bluuebunny/crossref_metadata_2025_split huggingface dataset:
UROLATAM Project: A multidisciplinary comprehensive care project for prostate cancer
Authors: Viñas Dozal J , Autrán Gómez A M , Mondragon Delgado M J , Palmeros Exome C , Hurtado Capetillo J M , Ruiz Garcia F , Torres Hernandez R M , Hernandez Ojeda H , Ricardez Espinoza A A , Villegas-Dominguez J E 
Published: October 2024

Abstract

Introduction
Prostate Cancer (PCa) represents a health problem in the world and its management is heterogeneous in care, depending on the resources each country has, modifying its effectiveness in prevention, diagnosis, treatment and follow-up.

Methods
The UROLATAM program was implemented based on the Design Thinking quadruple helix innovation model, consisting of the immersion, design, idea and prototype phases, characterized by being multidisciplinary and comprehensive. Teachers and students from different careers at the Universidad Veracruzana participated. Linkages were made with: Local government, government health institutions, colleges of specialist doctors, private institutions and civil society. This program was broadcast on radio, television and social networks inviting the population to participate in education and prevention activities, in addition to participating in diagnosis, treatment and follow-up actions for men over 40 years of age. The duration of the program was 4 days, including educational sessions for doctors, patients, family members and caregivers, as well as determination of prostate-specific antigen, urological consultation and prostate ultrasound, as well as rehabilitation exercises, diagnostic confirmation and treatment. who needed it.

Results
During the sessions, 944 patients aged 60.7 (±15.0) years were treated, 443 (47%) had never received a urological consultation, identifying a prevalence of 11.7% of Cap. The human team present with the patient was 25 specialist doctors, 16 medical residents, 38 undergraduate students, 3 rehabilitators and 6 administrative staff. None of the participants received a salary for participating in this project.

Conclusions
The multidisciplinary UROLATAM linkage project constitutes a useful educational, training and assistance tool for the population, as well as an educational element for the students who are part of the work team.

Key messages
• The UROLATAM project is replicable in countries that require additional support in the prostate cancer approach.
• The structure of the UROLATAM project can be replicated to address other public health problems.
‘Freeze the measles’: how to improve backward tracing with a new digital tool
Authors: Daole A , Giorgi S , Bonaldo L , Cruschelli G , Spagnolo G , Gallo A , Rizzo C 
Published: October 2024

Abstract

Background
A measles outbreak occurred in Tuscany, between January and April 2024. There were 37 cases (Incidence: 40,5 per million) with 32 cases (24 confirmed) in the Health District of Pisa. Even if bidirectional tracing showed a better effectiveness in pandemics, there aren’t ready-to-use standardized tools for backward tracing.

Methods
Pisa Public Health Unit created a digital tool based on a spreadsheet and called “Freeze the measles” which records measles cases and the locations where they passed through (hotspots). These were uploaded on a cloud shared with all the tracers. Hotspots have an expiry date of 21 days. Hotspots and home address case were plotted on a digital map. In a new investigation, tracers could find out if the case visited some hotspots before getting sick and check the distance between home address and hotspots, reducing recall bias. Every case was interviewed about 21 days before rash onset (backward) and plus or minus 4 days of rash onset (forward). The tool matched data to identify contacts and exposure.

Results
Since the index case wasn’t found, the first 5 unrelated cases were considered index cases for this outbreak. Second and third wave involved 17 cases. The tool allows to find an epidemiological link for 16 of them, while 1 case remained unrelated. A super-spreader was identified with 12 secondary cases occurred at hospital emergency room (7), at a near home minimarket (4) and in a large furniture store (1). In second and third waves, tool was able to link 94% of cases. 2 additional cases were imported. When the last hotspot became frozen without new cases occurring, the outbreak was considered ended. The outbreak lasted 33 days.

Conclusions
The “Freeze the measles” tool allows to identify transmission chains through an interactive map built on cases and their mobility.

