Healthcare Innovation Research Articles

Suggesting a holistic framework for understanding healthcare services leadership competence – a critical interpretive synthesis

PurposeHealthcare providers are under pressure due to increasing and more complex demands for services. Increased pressure on budgets and human resources adds to an ever-growing problem set. Competent leaders are in demand to ensure effective and well-performing healthcare organisations that deliver balanced results and high-quality services. Researchers have made significant efforts to identify and define determining competencies for healthcare leadership. Broad terms such as competence are, however, inherently at risk of becoming too generic to add analytical value. The purpose of this study is to suggest a holistic framework for understanding healthcare leadership competence, that can be crucial for operationalising important healthcare leadership competencies for researchers, decision-makers as well as practitioners.Design/methodology/approachIn the present study, a critical interpretive synthesis (CIS) was conducted to analyse competency descriptions for healthcare leaders. The descriptions were retrieved from peer reviewed empirical studies published between 2010 and 2022 that aimed to identify healthcare services leadership competencies. Grounded theory was utilised to code the data and inductively develop new categories of healthcare leadership competencies. The categorisation was then analysed to suggest a holistic framework for healthcare leadership competence.FindingsForty-one papers were included in the review. Coding and analysing the competence descriptions resulted in 12 healthcare leadership competence categories: (1) character, (2) interpersonal relations, (3) leadership, (4) professionalism, (5) soft HRM, (6) management, (7) organisational knowledge, (8) technology, (9) knowledge of the healthcare environment, (10) change and innovation, (11) knowledge transformation and (12) boundary spanning. Based on this result, a holistic framework for understanding and analysing healthcare services leadership competencies was suggested. This framework suggests that the 12 categories of healthcare leadership competencies include a range of knowledge, skills and abilities that can be understood across the dimension personal – and technical, and organisational internal and – external competencies.Research limitations/implicationsThis literature review was conducted with the results of searching only two electronic databases. Because of this, there is a chance that there exist empirical studies that could have added to the development of the competence categories or could have contradicted some of the descriptions used in this analysis that were assessed as quite harmonised. A CIS also opens for a broader search, including the grey literature, books, policy documents and so on, but this study was limited to peer-reviewed empirical studies. This limitation could also have affected the result, as complex phenomenon such as competence might have been disclosed in greater details in, for example, books.Practical implicationsThe holistic framework for healthcare leadership competences offers a common understanding of a “fuzzy” concept such as competence and can be used to identify specific competency needs in healthcare organisations, to develop strategic competency plans and educational programmes for healthcare leaders.Originality/valueThis study reveals a lack of consensus regarding the use and understanding of the concept of competence, and that key competencies addressed in the included papers are described vastly different in terms of what knowledge, skills and abilities they entail. This challenges the operationalisation of healthcare services leadership competencies. The proposed framework for healthcare services leadership competencies offers a common understanding of work-related competencies and a possibility to analyse key leadership competencies based on a holistic framework.

Transforming Healthcare in Saudi Arabia: A Comprehensive Evaluation of Vision 2030’s Impact

This comprehensive rapid review meticulously evaluates the transformative influence of Vision 2030 on the healthcare sector in Saudi Arabia. Vision 2030, with its broad scope, targets an extensive overhaul of healthcare through infrastructure enhancement, digital health adoption, workforce empowerment, innovative public health initiatives, and advancements in quality of care and patient safety. By employing a rigorous analytical approach, this review synthesizes a broad spectrum of data highlighting Saudi Arabia’s significant progress toward establishing an accessible, efficient, and superior healthcare system. It delves into the kingdom’s alignment with global healthcare trends and its distinctive contributions, notably in digital health and public health, illustrating a proactive stance on future healthcare challenges. The analysis rigorously explores Vision 2030’s ambitious objectives and the concrete outcomes achieved, providing deep insights into the evolving healthcare landscape in Saudi Arabia. Furthermore, it assesses the global ramifications of these reformative efforts, emphasizing the pivotal themes of innovation, equity, and excellence as the foundation for future healthcare advancements. This review not only sheds light on Vision 2030’s extensive impact on Saudi healthcare but also positions the kingdom as an exemplar of healthcare innovation and reform on the global stage, offering valuable lessons for healthcare policy and practice around the world.

