What is important to young medical technologists for radiology when choosing a job? / Was ist dem MTR-Nachwuchs bei der Stellenwahl wichtig?

AIM: Given the intensifying competition in Germany for medical technologists for radiology (MTR), our aim was to identify job-related preferences among MTR trainees. MATERIALS AND METHODS: For this purpose, a survey was carried out among MTR trainees at the MTR schools in Düsseldorf, Mainz, and Heidelberg. The focus was on the individual influence of 40 work- and employer-related factors and on the preferred place of work (hospital, practice) and area of operation (radiology, nuclear medicine, radiation therapy) after completing training. RESULTS: 90 MTR trainees took part in the survey. On average, they indicated a pleasant working atmosphere, regular compensation for overtime, and good teamwork as the most important criteria for applying for an MTR position. With regard to their preferred place of work, more than two-thirds stated that they would initially apply to a hospital after completing their training. Moreover, the majority of the respondents prefer to start their MTR careers in diagnostic and interventional radiology, followed by radiation therapy and nuclear medicine. CONCLUSION: Imaging clinics and practices can use the present results for targeted personnel recruitment in order to make their MTR positions as attractive as possible from the point of view of young MTRs. KEY POINTS: · The increasing competition for qualified young talent also affects imaging centers.. · The aim of the survey was to gain insight into the career- and job-related preferences of MTRs.. · Imaging clinics/practices can use these results as a starting point for establishing specific human resources measures for technologists.. · An increase in perceived employer attractiveness can lead to competitive advantages with respect to attracting and retaining qualified MTRs.. CITATION FORMAT: · Zippel C, Wirth P, Biedenstein S et al. What is important to young medical technologists for radiology when choosing a job?. Fortschr Röntgenstr 2024; DOI: 10.1055/a-2221-3971.

[Transparency and Efficiency through Digital Healthcare? Results of a Survey of Generation Y]. / Transparenz und Effizienz durch digitale Gesundheitsversorgung? Ergebnisse eines Surveys der Generation Y.

BACKGROUND: Generation Y represents a special target group in healthcare. Young, healthy and digitally socialized with integration of technologies into everyday life, they have specific needs. In the context of societal challenges such as demographic change and securing a skilled workforce, taking these needs into account, especially for maintaining health, should be the goal of public health as well as specific actors such as health insurers and employers. AIM OF THE WORK: The research was intended to test and deepen the findings of two previous stages of work, specifically a qualitative survey. In this way, two research questions were to be answered: I: the importance of transparency and efficiency in the use of digital health innovations by Generation Y and II: the influence of socio-demographic and technology-associated factors on the use of digital health innovations by Generation Y in addition to the needs. MATERIAL AND METHODS: As a conclusion of a sequential approach, assessments of transparency- and efficiency-associated needs in context of the use of digital health innovations of persons from Generation Y were collected in a quantitative online survey. 355 fully completed data sets were analyzed using SPSS software. An ordinal regression analysis was used to test the influence of predictors from six previously formulated hypotheses. RESULTS: The study was able to describe influences of the constructs transparency and efficiency on the use of apps and smart devices. The need for a sense of control had a significantly negative effect, while the need for structuring and seamless integration into everyday life had a significantly positive effect. Gender and technology readiness also had an impact. According to the data analysis, efficiency and thus a concrete everyday benefit from digital health innovations seems to be more relevant for Generation Y than autonomous empowerment and thus transparency. CONCLUSION: By taking into account the needs described as well as corresponding preferences, the target group could be addressed and usage could potentially be increased. Prevention and health promotion, as well as their organization, should be able to be incorporated into everyday life at a low threshold, and everyday life should be positively supplemented and efficiently supported.

Prevalence and patterns of mobile device usage among physicians in clinical practice: A systematic review.

