Optimizing Telehealth: Leveraging Key Performance Indicators for Enhanced TeleHealth and Digital Healthcare Outcomes (Telemechron Study).

Over the past decade, the use of telehealth has garnered increasing attention. The focus on quality aspects has seen significant growth in tandem with the telehealth expansion. Having useful indicators in this area is becoming increasingly strategic for fully integrating the technology into the health domain. These indicators can help monitor and evaluate the quality of telehealth services, guiding improvements and ensuring that these digital solutions meet the necessary standards for effective healthcare delivery. The purpose of this study is to analyze Key performance indicators (KPIs) in telehealth within institutional websites and the scientific dissemination world by means of a narrative review. A narrative review was proposed with these two specific points of view based on a standardized checklist and a quality control procedure for including scientific papers in the analysis. Results from scientific studies emphasize KPIs such as patient outcomes, operational efficiency, technical reliability, and cost-effectiveness. These include measures like improvements in condition management, patient satisfaction, consultation numbers, waiting times, and cost savings. Institutional documents from entities like the WHO also show diverse perspectives, focusing on equitable access, clinical excellence, patient prioritization, response times, and patient and staff satisfaction. The findings suggest that adopting a comprehensive set of KPIs and continuously monitoring and evaluating telehealth services can enhance their effectiveness, efficiency, and equity, ultimately improving healthcare outcomes and accessibility.

Quality of the digital gp visits and characteristics of the users: retrospective observational study.

OBJECTIVES: This study compares the demographics, diagnoses, re-admission rates, sick leaves, and prescribed medications of patients accessing digital general practitioner (GP) visits with those of patients opting for traditional face-to-face appointments in a primary health care setting. DESIGN: The study adopted a retrospective analysis of patient record data collected in 2019, comparing visits to a digital primary health center with traditional health center visits. SETTING: Primary health care. PARTICIPANTS: The data encompassed patients who utilized the digital clinic and those who visited public health centers for primary health care services. MAIN OUTCOME MEASURES: The study assessed demographics, health diagnoses, prescribed medications, sick leave recommendations, re-admission rates, and differences in costs between digital clinic and face-to-face visits. Secondary outcomes included a comparative analysis of medication categories, resolution rates for health problems, and potential impacts on health care utilization. RESULTS: Digital clinic users were typically younger, more educated, and predominantly female compared with health centre users. Digital visits were well-suited for uncomplicated infections, while health centre appointments were associated with a higher prevalence of chronic conditions. Medication patterns differed between the two modalities, with digital clinic users receiving generic over-the-counter drugs and antibiotics, whereas health centre visits commonly involved cardiac and antihypertensive medications. Sick leave recommendations were slightly higher in the digital clinic, but the difference was not significant. Approximately 70% of health problems addressed in the digital clinic were successfully resolved, and the cost of digital visits was about 50,3% of face-to-face appointments. CONCLUSION: Digital health care services offer a cost-efficient alternative for specific health problems, appealing to younger, educated individuals, when compared to the users of public health center, and may enable improvement of cost-effectiveness combined with acceptable demand management and patient segmentation practices. The results highlight the potential benefits of digital clinics, particularly for uncomplicated cases, while also emphasizing the importance of suitable referral mechanisms for in-person consultations.

Deployment and validation of a smart bed architecture for untethered patients with wireless biomonitoring stickers.

