Connected healthcare: Improving patient care using digital health technologies

Tailor-Made Doses of Pharmaceuticals by Tunable Modular Design: A Case Study on Tapering Antidepressant Medication

An abrupt cessation of antidepressant medication can be challenging due to the appearance of withdrawal symptoms. A slow hyperbolic tapering of an antidepressant, such as citalopram hydrobromide (CHB), can mitigate the withdrawal syndrome. However, there are no viable dosage forms on the market to implement the tapering scheme. A solution using a tunable modular design (TMD) approach to produce flexible and accurate doses of CHB is proposed. This design consists of two parts: 1) a module with a fixed amount of preloaded CHB in a freeze-dried polymer matrix, and 2) fine-tuning the CHB dose by inkjet printing. A noncontact food-grade printer, used for the first time for printing pharmaceuticals, is modified to allow for accurate printing of the highly concentrated CHB ink on the porous CHB-free or CHB-preloaded modules. The produced modules with submilligram precision are bench-marked with commercially available CHB tablets that are manually divided. The TMD covers the entire range of doses needed for the tapering (0.5-23.8 mg). The greatest variance is 13% and 88% when comparing the TMD and self-tapering, respectively. Self-tapering is proven inaccurate and showcases the need for the TMD to make available accurate and personalized doses to wean off treatment with CHB.

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.

Towards a common European ethical and legal framework for conducting clinical research: the GATEKEEPER experience

This paper examines the ethical and legal challenges encountered during the GATEKEEPER Project and how these challenges informed the development of a comprehensive framework for future Large-Scale Pilot (LSP) projects. GATEKEEPER is a LSP Project with 48 partners conducting 30 implementation studies across Europe with 50,000 target participants grouped into 9 Reference Use Cases. The project underscored the complexity of obtaining ethical approval across various jurisdictions with divergent regulations and procedures. Through a detailed analysis of the issues faced and the strategies employed to navigate these challenges, this study proposes an ethical and legal framework. This framework, derived from a comparative analysis of ethical application forms and regulations, aims to streamline the ethical approval process for future LSP research projects. By addressing the hurdles encountered in GATEKEEPER, the proposed framework offers a roadmap for more efficient and effective project management, ensuring smoother implementation of similar projects in the future.

Comparison of Self-Tracking Health Practices, eHealth Literacy, and Subjective Well-Being Between College Students With and Without Disabilities: Cross-Sectional Survey

BACKGROUND

College students with disabilities need to transition from pediatric-centered care to adult care. However, they may become overwhelmed by multiple responsibilities, such as academic activities, peer relationships, career preparation, job seeking, independent living, as well as managing their health and promoting healthy behaviors.

OBJECTIVE

As the use of smartphones and wearable devices for collecting personal health data becomes popular, this study aimed to compare the characteristics of self-tracking health practices between college students with disabilities and their counterparts. In addition, this study examined the relationships between disability status, self-tracking health practices, eHealth literacy, and subjective well-being among college students.

METHODS

The web-based questionnaire was designed using Qualtrics for the cross-sectional online survey. The survey data were collected from February 2023 to April 2023 and included responses from 702 participants.

RESULTS

More than 80% (563/702, 80.2%) of the respondents participated voluntarily in self-tracking health practices. College students with disabilities (n=83) showed significantly lower levels of eHealth literacy and subjective well-being compared with college students without disabilities (n=619). The group with disabilities reported significantly lower satisfaction (t411=-5.97, P<.001) and perceived efficacy (t411=-4.85, P<.001) when using smartphone health apps and wearable devices. Finally, the study identified a significant correlation between subjective well-being in college students and disability status (β=3.81, P<.001), self-tracking health practices (β=2.22, P=.03), and eHealth literacy (β=24.29, P<.001).

CONCLUSIONS

Given the significant relationships among disability status, self-tracking health practices, eHealth literacy, and subjective well-being in college students, it is recommended to examine their ability to leverage digital technology for self-care. Offering learning opportunities to enhance eHealth literacy and self-tracking health strategies within campus environments could be a strategic approach to improve the quality of life and well-being of college students.

Risks and benefits associated with the primary functions of artificial intelligence powered autoinjectors

Objectives

This research aims to present and assess the Primary Functions of autoinjectors introduced in ISO 11608-1:2022. Investigate the risks in current autoinjector technology, identify and assess risks and benefits associated with Artificial Intelligence (AI) powered autoinjectors, and propose a framework for mitigating these risks. ISO 11608-1:2022 is a standard that specifies requirements and test methods for needle-based injection systems intended to deliver drugs, focusing on design and function to ensure patient safety and product effectiveness. 'KZH' is an FDA product code used to classify autoinjectors, for regulatory purposes, ensuring they meet defined safety and efficacy standards before being marketed.

Method

A comprehensive analysis of autoinjectors problems is conducted using data from the United States Food and Drug Administration (FDA) database. This database records medical device reporting events, including those related to autoinjectors, reported by various sources. The analysis focuses on events associated with the product code KZH, covering data from January 1, 2008, to September 30, 2023. This research employs statistical frequency analysis and incorporates pertinent the FDA, United Kingdom, European Commission regulations, and ISO standards.

Results

500 medical device reporting events are assessed for autoinjectors under the KZH code. Ultimately, 188 of these events are confirmed to be associated with autoinjectors, all 500 medical devices were seen to lack AI capabilities. An analysis of these events for traditional mechanical autoinjectors revealed a predominant occurrence of malfunctions (72%) and injuries (26%) among event types. Device problems, such as breakage, defects, jams, and others, accounted for 45% of incidents, while 10% are attributed to patient problems, particularly missed and underdoses.

Conclusion

Traditional autoinjectors are designed to assist patients in medication administration, underscoring the need for quality control, reliability, and design enhancements. AI autoinjectors, sharing this goal, bring additional cybersecurity and software risks, requiring a comprehensive risk management framework that includes standards, tools, training, and ongoing monitoring. The integration of AI promises to improve functionality, enable real-time monitoring, and facilitate remote clinical trials, timely interventions, and tailored medical treatments.

The Impact of Digital Self-Monitoring of Weight on Improving Diabetes Clinical Outcomes: Quasi-Randomized Study

BACKGROUND

The management of type 2 diabetes (T2D) and obesity, particularly in the context of self-monitoring, remains a critical challenge in health care. As nearly 80% to 90% of patients with T2D have overweight or obesity, there is a compelling need for interventions that can effectively manage both conditions simultaneously. One of the goals in managing chronic conditions is to increase awareness and generate behavioral change to improve outcomes in diabetes and related comorbidities, such as overweight or obesity. There is a lack of real-life evidence to test the impact of self-monitoring of weight on glycemic outcomes and its underlying mechanisms.

OBJECTIVE

This study aims to assess the efficacy of digital self-monitoring of weight on blood glucose (BG) levels during diabetes management, investigating whether the weight changes may drive glucose fluctuations.

METHODS

In this retrospective, real-world quasi-randomized study, 50% of the individuals who regularly used the weight monitoring (WM) feature were propensity score matched with 50% of the users who did not use the weight monitoring feature (NWM) based on demographic and clinical characteristics. All the patients were diagnosed with T2D and tracked their BG levels. We analyzed monthly aggregated data 6 months before and after starting their weight monitoring. A piecewise mixed model was used for analyzing the time trajectories of BG and weight as well as exploring the disaggregation effect of between- and within-patient lagged effects of weight on BG.

RESULTS

The WM group exhibited a significant reduction in BG levels post intervention (P<.001), whereas the nonmonitoring group showed no significant changes (P=.59), and both groups showed no differences in BG pattern before the intervention (P=.59). Furthermore, the WM group achieved a meaningful decrease in BMI (P<.001). Finally, both within-patient (P<.001) and between-patient (P=.008) weight variability was positively associated with BG levels. However, 1-month lagged back BMI was not associated with BG levels (P=.36).