Public Health Outreach in Impoverished Areas of Cambodia: Addressing the Issues Related to Prescription Practices

During a two-week public health internship organized by Projects Abroad in impoverished areas in Cambodia, the authors participated in health check-ups and outreach activities. We identified issues such as polypharmacy and medication misuse. These problems stem from symptom-based prescriptions without considering individual patient conditions due to limited diagnostic equipments and medications. Our solution involved suggesting a documentation akin to Japan's prescription record books, and Drug Information Leaflets (DILs). Prescription record books would enable patients to record the medications they purchased at the pharmacy, so that physicians would know what medications patients are taking during their health checkups, and thus prevent polypharmacy. In addition, the DILs included medication details and illustrations, considering the low literacy rates in the areas. We emphasized the need for sustained non-communicable diseases (NCDs) treatment and the potential of external perspectives to introduce innovative healthcare approaches and improvements within local communities.

Secondary Use of Health Data for Medical AI: A Cross-Regional Examination of Taiwan and the EU

This paper conducts a comparative analysis of data governance mechanisms concerning the secondary use of health data in Taiwan and the European Union (EU). Both regions have adopted distinctive approaches and regulations for utilizing health data beyond primary care, encompassing areas such as medical research and healthcare system enhancement. Through an examination of these models, this study seeks to elucidate the strategies, frameworks, and legal structures employed by Taiwan and the EU to strike a delicate balance between the imperative of data-driven healthcare innovation and the safeguarding of individual privacy rights. This paper examines and compares several key aspects of the secondary use of health data in Taiwan and the EU. These aspects include data governance frameworks, legal and regulatory frameworks, data access and sharing mechanisms, and privacy and security considerations. This comparative exploration offers invaluable insights into the evolving global landscape of health data governance. It provides a deeper understanding of the strategies implemented by these regions to harness the potential of health data while upholding the ethical and legal considerations surrounding its secondary use. The findings aim to inform best practices for responsible and effective health data utilization, particularly in the context of medical AI applications.

Transformative Wearables: How AI and ML are Shaping Healthcare Innovations

Transformative Wearables: How AI and ML are Shaping Healthcare Innovations

Innovation in Healthcare Through Information Technologies: A Review

The application of innovative information technologies in healthcare can definitely subside the present limitations of the healthcare industry through better affability and accessibility. It encompasses the use of artificial intelligence, big data, biomedical research including drug invention, medical education, innovative/robotic surgical technology, cutting-edge equipment, telemedicine, virtual consultation, online supportive platforms, etc. The present review is an attempt to identify and analyse the impact of these innovative information technologies and explore the potential scope of improvement in the Indian healthcare system. The database search was performed in Scopus, Web of Science, PubMed, ProQuest, Google Scholar and Wiley Online Library. Initially, 319 articles related to innovative digital healthcare technologies have been sourced. However, 105 articles were taken into consideration for the review due to various exclusion criteria. Through an extensive review of previously published articles, the present study concludes that undoubtedly information technologies and their applications aid providers reduce inefficiencies, increasing quality, increasing access, removing human errors, reducing costs and making diagnosis, treatment and medicine more personalised for patients. It has really improved the quality, quick and convenient healthcare system.

Developing a hybrid feature selection method to detect botnet attacks in IoT devices

The Internet of Things, or IoT, is an important technology applied in various applications such as smart homes and innovative healthcare. Due to its architecture, IoT-based devices suffer from various security challenges, most commonly, botnet attacks. This article aims to develop a hybrid feature selection method to find the most influential features based on three feature selection methods, correlation, generalized normal distribution optimization, and lasso, to detect botnet attacks in IoT devices. The UNSW-NB15 dataset is used to assess the proposed system. Several classification models including decision tree (DT), random forest (RF), k-nearest neighbors (KNN), adaptive boosting (AdaBoost), and bagging are utilized for the classification purpose. The proposed system was evaluated using several performance metrics. The results showed the correlation feature selection method had the most accurate botnet attack detection rate. RF also outperformed other models with a 95.11% detection rate in binary classification and 83.96% in multi-classification. On the other hand, results showed that the proposed hybrid method outperformed the feature selection methods with an increase of about 3% in both classifications. The AdaBoost model achieved an accuracy of 99.28% with binary classification by using 18 features, and the RF model achieved an accuracy of 86.62% with multi-classification by using 22 features. The robustness and efficacy of the proposed approach were demonstrated by comparing the study's results with several other studies that have used the same dataset. The results of the study can be implemented in real applications to detect network interference of a dynamic nature in real-time and assist intrusion detection systems (IDS) in addressing these attacks.