Conventional patient monitoring in healthcare has limitations such as delayed identification of deteriorating conditions, disruptions to patient routines, and discomfort due to extensive wiring for bed-bound patients. To address these, we have recently developed an innovative IoT-based healthcare system for real-time wireless patient monitoring. This system includes a flexible epidermal patch that collects vital signs using low power electronics and transmits the data to IoT nodes in hospital beds. The nodes connect to a smart gateway that aggregates the information and interfaces with the hospital information system (HIS), facilitating the exchange of electronic health records (EHR) and enhancing access to patient vital signs for healthcare professionals. Our study validates the proposed smart bed architecture in a clinical setting, assessing its ability to meet healthcare personnel needs, patient comfort, and data transmission reliability. Technical performance assessment involves analyzing key performance indicators for communication across various interfaces, including the wearable device and the smart box, and the link between the gateway and the HIS. Also, a comparative analysis is conducted on data from our architecture and traditional hospital equipment. Usability evaluation involves questionnaires completed by patients and healthcare professionals. Results demonstrate the robustness of the architecture proposed, exhibiting reliable and efficient information flow, while offering significant improvements in patient monitoring over conventional wired methods, including unrestricted mobility and improved comfort to enhance healthcare delivery.

Enhancing user experience in the digital service environment: A comprehensive study on the design and evaluation of internet-based healthcare products.

RATIONALE: In the era of burgeoning digital technology, healthcare is a challenging transformative change towards virtual and digital platforms. Internet-based healthcare services are emerging as a popular trend within the medical area. User experience (UX) is paramount for the healthcare service, as it significantly influences experience satisfaction and fosters user viscosity. Gaining a profound understanding of users' demands and crafting services that align with their expectations is essential. METHODS: Consequently, exploring an effective design approach for the digital healthcare service that prioritizes UX along with utilizing a comprehensive evaluation methodology to handle UX data, is of profound importance. This study introduces a design methodology for Internet-based healthcare products grounded in the UX and mental (UX-M) model. Aiming to refine the Internet-based healthcare product design by integrating insights from the experience data, it employs the Delphi-ANP and the fuzzy comprehensive evaluation to determine evaluation indexes and conduct experiential assessments. RESULTS: The UX evaluation results of existing schemes are compared with the proposed design scheme of the intelligent guidance and internet hospital. The findings indicate that the UX evaluation of Internet-based medical services with the proposed method outperforms the existing schemes. CONCLUSIONS: On the one hand, UX research of Internet-based healthcare products can significantly enhance service satisfaction for patients utilizing online medical treatments. On the other hand, the analysis of experience-based evaluation empowers designers to refine and improve UX design of Internet-based medical services. Such research endeavors are critical for enhancing the overall quality of service offerings and elevating user satisfaction in the digital healthcare landscape.

Coopetition, exploration and exploitation capabilities, and growth performance in digital healthcare ventures.

Introduction: Studies focusing on coopetition and dynamic capabilities have expanded significantly over the past several decades. Coopetition strategy and dynamic capabilities are increasingly recognised as sources of sustained competitive advantage. The purpose of this paper is to provide a better understanding of the factors driving growth performance in digital healthcare ventures by examining the role of coopetition, exploration and exploitation capabilities, and environmental uncertainty. While numerous studies have examined the competitive advantage of coopetition, its specific contribution to the growth of ventures in the digital realm remains less explored. Clarifying the strategic role of coopetition in driving growth performance is critical for delineating the intricate relationship between coopetition and growth performance, particularly in the context of digital healthcare ventures. To fill in this research gap, this study uses coopetition theory and dynamic capabilities theory to look at how exploration and exploitation capabilities, as well as environmental uncertainty, affect the relationship between coopetition and growth performance in digital healthcare ventures. Methods: We collected a total of 338 questionnaires from Chinese digital healthcare ventures between March 2023 and August 2023. We conducted data analysis using SPSS 26.0 and its macro-program PROCESS. Results: Our results confirm that coopetition has a positive effect on growth performance in digital healthcare ventures. Furthermore, exploration and exploitation capabilities fully mediate the relationship between coopetition and growth performance. Moreover, environmental uncertainty significantly and distinctively moderates the impact of exploration and exploitation capabilities on growth performance. Discussion: This study contributes to the existing literature by providing deeper insight into the relationship between coopetition and growth performance in digital healthcare ventures. It also offers important practical implications for public health improvement and socio-economic development.

Smart laser Sintering: Deep Learning-Powered powder bed fusion 3D printing in precision medicine.

