Data Accuracy

In this commentary, we elaborate on the main points that Karamouzian and colleagues have made about HIV data scarcity in Middle Eastern and North African (MENA) countries. Without accessible and reliable data, no epidemic can be managed effectively or efficiently. Clearly, increased investments are needed to bolster capabilities to capture and interpret HIV surveillance data. We believe that this enhanced capacity can be achieved, in part, by leveraging and repurposing existing data platforms, technologies and patient cohorts. An immediate modest investment that capitalizes on available infrastructure can generate data on the HIV burden and spread that can be persuasive for MENA policy-makers to intensify efforts to track and contain the growing HIV epidemic in this region. A focus on key populations will yield the most valuable data, including among men who have sex with men (MSM), transgender women and men, persons who inject drugs (PWIDs), female partners of high risk men and female sex workers.

INTRODUCTION    The risk of clinical complications in antiphospholipid syndrome (APS) increases when a patient is positive for all 3 types of antiphospholipid (aPL) antibodies. However, there is a considerable disagreement between various platforms for aCL and anti-β2-glycoprotein I (anti-β2GPI) measurement, which leads to discrepancies between these platforms in assessing aPL antibody positivity. OBJECTIVES    The aim of this retrospective cross-sectional study was to assess whether 2 different platforms, the QUANTA Lite® enzyme-linked immunosorbent assay and the QUANTA Flash® chemiluminescent immunoassay, identify the same subjects as triple positive in a group of patients with APS and comorbid autoimmune diseases. PATIENTS AND METHODS    The study included 220 patients with systemic autoimmune diseases (74 with primary APS; 47 with secondary APS; and 99 with systemic lupus erythematosus without APS). All patients were tested for IgG and IgM aCL and anti-β2GPI antibodies using bot...

Objectives: The lexical-level deficits are one of the hallmark limitations observed in early school-age children with specific language impairment. These problems are the predictors of reading problems and poor performance at school. Most studies in Persian-speaker children with specific language impairment have focused on syntax and morphology and the naming errors profile of these children are overlooked. This study aimed to investigate the naming accuracy, latency, and the error profile of these children. Methods: This was an observational study. Twenty children with specific language impairment were selected according to the clinical judgment of two speech therapists from speech therapy clinics and 100 children with typical language development aged from 7 to 9 years were randomly selected from public schools. The Persian picture naming set was presented by DMDX for the examination of picture naming skills. Naming errors were categorized as semantic, formal, mixed, non-word, unrelated, and others errors. Then, the data were investigated in terms of descriptive statistics and analysis of differences by the Independent t test and Mann-Whitney U test. Results: The Persian-speaker children with specific language impairment name significantly slower and less accurate than the children compared to children with normal language development (P≤0.05). Although semantic errors were the most frequent errors in the two groups, the score differences of formal and omission errors were significant between the groups (P≤0.05). Discussion: The different naming accuracy and latency scores between the two groups may be due to language delay and the inefficiency of the semantic system in children with specific language impairment. There are a variety of word retrieval errors in Persian-speaker children. Although, there are differences between the two groups, the error type in picture naming cannot be used for differentiating between them. Highlights ● The naming skill in children with specific language disorder (SLI) is slower and less accurate than children with normal language development. ● The semantic errors are the most common errors in both normal children and children with language disorder. ● The formal and omission errors could differentiate between normal children and children with language disorder. ● Picture naming is a useful test for determining the word retrieval skills in children with and without language disorder. Plain Language Summary Language delays or disorders result in significant and often ongoing problems for children. A common outcome is less development of semantic representations of children with word finding difficulties. This makes retrieval skill inaccurate , slow, or wrong. The studies of naming skill in children with specific language disorders indicate significantly slower and less accurate naming processes in different languages. In the present study, the naming skill in children with specific language disorder are found to be slower and less accurate which maybe because of either a less developed language system or a delay in vocabulary development. In addition, the types of errors in children with and without language disorder are the same but the number of each error is different. In conclusion, the researchers and the therapist can use the picture naming task for determining the word retrieval problems.