CONCLUSIONS

This study highlights the substantial benefits of self-monitoring of weight in managing BG levels in patients with diabetes, facilitated by a digital health platform, and advocates for the integration of digital self-monitoring tools in chronic disease management. We also provide initial evidence of testing the underlying mechanisms associated with BG management, underscoring the potential role of patient empowerment.

Innovations in pharmacovigilance studies of medicines in older people

Pharmacovigilance is defined by the World Health Organization as "the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other medicine/vaccine related problem". Pharmacovigilance studies are critical for detecting and assessing adverse events of medicines that may not have been observed in clinical trials. This activity is especially important in older people who are often excluded from clinical trials as they have multiple chronic conditions and use multiple medicines for longer durations than the clinical trials. In this narrative review we describe innovative methods in pharmacovigilance studies of medicines in older people that leverage the increasing availability of digital health technologies, electronic health records and real-world health data to identify and quantify medication related harms in older people.

3D Printing Direct Powder Extrusion in the Production of Drug Delivery Systems: State of the Art and Future Perspectives

The production of tailored, on-demand drug delivery systems has gained attention in pharmaceutical development over the last few years, thanks to the application of 3D printing technology in the pharmaceutical field. Recently, direct powder extrusion (DPE) has emerged among the extrusion-based additive manufacturing techniques. It is a one-step procedure that allows the direct processing of powdered formulations. The aim of this systematic literature review is to analyze the production of drug delivery systems using DPE. A total of 27 articles have been identified through scientific databases (Scopus, PubMed, and ScienceDirect). The main characteristics of the three types of 3D printers based on DPE have been discussed. The selection of polymers and auxiliary excipients, as well as the flowability of the powder mixture, the rheological properties of the molten material, and the printing temperatures have been identified as the main critical parameters for successful printing. A wide range of drug delivery systems with varied geometries and different drug release profiles intended for oral, buccal, parenteral, and transdermal routes have been produced. The ability of this technique to manufacture personalized, on-demand drug delivery systems has been proven. For all these reasons, its implementation in hospital settings in the near future seems promising.

Determinants of behavioral intentions to use E-Pharmacy service: Insights from TAM theory and the moderating influence of technological literacy

BACKGROUND

The growing significance of E-Pharmacy services in healthcare necessitates investigating the factors influencing users' behavioral intentions on these platforms. Comprehending these variables is imperative to maximize service provision, elevate customer satisfaction, and ultimately elevate healthcare accessibility and results.

OBJECTIVE(S)

The main goal of this study is to explore the factors that shape consumers' inclination to use E-Pharmacy services, focusing on the framework provided by the Technology Acceptance Model. Additionally, we aimed to investigate how technological literacy plays a moderating role in this context, specifically within the South African setting.

METHODS

Using a sample of 480 South African clients, the Technology Acceptance Model (TAM) and partial least squares structural equation modeling (PLS-SEM) were used to investigate the factors influencing behavioral intention to use E-Pharmacy services.

RESULTS

The findings underscore perceived usefulness, trust, performance expectancy, and social Influence as fundamental drivers influencing users' intentions to adopt E-Pharmacy systems. Additionally, the study shows that consumers' intention to use E-Pharmacy services is significantly and favorably affected by their desire to utilize such services. This suggests that individuals are more likely to act on positive intentions when they are interested in using E-Pharmacy platforms. Intriguingly, technological literacy has emerged as a moderating factor in the relationship between the intention to use and the actual behavior of utilizing E-Pharmacy platforms. This demonstrates the importance of consumers' technical knowledge and skills in bridging the intention-behavior gap and highlights the necessity of adapting treatments and instructional strategies to account for various levels of technological literacy.

CONCLUSION

This study provides valuable insights into the complex relationships between factors influencing the acceptance of E-Pharmacy services in South Africa. This knowledge can have practical implications for lawmakers, developers of E-Pharmacy platforms, and healthcare professionals who aim to enhance user acceptance and utilization.

Digital stressors and resources perceived by emergency physicians and associations to their digital stress perception, mental health, job satisfaction and work engagement

BACKGROUND

Digital technologies are increasingly being integrated into healthcare settings, including emergency departments, with the potential to improve efficiency and patient care. Although digitalisation promises many benefits, the use of digital technologies can also introduce new stressors and challenges among medical staff, which may result in the development of various negative work and health outcomes. Therefore, this study aims to identify existing digital stressors and resources among emergency physicians, examine associations with various work- and health-related parameters, and finally identify the potential need for preventive measures.

METHODS

In this quantitative cross-sectional study, an online questionnaire was used to examine the relationship between digital stressors (technostress creators), digital resources (technostress inhibitors), technostress perception as well as mental health, job satisfaction and work engagement among 204 physicians working in German emergency medicine departments. Data collection lasted from December 2022 to April 2023. Validated scales were used for the questionnaire (e.g. "Technostress"-scale and the Copenhagen Psychosocial Questionnaire (COPSOQ). Descriptive and multiple regression analyses were run to test explorative assumptions.

RESULTS

The study found medium levels of technostress perception among the participating emergency physicians as well as low levels of persisting technostress inhibitors. The queried physicians on average reported medium levels of exhaustion symptoms, high levels of work engagement and job satisfaction. Significant associations between digital stressors and work- as well as health-related outcomes were analyzed.

CONCLUSION

This study provides a preliminary assessment of the persistence of digital stressors, digital resources and technostress levels, and their potential impact on relevant health and work-related outcomes, among physicians working in German emergency departments. Understanding and mitigating these stressors is essential to promote the well-being of physicians and ensure optimal patient care. As digitisation processes will continue to increase, the need for preventive support measures in dealing with technology stressors is obvious and should be expanded accordingly in the clinics. By integrating such support into everyday hospital life, medical staff in emergency departments can better focus on patient care and mitigate potential stress factors associated with digital technologies.

Building digital patient pathways for the management and treatment of multiple sclerosis

Recent advances in the field of artificial intelligence (AI) could yield new insights into the potential causes of multiple sclerosis (MS) and factors influencing its course as the use of AI opens new possibilities regarding the interpretation and use of big data from not only a cross-sectional, but also a longitudinal perspective. For each patient with MS, there is a vast amount of multimodal data being accumulated over time. But for the application of AI and related technologies, these data need to be available in a machine-readable format and need to be collected in a standardized and structured manner. Through the use of mobile electronic devices and the internet it has also become possible to provide healthcare services from remote and collect information on a patient's state of health outside of regular check-ups on site. Against this background, we argue that the concept of pathways in healthcare now could be applied to structure the collection of information across multiple devices and stakeholders in the virtual sphere, enabling us to exploit the full potential of AI technology by e.g., building digital twins. By going digital and using pathways, we can virtually link patients and their caregivers. Stakeholders then could rely on digital pathways for evidence-based guidance in the sequence of procedures and selection of therapy options based on advanced analytics supported by AI as well as for communication and education purposes. As far as we aware of, however, pathway modelling with respect to MS management and treatment has not been thoroughly investigated yet and still needs to be discussed. In this paper, we thus present our ideas for a modular-integrative framework for the development of digital patient pathways for MS treatment.