Medicines remain ineffective for over 50% of patients due to conventional mass production methods with fixed drug dosages. Three-dimensional (3D) printing, specifically selective laser sintering (SLS), offers a potential solution to this challenge, allowing the manufacturing of small, personalized batches of medication. Despite its simplicity and suitability for upscaling to large-scale production, SLS was not designed for pharmaceutical manufacturing and necessitates a time-consuming, trial-and-error adaptation process. In response, this study introduces a deep learning model trained on a variety of features to identify the best feature set to represent drugs and polymeric materials for the prediction of the printability of drug-loaded formulations using SLS. The proposed model demonstrates success by achieving 90% accuracy in predicting printability. Furthermore, explainability analysis unveils materials that facilitate SLS printability, offering invaluable insights for scientists to optimize SLS formulations, which can be expanded to other disciplines. This represents the first study in the field to develop an interpretable, uncertainty-optimized deep learning model for predicting the printability of drug-loaded formulations. This paves the way for accelerating formulation development, propelling us into a future of personalized medicine with unprecedented manufacturing precision.

Digital Healthcare and Internet Derived Information Obstruction Treatment (IDIOT) Syndrome: Understanding the Link Between Clicks and Consequences.

This article explores the phenomenon of Internet Derived Information Obstruction Treatment (IDIOT) syndrome, highlighting the impact of internet-derived health information on individuals' treatment decisions. Drawing on recent studies, including the rise of IDIOT syndrome due to increased internet use and the potential risks associated with self-medication based on online information, the editorial emphasizes the importance of critically evaluating health information. Insights from research conducted in the last few years highlight the complexity of health conditions and the necessity of seeking professional medical guidance to address the various clinical conditions and their consequences. This article sets the stage for a detailed examination of the IDIOT syndrome and its implications for healthcare decision-making in the digital era.

[Chat messenger use in the care of patients with Parkinson's disease]. / Chat-Messenger-Nutzung in der Parkinson-Versorgung.

BACKGROUND: The demand for chat messaging apps for communication between physicians, therapists and patients is increasing. The expectations for this form of communication and uncertainties regarding introduction and use are heterogeneous. OBJECTIVE: The implementation of chat messengers in the care of patients with Parkinson's disease should be facilitated by recommendations regarding introduction and usage. METHODS: Semi-structured interviews with neurologists and physiotherapists were conducted to capture the expectations and needs regarding the use of chat messengers. From the data analysis, recommendations were derived. RESULTS: The expectations for technical functionality exceeded the chat messenger functions. This concerns, e.g., the connection of the chat messenger to the electronic patient file. There is a great deal of uncertainty, particularly when it comes to the applicable General Data Protection Regulations (GDPR). The recommendations relating to the use of chat messengers, data protection aspects, the design of such tools and methodological considerations can help to implement the tool as an additional communication channel. CONCLUSION: Practical recommendations regarding functionality, the use of chat messengers in everyday life and in relation to data protection are derived from the results. By improving knowledge, physicians and therapists can contribute to the successful establishment of chat messengers as an additional communication tool.

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 âˆ¼ 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.

Medical data market platforms and medical data trade demands of medical device companies.

Objective: The significance of big data is increasingly acknowledged across all sectors, including medicine. Moreover, the trend of data trading is on the rise, particularly in exchanging other data for medical data to rejuvenate the medical industry. This study aimed to discern the facilitating factors of healthcare data trade. Methods: We assessed five medical data market platforms on October, 2022, based on three criteria: (a) clarity in articulating the data for sale; (b) transparency in specifying the data costs; and (c) explicit indication that payment grants data access. This helped identify the traded medical data types. Additionally, we anonymously surveyed 43 representatives from medical device companies about their demand for medical data trading, achieving a response rate of 66%. Results: Of the medical data traded on these platforms, 93.34% was structured, while 5.66% was unstructured, indicating an imbalance. Although there was a higher demand for structured medical data, there was also interest in purchasing unstructured medical data. Conclusion: Unstructured big data are crucial for medical device development, fueling the demand for trading such data. Many stakeholders view the data market as essential and are willing to procure medical data. Consequently, medical device companies will need methods to acquire unstructured medical data for developing innovative and enhanced medical devices.