Key messages
• Contact tracing needs an appropriate backward investigation to be more effective.
• New digital tools as ‘Freeze the measles’ could improve preparedness and management of outbreaks.
Adoption and Utilization of Telemedicine and Digital Health Services among Older Adults in Israel
Authors: Haimi M , Sergienko R 
Published: October 2024

Abstract

Background
As the population ages and the prevalence of long-term diseases rises, telecare is being used increasingly frequently to aid elderly people.

Aims
We aimed to explore the usage and adoption of 3 types of telehealth services among the senior population in Israel- prior, during, and after the COVID-19 pandemic rise in Israel.

Methods
We explored the usage characteristics of older adults (age 65 and above) belonging to ‘Clalit’, in the use of three types of telehealth services: digital services for administrative tasks, synchronous ‘online visits’ with the patient’s personal physician during clinic business hours, and ‘afterhours’ consultations during evenings, nights, and weekends. The data was collected and analyzed throughout three distinct time periods in Israel: before the COVID-19 pandemic, during the onset of the COVID-19 pandemic and following the COVID-19 ‘peak’.

Results
Data of 618850 patients who met the inclusion criteria was extracted. Telehealth services utilized for administrative purposes were the most popular. The older population significantly increased their use of all types of telehealth services during the COVID-19 period, and in the majority of types, this usage decreased after the COVID-19 peak, but to a level that was higher than the baseline level prior to the COVID-19 period. Prior to the COVID-19 period, 23.1% of the study population used ‘online visits’, and 2.2% used ‘afterhours’ consultations, at least once. The percentage of usage for these services increased during the COVID-19 period to 59.2% and 5.0%, and then decreased during the third period to 39.5% and 2.4%, respectively (P &lt; 0.001). Multiple patient variables have been found to be associated with the use of the different telehealth services, in each time-period.

Conclusions
The senior population uses telehealth services, and can increase their consumption, when they are needed. Suitable and straightforward telehealth solutions tailored for this population should be created.

Key messages
• The senior population uses telehealth services, and can increase their consumption, when they are needed.
• Suitable and straightforward telehealth solutions tailored for this population should be created.
User technology for AI-supported objective measurement of Work-related Quality of Life (MI-LQ)
Authors: Schreiber C , Geisler M , Voigt J , Kosakyan H , Hohn J , Hamm A , Mut E , Burkhardt J M , Braumann U D , Militzer-Horstmann C 
Published: October 2024

Abstract

Background
Understanding and enhancing job satisfaction is crucial for improving Work-Related Quality of Life (WrQoL) in today’s office work environments. Our work uses multimodal data collection and analysis techniques to objectively assess WrQoL, thus mitigating respondent bias and survey fatigue. Leveraging machine learning (ML) and automated methods measuring WrQoL presents a promising approach in public health research, particularly concerning stress-related health outcomes.

Methods
Through a systematic literature search of 9,242 publications to identify WrQoL indicators, we selected over 100 publications for data extraction. A base model, including workload, commute, overtime, valence, and arousal was formulated. To amass a wide data set, Objective measurement tools (computers, smartphones, and wearables) complemented by questionnaire data. This data will inform ML algorithms to predict individual WrQoL indicators. Developed as an input/output data platform, an app-prototype will objectively assess WrQoL, facilitating a field study with office workers to refine the model. A mobile app prototype serves as a user interface and data relay for WrQoL metric analysis.

Results
Our research develops instruments for measuring WrQoL using smartphones, wearables, and specialized trackers for heart rate variability (HRV) analysis, alongside a software prototype for keyboard and mouse tracking for workload assessment of valence and arousal. Fitness trackers with photoplethysmography functionality are favored for HRV assessment.

Conclusions
The systematic search identified influences on WrQoL, translated into measurable indicators in a base model. Leveraging user tech for assessment and a ML and mobile app framework, this approach facilitates objective WrQoL determination. By presenting the relationship between digital service use and WrQoL indicators, this methodology promises new insights, informing stress and burnout prevention strategies within public health initiatives.

