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Article | IMSEAR | ID: sea-223698


Good quality health, nutrition and demographic survey data are vital for evidence-based decision-making. Existing literature indicates system specific, data collection and reporting gaps that affect quality of health, nutrition and demographic survey data, thereby affecting its usability and relevance. To mitigate these, the National Data Quality Forum (NDQF), under the Indian Council of Medical Research (ICMR) - National Institute of Medical Statistics (NIMS) developed the National Guidelines for Data Quality in Surveys delineating assurance mechanisms to generate standard quality data in surveys. The present article highlights the principles from the guidelines for informing survey researchers/organizations in generating good quality survey data. It describes the process of development of the national guidelines, principles for each of the survey phases listed in the document and applicability of them to data user for ensuring data quality. The guidelines may be useful to a broad-spectrum of audience such as data producers from government and non-government organizations, policy makers, research institutions, as well as individual researchers, thereby playing a vital role in improving quality of health, nutrition and demographic data ecosystem.

Ethiop. j. health dev. (Online) ; 36(1): 1-8, 2022. tables
Article in English | AIM | ID: biblio-1398395


Background: Health data quality are limited within the health sectors of low-and middle-income countries (LMICs). Although public health decision-making is mainly dependent on the timely availability of quality data, the quality of healthdata is not satisfactory in some countries, including in the Somali Regional State. Therefore, this baseline assessment was aimed at assessing the level of data quality and its determinants in the public health sector of the Somali Regional State, Ethiopia. Methods: A baseline assessment was conducted as part of an implementation research project. The study was conducted in three selected public health facilities of the Jigjiga Woreda, including the Woreda Health Office and the Somali Regional Health Bureau. A total of 179 health care workers participated in the survey. Interviewer guided self-administered, record review, and observation data collection techniques were used for data collection. Data wasanalyzed using descriptive, bivariate, and multivariate logistic models to identify predictors of data quality. A P-value of 0.05 was used as the statistical significance cut-off point. Results:The overall data accuracy and content completeness in the studied facilities was88.12% and 75.75%, respectively. Data accuracy was 92.2% in the Karamara Hospital, 83.1% in Jigjiga Health Center, and 79.8% in the Ayardaga Health Center. Content completeness was 81.6% in the KaramaraHospital, 81.2% in the Jigjiga Health Center, and 69.7% in the Ayardaga health center. Forthe studied variables, the data recording value given by their immediate supervisors was a strong predictor of data accuracy in the study setting. The odds of thosewho felt thatdata recording was notvalued by supervisors had 0.26 times poorer data accuracy than their counterparts (AOR: 0.26, 95%CI: 0.10, 0.66). Conclusion:Both the accuracy and completeness of health data in Eastern Ethiopia were inadequate. As a result, health work force immediate supervisors and Performance Monitoring Teams (PMT) should undertake regular and ongoing supervision and provide timely feedback for corrective action. In addition, specialized training in data recording and documentation would be beneficial in bridging the gap between workers' skill. [Ethiop. J. Health Dev. 2022;36 (SI-1)]

Humans , Implementation Science , Facilities and Services Utilization , Research , Public Health , Educational Measurement , Evaluation Studies as Topic , Data Accuracy
Ethiop. j. health dev. (Online) ; 36(1): 1-10, 2022. tables
Article in English | AIM | ID: biblio-1398515


Background:Ethiopia utilisesthedistrict health information systemfor health information management. However,the lower level health structure seems inaccurate in comparisonto theparallel reportingsystem, withlimited evidence on its effect ondata quality and information use.Therefore,the present study aimed to assess the influence of a parallel reporting system on data quality and information use at the lower level structuresof the Amhara region, Northwest Ethiopia.Methods:The study was conducted in five districts of the Amhara region using an explanatory case study design. Twenty respondents were interviewed from the 1st­30thApril 2021,usinga semi-structured key informant interview(KII)guide with multiple probes to explore relevant information. The data was transcribed into English and transferred to the Open-Code 4.02 software for analysis. Textual data werecoded, and themes were identified from the synthesis. Inductive thematic analysis was applied to identify the relationships among the emerging themes in order todraw a relevant conclusion. Results:Five themeswere emerged fromthe analysis, includingthe current practice of parallel reporting, a program area of parallel reporting, the influence of parallel reporting, reasonsfor parallel reporting,and means to avoid parallel reporting.Likewise, parallelreportingwasdone at the district level and at the point of service delivery. The respondents described maternal and child health programs often usingparallel reporting. Parallel reporting was described as havingundesirable impacts on routinely collected health data quality and use. Moreover, it increases the work burden; andaffects service quality,the the satisfactionlevelsof clients and staff, and the overall efficiency. The main reasons for practicingparallel reporting were:missing important data elements in DHIS2, single language, varying stakeholders' interests, and lack of conductinga partnerforum.Conclusion and implication:Against the national health information system'sguiding principlesand vision, parallelreporting is practicedat the lower health system levelsfor various programs. Therefore, a corrective measure should be taken to achieve the country's information revolution (IR) agenda. To avoid parallel reporting mechanisms, it is recommended that regular partner forums at the district level must be strengthened, important data elements should beincorporated into the DHIS 2, and additional language platforms should be be included in theDHIS2 system.

