Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 1.469
Filtrar
1.
Artigo em Inglês | MEDLINE | ID: mdl-31610771

RESUMO

Immunisation at the earliest appropriate age and high levels of vaccine coverage at milestone ages are important in preventing the spread of vaccine-preventable diseases. At the Central Coast Public Health Unit, the authors sought to determine if follow-up of children said by the Australian Childhood Immunisation Register (ACIR) to be overdue for vaccination improved both of these factors. In a quality improvement activity, monthly ACIR lists of overdue Central Coast children aged 9 to 10 months of age were examined. The study alternated three months of intervention with three months of no intervention. The intervention was designed to find evidence of vaccination, first from the last known provider, and then if this was unsuccessful, from the parent. If no information was available, a letter was sent to the parents. If the child was indeed vaccinated, the register was updated. If the child was missing any vaccinations, the parent(s) were encouraged to complete the schedule. On reviewing routinely-published quarterly ACIR data at three-monthly intervals for 24 months after the intervention (or non-intervention), timeliness of vaccination improved in the intervention cohort. Central Coast fully vaccinated rates diverged from NSW rates during the study. In addition, the ACIR quarters that contained two out of three months of intervention rather than one out of three months of intervention had the highest rates of fully vaccinated children. The authors concluded that the intervention improved both timeliness of vaccination and the proportion of fully vaccinated children.


Assuntos
Programas de Imunização/estatística & dados numéricos , Esquemas de Imunização , Vacinação/estatística & dados numéricos , Vacinas/administração & dosagem , Austrália , Confiabilidade dos Dados , Pesquisas sobre Serviços de Saúde , Humanos , Lactente , Pais , Sistema de Registros
2.
Bone Joint J ; 101-B(10): 1292-1299, 2019 10.
Artigo em Inglês | MEDLINE | ID: mdl-31564146

RESUMO

AIMS: This study explores data quality in operation type and fracture classification recorded as part of a large research study and a national audit with an independent review. PATIENTS AND METHODS: At 17 centres, an expert surgeon reviewed a randomly selected subset of cases from their centre with regard to fracture classification using the AO system and type of operation performed. Agreement for these variables was then compared with the data collected during conduct of the World Hip Trauma Evaluation (WHiTE) cohort study. Both types of surgery and fracture classification were collapsed to identify the level of detail of reporting that achieved meaningful agreement. In the National Hip Fracture Database (NHFD), the types of operation and fracture classification were explored to identify the proportion of "highly improbable" combinations. RESULTS: The records were reviewed for 903 cases. Agreement for the subtypes of extracapsular fracture was poor; most centres achieved no better than "fair" agreement. When the classification was collapsed to a single option for "extracapsular" fracture, only four centres failed to have at least "moderate" agreement. There was only "moderate" agreement for the subtypes of intracapsular fracture, which improved to "substantial" when collapsed to "intracapsular". Subtrochanteric fracture types were well reported with "substantial" agreement. There was near "perfect" agreement for internal fixation procedures. "Perfect" or "substantial" agreement was achieved when the type of arthroplasty surgery was reported at the level of "hemiarthroplasty" and "total hip replacement". When reviewing data submitted to the NHFD, a minimum of 5.2% of cases contained "highly improbable" procedures for the stated fracture classification. CONCLUSION: The complexity of collecting fracture classification data at a national scale compromises the accuracy with which detailed classification systems can be reported. Data around type of surgery performed show similar tendencies. Data capture, reporting, and interpretation in future studies must take this into account. Cite this article: Bone Joint J 2019;101-B:1292-1299.


Assuntos
Artroplastia de Quadril/métodos , Fixação Interna de Fraturas/métodos , Hemiartroplastia/métodos , Fraturas do Quadril/classificação , Fraturas do Quadril/cirurgia , Reoperação/estatística & dados numéricos , Idoso , Idoso de 80 Anos ou mais , Artroplastia de Quadril/efeitos adversos , Estudos de Coortes , Confiabilidade dos Dados , Inglaterra , Feminino , Fixação Interna de Fraturas/efeitos adversos , Consolidação da Fratura/fisiologia , Hemiartroplastia/efeitos adversos , Humanos , Masculino , Auditoria Médica , Pessoa de Meia-Idade , Complicações Pós-Operatórias/fisiopatologia , Complicações Pós-Operatórias/cirurgia , Prognóstico , Amplitude de Movimento Articular/fisiologia , Reoperação/métodos , Resultado do Tratamento , País de Gales
5.
Einstein (Sao Paulo) ; 17(4): eAE4791, 2019.
Artigo em Inglês, Português | MEDLINE | ID: mdl-31553359