Introduction: Esophagogastroduodenoscopy (EGD) is currently considered as the primary method of determining the degree of mucosal injury following caustic ingestion. The present study aimed to evaluate the screening performance characteristics of EGD in predicting the depth of gastrointestinal mucosal injuries following caustic ingestion. Methods: Adult patients who were referred to emergency department due to ingestion of corrosive materials, over a 7-year period, were enrolled to this diagnostic accuracy study. Sensitivity, specificity, positive and negative predictive values as well as negative and positive likelihood ratios of EGD in predicting the depth of mucosal injury was calculated using pathologic findings as the gold standard. Results: 54 cases with the mean age of 35 ± 11.2 years were enrolled (59.25% male). Primary endoscopic results defined 28 (51.85%) cases as second grade and 26 (48.14%) as third grade of mucosal injury. On the other hand, pathologic findings reported 21 (38.88%) patients as first grade, 14 (25.92%) as second, and 19 patients (35.18%) as third grade. Sensitivity and specificity of endoscopy for determining grade II tissue injury were 50.00 (23.04-76.96) and 47.50 (31.51-63.87), respectively. These measures were 100.00 (82.35-100) and 80.00 (63.06-91.56), respectively for grade III. Accuracy of EGD was 87.03% for grade III and 48.14% for grade II. Conclusion: Based on the findings of the present study, endoscopic grading of caustic related mucosal injury based on the Zargar's classification has good accuracy in predicting grade III (87%) and fail accuracy in grade II injuries (48%). It seems that we should be cautious in planning treatment for these patients solely based on endoscopic results.

Routine health data can guide health systems improvements, but poor quality of these data hinders use. To address concerns about data quality in Malawi, the Ministry of Health and National Statistical Office conducted a data quality assessment (DQA) in July 2016 to identify systems-level factors that could be improved. We used 2-stage stratified random sampling methods to select health centers and hospitals under Ministry of Health auspices, included those managed by faith-based entities, for this DQA. Dispensaries, village clinics, police and military facilities, tertiary-level hospitals, and private facilities were excluded. We reviewed client registers and monthly reports to verify availability, completeness, and accuracy of data in 4 service areas: antenatal care (ANC), family planning, HIV testing and counseling, and acute respiratory infection (ARI). We also conducted interviews with facility and district personnel to assess health management information system (HMIS) function...

A Multi-Source Information System (MSIS), has been designed for the Renal Epidemiology and Information Network (REIN) dedicated to End-Stage Renal Disease (ESRD). MSIS aims at providing reliable follow-up data for ESRD patients. It is based on an n-tier architecture, made out of a universal client, a dynamic Web server connected to a production database and to a data warehouse. MSIS is operational since 2002 and progressively deployed in 9 regions in France. It includes 11,500 patients. MSIS facilitates documenting medical events which occur during the course of ESRD patient' health care and provides means to control the quality of each patient's record and reconstruct the patient trajectory of care. Consolidated data are made available to a data warehouse and to a geographic information system for analysis and data representation in support of public-health decision making.

In Wireless Sensors Networks (WSN) based application, a large number of sensor devices must be deployed. Energy efficiency and network lifetime are the two most challenging issues in WSN. As a consequence, the main goal is to reduce the overall energy consumption using clustering protocols which have to ensure reliability and connectivity in large-scale WSN. This work presents a new clustering and routing algorithm based on the properties of the sensor networks. The main goal of this work is to extend the network lifetime via charge equilibration in the WSN. According to many errors with sensing devices and to have greater data accuracy, we use a quorum mechanism. The proposed algorithms are evaluated widely and the results are compared with related works. The experimental results show that the proposed algorithm provides an effective improvement in terms of energy consumption, data accuracy and network lifetime.

To compare serum concentrations of specific IgE and mean papule diameters induced in the immediate skin reactivity test with cow's milk (CM) and its fractions with results of the oral challenge test (OCT), and to establish cutoff points capable of predicting clinical reactivity to CM in patients treated at a referral service. One hundred and twenty-two children (median of 17 months) with a history of immediate reactions to CM and presence of specific IgE for CM and/or its fractions (positive skin and/or IgE serum tests) were submitted to open OCT with CM. The OCT was positive in 59.8% of the children, 49% of whom were males. Serum levels of specific IgE, as well as mean CM papule diameters, were significantly higher in allergic patients (medians: 3.39kUA/L vs. 1.16kUA/L, 2.5mm vs. 0mm). The optimal cutoff points (Youden's index) of serum IgE specific for CM and its fractions capable of predicting CM reactivity (positive OCT) were: 5.17kUA/L for CM, 0.95kUA/L for α-lactalbumi...