Mobile devices and corresponding applications (apps) offer a unique potential for clinical work improvement. Healthcare employees already use them for a variety of clinical purposes. Even though their use might affect patients' health and data security, they have rarely found their way into organizational knowledge management strategies. We present the current state of research regarding the prevalence, patterns, and trends of smartphone and tablet usage among physicians in clinical practice. Five electronic databases were searched for quantitative studies. The extracted data were systematically analyzed and visualized in boxplots. The results show an increasing prevalence of smartphones and medical apps in clinical practice, especially among junior physicians. Current applications can be subdivided into four categories: Communication and Organization, Documentation and Monitoring, Diagnostic and Therapeutic Decision Support, and Education. Among them, there is a large number of applications with a direct impact on physicians' clinical actions and therefore on patients' health and data security. In consequence, healthcare organizations should systematically integrate mobile devices and apps into their knowledge management strategies, including a modern IT infrastructure and training courses. Further studies are necessary to identify organizational and external factors that support an efficient mobile device usage during clinical practice.

The Impact of Digital Transformation on Inpatient Care: Mixed Methods Study.

BACKGROUND: In the context of the digital transformation of all areas of society, health care providers are also under pressure to change. New technologies and a change in patients' self-perception and health awareness require rethinking the provision of health care services. New technologies and the extensive use of data can change provision processes, optimize them, or replace them with new services. The inpatient sector, which accounts for a particularly large share of health care spending, plays a major role in this regard. OBJECTIVE: This study examined the influences of current trends in digitization on inpatient service delivery. METHODS: We conducted a scoping review. This was applied to identify the international trends in digital transformation as they relate to hospitals. Future trends were considered from different perspectives. Using the defined inclusion criteria, international peer-reviewed articles published between 2016 and 2021 were selected. The extracted core trends were then contextualized for the German hospital sector with 12 experts. RESULTS: We included 44 articles in the literature analysis. From these, 8 core trends could be deduced. A heuristic impact model of the trends was derived from the data obtained and the experts' assessments. This model provides a development corridor for the interaction of the trends with regard to technological intensity and supply quality. Trend accelerators and barriers were identified. CONCLUSIONS: The impact analysis showed the dependencies of a successful digital transformation in the hospital sector. Although data interoperability is of particular importance for technological intensity, the changed self-image of patients was shown to be decisive with regard to the quality of care. We show that hospitals must find their role in new digitally driven ecosystems, adapt their business models to customer expectations, and use up-to-date information and communications technologies.

Big Data Analytics to Reduce Preventable Hospitalizations-Using Real-World Data to Predict Ambulatory Care-Sensitive Conditions.

The purpose of this study was to develop a prediction model to identify individuals and populations with a high risk of being hospitalized due to an ambulatory care-sensitive condition who might benefit from preventative actions or tailored treatment options to avoid subsequent hospital admission. A rate of 4.8% of all individuals observed had an ambulatory care-sensitive hospitalization in 2019 and 6389.3 hospital cases per 100,000 individuals could be observed. Based on real-world claims data, the predictive performance was compared between a machine learning model (Random Forest) and a statistical logistic regression model. One result was that both models achieve a generally comparable performance with c-values above 0.75, whereas the Random Forest model reached slightly higher c-values. The prediction models developed in this study reached c-values comparable to existing study results of prediction models for (avoidable) hospitalization from the literature. The prediction models were designed in such a way that they can support integrated care or public and population health interventions with little effort with an additional risk assessment tool in the case of availability of claims data. For the regions analyzed, the logistic regression revealed that switching to a higher age class or to a higher level of long-term care and unit from prior hospitalizations (all-cause and due to an ambulatory care-sensitive condition) increases the odds of having an ambulatory care-sensitive hospitalization in the upcoming year. This is also true for patients with prior diagnoses from the diagnosis groups of maternal disorders related to pregnancy, mental disorders due to alcohol/opioids, alcoholic liver disease and certain diseases of the circulatory system. Further model refinement activities and the integration of additional data, such as behavioral, social or environmental data would improve both model performance and the individual risk scores. The implementation of risk scores identifying populations potentially benefitting from public health and population health activities would be the next step to enable an evaluation of whether ambulatory care-sensitive hospitalizations can be prevented.

Technical Readiness and Stereotypes in Hospital Nursing-A Question of Gender and Age?