Key messages
• Progressive approach: ML-driven WrQoL assessment offers promising avenues for stress prevention in workplace health research.
• Methodological Advancement: The novel framework for WrQoL assessment using digital tools contributes to effective workplace health promotion strategies, with potential for tailored interventions.
Leveraging digital adherence technologies to enhance public health: insights from TB care in Ukraine
Authors: Kochanov V , Bogdanov A , Karpiuk K , Rodyna R , Germanovych M , Dravniece G 
Published: October 2024

Abstract

Background
Effective tuberculosis (TB) care is vital for public health, especially in war-affected Ukraine. In response to the complex healthcare delivery landscape, where traditional directly observation treatment methods became impractical, digital adherence technologies (DATs) emerged as a promising solution, offering more autonomy for people, and remote monitoring capabilities for healthcare providers.

Intervention
The PATH-led USAID-funded Support TB Control Efforts in Ukraine (STBCEU) project implemented smart pill boxes in eleven Ukrainian regions. These devices equipped with built-in reminders helped people adhere to their medication regimen, and signaled healthcare providers when the box was opened.

Results
Since April 2022, STBCEU has supported 2,022 people with TB who used smart pill boxes during their treatment, including 489 (24%) with drug-resistant TB (DR-TB). A total of 482 people continue utilizing boxes. Of 1,540 people with TB who completed the use of boxes, 1,207 people (78%) successfully completed TB treatment with an average of 84% treatment adherence rate digitally reported by the technology.

Conclusions
The integration of smart pill boxes in TB management has enhanced people-centered care, ensuring treatment continuity even in challenging circumstances and providing healthcare providers with real-time adherence data. The innovation contributed to TB control efforts and health equity through expanding opportunities for people to choose their treatment model based on their needs, available resources and community support programs. Leveraging digital solutions proved to be essential in strengthening healthcare systems. In the realm of TB management, DATs enhance differentiated care, embodying a harmonious integration of technology automation and provider interventions.

Key messages
• Integration of smart pill boxes enhanced patient-centered care, providing real-time adherence data and empowering individuals to choose personalized treatment models.
• Digital technologies like smart pill boxes transformed TB care, offering tailored support for patients and remote monitoring capabilities for healthcare providers even in challenging circumstances.
International case studies: success and failure factors for digital transformation in healthcare
Authors: Kraft L , Brecher A L , Sgraja S , Amelung V E 
Published: October 2024

Abstract

Background
The digitalization of healthcare systems is expected to lead to improvements in the quality and efficiency of healthcare services. Despite Germany’s leading economic and technological position, the implementation and utilization of digital health solutions is lagging far behind internationally. A look at other countries shows that the digital transformation in healthcare can be successful, and that financial resources and available technologies are not the only determining factors. Rather, it is a matter of political processes, the interests of different stakeholders and the acceptance of patients and HCPs.

Methods
While the impression often arises that the selection of countries in case studies is random, eight international case studies were identified using a scientific method. A systematic and multi-stage process was developed to select the case studies, taking into account various relevant criteria (e.g. degree of digitalization, geography, economy). The implementation and use of various digital health tools will be examined in selected countries and healthcare systems, in which the digitalization of the healthcare system is particularly advanced. Semi-structured interviews will be conducted with experts from the international healthcare systems between fall 2024 and summer 2025. The findings will inform the development of recommendations for actions for policymakers in Germany.

Conclusions
This study aims to provide new insights into the key success and failure factors for the digital transformation of healthcare systems. Recommendations for action, tailored specifically to the German healthcare system and aimed at policymakers, are intended to support decision-makers in setting the course for a successful further transformation towards digital health.

