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2.
BMC Med Inform Decis Mak ; 20(1): 340, 2020 12 17.
Artigo em Inglês | MEDLINE | ID: mdl-33334323

RESUMO

BACKGROUND: Effective planning for disease prevention and control requires accurate, adequately-analysed, interpreted and communicated data. In recent years, efforts have been put in strengthening health management information systems (HMIS) in Sub-Saharan Africa to improve data accessibility to decision-makers. This study assessed the quality of routine HMIS data at primary healthcare facility (HF) and district levels in Tanzania. METHODS: This cross-sectional study involved reviews of documents, information systems and databases, and collection of primary data from facility-level registers, tally sheets and monthly summary reports. Thirty-four indicators from Outpatient, Inpatient, Antenatal care, Family Planning, Post-natal care, Labour and Delivery, and Provider-Initiated Testing and Counselling service areas were assessed. Indicator records were tracked and compared across the process of data collection, compilation and submission to the district office. Copies of monthly report forms submitted by facilities to the district were also reviewed. The availability and utilization of HMIS tools were assessed, while completeness and data accuracy levels were quantified for each phase of the reporting system. RESULTS: A total of 115 HFs (including hospitals, health centres, dispensaries) in 11 districts were involved. Registers (availability rate = 91.1%; interquartile range (IQR) 66.7-100%) and report forms (86.9%; IQR 62.2-100%) were the most utilized tools. There was a limited use of tally-sheets (77.8%; IQR 35.6-100%). Tools availability at the dispensary was 91.1%, health centre 82.2% and hospital 77.8%, and was low in urban districts. The availability rate at the district level was 65% (IQR 48-75%). Wrongly filled or empty cells in registers and poor adherence to the coding procedures were observed. Reports were highly over-represented in comparison to registers' records, with large differences observed at the HF phase of the reporting system. The OPD and IPD areas indicated the highest levels of mismatch between data source and district office. Indicators with large number of clients, multiple variables, disease categorization, or those linked with dispensing medicine performed poorly. CONCLUSION: There are high variations in the tool utilisation and data accuracy at facility and district levels. The routine HMIS is weak and data at district level inaccurately reflects what is available at the source. These results highlight the need to design tailored and inter-service strategies for improving data quality.


Assuntos
Confiabilidade dos Dados , Coleta de Dados/normas , Sistemas de Informação Administrativa , Atenção Primária à Saúde/normas , Estudos Transversais , Feminino , Humanos , Masculino , Atenção Primária à Saúde/organização & administração , Tanzânia
4.
Biomedica ; 40(Supl. 2): 96-103, 2020 10 30.
Artigo em Inglês, Espanhol | MEDLINE | ID: mdl-33152193

RESUMO

Introduction: The COVID pandemic is a challenge for public health surveillance and an opportunity to assess its strengths and weaknesses to improve the response. Objective: To evaluate the performance of the Colombian public health surveillance system during the first 50 days of the COVID-19 pandemic in the country. Materials and methods: We analyzed the data published between March 6 and April 24, 2020, by the Instituto Nacional de Salud and the World Health Organization (WHO). We evaluated: i) the quality of the data according to the fulfillment of Benford's law, and ii) the timeliness of the information measured as the difference in dates between the data generated by the Instituto Nacional de Salud and WHO's situational reports. We assessed the fulfillment of Benford's law using the p values of the log-likelihood ratio, the chi square or Moreno's exact tests. Results: Until April 24 there were 4,881 cases of COVID-19 in Colombia. During most of the first 50 days of the pandemic, Benford's law was fulfilled except the first days of the epidemic. The difference between Instituto Nacional de Salud and WHO reports largely depends on the different reporting times. Conclusion: In general, the Colombian public health surveillance system fulfilled Benford's law suggesting that there was quality in the data. Future studies comparing the performance of the departments and districts will improve the diagnosis of the Colombian surveillance system.