(1) Background: The nursing profession is associated with various stereotypes. These social images or prejudices against specific groups can inhibit the personal growth of individuals, e.g., sociodemographic characteristics influence the social image of nurses. Based on the forward-looking topic digitization, we examined and discussed the influences of sociodemographic characteristics and motives of hospital nurses on technical readiness to gain insights into the digitization process in hospital nursing. (2) Methods: As part of an online survey on technical readiness among German hospital nurses, we particularly examined sociodemographic influences on technical readiness and the relationship between sociodemographic characteristics and professional motives. Furthermore, we included a qualitative analysis of optional comment fields. (3) Results: The analysis included 295 responses. Age and gender had a significant influence on technical readiness. Furthermore, the importance of motives differed between gender and age. The analysis of the comments produced three categories specifying our results: beneficial experiences, obstructive experiences and further conditions. (4) Conclusions: In general, the nurses showed high technical readiness. In order to gain high motivation for digitization and promote personal growth, special targeting and cooperation between gender and age groups can be beneficial. However, there are more sites at system level, such as funding, cooperation and consistence.

[Nursing home-sensitive conditions and approaches to reduce hospitalization of nursing home residents]. / Pflegeheim-sensitive Krankenhausfälle und Ansätze zur Verringerung der Hospitalisierung von Pflegeheimbewohnerinnen und -bewohnern.

BACKGROUND: Interventions to reduce potentially risky hospitalizations among nursing home residents are highly relevant for patient safety and quality improvement. A catalog of nursing home-sensitive conditions (NHSCs) grounds the policy recommendations and interventions. METHODS: In two previous research phases, an expert panel developed a catalog of 58 NHSCs using an adapted Delphi-procedure (the RAND/UCLA Appropriateness Method). This procedure was developed by the North American non-profit Research and Development Organisation (RAND) and clinicians of the University of California in Los Angeles (UCLA). We present the third phase of the project focused on the development of interventions to reduce NHSCs starting with an expert workshop. The workshop results were then evaluated by six experts from related sectors, supplemented, and systematically used to produce recommendations for action. Possible implementation obstacles were considered and the time horizon of effectiveness was estimated. RESULTS: The recommendations address communication, cooperation, documentation and care competence as well as facility-related, financial, and legal aspects. Indication bundles demonstrate the relevance for the German healthcare system. To increase effectiveness, the experts advise a meaningful combination of individual recommendations. DISCUSSION: By optimizing multidisciplinary communication and cooperation, combined with an- also digital - expansion of the infrastructure and the creation of institution-specific and legal prerequisites as well as remuneration structures, an estimated 35% of all hospitalizations, approximately 220,000 hospitalizations for Germany, could be prevented. The implementation expenditure could be refinanced by avoided hospitalization savings amounting to 768 million euros.

[Patients' Use of Digital Innovations in the Care Process: A Scoping Review]. / Nutzung digitaler Innovationen durch Patient*innen im Versorgungsprozess ­ Ein Scoping Review.

BACKGROUND: Digital innovations in healthcare continue to be extensively researched and publicly discussed. The research perspective is often indication-specific or process-oriented and focuses on an application by health professionals in care settings. From the patient's perspective, there are additional digital innovations and opportunities for use that take place privately in addition to sectoral care services. AIM: The aim of this scoping review was to map digital innovations currently available for patients and their possible applications in the care process by exploring the following question: Which digital innovations are currently available for patients in health care? MATERIAL AND METHODS: A systematic literature search in four databases helped identify 44 international publications as relevant for our analysis. They were categorized and analyzed according to the types of digital innovations, their use by patients, and their location within the care process. In addition, the intentions whereby digital innovations can be applied were discussed. RESULTS: We found that current research was focused on patient-applied digital innovations in the therapeutic field, and a broad application spectrum of interfaces for digital care was emerging. These included apps, smart devices, teleconsultation, patient portals, games, implants, robotics, intelligent information and communication systems, and ambient assisted living environments. CONCLUSION: Many digitally supported health applications are designed to be used exclusively by patients themselves, or are performed in only partial interaction with providers. In this respect, the active participation and personal responsibility of patients in the treatment process could be strengthened with the help of digital innovations.

Smartphone Use and Security Challenges in Hospitals: A Survey among Resident Physicians in Germany.