Data-Driven Decision Support Systems for Drug Discovery and Development: A Case Study in Pharmaceutical Management

This paper covers the use and influence of data-driven decision support systems (DSS) on drug management, particularly in the areas of drug exploration and production. The study, which employed a mixed-methods approach, involving literature review, qualitative interviews, quantitative assessments, and case study analysis, reveals the AI, machine learning and big data analytics ability to drive drug discovery and development processes revolution in the pharmaceutical industry. The study shows that handling of DSS allows sound decision making, consequently resulting in improved efficiency, decreased expenses and better innovation throughout the drug development process. Areas like data integration, algorithm robustness, and regulation are identified as the major issues, which offers an insight into the importance of these areas of concern in the effective application of a data-driven approach in pharmaceutical management. Such contrast with the like works underlines the role of our findings as an essential link in the AI-driven healthcare innovations chain. The research provides a foundation for further improving the state of knowledge and understanding of DSS in drug management, guiding future research aiming at expanding conceptual frameworks and designing practical implementations.

Fostering innovation and sustainable thinking in surgery: an evaluation of a surgical hackathon.

Surgery represents a major source of carbon emissions, with numerous initiatives promoting more sustainable practices. Healthcare innovation and the development of a digitally capable workforce are fundamental in leveraging technologies to tackle challenges, including sustainability in surgery. A surgical hackathon was organised with three major themes: (1) how to make surgery greener, (2) the future of plastic surgery in 10 years, and (3) improving healthcare outcomes using machine learning. Lectures were given on sustainability and innovation using the problem, innovation, market size, strategy and team (PIMST) framework to support their presentations, as well as technological support to translate ideas into simulations or minimum viable products. Pre- and post-event questionnaires were circulated to participants. Most attendees were medical students (65%), although doctors and engineers were also present. There was a significant increase in delegates' confidence in approaching innovation in surgery (+20%, p < 0.001). Reducing waste packaging (70%), promoting recyclable material usage (56%) and the social media dimension of public perceptions towards plastic surgery (40%) were reported as the most important issues arising from the hackathon. The top three prizes went to initiatives promoting an artificial intelligence-enhanced operative pathway, instrument sterilisation and an educational platform to teach students research and innovation skills. Surgical hackathons can result in significant improvements in confidence in approaching innovation, as well as raising awareness of important healthcare challenges. Future innovation events may build on this to continue to empower the future workforce to leverage technologies to tackle healthcare challenges such as sustainability.

Adopting, implementing and assimilating coproduced health and social care innovations involving structurally vulnerable populations: findings from a longitudinal, multiple case study design in Canada, Scotland and Sweden

BackgroundInnovations in coproduction are shaping public service reform in diverse contexts around the world. Although many innovations are local, others have expanded and evolved over time. We know very little, however, about the process of implementation and evolution of coproduction. The purpose of this study was to explore the adoption, implementation and assimilation of three approaches to the coproduction of public services with structurally vulnerable groups.MethodsWe conducted a 4 year longitudinal multiple case study (2019–2023) of three coproduced public service innovations involving vulnerable populations: ESTHER in Jönköping Region, Sweden involving people with multiple complex needs (Case 1); Making Recovery Real in Dundee, Scotland with people who have serious mental illness (Case 2); and Learning Centres in Manitoba, Canada (Case 3), also involving people with serious mental illness. Data sources included 14 interviews with strategic decision-makers and a document analysis to understand the history and contextual factors relating to each case. Three frameworks informed the case study protocol, semi-structured interview guides, data extraction, deductive coding and analysis: the Consolidated Framework for Implementation Research, the Diffusion of Innovation model and Lozeau’s Compatibility Gaps to understand assimilation.ResultsThe adoption of coproduction involving structurally vulnerable populations was a notable evolution of existing improvement efforts in Cases 1 and 3, while impetus by an external change agency, existing collaborative efforts among community organizations, and the opportunity to inform a new municipal mental health policy sparked adoption in Case 2. In all cases, coproduced innovation centred around a central philosophy that valued lived experience on an equal basis with professional knowledge in coproduction processes. This philosophical orientation offered flexibility and adaptability to local contexts, thereby facilitating implementation when compared with more defined programming. According to the informants, efforts to avoid co-optation risks were successful, resulting in the assimilation of new mindsets and coproduction processes, with examples of how this had led to transformative change.ConclusionsIn exploring innovations in coproduction with structurally vulnerable groups, our findings suggest several additional considerations when applying existing theoretical frameworks. These include the philosophical nature of the innovation, the need to study the evolution of the innovation itself as it emerges over time, greater attention to partnered processes as disruptors to existing power structures and an emphasis on driving transformational change in organizational cultures.