Humans , Parallel Lagoons , Data Accuracy , Abortifacient Agents , Certification , Lower Extremity
Article in Chinese | WPRIM | ID: wpr-996019


Quality management and control of single disease is a means to continuously improve medical quality and safety by building a set of quality control indicators and evaluation systems based on the whole process of disease diagnosis and treatment. In the actual single disease management process, the reporting of each disease involved data from various systems such as electronic medical records, and the data integration was difficult. While the traditional manual reporting method took a lot of time and the data accuracy could not be guaranteed. In the development process of hospital informatization, a hospital has designed a set of intelligent full-closed loop single disease management platform based on the hospital information system, by integrating the existing human and information data resources of the hospital. This platform integrated functions of single disease intranet reporting, in-depth capture of reporting elements, single-disease quality index management, and single-disease real-time intelligent control, in order to promote more refined and intelligent disease management and thus steadily improve medical quality and safety.

Article in Chinese | WPRIM | ID: wpr-995994


Objective:To study the feasibility of control charts in the quality management of hospital statistical data as a reference for improving such management.Methods:Main business indicators of the main campus and some business indicators of the affiliated campus of a tertiary general hospital from January to May 2022 were selected. K-S test and chi-square goodness of fit test were used to test data in its statistical daily report, analyzing whether the data conform to the specific distributions. Then appropriat control chart were used according to the data type and distribution type. Minitab 21.1 software was used to draw the hospital data quality control chart, and data quality was monitored by analyzing the distribution of data points in the control chart.Results:The test found that the number of admissions, ultrasound examinations and emergency department visits in the main campus, and CT examinations in the affiliated campus, conformed to normal distribution, and single value control charts were applied. The number of ambulance trips in the main campus and the affiliated campus conform to Poisson distribution, and the defect number control chart was applied. The number of inpatient deaths in the main campus conform to a geometric distribution, and a rare event control chart was applied. The volume of admissions and ultrasound examinations in the main campus were mostly influenced by other factors, and the single-value selective control chart was used to further determine the cause of abnormal data distribution. The results of the control chart analysis showed that, there were no abnormal points in the data distribution of admissions, color ultrasound volume and in-hospital deaths in the main campus, two abnormal points in the CT examination volume in the affiliated campus. The control charts for the number of emergency department visits in the main campus and the number of ambulance trips in the main and affiliated campuses each had one outlier. It was verified that one anomaly in the volume of CT examinations in the affiliated campus and one anomaly in the number of ambulance trips in the affiliated campus were caused by data errors, while the other data were correct.Conclusions:It is feasible to use control charts to monitor the quality of hospital data, which can be used as a quality management tool to assist the quality management of hospital data.

Journal of Chinese Physician ; (12): 1060-1066, 2022.
Article in Chinese | WPRIM | ID: wpr-956265


Objective:To evaluate the data quality of Shenzhen Type 1 Diabetes Alliance (SZT1D), and to provide a basis for evaluation and improvement for the continuous improvement of data quality.Methods:From December 2018 to July 2021, 697 first-visit type 1 diabetes (T1DM) patients (including 501 in Shenzhen and 196 out-of-Shenzhen) and 120 re-visited T1DM patients (including 113 in Shenzhen and 7 out-of-Shenzhen) who were registered by SZT1D in collaborative research platform network of China Type 1 Diabetes Alliance (hereinafter referred to as China T1D). The data quality was evaluated from three dimensions: data completion, accuracy and revisit. The data completion degree was evaluated by the overall data completion degree and the key indicator completion degree; the data accuracy was evaluated by the probability of abnormal blood glucose value; the patient′s return visit was evaluated by the return visit rate.Results:The main characteristics of T1DM in SZT1D were young and middle-aged adults [age: (34.4±17.1)years] with thin body [BMI: (19.80±3.52)kg/m 2)], half of male and female patients [proportion of male: 52.4%(365/697)]; the main types of diagnosis were classical T1DM [65.22%(150/230)] and latent autoimmune diabetes in adults(LADA) [26.08%(60/230)], and the fasting blood glucose (FPG) [(10.93±6.98)mmol/L] and glycosylated hemoglobin (HbA 1c) [(10.63±3.01)%] were high. The average completion rate of the overall data of the first diagnosed patients in SZT1D was only 60% [(62.9±31.5)%]: the number of patients with overall data completion ≥80% in SZT1D was only 50.2%(350/697); the number of patients with overall data completion ≥80% in Shenzhen was less than that outside Shenzhen [44.3%(222/501) vs 65.3%(128/196), P<0.001]. The key indicators with better completion rate of first-visit were disease course [76.2%(531/697)], age of onset [75.8%(528/697)], family history of diabetes [74.9%(522/697)], etc., but none of them had a completion rate of more than 80%, and the diabetes self-management behavior assessment questionnaire and scale score were completely missing; the frequency of daily blood glucose monitoring [46.1%(231/501) vs 64.3%(126/196), P<0.001], current insulin regimen [44.3%(222/501) vs 63.3%(124/196), P<0.001], number of diabetic ketoacidosis (DKA) since the onset of the disease [45.7%(229/501) vs 64.8%(127/196), P<0.001] and the number of symptomatic hypoglycemia in the past 1 month [39.3%(197/501) vs 63.8%(125/196), P<0.001] were higher in Shenzhen than those reported outside Shenzhen. In addition, the probability of abnormal FPG and postprandial glucose (PPG) [5.2%(24/466); 3.8%(19/236)] were low. The revisit rate was not high [17.2%(120/697)], and the revisit rate in Shenzhen was higher than that outside Shenzhen [22.6%(113/501) vs 3.6%(7/196), P<0.001]. The first revisit rate was 16.2%(113/697) and the second revisit rate was seriously insufficient [1.0%(7/697)]. Conclusions:The data quality of T1DM patients recorded by SZT1D needs to be further improved. Improving the information interconnection between China-T1D and SZT1D, employing quality control personnel and building a systematic data quality evaluation analysis and feedback mechanism are methods to promote the comprehensive, accurate and efficient input of T1DM data and continuously improve the evaluation methods to improve the overall data quality.