Assuntos
Betacoronavirus , Infecções por Coronavirus/epidemiologia , Coleta de Dados/normas , Pandemias , Pneumonia Viral/epidemiologia , Vigilância da População , Saúde Pública , Colômbia/epidemiologia , Coleta de Dados/métodos , Coleta de Dados/estatística & dados numéricos , Surtos de Doenças , Humanos , Vírus da Influenza A Subtipo H1N1 , Influenza Humana/epidemiologia , Internet , Vigilância da População/métodos , Controle de Qualidade , Distribuições Estatísticas , Infecção por Zika virus/epidemiologia
6.
PLoS One ; 15(9): e0238851, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32915874

RESUMO

Assistive products outcomes are needed globally to inform policy, practice, and drive investment. The International Society of Wheelchair Professionals developed a Minimum Uniform Dataset (MUD) for wheelchair services worldwide with the intent to gather data that is comparable globally. The MUD was developed with the participation of members from around the globe and its feasibility piloted at 3 sites. Three versions of the MUD are now available-a short form with 29 data points (available in English, Spanish, and French) and a standard version with 38 data points in English. Future work is to validate and complete the translation cycles followed by promoting the use of the MUD globally so that the data can be leveraged to inform policy, practice and direct investments.


Assuntos
Coleta de Dados/normas , Pessoas com Deficiência/reabilitação , Inquéritos e Questionários/normas , Análise e Desempenho de Tarefas , Cadeiras de Rodas/normas , Humanos , Agências Internacionais , Tradução
7.
PLoS One ; 15(8): e0237656, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32866167

RESUMO

OBJECTIVE: Preterm birth is the primary driver of neonatal mortality worldwide, but it is defined by gestational age (GA) which is challenging to accurately assess in low-resource settings. In a commitment to reducing preterm birth while reinforcing and strengthening facility data sources, the East Africa Preterm Birth Initiative (PTBi-EA) chose eligibility criteria that combined GA and birth weight. This analysis evaluated the quality of the GA data as recorded in maternity registers in PTBi-EA study facilities and the strength of the PTBi-EA eligibility criteria. METHODS: We conducted a retrospective analysis of maternity register data from March-September 2016. GA data from 23 study facilities in Migori, Kenya and the Busoga Region of Uganda were evaluated for completeness (variable present), consistency (recorded versus calculated GA), and plausibility (falling within the 3rd and 97th birth weight percentiles for GA of the INTERGROWTH-21st Newborn Birth Weight Standards). Preterm birth rates were calculated using: 1) recorded GA <37 weeks, 2) recorded GA <37 weeks, excluding implausible GAs, 3) birth weight <2500g, and 4) PTBi-EA eligibility criteria of <2500g and between 2500g and 3000g if the recorded GA is <37 weeks. RESULTS: In both countries, GA was the least recorded variable in the maternity register (77.6%). Recorded and calculated GA (Kenya only) were consistent in 29.5% of births. Implausible GAs accounted for 11.7% of births. The four preterm birth rates were 1) 14.5%, 2) 10.6%, 3) 9.6%, 4) 13.4%. CONCLUSIONS: Maternity register GA data presented quality concerns in PTBi-EA study sites. The PTBi-EA eligibility criteria of <2500g and between 2500g and 3000g if the recorded GA is <37 weeks accommodated these concerns by using both birth weight and GA, balancing issues of accuracy and completeness with practical applicability.


Assuntos
Coleta de Dados/normas , Idade Gestacional , Serviços de Saúde Materna/organização & administração , Nascimento Prematuro/epidemiologia , Sistema de Registros/estatística & dados numéricos , Peso ao Nascer , Coleta de Dados/estatística & dados numéricos , Feminino , Humanos , Lactente , Mortalidade Infantil , Recém-Nascido de Peso Extremamente Baixo ao Nascer , Lactente Extremamente Prematuro , Recém-Nascido , Quênia/epidemiologia , Serviços de Saúde Materna/estatística & dados numéricos , Gravidez , Nascimento Prematuro/prevenção & controle , Melhoria de Qualidade , Sistema de Registros/normas , Reprodutibilidade dos Testes , Estudos Retrospectivos , Uganda/epidemiologia
8.
Cochrane Database Syst Rev ; 8: CD012012, 2020 08 13.
Artigo em Inglês | MEDLINE | ID: mdl-32803893