Lifestyle management of hypertension: International Society of Hypertension position paper endorsed by the World Hypertension League and European Society of Hypertension

Hypertension, defined as persistently elevated systolic blood pressure (SBP) >140 mmHg and/or diastolic blood pressure (DBP) at least 90 mmHg (International Society of Hypertension guidelines), affects over 1.5 billion people worldwide. Hypertension is associated with increased risk of cardiovascular disease (CVD) events (e.g. coronary heart disease, heart failure and stroke) and death. An international panel of experts convened by the International Society of Hypertension College of Experts compiled lifestyle management recommendations as first-line strategy to prevent and control hypertension in adulthood. We also recommend that lifestyle changes be continued even when blood pressure-lowering medications are prescribed. Specific recommendations based on literature evidence are summarized with advice to start these measures early in life, including maintaining a healthy body weight, increased levels of different types of physical activity, healthy eating and drinking, avoidance and cessation of smoking and alcohol use, management of stress and sleep levels. We also discuss the relevance of specific approaches including consumption of sodium, potassium, sugar, fibre, coffee, tea, intermittent fasting as well as integrated strategies to implement these recommendations using, for example, behaviour change-related technologies and digital tools.

3D Printing of Dietary Products for the Management of Inborn Errors of Intermediary Metabolism in Pediatric Populations

The incidence of Inborn Error of Intermediary Metabolism (IEiM) diseases may be low, yet collectively, they impact approximately 6-10% of the global population, primarily affecting children. Precise treatment doses and strict adherence to prescribed diet and pharmacological treatment regimens are imperative to avert metabolic disturbances in patients. However, the existing dietary and pharmacological products suffer from poor palatability, posing challenges to patient adherence. Furthermore, frequent dose adjustments contingent on age and drug blood levels further complicate treatment. Semi-solid extrusion (SSE) 3D printing technology is currently under assessment as a pioneering method for crafting customized chewable dosage forms, surmounting the primary limitations prevalent in present therapies. This method offers a spectrum of advantages, including the flexibility to tailor patient-specific doses, excipients, and organoleptic properties. These elements are pivotal in ensuring the treatment's efficacy, safety, and adherence. This comprehensive review presents the current landscape of available dietary products, diagnostic methods, therapeutic monitoring, and the latest advancements in SSE technology. It highlights the rationale underpinning their adoption while addressing regulatory aspects imperative for their seamless integration into clinical practice.

Analysis of the management and therapeutic performance of diabetes mellitus employing special target

Diabetes mellitus (DM) is a chronic metabolic condition characterized predominantly by hyperglycemia. The most common causes contributing to the pathophysiology of diabetes are insufficient insulin secretion, resistance to insulin's tissue-acting effects, or a combination of both. Over the last 30 years, the global prevalence of diabetes increased from 4% to 6.4%. If no better treatment or cure is found, this amount might climb to 430 million in the coming years. The major factors of the disease's deterioration include age, obesity, and a sedentary lifestyle. Finding new therapies to manage diabetes safely and effectively without jeopardizing patient compliance has always been essential. Among the medications available to manage DM on this journey are glucagon-like peptide-1 agonists, thiazolidinediones, sulphonyl urease, glinides, biguanides, and insulin-targeting receptors discovered more than 10 years ago. Despite the extensive preliminary studies, a few clinical observations suggest this process is still in its early stages. The present review focuses on targets that contribute to insulin regulation and may be employed as targets in treating diabetes since they may be more efficient and secure than current and traditional treatments.

3D printed multi-drug-loaded suppositories for acute severe ulcerative colitis

Acute severe ulcerative colitis (ASUC) is a growing health burden that often requires treatment with multiple therapeutic agents. As inflammation is localised in the rectum and colon, local drug delivery using suppositories could improve therapeutic outcomes. Three-dimensional (3D) printing is a novel manufacturing tool that permits the combination of multiple drugs in personalised dosage forms, created based on each patient's disease condition. This study, for the first time, demonstrates the feasibility of producing 3D printed suppositories with two anti-inflammatory agents, budesonide and tofacitinib citrate, for the treatment of ASUC. As both drugs are poorly water-soluble, the suppositories' ability to self-emulsify was exploited to improve their performance. The suppositories were fabricated via semi-solid extrusion (SSE) 3D printing and contained tofacitinib citrate and budesonide in varying doses (10 or 5 mg; 4 or 2 mg, respectively). The suppositories displayed similar dissolution and disintegration behaviours irrespective of their drug content, demonstrating the flexibility of the technology. Overall, this study demonstrates the feasibility of using SSE 3D printing to create multi-drug suppositories for the treatment of ASUC, with the possibility of titrating the drug doses based on the disease progression.

Using chronobiology-based second-generation artificial intelligence digital system for overcoming antimicrobial drug resistance in chronic infections

Antimicrobial resistance results from the widespread use of antimicrobial agents and is a significant obstacle to the effectiveness of these agents. Numerous methods are used to overcome this problem with moderate success. Besides efforts of antimicrobial stewards, several artificial intelligence (AI)-based technologies are being explored for preventing resistance development. These first-generation systems mainly focus on improving patients' adherence. Chronobiology is inherent in all biological systems. Host response to infections and pathogens activity are assumed to be affected by the circadian clock. This paper describes the problem of antimicrobial resistance and reviews some of the current AI technologies. We present the establishment of a second-generation AI chronobiology-based approach to help in preventing further resistance and possibly overcome existing resistance. An algorithm-controlled regimen that improves the long-term effectiveness of antimicrobial agents is being developed based on the implementation of variability in dosing and drug administration times. The method provides a means for ensuring a sustainable response and improved outcomes. Ongoing clinical trials determine the effectiveness of this second-generation system in chronic infections. Data from these studies are expected to shed light on a new aspect of resistance mechanisms and suggest methods for overcoming them.IMPORTANCE SECTIONThe paper presents the establishment of a second-generation AI chronobiology-based approach to help in preventing further resistance and possibly overcome existing resistance.Key messagesAntimicrobial resistance results from the widespread use of antimicrobial agents and is a significant obstacle to the effectiveness of these agents.We present the establishment of a second-generation AI chronobiology-based approach to help in preventing further resistance and possibly overcome existing resistance.

Simultaneous fabrication of multiple tablets within seconds using tomographic volumetric 3D printing

3D printing is driving a shift in patient care away from a generalised model and towards personalised treatments. To complement fast-paced clinical environments, 3D printing technologies must provide sufficiently high throughputs for them to be feasibly implemented. Volumetric printing is an emerging 3D printing technology that affords such speeds, being capable of producing entire objects within seconds. In this study, for the first time, rotatory volumetric printing was used to simultaneously produce two torus- or cylinder-shaped paracetamol-loaded Printlets (3D printed tablets). Six resin formulations comprising paracetamol as the model drug, poly(ethylene glycol) diacrylate (PEGDA) 575 or 700 as photoreactive monomers, water and PEG 300 as non-reactive diluents, and lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP) as the photoinitiator were investigated. Two printlets were successfully printed in 12 to 32 s and exhibited sustained drug release profiles. These results support the use of rotary volumetric printing for efficient and effective manufacturing of various personalised medicines at the same time. With the speed and precision it affords, rotatory volumetric printing has the potential to become one of the most promising alternative manufacturing technologies in the pharmaceutical industry.

Does clinical research account for diversity in deploying digital health technologies?

Digital health technologies (DHTs) should expand access to clinical research to represent the social determinants of health (SDoH) across the population. The frequency of reporting participant SDoH data in clinical publications is low and is not known for studies that utilize DHTs. We evaluated representation of 11 SDoH domains in 126 DHT-enabled clinical research publications and proposed a framework under which these domains could be captured and subsequently reported in future studies. Sex, Race, and Education were most frequently reported (in 94.4%, 27.8%, and 20.6% of publications, respectively). The remaining 8 domains were reported in fewer than 10% of publications. Medical codes were identified that map to each of the proposed SDoH domains and the resulting resource is suggested to highlight that existing infrastructure could be used to capture SDoH data. An opportunity exists to increase reporting on the representation of SDoH among participants to encourage equitable and inclusive research progress through DHT-enabled clinical studies.