J. health inform ; 13(1): 17-23, jan.-mar. 2021. ilus
Article in Portuguese | LILACS | ID: biblio-1363036


Objetivo: Este artigo descreve um trabalho de pesquisa sobre a aplicação de um modelo adaptado de avaliação da Qualidade da Informação (QI) do Prontuário Eletrônico do Paciente (PEP) do Hospital de Clínicas de Itajubá com o objetivo de propor melhorias na qualidade dos dados. Método: Foi aplicado o modelo adaptado de avaliação da QI que contém passos e instruções para avaliação da informação, impacto no negócio e assim desenvolver os planos de melhorias para as informações do PEP. Resultados: Os resultados demonstram que as dimensões da QI Reputação, Acessibilidade e Valor agregado são as que impactam o processo de decisão clínica. Através da identificação destas dimensões foi realizada a investigação das causas raiz e desenvolvido os planos de melhorias da QI. Conclusão: O caminho metodológico permitiu desenvolver um projeto de Qualidade de Informação tendo como resultado as ações necessárias para melhoria contínua da informação.

Objective: This article describes a research project on the application of an adapted Data Quality Assessment model of the Electronic Health Records (EHR) of the Hospital de Clínicas de Itajubá in order to propose improvements in data quality. Method: The adapted IQ evaluation model was applied, which contains steps and instructions for assessing information, impact on business and thus developing improvement plans for EHR information. Results: The results demonstrate that the dimensions of data Quality Reputation, Accessibility and Added Value are what impact the making decision process. Through the identification of these dimensions, root causes were investigated and IQ improvement plans were developed. Conclusion: The methodological path allowed the development of an Information Quality project, resulting in the necessary actions for continuous information improvement.

Objetivo: Este articulo describe un proyecto de investigación sobre la aplicación de un modelo de Evaluación de la Calidad de la Información del Registro electrónico de pacientes (REP) del Hospital de Clínicas Itajubá para proponer mejoras en la calidad de los datos. Método: Se aplicó el modelo de evaluación Calidad de la Información adaptado, que contiene pasos e instrucciones para asesorar información, impacto en los negocios y, por lo tanto, desarrollar planes de mejora para la información REP. Resultados: Los resultados demuestran que las dimensiones de reputación, accesibilidad y valor agregado son las que impactan el proceso de decisión clínica. A través de la identificación de estas dimensiones, se investigaron las causas raíz y se desarrollaron planes de mejora del coeficiente intelectual. Conclusión: La ruta metodológica permitió el desarrollo de un proyecto de calidad de la información, lo que resultó en las acciones necesarias para la mejora contínua de la información.

Humans , Decision Support Systems, Clinical , Electronic Health Records , Quality Improvement , Data Accuracy
Cad. Saúde Pública (Online) ; 37(10): e00317020, 2021. tab
Article in Portuguese | LILACS | ID: biblio-1339524


A violência policial letal é um problema de saúde pública. Embora o Sistema de Informações sobre Mortalidade (SIM) seja o registro mais confiável sobre mortes por agressão, o mesmo não acontece nos casos de violência policial letal, que apresenta um alto grau de subnotificação quando comparado aos dados da Secretaria de Segurança Pública de São Paulo (SSP-SP). O presente estudo tem como objetivo estimar a subnotificação nas duas fontes oficiais de informação (SIM e SSP-SP), identificando as categorias da CID-10 utilizadas nos casos de violência policial letal incorretamente classificadas e calcular as taxas de mortalidade nos anos de 2014 e 2015 no Município de São Paulo, Brasil. Por meio da vinculação dos dados do SIM e da SSP-SP, descrevemos o uso das causas básicas de morte nos casos de violência policial letal, estimamos a subnotificação no SIM e na SSP-SP com a metodologia captura-recaptura e as taxas de mortalidade no município. A partir da vinculação das duas bases de dados, nota-se que a maior parte dos óbitos por violência policial letal foi classificada incorretamente (53%) em outras causas básicas de morte no SIM. Observa-se que tanto o SIM como a SSP-SP subnotificam as mortes cometidas por policiais em magnitudes distintas (53,2% no SIM e 7,9% na SSP-SP). A reclassificação dos óbitos a partir da vinculação adicionou ganho por parte do SIM, que passou a ter a mesma taxa média de mortalidade do que a SSP-SP (3,44/100 mil), diminuindo a subnotificação em comparação com o cenário inicial. O registro correto da morte é o primeiro passo para o direito à justiça e à verdade. Registrar com qualidade é garantir o direito à informação, sendo este não um fim, mas apenas o começo na tarefa da prevenção. O compartilhamento de dados e o trabalho intersetorial se faz urgente.