RESUMO

Data collection for clinical research can be difficult, and electronic health record systems can facilitate this process. The aim of this study was to describe and evaluate the secondary use of electronic health records in data collection for an observational clinical study. We used Cerner Millennium®, an electronic health record software, following these steps: (1) data crossing between the study's case report forms and the electronic health record; (2) development of a manual collection method for data not recorded in Cerner Millennium®; (3) development of a study interface for automatic data collection in the electronic health records; (4) employee training; (5) data quality assessment; and (6) filling out the electronic case report form at the end of the study. Three case report forms were consolidated into the electronic case report form at the end of the study. Researchers performed daily qualitative and quantitative analyses of the data. Data were collected from 94 patients. In the first case report form, 76.5% of variables were obtained electronically, in the second, 95.5%, and in the third, 100%. The daily quality assessment of the whole process showed complete and correct data, widespread employee compliance and minimal interference in their practice. The secondary use of electronic health records is safe and effective, reduces manual labor, and provides data reliability. Anesthetic care and data collection may be done by the same professional.


Assuntos
Registros Eletrônicos de Saúde/normas , Controle de Formulários e Registros/métodos , Sistemas Computadorizados de Registros Médicos/normas , Anestesia Geral/normas , Confiabilidade dos Dados , Formulários como Assunto , Humanos , Complicações Pós-Operatórias , Estudos Prospectivos , Reprodutibilidade dos Testes , Respiração Artificial/normas , Procedimentos Cirúrgicos Robóticos/normas , Fatores de Tempo
6.
BMC Bioinformatics ; 20(1): 465, 2019 Sep 10.
Artigo em Inglês | MEDLINE | ID: mdl-31500563

RESUMO

BACKGROUND: Atomic force microscopy (AFM) allows the mechanical characterization of single cells and live tissue by quantifying force-distance (FD) data in nano-indentation experiments. One of the main problems when dealing with biological tissue is the fact that the measured FD curves can be disturbed. These disturbances are caused, for instance, by passive cell movement, adhesive forces between the AFM probe and the cell, or insufficient attachment of the tissue to the supporting cover slide. In practice, the resulting artifacts are easily spotted by an experimenter who then manually sorts out curves before proceeding with data evaluation. However, this manual sorting step becomes increasingly cumbersome for studies that involve numerous measurements or for quantitative imaging based on FD maps. RESULTS: We introduce the Python package nanite, which automates all basic aspects of FD data analysis, including data import, tip-sample separation, base line correction, contact point retrieval, and model fitting. In addition, nanite enables the automation of the sorting step using supervised learning. This learning approach relates subjective ratings to predefined features extracted from FD curves. For ratings ranging from 0 to 10, our approach achieves a mean squared error below 1.0 rating points and a classification accuracy between good and poor curves that is above 87%. We showcase our approach by quantifying Young's moduli of the zebrafish spinal cord at different classification thresholds and by introducing data quality as a new dimension for quantitative AFM image analysis. CONCLUSION: The addition of quality-based sorting using supervised learning enables a fully automated and reproducible FD data analysis pipeline for biological samples in AFM.


Assuntos
Confiabilidade dos Dados , Aprendizado de Máquina , Microscopia de Força Atômica , Software , Animais , Automação , Nanotecnologia , Peixe-Zebra
7.
Stud Health Technol Inform ; 267: 39-45, 2019 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-31483252

RESUMO

Registries are a widely accepted method in health services research. Registry owners are faced with the challenge to document and assure data quality, vital for answering research questions and conducting quality research. Therefore a survey on indicators for data quality was conducted as part of a German funding initiative. A list of 51 pre-defined quality indicators was provided to 16 patient registry projects in a web based survey. The assessment included three criteria derived from the Rand Appropriateness Method (RAM), the application area, and three criteria representing a project-specific perspective. Considering the criteria adapted from RAM, a core set of 17 indicators could be identified. This core set covered important dimensions, such as case completeness, data completeness and validity. Adding importance as a criterion from a project-specific perspective led to a subset of six indicators. The selection of indicators identified through this survey may be applied on different use cases, e.g. a) benchmarking between registries, b) benchmarking of study sites, and c) value-based remuneration of study sites. Thus, the presented core set of indicators can be used as a basis to improve quality of registry data with a systematic approach.