Key messages
• International case studies will be used to identify factors that contribute to the success or failure of digital transformation in healthcare systems.
• Based on the findings of this research, recommendations for action will be developed for policymakers in Germany to set the course for the successful further digitalization of healthcare.
Discrepancies in breast cancer screening and hypothesis of artificial intelligence support
Authors: Riccardi M T , Rosca V , Forestiero F , Rudniki T , Testa A , Cerone G , Rossi E , Trinito M O 
Published: October 2024

Abstract

In Italy,the National Breast Screening Programme offers mammography as the 1st level examination, blindly assessed by two radiologists.In the context of continuous quality control,discrepancies in the assessment of mammograms between the 1st and 2nd reader have been studied,focusing on the most significant ones.The aims of the present study are:to evaluate the outcome of women sent to the 2nd level of review;to evaluate the possibility of using artificial intelligence (AI) software to assist radiologists in case of discrepancies. In the Local Health Authority Roma2,radiologists use a standardised classification that rates radiographs on a five-level scale from R1 to R5:R1=no abnormalities,R2=benign findings,R3=equivocal findings,R4=suspected cancer,R5=strongly suspected cancer.Data were extracted from the mammograms performed in 2023 that showed discrepancies (R1/R2 vs. R4/R5).2nd level mammography≥R4 and 2nd level histology≥B4 were considered positive. For the second aim,”IA Lunit INSIGHT” software was used to create specific target groups using the following cut-offs:G1&lt;10%, G2 11-29%; G3 30-59%; G4 60-85%; G5 86-100%(groups ≥G3 were considered positive). Of the 36,339 mammograms,524(1.5%) were discordant:347(66.2%) were considered suspicious by the second radiologist.49(9.4%) were confirmed positive by Level II mammography and 23(4.4%) reported histology≥B4. The AI red a random sample of 247 mammograms and classified 34 women as positive (1 G5, 6 G4, 9 G3), of whom 11 (4.5%) were confirmed positive by Level II mammography and 6 (2.4%) were histologically positive. Of the negative women, 2 had histology≥B4. Discrepancies may be one of the factors leading to inappropriate referral to second level investigation. In such cases, the use of AI may improve the appropriateness of further investigation, although this hypothesis needs to be tested in larger numbers, with additional comparisons with experienced radiologists and consideration of retraining.

Key messages
• Continuous monitoring in cancer screening programs are vital to assure a sustainability of the process.
• Artificial Intelligence software are promising in aiding health care professionals in case of discrepancies.
AI-Powered Post-Discharge Monitoring to Prevent Patients Readmissions and Reduce Workforce Burden
Authors: Santos M , Peyroteo M , Lapão L 
Published: October 2024

Abstract

Background
Patient readmission poses a significant burden on healthcare systems, straining resources, negatively impacting patient treatment, and it is often a Public Health problem. Traditional post-discharge follow-up methods, such as phone calls, often lack efficiency and personalization. Artificial intelligence (e.g., Machine Learning (ML)) offers a transformative approach that can potentially improve post-discharge care.

Methods
This scoping review aimed to map existing research on AI-powered solutions for post-discharge monitoring, focusing on their application in risk stratification and their potential for reducing hospital readmissions within a public health framework. Following PRISMA-ScR guidelines, a search was conducted across four databases using keywords related to AI, post-discharge, and risk stratification.

Results
Studies published between 2018 and January 2024 were included if they described the development and application of an ML model in a post-discharge setting for risk stratification. Sixteen studies met the inclusion criteria. Tree-based algorithms, particularly XGBoost, were the predominant ML approach, with promising performance metrics for readmission risk prediction.

Conclusions
However, limitations were identified, including restricted generalizability due to data source limitations and a lack of real-time implementation in many studies. This review highlights the potential of AI in post-discharge monitoring, particularly the use of ML for risk stratification, as a promising tool for public health contact tracing. While challenges remain regarding generalizability and real-world implementation, the findings suggest AI holds immense promise for improving post-discharge care, potentially reducing readmissions, and optimizing resource allocation. Future research with broader datasets and real-time applications can further solidify the role of AI in revolutionizing post-discharge care within public health systems.