Deadly police force is a public health problem. Although the Mortality Information System (SIM) is the most reliable record of deaths from violence, the same is not true for cases of deadly police force, which displays a high degree of underreporting when compared to data from the São Paulo Department of Law Enforcement (SSP-SP). The current study aimed to estimate underreporting in the two official data sources (SIM and SSP-SP), identifying the ICD-10 categories used in cases of incorrectly classified deadly police force and mortality rates in the years 2014 and 2015 in the city of São Paulo, Brazil. Using linkage of data from the SIM and SSP-SP databases, we describe the use of underlying causes of death in cases of deadly police force, estimating underreporting in the SIM and the SSP-SP with the capture-recapture methodology and mortality rates in the city. Based on the database linkage, most of the deaths from deadly police force were classified incorrectly (53%) as other underlying causes of death in the SIM. Both the SIM and SSP-SP underreported the deaths committed by police officers, with different magnitudes (53.2% in the SIM and 7.9% in the SSP-SP). Reclassification of the deaths via linkage added a gain in the SIM, which now had the same mean mortality rate as the SSP-SP (3.44/100,000), thereby decreasing the underreporting in comparison to the initial scenario. Correct recording of death is the first step to the ensuring the right to justice and truth. Recording with quality means to guarantee the right to information, which is not an end per se, but the start in the task of prevention. Data-sharing and inter-sector work are urgently needed.

La violencia policial letal es un problema de salud pública. A pesar de que el Sistema de Información de la Mortalidad (SIM) sea el registro más fiable sobre muertes por agresión, este no se produce en los casos de violencia policial letal, que presenta un alto grado de subnotificación, cuando se compara con los datos de la Secretaria de Seguridad Pública de São Paulo (SSP-SP). Este estudio tiene como objetivo estimar la subnotificación en las dos fuentes oficiales de información (SIM y SSP-SP), identificando las categorías de la CID-10 utilizadas en los casos de violencia policial letal incorrectamente clasificados, así como calcular las tasas de mortalidad durante los años de 2014 y 2015 en el municipio de São Paulo, Brasil. Mediante la vinculación de los datos del SIM y de la SSP-SP, describimos el uso de las causas básicas de muerte en los casos de violencia policial letal, estimamos la subnotificación en el SIM y en la SSP-SP, con la metodología capture-recapture y las tasas de mortalidad en el municipio. A partir de la vinculación de las dos bases de datos, se nota que la mayor parte de los óbitos de violencia policial letal se clasificaron incorrectamente (53%) en otras causas básicas de muerte en el SIM. Se observa que tanto el SIM, como la SSP-SP, subnotifican las muertes cometidas por policías, en magnitudes distintas (53,2% en el SIM y 7,9% en la SSP-SP). La reclasificación de los óbitos a partir de la vinculación benefició al SIM, que pasó a tener la misma tasa media de mortalidad que la SSP-SP (3,44/100 mil), disminuyendo la subnotificación, en comparación con el escenario inicial. El registro correcto de la muerte es el primer paso para el derecho a la justicia y a la verdad. Registrar con calidad es garantizar el derecho a la información, siendo este no un fin, sino solo el comienzo de la tarea de prevención. El intercambio de datos y el trabajo intersectorial es algo urgente.

Humans , Police , Data Accuracy , Brazil/epidemiology , Cause of Death , Law Enforcement
Cad. saúde colet., (Rio J.) ; 29(spe): 205-210, 2021. tab, graf
Article in Portuguese | LILACS-Express | LILACS | ID: biblio-1364659


Resumo Introdução O debate em torno do quesito de óbito no Censo Demográfico brasileiro foi retomado pela proximidade do Censo Demográfico de 2020. Há certa vantagem em obter informações de óbito por meio do Censo, mas é importante garantir a qualidade dessa informação. Objetivo Analisar a qualidade da declaração de idade para os dados de óbito do Censo Demográfico de 2010. Método Foram utilizadas as informações acerca dos óbitos nos domicílios, coletadas no questionário do universo do Censo Demográfico de 2010 do IBGE. A análise foi realizada a partir dos índices de Whipple e Myers. Resultados Para o Brasil como um todo, os resultados observados atestam uma boa qualidade dos dados de declaração de idade dos óbitos. No entanto, quando é estratificada a análise ao âmbito de unidades federativas, algumas distorções foram verificadas, sobretudo nas unidades pertencentes às regiões Norte e Centro-Oeste. Conclusão O uso dos dados de mortalidade para as análises em âmbito macro, do país como um todo, não requer ajustes para adequar as qualidades das informações, assim como para as análises em termos das grandes regiões.