Assuntos
Confiabilidade dos Dados , Benchmarking , Humanos , Indicadores de Qualidade em Assistência à Saúde , Sistema de Registros , Inquéritos e Questionários
8.
Stud Health Technol Inform ; 267: 247-253, 2019 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-31483279

RESUMO

INTRODUCTION: Data quality (DQ) is an important prerequisite for secondary use of electronic health record (EHR) data in clinical research, particularly with regards to progressing towards a learning health system, one of the MIRACUM consortium's goals. Following the successful integration of the i2b2 research data repository in MIRACUM, we present a standardized and generic DQ framework. STATE OF THE ART: Already established DQ evaluation methods do not cover all of MIRACUM's requirements. CONCEPT: A data quality analysis plan was developed to assess common data quality dimensions for demographic-, condition-, procedure- and department-related variables of MIRACUM's research data repository. IMPLEMENTATION: A data quality analysis (DQA) tool was developed using R scripts packaged in a Docker image with all the necessary dependencies and R libraries for easy distribution. It integrates with the i2b2 data repository at each MIRACUM site, executes an analysis on the data and generates a DQ report. LESSONS LEARNED: Our DQA tool brings the analysis to the data and thus meets the MIRACUM data protection requirements. It evaluates established DQ dimensions of data repositories in a standardized and easily distributable way. This analysis allowed us to reveal and revise inconsistencies in earlier versions of the ETL jobs. The framework is portable, easy to deploy across different sites and even further adaptable to other database schemes. CONCLUSION: The presented framework provides the first step towards a unified, standardized and harmonized EHR DQ assessment in MIRACUM. DQ issues can now be systematically identified by individual hospitals to subsequently implement site- or consortium-wide feedback loops to increase data quality.


Assuntos
Confiabilidade dos Dados , Registros Eletrônicos de Saúde , Bases de Dados Factuais
9.
Am J Orthod Dentofacial Orthop ; 156(3): 420-428, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31474272

RESUMO

INTRODUCTION: This study aimed to test the accuracy of the 3-dimensional (3D) digital dental models generated by the Dental Monitoring (DM) smartphone application in both photograph and video modes over successive DM examinations in comparison with 3D digital dental models generated by the iTero Element intraoral scanner. METHODS: Ten typodonts with setups of class I malocclusion and comparable severity of anterior crowding were used in the study. iTero Element scans along with DM examination in photograph and video modes were performed before tooth movement and after each set of 10 Invisalign aligners for each typodont. Stereolithography (STL) files generated from the DM examinations in photograph and video modes were superimposed with the STL files from the iTero scans using GOM Inspect software to determine the accuracy of both photograph and video modes of DM technology. RESULTS: No clinically significant differences, according to the American Board of Orthodontics-determined standards, were found. Mean global deviations for the maxillary arch ranged from 0.00149 to 0.02756 mm in photograph mode and from 0.0148 to 0.0256 mm in video mode. Mean global deviations for the mandibular arch ranged from 0.0164 to 0.0275 mm in photograph mode and from 0.0150 to 0.0264 mm in video mode. Statistically significant differences were found between the 3D models generated by the iTero and the DM application in photograph and video modes over successive DM examinations. CONCLUSIONS: 3D digital dental models generated by the DM smartphone application in photograph and video modes are accurate enough to be used for clinical applications.


Assuntos
Confiabilidade dos Dados , Técnica de Moldagem Odontológica , Modelos Dentários , Processamento de Imagem Assistida por Computador/métodos , Imagem Tridimensional/métodos , Projeto Auxiliado por Computador , Arco Dental , Humanos , Má Oclusão/diagnóstico por imagem , Aparelhos Ortodônticos/normas , Aparelhos Ortodônticos Removíveis , Ortodontia/normas , Fotografia Dentária , Smartphone , Software , Estereolitografia , Tecnologia Odontológica/métodos , Técnicas de Movimentação Dentária , Gravação em Vídeo
11.
Stud Health Technol Inform ; 264: 1690-1691, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438295

RESUMO

The learning health system depends on a cycle of evidence generation, translation to practice, and continuous practice-based data collection. Clinical practice guidelines (CPGs) represent medical evidence, translated into recommendations on appropriate clinical care. The FAIR guiding principles offer a framework for publishing the extensive knowledge work of CPGs and their resources. In this narrative literature review, we propose that FAIR CPGs would lead to more efficient production and dissemination of CPG knowledge to practice.