Clinical applications of smart wearable sensors

Smart wearable sensors are electronic devices worn on the body that collect, process, and transmit various physiological data. Compared to traditional devices, their advantages in terms of portability and comfort have made them increasingly important in the medical field. This review takes a unique clinical physician's standpoint, diverging from conventional sensor-type-based classifications, and provides a comprehensive overview of the diverse clinical applications of wearable sensors in recent years. In this review, we categorize these applications according to different diseases, encompassing skin diseases and injuries, cardiovascular diseases, abnormal human motion, as well as endocrine and metabolic disorders. Additionally, we discuss the challenges and perspectives hindering the development of sensors for clinical use, emphasizing the critical need for interdisciplinary collaboration between medical and engineering professionals. Overall, this review would serve as an important reference for the future direction of sensor devices in clinical use.

Digital solutions to follow up on discharged new parents-A systematic literature review

New parents and their newborns are followed up after discharge either through home visits from midwives/nurses or using information and communication technology. This follow-up focuses on individual needs related to breastfeeding and infant feeding, practical advice on caring for babies, supporting and strengthening the new mother's knowledge and self-confidence concerning child development and parenting skills, and supporting the relationship between parents and baby. This systematic review aims to integrate available research results that describe new parents' experiences when health and care providers used telemedicine as a platform for follow-up after discharge from the childbirth department. This literature review was conducted following the PRISMA statement and was prospectively registered in PROSPERO CRD42021236912. The studies were identified through the following databases: AMED, Academic, EMBASE, Google Scholar, Ovid MEDLINE via PubMed, Cochrane database, and CINAHL. Results from these studies were compiled using thematic analysis. A total of 886 studies were identified. Screening resulted in eight studies that met the inclusion criteria. Thematic analysis produced the following themes: a) Flexibility and convenience of digital support, b) Digital literacy, c) Parents feeling safe with digital support, and d) Adequate substitute for physical meetings. New parents who live in a home environment with a relaxed atmosphere and around-the-clock digital support experience a sense of control, security, full attention, and encouragement. Digital follow up at home has proven effective because it can meet the support needs of new parents when necessary.

Survey on Path Planning for UAVs in Healthcare Missions

This article presents a comprehensive review of the state-of-the-art applications and methodologies related to the use of unmanned aerial vehicles (UAVs) in the healthcare sector, with a particular focus on path planning. UAVs have gained remarkable attention in healthcare during the outbreak of COVID-19, and this study explores their potential as a viable option for medical transportation. The survey categorizes existing studies by mission type, challenges addressed, and performance metrics to provide a clearer picture of the path planning problems and potential directions for future research. It highlights the importance of addressing the path planning problem and the challenges that UAVs may face during their missions, including the UAV delivery range limitation, and discusses recent solutions in this field. The study concludes by encouraging researchers to conduct their studies in a realistic environment to reveal UAVs' real potential, usability, and feasibility in the healthcare domain.

Technologies in Home-Based Digital Rehabilitation: Scoping Review

BACKGROUND

Due to growing pressure on the health care system, a shift in rehabilitation to home settings is essential. However, efficient support for home-based rehabilitation is lacking. The COVID-19 pandemic has further exacerbated these challenges and has affected individuals and health care professionals during rehabilitation. Digital rehabilitation (DR) could support home-based rehabilitation. To develop and implement DR solutions that meet clients' needs and ease the growing pressure on the health care system, it is necessary to provide an overview of existing, relevant, and future solutions shaping the constantly evolving market of technologies for home-based DR.

OBJECTIVE

In this scoping review, we aimed to identify digital technologies for home-based DR, predict new or emerging DR trends, and report on the influences of the COVID-19 pandemic on DR.

METHODS

The scoping review followed the framework of Arksey and O'Malley, with improvements made by Levac et al. A literature search was performed in PubMed, Embase, CINAHL, PsycINFO, and the Cochrane Library. The search spanned January 2015 to January 2022. A bibliometric analysis was performed to provide an overview of the included references, and a co-occurrence analysis identified the technologies for home-based DR. A full-text analysis of all included reviews filtered the trends for home-based DR. A gray literature search supplemented the results of the review analysis and revealed the influences of the COVID-19 pandemic on the development of DR.

RESULTS

A total of 2437 records were included in the bibliometric analysis and 95 in the full-text analysis, and 40 records were included as a result of the gray literature search. Sensors, robotic devices, gamification, virtual and augmented reality, and digital and mobile apps are already used in home-based DR; however, artificial intelligence and machine learning, exoskeletons, and digital and mobile apps represent new and emerging trends. Advantages and disadvantages were displayed for all technologies. The COVID-19 pandemic has led to an increased use of digital technologies as remote approaches but has not led to the development of new technologies.

CONCLUSIONS

Multiple tools are available and implemented for home-based DR; however, some technologies face limitations in the application of home-based rehabilitation. However, artificial intelligence and machine learning could be instrumental in redesigning rehabilitation and addressing future challenges of the health care system, and the rehabilitation sector in particular. The results show the need for feasible and effective approaches to implement DR that meet clients' needs and adhere to framework conditions, regardless of exceptional situations such as the COVID-19 pandemic.

Current methods for contactless optical patient diagnosis: a systematic review

Many countries around the world face a shortage of medical personnel, leading to work overload or even burnout. This calls for political and scientific solutions to relieve the medical personnel. The measurement of vital signs in hospitals is still predominately carried out manually with traditional contact-based methods, taking over a substantial share of the medical personnel's workload. The introduction of contactless methods for vital sign monitoring (e.g., with a camera) has great potential to relieve the medical personnel. This systematic review's objective is to analyze the state of the art in the field of contactless optical patient diagnosis. This review distinguishes itself from already existing reviews by considering studies that do not only propose the contactless measurement of vital signs but also include an automatic diagnosis of the patient's condition. This means that the included studies incorporate the physician's reasoning and evaluation of vital signs into their algorithms, allowing an automated patient diagnosis. The literature screening of two independent reviewers resulted in a total of five eligible studies. The highest number of studies (three) introduce methods for the risk assessment of infectious diseases, one study introduces a method for the risk assessment of cardiovascular diseases, and one study introduces a method for the diagnosis of obstructive sleep apnea. Overall, high heterogeneity in relevant study parameters is reported among the included studies. The low number of included studies indicates a large research gap and emphasizes the demand for further research on this emerging topic.

Development of an Evidence-Based Conceptual Model of the Health Care Sector Under Digital Transformation: Integrative Review

BACKGROUND

Digital transformation is currently one of the most influential developments. It is fundamentally changing consumers' expectations and behaviors, challenging traditional firms, and disrupting numerous markets. Recent discussions in the health care sector tend to assess the influence of technological implications but neglect other factors needed for a holistic view on the digital transformation. This calls for a reevaluation of the current state of digital transformation in health care. Consequently, there is a need for a holistic view on the complex interdependencies of digital transformation in the health care sector.

OBJECTIVE

This study aimed to examine the effects of digital transformation on the health care sector. This is accomplished by providing a conceptual model of the health care sector under digital transformation.

METHODS

First, the most essential stakeholders in the health care sector were identified by a scoping review and grounded theory approach. Second, the effects on these stakeholders were assessed. PubMed, Web of Science, and Dimensions were searched for relevant studies. On the basis of an integrative review and grounded theory methodology, the relevant academic literature was systematized and quantitatively and qualitatively analyzed to evaluate the impact on the value creation of, and the relationships among, the stakeholders. Third, the findings were synthesized into a conceptual model of the health care sector under digital transformation.