Effectiveness of artificial intelligence in detecting and managing depressive disorders: Systematic review.

OBJECTIVES: This study underscores the importance of exploring AI's creative applications in treating depressive disorders to revolutionize mental health care. Through innovative integration of AI technologies, the research confirms their positive effects on preventing, diagnosing, and treating depression. The systematic review establishes an evidence base for AI in depression management, offering directions for effective interventions. METHODS: This systematic literature review investigates the effectiveness of AI in depression management by analyzing studies from January 1, 2017, to May 31, 2022. Utilizing search engines like IEEE Xplore, PubMed, and Web of Science, the review focused on keywords such as Depression/Mental Health, Machine Learning/Artificial Intelligence, and Prediction/Diagnosis. The analysis of 95 documents involved classification based on use, data type, and algorithm type. RESULTS: The study revealed that AI in depression management excelled in accuracy, particularly in monitoring and prediction. Biomarker-derived data demonstrated the highest accuracy, with the CNN algorithm proving most effective. The findings affirm the therapeutic benefits of AI, including treatment, detection, and disease prediction, highlighting its potential in analyzing monitored data for depression management. LIMITATIONS: This study exclusively examined the application of AI in individuals with depressive disorders. Interpretation should be cautious due to the limited scope of subjects to this specific population. CONCLUSIONS: To introduce digital healthcare and therapies for ongoing depression management, it's crucial to present empirical evidence on the medical fee payment system, safety, and efficacy. These findings support enhanced medical accessibility through digital healthcare, offering personalized disease management for patients seeking non-face-to-face treatment.

The reflexive imperative in the digital age: Using Archer's 'fractured reflexivity' to theorise widening inequities in UK general practice.

'Reflexivity', as used by Margaret Archer, means creative self-mastery that enables individuals to evaluate their social situation and act purposively within it. People with complex health and social needs may be less able to reflect on their predicament and act to address it. Reflexivity is imperative in complex and changing social situations. The substantial widening of health inequities since the introduction of remote and digital modalities in health care has been well-documented but inadequately theorised. In this article, we use Archer's theory of fractured reflexivity to understand digital disparities in data from a 28-month longitudinal ethnographic study of 12 UK general practices and a sample of in-depth clinical cases from 'Deep End' practices serving highly deprived populations. Through four composite patient cases crafted to illustrate different dimensions of disadvantage, we show how adverse past experiences and structural inequities intersect with patients' reflexive capacity to self-advocate and act strategically. In some cases, staff were able to use creative workarounds to compensate for patients' fractured reflexivity, but such actions were limited by workforce capacity and staff awareness. Unless a more systematic safety net is introduced and resourced, people with complex needs are likely to remain multiply disadvantaged by remote and digital health care.

Clinical Implication of Maumgyeol Basic Biotypes-Electroencephalography- and Photoplethysmogram-Based Bwave State Inventory.

OBJECTIVE: The development of individual subtypes based on biomarkers offers a cost-effective and timely avenue to comprehending individual differences pertaining to mental health, independent from individuals' subjective insights. Incorporating 2-channel electroencephalography (EEG) and photoplethysmogram (PPG), we sought to establish a subtype classification system with clinical relevance. METHODS: One hundred healthy participants and 99 patients with psychiatric disorders were recruited. Classification thresholds were determined using the EEG and PPG data from 2,278 individuals without mental disorders, serving to classify subtypes in our sample of 199 participants. Multivariate analysis of variance was applied to examine psychological distinctions among these subtypes. K-means clustering was employed to verify the classification system. RESULTS: The distribution of subtypes differed between healthy participants and those with psychiatric disorders. Cognitive abilities were contingent upon brain subtypes, while mind subtypes exhibited significant differences in symptom severity, overall health, and cognitive stress. K-means clustering revealed that the results of our theory-based classification and data-driven classification are comparable. The synergistic assessment of both brain and mind subtypes was also explored. CONCLUSION: Our subtype classification system offers a concise means to access individuals' mental health. The utilization of EEG and PPG signals for subtype classification offers potential for the future of digital mental healthcare.