Assuntos
Programas Governamentais , Sistemas de Informação em Saúde , Guias de Prática Clínica como Assunto , Confiabilidade dos Dados
12.
Stud Health Technol Inform ; 265: 101-106, 2019 Aug 09.
Artigo em Inglês | MEDLINE | ID: mdl-31431584

RESUMO

Medication errors are preventable adverse events or unsafe conditions caused by inappropriate uses of medication. To collect data of patient safety events (PSE) and to analyze the root causes of PSE, reporting systems have been implemented in healthcare settings and patient safety organizations (PSO). However, the poor data quality of reports impedes the reporting and root cause analysis (RCA) of PSE. Incomplete or missing data is the most prevalent problem in event reports. To assess the data quality of PSE reports, we used an adapted taxonomy as the data evaluation model to evaluate the quality of narrative reports collected by a PSO. Sample reports were extracted based on eight error types and scored by experts. Most structured fields in the reports were ignored by reporters. In contrast, the narrative parts of the reports contain rich and valuable information. The evaluation results show that the adapted taxonomy is a promising tool for report quality assessment and improvement.


Assuntos
Confiabilidade dos Dados , Erros de Medicação , Humanos , Narração , Segurança do Paciente , Análise de Causa Fundamental
13.
Stud Health Technol Inform ; 264: 1980-1981, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438438

RESUMO

Vital Sign Data Quality is essential for successful implementation of clinical decision support systems in emergency care. Studies have shown that data quality is inadequate and needs improvement. This study shows that data quality is dependent on both technical and human factors and provides a conceptual model of data quality governance and improvement in the emergency department.


Assuntos
Confiabilidade dos Dados , Sinais Vitais , Serviço Hospitalar de Emergência , Teoria Fundamentada , Humanos , Suécia
14.
Stud Health Technol Inform ; 264: 773-777, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438029

RESUMO

ObsCare is an obstetric-specific Electronic Health Record in use in nine Portuguese obstetric departments. Like other EHRs, it faces major challenges related to semantic interoperability and data quality. openEHR is proposed to address those needs. This study aimed to describe a summary representation of Obscare workflow and to validate whether archetypes in the openEHR Clinical Knowledge Manager repository can represent ObsCare clinical concepts. The study included the phases: a) ObsCare form selection; b) Description of the workflow care process; c) Detailed data extraction; and d) CKM models analysis. 379 variables were analyzed: 219 were fully represented in CKM repository; 99 were partially represented and needed archetype modification; and 61 were not represented and need new archetypes. To conclude, our study showed that the openEHR CKM repository requires further enhancements to be able to fully answer to the needs of an obstetric-specific EHR, the ObsCare software.


Assuntos
Registros Eletrônicos de Saúde , Software , Confiabilidade dos Dados , Assistência à Saúde , Feminino , Humanos , Trabalho de Parto , Gravidez
15.
Stud Health Technol Inform ; 264: 1606-1607, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438254

RESUMO

Data quality assessments (DQA) reveal quality problems in electronic medical records (EHR) data. Generally, DQA methods describe quality rules in programming languages through hard-coding, which limits the implementation of DQA between heterogeneous systems and the interoperability of quality rules. To cover this gap, we conducted a case study applying Guideline Definition Language (GDL) in DQA to assess the quality of patient admission data in an EHR system of a hospital in China.


Assuntos
Confiabilidade dos Dados , China , Registros Eletrônicos de Saúde , Humanos , Linguagens de Programação
16.
Stud Health Technol Inform ; 264: 1488-1489, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438195

RESUMO

Large healthcare datasets of Electronic Health Record data became indispensable in clinical research. Data quality in such datasets recently became a focus of many distributed research networks. Despite the fact that data quality is specific to a given research question, many existing data quality platform prove that general data quality assessment on dataset level (given a spectrum of research questions) is possible and highly requested by researchers. We present comparison of 12 datasets and extension of Achilles Heel data quality software tool with new rules and data characterization measures.


Assuntos
Confiabilidade dos Dados , Registros Eletrônicos de Saúde , Software
17.
Stud Health Technol Inform ; 264: 1508-1509, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438205

RESUMO

The Demonstrator study aims to analyse comorbidities and rare diseases among patients from German university hospitals within the German Medical Informatics Initiative. This work aimed to design and determine the feasibility of a model to assess the quality of the claims data used in the study. Several data quality issues were identified affecting small amounts of cases in one of the participating sites. As a next step an extension to all participating sites is planned.


