BACKGROUND: The burden of chronic and societal diseases is affected by many risk factors that can change over time. The minimalisation of disease-associated risk factors may contribute to long-term health. Therefore, new data-driven health management should be used in clinical decision-making in order to minimise future individual risks of disease and adverse health effects. METHODS: We aimed to develop a health trajectories (HT) management methodology based on electronic health records (EHR) and analysing overlapping groups of patients who share a similar risk of developing a particular disease or experiencing specific adverse health effects. Formal concept analysis (FCA) was applied to identify and visualise overlapping patient groups, as well as for decision-making. To demonstrate its capabilities, the theoretical model presented uses genuine data from a local total knee arthroplasty (TKA) register (a total of 1885 patients) and shows the influence of step by step changes in five lifestyle factors (BMI, smoking, activity, sports and long-distance walking) on the risk of early reoperation after TKA. RESULTS: The theoretical model of HT management demonstrates the potential of using EHR data to make data-driven recommendations to support both patients' and physicians' decision-making. The model example developed from the TKA register acts as a clinical decision-making tool, built to show surgeons and patients the likelihood of early reoperation after TKA and how the likelihood changes when factors are modified. The presented data-driven tool suits an individualised approach to health management because it quantifies the impact of various combinations of factors on the early reoperation rate after TKA and shows alternative combinations of factors that may change the reoperation risk. CONCLUSION: This theoretical model introduces future HT management as an understandable way of conceiving patients' futures with a view to positively (or negatively) changing their behaviour. The model's ability to influence beneficial health care decision-making to improve patient outcomes should be proved using various real-world data from EHR datasets.

• MeSH
• individualizovaná medicína * MeSH
• klinické rozhodování MeSH
• lidé MeSH
• reoperace MeSH
• teoretické modely MeSH
• totální endoprotéza kolene * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

• MeSH
• lékařská informatika MeSH
• telemedicína MeSH
• Publikační typ
• kongresy MeSH
• souborné dílo MeSH

• Konspekt
• Veřejné zdraví a hygiena
• NLK Obory
• lékařská informatika

Interpretation of cardiotocogram (CTG) is a difficult task since its evaluation is complicated by a great inter- and intra-individual variability. Previous studies have predominantly analyzed clinicians' agreement on CTG evaluation based on quantitative measures (e.g. kappa coefficient) that do not offer any insight into clinical decision making. In this paper we aim to examine the agreement on evaluation in detail and provide data-driven analysis of clinical evaluation. For this study, nine obstetricians provided clinical evaluation of 634 CTG recordings (each ca. 60min long). We studied the agreement on evaluation and its dependence on the increasing number of clinicians involved in the final decision. We showed that despite of large number of clinicians the agreement on CTG evaluations is difficult to reach. The main reason is inherent inter- and intra-observer variability of CTG evaluation. Latent class model provides better and more natural way to aggregate the CTG evaluation than the majority voting especially for larger number of clinicians. Significant improvement was reached in particular for the pathological evaluation - giving a new insight into the process of CTG evaluation. Further, the analysis of latent class model revealed that clinicians unconsciously use four classes when evaluating CTG recordings, despite the fact that the clinical evaluation was based on FIGO guidelines where three classes are defined.

• MeSH
• kardiotokografie statistika a číselné údaje   MeSH
• lidé MeSH
• metody pro podporu rozhodování * MeSH
• odchylka pozorovatele MeSH
• porodnictví statistika a číselné údaje   MeSH
• reprodukovatelnost výsledků MeSH
• rozpoznávání automatizované metody   MeSH
• senzitivita a specificita MeSH
• systémy pro podporu klinického rozhodování * MeSH
• umělá inteligence * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

A major prospect of Medical Informatics are methods, tools and infrastructures to support data-driven medical care and biomedical research. We need new concepts for application systems that also care for transparency which data from which sources in which quality build the evidence base for individual decisions. These systems have to be able to také into account patient generated data, patient preferences, and environmental contexts for an individualized decision that really meets the patients’ expectations, values and needs. Currently, these soft factors for medical decision support are not sufficiently understood and researched inall its dimensions.

• MeSH
• lékařská informatika * metody   trendy   výchova   MeSH
• lékařská počítačová informatika MeSH
• Publikační typ
• autobiografie MeSH
• Geografické názvy
• Německo MeSH

• MeSH
• Bayesova věta MeSH
• rozhodování MeSH
• statistika jako téma MeSH

• Konspekt
• Statistika
• NLK Obory
• statistika, zdravotnická statistika

The increasing trend of adolescents' emotional symptoms has become a global public health problem. Especially, adolescents with chronic diseases or disabilities face more risks of emotional problems. Ample evidence showed family environment associates with adolescents' emotional health. However, the categories of family-related factors that most strongly influence adolescents' emotional health remained unclear. Additionally, it was not known that whether family environment influences emotional health differently between normally developed adolescents and those with chronic condition(s). Health Behaviours in School-aged Children (HBSC) database provides mass data about adolescents' self-reported health and social environmental backgrounds, which offers opportunities to apply data-driven approaches to determine critical family environmental factors that influence adolescents' health. Thus, based on the national HBSC data in the Czech Republic collected from 2017 to 2018, the current study adopted a data-driven method, classification-regression-decision-tree analysis, to investigate the impacts of family environmental factors, including demographic factors and psycho-social factors on adolescents' emotional health. The results suggested that family psycho-social functions played a significant role in maintaining adolescents' emotional health. Both normally developed adolescents and chronic-condition(s) adolescents benefited from communication with parents, family support, and parental monitoring. Besides, for adolescents with chronic condition(s), school-related parental support was also meaningful for decreasing emotional problems. In conclusion, the findings suggest the necessity of interventions to strengthen family-school communication and cooperation to improve chronic-disease adolescents' mental health. The interventions aiming to improve parent-adolescent communication, parental monitoring, and family support are essential for all adolescents.

• MeSH
• chronická nemoc MeSH
• dítě MeSH
• duševní zdraví * MeSH
• emoce MeSH
• lidé MeSH
• mladiství MeSH
• rodiče * psychologie   MeSH
• rozhodovací stromy MeSH
• Check Tag
• dítě MeSH
• lidé MeSH
• mladiství MeSH
• Publikační typ
• časopisecké články MeSH

Waste sorting at the source is a vital strategy of waste management and to improve urban sustainability. If the strategy is implemented by relying solely on publicity and civic awareness, the impact is less significant. Proactive measures, such as policy regulations, supervisory guidance, and stimulating incentives, play essential roles for better management. The unknown waste-dumping behaviour of residents is a great challenge for decision-makers to allocate resources for waste-collection operations and to refine regulations. Traditional behaviour analysis methods such as questionnaire surveys and simulation methods have limitations considering the population size and the complexity of individual behaviour. This study aims to design a data-driven analytical framework to analyse household waste-dumping behaviour and facilitate policy regulations by using the Internet of Things (IoT) and data mining technologies. The analytical framework is further developed into a four-step management cycle. A case study in Shanghai is employed to demonstrate the effectiveness of the analytical framework and management cycle. The results of behaviour analyses reveal that (1) waste-dumping frequency is high in the evening but negligible in the early afternoon; (2) compared to working days, peak-value time at weekends occurs later in the morning and earlier in the evening; (3) residents require longer waste-dumping time windows than those empirically recommended by administrators. Managerial insights and decision support based on these research results have been presented for decision-makers to guide operations management and facilitate policy regulations.

• MeSH
• nakládání s odpady * MeSH
• odpadky - odstraňování * MeSH
• skládková zařízení MeSH
• trvale udržitelný růst MeSH
• velkoměsta MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Čína MeSH
• velkoměsta MeSH

Electronic Health Record (EHR) systems are now being developed in many places. More advanced systems provide also reminder facilities, usually based on if-then rules. In this paper we propose a method how to build the reminder facility directly upon the guideline interchange format (GLIF) model of medical guidelines. The method compares data items on the input of EHR system with medical guidelines GLIF model and is able to reveal if the input data item, that represents patient diagnosis or proposed patient treatment, contradicts with medical guidelines or not. The reminder facility can be part of EHR system itself or it can be realized by a stand-alone reminder system (SRS). The possible architecture of stand-alone reminder system is described in this paper and the advantages of stand-alone solution are discussed. The part of the EHR system could be also a browser that would present graphical GLIF model in easy to understand manner on the user screen. This browser can be data driven and focus attention of user to the relevant part of medical guidelines GLIF model.

• MeSH
• chorobopisy - počítačové systémy normy   MeSH
• chorobopisy - spojování normy   MeSH
• financování organizované MeSH
• metody pro podporu rozhodování MeSH
• registrace MeSH
• rozhodovací podpůrné systémy pro řízení normy   MeSH
• šíření informací metody   MeSH
• směrnice pro lékařskou praxi jako téma normy   MeSH
• systémy řízení databází normy   MeSH
• telemedicína normy   MeSH
• ukládání a vyhledávání informací normy   MeSH
• uživatelské rozhraní počítače MeSH
• Publikační typ
• srovnávací studie MeSH
• Geografické názvy
• Česká republika MeSH

Úvod: Předpokladem zdokonalení jakékoli činnosti je kontrola výsledků a poskytnutí zpětné vazby s dopadem na úpravu prováděných postupů. Další nedílnou součástí vedoucí k optimalizaci postupů, jejich vylepšení a ideálně zavedení standardu je srovnání aktuálních zkušeností odborníků v dané oblasti. Pro objektivní srovnání a hodnocení postupů je vždy nezbytné tyto postupy ideálně parametricky popsat, získat reprezentativní data, objektivně zhodnotit dosažené výsledky a na základě takového analytického hodnocení poskytnout nezpochybnitelnou a daty podloženou zpětnou vazbu. Ta může po vyhodnocení vést ke shodě nad definicí standardů v dané oblasti péče. Metoda: Totální mezorektální excize (TME) je standardním postupem chirurgické léčby karcinomu rekta (C20). Přesto se i v závislosti na nastavených vnitřních postupech a zkušenostech chirurgů kvalita prováděných výkonů mezi pracovišti významně liší. Klíčová je možnost hodnotit kvalitu chirurgické péče. Cennou zpětnou vazbu v této situaci může nabídnout patolog, který resekát hodnotí. Výsledky: V práci je popsán informační systém pro parametrické hodnocení kvality TME, jeho technické zázemí formou multicentrického klinického registru a struktura sledovaných parametrů. Závěr: Navrhovaný systém parametrického hodnocení TME považujeme za významný prostředek ke zlepšení kvality provádění TME s cílem omezit lokální recidivy a zlepšit prognózu operovaných.

Introduction: Improvement in any human activity is preconditioned by inspection of results and providing feedback used for modification of the processes applied. Comparison of experts' experience in the given field is another indispensable part leading to optimisation and improvement of processes, and optimally to implementation of standards. For the purpose of objective comparison and assessment of the processes, it is always necessary to describe the processes in a parametric way, to obtain representative data, to assess the achieved results, and to provide unquestionable and data-driven feedback based on such analysis. This may lead to a consensus on the definition of standards in the given area of health care. Method: Total mesorectal excision (TME) is a standard procedure of rectal cancer (C20) surgical treatment. However, the quality of performed procedures varies in different health care facilities, which is given, among others, by internal processes and surgeons' experience. Assessment of surgical treatment results is therefore of key importance. A pathologist who assesses the resected tissue can provide valuable feedback in this respect. Results: An information system for the parametric assessment of TME performance is described in our article, including technical background in the form of a multicentre clinical registry and the structure of observed parameters. Conclusion: We consider the proposed system of TME parametric assessment as significant for improvement of TME performance, aimed at reducing local recurrences and at improving the overall prognosis of patients.

• Klíčová slova
• klinické registry,
• MeSH
• chirurgie trávicího traktu MeSH
• datové kurátorství metody   MeSH
• faktografické databáze MeSH
• lidé MeSH
• mezioborová komunikace MeSH
• nádory rekta * chirurgie   MeSH
• online systémy MeSH
• registrace * MeSH
• řízení kvality MeSH
• sběr dat metody   MeSH
• systémy pro podporu klinického rozhodování * MeSH
• systémy řízení databází MeSH
• zlepšení kvality MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• práce podpořená grantem MeSH

OBJECTIVE: The clinical diagnosis of corticobasal syndrome (CBS) represents a challenge for physicians and reliable diagnostic imaging biomarkers would support the diagnostic work-up. We aimed to investigate the neural signatures of CBS using multimodal T1-weighted and resting-state functional magnetic resonance imaging (MRI). METHODS: Nineteen patients with CBS (age 67.0 ± 6.0 years; mean±SD) and 19 matched controls (66.5 ± 6.0) were enrolled from the German Frontotemporal Lobar Degeneration Consortium. Changes in functional connectivity and structure were respectively assessed with eigenvector centrality mapping complemented by seed-based analysis and with voxel-based morphometry. In addition to mass-univariate statistics, multivariate support vector machine (SVM) classification tested the potential of multimodal MRI to differentiate patients and controls. External validity of SVM was assessed on independent CBS data from the 4RTNI database. RESULTS: A decrease in brain interconnectedness was observed in the right central operculum, middle temporal gyrus and posterior insula, while widespread connectivity increases were found in the anterior cingulum, medial superior-frontal gyrus and in the bilateral caudate nuclei. Severe and diffuse gray matter volume reduction, especially in the bilateral insula, putamen and thalamus, characterized CBS. SVM classification revealed that both connectivity (area under the curve 0.81) and structural abnormalities (0.80) distinguished CBS from controls, while their combination led to statistically non-significant improvement in discrimination power, questioning the additional value of functional connectivity over atrophy. SVM analyses based on structural MRI generalized moderately well to new data, which was decisively improved when guided by meta-analytically derived disease-specific regions-of-interest. CONCLUSIONS: Our data-driven results show impairment of functional connectivity and brain structure in CBS and explore their potential as imaging biomarkers.

• MeSH
• konektom metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• magnetická rezonanční tomografie * MeSH
• mozková kůra diagnostické zobrazování   patologie   patofyziologie   MeSH
• multimodální zobrazování MeSH
• nemoci bazálních ganglií diagnostické zobrazování   patologie   patofyziologie   MeSH
• nervová síť diagnostické zobrazování   patologie   patofyziologie   MeSH
• neurozobrazování metody   MeSH
• šedá hmota diagnostické zobrazování   patologie   patofyziologie   MeSH
• senioři MeSH
• support vector machine * MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH