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1.
J Glob Health ; 10(1): 010408, 2020 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-32257156

RESUMEN

Background: HIV treatment and care services were scaled up in 2007 in India with objective to increase HIV-care coverage. CD4 count based criteria was mainly used for treatment initiation with increasing threshold in later years. Therefore, this paper aimed to evaluate the survival by varying CD4 criteria for antiretroviral treatment (ART) initiation among of HIV-positive patients, and independent factors associated with the mortality. Methods: This retrospective cohort study included 127 949 HIV-positive patients aged ≥15 years, who initiated ART between 2007 and 2013 in Andhra Pradesh state, India. The patient's demographic and clinical characteristics were extracted from the patient's health records from electronic Computerized Management Information System Software (CMIS). Incidence of mortality/100 person-years was calculated for CD4 and treatment initiation categories. Kaplan-Meier and multivariable Cox-regression analyses were used to explore the association. Results: Median CD4 count was 172 (inter-quartile range (IQR) = 102-240) at the time of treatment initiation, and 19.3% of them had ≤ 100 CD4 count. Incidence of mortality for the period 2007-08 (CD4 ≤ 200 cells/mm3) was 8.5/100 person-years compared to 6.4/100 person-years at risk for the period 2012 onwards (CD4 ≤ 350 cells/mm3). Earlier thresholds for treatment initiation showed higher risk of mortality (2007-08 (CD4 ≤ 200 cells/mm3), adjusted hazard ratio (HR): 1.86, 95% confidence interval (CI): 1.68-2.07; 2009-11 (CD4 ≤ 250 cells/mm3), HR = 1.67, 95% CI = 1.51-1.85) compared to 2012 onwards (CD4 ≤ 350 cells/mm3) criteria for treatment initiation. Conclusions: Increasing CD4 threshold for treatment initiation over time was independently associated with lower risk of mortality. More efforts are required to detect and treat early, monitoring of follow-ups, promote health education to improve ART adherence, and provide supportive environment that encourages HIV-infected patients to disclose their HIV status in confidence.


Asunto(s)
Fármacos Anti-VIH/uso terapéutico , Registros Electrónicos de Salud , Infecciones por VIH/tratamiento farmacológico , Adolescente , Adulto , Recuento de Linfocito CD4 , Femenino , Infecciones por VIH/mortalidad , Infecciones por VIH/virología , Mortalidad Hospitalaria , Humanos , Incidencia , India , Masculino , Persona de Mediana Edad , Modelos de Riesgos Proporcionales , Estudios Retrospectivos
2.
RECIIS (Online) ; 14(1): 150-166, jan.-mar. 2020. ilus, tab, graf
Artículo en Portugués | LILACS | ID: biblio-1087302

RESUMEN

A internet das coisas e o aprendizado de máquina são temas emergentes na área da saúde com potencial para otimizar a área e criar um sistema de saúde inteligente em virtude do envelhecimento da população. Este artigo analisa a produção científica do período de 2009 a 2019 a respeito da internet das coisas e do aprendizado de máquina na área da saúde. Utiliza metodologia bibliométrica em 1.353 artigos recuperados na base de dados Web of Science. Constata um crescimento da produção científica sobre o tema, sendo os Estados Unidos o principal polo de pesquisa na área. Identifica os autores mais produtivos e com maior impacto, periódicos mais produtivos, colaboração entre países e palavras-chave utilizadas, bem como suas relações. Incentiva que novas pesquisas explorem as abordagens identificadas no estudo.


The internet of things and machine learning are emerging issues with the potential to optimize the health field and create an intelligent health system due to the aging population. This article analyzes the scientific production of the period from 2009 to 2019 regarding the internet of things and machine learning in the health area. It uses bibliometric methodology in 1.353 articles retrieved from the Web of Science database. It notes an increase in scientific production on the subject, the United States being the main research center in this area. It identifies the most productive and influential authors, the most productive journals, collaboration between countries and keywords used, as well as their relations. It encourages new research to explore the approaches identified in the study.


La internet de las cosas y el aprendizaje de máquinas son temas emergentes en el área de la salud con potencial para optimizar el área y crear un sistema de salud inteligente en virtud del envejecimiento de la población. Este artículo analiza la producción científica del período de 2009 hasta 2019 respecto a internet de las cosas y del aprendizaje de máquina en el área de la salud. Utiliza metodología bibliométrica en 1.353 artículos recuperados en la base de datos Web of Science. Constata un crecimiento de la producción científica sobre el tema, siendo los Estados Unidos el principal polo de investigación en el área. Identifica a los autores más productivos y con mayor impacto, periódicos más productivos, colaboración entre países y palabras clave utilizadas, así como sus relaciones. Estimula a que nuevas investigaciones exploren los enfoques identificados en el estudio.


Asunto(s)
Humanos , Tecnología , Sistemas de Salud , Inteligencia Artificial , Internet , Actividades Científicas y Tecnológicas , Bibliometría , Publicaciones Científicas y Técnicas , Registros Electrónicos de Salud , Aprendizaje Automático
3.
Bone Joint J ; 102-B(4): 423-425, 2020 Apr.
Artículo en Inglés | MEDLINE | ID: mdl-32228082

RESUMEN

AIMS: Dislocation remains a significant complication after total hip arthroplasty (THA), being the third leading indication for revision. We present a series of acetabular revision using a dual mobility cup (DMC) and compare this with our previous series using the posterior lip augmentation device (PLAD). METHODS: A retrospective review of patients treated with either a DMC or PLAD for dislocation in patients with a Charnley THA was performed. They were identified using electronic patient records (EPR). EPR data and radiographs were evaluated to determine operating time, length of stay, and the incidence of complications and recurrent dislocation postoperatively. RESULTS: A total of 28 patients underwent revision using a DMC for dislocation following Charnley THA between 2013 and 2017. The rate of recurrent dislocation and overall complications were compared with those of a previous series of 54 patients who underwent revision for dislocation using a PLAD, between 2007 and 2013. There was no statistically significant difference in the mean distribution of sex or age between the groups. The mean operating time was 71 mins (45 to 113) for DMCs and 43 mins (21 to 84) for PLADs (p = 0.001). There were no redislocations or revisions in the DMC group at a mean follow-up of 55 months (21 to 76), compared with our previous series of PLAD which had a redislocation rate of 16% (n = 9) and an overall revision rate of 25% (n = 14, p = 0.001) at a mean follow-up of 86 months (45 to 128). CONCLUSION: These results indicate that DMC outperforms PLAD as a treatment for dislocation in patients with a Charnley THA. This should therefore be the preferred form of treatment for these patients despite a slightly longer operating time. Work is currently ongoing to review outcomes of DMC over a longer follow-up period. PLAD should be used with caution in this patient group with preference given to acetabular revision to DMC. Cite this article: Bone Joint J 2020;102-B(4):423-425.


Asunto(s)
Acetábulo/cirugía , Artroplastia de Reemplazo de Cadera/instrumentación , Luxación de la Cadera/cirugía , Prótesis de Cadera , Anciano , Anciano de 80 o más Años , Artroplastia de Reemplazo de Cadera/efectos adversos , Artroplastia de Reemplazo de Cadera/métodos , Registros Electrónicos de Salud , Femenino , Luxación de la Cadera/etiología , Humanos , Tiempo de Internación/estadística & datos numéricos , Masculino , Persona de Mediana Edad , Tempo Operativo , Diseño de Prótesis , Falla de Prótesis/etiología , Reoperación/métodos , Estudios Retrospectivos
4.
Appl Clin Inform ; 11(2): 265-275, 2020 03.
Artículo en Inglés | MEDLINE | ID: mdl-32268390