Assuntos
Confiabilidade dos Dados , Informática Médica , Hospitais Universitários , Humanos
18.
Pan Afr Med J ; 33(Suppl 2): 10, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31402968

RESUMO

Introduction: in spite of the efforts and resources committed by the division of infectious disease and epidemiology (DIDE) of the national public health institute of Liberia (NPHIL)/Ministry of health to strengthening integrated disease surveillance and response (IDSR) across the country, quality data management system remains a challenge to the Liberia NPHIL/MoH (Ministry of health), with incomplete and inconsistent data constantly being reported at different levels of the surveillance system. As part of the monitoring and evaluation strategy for IDSR continuous improvement, data quality assessment (DQA) of the IDSR system to identify successes and gaps in the disease surveillance information system (DSIS) with the aim of ensuring data accuracy, reliability and credibility of generated data at all levels of the health system; and to inform an operational plan to address data quality needs for IDSR activities is required. Methods: multi-stage cluster sampling that included stage 1: simple random sample (SRS) of five counties, stage 2: simple random sample of two districts and stage 3: simple random sample of three health facilities was employed during the study pilot assessment done in Montserrado County with Liberia institute of bio medical research (LIBR) inclusive. A total of thirty (30) facilities was targeted, twenty nine (29) of the facilities were successfully audited: one hospital, two health centers, twenty clinics and respondents included: health facility surveillance focal persons (HFSFP), zonal surveillance officers (ZSOs), district surveillance officers (DSOs) and County surveillance officers (CSOs). Results: the assessment revealed that data use is limited to risk communication and sensitization, no examples of use of data for prioritization or decision making at the subnational level. The findings indicated the following: 23% (7/29) of health facilities having dedicated phone for reporting, 20% (6/29) reported no cell phone network, 17% (5/29) reported daily access to internet, 56.6% (17/29) reported a consistent supply of electricity, and no facility reported access to functional laptop. It was also established that 40% of health facilities have experienced a stock out of laboratory specimens packaging supplies in the past year. About half of the surveyed health facilities delivered specimens through riders and were assisted by the DSOs. There was a large variety in the reported packaging process, with many staff unable to give clear processes. The findings during the exercise also indicated that 91% of health facility staff were mentored on data quality check and data management including the importance of the timeliness and completeness of reporting through supportive supervision and mentorship; 65% of the health facility assessed received supervision on IDSR core performance indicator; and 58% of the health facility officer in charge gave feedback to the community level. Conclusion: public health is a data-intensive field which needs high-quality data and authoritative information to support public health assessment, decision-making and to assure the health of communities. Data quality assessment is important for public health. In this review completeness, accuracy, and timeliness were the three most-assessed attributes. Quantitative data quality assessment primarily used descriptive surveys and data audits, while qualitative data quality assessment methods include primarily interviews, questionnaires administration, documentation reviews and field observations. We found that data-use and data-process have not been given adequate attention, although they were equally important factors which determine the quality of data. Other limitations of the previous studies were inconsistency in the definition of the attributes of data quality, failure to address data users' concerns and a lack of triangulation of mixed methods for data quality assessment. The reliability and validity of the data quality assessment were rarely reported. These gaps suggest that in the future, data quality assessment for public health needs to consider equally the three dimensions of data quality, data use and data process. Measuring the perceptions of end users or consumers towards data quality will enrich our understanding of data quality issues. Data use is limited to risk communication and sensitization, no examples of use of data for prioritization or decision making at the sub national level.


Assuntos
Controle de Doenças Transmissíveis/métodos , Doenças Transmissíveis/epidemiologia , Vigilância em Saúde Pública/métodos , Saúde Pública , Análise por Conglomerados , Comunicação , Confiabilidade dos Dados , Instalações de Saúde/estatística & dados numéricos , Humanos , Libéria/epidemiologia , Projetos Piloto , Reprodutibilidade dos Testes , Risco , Inquéritos e Questionários
19.
Stud Health Technol Inform ; 264: 1425-1426, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438163

RESUMO

We present the regional professional network to support the Renal Epidemiology Information Network (REIN) registry in maintaining high quality data production and information analyses in Ile-De-France region. The network is based on a long term partnership between the nephrologists and a regional methodology support unit. It integrates clinical research assistants for data quality control. We also present organizational methods on maintaining the registry and enhancing information analyses and automating analyses reports.


Assuntos
Sistema de Registros , Confiabilidade dos Dados , França , Serviços de Informação
20.
Stud Health Technol Inform ; 264: 1458-1459, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438180

RESUMO

Standardised, automated quality reports were generated at three pilot locations of the decentralized translational research network DKTK with separated local data warehouses (LDW), for assessing syntactic conformity against common data element definitions deposited in a central metadata repository (MDR). Deviations in the LDW were categorised, and locally corrected. Comparisons of reports from two time points confirm a major improvement in data quality in terms of syntactic conformity, an essential prerequisite for network-wide data integration.


Assuntos
Confiabilidade dos Dados , Pesquisa Médica Translacional , Elementos de Dados Comuns , Data Warehousing , Metadados
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA