RPM) is the foremost of these advancements. RPM systems are based on the collection of patient vital signs extracted using invasive and noninvasive techniques, then sending them in real-time to physicians. These data may help physicians in taking the right decision at the right time. The main objective of this paper is to outline research directions on remote patient monitoring, explain the role of AI in building RPM systems, make an overview of the state of the art of RPM, its advantages, its challenges, and its probable future directions. For studying the literature, five databases have been chosen (i.e., science direct, IEEE-Explore, Springer, PubMed, and science.gov). We followed the (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) PRISMA, which is a standard methodology for systematic reviews and meta-analyses. A total of 56 articles are reviewed based on the combination of a set of selected search terms including RPM, data mining, clinical decision support system, electronic health record, cloud computing, internet of things, and wireless body area network. The result of this study approved the effectiveness of RPM in improving healthcare delivery, increase diagnosis speed, and reduce costs. To this end, we also present the chronic disease monitoring system as a case study to provide enhanced solutions for RPMs.

Mobile health applications for disease screening and treatment support in low-and middle-income countries: A narrative review

The advances in mobile technologies and applications are driving the transformation in health services delivery globally. Mobile phone penetration is increasing exponentially in low-and middle-income countries, hence using mobile phones for healthcare services could reach more people in resource-limited settings than the traditional forms of healthcare provision. The review presents recent literature on facilitators and barriers of implementing mHealth for disease screening and treatment support in low-and middle-income countries. We searched for relevant literature from the following electronic databases: MEDLINE; CINAHL with full text via EBSCOhost; Science Direct; PubMed; Google Scholar and Web of Science using the keywords for relevant studies. We searched for published studies from 2015 to August 2020 with no language limitations. A total of 721 articles identified, 125 articles met the inclusion criteria and were included in the qualitative synthesis. The review demonstrates relevant facilitators for the implementation of mHealth, which includes knowledge, attitudes, and perceptions of stakeholders on the use of mHealth and the performance of mHealth for disease diagnosis in low and-middle-income countries. Barriers and challenges hindering the implementation of mHealth applications were also identified. We proposed a framework for improving the implementation of mHealth for disease screening and treatment support in low-and middle-income countries.

Mapping evidence of mobile health technologies for disease diagnosis and treatment support by health workers in sub-Saharan Africa: a scoping review

Background

The rapid growth of mobile technology has given rise to the development of mobile health (mHealth) applications aimed at treating and preventing a wide range of health conditions. However, evidence on the use of mHealth in high disease burdened settings such as sub-Sharan Africa is not clear. Given this, we systematically mapped evidence on mHealth for disease diagnosis and treatment support by health workers in sub-Saharan Africa.

Methods

We conducted a scoping review study guided by the Arksey and O’Malley’s framework, Levac et al. recommendations, and Joanna Briggs Institute guidelines. We thoroughly searched the following databases: MEDLINE and CINAHL with full text via EBSCOhost; PubMed; Science Direct and Google Scholar for relevant articles from the inception of mHealth technology to April 2020. Two reviewers independently screened abstracts and full-text articles using the eligibility criteria as reference. This study employed the mixed methods appraisal tool version 2018 to assess the methodological quality of the included studies.

Results

Out of the 798 articles identified, only 12 published articles presented evidence on the availability and use of mHealth for disease diagnosis and treatment support by health workers in SSA since 2010. Of the 12 studies, four studies were conducted in Kenya; two in Malawi; two in Nigeria; one in South Africa; one in Zimbabwe; one in Mozambique, and one in Lesotho. Out of the 12 studies, one reported the use of mHealth for diseases diagnosis; three reported the use of mHealth to manage HIV; two on the management of HIV/TB; two on the treatment of malaria; one each on the management of hypertension; cervical cancer; and three were not specific on any disease condition. All the 12 included studies underwent methodological quality appraisal with a scored between 70 and 100%.

Conclusions

The study shows that there is limited research on the availability and use of mHealth by health workers for disease diagnosis and treatment support in sub-Saharan Africa. We, therefore, recommend primary studies focusing on the use of mHealth by health workers for disease diagnosis and treatment support in sub-Saharan Africa.

mHealth applications to support caregiver needs and engagement during stroke recovery: A content review

Caregiving in stroke results in severe physical, psychological, and social impacts on the caregiver. Over the past few years, researchers have explored the use of mHealth technologies to support healthcare-related activities due to their ability to provide real-time care at any given place or time. The purpose of this content review is to investigate mHealth apps in supporting stroke caregiving engagement based on three aspects: motivation, value, and satisfaction. We searched app stores and repositories for apps related to stroke caregiving published up to September 2020. Extracted apps were reviewed and filtered using inclusion criteria, and then downloaded onto compatible devices to determine eligibility. Results were compared with evidence-based frameworks to identify the ability of these apps in engaging and supporting the caregiver. Forty-seven apps were included in this review that enabled caregivers to support their needs, such as adjustment to new roles and relationships, involvement in care and caring for oneself using several different functionalities. These functionalities include information resources, risk assessment, remote monitoring, data sharing, reminders and so on. However, no single app was identified that focuses on all aspects of stroke caregiving. We also identified several challenges faced by users through their reviews and the factors associated with value and satisfaction. Our findings can add to the knowledge of existing mHealth technologies and their functionalities to support stroke caregiving needs, and the importance of considering user engagement in the design. They can be used by developers and researchers looking to design better mHealth apps for stroke caregiving.

EDDAMAP: efficient data-dependent approach for monitoring asymptomatic patient

Background

A pandemic affects healthcare delivery and consequently leads to socioeconomic complications. During a pandemic, a community where there lives an asymptomatic patient (AP) becomes a potential endemic zone. Assuming we want to monitor the travel and/or activity of an AP in a community where there is a pandemic. Presently, most monitoring algorithms are relatively less efficient to find a suitable solution as they overlook the continuous mobility instances and activities of the AP over time. Conversely, this paper proposes an EDDAMAP as a compelling data-dependent technique and/or algorithm towards efficient continuous monitoring of the travel and/or activity of an AP.

Methods

In this paper, it is assumed that an AP is infected with a contagious disease in which the EDDAMAP technique exploits a GPS-enabled mobile device by tagging it to the AP along with its travel within a community. The technique further examines the Spatio-temporal trajectory of the AP to infer its spatial time-bounded activity. The technique aims to learn the travels of the AP and correlates them to its activities to derive some classes of point of interests (POIs) in a location. Further, the technique explores the natural occurring POIs via modelling to identify some regular stay places (SP) and present them as endemic zones. The technique adopts concurrent object feature localization and recognition, branch and bound formalism and graph theory to cater for the worst error-guaranteed approximation to obtain a valid and efficient query solution and also experiments with a real-world GeoLife dataset to confirm its performance.

Results

The EDDAMAP technique proofs a compelling technique towards efficient monitoring of an AP in case of a pandemic.

Conclusions

The EDDAMAP technique will promote the discovery of endemic zones and hence some public healthcare facilities can rely on it to facilitate the design of patient monitoring system applications to curtail a global pandemic.