Alpha-1-antitrypsin-deficiency is associated with lower cardiovascular risk: an approach based on federated learning.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is an inflammatory multisystemic disease caused by environmental exposures and/or genetic factors. Inherited alpha-1-antitrypsin deficiency (AATD) is one of the best recognized genetic factors increasing the risk for an early onset COPD with emphysema. The aim of this study was to gain a better understanding of the associations between comorbidities and specific biomarkers in COPD patients with and without AATD to enable future investigations aimed, for example, at identifying risk factors or improving care. METHODS: We focused on cardiovascular comorbidities, blood high sensitivity troponin (hs-troponin) and lipid profiles in COPD patients with and without AATD. We used clinical data from six German University Medical Centres of the MIRACUM (Medical Informatics Initiative in Research and Medicine) consortium. The codes for the international classification of diseases (ICD) were used for COPD as a main diagnosis and for comorbidities and blood laboratory data were obtained. Data analyses were based on the DataSHIELD framework. RESULTS: Out of 112,852 visits complete information was available for 43,057 COPD patients. According to our findings, 746 patients with AATD (1.73%) showed significantly lower total blood cholesterol levels and less cardiovascular comorbidities than non-AATD COPD patients. Moreover, after adjusting for the confounder factors, such as age, gender, and nicotine abuse, we confirmed that hs-troponin is a suitable predictor of overall mortality in COPD patients. The comorbidities associated with AATD in the current study differ from other studies, which may reflect geographic and population-based differences as well as the heterogeneous characteristics of AATD. CONCLUSION: The concept of MIRACUM is suitable for the analysis of a large healthcare database. This study provided evidence that COPD patients with AATD have a lower cardiovascular risk and revealed that hs-troponin is a predictor for hospital mortality in individuals with COPD.

[The Medical Informatics Initiative at a glance-establishing a health research data infrastructure in Germany]. / Die Medizininformatik-Initiative im Überblick ­ Aufbau einer Gesundheitsforschungsdateninfrastruktur in Deutschland.

The Medical Informatics Initiative (MII) funded by the Federal Ministry of Education and Research (BMBF) 2016-2027 is successfully laying the foundations for data-based medicine in Germany. As part of this funding, 51 new professorships, 21 junior research groups, and various new degree programs have been established to strengthen teaching, training, and continuing education in the field of medical informatics and to improve expertise in medical data sciences. A joint decentralized federated research data infrastructure encompassing the entire university medical center and its partners was created in the form of data integration centers (DIC) at all locations and the German Portal for Medical Research Data (FDPG) as a central access point. A modular core dataset (KDS) was defined and implemented for the secondary use of patient treatment data with consistent use of international standards (e.g., FHIR, SNOMED CT, and LOINC). An officially approved nationwide broad consent was introduced as the legal basis. The first data exports and data use projects have been carried out, embedded in an overarching usage policy and standardized contractual regulations. The further development of the MII health research data infrastructures within the cooperative framework of the Network of University Medicine (NUM) offers an excellent starting point for a German contribution to the upcoming European Health Data Space (EHDS), which opens opportunities for Germany as a medical research location.

[Development of competencies in the Medical Informatics Initiative (MII)-educational offers for a competent and secure handling of medical data]. / Kompetenzentwicklung in der Medizininformatik-Initiative (MII) ­ Lehrangebote für einen souveränen und sicheren Umgang mit medizinischen Daten.

In order to achieve the goals of the Medical Informatics Initiative (MII), staff with skills in the field of medical informatics and data science are required. Each consortium has established training activities. Further, cross-consortium activities have emerged. This article describes the concepts, implemented programs, and experiences in the consortia. Fifty-one new professorships have been established and 10 new study programs have been created: 1 bachelor's degree and 6 consecutive and 3 part-time master's degree programs. Further, learning and training opportunities can be used by all MII partners. Certification and recognition opportunities have been created.The educational offers are aimed at target groups with a background in computer science, medicine, nursing, bioinformatics, biology, natural science, and data science. Additional qualifications for physicians in computer science and computer scientists in medicine seem to be particularly important. They can lead to higher quality in software development and better support for treatment processes by application systems.Digital learning methods were important in all consortia. They offer flexibility for cross-location and interprofessional training. This enables learning at an individual pace and an exchange between professional groups.The success of the MII depends largely on society's acceptance of the multiple use of medical data in both healthcare and research. The information required for this is provided by the MII's public relations work. There is also an enormous need in society for medical and digital literacy.