Abstract Background The debate on deaths in the Brazilian population census has been resumed by the proximity of the next 2020 census. There are some advantages in obtaining death information through the census, but it is important to ensure the quality of this information. Objective To analyze the quality of the age declaration for the 2010 demographic census death data. Method Information on household deaths collected from the 2010 IBGE demographic census questionnaire was used. The analysis was performed from the Whipple and Myers indices. Results For Brazil as a whole, the observed results attest to a good quality of the death declaration data. However, when the analysis at the state level is stratified, some distortions were found, especially in the North and Midwest areas. Conclusion The use of mortality data for macro-level analyzes of the country as a whole does not require adjustments to suit the quality of the information, as well as for analysis in terms of large regions.

Cad. saúde colet., (Rio J.) ; 28(4): 477-487, out.-dez. 2020. tab, graf
Article in Portuguese | LILACS-Express | LILACS | ID: biblio-1142660


Resumo Introdução Informação de qualidade é condição necessária para a análise objetiva da situação de saúde, para a tomada de decisões baseadas em evidências e para a programação de ações públicas que almejem o desenvolvimento de boas condições de saúde para a população em geral. Objetivo Avaliar a qualidade do preenchimento das notificações compulsórias de violência no Brasil, com ênfase na dimensão completude dos dados. Método Estudo descritivo com dados do Sistema de Informação de Agravos de Notificação (Sinan) no período de 2011 a 2014. Calcularam-se os percentuais de incompletude com base nos campos sem informação (ignorados/em branco) e a média anual da incompletude para variáveis essenciais e obrigatórias. Resultados O percentual médio global de incompletude das variáveis analisadas foi classificado como ruim (22,4%). O percentual médio de incompletude por blocos variou de regular para as variáveis de notificação individual (14,4%) e identificação da vítima (14,6%) a ruim para as variáveis sobre conclusão (30,8%) e encaminhamento (32,9%). Conclusão Os dados de notificação de violência apresentaram qualidade de preenchimento ruim, apesar do aumento no número de notificações no período analisado. Recomenda-se monitoramento dos dados e capacitação de profissionais no correto preenchimento das notificações.

Abstract Background Quality information is a necessary condition for the objective analysis of the health situation, for making evidence-based decisions and for the programming of public actions that aim at the development of good health conditions for the general population. Objective To evaluate the quality of the filling of compulsory notifications of violence in Brazil, with emphasis on the completeness of the data. Method Descriptive study with data from the National Disease Notification Information System (Sinan) for the period 2011 to 2014 was carried out. Percentages of incompleteness were calculated on the basis of uninformed fields (ignored/blank) and the annual average percentage of incompleteness for essential and mandatory variables. Results The overall average percentage of incompleteness of the analyzed variables was classified as Bad (22.4%). The average percentage of incompleteness by blocks ranged from regular for variables on reporting (14.4%) and victim identification (14.6%) to Bad for variables on ending (30.8%) and referral (32.9%). Conclusion The data of notification of violence presented Bad quality of completion, despite the increase in the number of notifications. It is recommended to monitor the data and to train professionals in the correct completion of notifications.

Article in Chinese | WPRIM | ID: wpr-798887


Objective@#To assess the quality of data of intervention in population at high risk for HIV/AIDS, especially in female sex workers (FSWs) and men who have sex with men (MSM), in China during 2014-2018, for the purpose of improving intervention data quality.@*Methods@#Data accuracy was evaluated by sampling monthly reported intervention data and comparing the consistency of the information recorded in national HIV/AIDS prevention and treatment information system to original paper records. Data authenticity was assessed by visiting intervention sites and interviewing owners, manager and/or target groups at sites. The assessment results of both national level and provincial level were summarized by year and analyzed with descriptive statistical method. The data quality problems recognized by assessments were summed up.@*Results@#The annual concordance rate of the data recorded in information system to paper records was 94.6%(17 671/18 673) in provincial level assessment and 79.4%(558/703) in national level assessment. Up to 81.6%(8 617/10 559) and 84.4% (249/295) of all sampled intervention sites were annually evaluated as "good" in provincial and state level assessments respectively. The assessment found that the intervention data in original paper records were not completely consistent to that recorded in the information system, the deficiency of ability on intervention data management, and the insufficient coverage and effect of intervention service influenced the intervention data quality.@*Conclusions@#In general, the accuracy and authenticity of intervention data were fine in China during 2014-2018. Intervention data quality can be improved through measures of enhancing data quality management, strengthening training for the prevention and intervention in FSWs and MSM, and providing high- quality intervention service.