RESULTS

A total of 2505 records were identified from the database search; of these, 140 (5.59%) were included and analyzed. The results revealed that providers of medical treatments, patients, governing institutions, and payers are the most essential stakeholders in the health care sector. As for the individual stakeholders, patients are experiencing a technology-enabled growth of influence in the sector. Providers are becoming increasingly dependent on intermediaries for essential parts of the value creation and patient interaction. Payers are expected to try to increase their influence on intermediaries to exploit the enormous amounts of data while seeing their business models be challenged by emerging technologies. Governing institutions regulating the health care sector are increasingly facing challenges from new entrants in the sector. Intermediaries increasingly interconnect all these stakeholders, which in turn drives new ways of value creation. These collaborative efforts have led to the establishment of a virtually integrated health care ecosystem.

CONCLUSIONS

The conceptual model provides a novel and evidence-based perspective on the interrelations among actors in the health care sector, indicating that individual stakeholders need to recognize their role in the system. The model can be the basis of further evaluations of strategic actions of actors and their effects on other actors or the health care ecosystem itself.

Digital health in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) can be prevented and treated through effective care, reducing exacerbations and hospitalizations. Early identification of individuals at high risk of COPD exacerbation is an opportunity for preventive measures. However, many patients struggle to follow their treatment plans because of a lack of knowledge about the disease, limited access to resources, and insufficient clinical support. The growth of digital health-which encompasses advancements in health information technology, artificial intelligence, telehealth, the Internet of Things, mobile health, wearable technology, and digital therapeutics-offers opportunities for improving the early diagnosis and management of COPD. This study reviewed the field of digital health in terms of COPD. The findings showed that despite significant advances in digital health, there are still obstacles impeding its effectiveness. Finally, we highlighted some of the major challenges and possibilities for developing and integrating digital health in COPD management.

Energy Consumption and Carbon Footprint of 3D Printing in Pharmaceutical Manufacture

Achieving carbon neutrality is seen as an important goal in order to mitigate the effects of climate change, as carbon dioxide is a major greenhouse gas that contributes to global warming. Many countries, cities and organizations have set targets to become carbon neutral. The pharmaceutical sector is no exception, being a major contributor of carbon emissions (emitting approximately 55% more than the automotive sector for instance) and hence is in need of strategies to reduce its environmental impact. Three-dimensional (3D) printing is an advanced pharmaceutical fabrication technology that has the potential to replace traditional manufacturing tools. Being a new technology, the environmental impact of 3D printed medicines has not been investigated, which is a barrier to its uptake by the pharmaceutical industry. Here, the energy consumption (and carbon emission) of 3D printers is considered, focusing on technologies that have successfully been demonstrated to produce solid dosage forms. The energy consumption of 6 benchtop 3D printers was measured during standby mode and printing. On standby, energy consumption ranged from 0.03 to 0.17 kWh. The energy required for producing 10 printlets ranged from 0.06 to 3.08 kWh, with printers using high temperatures consuming more energy. Carbon emissions ranged between 11.60-112.16 g CO₂ (eq) per 10 printlets, comparable with traditional tableting. Further analyses revealed that decreasing printing temperature was found to reduce the energy demand considerably, suggesting that developing formulations that are printable at lower temperatures can reduce CO₂ emissions. The study delivers key initial insights into the environmental impact of a potentially transformative manufacturing technology and provides encouraging results in demonstrating that 3D printing can deliver quality medicines without being environmentally detrimental.

Free-living core body temperature monitoring using a wrist-worn sensor after COVID-19 booster vaccination: a pilot study

Core body temperature (CBT) is a key vital sign and fever is an important indicator of disease. In the past decade, there has been growing interest for vital sign monitoring technology that may be embedded in wearable devices, and the COVID-19 pandemic has highlighted the need for remote patient monitoring systems. While wrist-worn sensors allow continuous assessment of heart rate and oxygen saturation, reliable measurement of CBT at the wrist remains challenging. In this study, CBT was measured continuously in a free-living setting using a novel technology worn at the wrist and compared to reference core body temperature measurements, i.e., CBT values acquired with an ingestible temperature-sensing pill. Fifty individuals who received the COVID-19 booster vaccination were included. The datasets of 33 individuals were used to develop the CBT prediction algorithm, and the algorithm was then validated on the datasets of 17 participants. Mean observation time was 26.4 h and CBT > 38.0 °C occurred in 66% of the participants. CBT predicted by the wrist-worn sensor showed good correlation to the reference CBT (r = 0.72). Bland-Altman statistics showed an average bias of 0.11 °C of CBT predicted by the wrist-worn device compared to reference CBT, and limits of agreement were - 0.67 to + 0.93 °C, which is comparable to the bias and limits of agreement of commonly used tympanic membrane thermometers. The small size of the components needed for this technology would allow its integration into a variety of wearable monitoring systems assessing other vital signs and at the same time allowing maximal freedom of movement to the user.

Machine learning using multi-modal data predicts the production of selective laser sintered 3D printed drug products

Three-dimensional (3D) printing is drastically redefining medicine production, offering digital precision and personalized design opportunities. One emerging 3D printing technology is selective laser sintering (SLS), which is garnering attention for its high precision, and compatibility with a wide range of pharmaceutical materials, including low-solubility compounds. However, the full potential of SLS for medicines is yet to be realized, requiring expertise and considerable time-consuming and resource-intensive trial-and-error research. Machine learning (ML), a subset of artificial intelligence, is an in silico tool that is accomplishing remarkable breakthroughs in several sectors for its ability to make highly accurate predictions. Therefore, the present study harnessed ML to predict the printability of SLS formulations. Using a dataset of 170 formulations from 78 materials, ML models were developed from inputs that included the formulation composition and characterization data retrieved from Fourier-transformed infrared spectroscopy (FT-IR), X-ray powder diffraction (XRPD) and differential scanning calorimetry (DSC). Multiple ML models were explored, including supervised and unsupervised approaches. The results revealed that ML can achieve high accuracies, by using the formulation composition leading to a maximum F1 score of 81.9%. Using the FT-IR, XRPD and DSC data as inputs resulted in an F1 score of 84.2%, 81.3%, and 80.1%, respectively. A subsequent ML pipeline was built to combine the predictions from FT-IR, XRPD and DSC into one consensus model, where the F1 score was found to further increase to 88.9%. Therefore, it was determined for the first time that ML predictions of 3D printability benefit from multi-modal data, combining numeric, spectral, thermogram and diffraction data. The study lays the groundwork for leveraging existing characterization data for developing high-performing computational models to accelerate formulation development.

Creating personas for exposome research: the experience from the HEAP project

The exposome is a complex scientific field that has enjoyed consistent growth over the last two decades, defined as the composite of every exposure to which an individual is subjected from conception to death. The study of the exposome requires consideration of both the nature of those exposures and their changes over time, and as such necessitates high quality data and software solutions. As the exposome is both a broad and a recent concept, it is challenging to define or to introduce in a structured way. Thus, an approach to assist with clear definitions and a structured framework is needed for the wider scientific and public communication. Results: A set of 14 personas were developed through three focus groups and a series of 14 semi-structured interviews. The focus groups defined the broad themes specific to exposome research, while the sub-themes emerged to saturation via the interviews process. Personas are imaginary individuals that represent segments/groups of real people within a population. Within the context of the HEAP project, the created personas represented both exposome data generators and users. Conclusion: Personas have been implemented successfully in computer science, improving the understanding of human-computer interaction. The creation of personas specific to exposome research adds a useful tool supporting education and outreach activities for a complex scientific field.

Describing the evidence-base for research engagement by health care providers and health care organisations: a scoping review

BACKGROUND

Having a research-engaged health and medical workforce is associated with improvements in clinical outcomes for patients. As such, there has been significant government investment internationally to support health care organisations and services to increase staff engagement with research.

OBJECTIVES

This scoping review sought to provide an overview of the literature describing strategies employed to increase research engagement by health care providers and organisations, and to undertake a qualitative analysis to generate a list of research engagement strategies.