[Interoperability Working Group: core dataset and information systems for data integration and data exchange in the Medical Informatics Initiative]. / Arbeitsgruppe Interoperabilität: Kerndatensatz und Informationssysteme für Integration und Austausch von Daten in der Medizininformatik-Initiative.

The interoperability Working Group of the Medical Informatics Initiative (MII) is the platform for the coordination of overarching procedures, data structures, and interfaces between the data integration centers (DIC) of the university hospitals and national and international interoperability committees. The goal is the joint content-related and technical design of a distributed infrastructure for the secondary use of healthcare data that can be used via the Research Data Portal for Health. Important general conditions are data privacy and IT security for the use of health data in biomedical research. To this end, suitable methods are used in dedicated task forces to enable procedural, syntactic, and semantic interoperability for data use projects. The MII core dataset was developed as several modules with corresponding information models and implemented using the HL7® FHIR® standard to enable content-related and technical specifications for the interoperable provision of healthcare data through the DIC. International terminologies and consented metadata are used to describe these data in more detail. The overall architecture, including overarching interfaces, implements the methodological and legal requirements for a distributed data use infrastructure, for example, by providing pseudonymized data or by federated analyses. With these results of the Interoperability Working Group, the MII is presenting a future-oriented solution for the exchange and use of healthcare data, the applicability of which goes beyond the purpose of research and can play an essential role in the digital transformation of the healthcare system.

PREDICT-juvenile-stroke: PRospective evaluation of a prediction score determining individual clinical outcome three months after ischemic stroke in young adults - a study protocol.

BACKGROUND: Although of high individual and socioeconomic relevance, a reliable prediction model for the prognosis of juvenile stroke (18-55 years) is missing. Therefore, the study presented in this protocol aims to prospectively validate the discriminatory power of a prediction score for the 3 months functional outcome after juvenile stroke or transient ischemic attack (TIA) that has been derived from an independent retrospective study using standard clinical workup data. METHODS: PREDICT-Juvenile-Stroke is a multi-centre (n = 4) prospective observational cohort study collecting standard clinical workup data and data on treatment success at 3 months after acute ischemic stroke or TIA that aims to validate a new prediction score for juvenile stroke. The prediction score has been developed upon single center retrospective analysis of 340 juvenile stroke patients. The score determines the patient's individual probability for treatment success defined by a modified Rankin Scale (mRS) 0-2 or return to pre-stroke baseline mRS 3 months after stroke or TIA. This probability will be compared to the observed clinical outcome at 3 months using the area under the receiver operating characteristic curve. The primary endpoint is to validate the clinical potential of the new prediction score for a favourable outcome 3 months after juvenile stroke or TIA. Secondary outcomes are to determine to what extent predictive factors in juvenile stroke or TIA patients differ from those in older patients and to determine the predictive accuracy of the juvenile stroke prediction score on other clinical and paraclinical endpoints. A minimum of 430 juvenile patients (< 55 years) with acute ischemic stroke or TIA, and the same number of older patients will be enrolled for the prospective validation study. DISCUSSION: The juvenile stroke prediction score has the potential to enable personalisation of counselling, provision of appropriate information regarding the prognosis and identification of patients who benefit from specific treatments. TRIAL REGISTRATION: The study has been registered at https://drks.de on March 31, 2022 ( DRKS00024407 ).

Representation of evidence-based clinical practice guideline recommendations on FHIR.