Evaluation of Psychiatric High and Intensive Care (EPHIC-study): monitoring innovative care from a value-based approach

IntroductionSystematic monitoring and evaluation of innovative healthcare programs are essential to develop sustainable solutions to health needs in the population (Porter &amp; Teisberg, 2006). Development of Psychiatric High and Intensive Care Units (HIC’s) in Belgium, following the Dutch Model (van Mierlo et al., 2013), is an innovative model for patients with acute and severe psychiatric illness, resulting in potential danger. HIC aims to provide intensive, need-adapted care with interventions that reduce (perceived) coercion, focusing on participative processes and continuity of care.Objectives(1) What are the clinical characteristics of admitted patients? (2) How does clinical symptomatology evolve during admission? (3) How do patients, relatives and caregivers experience the process of care and recovery? (4) What is the role of HIC’s in the reformed mental health care?MethodsThis is an explorative, hypothesis-generating study, using a mixed-method approach, consisting of qualitative and quantitative methods against a value-based framework. Data collection lasted 18 months in the first 9 HIC’s in Belgium. Results are based on validated questionnaires completed by adult patients and their HIC caregivers at admission and discharge (N=472).ResultsWe provide the first, preliminary results. Suicidality, psychotic and substance-related symptoms are the most important primary symptoms. Almost 70% have 2 or more symptoms, with psychiatric comorbidity of 50%. Substance-related- and psychotic disorders are the two most common diagnoses, followed by personality disorder cluster B and depressive disorder. 83% have been in residential care in the past, of whom 87% twice or more. The median age is 36 years, but the median age of onset of mental disorders is 21 years, which equals to 15 years in mental disorder progress and comorbidity development. Over 50% meet the criteria for Severe Mental Illness and 56% are involuntary admitted. There is a high degree of unmet needs: no outpatient care is provided for one out of five prior to admission and there is a low follow-up by mobile teams prior to and after admission (around 12% each). We found significant improvements after an average stay of 22 days for aggression, suicidality and crisis (respectively decrease of 68%, 25% and 9%); readiness to change and motivation for treatment (respectively increase of 5% and 14%) The Client Satisfaction Questionnaire scores range from 1 to 4, with an average score 3.15 out of 4.ConclusionsBased on these preliminary results we can conclude that aggression, suicidality, crisis, readiness to change and motivation for treatment all improve significantly after a short stay of 3 weeks. Despite a vulnerable, severely distressed population, patients are generally satisfied with received care. There is a high degree of unmet needs: insufficient provided outpatient care and low follow up by mobile teams.Disclosure of InterestNone Declared

Online Ambulance Booking System

Abstract: The Online Ambulance Booking Service is a vital healthcare innovation designed to address the critical need for efficient and timely emergency medical transportation. In the modern world, access to medical care is of utmost importance, and this service aims to bridge the gap between patients and emergency medical services. This abstract provides an overview of the key features and functionalities of the system. The Online Ambulance Booking Service leverages technology to create a userfriendly platform that enables individuals to request ambulance services with ease. Users can access the service through a web application or mobile app, making it accessible to a wide range of people. The Online Ambulance Booking Service is a solution that enhances emergency medical response, saving valuable time in critical situations. It fosters a sense of security and reliability in healthcare services, benefiting both the general public and healthcare providers. This abstract highlight the importance of such a service in the healthcare industry, emphasizing its role in improving patient outcomes and reducing response times during emergencies.