RESUMEN

BACKGROUND: UW Medicine was one of the first health systems to encounter and treat COVID-19 patients in the United States, starting in late February 2020. OBJECTIVE: Here we describe the rapid rollout of capabilities by UW Medicine Information Technology Services (ITS) to support our clinical response to the COVID-19 pandemic and provide recommendations for health systems to urgently consider, as they plan their own response to this and potentially other future pandemics. METHODS: Our recommendations include establishing a hospital incident command structure that includes tight integration with IT, creating automated dashboards for incident command, optimizing emergency communication to staff and patients, and preparing human resources, security, other policies, and equipment to support the transition of all nonessential staff to telework.We describe how UW Medicine quickly expanded telemedicine capabilities to include most primary care providers and increasing numbers of specialty providers. We look at how we managed expedited change control processes to quickly update electronic health records (EHR) with new COVID-19 laboratory and clinical workflows. We also examine the integration of new technology such as tele-intensive care (ICU) equipment and improved integration with teleconferencing software into our EHR. To support the rapid preparation for COVID-19 at other health systems, we include samples of the UW Medicine's COVID-19 order set, COVID-19 documentation template, dashboard metric categories, and a list of the top 10 things your health care IT organization can do now to prepare. CONCLUSION: The COVID-19 response requires new and expedited ways of approaching ITS support to clinical needs. UW Medicine ITS leadership hope that by quickly sharing our nimble response to clinical and operational requests, we can help other systems prepare to respond to this public health emergency.


Asunto(s)
Infecciones por Coronavirus , Prestación de Atención de Salud/organización & administración , Tecnología de la Información , Informática Médica , Pandemias , Neumonía Viral , Betacoronavirus , Comunicación , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/prevención & control , Infecciones por Coronavirus/terapia , Sistemas de Apoyo a Decisiones Clínicas , Registros Electrónicos de Salud , Sistemas Prepagos de Salud , Humanos , Noroeste de Estados Unidos , Pandemias/prevención & control , Neumonía Viral/diagnóstico , Neumonía Viral/prevención & control , Neumonía Viral/terapia , Salud Pública , Telemedicina , Flujo de Trabajo
5.
Zhonghua Yu Fang Yi Xue Za Zhi ; 54(4): 378-384, 2020 Apr 06.
Artículo en Chino | MEDLINE | ID: mdl-32268645

RESUMEN

In the perspective of promoting the strategic goal of healthy China, this study reviewed the informatization process of disease prevention and control in China and clarified the important role of national health information in chronic disease information surveillance throughout the life cycle. Guided by goals, needs, and problems, it is proposed that when basic personal electronic health record (EHR) are not well-established, personal electronic disease record (EDR) could be established to support business collaboration. Driven by the construction of national health informatization, this study proposed the relationship between the national health and chronic disease prevention and control coverage and described the architecture design of an integrated and restructured national disease prevention and control information system and its life-cycle monitoring and information management model for chronic disease health events.


Asunto(s)
Enfermedad Crónica/epidemiología , Prestación de Atención de Salud , Registros Electrónicos de Salud , Monitoreo Epidemiológico , China , Política de Salud , Humanos
6.
BMJ ; 369: m958, 2020 04 08.
Artículo en Inglés | MEDLINE | ID: mdl-32269037

RESUMEN

OBJECTIVE: To provide focused evaluation of predictive modeling of electronic medical record (EMR) data to predict 30 day hospital readmission. DESIGN: Systematic review. DATA SOURCE: Ovid Medline, Ovid Embase, CINAHL, Web of Science, and Scopus from January 2015 to January 2019. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: All studies of predictive models for 28 day or 30 day hospital readmission that used EMR data. OUTCOME MEASURES: Characteristics of included studies, methods of prediction, predictive features, and performance of predictive models. RESULTS: Of 4442 citations reviewed, 41 studies met the inclusion criteria. Seventeen models predicted risk of readmission for all patients and 24 developed predictions for patient specific populations, with 13 of those being developed for patients with heart conditions. Except for two studies from the UK and Israel, all were from the US. The total sample size for each model ranged between 349 and 1 195 640. Twenty five models used a split sample validation technique. Seventeen of 41 studies reported C statistics of 0.75 or greater. Fifteen models used calibration techniques to further refine the model. Using EMR data enabled final predictive models to use a wide variety of clinical measures such as laboratory results and vital signs; however, use of socioeconomic features or functional status was rare. Using natural language processing, three models were able to extract relevant psychosocial features, which substantially improved their predictions. Twenty six studies used logistic or Cox regression models, and the rest used machine learning methods. No statistically significant difference (difference 0.03, 95% confidence interval -0.0 to 0.07) was found between average C statistics of models developed using regression methods (0.71, 0.68 to 0.73) and machine learning (0.74, 0.71 to 0.77). CONCLUSIONS: On average, prediction models using EMR data have better predictive performance than those using administrative data. However, this improvement remains modest. Most of the studies examined lacked inclusion of socioeconomic features, failed to calibrate the models, neglected to conduct rigorous diagnostic testing, and did not discuss clinical impact.


