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PubMedDate not supplied

Assessing the quality of project data by means of a data sufficiency categorization scheme.

Improving the quality of gathered or abstracted data is often an important part of a quality improvement project's early stages. This is especially so if indicators will be compared across providers or if various data elements will be used for severity adjustment. One common data problem is missing data. This paper describes a flowchart-based approach for assessing the magnitude of missing data problems. The approach is demonstrated by means of two indicators currently used in multihospital cooperative improvement projects. The approach results in assigning each observation (e.g., patient record) in a sample into one of five data categories. These categories follow standard definitions advanced by the Joint Commission on Accreditation of Healthcare Organizations. Two of the categories tally observations with missing data problems. Assessment of missing data can be viewed as one component of reliability assessment, and its relationship to other forms of reliability assessment is discussed, with emphasis on the relationship to interrater agreement.

Abstracting and Indexing↗
PubMed1996

Reliability and validity of the addiction severity index among homeless substance misusers.

Retrospective self-reports of behavior are widely used in alcohol and drug research. However, assessments of the reliability and validity of such data among certain populations are nonexistent. This study examines the ability of the Addiction Severity Index (ASI), a widely used clinical and research instrument, to provide valid and reliable data within a homeless population of drug misusers. The results support the usefulness of the ASI in producing quality data among homeless substance misusers seeking treatment. Qualitative data gathered from field interviewers are used to highlight strategies for enhancing the quality of ASI data in the future.

Adult↗
PubMedDate not supplied

Growth curve model analysis for quality of life data.

There is increasing interest in measuring health related quality of life in cancer clinical trials. Most quality of life data are measured repeatedly over a fixed time schedule to capture changes and to reflect relative advantages of study treatments. A multivariate repeated measures model is usually used to analyse this type of data. However, one of the difficulties of this analysis is that quality of life may be affected by the occurrence of some critical events experienced by patients. We may separate a patient's lifetime during study into different 'health states'. The duration of these health states may vary among patients, and may relate to the efficacy of the study treatment. In some cases quality of life data may be missing due to one of the many different types of missing data mechanisms specific for a health state. It is reasonable to assume that the missing data mechanism for a treatment arm is homogeneous within a defined health state, and to control for the potential confounding effect to appropriately assess the impact of treatment on the quality of life. In this paper, we propose a growth curve model conditional on a time-dependent variable of defined health states in order to assess the overall treatment effect while taking into account occurrences of missing data and measurements from irregular visits. A specific contrast can be drawn within the overall model for testing a specific hypothesis without relying on the analysis of subgroups of patients based on a smaller number of repeated measurements. Quality of life data from a recently completed small-cell lung cancer randomized trial are used to illustrate this method.

Antineoplastic Combined Chemotherapy Protocols↗
PubMed1992

Statistical analysis of longitudinal quality of life data with missing measurements.

The statistical analysis of longitudinal quality of life data in the presence of missing data is discussed. In cancer trials missing data are generated due to the fact that patients die, drop out, or are censored. These missing data are problematic in the monitoring of the quality of life during the trial. However, by means of assuming that the cause of the missing data lies in the observed history of the patients and not in their unobserved future, the missing data are ignorable. Consequently, all available data can be used to estimate quality of life change patterns with time. The computations that are required are illustrated with real quality of life data and three commonly used computer packages for statistical analysis.

Analysis of Variance↗
PubMed1993

The quality of survey data obtained from elderly adults.

The quality of survey data obtained from elderly adults has important implications for nutrition status assessment, policy decisions and program development. Self-reported information by adults of all ages is subject to inaccuracies. Accuracy of data obtained from older respondents may be lower than that of younger respondents. Errors made by older adults are largely due to misinterpretation of the questions asked, motivations related to participation and reporting of information, and changes in memory associated with aging and other factors which may impact respondent accuracy. Cooperative efforts by cognitive psychologists, survey researchers and nutritionists are necessary for improving both questionnaire design and the accuracy of information obtained.

Age Factors↗
PubMed2003

Reliability and validity of the School Health Policies and Programs Study 2000 questionnaires.