BACKGROUND: Various formalisms have been developed to represent clinical practice guideline recommendations in a computer-interpretable way. However, none of the existing formalisms leverage the structured and computable information that emerge from the evidence-based guideline development process. Thus, we here propose a FHIR-based format that uses computer-interpretable representations of the knowledge artifacts that emerge during the process of evidence-based guideline development to directly serve as the basis of evidence-based recommendations. METHODS: We identified the information required to represent evidence-based clinical practice guideline recommendations and reviewed the knowledge artifacts emerging during the evidence-based guideline development process. We then conducted a consensus-based design process with domain experts to develop an information model for guideline recommendation representation that is structurally aligned to the evidence-based guideline recommendation development process and a corresponding representation based on FHIR resources developed for evidence-based medicine (EBMonFHIR). The resulting recommendations were modelled and represented in conformance with the FHIR Clinical Guidelines (CPG-on-FHIR) implementation guide. RESULTS: The information model of evidence-based clinical guideline recommendations and its EBMonFHIR-/CPG-on-FHIR-based representation contain the clinical contents of individual guideline recommendations, a set of metadata for the recommendations, the ratings for the recommendations (e.g., strength of recommendation, certainty of overall evidence), the ratings of certainty of evidence for individual outcomes (e.g., risk of bias) and links to the underlying evidence (systematic reviews based on primary studies). We created profiles and an implementation guide for all FHIR resources required to represent the knowledge artifacts generated during evidence-based guideline development and their re-use as the basis for recommendations and used the profiles to implement an exemplary clinical guideline recommendation. CONCLUSIONS: The FHIR implementation guide presented here can be used to directly link the evidence assessment process of evidence-based guideline recommendation development, i.e. systematic reviews and evidence grading, and the underlying evidence from primary studies to the resulting guideline recommendations. This not only allows the evidence on which recommendations are based on to be evaluated transparently and critically, but also enables guideline developers to leverage computable evidence in a more direct way to facilitate the generation of computer-interpretable guideline recommendations.

Automated Monitoring of Adherence to Evidenced-Based Clinical Guideline Recommendations: Design and Implementation Study.

BACKGROUND: Clinical practice guidelines are systematically developed statements intended to optimize patient care. However, a gapless implementation of guideline recommendations requires health care personnel not only to be aware of the recommendations and to support their content but also to recognize every situation in which they are applicable. To not miss situations in which recommendations should be applied, computerized clinical decision support can be provided through a system that allows an automated monitoring of adherence to clinical guideline recommendations in individual patients. OBJECTIVE: This study aims to collect and analyze the requirements for a system that allows the monitoring of adherence to evidence-based clinical guideline recommendations in individual patients and, based on these requirements, to design and implement a software prototype that integrates guideline recommendations with individual patient data, and to demonstrate the prototype's utility in treatment recommendations. METHODS: We performed a work process analysis with experienced intensive care clinicians to develop a conceptual model of how to support guideline adherence monitoring in clinical routine and identified which steps in the model could be supported electronically. We then identified the core requirements of a software system to support recommendation adherence monitoring in a consensus-based requirements analysis within the loosely structured focus group work of key stakeholders (clinicians, guideline developers, health data engineers, and software developers). On the basis of these requirements, we designed and implemented a modular system architecture. To demonstrate its utility, we applied the prototype to monitor adherence to a COVID-19 treatment recommendation using clinical data from a large European university hospital. RESULTS: We designed a system that integrates guideline recommendations with real-time clinical data to evaluate individual guideline recommendation adherence and developed a functional prototype. The needs analysis with clinical staff resulted in a flowchart describing the work process of how adherence to recommendations should be monitored. Four core requirements were identified: the ability to decide whether a recommendation is applicable and implemented for a specific patient, the ability to integrate clinical data from different data formats and data structures, the ability to display raw patient data, and the use of a Fast Healthcare Interoperability Resources-based format for the representation of clinical practice guidelines to provide an interoperable, standards-based guideline recommendation exchange format. CONCLUSIONS: Our system has advantages in terms of individual patient treatment and quality management in hospitals. However, further studies are needed to measure its impact on patient outcomes and evaluate its resource effectiveness in different clinical settings. We specified a modular software architecture that allows experts from different fields to work independently and focus on their area of expertise. We have released the source code of our system under an open-source license and invite for collaborative further development of the system.

A nationwide registry for recurrent urolithiasis in the upper urinary tract - The RECUR study protocol.