METHODS

A scoping review using systematic search strategies was undertaken to locate peer-review publications and grey literature related to research engagement by health care providers and organisations. Research engagement was defined as a 'deliberate set of intellectual and practical activities undertaken by health care staff and organisations to conduct research'. A database search of electronic records was performed with no limit on publication date. Publications were included regardless of study type (excluding systematic reviews) and categorised as either databased (presenting data or new analysis of existing data) and non-databased (no new data or analyses). Databased publications were further classified according to study type, study design and setting. A qualitative synthesis using a Framework Approach was undertaken with all studies that described a strategy to improve research engagement.

RESULTS

A total of 152 publications were included in this study with 54% categorised as non-databased. Of the databased articles, the majority (72%) were descriptive studies describing prevalence of correlates of research engagement, 17 (25%) described intervention studies where only two were controlled studies. The following research engagement strategies were identified: i) dual skilled team/staff, ii) resources or physical infrastructure, iii) incentives, iv) leadership support of research, v) education/training, vi) networks, vii) forming partnerships or collaborations and viii) overall leadership structure of entity.

CONCLUSIONS

The literature on research engagement is primarily opinion-based and descriptive in nature. To provide the evidence needed to inform strategies, this needs to progress beyond descriptive to more rigorous well-designed intervention research.

Leakage of stomal effluent outside the baseplate leads to rise in product usage and health professional interactions

BACKGROUND

Leakage of stomal effluent outside the baseplate that soils clothes or bedsheets is a common problem for many people with a stoma and significantly impacts their quality of life.

AIM

To understand behavioural changes for people experiencing faecal leakage outside the baseplate regarding the usage of pouching systems, supporting products and interactions with health professionals.

METHODS

Retrospective, self-reported questionnaire.

FINDINGS

Respondents on average experienced 1.1 incidents of faecal leakage outside the baseplate per fortnight. In periods with issues of leakage, 21% of respondents had been in contact with health professionals, 40% increased their use of pouching systems, 25% increased their use of existing supporting products, and 21% included additional supporting products to their change routine. The increased use of healthcare resources was estimated to cost £32.47 in the 3 weeks following a leakage incident.

CONCLUSION

Incidents of leakage outside the baseplate lead to increased use of healthcare resources.

User's image perception improved strategy and application of augmented reality systems in smart medical care: A review

BACKGROUND

Augmented reality (AR) is a new human-computer interaction technology that combines virtual reality, computer vision, and computer networks. With the rapid advancement of the medical field towards intelligence and data visualisation, AR systems are becoming increasingly popular in the medical field because they can provide doctors with clear enough medical images and accurate image navigation in practical applications. However, it has been discovered that different display types of AR systems have different effects on doctors' perception of the image after virtual-real fusion during the actual medical application. If doctors cannot correctly perceive the image, they may be unable to correctly match the virtual information with the real world, which will have a significant impact on their ability to recognise complex structures.

METHODS

This paper uses Citespace, a literature analysis tool, to visualise and analyse the research hotspots when AR systems are used in the medical field.

RESULTS

A visual analysis of the 1163 articles retrieved from the Web of Science Core Collection database reveals that display technology and visualisation technology are the key research directions of AR systems at the moment.

CONCLUSION

This paper categorises AR systems based on their display principles, reviews current image perception optimisation schemes for various types of systems, and analyses and compares different display types of AR systems based on their practical applications in the field of smart medical care so that doctors can select the appropriate display types based on different application scenarios. Finally, the future development direction of AR display technology is anticipated in order for AR technology to be more effectively applied in the field of smart medical care. The advancement of display technology for AR systems is critical for their use in the medical field, and the advantages and disadvantages of various display types should be considered in different application scenarios to select the best AR system.

Artificial intelligence and digital medicine for integrated home care services in Italy: Opportunities and limits

Home healthcare in the Italian health system has proven to be an essential factor in adequately responding to the health needs of an increasingly aging population. The opportunities offered by digitization and new technologies, such as artificial intelligence (AI) and robotics, are a lever for making home care services more effective and efficient on the one hand, and on the other for improving remote patient monitoring. Telemedicine devices have enormous potential for telemonitoring and telerehabilitation of patients suffering from chronic disabling diseases; in particular, AI systems can now provide very useful managerial and decision-making support in numerous clinical areas. AI combined with digitalization, could also allow for the remote monitoring of patients' health conditions. In this paper authors describe some digital and healthcare tools or system of AI, such as the Connected Care model, the Home Care Premium (HCP) project, The Resilia App and some professional service robotics. In this context, to optimize potential and concrete healthcare improvements, some limits need to be overcome: gaps in health information systems and digital tools at all levels of the Italian National Health Service, the slow dissemination of the computerized medical record, issues of digital literacy, the high cost of devices, the poor protection of data privacy. The danger of over-reliance on such systems should also be examined. Therefore the legal systems of the various countries, including Italy, should indicate clear decision-making paths for the patient.

Invited review: integration of technologies and systems for precision animal agriculture-a case study on precision dairy farming

Precision livestock farming (PLF) offers a strategic solution to enhance the management capacity of large animal groups, while simultaneously improving profitability, efficiency, and minimizing environmental impacts associated with livestock production systems. Additionally, PLF contributes to optimizing the ability to manage and monitor animal welfare while providing solutions to global grand challenges posed by the growing demand for animal products and ensuring global food security. By enabling a return to the "per animal" approach by harnessing technological advancements, PLF enables cost-effective, individualized care for animals through enhanced monitoring and control capabilities within complex farming systems. Meeting the nutritional requirements of a global population exponentially approaching ten billion people will likely require the density of animal proteins for decades to come. The development and application of digital technologies are critical to facilitate the responsible and sustainable intensification of livestock production over the next several decades to maximize the potential benefits of PLF. Real-time continuous monitoring of each animal is expected to enable more precise and accurate tracking and management of health and well-being. Importantly, the digitalization of agriculture is expected to provide collateral benefits of ensuring auditability in value chains while assuaging concerns associated with labor shortages. Despite notable advances in PLF technology adoption, a number of critical concerns currently limit the viability of these state-of-the-art technologies. The potential benefits of PLF for livestock management systems which are enabled by autonomous continuous monitoring and environmental control can be rapidly enhanced through an Internet of Things approach to monitoring and (where appropriate) closed-loop management. In this paper, we analyze the multilayered network of sensors, actuators, communication, networking, and analytics currently used in PLF, focusing on dairy farming as an illustrative example. We explore the current state-of-the-art, identify key shortcomings, and propose potential solutions to bridge the gap between technology and animal agriculture. Additionally, we examine the potential implications of advancements in communication, robotics, and artificial intelligence on the health, security, and welfare of animals.

A virtual reality simulation of a novel way to illuminate the surgical field - A feasibility study on the use of automated lighting systems in the operating theatre

Introduction

Surgical lighting systems have to be re-adjusted manually during surgery by the medical personnel. While some authors suggest that interaction with a surgical lighting system in the operating room might be a distractor, others support the idea that manual interaction with the surgical lighting system is a hygiene problem as pathogens might be present on the handle. In any case, it seems desirable to develop a novel approach to surgical lighting that minimizes the need for manual interaction during a surgical procedure.

Methodes

We investigated the effect of manual interaction with a classical surgical lighting system and simulated a proposed novel design of a surgical lighting system in a virtual reality environment with respect to performance accuracy as well as cognitive load (measured by electroencephalographical recordings).

Results

We found that manual interaction with the surgical lights has no effect on the quality of performance, yet for the price of a higher mental effort, possibly leading to faster fatigue of the medical personnel in the long run.

Discussion

Our proposed novel surgical lighting system negates the need for manual interaction and leads to a performance quality comparable to the classical lighting system, yet with less mental load for the surgical personnel.