To help assess the quality of the questionnaires developed for the School Health Policies and Programs Study (SHPPS) 2000, the Centers for Disease Control and Prevention (CDC) conducted a data quality substudy in conjunction with SHPPS 2000. The substudy assessed validity of the state- and district-level questionnaires through telephone interviews with a subsample of the original state- and district-level respondents, and the test-retest reliability of the school- and classroom-level questionnaires through computer-assisted repeat interviews with a subsample of the school- and classroom-level respondents. Results indicated that although a few threats to the validity of responses to the state- and district-level questionnaires were identified, the questionnaires generally produced valid data. Among the school- and classroom-level questionnaires, some questions demonstrated poor reliability, but most exhibited moderate or substantial reliability, and some exhibited almost perfect reliability. CDC will use these results to revise the SHPPS 2000 questionnaires and will consider alternative methods of data collection to improve the quality of data collected in future versions of SHPPS.

Centers for Disease Control and Prevention, U.S.↗
PubMed1992

A rationale and framework for establishing the quality of human exposure assessments.

Exposure assessments, performed as input to an evaluation of potential human health risk, are an element of risk assessment. Risk assessment results feed governmental and corporate risk management decisions, which seek to balance the estimated potential human health risks with other factors. Risk managers presume that the risk information provided to them is scientifically valid and accurate. Government agencies have begun to apply a system known as good laboratory practices (GLP) to ensure adequate data quality on animal studies, which are often the first step in the health-effects evaluation of risk assessment. This paper explores a rationale and framework for establishing the quality of human exposure assessments and proposes a set of good exposure assessment practices (GEAP). The components of the proposed GEAP include the writing of a study protocol before conducting the study, consideration of available resources, specification of an exposure model, a study design (including sampling and analytical methods and data analysis), quality assurance, archiving, communications, and a statement of overall uncertainty in exposure estimates. The GEAP concept is offered as a starting point for developing a consensus among the community of exposure assessors regarding a minimum standard for good practices. If a consensus on GEAP can be reached and applied, exposure assessments would have improved scientific bases, interpretability, and utility.

Environmental Monitoring↗
PubMed2005

Interventions to improve health outcomes for patients with low literacy. A systematic review.

OBJECTIVE: To perform a systematic review of interventions designed to improve health outcomes for persons with low literacy skills. DATA SOURCES: We searched MEDLINE, Cumulative Index to Nursing and Allied Health (CINAHL), Educational Resources Information Center (ERIC), Public Affairs Information Service (PAIS), Industrial and Labor Relations Review (ILLR), PsycInfo, and Ageline from 1980 to 2003. STUDY SELECTION: We included controlled and uncontrolled trials that measured literacy and examined the effect of interventions for people with low literacy on health outcomes, including health knowledge, health behaviors, use of health care resources, intermediate markers of disease status, and measures of morbidity or mortality. Two abstractors reviewed each study for inclusion. Disagreements were resolved by consensus among the research team. DATA EXTRACTION: One reviewer abstracted data from each article into an evidence table; the second reviewer checked each entry. Disagreements about information in evidence tables were resolved by team consensus. Both data extractors independently completed an 11-item quality scale for each article; scores were averaged to give a final measure of article quality. DATA SYNTHESIS: We identified 20 articles examining interventions designed to improve health among people with low literacy. The most common outcome studied was health knowledge; fewer studies examined health behaviors, intermediate markers, or measures of disease prevalence or severity. The effectiveness of interventions appeared mixed. Limitations in research quality and heterogeneity in outcome measures make drawing firm conclusions about effective strategies difficult. Only 5 articles examined the interaction between literacy level and the effect of the intervention; they also found mixed results. CONCLUSIONS: Several interventions have been developed to improve health for people with low literacy. Limitations in study design, interventions tested, and outcomes assessed make drawing conclusions about effectiveness difficult. Further research is required to understand better the types of interventions that are most effective and efficient for overcoming literacy-related barriers to good health.

Clinical Trials as Topic↗
PubMed1975

A large scale mastitis control programme in Somerset.

The results of a mastitis control programme operated in south west England for three years are given. Farmers participating in the full mastitis control group agreed to treat each cow at drying off with 500 mg benzathine cloxacillin in each quarter, to have their milking machines tested and to correct any faults, and to practise teat dipping. Data covering cell counts, milk production, milk quality and clinical mastitis, were assessed from herds taking part in the programme. Cell counts were analysed from all 507 herds taking part in the programme. Milk production records for the full mastitis control group (188 herds) over a three year period are discussed, and these results compared with milk production figures from Milk Marketing Board records from herds in the south west of England which were carrying out no specific mastitis control programme. The milk quality data compare the findings in 159 herds in the full mastitis control programme with those in 247 herds in the partial and no mastitis control groups. Cases of clinical mastitis during the three year period were recorded in 73 herds in the full mastitis control group. The problems of applying the control routines are presented with observations on clinical mastitis, bulk milk cell count, milk production and milk quality. After three years, herds in the programme had on average increased milk production by 75 gallons a cow, achieved a 14.6 per cent reduction in the incidence of clinical mastitis, and improved the milk total solids percentage by one milk quality payment class.