Asunto(s)
Registros Electrónicos de Salud/estadística & datos numéricos , Readmisión del Paciente/estadística & datos numéricos , Adulto , Femenino , Humanos , Israel , Aprendizaje Automático , Masculino , Persona de Mediana Edad , Modelos Estadísticos , Medición de Riesgo
8.
An. Fac. Cienc. Méd. (Asunción) ; 53(1): 17-30, 20200401.
Artículo en Inglés | LILACS | ID: biblio-1095632

RESUMEN

Actualmente, la gestión de datos en el departamento de oncología es compleja y requiere sistemas de información avanzados para procesar datos donde la información "ómica" debe integrarse junto con los datos clínicos del paciente para mejorar el análisis de datos y el proceso de toma de decisiones. Este trabajo de investigación presenta una experiencia práctica en este contexto. Se ha diseñado un Modelo Conceptual (MC) para desarrollar un Sistema de Información (SI) con el fin de gestionar datos clínicos, patológicos y moleculares de manera integral en el departamento de oncología de dos hospitales principales en Paraguay. Además, se han propuesto arquetipos basados en modelos para especificar la estrategia de interacción del usuario. El MC y los arquetipos asociados son la base para desarrollar un SI clínico con el fin de cargar -primero- y gestionar -segundo- todos los datos clínicos que requiere el dominio, mostrando cuán factible es el enfoque en la práctica y cuánto se mejora la gestión de datos. En este trabajo, queremos reforzar con esta experiencia real, cómo el uso correcto de un MC junto con los arquetipos ayuda a diseñar, desarrollar y administrar mejores sistemas de información, enfatizando la relevancia del dominio clínico seleccionado.


Currently, data management in oncology department is complex and requires advanced Information Systems (ISs) to process data where "omic" information should be integrated together with patient's clinical data to improve data analysis and decision-making process. This research paper reports a practical experience in this context. A Conceptual Model (CM) has been designed to develop an Information System (IS) in order to manage clinical, pathological, and molecular data in a holistic way at the oncology department of two main Hospitals in Paraguay. Additionally, model-based archetypes have been proposed to specify the selected user interaction strategy. The CM and its associated archetypes are the basis to develop a clinical IS in order to load -firstly- and manage -secondly- all the clinical data that the domain requires, showing how feasible the approach is in practice, and how much the corresponding clinical data management is improved. In this work, we want to reinforce with this real experience how using a CM along with archetypes correctly helps to design, develop and manage better information systems, emphasizing the relevance of the selected clinical domain


Asunto(s)
Registros Electrónicos de Salud
10.
J Korean Med Sci ; 35(12): e78, 2020 Mar 30.
Artículo en Inglés | MEDLINE | ID: mdl-32233158

RESUMEN

BACKGROUND: Human leukocyte antigen (HLA) typing is important for transplant patients to prevent a severe mismatch reaction, and the result can also support the diagnosis of various disease or prediction of drug side effects. However, such secondary applications of HLA typing results are limited because they are typically provided in free-text format or PDFs on electronic medical records. We here propose a method to convert HLA genotype information stored in an unstructured format into a reusable structured format by extracting serotype/allele information. METHODS: We queried HLA typing reports from the clinical data warehouse of Seoul National University Hospital (SUPPREME) from 2000 to 2018 as a rule-development data set (64,024 reports) and from the most recent year (6,181 reports) as a test set. We used a rule-based natural language approach using a Python regex function to extract the 1) number of patients in the report, 2) clinical characteristics such as indication of the HLA testing, and 3) precise HLA genotypes. The performance of the rules and codes was evaluated by comparison between the extracted results from the test set and a validation set generated by manual curation. RESULTS: Among 11,287 reports for development set and 1,107 for the test set describing HLA typing for a single patient, iterative rule generation developed 124 extracting rules and 8 cleaning rules for HLA genotypes. Application of these rules extracted HLA genotypes with 0.892-0.999 precision and 0.795-0.998 recall for the five HLA genes. The precision and recall of the extracting rules for the number of patients in a report were 0.997 and 0.994 and those for the clinical variable extraction were 0.997 and 0.992, respectively. All extracted HLA alleles and serotypes were transformed according to formal HLA nomenclature by the cleaning rules. CONCLUSION: The rule-based HLA genotype extraction method shows reliable accuracy. We believe that there are significant number of patients who takes profit when this under-used genetic information will be return to them.


