Data Accuracy in Medical Record Abstraction

Clinical Research Data Quality Literature Review and Pooled Analysis We present a literature review and secondary analysis of data accuracy in clinical research and related secondary data uses. A total of 93 papers meeting our inclusion criteria were categorized according to the data processing methods. Quantitative data accuracy information was abstracted from the articles and pooled. Our analysis demonstrates that the accuracy associated with data processing methods varies widely, with error rates ranging from 2 errors per 10,000 files to 5019 errors per 10,000 fields. Medical record abstraction was associated with the highest error rates (70–5019 errors per 10,000 fields). Data entered and processed at healthcare facilities had comparable error rates to data processed at central data processing centers. Error rates for data processed with single entry in the presence of on-screen checks were comparable to double entered data. While data processing and cleaning methods may explain a significant amount of the variability in data accuracy, additional factors not resolvable here likely exist. Defining Data Quality for Clinical Research: A Concept Analysis Despite notable previous attempts by experts to define data quality, the concept remains ambiguous and subject to the vagaries of natural language. This current lack of clarity continues to hamper research related to data quality issues. We present a formal concept analysis of data quality, which builds on and synthesizes previously published work. We further posit that discipline-level specificity may be required to achieve the desired definitional clarity. To this end, we combine work from the clinical research domain with findings from the general data quality literature to produce a discipline-specific definition and operationalization for data quality in clinical research. While the results are helpful to clinical research, the methodology of concept analysis may be useful in other fields to clarify data quality attributes and to achieve operational definitions. Medical Record Abstractor’s Perceptions of Factors Impacting the Accuracy of Abstracted Data Medical record abstraction (MRA) is known to be a significant source of data errors in secondary data uses. Factors impacting the accuracy of abstracted data are not reported consistently in the literature. Two Delphi processes were conducted with experienced medical record abstractors to assess abstractor’s perceptions about the factors. The Delphi process identified 9 factors that were not found in the literature, and differed with the literature by 5 factors in the top 25%. The Delphi results refuted seven factors reported in the literature as impacting the quality of abstracted data. The results provide insight into and indicate content validity of a significant number of the factors reported in the literature. Further, the results indicate general consistency between the perceptions of clinical research medical record abstractors and registry and quality improvement abstractors. Distributed Cognition Artifacts on Clinical Research Data Collection Forms Medical record abstraction, a primary mode of data collection in secondary data use, is associated with high error rates. Distributed cognition in medical record abstraction has not been studied as a possible explanation for abstraction errors. We employed the theory of distributed representation and representational analysis to systematically evaluate cognitive demands in medical record abstraction and the extent of external cognitive support employed in a sample of clinical research data collection forms. We show that the cognitive load required for abstraction in 61% of the sampled data elements was high, exceedingly so in 9%. Further, the data collection forms did not support external cognition for the most complex data elements. High working memory demands are a possible explanation for the association of data errors with data elements requiring abstractor interpretation, comparison, mapping or calculation. The representational analysis used here can be used to identify data elements with high cognitive demands.

Autoregulation of TRA-2 pre -mRNA splicing

One of the most elegant and tightly regulated mechanisms for control of gene expression is alternative pre-mRNA splicing. Despite the importance of regulated splicing in a variety of biological processes relatively little is understood about the mechanisms by which specific alternative splice choices are made and regulated. The transformer-2 (tra-2) gene encodes a splicing regulator that controls the use of alternative splicing pathways in the sex determination cascade of D. melanogaster and is particularly interesting because it directs the splicing of several distinct pre-mRNAs in different manners. The tra-2 protein positively regulates the splicing of both doublesex (dsx) and fruitless (fru) pre-mRNAs. Additionally tra-2 controls exuperantia (exu) by directing the choices between splicing and cleavage/polyadenylation and autoregulates the tra-2 pre-mRNA processing by repressing the removal of a specific intron (called M1). The goal of this study is to identify the molecular mechanisms by which TRA-2 protein affects the alternative splicing of pre-mRNA deriving from the tra-2 gene itself.^ The autoregulation of M1 splicing plays a key role in regulation of the relative levels of two functionally distinct TRA-2 protein isoforms expressed in the male germline. We have examined whether the structure, function, and regulation of tra-2 are conserved in Drosophila virilis, a species diverged from D. melanogaster by over 60 million years. We find that the D. virilis homolog of tra-2 produces alternatively spliced RNAs encoding a set of protein isoforms analogous to those found in D. melanogaster. When introduced into the genome of D. melanogaster, this homolog can functionally replace the endogenous tra-2 gene for both normal female sexual differentiation and spermatogenesis. Examination of alternative pre-mRNAs produced in D. virilis testes suggests that the germline-specific autoregulation of tra-2 function is accomplished by a strategy similar to that used in D. melanogaster.^ To identify elements necessary for regulation of tra-2 M1 splicing, we mutagenized evolutionarily conserved sequences within the tra-2 M1 intron and flanking exons. Constructs containing these mutations were used to generate transgenic fly lines that have been tested for their ability to carry out autoregulation. These transgenic fly experiments elucidated several elements that are necessary for setting up a context under which tissue-specific regulation of M1 splicing can occur. These elements include a suboptimal 3$\sp\prime$ splice site, an element that has been conserved between D. virilis and D. melanogaster, and an element that resembles the 3$\sp\prime$ portion of a dsx repeat and other splicing enhancers.^ Although important contextual features of the tra-2 M1 intron have been delineated in the transgenic fly experiments, the specific RNA sequences that interact directly with the TRA-2 protein were not identified. Using Drosophila nuclear extracts from Schneider cells, we have shown that recombinant TRA-2 protein represses M1 splicing in vitro. UV crosslinking analysis suggests that the TRA-2 protein binds to several different sites within and near the M1 intron. ^