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PubMed2000

Data quality in predictive toxicology: identification of chemical structures and calculation of chemical properties.

Every technique for toxicity prediction and for the detection of structure-activity relationships relies on the accurate estimation and representation of chemical and toxicologic properties. In this paper we discuss the potential sources of errors associated with the identification of compounds, the representation of their structures, and the calculation of chemical descriptors. It is based on a case study where machine learning techniques were applied to data from noncongeneric compounds and a complex toxicologic end point (carcinogenicity). We propose methods applicable to the routine quality control of large chemical datasets, but our main intention is to raise awareness about this topic and to open a discussion about quality assurance in predictive toxicology. The accuracy and reproducibility of toxicity data will be reported in another paper.

Data Interpretation, Statistical↗
PubMed1990

Tapping into quality data is next for hospital CME programs.

Hospitals have traditionally been one of physicians' favorite places in receive continuing medical education (CME). However, medical specialty societies are also playing an increasingly large role in the delivery of CME. In light of such results, executives might want to start considering other ways to make hospital-sponsored CME relevant, experts suggest. For example, some hospitals are turning their attention toward problem- or practice-based CME.

Clinical Competence↗
PubMed2001

The 1996 Paso del Norte Ozone Study: analysis of meteorological and air quality data that influence local ozone concentrations.

The 1996 Paso del Norte Ozone Study and subsequent data analyses were implemented to develop an understanding of the chemical and physical processes which lead to high concentrations of ozone in the Paso del Norte study area which includes El Paso County, Texas, Sunland Park, New Mexico, and Ciudad Juárez, Mexico. Both the data and data analysis results are being used to support photochemical grid modeling. El Paso County and Sunland Park fail to meet the National Ambient Air Quality Standard (NAAQS) for ozone, and neighboring Ciudad Juárez fails to meet the Mexican ambient standard for ozone. This paper summarizes the measurement campaigns of the 1996 Paso del Norte Ozone Study and the findings and conclusions that arose from subsequent data analyses. Data analyses showed that high ozone concentrations resulted from a combination of conditions, including high surface temperatures, strong sunlight with few clouds, light surface winds and high concentrations of ozone precursors at ground level in the morning, and slow convective boundary layer (CBL) growth. Synoptic-scale meteorological conditions observed during high ozone episodes included an aloft high-pressure system and aloft warming. Aloft carryover of ozone and ozone precursors did not significantly contribute to high concentrations of ozone at the surface.

Air Movements↗
PubMed2006

An evaluation of data quality in a network for surveillance of Mycobacterium tuberculosis resistance to antituberculosis drugs in Ile-de-France region-2001-2002.

We evaluated the French Azay-Mycobacteria network for surveillance of Mycobacterium tuberculosis drug resistance by matching data with those collected through the mandatory notification (MNTB). Sensitivity of Azay was 96% by capture-recapture analysis. Cases reported to MNTB were more often smear-positive than non-reported cases. Concordance of data collected for common cases was excellent for a majority of variables (k > 0.79), excepted for tuberculosis site (k = 0.52). These results suggest a good quality of the network.

Antitubercular Agents↗
PubMedDate not supplied

Retrospective data quality audits of the Harvard Six Cities and American Cancer Society studies.

The Harvard Six Cities (6-Cities) and American Cancer Society (ACS) studies are longitudinal cohort mortality studies of large populations that provided important information about the human health effects associated with long-term exposure to fine particulate air pollution. Possible changes to federal regulation of particulates prompted a review of data collection methods, analysis, and reported results from these two studies. This article describes the methodology used to conduct quality assurance audits of both studies and summarizes the audit findings. Statistically based, randomly selected samples of 250 health questionnaires and 250 death certificates from each study were audited against data from analysis files. In cases where study-specific data could not be located, validation was performed using information and data from other sources. Some errors were found in programming and data transformation in both studies, but none affected the results of the original investigations. Both audits confirmed that the published studies are an accurate representation of the collected data. The audits also underscored the importance of adequate attention to documentation and record-keeping practices during the conduct of all studies and proper archiving at their conclusion.

Air Pollution↗