RESUMO

BACKGROUND: A well-functioning routine health information system (RHIS) can provide the information needed for health system management, for governance, accountability, planning, policy making, surveillance and quality improvement, but poor information support has been identified as a major obstacle for improving health system management. OBJECTIVES: To assess the effects of interventions to improve routine health information systems in terms of RHIS performance, and also, in terms of improved health system management performance, and improved patient and population health outcomes. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library, MEDLINE Ovid and Embase Ovid in May 2019. We searched Global Health, Ovid and PsycInfo in April 2016. In January 2020 we searched for grey literature in the Grey Literature Report and in OpenGrey, and for ongoing trials using the International Clinical Trials Registry Platform (ICTRP) and ClinicalTrials.gov. In October 2019 we also did a cited reference search using Web of Science, and a 'similar articles' search in PubMed. SELECTION CRITERIA: Randomised and non-randomised trials, controlled before-after studies and time-series studies comparing routine health information system interventions, with controls, in primary, hospital or community health care settings. Participants included clinical staff and management, district management and community health workers using routine information systems. DATA COLLECTION AND ANALYSIS: Two authors independently reviewed records to identify studies for inclusion, extracted data from the included studies and assessed the risk of bias. Interventions and outcomes were too varied across studies to allow for pooled risk analysis. We present a 'Summary of findings' table for each intervention comparisons broadly categorised into Technical and Organisational (or a combination), and report outcomes on data quality and service quality. We used the GRADE approach to assess the certainty of the evidence. MAIN RESULTS: We included six studies: four cluster randomised trials and two controlled before-after studies, from Africa and South America. Three studies evaluated technical interventions, one study evaluated an organisational intervention, and two studies evaluated a combination of technical and organisational interventions. Four studies reported on data quality and six studies reported on service quality. In terms of data quality, a web-based electronic TB laboratory information system probably reduces the length of time to reporting of TB test results, and probably reduces the overall rate of recording errors of TB test results, compared to a paper-based system (moderate certainty evidence). We are uncertain about the effect of the electronic laboratory information system on the recording rate of serious (misidentification) errors for TB test results compared to a paper-based system (very low certainty evidence). Misidentification errors are inaccuracies in transferring test results between an electronic register and patients' clinical charts. We are also uncertain about the effect of the intervention on service quality (timeliness of starting or changing a patient's TB treatment) (very low certainty evidence). A hand-held electronic device probably improves the length of time to report TB test results, and probably reduces the total frequency of recording errors in TB test results between the laboratory notebook and the electronic information record system, compared to a paper-based system (moderate-certainty evidence). We are, however, uncertain about the effect of the intervention on the frequency of serious (misidentification) errors in recording between the laboratory notebook and the electronic information record, compared to a paper-based system (very low certainty evidence). We are uncertain about the effect of a hospital electronic health information system on service quality (length of time outpatients spend at hospital, length of hospital stay, and hospital revenue collection), compared to a paper-based system (very low certainty evidence). High-intensity brief text messaging (SMS) may make little or no difference to data quality (in terms of completeness of documentation of pregnancy outcomes), compared to low-intensity brief text messaging (low-certainty evidence). We are uncertain about the effect of electronic drug stock notification (with either data management support or product transfer support) on service quality (in terms of transporting stock and stock levels), compared to paper-based stock notification (very low certainty evidence). We are uncertain about the effect of health information strengthening (where it is part of comprehensive service quality improvement intervention) on service quality (health worker motivation, receipt of training by health workers, health information index scores, quality of clinical observation of children and adults) (very low certainty evidence). AUTHORS' CONCLUSIONS: The review indicates mixed effects of mainly technical interventions to improve data quality, with gaps in evidence on interventions aimed at enhancing data-informed health system management. There is a gap in interventions studying information support beyond clinical management, such as for human resources, finances, drug supply and governance. We need to have a better understanding of the causal mechanisms by which information support may affect change in management decision-making, to inform robust intervention design and evaluation methods.