BACKGROUND: Urinary stone disease is a widespread disease with tremendous impact on those affected and on societies around the globe. Nevertheless, clinical and health care research in this area seem to lag far behind cardiovascular diseases or cancer. This may be due to the lack of an immediate deadly threat from the disease and therefore less public and professional interest. However, the patients suffer from recurring, sometimes intense pain and often must be treated in hospital. Long-term morbidity includes doubled rates of chronic kidney disease and arterial hypertension after at least one stone-related event. Observational studies, more specifically, registries and other electronic data sets have been proposed as a means of filling critical gaps in evidence. We propose a nationwide digital and fully automated registry as part of the German Ministry for Education and Research (BMBF) call for the "establishment of model registries". METHODS: RECUR builds on the technical infrastructure of Germany's Medical Informatics Initiative. Local data integration centres (DIC) of participating medical universities will collect pseudonymized and harmonized data from respective hospital information systems. In addition to their clinical data, participants will provide patient reported outcomes using a mobile patient app. Scientific data exploration includes queries and analysis of federated data from DICs of eleven participating sites. All primary patient data will remain at the participating sites at all times. With comprehensive data from this longitudinal registry, we will be able to describe the disease burden, to determine and validate risk factors, and to evaluate treatments. Implementation and operation of the RECUR registry will be funded by the BMBF for five years. Subsequently, the registry is to be continued by the German Society of Urology without significant costs for study personnel. DISCUSSION: The proposed registry will substantially improve the structural and procedural framework for patients with recurrent urolithiasis. This includes advanced diagnostic algorithms and treatment pathways. The registry will help us identify those patients who will most benefit from specific interventions to prevent recurrences. The RECUR study protocol and the registry's technical architecture including full digitalization and automation of almost all registry-associated proceedings can be transferred to future registries. TRIAL REGISTRATION: This study is registered at the German Clinical Trial Register (Deutsches Register Klinischer Studien), DRKS-ID DRKS00026923 , date of registration January, 11th 2022.

Visualization Techniques of Time-Oriented Data for the Comparison of Single Patients With Multiple Patients or Cohorts: Scoping Review.

BACKGROUND: Visual analysis and data delivery in the form of visualizations are of great importance in health care, as such forms of presentation can reduce errors and improve care and can also help provide new insights into long-term disease progression. Information visualization and visual analytics also address the complexity of long-term, time-oriented patient data by reducing inherent complexity and facilitating a focus on underlying and hidden patterns. OBJECTIVE: This review aims to provide an overview of visualization techniques for time-oriented data in health care, supporting the comparison of patients. We systematically collected literature and report on the visualization techniques supporting the comparison of time-based data sets of single patients with those of multiple patients or their cohorts and summarized the use of these techniques. METHODS: This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. After all collected articles were screened by 16 reviewers according to the criteria, 6 reviewers extracted the set of variables under investigation. The characteristics of these variables were based on existing taxonomies or identified through open coding. RESULTS: Of the 249 screened articles, we identified 22 (8.8%) that fit all criteria and reviewed them in depth. We collected and synthesized findings from these articles for medical aspects such as medical context, medical objective, and medical data type, as well as for the core investigated aspects of visualization techniques, interaction techniques, and supported tasks. The extracted articles were published between 2003 and 2019 and were mostly situated in clinical research. These systems used a wide range of visualization techniques, most frequently showing changes over time. Timelines and temporal line charts occurred 8 times each, followed by histograms with 7 occurrences and scatterplots with 5 occurrences. We report on the findings quantitatively through visual summarization, as well as qualitatively. CONCLUSIONS: The articles under review in general mitigated complexity through visualization and supported diverse medical objectives. We identified 3 distinct patient entities: single patients, multiple patients, and cohorts. Cohorts were typically visualized in condensed form, either through prior data aggregation or through visual summarization, whereas visualization of individual patients often contained finer details. All the systems provided mechanisms for viewing and comparing patient data. However, explicitly comparing a single patient with multiple patients or a cohort was supported only by a few systems. These systems mainly use basic visualization techniques, with some using novel visualizations tailored to a specific task. Overall, we found the visual comparison of measurements between single and multiple patients or cohorts to be underdeveloped, and we argue for further research in a systematic review, as well as the usefulness of a design space.

Observational study on implications of the COVID-19-pandemic for cardiopulmonary resuscitation in out-of-hospital cardiac arrest: qualitative and quantitative insights from a model region in Germany.