Data quality is core theme of programme's performance assessment and many organizations do not have any data quality improvement strategy, wherein data quality dimensions and data quality assessment framework are important constituents. As there is limited published research about the data quality specifics that are relevant to the context of Pakistan's Tuberculosis control programme, this study aims at identifying the applicable data quality dimensions by using the 'fitness-for-purpose' perspective. Forty-two respondents pooled a total of 473 years of professional experience, out of which 223 years (47%) were in TB control related programmes. Based on the responses against 11 practical cases, adopted from the routine recording and reporting system of Pakistan's TB control programme (real identities of patient were masked), completeness, accuracy, consistency, vagueness, uniqueness and timeliness are the applicable data quality dimensions relevant to the programm...

Public health surveillance is the foundation of effective public health practice. Public health surveillance is defined as the ongoing systematic collection, analysis, and interpretation of data, closely integrated with the dissemination of these data to the public health practitioners, clinicians, and policy makers responsible for preventing and controlling disease and injury. 1 Ideally, surveillance systems should support timely, efficient, flexible, scalable, and interoperable data acquisition, analysis, and dissemination. However, many current systems rely on disease-specific approaches that inhibit efficiency and interoperability (eg, manual data entry and data recoding that place a substantial burden on data partners) and use slow, inefficient, out-of-date technologies that no longer meet user needs for data management, analysis, visualization, and dissemination. 2-4 Advances in information technology, data science, analytic methods, and information sharing provide an opportunity to substantially enhance surveillance. As a global leader in public health surveillance, the Centers for Disease Control and Prevention (CDC) is working with public health partners to transform and modernize CDC's surveillance systems and approaches. Here, we describe recent enhancements in surveillance data analysis and visualization, information sharing, and dissemination at CDC and identify the challenges ahead.

To describe the methodology for the development of data quality metrics in multi-institutional databases, deriving a cumulative data quality score [Aggregate Data Quality score (ADQ)]. The ESTS database was used to create and apply the metrics. The Units contributing to the ESTS database were ranked for the quality of data uploaded using the ADQ. We analysed data obtained from 96 Units contributing with at least 100 major lung resections (January 2007 to December 2014). The Units were anonymized assigning a casual numeric code. The following metrics were developed for measuring the data quality of each Unit: (i) record Completeness (COM); rate of present variables on 16 expected variables for all the records uploaded [1 - ('null values'/total expected values for the Unit) × 100, the concept of 'null value' was defined for each variable]; (ii) record Reliability (REL); rate of consistent checks on 9 checks tested for all the records uploaded [1 - (valid controls/total...

Energy intake (EI) and physical activity energy expenditure (PAEE) are key modifiable determinants of energy balance, traditionally assessed by self-report despite its repeated demonstration of considerable inaccuracies. We argue here that it is time to move from the common view that self-reports of EI and PAEE are imperfect, but nevertheless deserving of use, to a view commensurate with the evidence that self-reports of EI and PAEE are so poor that they are wholly unacceptable for scientific research on EI and PAEE. While new strategies for objectively determining energy balance are in their infancy, it is unacceptable to use decidedly inaccurate instruments, which may misguide health-care policies, future research and clinical judgment. The scientific and medical communities should discontinue reliance on self-reported EI and PAEE. Researchers and sponsors should develop objective measures of energy balance.International Journal of Obesity advance online publication, 23 December 2...

The proliferation of new technology platforms and tools is dramatically advancing our ability to capture, integrate and use clinical and other health related data for research and care. Another critical and increasingly common source of data comes directly from patients - often in the form of Patient Reported Outcomes (PRO). As more providers and payers recognize that patient experiences reflect a critical dimension of the value proposition, these data are informing broader strategies to achieve performance improvement and accountability in health systems. Combined with other traditional (e.g., claims) and more recent (e.g., Electronic Health Record) data assets, PROs can help to examine experiences and outcomes that convey a more complete picture of both individual and population health. One of the areas of research where this is most evident is cancer survivorship, including long-term adverse effects, as the population of survivors is increasing given advances in detection and tre...

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.

Birth weight is essential information in fetal programming studies and is generally obtained retrospectively. In Brazil's Information System on Live Births (SINASC), birth weight is valid information but is not always accessible. The study aimed to establish an algorithm for the selection of the most reliable data source for birth weight in the absence of information in the SINASC database. In a cross-sectional study of 6-14-year-old schoolchildren in Niterói, Rio de Janeiro State, Brazil, in 2010, birth weight was collected through a self-completed questionnaire, interview, medical records from the Family Physician Program, and the SINASC database. We calculated intra-class correlation coefficients (ICCs) and differences in mean birth weight. ICCs varied from 0.90 to 0.99. All the other sources showed higher mean birth weight than SINASC, allowing differences up to 100g. Birth weight is recorded at birth (SINASC) or close to it (Family Physician Program), and in the absence of ...