Although mobile devices support physicians in a variety of ways in everyday clinical practice, the use of (personal) mobile devices poses potential risks for information security, data protection, and patient safety in hospitals. We used a cross-sectional survey-based study design to assess the current state of smartphone use among resident physicians in hospitals and to investigate the relationships between working conditions, current smartphone usage patterns, and security-related behavior. In total, data from 343 participating physicians could be analyzed. A large majority (98.3%) used their smartphones during clinical practice. Of the respondents who used a smartphone during clinical practice, only 4.5% were provided with a smartphone by their employer. Approximately three-quarters of the respondents who used their smartphones for professional communication never/almost never used dedicated GDPR-compliant messenger services. Using a hierarchical regression model, we found a significant effect of the organizational resources Social Support (Supervisor) and Information Security-related Communication on security-related behavior during the selection of medical apps (App Selection). Smartphones are an important part of digital support for physicians in everyday clinical practice. To minimize the risks of use, technical and organizational measures should be taken by the hospital management, resulting, for example, in a Bring-Your-Own-Device (BYOD) initiative.

Nursing Home-Sensitive Hospitalizations and the Relevance of Telemedicine: A Scoping Review.

The aging of society is increasing the number of hospitalizations of nursing home residents. Telemedicine might help reduce the frequency of these potentially risk-associated hospitalizations. This scoping review looked for evidence of a change in the rate of hospitalization and, if mentioned, any cost savings and/or staff acceptance of the use of telemedicine in a nursing home setting. To identify available evidence, the electronic databases PubMed, Livivo, EBSCO and JSTOR were searched (without time or regional constraints) for comparative primary research studies on this topic in peer-reviewed journals. A total of 1127 articles were retrieved and 923 titles and abstracts were screened, with 16 studies published between 2001 and 2022 being included. Telemedicine consultation reduced the hospitalization of nursing home residents in 14/16 and care costs in 8/11 articles. Staff satisfaction was mentioned positively in five studies. Most studies used telemedicine involving medical diagnostic technologies (10), (electronic) health records (9), specialists (9) and specialized nursing staff (11). Few studies had a higher level of evidence: only one randomized clinical trial was included. There is the need for high credibility studies, using guidelines on protocol and reporting, to better understand the hindering and facilitating factors of telemedicine provision in the healthcare of nursing home residents.

Planetary Health and Hospitals' Contribution-A Scoping Review.

Climate change is one of the greatest global threats for planetary and human health. This leads to new challenges for public health. Hospitals emit large amounts of greenhouse gases (GHG) in their healthcare delivery through transportation, waste and other resources and are considered as key players in reducing healthcare's environmental footprint. The aim of this scoping review is to provide the state of research on hospitals' carbon footprint and to determine their contribution to mitigating emissions. We conducted a systematic literature search in three databases for studies related to measurement and actions to reduce GHG emissions in hospitals. We identified 21 studies, the oldest being published in 2012, and the most recent study in 2021. Eight studies focused on GHG emissions hospital-wide, while thirteen studies addressed hospital-based departments. Climate actions in the areas of waste and transportation lead to significant reductions in GHG emissions. Digital transformation is a key factor in implementing climate actions and promoting equity in healthcare. The increasing number of studies published over time indicates the importance of the topic. The results suggest a need for standardization of measurement and performance indicators on climate actions to mitigate GHG emissions.

Digitization in Everyday Nursing Care: A Vignette Study in German Hospitals.

(1) Background: Digitization in hospital nursing promises to transform the organization of care processes and, therefore, provide relief to nurse staffing shortages. While technological solutions are advanced and application fields numerous, comprehensive implementation remains challenging. Nursing leadership is crucial to digital change processes. This vignette study examined the effects of the motives and values on nurses' motivation to use innovative technologies. (2) Methods: We asked hospital nurses in an online vignette study to assess a fictitious situation about the introduction of digital technology. We varied the devices on the degree of novelty (tablet/smart glasses), addressed motives (intrinsic/extrinsic), and values (efficiency/patient orientation). (3) Results: The analysis included 299 responses. The tablet vignettes caused more motivation than those of the smart glasses (Z = -6.653, p < 0.001). The dataset did not show significant differences between intrinsic and extrinsic motives. The nursing leader was more motivating when emphasizing efficiency rather than patient orientation (Z = -2.995, p = 0.003). (4) Conclusions: The results suggest efficiency as a motive for using known digital technologies. The nursing staff's willingness to use digital technology is generally high. Management actions can provide a structural framework and training so that nursing leaders can ensure their staff's engagement in using also unknown devices.