Article in Chinese | WPRIM | ID: wpr-787703


To assess the quality of data of intervention in population at high risk for HIV/AIDS, especially in female sex workers (FSWs) and men who have sex with men (MSM), in China during 2014-2018, for the purpose of improving intervention data quality. Data accuracy was evaluated by sampling monthly reported intervention data and comparing the consistency of the information recorded in national HIV/AIDS prevention and treatment information system to original paper records. Data authenticity was assessed by visiting intervention sites and interviewing owners, manager and/or target groups at sites. The assessment results of both national level and provincial level were summarized by year and analyzed with descriptive statistical method. The data quality problems recognized by assessments were summed up. The annual concordance rate of the data recorded in information system to paper records was 94.6(17 671/18 673) in provincial level assessment and 79.4(558/703) in national level assessment. Up to 81.6(8 617/10 559) and 84.4 (249/295) of all sampled intervention sites were annually evaluated as "good" in provincial and state level assessments respectively. The assessment found that the intervention data in original paper records were not completely consistent to that recorded in the information system, the deficiency of ability on intervention data management, and the insufficient coverage and effect of intervention service influenced the intervention data quality. In general, the accuracy and authenticity of intervention data were fine in China during 2014-2018. Intervention data quality can be improved through measures of enhancing data quality management, strengthening training for the prevention and intervention in FSWs and MSM, and providing high- quality intervention service.

Article in Chinese | WPRIM | ID: wpr-876217


Objective An analysis of informationized multi-platform big data was conducted to learn about the quality change of health management data for hypertension and diabetes patients in Baoshan District of Shanghai since 2017.The result provided important information for further evaluation of the effect of quality control measures, and the prevention and management of chronic diseases. Methods Height, weight, blood glucose level, diagnosis and treatment information were collected from different databases of patients with hypertension and diabetes in Baoshan District from 2017 to 2019, and the consistency of the data from different sources was analyzed. Results Both the percentages of weight and height inconsistency among patients with hypertension and diabetes together were lower in 2019 than in 2017 (10.99% vs 18.72%, χ2=822.38, P < 0.001 and 0.86% vs 2.74%, χ2=347.03, P < 0.001, respectively).In 2019, the percentage of registered hypertensive patients with abnormal traceability from diagnosis was higher than that in 2017 (12.67% vs 11.72%, χ2=4.01, P=0.045).Similar results were also obtained in patients with diabetes.Analysis of glycated hemoglobin value last position in diabetic patients showed that the coefficient of variation of the last position composition ratio of the value in 2019 was significantly lower than that in 2017 (0.19 vs 0.31).The ratio in patients with the last position of glycosylated hemoglobin value of 0 was lower in 2019(4 701 cases, 12.72%) than that in 2017 (9 485 cases, 17.14%), and the difference was statistically significant. Conclusion The study result shows an improvement in quality management of hypertension and diabetes in Baoshan District of Shanghai.Information technology should be more widely used in promoting technical standardization, strengthening technical training, data quality control and effect evaluation.

Indian J Public Health ; 2019 Dec; 63(4): 305-312
Article | IMSEAR | ID: sea-198164


Background: High-quality data are of prime importance in any health survey because survey data are considered as a gold standard for nationally representative data. The quality of data collection largely depends on the design of the questionnaire, training, and skills of the interviewer. Objectives: In the present study, we tried to evaluate three key components, such as questionnaire design, human resource and training of the field staff for Integrated Biological and Behavioural Surveillance carried out among the HIV high-risk subpopulation. Methods: A mixed-methods approach was used. Qualitative and quantitative data collection was carried out in the year 2015 with cross-sectional survey design in western states of India. The in-depth interviews of 10 stakeholders, structured interviews of the survey respondents (n = 560), and field investigators (n = 71) were conducted. Data triangulation was used to find out the concurrence of the qualitative and quantitative data. Results: Comprehensive and standardized survey questionnaire, structured training agenda, and strategic preparation for recruiting human resources were the overall strengths of the survey. However, during the implementation of the survey, there were some difficulties reported in data collection process. Overall, the respondents and investigators felt that the questionnaire was long and exhaustive. Difficulties were faced while collecting data on sexual history. The field staffs were not adequately experienced to work with sensitive population. Conclusions: In order to have accurate, reliable data, especially on sexual behavior; emphasis should be given on simple questionnaire with the use of community-friendly language, skilled and experienced interviewers for data collection, and extensive field training.

RECIIS (Online) ; 13(1): 158-171, jan.-mar. 2019. tab, graf
Article in Portuguese | LILACS | ID: biblio-987723


Este artigo apresenta os resultados de uma pesquisa que teve como objetivo analisar a qualidade da declaração da idade nos registros de óbito no Brasil, de 1996 a 2015. Foi realizada uma análise por 'idade simples' dos microdados de óbitos no Brasil no período mencionado. A preferência por dígitos terminais 0 e 5 foi avaliada usando o índice de Whipple (IW). Já a preferência pelos dígitos terminais de 0 a 9 foi expressa usando o método de Myers (IM). A qualidade dos dados de idade foi alta no período [IWtot = 0,55 ­ 0,83 (masculino) e 0,71 ­ 0,93 (feminino); IM = 0,388 ­ 1,004 (masculino) e 0,430 ­ 1,589 (feminino)]. A qualidade da informação foi mais satisfatória entre homens e não houve tendência significativa a uma melhora, sugerindo sua estabilidade durante os 20 anos analisados. Foi encontrada preferência pelo dígito terminal 0 (zero) principalmente entre mulheres. Concluiu-se que os dados de óbito no Brasil, com relação à idade, são satisfatórios, podendo ser utilizados em análises demográficas e epidemiológicas.