Systematic reviews and/or meta-analyses generally provide the best evidence for medical research. Authors are recommended to use flow diagrams to present the review process, allowing for better understanding among readers. However, no studies as of yet have assessed the quality of flow diagrams in systematic review/meta-analyses. Our study aims to evaluate the quality of systematic review/meta-analyses over a period of ten years, by assessing the quality of the flow diagrams, and the correlation to the methodological quality. Two hundred articles of "systematic review" and/or "meta-analysis" from January 2004 to August 2015 were randomly retrieved in Pubmed to be assessed for the flow diagram and methodological qualities. The flow diagrams were evaluated using a 16-grade scale corresponding to the four stages of PRISMA flow diagram. It composes four parts: Identification, Screening, Eligibility and Inclusion. Of the 200 articles screened, 154 articles were includ...

Health workers are the key drivers for strengthening Prevention of Mother-to-Child Transmission (PMTCT) program information management in the health facilities. Thus understanding how health workers perceive information management can enlighten areas that require interventions to improve information management processes in the health facilities. The purpose is to assess health workers' perceptions toward PMTCT program information management and factors affecting information management in the health facilities. The study was conducted in five out of forty-three health facilities providing PMTCT services in Lilongwe district and thirty out of sixty-eight health workers were recruited across the study sites. Purposive and convenience sampling were used. Semi-structured questionnaires and in-depth interviews were used to collect demographic information and health workers' perceptions toward information management, respectively. Thematic and content analysis techniques were emplo...

Verbal autopsy (VA) methods are designed to collect cause-of-death information from populations where many deaths occur outside of health facilities and where death certification is weak or absent. A VA consists of an interview with a relative or carer of a recently deceased individual in order to gather information on the signs and symptoms the decedent presented with prior to death. These details are then used to determine and assign a likely cause-of-death. At a population level this information can be invaluable to help guide prioritisation and direct health policy and services. To date VAs have largely been restricted to research contexts but many countries are now venturing to incorporate VA methods into routine civil registration and vital statistics (CRVS) systems. Given the sensitive nature of death, however, there are a number of ethical, legal and social issues that should be considered when scaling-up VAs, particularly in the cross-cultural and socio-economically disadva...

Routine health data can guide health systems improvements, but poor quality of these data hinders use. To address concerns about data quality in Malawi, the Ministry of Health and National Statistical Office conducted a data quality assessment (DQA) in July 2016 to identify systems-level factors that could be improved. We used 2-stage stratified random sampling methods to select health centers and hospitals under Ministry of Health auspices, included those managed by faith-based entities, for this DQA. Dispensaries, village clinics, police and military facilities, tertiary-level hospitals, and private facilities were excluded. We reviewed client registers and monthly reports to verify availability, completeness, and accuracy of data in 4 service areas: antenatal care (ANC), family planning, HIV testing and counseling, and acute respiratory infection (ARI). We also conducted interviews with facility and district personnel to assess health management information system (HMIS) function...

The present study aimed to assess the accuracy of linear measurements performed with two software packages in multislice (MSCT) and cone beam (CBCT) computed tomography (CT) images. The sample consisted of 10 human mandibles marked standardly 8 times with metallic orthodontic wires. The mandibles underwent both MSCT and CBCT scanning and were measured linearly and digitally with two software packages, namely Studio 3.1® (Anne Solutions®, SP, Brazil) (ST) and Implant Viewer 2.817® (Anne Solutions®, SP, Brazil) (IV). The linear measurements were the mandibular height (MH) and width (MW), and the distance from the alveolar ridge to the mandibular canal (AC). To validate the measurements, the mandibles were sectioned in the marked regions and measured with a digital caliper. Statistically significant differences were not observed between the measurements (MH, MW, and AC) taken digitally with the two software packages from images obtained from the two scanning modalities (MSCT and CBCT) ...

Objective-To assess problem list completeness using an objective measure across a range of sites, and to identify success factors for problem list completeness. Methods-We conducted a retrospective analysis of electronic health record data and interviews at ten healthcare organizations within the United States, United Kingdom, and Argentina who use a variety of electronic health record systems: four self-developed and six commercial. At each site, we assessed the proportion of patients who have diabetes recorded on their problem list out of all patients with a hemoglobin A1c elevation >= 7.0%, which is diagnostic of diabetes. We then conducted interviews with informatics leaders at the four highest performing sites to determine factors associated with success. Finally, we surveyed all the sites about common practices implemented at the top performing sites to determine whether there was an association between problem list management practices and problem list completeness. Results-Problem list completeness across the ten sites ranged from 60.2% to 99.4%, with a mean of 78.2%. Financial incentives, problem-oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture were identified as success factors at the four hospitals with problem list completeness at or near 90.0%. Discussion-Incomplete problem lists represent a global data integrity problem that could compromise quality of care and put patients at risk. There was a wide range of problem list completeness across the healthcare facilities. Nevertheless, some facilities have achieved high levels of problem list completeness, and it is important to better understand the factors that contribute to success to improve patient safety. Conclusion-Problem list completeness varies substantially across healthcare facilities. In our review of EHR systems at ten healthcare facilities, we identified six success factors which may be useful for healthcare organizations seeking to improve the quality of their problem list documentation: financial incentives, problem oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture.

Epidemiological studies are necessary to take public health decisions. Their relevance depends on the quality of data. Doctors in continuous care collect a big amount of data that can be used for epidemiological purpose, but spatial data may be dirty; based on city names, the localization is imprecise, even more if it is misspelled. The only way to identify a city without ambiguity is to use its identifier, which can be retrieved by cleansing geographical textual data. In France, cities are organized in administrative zones called departments and some city names are shared by several cities in several departments. The clear identification of the department and the city name allows to deduce the city unique identifier and to make some spatial analysis such as epidemiological studies. In this paper, we propose a method to cleanse such data, using several steps. After having standardized the text to cleanse, we use the Levenshtein distance to generate a first set of propositions. Final...

Large database research in axial spondyloarthritis (AxSpA) is limited by a lack of methods for identifying most types of AxSpA. Our objective was to develop methods for identifying AxSpA concepts in the free text of documents from electronic medical records. Veterans with documents in the national Veteran Health Administration Corporate Data Warehouse between January 1, 2005 and June 30, 2015 were included. Methods were developed for exploring, selecting, and extracting meaningful terms that were likely to represent AxSpA concepts. With annotation, clinical experts reviewed sections of text containing the meaningful terms (snippets) and classified the snippets according to whether or not they represented the intended AxSpA concept. With natural language processing (NLP) tools, computers were trained to replicate the clinical experts' snippet classifications. Three AxSpA concepts were selected by clinical experts, including sacroiliitis, terms including the prefix spond*, and HLA...

The Global Alliance for Infections in Surgery appreciates the great effort of the task force who derived and validated the Sepsis-3 definitions and considers the new definitions an important step forward in the evolution of our understanding of sepsis. Nevertheless, more than a year after their publication, we have a few concerns regarding the use of the Sepsis-3 definitions.

As a measure of stroke severity, the National Institutes of Health Stroke Scale (NIHSS) is an important predictor of patient- and hospital-level outcomes, yet is often undocumented. The purpose of this study is to quantify and correct for potential selection bias in observed NIHSS data. Data were obtained from the Michigan Stroke Registry and included 10 262 patients with ischemic stroke aged ≥65 years discharged from 23 hospitals from 2009 to 2012, of which 74.6% of patients had documented NIHSS. We estimated models predicting NIHSS documentation and NIHSS score and used the Heckman selection model to estimate a correlation coefficient (ρ) between the 2 model error terms, which quantifies the degree of selection bias in the documentation of NIHSS. The Heckman model found modest, but significant, selection bias (ρ=0.19; 95% confidence interval: 0.09, 0.29; P<0.001), indicating that because NIHSS score increased (ie, strokes were more severe), the probability of documentation also...

Public health surveillance is the foundation of effective public health practice. Public health surveillance is defined as the ongoing systematic collection, analysis, and interpretation of data, closely integrated with the dissemination of these data to the public health practitioners, clinicians, and policy makers responsible for preventing and controlling disease and injury. 1 Ideally, surveillance systems should support timely, efficient, flexible, scalable, and interoperable data acquisition, analysis, and dissemination. However, many current systems rely on disease-specific approaches that inhibit efficiency and interoperability (eg, manual data entry and data recoding that place a substantial burden on data partners) and use slow, inefficient, out-of-date technologies that no longer meet user needs for data management, analysis, visualization, and dissemination. 2-4 Advances in information technology, data science, analytic methods, and information sharing provide an opportunity to substantially enhance surveillance. As a global leader in public health surveillance, the Centers for Disease Control and Prevention (CDC) is working with public health partners to transform and modernize CDC's surveillance systems and approaches. Here, we describe recent enhancements in surveillance data analysis and visualization, information sharing, and dissemination at CDC and identify the challenges ahead.