Technology acceptance of digital devices for home use: Qualitative results of a mixed methods study

Objective

Digital devices have demonstrated benefits to patients with chronic and neurodegenerative diseases. But when patients use medical devices in their homes, the technologies have to fit into their lives. We investigated the technology acceptance of seven digital devices for home use.

Methods

We conducted 60 semi-structured interviews with participants of a larger device study on their views on the acceptability of seven devices. Transcriptions were analysed using qualitative content analysis.

Results

Based on the unified theory of acceptance and use of technology, we evaluated effort, facilitating conditions, performance expectancy and social influence of each device.In the effort category, five themes emerged: (a) the hassle to use the device; (b) its usability; (c) comfort; (d) disturbance to daily life; and (e) problems during usage. Facilitating conditions consisted of five themes: (a) expectations regarding a device; (b) quality of the instructions; (c) insecurities with usage; (d) possibilities of optimization; and (e) possibilities to use the device longer. Regarding performance expectancy, we identified three themes: (a) insecurities with the performance of a device; (b) feedback; and (c) motivation for using a device. In the social influence category, three themes emerged: (a) reactions of peers; (b) concerns with the visibility of a device; and (c) concerns regarding data privacy.

Conclusions

We identify key factors that determine the acceptability of medical devices for home use from the participants' perspective. These include low effort of use, minor disruptions to their daily lives and good support from the study team.

IT and the Quality and Efficiency of Mental Health Care in a Time of COVID-19: Case Study of Mental Health Providers in England

BACKGROUND

In England, COVID-19 has significantly affected mental health care and tested the resilience of health care providers. In many areas, the increased use of IT has enabled traditional modes of service delivery to be supported or even replaced by remote forms of provision.

OBJECTIVE

This study aimed to assess the use and impact of IT, in remote service provision, on the quality and efficiency of mental health care during the pandemic. We drew on sociotechnical systems theory as a conceptual framework to help structure the gathering, analysis, and interpretation of data.

METHODS

We conducted a national scoping survey that involved documentary analysis and semistructured interviews with 6 national stakeholders and case studies of 4 purposefully selected mental health providers in England involving interviews with 53 staff members.

RESULTS

Following the outbreak of COVID-19, mental health providers rapidly adjusted their traditional forms of service delivery, switching to digital and telephone consultations for most services. The informants provided nuanced perspectives on the impact on the quality and efficiency of remote service delivery during the pandemic. Notably, it has allowed providers to attend to as many patients as possible in the face of COVID-19 restrictions, to the convenience of both patients and staff. Among its negative effects are concerns about the unsuitability of remote consultation for some people with mental health conditions and the potential to widen the digital divide and exacerbate existing inequalities. Sociotechnical systems theory was found to be a suitable framework for understanding the range of systemic and sociotechnical factors that influence the use of technology in mental health care delivery in times of crisis and normalcy.

CONCLUSIONS

Although the use of IT has boosted mental health care delivery during the pandemic, it has had mixed effects on quality and efficiency. In general, patients have benefited from the convenience of remote consultation when face-to-face contact was impossible. In contrast, patient choice was often compromised, and patient experience and outcomes might have been affected for some people with mental health conditions for which remote consultation is less suitable. However, the full impact of IT on the quality and efficiency of mental health care provision along with the systemic and sociotechnical determinants requires more sustained and longitudinal research.

To infinity and beyond: Strategies for fabricating medicines in outer space

Recent advancements in next generation spacecrafts have reignited public excitement over life beyond Earth. However, to safeguard the health and safety of humans in the hostile environment of space, innovation in pharmaceutical manufacturing and drug delivery deserves urgent attention. In this review/commentary, the current state of medicines provision in space is explored, accompanied by a forward look on the future of pharmaceutical manufacturing in outer space. The hazards associated with spaceflight, and their corresponding medical problems, are first briefly discussed. Subsequently, the infeasibility of present-day medicines provision systems for supporting deep space exploration is examined. The existing knowledge gaps on the altered clinical effects of medicines in space are evaluated, and suggestions are provided on how clinical trials in space might be conducted. An envisioned model of on-site production and delivery of medicines in space is proposed, referencing emerging technologies (e.g. Chemputing, synthetic biology, and 3D printing) being developed on Earth that may be adapted for extra-terrestrial use. This review concludes with a critical analysis on the regulatory considerations necessary to facilitate the adoption of these technologies and proposes a framework by which these may be enforced. In doing so, this commentary aims to instigate discussions on the pharmaceutical needs of deep space exploration, and strategies on how these may be met.

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Space is a hostile environment that threatens human health and drug stability.

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Data on the behaviour of medicines in space is critical but lacking.

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Novel drug manufacturing and delivery strategies are needed to safeguard crewmembers’ safety.

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Chemputing, synthetic biology, and 3D printing are examples of such emerging technologies.

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A regulatory framework for space medicines must be implemented to assure quality.

3D Printed Fractal-like Structures with High Percentage of Drug for Zero-Order Colonic Release

Colonic drug delivery of drugs is an area of great interest due to the need to treat high prevalence colonic local diseases as well as systemic conditions that may benefit from the advantages associated to this route of drug administration. In the last decade, the use of 3D printing technologies has expanded, offering the possibility of preparing personalized medicines in small batches directly at the point of care. The aim of this work is to design a high drug loaded 3D printed system prepared by a combination of Fused Deposition Modelling (FDM) and Injection Volume Filling (IVF) techniques intended for zero-order colonic drug release. For this purpose, different batches of binary and ternary filaments based on the thermoplastic polyurethane Tecoflex EG-72D (TPU), theophylline anhydrous (AT) as model drug, and magnesium stearate as lubricant have been developed and characterized. Filaments with the highest drug load and the best rheological properties were selected for the manufacture of a printed fractal-like structure based on multiple toroids. This design was proposed to provide high surface area, leading to increased drug release and water uptake in the colonic region. This structure was 3D printed by FDM and then coated in a unique step by IVF technology using the enteric polymer DrugCoat S 12.5. This way, an additional coating process is avoided, reducing costs and production time. Studies of drug release confirmed the ability of the structures to provide a five-hour period of constant drug delivery in the colonic region.

Separating Features From Functionality in Vaccination Apps: Computational Analysis

BACKGROUND

Some latest estimates show that approximately 95% of Americans own a smartphone with numerous functions such as SMS text messaging, the ability to take high-resolution pictures, and mobile software apps. Mobile health apps focusing on vaccination and immunization have proliferated in the digital health information technology market. Mobile health apps have the potential to positively affect vaccination coverage. However, their general functionality, user and disease coverage, and exchange of information have not been comprehensively studied or evaluated computationally.

OBJECTIVE

The primary aim of this study is to develop a computational method to explore the descriptive, usability, information exchange, and privacy features of vaccination apps, which can inform vaccination app design. Furthermore, we sought to identify potential limitations and drawbacks in the apps' design, readability, and information exchange abilities.

METHODS

A comprehensive codebook was developed to conduct a content analysis on vaccination apps' descriptive, usability, information exchange, and privacy features. The search and selection process for vaccination-related apps was conducted from March to May 2019. We identified a total of 211 apps across both platforms, with iOS and Android representing 62.1% (131/211) and 37.9% (80/211) of the apps, respectively. Of the 211 apps, 119 (56.4%) were included in the final study analysis, with 42 features evaluated according to the developed codebook. The apps selected were a mix of apps used in the United States and internationally. Principal component analysis was used to reduce the dimensionality of the data. Furthermore, cluster analysis was used with unsupervised machine learning to determine patterns within the data to group the apps based on preselected features.