Donating Health Data to Research: Influential Characteristics of Individuals Engaging in Self-Tracking.

Health self-tracking is an ongoing trend as software and hardware evolve, making the collection of personal data not only fun for users but also increasingly interesting for public health research. In a quantitative approach we studied German health self-trackers (N = 919) for differences in their data disclosure behavior by comparing data showing and sharing behavior among peers and their willingness to donate data to research. In addition, we examined user characteristics that may positively influence willingness to make the self-tracked data available to research and propose a framework for structuring research related to self-measurement. Results show that users' willingness to disclose data as a "donation" more than doubled compared to their "sharing" behavior (willingness to donate = 4.5/10; sharing frequency = 2.09/10). Younger men (up to 34 years), who record their vital signs daily, are less concerned about privacy, regularly donate money, and share their data with third parties because they want to receive feedback, are most likely to donate data to research and are thus a promising target audience for health data donation appeals. The paper adds to qualitative accounts of self-tracking but also engages with discussions around data sharing and privacy.

Social Media Mining of Long-COVID Self-Medication Reported by Reddit Users: Feasibility Study to Support Drug Repurposing.

BACKGROUND: Since the beginning of the COVID-19 pandemic, over 480 million people have been infected and more than 6 million people have died from COVID-19 worldwide. In some patients with acute COVID-19, symptoms manifest over a longer period, which is also called "long-COVID." Unmet medical needs related to long-COVID are high, since there are no treatments approved. Patients experiment with various medications and supplements hoping to alleviate their suffering. They often share their experiences on social media. OBJECTIVE: The aim of this study was to explore the feasibility of social media mining methods to extract important compounds from the perspective of patients. The goal is to provide an overview of different medication strategies and important agents mentioned in Reddit users' self-reports to support hypothesis generation for drug repurposing, by incorporating patients' experiences. METHODS: We used named-entity recognition to extract substances representing medications or supplements used to treat long-COVID from almost 70,000 posts on the "/r/covidlonghaulers" subreddit. We analyzed substances by frequency, co-occurrences, and network analysis to identify important substances and substance clusters. RESULTS: The named-entity recognition algorithm achieved an F1 score of 0.67. A total of 28,447 substance entities and 5789 word co-occurrence pairs were extracted. "Histamine antagonists," "famotidine," "magnesium," "vitamins," and "steroids" were the most frequently mentioned substances. Network analysis revealed three clusters of substances, indicating certain medication patterns. CONCLUSIONS: This feasibility study indicates that network analysis can be used to characterize the medication strategies discussed in social media. Comparison with existing literature shows that this approach identifies substances that are promising candidates for drug repurposing, such as antihistamines, steroids, or antidepressants. In the context of a pandemic, the proposed method could be used to support drug repurposing hypothesis development by prioritizing substances that are important to users.

[Expectations of generation Y for digital health innovations]. / Erwartungen der Generation Y an digitale Gesundheitsinnovationen.

BACKGROUND AND AIM: "Generation Y" is the term used to describe younger adults born between approximately 1980 and 2000. The generation is attributed with being digitally savvy and technically adept. It can thus be assumed that there is an increased desire among these people to use digital healthcare innovations when needed. However, the exact expectations in this regard are largely unknown. The aim of this study is to examine the expectations and needs of Generation Y in more detail. MATERIALS AND METHODS: For data collection, five focus group interviews were conducted in April 2021, each with six people between 23 and 36 years of age, with three people per group working in the health sector. The interview material was analyzed using content analysis according to Mayring. RESULTS: One of the expectations among respondents was to use low-threshold digital healthcare innovations. There was also a great demand for health information. The focus was on increasing efficiency in everyday life, in particular a reduction in the amount of time required. Influences of the corona pandemic on expectations were observed. DISCUSSION: Three functions of digital applications emerge as particularly relevant: "administration," "tracking," and "information." For these, preference profiles of Generation Y were created. Customized solutions offered by digital innovations could help to implement target-group-specific health promotion and prevention more concretely and generate added value for Generation Y. Since the everyday life of the target group is already characterized by digitization and digital innovations, there is great potential here.

Supporting family care: a scoping app review.