BACKGROUND: The city of Freiburg has been among the most affected regions by the COVID-19 pandemic in Germany. In out of hospital cardiac arrest (OHCA) care, all parts of the rescue system were exposed to profound infrastructural changes. We aimed to provide a comprehensive overview of these changes in the resuscitation landscape in the Freiburg region. METHODS: Utstein-style quantitative data on OHCA with CPR initiated, occurring in the first pandemic wave between February 27th, 2020 and April 30th, 2020 were compared to the same time periods between 2016 and 2019. Additionally, qualitative changes in the entire rescue system were analyzed and described. RESULTS: Incidence of OHCA with attempted CPR did not significantly increase during the pandemic period (11.1/100.000 inhabitants/63 days vs 10.4/100.000 inhabitants/63 days, p = 1.000). In witnessed cases, bystander-CPR decreased significantly from 57.7% (30/52) to 25% (4/16) (p = 0.043). A severe pre-existing condition (PEC) was documented more often, 66.7% (16/24) vs 38.2% (39/102) there were longer emergency medical services (EMS) response times, more resuscitation attempts terminated on scene, 62.5% (15/24) vs. 34.3% (35/102) and less patients transported to hospital (p = 0.019). Public basic life support courses, an app-based first-responder alarm system, Kids Save Lives activities and a prehospital extracorporeal CPR (eCPR) service were paused during the peak of the pandemic. CONCLUSION: In our region, bystander CPR in witnessed OHCA cases as well as the number of patients transported to hospital significantly decreased during the first pandemic wave. Several important parts of the resuscitation landscape were paused. The COVID-19 pandemic impedes OHCA care, which leads to additional casualties. Countermeasures should be taken.

Reducing burden from respiratory infections in refugees and immigrants: a systematic review of interventions in OECD, EU, EEA and EU-applicant countries.

BACKGROUND: Respiratory diseases are a major reason for refugees and other immigrants seeking health care in countries of arrival. The burden of respiratory diseases in refugees is exacerbated by sometimes poor living conditions characterised by crowding in mass accommodations and basic living portals. The lack of synthesised evidence and guideline-relevant information to reduce morbidity and mortality from respiratory infections endangers this population. METHODS: A systematic review of all controlled and observational studies assessing interventions targeting the treatment, diagnosis and management of respiratory infections in refugees and immigrants in OECD, EU, EEA and EU-applicant countries published between 2000 and 2019 in MEDLINE, CINAHL, PSYNDEX and the Web of Science. RESULTS: Nine of 5779 identified unique records met our eligibility criteria. Seven studies reported an increase in vaccine coverage from 2 to 52% after educational multilingual interventions for respiratory-related childhood diseases (4 studies) and for influenza (5 studies). There was limited evidence in one study that hand sanitiser reduced rates of upper respiratory infections and when provided together with face masks also the rates of influenza-like-illness in a hard to reach migrant neighbourhood. In outbreak situations of vaccine-preventable diseases, secondary cases and outbreak hazards were reduced by general vaccination strategies early after arrival but not by serological testing after exposure (1 study). We identified evidence gaps regarding interventions assessing housing standards, reducing burden of bacterial pneumonia and implementation of operational standards in refugee care and reception centres. CONCLUSIONS: Multilingual health literacy interventions should be considered to increase uptake of vaccinations in refugees and immigrants. Immediate vaccinations upon arrival at refugee housings may reduce secondary infections and outbreaks. Well-designed controlled studies on housing and operational standards in refugee and immigrant populations early after arrival as well as adequate ways to gain informed consent for early vaccinations in mass housings is required to inform guidelines.

High-resolution pediatric reference intervals for 15 biochemical analytes described using fractional polynomials.