The potential of virtual healthcare technologies to reduce healthcare services' carbon footprint.

The COVID-19 pandemic demonstrated the potential to reduce our carbon footprint especially by reducing travel. We aim to describe healthcare and health education services' contribution to the global climate emergency and identify the need for increased use of virtual health service delivery and undergraduate/postgraduate education to help reduce the impact of health service and health education delivery on the environment. Health care services, as one of the largest contributors to carbon emissions, must take steps to rapidly reduce their carbon footprint. Health services have unfortunately paid little attention to this issue until recently. Virtual healthcare and education have a valuable role in transition to a net carbon-zero outcome. Given the increasing use of and satisfaction with virtual health services such as telehealth, and the increase in virtual education opportunities, it is important that a concerted effort is undertaken to increase their use across health services and education in the future.

Establishment of a Dataset for the Traditional Korean Medicine Examination in Healthy Adults.

We established a protocol for the traditional Korean medicine examination (KME) and methodically gathered data following this protocol. Potential indicators for KME were extracted through a literature review; the first KME protocol was developed based on three rounds of expert opinions. The first KME protocol's feasibility was confirmed, and data were collected over four years from traditional Korean medicine (KM) hospitals, focusing on healthy adults, using the final KME protocol. A literature review identified 175 potential core indicators, condensed into 73 indicators after three rounds of expert consultation. The first KME protocol, which was categorized under questionnaires and medical examinations, was developed after the third round of expert opinions. A pilot study using the first KME protocol was conducted to ensure its validity, leading to modifications resulting in the development of the final KME protocol. Over four years, data were collected from six KM hospitals, focusing on healthy adults; we obtained a dataset comprising 11,036 healthy adults. This is the first protocol incorporating core indicators of KME in a quantitative form and systematically collecting data. Our protocol holds potential merit in evaluating predisposition to diseases or predicting diseases.

Real-World Effectiveness of the Gla-300 + Cap + App Program in Adult Users Living with Type 2 Diabetes in Taiwan.

INTRODUCTION: Health2Sync (H2S) is a digital health technology platform that provides coaching and titration support to patients with diabetes. The Mallya cap converts a conventional insulin pen into a smart connected device that can automatically synchronize dose values and associated timestamps (upon injection) to the H2S platform. This single-arm real-world study evaluated the effectiveness of insulin glargine 300 U/mL (Gla-300) combined with H2S and Mallya cap (Gla-300 + Cap + App program) on clinical outcomes among users with type 2 diabetes (T2D) in Taiwan. METHODS: Adults (aged ≥ 20 years) with T2D who were registered H2S users and initiated Mallya cap for a new/existing Gla-300 regimen (identification period May 1, 2021-May 31, 2022) were included in this retrospective cohort study. Follow-up data from H2S were collected for 90 days. Glycated hemoglobin (HbA1c) change (baseline to follow-up) and HbA1c goal attainment were primary outcomes. Hypoglycemia incidence and usage metrics of Mallya cap were secondary outcomes. RESULTS: Of 83 participants, 38.6% were new Gla-300 users. HbA1c was reduced in both new (- 2.4 [2.7] %, - 26.2 [29.5] mmol/mol) and previous Gla-300 users (- 0.5 [1.6] %, - 5.5 [17.5] mmol/mol). Reduction in HbA1c was significant (p < 0.05) in both groups. At follow-up, 43.4% of users had a reduction of > 0.5%. Mean HbA1c reductions increased numerically with higher baseline HbA1c and with longer duration of Mallya cap usage. CONCLUSIONS: Use of digital technology within a connected ecosystem such as Gla-300 + Cap + App program could help people with type 2 diabetes to improve their glycemic condition.