This article presents the results of a research aimed at analyzing the quality of the information about the age on the death registers in Brazil, from 1996 to 2015. An analysis was performed by simple age of the deaths microdata in Brazil for that period. The preference for the last digits 0 and 5 was evaluated using the Whipple index (IW), while the preference for the last digits from 0 to 9 was expressed using the Myers (IM) method. The quality of the age data was high in the period [IWTtot = 0.55 - 0.83 (male) and 0.71 - 0.93 (female); IM = 0.388 - 1.004 (male) and 0.430 ­ 1.589 (female)]. The quality of the information was more satisfactory among men, and there was not a significant trend in the improvement suggesting stable quality during the 20 years analyzed. The preference was given to the last digit 0, mainly among women. It was concluded that data from death registers in Brazil regarding the age are satisfactory and can be used in demographic and epidemiological analyses.

Este artículo presenta los resultados de una investigación que tuvo como objetivo analizar la calidad de la declaración de la edad en los registros de óbito en Brasil, desde 1996 hasta 2015. Se realizó el análisis por edad simple de los microdatos de óbitos en Brasil en el periodo mencionado. La preferencia por dígitos finales 0 y 5 fue evaluada usando el índice de Whipple (IW). La preferencia por los dígitos finales desde 0 hasta 9 fue expresada usando el método de Myers (IM). La calidad de los datos de edad fue alta en el período [(IWtot = 0,55 - 0,83 (masculino) y 0,71 - 0,93 (femenino), IM = 0,388 - 1,004 (masculino) y 0,430 - 1,589 (femenino)]. La calidad de la información fue más satisfactoria entre hombres y no hubo tendencia significativa en la mejora, sugiriendo estabilidad en la calidad en los 20 años analizados. Se encontró una preferencia por el dígito terminal 0 principalmente entre mujeres. Se concluye que los datos de óbito en Brasil con relación a la edad son satisfactorios y pueden ser utilizados en análisis demográficos y epidemiológicos.

Humans , Demography , Mortality Registries , Health Status Indicators , Ecological Studies , Brazil , Information Systems , Mortality
Rev. bras. estud. popul ; 36: e0102, 2019. tab, graf
Article in English | LILACS | ID: biblio-1098837


Suriname statistical office assumes that mortality data in the country is of good quality and does not perform any test before producing life table estimates. However, lack of data quality is a concern in the less developed areas of the world. The primary objective of this article is to evaluate the quality of death counts registration in the country and its main regions from 2004 to 2012 and to produce estimates of adult mortality by sex. We use data from population, by age and sex, from the last censuses and death counts from the Statistical office. We use traditional demographic methods to perform the analysis. We find that the quality of the death count registration in Suriname and its central regions is reasonably good. We also find that population data can be considered good. The results reveal a small difference in the completeness for males and females and that for the sub-national population the choice of method has implication on the results. To sum up, data quality in Suriname is better than in most countries in the region, but there are considerable regional differences as observed in other locations.

O Instituto de Estatística do Suriname assume que os dados de mortalidade no país são de boa qualidade e não realiza nenhum teste antes de produzir estimativas da tabela de vida. No entanto, a falta de qualidade dos dados é uma preocupação nas áreas menos desenvolvidas do mundo. O objetivo principal deste artigo é avaliar a qualidade do registro de óbitos no país e suas principais regiões, entre 2004 e 2012, e produzir estimativas de mortalidade adulta por sexo. Utilizamos dados populacionais, por idade e sexo, dos últimos censos e contagem de mortes do Centro Nacional de Estatística. Para realizar a análise, foram empregados métodos demográficos tradicionais. Concluímos que a qualidade do registro de óbitos no Suriname e em suas regiões centrais é razoável. Também mostramos que os dados de registro da população podem ser considerados bons. Os resultados revelam uma pequena diferença no grau de cobertura do registro de óbitos para homens e mulheres e que, para as regiões, a escolha do método tem implicações nos resultados. Em suma, a qualidade dos dados no Suriname é melhor do que na maioria dos países da região, mas há diferenças regionais consideráveis, como observado em outros lugares.

La oficina de estadísticas de Surinam supone que los datos de mortalidad en el país son de buena calidad y no hace ninguna prueba antes de producir estimaciones de la tabla de vida. Sin embargo, la falta de calidad de datos es una preocupación en las zonas menos desarrolladas del mundo. El objetivo principal de este artículo es evaluar la calidad del registro de recuentos de defunciones en el país y sus principales regiones entre 2004 y 2012 y producir estimaciones de mortalidad de adultos por sexo. Utilizamos datos de la población, por edad y sexo, de los últimos censos y recuentos de muertes de la oficina de Estadística. Utilizamos métodos demográficos tradicionales para realizar el análisis. Encontramos que la calidad del registro del recuento de defunciones en Surinam y sus regiones centrales es de razonable a buena. Asimismo, hallamos que los datos de población pueden considerarse también buenos. Los resultados revelan una pequeña diferencia en la integridad para hombres y mujeres y que para la población subnacional la elección del método tiene implicaciones en los resultados. En resumen, la calidad de los datos en Surinam es mejor que la de la mayoría de los países de la región, pero existen diferencias regionales considerables, como también se observa en otros lugares.