OBJECTIVES: Assessment of children's laboratory test results requires consideration of the extensive changes that occur during physiological development and result in pronounced sex- and age-specific dynamics in many biochemical analytes. Pediatric reference intervals have to account for these dynamics, but ethical and practical challenges limit the availability of appropriate pediatric reference intervals that cover children from birth to adulthood. We have therefore initiated the multi-center data-driven PEDREF project (Next-Generation Pediatric Reference Intervals) to create pediatric reference intervals using data from laboratory information systems. METHODS: We analyzed laboratory test results from 638,683 patients (217,883-982,548 samples per analyte, a median of 603,745 test results per analyte, and 10,298,067 test results in total) performed during patient care in 13 German centers. Test results from children with repeat measurements were discarded, and we estimated the distribution of physiological test results using a validated statistical approach (kosmic). RESULTS: We report continuous pediatric reference intervals and percentile charts for alanine transaminase, aspartate transaminase, lactate dehydrogenase, alkaline phosphatase, γ-glutamyl-transferase, total protein, albumin, creatinine, urea, sodium, potassium, calcium, chloride, anorganic phosphate, and magnesium. Reference intervals are provided as tables and fractional polynomial functions (i.e., mathematical equations) that can be integrated into laboratory information systems. Additionally, Z-scores and percentiles enable the normalization of test results by age and sex to facilitate their interpretation across age groups. CONCLUSIONS: The provided reference intervals and percentile charts enable precise assessment of laboratory test results in children from birth to adulthood. Our findings highlight the pronounced dynamics in many biochemical analytes in neonates, which require particular consideration in reference intervals to support clinical decision making most effectively.

Telemedicine in Intensive Care Units: Scoping Review.

BACKGROUND: The role of telemedicine in intensive care has been increasing steadily. Tele-intensive care unit (ICU) interventions are varied and can be used in different levels of treatment, often with direct implications for the intensive care processes. Although a substantial body of primary and secondary literature has been published on the topic, there is a need for broadening the understanding of the organizational factors influencing the effectiveness of telemedical interventions in the ICU. OBJECTIVE: This scoping review aims to provide a map of existing evidence on tele-ICU interventions, focusing on the analysis of the implementation context and identifying areas for further technological research. METHODS: A research protocol outlining the method has been published in JMIR Research Protocols. This review follows the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). A core research team was assembled to provide feedback and discuss findings. RESULTS: A total of 3019 results were retrieved. After screening, 25 studies were included in the final analysis. We were able to characterize the context of tele-ICU studies and identify three use cases for tele-ICU interventions. The first use case is extending coverage, which describes interventions aimed at extending the availability of intensive care capabilities. The second use case is improving compliance, which includes interventions targeted at improving patient safety, intensive care best practices, and quality of care. The third use case, facilitating transfer, describes telemedicine interventions targeted toward the management of patient transfers to or from the ICU. CONCLUSIONS: The benefits of tele-ICU interventions have been well documented for centralized systems aimed at extending critical care capabilities in a community setting and improving care compliance in tertiary hospitals. No strong evidence has been found on the reduction of patient transfers following tele-ICU intervention. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/19695.

[RECUR - Establishment of An Automated Digital Registry for Patients with Recurrent Stones in the Upper Urinary Tract]. / RECUR ­ Aufbau eines automatisierten digitalen Registers für Patient*innen mit rezidivierenden Steinen des oberen Harntraktes.

Kidney stones, like cardiovascular diseases and diabetes mellitus, affect a large number of people. Patients suffer from acute pain, repeated hospitalizations and associated secondary diseases, such as arterial hypertension and renal insufficiency. This results in considerable costs for the society and its health care system. The recurrence rate is as high as 50%. The registry for RECurrent URolithiasis (RECUR) aims to fill existing evidence gaps. The prospective and longitudinal RECUR registry is funded by the German Ministry of Education and Science (BMBF). It is based on the digital infrastructure of the German Medical Informatics Initiative (MII). RECUR aims to include patients that have suffered from more than one stone occurrence and treated at any one of the ten participating university hospitals of the MIRACUM consortium. The intention is to obtain new information on risk factors and to evaluate different diagnosis and treatment algorithms. Along with the data form the patient's Electronic Health Records (EHR), the RECUR project will also collect Patient Reported Outcomes data from patients with recurrent kidney stones. These data will be collected at participating sites using digital questionnaires via a smartphone app. These data will be merged with medical data from the hospital information systems and saved in the MII research data repositories. The RECUR registry has a model character due to its fully federated, digital approach. This allows the recruitment of many patients, the collection of a wide range of data and their processing with low administrative and personnel costs.

Interviews with experts in rare diseases for the development of clinical decision support system software - a qualitative study.