Machine Translation for Multilingual Cancer Patient Education: Bridging Languages, Navigating Challenges.

This commentary evaluates the use of machine translation for multilingual patienteducation in oncology. It critically examines the balance between technologicalbenefits in language accessibility and the potential for increasing healthcare disparities.The analysis emphasizes the need for a multidisciplinary approach to translation thatincorporates linguistic accuracy, medical clarity, and cultural relevance. Additionally, ithighlights the ethical considerations of digital literacy and access, underscoring theimportance of equitable patient education. This contribution seeks to advance thediscussion on the thoughtful integration of technology in healthcare communication,focusing on maintaining high standards of equity, quality, and patient care.

Digital psychiatry in Nigeria: A scoping review.

Background: Mental healthcare workforce shortage in Nigeria poses a major obstacle to mental health services scale-up. Digital psychiatry may provide a veritable platform to bridge treatment gaps. Aim: To provide an overview of quantity and range of peer-reviewed publications on digital psychiatry in Nigeria. Setting: A comprehensive literature search encompassed all original, peer-reviewed research articles on digital psychiatry in Nigeria. PubMed, Google Scholar, and a direct exploration of relevant journal article reference lists were utilised. Inclusion criteria covered peer-reviewed original articles conducted in Nigeria between January 2013 and January 2023, regardless of quality. Exclusions comprised case reports, reviews, dissertations, and abstracts. Methods: Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines were adhered to, while methodological framework of Arksey and O'Malley was used to describe the review. Results: Fourteen studies meeting inclusion criteria exhibited two primary research areas: implementation and intervention. Most studies focused on intervention strategies, showcasing efficacy of digital devices in enhancing outcomes in depression and clinic appointments. Implementation studies indicated favorable acceptance by both clients and healthcare practitioners. Conclusion: Digital technology seems acceptable to Nigerian patients and clinicians. Policies to operationalise provision of digital healthcare services will have positive impact in addressing unmet mental health needs. Finally, the quality of the evidence from majority of studies has to be enhanced, and additional studies are required to uncover gaps in some regions of the country. Contribution: This research demonstrates that, despite some drawbacks, digital methods of providing mental healthcare are practical in Nigeria.

Inequity in access to digital public primary healthcare in Sweden: a cross-sectional study of the effects of urbanicity and socioeconomic status on utilization.

BACKGROUND: Social and geographical inequity in access to primary healthcare is an ongoing concern in Sweden. Digital care can potentially decrease geographical inequity. This study aimed to evaluate how urbanicity affects the utilization of a public digital primary healthcare service - PHC Online. METHODS: We performed an ecological cross-sectional study of 4,482 PHC Online visits grouped by 83 public primary healthcare centers. Multiple linear regression analysis was performed with PHC Online visits per 1,000 registered patients as the dependent variable and urbanicity (municipalities grouped by number of inhabitants), socioeconomic status (Care Need Index), and morbidity (Adjusted Clinical Groups) per primary healthcare center as independent variables. RESULTS: Utilization of PHC Online was more common among those of a younger age (median 32 years) and among women (65%). Urbanicity did not affect utilization. Lower socioeconomic status and higher morbidity had negative effects on utilization (B -3.289, p = 0.001, B -7.728, p = 0.045). CONCLUSIONS: Geographical differences based on urbanicity do not seem to affect the utilization of PHC Online. Further studies are needed to clarify a possible association to geographical barriers in access to primary healthcare, specifically accounting for factors associated with urbanicity and distance to physical clinics, and how age and sex affect such an association. Lower utilization of PHC Online in low socioeconomic status and high morbidity populations raises questions on the effect of digital primary care on equitable access to primary healthcare.