Asunto(s)
Antígenos HLA/genética , Prueba de Histocompatibilidad , Almacenamiento y Recuperación de la Información , Procesamiento de Lenguaje Natural , Algoritmos , Data Warehousing , Registros Electrónicos de Salud , Genotipo , Humanos , Seúl
11.
Ann Hematol ; 99(5): 1007-1016, 2020 May.
Artículo en Inglés | MEDLINE | ID: mdl-32157418

RESUMEN

Controversy regarding the risk of non-hematologic malignancies in myelofibrosis patients still exists. We aimed to examine the association between myelofibrosis and non-hematologic malignancies. A cohort of 1,469,790 adults without a diagnosis of myelofibrosis was identified on 1 January 2007, from the electronic medical records of the largest healthcare provider in Israel. Participants were followed up until 31 December 2015, for the occurrence of myelofibrosis. All cases of myelofibrosis were adjudicated by reviewing patients' electronic medical files. Using risk set sampling, four randomly selected controls (without myelofibrosis) were matched to each case of myelofibrosis on age, sex, ethnicity, and index date. Patients with and without myelofibrosis were followed from the index date until 31 December 2016 for the occurrence of non-hematologic malignancies based on the data from the Israel National Cancer Registry. The study included 550 patients with myelofibrosis and 2200 matched controls. Non-hematologic cancers occurred in 35 patients with myelofibrosis and 138 patients without myelofibrosis, reflecting a crude incidence rate of 27.9 and 15.3 per 1000 person-years, respectively. Myelofibrosis was independently associated with increased risk of non-hematologic malignancies with propensity score adjusted HR of 1.85 (95% CI, 1.09-3.15). No significant association was detected between myelofibrosis and the specific sites of non-hematologic malignancies. Treatment with ruxolitinib was not significantly associated with non-hematologic malignancies HR 1.36 (0.60-3.11). In conclusion, myelofibrosis appears to be associated with increased risk of non-hematologic malignancies. However, this study raises concerns about surveillance bias, suggesting that the association might be attributed to earlier detection rather than real increased risk.


Asunto(s)
Registros Electrónicos de Salud , Neoplasias/epidemiología , Mielofibrosis Primaria/epidemiología , Sistema de Registros , Anciano , Femenino , Humanos , Incidencia , Masculino , Persona de Mediana Edad , Estudios Retrospectivos , Factores de Riesgo
12.
Am J Nurs ; 120(4): 13, 2020 04.
Artículo en Inglés | MEDLINE | ID: mdl-32218026
13.
Artículo en Ruso | MEDLINE | ID: mdl-32119221

RESUMEN

Actually, the opportunity exists to obtain admittance to various data. The article presents the essence of approach to development of decentralized prototype of system managing medical records of patient using blockchain technology. The global analysis of cloud technologies using various experience of their implementation is given. The scientific novelty of study consists in step-by-step application of genuine prototype of patient medical data management system using blockchain technology. It is scientifically justified that applying cloud technologies in medicine permits to improve safety and integrity of medical data of patient and to support linking uncoordinated databases into one whole, making interaction of patients and physicians much more effective and comfortable.


