Descriptive epidemiology of cancer in three regions of Kazakhstan

The current study investigated data quality and estimated cancer incidence and mortality rates using data provided by Pavlodar, Semipalatinsk and Ust-Kamenogorsk Regional Cancer Registries of Kazakhstan during the period of 1996–1998. Assessment of data quality was performed using standard quality indicators including internal database checks, proportion of cases verified from death certificates only, mortality:incidence ratio, data patterns, proportion of cases with unknown primary site, proportion of cases with unknown age. Crude and age-adjusted incidence and mortality rates and 95% confidence intervals were calculated, by gender, for all cancers combined and for 28 specific cancer sites for each year of the study period. The five most frequent cancers were identified and described for every population. The results of the study provide the first simultaneous assessment of data quality and standardized incidence and mortality rates for Kazakh cancer registries. ^

The feasibility of self-report advance directives among elderly patients with cognitive impairment

The central objective of this dissertation was to determine the feasibility of self-completed advance directives (AD) in older persons suffering from mild and moderate stages of dementia. This was accomplished by identifying differences in ability to complete AD among elderly subjects with increasing degrees of dementia and cognitive incompetence. Secondary objectives were to describe and compare advance directives completed by elders and identified proxy decision makers. Secondary objectives were accomplished by measuring the agreement between advance directives completed by proxy and elder, and comparing that agreement across groups defined by the elder's cognitive status. This cross-sectional study employed a structured interview to elicit AD, followed by a similar interview with a proxy decision maker identified by the elder. A stratified sampling scheme recruited elders with normal cognition, mild, and moderate forms of dementia using the Mini Mental-State Exam (MMSE). The Hopkins Competency Assessment Test (HCAT) was used for evaluation of competency to make medical decisions. Analysis was conducted on "between group" (non-demented $\leftrightarrow$ mild dementia $\leftrightarrow$ moderate dementia, and competent $\leftrightarrow$ incompetent) and "within group" (elder $\leftrightarrow$ family member) variation.^ The 118 elderly subjects interviewed were generally male, Caucasian, and of low socioeconomic status. Mean age was 77. Overall, elders preferred a "trial of therapy" regarding AD rather than to "always receive the therapy". No intervention was refused outright more often than it was accepted. A test-retest of elders' AD revealed stable responses. Eleven logic checks measured appropriateness of AD responses independent of preference. No difference was found in logic error rates between elders grouped by MMSE or HCAT. Agreement between proxy and elder responses showed significant dissimilarity, indicating that proxies were not making the same medical decisions as the elders.^ Conclusions based on these data are: (1) Self reporting AD is feasible among elders showing signs of cognitive impairment and they should be given all opportunities to complete advance directives, (2) variation in preferences for advance directives in cognitively impaired elders should not be assumed to be the effects of their impairment alone, (3) proxies do not appear to forego life-prolonging interventions in the face of increasing impairment in their ward, however, their advance directives choices are frequently not those of the elder they represent. ^

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.