Foresight in Health Using Machine Learning

Abstract: Our aim to "Foresight in Health Using Machine Learning" is an innovative healthcare analytics project that harnesses historical data, advanced analytics, and machine learning techniques to predict significant human diseases. This project employs a variety of machine learning algorithms, including Decision Tree, Random Forest, Logistic Regression, and Support Vector Machine, to forecast diseases such as Diabetics, Breast cancer, Skin diseases, Liver disease and Heart disease based on user-provided data.The system features a user-friendly interface developed with the Flask framework, guiding end users to input essential details for disease prediction. Once the prediction is generated, immediate output is displayed to the end user in our web, facilitating proactive preventive measures to mitigate the risk of serious illnesses. "Foresight in Health" represents a groundbreaking endeavor aimed at leveraging data-driven insights to enhance healthcare outcomes and promote early intervention in disease management

Business model innovation in healthcare: A theoretical review of entrepreneurial strategies in the medical sector

This theoretical review explores the critical role of business model innovation in the healthcare industry, focusing on entrepreneurial strategies within the medical sector. With the constant evolution of healthcare needs, technologies, and regulations, traditional models are becoming increasingly insufficient to meet the demands of patients, providers, and other stakeholders. Business model innovation offers a pathway for organizations to adapt, thrive, and deliver value in this dynamic landscape. Drawing upon existing literature and case studies, this paper examines the fundamental concepts of business model innovation and its application within healthcare. It explores various entrepreneurial strategies, including opportunity identification, collaboration, technology integration, and patient-centered approaches, highlighting their impact on reshaping the healthcare ecosystem. Furthermore, the theoretical framework delineates key components of successful business model innovation, such as value proposition design, revenue model development, infrastructure optimization, and customer segmentation. Through analysis of real-world examples and challenges, this review elucidates the opportunities and barriers associated with business model innovation in healthcare. It underscores the importance of fostering a culture of innovation, promoting interdisciplinary collaboration, and addressing regulatory complexities to drive sustainable change. Additionally, it outlines future directions for research, implications for healthcare practitioners and policymakers, and the imperative for continuous adaptation and improvement. Ultimately, this review contributes to a deeper understanding of how entrepreneurial strategies can catalyze business model innovation in healthcare, paving the way for enhanced quality, accessibility, and affordability of healthcare services in the digital age.

Using the consolidated Framework for Implementation Research to integrate innovation recipients’ perspectives into the implementation of a digital version of the spinal cord injury health maintenance tool: a qualitative analysis

BackgroundDespite advances in managing secondary health complications after spinal cord injury (SCI), challenges remain in developing targeted community health strategies. In response, the SCI Health Maintenance Tool (SCI-HMT) was developed between 2018 and 2023 in NSW, Australia to support people with SCI and their general practitioners (GPs) to promote better community self-management. Successful implementation of innovations such as the SCI-HMT are determined by a range of contextual factors, including the perspectives of the innovation recipients for whom the innovation is intended to benefit, who are rarely included in the implementation process. During the digitizing of the booklet version of the SCI-HMT into a website and App, we used the Consolidated Framework for Implementation Research (CFIR) as a tool to guide collection and analysis of qualitative data from a range of innovation recipients to promote equity and to inform actionable findings designed to improve the implementation of the SCI-HMT.MethodsData from twenty-three innovation recipients in the development phase of the SCI-HMT were coded to the five CFIR domains to inform a semi-structured interview guide. This interview guide was used to prospectively explore the barriers and facilitators to planned implementation of the digital SCI-HMT with six health professionals and four people with SCI. A team including researchers and innovation recipients then interpreted these data to produce a reflective statement matched to each domain. Each reflective statement prefaced an actionable finding, defined as alterations that can be made to a program to improve its adoption into practice.ResultsFive reflective statements synthesizing all participant data and linked to an actionable finding to improve the implementation plan were created. Using the CFIR to guide our research emphasized how partnership is the key theme connecting all implementation facilitators, for example ensuring that the tone, scope, content and presentation of the SCI-HMT balanced the needs of innovation recipients alongside the provision of evidence-based clinical information.ConclusionsUnderstanding recipient perspectives is an essential contextual factor to consider when developing implementation strategies for healthcare innovations. The revised CFIR provided an effective, systematic method to understand, integrate and value recipient perspectives in the development of an implementation strategy for the SCI-HMT.Trial registrationN/A.