Humans , Male , Female , Child, Preschool , Child , Adolescent , Adult , Middle Aged , Aged , Aged, 80 and over , Young Adult , Mortality Registries , Data Accuracy , Suriname/epidemiology , Death Certificates , Mortality , Censuses , Age and Sex Distribution
Article in Chinese | WPRIM | ID: wpr-800115


Medical artificial intelligence (AI) is an important technical strategy to promote medical supply-side reforms and national development.Images of ophthalmic disease are the important data resource for the development and application of ophthalmic AI-aided diagnosis and treatment systems based on medical big data.In order to establish an AI ophthalmic disease imaging database that can be effectively utilized as big data resources, improve the efficiency of ophthalmic AI research, and promote the development of ophthalmic AI research based on big data in the new era, the International Ophthalmic Artificial Intelligence Research and Development Alliance drafted and adopted the "Guidelines for image quality assessment of artificial intelligence ophthalmic diseases imaging database" . Specifications and recommendations of the image quality assessment for the AI ophthalmic disease image database were formulated on data types, data related information, data quality, informed consent, and data sharing.

Colomb. med ; 49(1): 121-127, Jan.-Mar. 2018. tab, graf
Article in English | LILACS | ID: biblio-952902


Abstract Objective: To evaluate the quality of the certification of general death and cancer in Colombia. Methods: Validity indicators were described for each province and the cities of Bogotá, Cali, Manizales, Pasto and Bucaramanga. A factorial analysis of principal components was carried out in order to identify non-obvious relationships. Results: Were analyzed 984,159 deaths, among them there were 164,542 deaths due to cancer. 93.7% of the general mortality was well certified. The predominant errors were signs, symptoms and ill-defined conditions. 92.8% of cancer mortality was well certified. The predominant errors were due to poorly defined cancer sites. Conclusions: Certification of quality indicators in Colombia has improved. Given the good performance of the quality indicators for certificating general death and cancer, it is considered that this is a valid input for the estimation of cancer incidences.

Resumen Objetivo: Evaluar la calidad de la certificación de la muerte general y por cáncer en Colombia. Métodos: Se describieron indicadores de validez para cada departamento y las ciudades de Bogotá, Cali, Manizales, Pasto y Bucaramanga. Se realizó un análisis factorial de componentes principales con el fin de identificar relaciones no evidentes. Resultados: Se analizaron 984,159 defunciones, dentro de las cuales había 164,542 muertes por cáncer. El 93.7% de la mortalidad general estaba bien certificada. Los errores predominantes fueron signos, síntomas y afecciones mal definidas. El 92.8% de la mortalidad por cáncer estaba bien certificada. Los errores predominantes fueron cánceres de sitio mal definido. Conclusiones: Los indicadores de calidad de certificación en Colombia mejoraron. Ante el buen comportamiento de los indicadores de calidad de la certificación de la muerte general y por cáncer, se considera que ésta es un insumo válido para la estimación de incidencia de cáncer.

Humans , Registries/standards , Death Certificates , Neoplasms/epidemiology , Incidence , Colombia/epidemiology , Quality Indicators, Health Care , Principal Component Analysis , Neoplasms/mortality
Article | IMSEAR | ID: sea-200896


For many years, the quality concept in clinical trials has been discussed and recommended by Good Clinical Practice (GCP) guidelines. Regulatory Authorities and also the Public Involvement anticipate that the pharmaceutical industry will concentrate on creating quality frameworks amid the arranging and leading of conventions of controlled protocols. Nevertheless, many factors have been suggested as contributing to the occurrence of scientific misconduct within the research field, such as: personal and financial interests, site monitoring, available resources, workload, competition among investigators, and the implicit consent of sponsors. The negligence on data fraud represents not only omission but misconduct as well, in this case, a passive attitude intrinsically related to the act of transgression. A properly culture of research must be based on a fundamental ethos of integrity, openness and honest work of high quality in all parts of the research process. There is a need to change the focus from inspection-based quality improvement to planned systematic quality management within clinical trials. In search for a monitoring improvement, a full statistical  way to deal with information recognition comprises of executing however many measurable tests as could be allowed on whatever number clinical information factors as could be expected under varied circumstances. Adoption of specific and preventive clinical trial monitoring procedures can identify potential misconduct and data fraud leading to improvement in overall data quality and scientific reports.

Article in Chinese | WPRIM | ID: wpr-712569


Following an overview of the present big medical data sharing abroad, the paper identified the problems of the regional health information platform in data sharing and utilization as follows. Namely, poor data integration, low data availability, poor data security and privacy, unclear data sharing model, and poor data management accountability. On such basis, the authors made thoughtful studies in data quality management, information security and privacy protection and data sharing model. These efforts provide useful references for big health data integration sharing and open access.