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نتیجه جستجو - Evidence-based medicine

تعداد مقالات یافته شده: 8
ردیف عنوان نوع
1 Suicide in psychiatry and medical liability: A case series
خودکشی در روانپزشکی و مسئولیت پزشکی: یک سری پرونده-2020
The suicide of a patient is a serious event that may constitute a therapeutic failure. To prevent these situations, national and international guidelines exist. When a suicide occurs in a psychiatric hospital or immediately after release, legal action may follow, most frequently for malpractice claims related to the failure to provide reasonable management of the suicide risk. In an attempt to respond to the increased anxiety in the health care system and among practitioners, we used case reports to determine the minimum medico-legal standards that the physician must follow in the context of suicide.From February 1st to May 30th, 2019, we gathered all available expert psychiatric reports following criminal prosecutions from the University Center of Legal Medicine of Geneva. We restricted the extraction of cases to those from January 1st, 2007, to May 30th, 2019.We identified 7 cases. The psychiatrist expert provided a care setting assessment, clinical/survey assessment, and suicidal risk assessment. Improper care setting assessment was the most commonly found conclusion, but the two other categories were as detrimental concerning suicidal risk. Only one psychiatrist was condemned, but the decision was revoked on appeal. The combination of our cases and a scoping review on the subject leads to the recommendation of minimum medico-legal standards to complete individualized suicide risk reduction plans.Minimal medico-legal standards should be applied and documented to optimize care practice for the reduction of suicidal risk at three different levels: the initial evaluation, the treatment, and the surveillance.
Keywords: Suicide | Prevention | Forensic psychiatry | Responsibility | Evidence-based medicine
مقاله انگلیسی
2 Distributed learning on 20 000+ lung cancer patients – The Personal Health Train
یادگیری توزیع شده بر روی 20 000+ بیمار مبتلا به سرطان ریه - آموزش بهداشت شخصی-2020
Background and purpose: Access to healthcare data is indispensable for scientific progress and innovation. Sharing healthcare data is time-consuming and notoriously difficult due to privacy and regulatory concerns. The Personal Health Train (PHT) provides a privacy-by-design infrastructure connecting FAIR (Findable, Accessible, Interoperable, Reusable) data sources and allows distributed data analysis and machine learning. Patient data never leaves a healthcare institute. Materials and methods: Lung cancer patient-specific databases (tumor staging and post-treatment survival information) of oncology departments were translated according to a FAIR data model and stored locally in a graph database. Software was installed locally to enable deployment of distributed machine learning algorithms via a central server. Algorithms (MATLAB, code and documentation publicly available) are patient privacy-preserving as only summary statistics and regression coefficients are exchanged with the central server. A logistic regression model to predict post-treatment two-year survival was trained and evaluated by receiver operating characteristic curves (ROC), root mean square prediction error (RMSE) and calibration plots. Results: In 4 months, we connected databases with 23 203 patient cases across 8 healthcare institutes in 5 countries (Amsterdam, Cardiff, Maastricht, Manchester, Nijmegen, Rome, Rotterdam, Shanghai) using the PHT. Summary statistics were computed across databases. A distributed logistic regression model predicting post-treatment two-year survival was trained on 14 810 patients treated between 1978 and 2011 and validated on 8 393 patients treated between 2012 and 2015. Conclusion: The PHT infrastructure demonstrably overcomes patient privacy barriers to healthcare data sharing and enables fast data analyses across multiple institutes from different countries with different regulatory regimens. This infrastructure promotes global evidence-based medicine while prioritizing patient privacy.
Keywords: Lung cancer | Big data | Distributed learning | Federated learning | Machine learning | Survival analysis | Prediction modeling | FAIR data
مقاله انگلیسی
3 Concurrence of big data analytics and healthcare: A systematic review
انطباق با تجزیه و تحلیل داده های بزرگ و مراقبت های بهداشتی: یک مرور سیستماتیک-2018
Background: The application of Big Data analytics in healthcare has immense potential for improving the quality of care, reducing waste and error, and reducing the cost of care. Purpose: This systematic review of literature aims to determine the scope of Big Data analytics in healthcare including its applications and challenges in its adoption in healthcare. It also intends to identify the strategies to overcome the challenges. Data sources: A systematic search of the articles was carried out on five major scientific databases: ScienceDirect, PubMed, Emerald, IEEE Xplore and Taylor & Francis. The articles on Big Data analytics in healthcare published in English language literature from January 2013 to January 2018 were considered. Study selection: Descriptive articles and usability studies of Big Data analytics in healthcare and medicine were selected. Data extraction: Two reviewers independently extracted information on definitions of Big Data analytics; sources and applications of Big Data analytics in healthcare; challenges and strategies to overcome the challenges in healthcare. Results: A total of 58 articles were selected as per the inclusion criteria and analyzed. The analyses of these articles found that: (1) researchers lack consensus about the operational definition of Big Data in healthcare; (2) Big Data in healthcare comes from the internal sources within the hospitals or clinics as well external sources including government, laboratories, pharma companies, data aggregators, medical journals etc.; (3) natural language processing (NLP) is most widely used Big Data analytical technique for healthcare and most of the processing tools used for analytics are based on Hadoop; (4) Big Data analytics finds its application for clinical decision support; optimization of clinical operations and reduction of cost of care (5) major challenge in adoption of Big Data analytics is non-availability of evidence of its practical benefits in healthcare. Conclusion: This review study unveils that there is a paucity of information on evidence of real-world use of Big Data analytics in healthcare. This is because, the usability studies have considered only qualitative approach which describes potential benefits but does not take into account the quantitative study. Also, majority of the studies were from developed countries which brings out the need for promotion of research on Healthcare Big Data analytics in developing countries.
Keywords: Big data , Analytics , Healthcare , Predictive analytics , Evidence-based medicine
مقاله انگلیسی
4 دسترس پذیری سیستم اطلاعات بهداشتی برای تصمیم گیری با رویکرد پزشکی مبتنی بر شواهد - مطالعه موردی: کرمانشاه، ایران
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 10
پزشکی مبتنی بر شواهد (EBM) ، کاربرد موثر و مناسب، بهترین شواهد در تصمیم گیری بالینی برای مراقبت از بیمار است. اين مطالعه با هدف ارزيابی سيستم اطلاعات بهداشتی جهت تصميم گيری با روش EBM در بيمارستان آموزشی شهر کرمانشاه انجام شد. جامعه آماری شامل تمامی متخصصان و کارشناسان و همچنین پرستاران شاغل در بیمارستان های آموزشی شهر کرمانشاه است. داده ها از طریق پرسشنامه جمع آوری شد. اعتبارسنجی محتویات پرسشنامه با هدف تکمیل پرسش های پرسشنامه، توسط متخصصان تایید شد. سپس قابلیت اطمینان پرسشنامه با استفاده از ضریب آلفای کرونباخ مورد ارزیابی قرار گرفت. نتایج نشان داد که میزان دسترسی به منابع اینترنتی در سطح مطلوب است. با توجه به متحصصین دانشگاهی (P = 0.021) اختلاف معنی داری حداقل بین یک گروه قابل دسترس سیستم اطلاعاتی بیمارستان اطلاعاتی EBM در دسترسی به داده های اینترنتی وجود دارد. رضایت از سیستم اطلاعات بیمارستانی در تهیه دارو مبتنی بر شواهد، از نظر دانش لازم اجرای آن بر اساس آموزش عالی، اختلاف آماری معنی داری حداقل در یک گروه نشان داد(001/0 P =). بیمارستان کرمانشاه از لحاظ دسترسی به منابع اینترنتی، دانش EBM و پیاده سازی آن شرایط مطلوبی دارد؛ این نشان می دهد که قابل دسترس بودن، بستر مناسب برای تصمیم گیری با رویکرد EBM است. با این حال، بهتر است دوره های آموزشی منظم برای آموزش پزشکان و پرستاران به منظور پیاده سازی عملی رویکرد EBM به کار گرفته شود.
کلید واژه ها: پزشکی مبتنی بر شواهد | سیستم اطلاعات بیمارستانی | تصمیم بالینی
مقاله ترجمه شده
5 A new standardized data collection system for interdisciplinary thyroid cancer management: Thyroid COBRA
یک سیستم جمع آوری داده استاندارد برای مدیریت سرطان تیروئید: تیروئید COBRA-2018
The big data approach offers a powerful alternative to Evidence-based medicine. This approach could guide cancer management thanks to machine learning application to large-scale data. Aim of the Thyroid CoBRA (Consortium for Brachytherapy Data Analysis) project is to develop a standardized web data collection system, focused on thyroid cancer. The Metabolic Radiotherapy Working Group of Italian Association of Radiation Oncology (AIRO) endorsed the implementation of a consortium directed to thyroid cancer management and data collection. The agreement conditions, the ontology of the collected data and the related software services were defined by a multicentre ad hoc working-group (WG). Six Italian cancer centres were firstly started the project, defined and signed the Thyroid COBRA consortium agreement. Three data set tiers were identified: Registry, Procedures and Research. The COBRA-Storage System (C-SS) appeared to be not time-consuming and to be privacy respecting, as data can be extracted directly from the single centres storage platforms through a secured connection that ensures reliable encryption of sensible data. Automatic data archiving could be directly performed from Image Hospital Storage System or the Radiotherapy Treatment Planning Systems. The C-SS architecture will allow “Cloud storage way” or “distributed learning” approaches for predictive model definition and further clinical decision support tools development. The development of the Thyroid COBRA data Storage System C-SS through a multicentre consortium ap proach appeared to be a feasible tool in the setup of complex and privacy saving data sharing system oriented to the management of thyroid cancer and in the near future every cancer type.