Assuntos
Assistência à Saúde/organização & administração , Sistemas de Informação em Saúde/normas , Política Organizacional , Melhoria de Qualidade , Viés , Sistemas de Informação em Laboratório Clínico/organização & administração , Sistemas de Informação em Laboratório Clínico/normas , Computadores de Mão , Coleta de Dados/normas , Tomada de Decisões , Assistência à Saúde/normas , Serviços de Informação sobre Medicamentos/normas , Sistemas de Informação Hospitalar/normas , Testes de Sensibilidade Microbiana , Inovação Organizacional , Preparações Farmacêuticas/provisão & distribução , Ensaios Clínicos Controlados Aleatórios como Assunto , Envio de Mensagens de Texto/normas , Tuberculose/diagnóstico , Tuberculose/tratamento farmacológico
11.
Neurology ; 95(3): e310-e319, 2020 07 21.
Artigo em Inglês | MEDLINE | ID: mdl-32591468

RESUMO

OBJECTIVE: To conduct a data quality improvement project to improve the quality measure data mapping and to measure key phrase logic in the Axon Registry.® METHODS: Prior validation analysis of the Axon Registry identified 2 main areas for remediation: methodology for mapping data from electronic health record (EHR) into the registry clinical data record (CDR) and key phrase logic for each measure. Practice groups participating in Axon Registry and 6 Axon Registry quality measures were selected for intervention. Mapping of measure elements and measure performances for each of the selected measures and practices were reviewed before intervention. The Data Accuracy Plan (DAP) was performed, and documentation data and visit data counts and data yield after intervention were calculated and analyzed. RESULTS: Documentation data and visit data counts and data yield increased for all 6 quality measures and all practices in the DAP. Increase in documentation data count ranged from 815 to 15,782 occurrences, while visit data count increase ranged from 519 to 16,383 visits. Average data yield range was 7.22% to 33.46% before intervention and increased to a range from 15.34% to 74.40% after intervention. CONCLUSION: There was substantial improvement in the accuracy of data extraction for quality measure elements after intervention to improve methodology for mapping EHR data into CDR and key phrase logic. Implementation of changes and continued review of data mapping and data dictionary are important to ensure accurate measure performance and to improve reliability and validity of Axon Registry data.


Assuntos
Axônios , Confiabilidade dos Dados , Coleta de Dados/normas , Registros Eletrônicos de Saúde/normas , Melhoria de Qualidade/normas , Sistema de Registros/normas , Coleta de Dados/métodos , Registros Eletrônicos de Saúde/estatística & dados numéricos , Humanos
13.
Am J Hum Genet ; 107(1): 72-82, 2020 07 02.
Artigo em Inglês | MEDLINE | ID: mdl-32504544

RESUMO

Genetics researchers and clinical professionals rely on diversity measures such as race, ethnicity, and ancestry (REA) to stratify study participants and patients for a variety of applications in research and precision medicine. However, there are no comprehensive, widely accepted standards or guidelines for collecting and using such data in clinical genetics practice. Two NIH-funded research consortia, the Clinical Genome Resource (ClinGen) and Clinical Sequencing Evidence-generating Research (CSER), have partnered to address this issue and report how REA are currently collected, conceptualized, and used. Surveying clinical genetics professionals and researchers (n = 448), we found heterogeneity in the way REA are perceived, defined, and measured, with variation in the perceived importance of REA in both clinical and research settings. The majority of respondents (>55%) felt that REA are at least somewhat important for clinical variant interpretation, ordering genetic tests, and communicating results to patients. However, there was no consensus on the relevance of REA, including how each of these measures should be used in different scenarios and what information they can convey in the context of human genetics. A lack of common definitions and applications of REA across the precision medicine pipeline may contribute to inconsistencies in data collection, missing or inaccurate classifications, and misleading or inconclusive results. Thus, our findings support the need for standardization and harmonization of REA data collection and use in clinical genetics and precision health research.