Asunto(s)
Cadena de Bloques , Nube Computacional , Registros Electrónicos de Salud , Manejo de Datos , Registros Electrónicos de Salud/estadística & datos numéricos , Humanos
14.
J Med Syst ; 44(5): 92, 2020 Mar 18.
Artículo en Inglés | MEDLINE | ID: mdl-32189085

RESUMEN

An electronic health (e-health) system, such as a medical cyber-physical system, offers a number of benefits (e.g. inform medical diagnosis). There are, however, a number of considerations in the implementation of the medical cyber-physical system, such as the integrity of medical / healthcare data (e.g. manipulated data can result in misdiagnosis). A number of digital signature schemes have been proposed in recent years to mitigate some of these challenges. However, the security of existing signatures is mostly based on conventional difficult mathematical problems, which are known to be insecure against quantum attacks. In this paper, we propose a certificateless signature scheme, based on NTRU lattice. The latter is based on the difficulty of small integer solutions on the NTRU lattice, and is known to be quantum attack resilience. Security analysis and performance evaluations demonstrate that our proposed scheme achieves significantly reduced communication and computation costs in comparison to two other competing quantum resilience schemes, while being quantum attack resilience.


Asunto(s)
Seguridad Computacional , Confidencialidad , Registros Electrónicos de Salud/normas , Algoritmos , Comunicación , Costos y Análisis de Costo , Errores Diagnósticos , Humanos , Examen Físico
18.
Am J Nurs ; 120(3): 16, 2020 03.
Artículo en Inglés | MEDLINE | ID: mdl-32079784

RESUMEN

A lot more than you might think, according to a recent report.


Asunto(s)
Registros Electrónicos de Salud/organización & administración , Humanos , Errores Médicos/prevención & control
20.
PLoS One ; 15(2): e0228545, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-32045428

RESUMEN

A key requirement for longitudinal studies using routinely-collected health data is to be able to measure what individuals are present in the datasets used, and over what time period. Individuals can enter and leave the covered population of administrative datasets for a variety of reasons, including both life events and characteristics of the datasets themselves. An automated, customizable method of determining individuals' presence was developed for the primary care dataset in Swansea University's SAIL Databank. The primary care dataset covers only a portion of Wales, with 76% of practices participating. The start and end date of the data varies by practice. Additionally, individuals can change practices or leave Wales. To address these issues, a two step process was developed. First, the period for which each practice had data available was calculated by measuring changes in the rate of events recorded over time. Second, the registration records for each individual were simplified. Anomalies such as short gaps and overlaps were resolved by applying a set of rules. The result of these two analyses was a cleaned set of records indicating start and end dates of available primary care data for each individual. Analysis of GP records showed that 91.0% of events occurred within periods calculated as having available data by the algorithm. 98.4% of those events were observed at the same practice of registration as that computed by the algorithm. A standardized method for solving this common problem has enabled faster development of studies using this data set. Using a rigorous, tested, standardized method of verifying presence in the study population will also positively influence the quality of research.


Asunto(s)
Recolección de Datos/métodos , Conjuntos de Datos como Asunto , Registros Electrónicos de Salud/estadística & datos numéricos , Estudios de Seguimiento , Registro Médico Coordinado , Algoritmos , Continuidad de la Atención al Paciente/normas , Continuidad de la Atención al Paciente/estadística & datos numéricos , Recolección de Datos/normas , Bases de Datos Factuales , Conjuntos de Datos como Asunto/normas , Conjuntos de Datos como Asunto/estadística & datos numéricos , Pruebas Diagnósticas de Rutina/normas , Pruebas Diagnósticas de Rutina/estadística & datos numéricos , Registros Electrónicos de Salud/organización & administración , Registros Electrónicos de Salud/normas , Femenino , Humanos , Incidencia , Estudios Longitudinales , Masculino , Registro Médico Coordinado/normas , Pautas de la Práctica en Medicina/estadística & datos numéricos , Atención Primaria de Salud/organización & administración , Atención Primaria de Salud/normas , Atención Primaria de Salud/estadística & datos numéricos , Proyectos de Investigación , Accidente Cerebrovascular/tratamiento farmacológico , Accidente Cerebrovascular/epidemiología , Accidente Cerebrovascular/prevención & control , Factores de Tiempo , Gales/epidemiología , Warfarina/uso terapéutico
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