BACKGROUND: Patients with rare diseases (RDs) are often diagnosed too late or not at all. Clinical decision support systems (CDSSs) could support the diagnosis in RDs. The MIRACUM (Medical Informatics in Research and Medicine) consortium, which is one of four funded consortia in the German Medical Informatics Initiative, will develop a CDSS for RDs based on distributed clinical data from ten university hospitals. This qualitative study aims to investigate (1) the relevant organizational conditions for the operation of a CDSS for RDs when diagnose patients (e.g. the diagnosis workflow), (2) which data is necessary for decision support, and (3) the appropriate user group for such a CDSS. METHODS: Interviews were carried out with RDs experts. Participants were recruited from staff physicians at the Rare Disease Centers (RDCs) at the MIRACUM locations, which offer diagnosis and treatment of RDs. An interview guide was developed with a category-guided deductive approach. The interviews were recorded on an audio device and then transcribed into written form. We continued data collection until all interviews were completed. Afterwards, data analysis was performed using Mayring's qualitative content analysis approach. RESULTS: A total of seven experts were included in the study. The results show that medical center guides and physicians from RDC B-centers (with a focus on different RDs) are involved in the diagnostic process. Furthermore, interdisciplinary case discussions between physicians are conducted. The experts explained that RDs exist which cannot be fully differentiated, but rather described only by their overall symptoms or findings: diagnosis is dependent on the disease or disease group. At the end of the diagnostic process, most centers prepare a summary of the patient case. Furthermore, the experts considered both physicians and experts from the B-centers to be potential users of a CDSS. The experts also have different experiences with CDSS for RDs. CONCLUSIONS: This qualitative study is a first step towards establishing the requirements for the development of a CDSS for RDs. Further research is necessary to create solutions by also including the experts on RDs.

How Thick Is the Oral Mucosa around Implants after Augmentation with Different Materials: A Systematic Review of the Effectiveness of Substitute Matrices in Comparison to Connective Tissue Grafts.

This systematic review aimed to assess the effectiveness of xenogeneic collagen matrices (XCMs) and acellular dermal matrices (ADMs) in comparison to connective tissue grafts (CTGs) for the augmentation of oral mucosa around dental implants. MEDLINE and the Web of Science were searched for clinical studies that compared substitute materials for the augmentation of oral mucosa to the subepithelial connective tissue graft around dental implants during or after implantation. The review was conducted according to the recommendations of the PRISMA statement. From an initial search result set of 1050 references, seven articles were included in the review. The study designs were heterogeneous, so no meta-analysis could be performed. Both the CTG and either type of substitute material resulted in increased mucosal thickness. Four studies showed no significant difference, while three demonstrated a significant difference, favoring the CTGs over alternative materials. Soft tissue augmentation around dental implants is a safe procedure and leads to thicker mucosal tissue. The subepithelial connective tissue graft can still be regarded as the gold standard, but substitute materials may be an acceptable alternative in some situations, such as for pain-sensitive patients, among inexperienced surgeons, and for sites with an already thick biotype.

How to compete with Google and Co.: big data and artificial intelligence in stones.

PURPOSE OF REVIEW: To elucidate the keywords big data and artificial intelligence and corresponding literature in the field of urolithiasis. RECENT FINDINGS: Numbers of publications on big data and artificial intelligence in the field of urolithiasis are rising, but still low. Most publications describe the development, testing, and validation of automated computational analyses of clinical data sets and/or images in a preclinical setting. SUMMARY: In the field of digital health services, there is a discrepancy between the enormous commitment of large private companies and investments of public funds. This situation means a still small number of medical publications on this topic in the urolithiasis field. Nevertheless, as doctors and scientists, we should try to provide our patients with secure and worthwhile digital services.

Well informed physician-patient communication in consultations on back pain - study protocol of the cluster randomized GAP trial.