RESULTS

The results indicated that readability and information exchange were highly correlated features based on principal component analysis. Of the 119 apps, 53 (44.5%) were iOS apps, 55 (46.2%) were for the Android operating system, and 11 (9.2%) could be found on both platforms. Cluster 1 of the k-means analysis contained 22.7% (27/119) of the apps; these were shown to have the highest percentage of features represented among the selected features.

CONCLUSIONS

We conclude that our computational method was able to identify important features of vaccination apps correlating with end user experience and categorize those apps through cluster analysis. Collaborating with clinical health providers and public health officials during design and development can improve the overall functionality of the apps.

A Review of Digital Health and Biotelemetry: Modern Approaches towards Personalized Medicine and Remote Health Assessment

With the prevalence of digitalization in all aspects of modern society, health assessment is becoming digital too. Taking advantage of the most recent technological advances and approaching medicine from an interdisciplinary perspective has allowed for important progress in healthcare services. Digital health technologies and biotelemetry devices have been more extensively employed for preventing, detecting, diagnosing, monitoring, and predicting the evolution of various diseases, without requiring wires, invasive procedures, or face-to-face interaction with medical personnel. This paper aims to review the concepts correlated to digital health, classify and describe biotelemetry devices, and present the potential of digitalization for remote health assessment, the transition to personalized medicine, and the streamlining of clinical trials.

Innovations in Chewable Formulations: The Novelty and Applications of 3D Printing in Drug Product Design

Since their introduction, chewable dosage forms have gained traction due to their ability to facilitate swallowing, especially in paediatric, geriatric and dysphagia patients. Their benefits stretch beyond human use to also include veterinary applications, improving administration and palatability in different animal species. Despite their advantages, current chewable formulations do not account for individualised dosing and palatability preferences. In light of this, three-dimensional (3D) printing, and in particular the semi-solid extrusion technology, has been suggested as a novel manufacturing method for producing customised chewable dosage forms. This advanced approach offers flexibility for selecting patient-specific doses, excipients, and organoleptic properties, which are critical for ensuring efficacy, safety and adherence to the treatment. This review provides an overview of the latest advancements in chewable dosage forms for human and veterinary use, highlighting the motivations behind their use and covering formulation considerations, as well as regulatory aspects.

The Interplay of Work, Digital Health Usage, and the Perceived Effects of Digitalization on Physicians' Work: Network Analysis Approach

Background

In health care, the benefits of digitalization need to outweigh the risks, but there is limited knowledge about the factors affecting this balance in the work environment of physicians. To achieve the benefits of digitalization, a more comprehensive understanding of this complex phenomenon related to the digitalization of physicians’ work is needed.

Objective

The aim of this study was to examine physicians’ perceptions of the effects of health care digitalization on their work and to analyze how these perceptions are associated with multiple factors related to work and digital health usage.

Methods

A representative sample of 4630 (response rate 24.46%) Finnish physicians (2960/4617, 64.11% women) was used. Statements measuring the perceived effects of digitalization on work included the patients’ active role, preventive work, interprofessional cooperation, decision support, access to patient information, and faster consultations. Network analysis of the perceived effects of digitalization and factors related to work and digital health usage was conducted using mixed graphical modeling. Adjusted and standardized regression coefficients are denoted by b. Centrality statistics were examined to evaluate the relative influence of each variable in terms of node strength.

Results

Nearly half of physicians considered that digitalization has promoted an active role for patients in their own care (2104/4537, 46.37%) and easier access to patient information (1986/4551, 43.64%), but only 1 in 10 (445/4529, 9.82%) felt that the impact has been positive on consultation times with patients. Almost half of the respondents estimated that digitalization has neither increased nor decreased the possibilities for preventive work (2036/4506, 45.18%) and supportiveness of clinical decision support systems (1941/4458, 43.54%). When all variables were integrated into the network, the most influential variables were purpose of using health information systems, employment sector, and specialization status. However, the grade given to the electronic health record (EHR) system that was primarily used had the strongest direct links to faster consultations (b=0.32) and facilitated access to patient information (b=0.28). At least 6 months of use of the main EHR was associated with facilitated access to patient information (b=0.18).

Conclusions

The results highlight the complex interdependence of multiple factors associated with the perceived effects of digitalization on physicians’ work. It seems that a high-quality EHR system is critical for promoting smooth clinical practice. In addition, work-related factors may influence other factors that affect digital health success. These factors should be considered when developing and implementing new digital health technologies or services for physicians’ work. The adoption of digital health is not just a technological project but a project that changes existing work practices.

Large-Scale Customized Production Scheduling of Multiagent-Based Medical 3D Printing

Three-dimensional (3D) printing, also known as additive manufacturing, has unique advantages over traditional manufacturing technologies; thus, it has attracted widespread attention in the medical field. Especially in the context of the frequent occurrence of major public health events, where the medical industry’s demand for large-scale and customized production is increasing, traditional 3D printing production scheduling methods take a long time to handle large-scale customized medical 3D printing (M-3DP) production and have weak intelligent collaboration ability in the face of job-to-device matching under multimaterial printing. Given the problem caused by M-3DP large-scale customized production scheduling, an intelligent collaborative scheduling multiagent-based method is proposed in this study. First, a multiagent-based optimization model is established. On this basis, an improved genetic algorithm embedded with the product mix strategy and the intelligent matching mechanism is designed to optimize the completion time and load balance between devices. Finally, the effectiveness of the proposed method is evaluated using numerical simulation. The simulation results indicated that compared with the simple genetic algorithm, particle swarm optimization, and snake optimizer, the improved genetic algorithm could better reduce the M-3DP mass customization production scheduling time, optimize the load balance between devices, and promote the “intelligent manufacturing” process of M-3DP mass customization.

Administration strategies and smart devices for drug release in specific sites of the upper GI tract

Targeting the release of drugs in specific sites of the upper GI tract would meet local therapeutic goals, improve the bioavailability of specific drugs and help overcoming compliance-related limitations, especially in chronic illnesses of great social/economic impact and involving polytherapies (e.g. Parkinson's and Alzeimer's disease, tubercolosis, malaria, HIV, HCV). It has been traditionally pursued using gastroretentive (GR) systems, i.e. low-density, high-density, magnetic, adhesive and expandable devices. More recently, the interest towards oral administration of biologics has prompted the development of novel drug delivery systems (DDSs) provided with needles and able to inject different formulations in the mucosa of the upper GI tract and particularly of esophagus, stomach or small intestine. Besides comprehensive literature analysis, DDSs identified as smart devices in view of their high degree of complexity in terms of design, working mechanism, materials employed and manufacturing steps were discussed making use of graphic tools.

A Semi-Automated 3D-Printed Chainmail Design Algorithm with Preprogrammed Directional Functions for Hand Exoskeleton

The problem of computerising the design and development of 3D-printed chainmail with programmed directional functions provides a basis for further research, including the automation of medical devices. The scope of the present research was focused on computational optimisation of the selection of materials and shapes for 3D printing, including the design of medical devices, which constitutes a significant scientific, technical, and clinical problem. The aim of this article was to solve the scientific problem of automated or semi-automated efficient and practical design of 3D-printed chainmail with programmed directional functions (variable stiffness/elasticity depending on the direction). We demonstrate for the first time that 3D-printed particles can be arranged into single-layer chainmail with a tunable one- or two-directional bending modulus for use in a medical hand exoskeleton. In the present work, we accomplished this in two ways: based on traditional programming and based on machine learning. This paper presents the novel results of our research, including 3D printouts, providing routes toward the wider implementation of adaptive chainmails. Our research resulted in an automated or semi-automated efficient and practical 3D printed chainmail design with programmed directional functions for a wrist exoskeleton with variable stiffness/flexibility, depending on the direction. We also compared two methodologies of planning and construction: the use of traditional software and machine-learning-based software, with the latter being more efficient for more complex chainmail designs.