Assuntos
Coleta de Dados/normas , Testes Genéticos/normas , Adulto , Criança , Grupos Étnicos , Feminino , Variação Genética/genética , Genômica/normas , Humanos , Masculino , Medicina de Precisão/normas , Inquéritos e Questionários
16.
Epilepsia ; 61(7): 1319-1335, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32474909

RESUMO

Our objective was to undertake a systematic review ascertaining the accuracy of using administrative healthcare data to identify epilepsy cases. We searched MEDLINE and Embase from 01/01/1975 to 03/07/2018 for studies evaluating the diagnostic accuracy of routinely collected healthcare data in identifying epilepsy cases. Any disease coding system in use since the International Classification of Diseases, Ninth Revision (ICD-9) was permissible. Two authors independently screened studies, extracted data, and quality-assessed studies. We assessed positive predictive value (PPV), sensitivity, negative predictive value (NPV), and specificity. The primary analysis was a narrative synthesis of review findings. Thirty studies were included, published between 1989 and 2018. Risks of bias were low, high, and unclear in 4, 14, and 12 studies, respectively. Coding systems included ICD-9, ICD-10, and Read Codes, with or without antiepileptic drugs (AEDs). PPVs included ranges of 5.2%-100% (Canada), 32.7%-96.0% (USA), 47.0%-100% (UK), and 37.0%-88.0% (Norway). Sensitivities included ranges of 22.2%-99.7% (Canada), 12.2%-97.3% (USA), and 79.0%-94.0% (UK). Nineteen studies contained at least one algorithm with a PPV >80%. Sixteen studies contained at least one algorithm with a sensitivity >80%. PPV was highest in algorithms consisting of disease codes (ICD-10 G40-41, ICD-9 345) in combination with one or more AEDs. The addition of symptom codes to this (ICD-10 R56; ICD-9 780.3, 780.39) lowered PPV. Sensitivity was highest in algorithms consisting of symptom codes with one or more AEDs. Although using AEDs alone achieved high sensitivities, the associated PPVs were low. Most NPVs and specificities were >90%. We conclude that it is reasonable to use administrative data to identify people with epilepsy (PWE) in epidemiological research. Studies prioritizing high PPVs should focus on combining disease codes with AEDs. Studies prioritizing high sensitivities should focus on combining symptom codes with AEDs. We caution against the use of AEDs alone to identify PWE.


Assuntos
Coleta de Dados/estatística & dados numéricos , Bases de Dados Factuais/estatística & dados numéricos , Assistência à Saúde/estatística & dados numéricos , Epilepsia/epidemiologia , Estudos de Validação como Assunto , Coleta de Dados/normas , Bases de Dados Factuais/normas , Assistência à Saúde/normas , Epilepsia/diagnóstico , Humanos
17.
J Stud Alcohol Drugs ; 81(2): 212-219, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-32359051

RESUMO

OBJECTIVE: The aim of this study was to compare data on both alcohol use and alcohol-related consequences between intensive longitudinal data collection and the retrospective Timeline Followback (TLFB) interview. METHOD: Heavy drinking college students (n = 96; 52% women) completed daily reports across a 28-day period to assess alcohol use and positive and negative consequences of drinking. They returned to the lab at the end of this period to complete a TLFB assessing behavior over those same 28 days. First, t tests were used to compare variables aggregated across the full 28 days at the between-person level. Next, hierarchical linear modeling was used to examine within-person differences between methods for each variable in weekly and daily increments. RESULTS: Many alcohol use and consequence variables were significantly different when derived from self-reports during TLFB versus daily reports. In contrast to prior work, we found that higher estimates of drinking were reported retrospectively on the TLFB than on the daily reports. In addition, discrepancies were greater on some variables for heavier drinkers and when more time had elapsed between the end of the daily reporting period and TLFB collection. CONCLUSIONS: Recall of drinking behavior during TLFB and daily reports may differ in systematic ways, with discrepancies varying based on participant and methodological characteristics.