BACKGROUND: Back pain is one of the most frequent causes of health-related work absence. In Germany, more than 70% of adults suffer from at least one back pain episode per annum. It has strong impact on health care costs and patients' quality of life. Patients increasingly seek health information on the internet. However, judging its trustworthiness is difficult. In addition, physicians who are being confronted with this type of information often experience it to complicate the physician-patient interaction. The GAP trial aims to develop, implement and evaluate an evidence-based, easy-to-understand and trustworthy internet information portal on lower back pain to be used by general practitioners and patients during and after the consultation. Effectiveness of GAP portal use compared to routine consultation on improving communication and informedness of both physicians and patients will be assessed. In addition, effects on health care costs and patients' days of sick leave will be evaluated. METHODS: We will conduct a prospective multi-centre, cluster-randomized parallel group trial including 1500 patients and 150 recruiting general practitioners. The intervention group will have access to the GAP portal. The portal will contain brief guides for patients and physicians on how to improve the consultation as well as information on epidemiology, aetiology, symptoms, benefits and harms of treatment options for acute, sub-acute and chronic lower back pain. The GAP portal will be designed to be user-friendly and present information on back pain tailored for either patients or physicians in form of brief fact sheets, educative videos, info-graphics, animations and glossaries. Physicians and patients will assess their informedness and the physician-patient communication in consultations at baseline and at two time points after the consultations under investigation. Days of sick leave and health care costs related to back pain will be compared between control and intervention group using routine data of company health insurance funds. DISCUSSION: The GAP-trial intends to improve the communication between physicians and their patients and the informedness of both groups. If proven beneficial, the evidence-based and user-friendly portal will be made accessible for all patients and health professionals in back pain care. Inclusion of further indications might be implemented and evaluated in the long term. TRIAL REGISTRATION: German Clinical Trials Register DRKS00014279 (registered 27th of April 2018).

Boosting competence-orientation in undergraduate medical education - A web-based tool linking curricular mapping and visual analytics.

Objectives: Transition to competency-based medical education is a highly challenging endeavor. Students, teachers and institutions need curricular transparency for understanding the build-up of competencies in terms of coverage, sequence and consistence of learning objectives and assessment. The project aim was to develop and implement a web-based interactive platform for curriculum mapping, diagnostics, and development. The tool should be transferable to other faculties and allow description and visualization of medical curricula in comparison to given national competency-based standards. Methods: In a design-based multi-center approach, four German medical faculties cooperated and developed a standardized, common mapping tool (MERlin database). Implemented are techniques for big data handling and visual analytics. Results: The platform profile is adapted closely to user needs. Intuitive data entry and comfortable quality maintenance support teacher engagement. Individual navigation for curricular diagnostics is guided by practice-oriented questions. Sophisticated, easy-understandable visualizations show curricular strengths and weaknesses. Transparency in contributing departments facilitates goal-oriented dialogs. Currently, 14 of 38 German faculties use the platform. Conclusions: In view of huge amounts of data and complex curricular structures, the MERlin database facilitates effective curriculum mapping, goal-oriented curriculum development, comparison to national competency-based standards, effective data sharing and benchmarking across faculties with different curriculum management systems.

Anxiety as a risk factor of Alzheimer's disease and vascular dementia.

BACKGROUND: The aetiology of dementia is not yet fully understood. Stress can have a damaging effect on brain health. The prognostic effect of anxiety is still unclear regarding Alzheimer's disease as well as vascular dementia.AimsTo explore the association between anxiety and future dementia. METHOD: Medline, PsycINFO, CINAHL, Web of Science and ALOIS were searched for publications up to 12 January 2018. Longitudinal studies with a follow-up of at least 2 years were included, if the trait or state anxiety had been assessed at baseline. Studies with cognitive impairment at baseline were not included. We used a random effects model to calculate the pooled time to Alzheimer's disease and incidence of vascular dementia. RESULTS: Anxiety predicts risk of Alzheimer's disease (n = 26 193 out of seven studies, hazard ratio1.53, 95% CI 1.16-2.01, P < 0.01) and vascular dementia (n = 4916 out of two studies, odds ratio1.88, 95% CI 1.05-3.36, P < 0.01). The pooled hazard ratio regarding risk of Alzheimer's disease was still significant when excluding studies with critical risk of bias (n = 14 110 out of six studies, hazard ratio 1.35, 95% CI 1.08-1.70, P < 0.01). CONCLUSIONS: Anxiety is a risk factor for both types of dementia. The temporal and functional relation between anxiety and dementia needs investigation in future studies. The protective value of treating anxiety should be explored further.Declaration of interestNone.