Project CHARIOT: study protocol for a hybrid type 1 effectiveness-implementation study of comprehensive tele-harm reduction for engagement of people who inject drugs in HIV prevention services

BackgroundPeople who inject drugs (PWID) remain a high priority population under the federal Ending the HIV Epidemic initiative with 11% of new HIV infections attributable to injection drug use. There is a critical need for innovative, efficacious, scalable, and community-driven models of healthcare in non-stigmatizing settings for PWID. We seek to test a Comprehensive-TeleHarm Reduction (C-THR) intervention for HIV prevention services delivered via a syringe services program (SSP).MethodsThe CHARIOT trial is a hybrid type I effectiveness-implementation study using a parallel two-arm randomized controlled trial design. Participants (i.e., PWID; n = 350) will be recruited from a syringe services program (SSP) in Miami, Florida. Participants will be randomized to receive either C-THR or non-SSP clinic referral and patient navigation. The objectives are: (1) to determine if the C-THR intervention increases engagement in HIV prevention (i.e., HIV pre-exposure prophylaxis; PrEP or medications for opioid use disorder; MOUD) compared to non-SSP clinic referral and patient navigation, (2) to examine the long-term effectiveness and cost-effectiveness of the C-THR intervention, and (3) to assess the barriers and facilitators to implementation and sustainment of the C-THR intervention. The co-primary outcomes are PrEP or MOUD engagement across follow-up at 3, 6, 9 and 12 months. For PrEP, engagement is confirmed by tenofovir on dried blood spot or cabotegravir injection within the previous 8 weeks. For MOUD, engagement is defined as screening positive for norbuprenorphine or methadone on urine drug screen; or naltrexone or buprenorphine injection within the previous 4 weeks. Secondary outcomes include PrEP adherence, engagement in HCV treatment and sustained virologic response, and treatment of sexually transmitted infections. The short and long term cost-effectiveness analyses and mixed-methods implementation evaluation will provide compelling data on the sustainability and possible impact of C-THR on comprehensive HIV prevention delivered via SSPs.DiscussionThe CHARIOT trial will be the first to our knowledge to test the efficacy of an innovative, peer-led telehealth intervention with PWID at risk for HIV delivered via an SSP. This innovative healthcare model seeks to transform the way PWID access care by bypassing the traditional healthcare system, reducing multi-level barriers to care, and meeting PWID where they are.Trial Registration: ClinicalTrials.gov NCT05897099. Trial registry name: Comprehensive HIV and Harm Prevention Via Telehealth (CHARIOT). Registration date: 06/12/2023.

Patient Characteristics and Telemedicine Use in the US, 2022

Telemedicine use was common during the COVID-19 pandemic, expanding many patients' approaches to accessing health care. Of concern is whether telemedicine access was poorer among higher-needs and disadvantaged populations. To assess patient characteristics associated with telemedicine use and telemedicine mode and describe telemedicine visit experiences by telemedicine mode. This cross-sectional study included data from the 2022 Health Information National Trends Survey and included US adults with a health care visit. Data were analyzed from May to September 2023. Patient characteristics. Any telemedicine visits vs in-person visits only; telemedicine mode (video vs audio-only). Multivariable logistic models assessed patient characteristics associated with telemedicine visits and mode. Bivariate analyses compared telemedicine experiences by mode. The study included 5437 adult patients (mean [SE] age, 49.4 [0.23] years; 3136 females [53.4%]; 1928 males [46.6%]). In 2022, 2384 patients (43%) had a telemedicine visit; 1565 (70%) had a video visit while 819 (30%) had an audio-only visit. In multivariable models, older age (≥75 years: adjusted odds ratio [aOR], 0.63; 95% CI, 0.42-0.94), no internet use (aOR, 0.62; 95% CI, 0.48-0.81), and living in the Midwest (aOR, 0.50; 95% CI, 0.35-0.70) were negatively associated with having telemedicine visits. Female sex (aOR, 1.43; 95% CI, 1.12-1.83), having chronic conditions (aOR, 2.13; 95% CI, 1.66-2.73), and multiple health care visits (2-4 visits: aOR, 1.77; 95% CI, 1.23-2.54; ≥5 visits: aOR, 3.29; 95% CI, 2.20-4.92) were positively associated. Among individuals who used telemedicine, older age (65-74 years: aOR, 2.13; 95% CI, 1.09-4.14; ≥75 years: aOR, 3.58; 95% CI, 1.60-8.00), no health insurance (aOR, 2.84; 95% CI, 1.42-5.67), and no internet use (aOR, 2.11; 95% CI, 1.18-3.78) were positively associated with having audio-only visits. We observed no significant differences in telemedicine use or mode by education, race and ethnicity, or income. Patients' experiences using telemedicine were generally similar for video and audio-only except more individuals who used audio-only had privacy concerns (20% vs 12%, P = .02). In this cross-sectional study of adults with health care visits, many patients, including those with the greatest care needs, chose telemedicine even after in-person visits were available. These findings support continuing this care delivery approach as an option valued by patients. Differences were not observed by most common measures of socioeconomic status. Continued monitoring of telemedicine use is needed to ensure equitable access to health care innovations.