BACKGROUND: Mobile applications (apps) may provide family caregivers of people with chronic diseases and conditions with access to support and good information. However, thorough understanding of how these apps meet the main needs and requirements of the users is currently lacking. The aim of this study was to review the currently available apps for family caregivers and evaluate their relevance to main domains of caregiving activities, caregivers' personal needs, and caregivers' groups found in previous research on family caregivers. METHODS: We conducted a scoping review on English-language and German-language apps for family caregivers on two major app stores: Google Play Store and iOS App Store. Apps were included if the main target group were family caregivers. Data were extracted from the app descriptions provided by the app producers in the app stores. RESULTS: The majority of the apps was designed to assist caregivers in their caregiving activities. Apps were rarely tailored to specific groups of family caregivers such as young carers and their needs. Further, apps addressing caregivers' personal health, financial security, and work issues were scarce. Commercial apps dominated the market, often intermediating paid services or available for users of specific hardware. Public and non-profit organizations provided best-rated and free-of-charge apps but had a very limited range of services with focus on caregivers' health and training. CONCLUSIONS: Our results indicate that current apps for family caregivers do not distinguish specific groups of family caregivers, also they rarely address caregivers' personal needs.

How can Big Data Analytics Support People-Centred and Integrated Health Services: A Scoping Review.

Introduction: Health systems in high-income countries face a variety of challenges calling for a systemic approach to improve quality and efficiency. Putting people in the centre is the main idea of the WHO model of people-centred and integrated health services. Integrating health services is fuelled by an integration of health data with great potentials for decision support based on big data analytics. The research question of this paper is "How can big data analytics support people-centred and integrated health services?" Methods: A scoping review following the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses - Scoping Review (PRISMA-ScR) statement was conducted to gather information on how big data analytics can support people-centred and integrated health services. The results were summarized in a role model of a people-centred and integrated health services platform illustrating which data sources might be integrated and which types of analytics might be applied to support the strategies of the people-centred and integrated health services framework to become more integrated across the continuum of care. Additional rapid literature reviews were conducted to generate frequency distributions of the most often used data types and analytical methods in the medical literature. Finally, the main challenges connected with big data analytics were worked out based on a content analysis of the results from the scoping literature review. Results: Based on the results from the rapid literature reviews the most often used data sources for big data analytics (BDA) in healthcare were biomarkers (39.3%) and medical images (30.9%). The most often used analytical models were support vector machines (27.3%) and neural networks (20.4%). The people-centred and integrated health services framework defines different strategic interventions for health services to become more integrated. To support all aspects of these interventions a comparably integrated platform of health-related data would be needed, so that a role model labelled as people-centred health platform was developed. Based on integrated data the results of the scoping review (n = 72) indicate, that big data analytics could for example support the strategic intervention of tailoring personalized health plans (43.1%), e.g. by predicting individual risk factors for different therapy options. Also BDA might enhance clinical decision support tools (31.9%), e.g. by calculating risk factors for disease uptake or progression. BDA might also assist in designing population-based services (26.4% by clustering comparable individuals in manageable risk groups e.g. mentored by specifically trained, non-medical professionals. The main challenges of big data analytics in healthcare were categorized in regulatory, (information-) technological, methodological, and cultural issues, whereas methodological challenges were mentioned most often (55.0%), followed by regulatory challenges (43.7%). Discussion: The BDA applications presented in this literature review are based on findings which have already been published. For some important components of the framework on people-centred care like enhancing the role of community care or establishing intersectoral partnerships between health and social care institutions only few examples of enabling big data analytical tools were found in the literature. Quite the opposite does this mean that these strategies have less potential value, but rather that the source systems in these fields need to be further developed to be suitable for big data analytics. Conclusions: Big data analytics can support people-centred and integrated health services e.g. by patient similarity stratifications or predictions of individual risk factors. But BDA fails to unfold its full potential until data source systems are still disconnected and actions towards a comprehensive and people-centred health-related data platform are politically insufficiently incentivized. This work highlighted the potential of big data analysis in the context of the model of people-centred and integrated health services, whereby the role model of the person-centered health platform can be used as a blueprint to support strategies to improve person-centered health care. Likely because health data is extremely sensitive and complex, there are only few practical examples of platforms to some extent already capable of merging and processing people-centred big data, but the integration of health data can be expected to further proceed so that analytical opportunities might also become reality in the near future.