Key messages
• This study shows the potential of AI and risk stratification in post-discharge monitoring, improving public health outcomes by reducing hospital readmissions and optimizing the healthcare workforce.
• This review highlights the value of AI in public health, particularly for improving post-discharge care through effective prediction of high-risk readmissions.
Development of an assessment process for digital medical devices in Austria
Authors: Laschkolnig A , Tanriverdi E , Dick D , Herzog A 
Published: October 2024

Abstract

Issue/problem
Digital medical devices have experienced a rapid development in recent years and are playing an increasingly important role in healthcare. These devices offer numerous benefits and can improve patient care. However, despite their potential benefits, the use of digital medical devices also poses risks and regulation from governmental side is needed from a Public Health Perspective. This is why some countries already implemented assessment processes for Digital Medical Devices (e.g. Germany and France) leading to the question how such a process could be established in Austria too.

Description of the problem
While digital medical devices must fulfil requirements set by the medical device regulation to enter market, several other aspects are of interests when offering digital medical devices in routine care. These include e.g. medical effectiveness, data security and interoperability. The objective of the ongoing pilot project is to develop a process for the assessment of quality-assured digital medical devices in Austria in 2024. For this, a combination of literature research, interviews and workshops with relevant stakeholders is used in order to gain all necessary information. Process and assessment criteria will be tested and revised in a pilot phase with several digital medical devices.

Results
At the end of the project, an assessment framework as well as a potential evaluation process will be designed in accordance with relevant stakeholders. Moreover, legals aspects and the potential integration into the austrian health telematics infrastrucutur will be assessed. This will form a basis for implementing digital medical devices within the austrian healthcare system.

Key messages
• The result of this project aims to build the basis for implementing an evaluation process for digital medical devices in Austria.
• The establishment of an evaluation process for digital medical devices supports the integration of quality assured digital medical devices in healthcare.
Global health resource distribution during COVID-19 and in future pandemics: Here’s what people say
Authors: Trutzenberg F , Hagel M L , Eid M 
Published: October 2024

Abstract

During the COVID-19 pandemic, countless individuals across the world needed novel and sophisticated health care resources simultaneously, leading to dramatic global shortages. How to distribute resources in such situations? This dilemma is neither new nor understudied: Its complexity is well known to medical ethicists, public health scientists and philosophers. Building on this knowledge, powerful global distribution frameworks were proposed already early into the pandemic. Despite this knowledge, no globally consensual regulations existed (and exist) on the political sphere. Worse still, numerous countries hoarded resources for themselves, increasing global inequalities and prolonging the pandemic for everyone. For future emergencies, it is thus necessary to develop immediately applicable strategies. Because public acceptance is key for such interventions, evidence on the public opinion towards allocation principles is strongly needed. In 2021, we asked representative samples of N = 2694 adults in England and Germany to rate seven COVID-19-specific global allocation principles. In line with literature on justice attitudes in general, extensions of bifactor(S-1) models showed that participants would have preferred a more equity- or equality-based global resource distribution during the pandemic, presenting themselves as more cosmopolitan than global leaders. Trying to understand these attitudes better, we tested preregistered hypotheses on relations with other constructs and found positive associations between equity- and equality-directed preferences and global human identification, among others. To ensure generalisability on future pandemics, we collected data from a second cohort in spring 2024. All results will be presented in detail. With their responses, European citizens call upon the development of fairer and more efficient global distribution mechanisms. This global public health perspective could inform preparations for future global emergencies.

Key messages
• European citizens would have preferred a more equity- or equality-based global distribution of scarce health care resources during the COVID-19 pandemic than global leaders organised.
• Citizens’ global perspective on public health and their strong emphasis on global fairness should inform preparations for future pandemics and other global emergencies.