Assuntos
Consumo de Álcool na Faculdade/psicologia , Coleta de Dados/normas , Rememoração Mental , Autorrelato/normas , Adolescente , Intoxicação Alcoólica/diagnóstico , Intoxicação Alcoólica/psicologia , Coleta de Dados/métodos , Feminino , Comportamentos Relacionados com a Saúde/fisiologia , Humanos , Estudos Longitudinais , Masculino , Rememoração Mental/fisiologia , Estudos Retrospectivos , Adulto Jovem
19.
Neural Netw ; 128: 268-278, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32454371

RESUMO

Multi-class classification for highly imbalanced data is a challenging task in which multiple issues must be resolved simultaneously, including (i) accuracy on classifying highly imbalanced multi-class data; (ii) training efficiency for large data; and (iii) sensitivity to high imbalance ratio (IR). In this paper, a novel sequential ensemble learning (SEL) framework is designed to simultaneously resolve these issues. SEL framework provides a significant property over traditional AdaBoost, in which the majority samples can be divided into multiple small and disjoint subsets for training multiple weak learners without compromising accuracy (while AdaBoost cannot). To ensure the class balance and majority-disjoint property of subsets, a learning strategy called balanced and majority-disjoint subsets division (BMSD) is developed. Unfortunately it is difficult to derive a general learner combination method (LCM) for any kind of weak learner. In this work, LCM is specifically designed for extreme learning machine, called LCM-ELM. The proposed SEL framework with BMSD and LCM-ELM has been compared with state-of-the-art methods over 16 benchmark datasets. In the experiments, under highly imbalanced multi-class data (IR up to 14K; data size up to 493K), (i) the proposed works improve the performance in different measures including G-mean, macro-F, micro-F, MAUC; (ii) training time is significantly reduced.


Assuntos
Aprendizado de Máquina/normas , Coleta de Dados/normas
20.
Br J Radiol ; 93(1111): 20200055, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32462887

RESUMO

OBJECTIVE: To assess the accuracy and agreement of radiology information system (RIS) kerma-area product (KAP) data with respect to automatically populated dose management system (DMS) data for digital radiography (DR). METHODS: All adult radiographic examinations over 12 months were exported from the RIS and DMS at three centres. Examinations were matched by unique identifier fields, and grouped by examination type. Each centre's RIS sample completeness was calculated, as was the percentage of the RIS examination KAP values within 5% of their DMS counterparts (used as an accuracy metric). For each centre, the percentage agreement between the RIS and DMS examination median KAP values was computed using a Bland-Altman analysis. At two centres, up to 42.5% of the RIS KAP units entries were blank or invalid; corrections were attempted to improve data quality in these cases. RESULTS: Statistically significant intersite variation was seen in RIS data accuracy and the agreement between the uncorrected RIS and DMS median KAP data, with a Bland-Altman bias of up to 11.1% (with a -31.7% to 53.9% 95% confidence interval) at one centre. Attempts to correct invalid KAP units increased accuracy but produced worse agreement at one centre, a slight improvement at another and no significant change in the third. CONCLUSION: The RIS data poorly represented the DMS data. ADVANCES IN KNOWLEDGE: RIS KAP data are a poor surrogate for DMS data in DR. RIS data should only be used in patient dose surveys with an understanding of its limitations and potential inaccuracies.


Assuntos
Intensificação de Imagem Radiográfica/normas , Sistemas de Informação em Radiologia/normas , Adulto , Viés , Coleta de Dados/métodos , Coleta de Dados/normas , Humanos , Doses de Radiação , Proteção Radiológica/normas , Padrões de Referência , Sensibilidade e Especificidade
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