Keywords: Big data ، Data pooling ، Personalized medicine ، Radiotherapy ، Thyroid ، Cancer management
مقاله انگلیسی
6 No suitable precise or optimized epidemiologic search filters were available for bibliographic databases
فیلترهای جستجوی اپیدمیولوژیک دقیق یا بهینه شده نامناسب در دسترس برای پایگاه داده های کتابشناختی-2017
Objectives: To determine a suitable approach to a systematic search for epidemiologic publications in bibliographic databases. For this purpose, suitable sensitive, precise, and optimized filters were to be selected for MEDLINE searches. In addition, the relevance of biblio graphic databases was determined. Study Design and Setting: Epidemiologic systematic reviews (SRs) retrieved in a systematic search and company dossiers were screened to identify epidemiologic publications (primary studies and SRs) published since 2007. These publications were used to generate a test and validation set. Furthermore, each SR’s search strategy was reviewed, and epidemiologic filters were extracted. The search syn taxes were validated using the relative recall method. Results: The test set comprises 729 relevant epidemiologic publications, of which 566 were MEDLINE-indexed. About 27 epidemi ologic filters were extracted. One suitable sensitive filter was identified (Larney et al. 2013: 95.94% sensitivity). Precision was presumably underestimated so that no precise or optimized filters can be recommended. About 77.64% of the publications were found in MEDLINE. Conclusion: There is currently no suitable approach to conducting efficient systematic searches for epidemiologic publications in bibliographic databases. The filter by Larney et al. (2013) can be used for sensitive MEDLINE searches. No robust conclusions can be drawn on precise or optimized filters. Additional search approaches should be considered.  2016 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Information storage and retrieval | Evidence-based medicine | Databases | bibliographic | MEDLINE | Review literature as topic | Epidemiology
مقاله انگلیسی
7 Clinical practice guidelines were adapted and implemented meeting country-specific requirements-the example of Kazakhstan
رهنمودهای درمان بالینی به تصویب رسیده و اجرا شده نشست الزامات کشور خاص مانند از قزاقستان-2016
Objectives: In a twinning partnership between the Canadian Society for International Health and Kazakhstan’s Ministry of Health, a proj- ect to build capacity and a process for the adaptation and implementation of international clinical practice guidelines (CPGs) was undertaken.
Study Design and Setting: A pragmatic CPG adaptation process was developed that took into consideration national and local con- texts. A 15-step process ranging from topic prioritization to copyright clearance to final Ministry of Health approval was developed. Animplementation strategy was developed and piloted in three local regions using a five-step approach.
Results: High-quality international CPG candidates were identified for all topics; forty-two CPGs were adapted locally by the clinical working groups. Three CPGs using 21 recommendations were implemented locally. Many challenges were identified including priority setting, obtaining permission to use and translate guidelines into Russian and producing high-quality translations, and organizational bar- riers during implementation. Facilitators included tools to guide the process and the creation of working groups.
Conclusion: We describe a process of large-scale adaptation of international CPGs with the pilot implementation of selected adapted CPGs and recommendations. Further evaluation and monitoring are required to ensure its integrity. © 2016 Elsevier Inc. All rights reserved.
Keywords: Evidence-based medicine | Practice guidelines as topic | Guideline adherence | Quality Assurance | Health care | Implementation research | Knowledge | translation
مقاله انگلیسی
8 مدیریت بیمارستان: چالش ها و استراتژی ها
سال انتشار: 2005 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 14
هیچ سیستم مراقبت بهداشتی در جهان پایدار نیست و تمام سیستم ها در نزدیک ۲۰ سال اینده تغییر قابل توجهی خواهد داشت. تغییرات محرک در ملت های صنعتی سبب ایجاد محدودیت برای رفاه دولتی؛ روش های صنعتی طاقت فرسا؛ و ابزارهایی برای هزینه های جاری و افزایش تجربه ها در کمال مصرف کننده و تقاضاها است. تغییرات در کشورهای پیشرفته به وسیله رشد طبقه متوسط؛ تقاضاهای بیشتر از طبقه متوسط؛ و جهانی شدن اقتصاد یک محرک اغاز گر است. فاکتورهای پیروی شده زیر بیشترین نفوذ تغییراتی در سلامت سیستم های اجرا شده دارد:
۱. انتقالات بهداشتی- جمعیت شناسی؛ اپیدمولوژیک؛ ظهور بیماری های عفونی.
۲. اخرین پیشرفتهای تکنولوژیکی – تشخیصی؛ درمانی و پیشگیری.
۳. کشف و نواوری در پیوند اعضا
۴. مداخلات پزشکی کمک کننده با استفاده از ربات و کامپیوتر
۵. بیولوژی مولکولی
۶. مهندسی ژنتیک و ژن درمانی
۷. اطلاعات برگزیده از راه ها
۸. مدیریت کیفی جامع
۹. مصرف گرایی
۱۰. هزینه بهره وری
۱۱. مسایل اخلاقی و حقوقی
۱۲. تحقیق و توسعه
۱۳. شواهد مبتنی بر پزشکی
۱۴. مدیریت مراقبت شده- درخواست مدیریتی ( سرانه هزینه های کاربردی)؛ مدیریت پزشکی( بازبینی استفاده؛ مدیریت بیماری؛ استفاده از دستورالعمل ها) و انتقال حامل ها( دارو سازی)
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