Dataset Information

Neurosyphilis Surveillance: Exploring the Use of Multiple Data Sources to Better Understand Morbidity in California.

ABSTRACT:

Abstract

Accurate reporting of neurosyphilis diagnoses is important to quantify and monitor severe outcomes associated with infection of Treponemal pallidum. This analysis compared the demographic distribution of neurosyphilis diagnoses in sexually transmitted disease surveillance data with administrative hospital data in the California Project Area from 2016 to 2018. Although neurosyphilis morbidity was similar, significant differences were noted by sex, age group, race/ethnicity, and region. Both sexually transmitted disease surveillance and administrative hospital data may be imperfect systems to understand the true morbidity of neurosyphilis.

SUBMITTER: Burghardt NO

PROVIDER: S-EPMC8284351 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Publications

Neurosyphilis Surveillance: Exploring the Use of Multiple Data Sources to Better Understand Morbidity in California.

Burghardt Nicole Olson NO Nelson Lauren N LN Tang Eric C EC Plotzker Rosalyn E RE Jacobson Kathleen K Murphy Ryan D RD

Sexually transmitted diseases 20210801 8S

<h4>Abstract</h4>Accurate reporting of neurosyphilis diagnoses is important to quantify and monitor severe outcomes associated with infection of Treponemal pallidum. This analysis compared the demographic distribution of neurosyphilis diagnoses in sexually transmitted disease surveillance data with administrative hospital data in the California Project Area from 2016 to 2018. Although neurosyphilis morbidity was similar, significant differences were noted by sex, age group, race/ethnicity, and r ...[more]

PMID: 33967237

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Project description:BackgroundEffective animal health surveillance systems require reliable, high-quality, and timely data for decision making. In Tanzania, the animal health surveillance system has been relying on a few data sources, which suffer from delays in reporting, underreporting, and high cost of data collection and transmission. The integration of data from multiple sources can enhance early detection and response to animal diseases and facilitate the early control of outbreaks. This study aimed to identify and assess existing and potential data sources for the animal health surveillance system in Tanzania and how they can be better used for early warning surveillance. The study used a mixed-method design to identify and assess data sources. Data were collected through document reviews, internet search, cross-sectional survey, key informant interviews, site visits, and non-participant observation. The assessment was done using pre-defined criteria.ResultsA total of 13 data sources were identified and assessed. Most surveillance data came from livestock farmers, slaughter facilities, and livestock markets; while animal dip sites were the least used sources. Commercial farms and veterinary shops, electronic surveillance tools like AfyaData and Event Mobile Application (EMA-i) and information systems such as the Tanzania National Livestock Identification and Traceability System (TANLITS) and Agricultural Routine Data System (ARDS) show potential to generate relevant data for the national animal health surveillance system. The common variables found across most sources were: the name of the place (12/13), animal type/species (12/13), syndromes (10/13) and number of affected animals (8/13). The majority of the sources had good surveillance data contents and were accessible with medium to maximum spatial coverage. However, there was significant variation in terms of data frequency, accuracy and cost. There were limited integration and coordination of data flow from the identified sources with minimum to non-existing automated data entry and transmission.ConclusionThe study demonstrated how the available data sources have great potential for early warning surveillance in Tanzania. Both existing and potential data sources had complementary strengths and weaknesses; a multi-source surveillance system would be best placed to harness these different strengths.

Project description:ProblemReflective practice is necessary for self-regulated learning. Helping medical students develop these skills can be challenging since they are difficult to observe. One common solution is to assign students' reflective self-assessments, which produce large quantities of narrative assessment data. Reflective self-assessments also provide feedback to faculty regarding students' understanding of content, reflective abilities, and areas for course improvement. To maximize student learning and feedback to faculty, reflective self-assessments must be reviewed and analyzed, activities that are often difficult for faculty due to the time-intensive and cumbersome nature of processing large quantities of narrative assessment data.ApproachThe authors collected narrative assessment data (2,224 students' reflective self-assessments) from 344 medical students' reflective self-assessments. In academic years 2019-2020 and 2021-2022, students at the University of Cincinnati College of Medicine responded to 2 prompts (aspects that surprised students, areas for student improvement) after reviewing their standardized patient encounters. These free-text entries were analyzed using TopEx, an open-source natural language processing (NLP) tool, to identify common topics and themes, which faculty then reviewed.OutcomesTopEx expedited theme identification in students' reflective self-assessments, unveiling 10 themes for prompt 1 such as question organization and history analysis, and 8 for prompt 2, including sensitive histories and exam efficiency. Using TopEx offered a user-friendly, time-saving analysis method without requiring complex NLP implementations. The authors discerned 4 education enhancement implications: aggregating themes for future student reflection, revising self-assessments for common improvement areas, adjusting curriculum to guide students better, and aiding faculty in providing targeted upcoming feedback.Next stepsThe University of Cincinnati College of Medicine aims to refine and expand the utilization of TopEx for deeper narrative assessment analysis, while other institutions may model or extend this approach to uncover broader educational insights and drive curricular advancements.

Dataset Information

Neurosyphilis Surveillance: Exploring the Use of Multiple Data Sources to Better Understand Morbidity in California.

Abstract

Publications

Neurosyphilis Surveillance: Exploring the Use of Multiple Data Sources to Better Understand Morbidity in California.

Similar Datasets

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