Role of Artificial Intelligence in Health care System

The Indian healthcare scenario presents a spectrum of contrasting landscapes. In all, 400 million individuals had no access to any form of basic healthcare while two billion people do not have access to required medications. Therefore, more than one-fourth of the world population has unmet health needs. This leaves the global community with the challenge of how to support a significant number of the world’s populace still lacking in access to basic healthcare facilities. AI has been a disruptive healthcare innovation. With its sophisticated algorithms and several applications, AI has assisted doctors and medical professionals in the domains of health information systems, geocoding health data, epidemic and syndromic surveillance, predictive modelling and decision support, and medical imaging. Artificial intelligence (AI) rapidly dominates the health service system. It removes the manual health system into automatic, in which humans conduct the routine works/tasks in medical practice to the management of patients and medical resources. Drug development is a famously costly procedure. Machine Learning can improve the efficiency of many of the analytical techniques used in drug development. In terms of practical implications, this paper aims to create a fruitful discussion with healthcare professionals and administrative staff and the role of artificial intelligence in healthcare system. Furthermore, this investigation offers a broad comprehension of bibliometric variables of AI techniques in healthcare.

From value creation to value capture practices in healthcare innovation collaborations

ABSTRACT Healthcare is a challenging field for innovation: it is characterised by complex regulation and needs for enhanced collaboration between public and private actors who differ in terms of their motivations, innovation needs, and institutional logics. These complexities relate to multiple ways of approaching value capture in terms of securing financial or non-financial benefits from value creation in innovation collaboration. At the same time, existing scholarly knowledge offers limited help to understand or manage value capture practices in public-private collaborations. Exploring the specific practices of value capture is needed not only to understand how the returns from shared value creation activities are secured but also to understand why public and private organisations should invest their limited resources in collaboration in the first place. Applying insights from the innovation management and industrial marketing literatures, the present case study explores value capture practices in public-private collaborations for healthcare technological innovation. Empirically, it draws from twelve collaborations between a public hospital and private firms providing insight into both private firms and a public hospital organization. As a result, the study suggests a categorisation of value capture practices emerging in innovation collaboration in healthcare, thereby explicating how such practices incorporate approaches of both public and private sector participants.

Exploring Digital Health Horizons: A Narrative Review of E-Health Innovations in Poland, Spain, Romania and Estonia.

E-health offers new opportunities for self-management, health and social care and access to health information. Over the last decade, the use of e-health solutions by patients, healthcare providers, professionals and citizens has increased significantly. This article provides an overview of e-health innovations in Poland, Spain, Romania and Estonia, focussing on the digital development of healthcare services. It outlines the concept of e-health and the innovative solutions the countries listed have introduced in this area. They all face challenges such as the cost of implementing new technologies, data access and the security of patient data. As a result, there is a constant need for coordinated collaboration, legislation and clear guidelines for the use of technology in healthcare. The lessons learnt from these countries are helping to shape the digital future of healthcare in Europe. In Poland, the Ministry of Health oversees the eHealth Centre, which has made remarkable progress in the field of eHealth services such as the Internet patient account, electronic prescriptions and electronic referrals. The biggest challenges include financing innovation and improving digital skills. Poland has also recently introduced the no-fault system as an alternative compensation system for medical errors, modelled on similar systems in Denmark and Sweden. Technological progress is driving the transformation of the Spanish healthcare system, which is particularly evident in the area of telemedicine and innovative healthcare systems. The Spanish Digital Health Strategy lines up with broader national initiatives. Despite challenges such as underfunding, Romania has introduced digital healthcare with the Health Electronic Record since 2014. As an absolute pioneer in the digitalisation of healthcare in Europe, Estonia is proud of its achievements in the digitalisation of healthcare data and services. The Estonian eHealth Foundation and the nationwide health information system are an example of seamless integration and set a benchmark for comprehensive digital healthcare.