Animals↗
PubMed2004

Literacy and health outcomes: a systematic review of the literature.

OBJECTIVE: To review the relationship between literacy and health outcomes. DATA SOURCES: We searched MEDLINE, Cumulative Index to Nursing and Allied Health (CINAHL), Educational Resources Information Center (ERIC), Public Affairs Information Service (PAIS), Industrial and Labor Relations Review (ILLR), PsychInfo, and Ageline from 1980 to 2003. STUDY SELECTION: We included observational studies that reported original data, measured literacy with any valid instrument, and measured one or more health outcomes. Two abstractors reviewed each study for inclusion and resolved disagreements by discussion. DATA EXTRACTION: One reviewer abstracted data from each article into an evidence table; the second reviewer checked each entry. The whole study team reconciled disagreements about information in evidence tables. Both data extractors independently completed an 11-item quality scale for each article; scores were averaged to give a final measure of article quality. DATA SYNTHESIS: We reviewed 3,015 titles and abstracts and pulled 684 articles for full review; 73 articles met inclusion criteria and, of those, 44 addressed the questions of this report. Patients with low literacy had poorer health outcomes, including knowledge, intermediate disease markers, measures of morbidity, general health status, and use of health resources. Patients with low literacy were generally 1.5 to 3 times more likely to experience a given poor outcome. The average quality of the articles was fair to good. Most studies were cross-sectional in design; many failed to address adequately confounding and the use of multiple comparisons. CONCLUSIONS: Low literacy is associated with several adverse health outcomes. Future research, using more rigorous methods, will better define these relationships and guide developers of new interventions.

Educational Status↗
PubMed2002

Data management and quality assurance for an International project: the Indo-US Cross-National Dementia Epidemiology Study.

BACKGROUND: Data management and quality assurance play a vital but often neglected role in ensuring high quality research, particularly in collaborative and international studies. OBJECTIVE: A data management and quality assurance program was set up for a cross-national epidemiological study of Alzheimer's disease, with centers in India and the United States. METHODS: The study involved (a) the development of instruments for the assessment of elderly illiterate Hindi-speaking individuals; and (b) the use of those instruments to carry out an epidemiological study in a population-based cohort of over 5000 persons. Responsibility for data management and quality assurance was shared between the two sites. A cooperative system was instituted for forms and edit development, data entry, checking, transmission, and further checking to ensure that quality data were available for timely analysis. A quality control software program (CHECKS) was written expressly for this project to ensure the highest possible level of data integrity. CONCLUSIONS: This report addresses issues particularly relevant to data management and quality assurance at developing country sites, and to collaborations between sites in developed and developing countries.

Alzheimer Disease↗
PubMed2001

A critical review of the scientific literature on potential endocrine-mediated effects in fish and wildlife.

A rigorous approach to evaluating the reliability and relevance of experimental methods and results is critical for making appropriate, scientifically sound decisions. A literature evaluation framework was modified and adapted based on criteria described by Klimisch et al. (H. J. Klimisch, M. Andrae, and U. Tillman, 1997, Reg. Tox. Pharm. 25, 1-5) and requirements of the USEPA High Product Volume Challenge Program. This simple framework was used to evaluate an appropriate selection of peer-reviewed references to assign a Study Reliability "score" to the study design, endpoints, and conclusions compared to established data quality guidelines. Subsequently, the interpretation of the data was evaluated and assigned a Relevance Index based on the overall strength of evidence of endocrine modulation potential, which was evaluated based on the Weybridge (European Commission (1996). European workshop on the impact of endocrine disrupters on human health and wildlife. Report of proceedings from a workshop held in Weybridge, UK, 2-4 December 1996. Report reference EUR 17549, European Commission, DGXII, Brussels, Belgium.) definition. This report describes the evaluation of 50 peer-reviewed primary publications. The vast majority of studies reviewed were published in the period from 1996 to the present and most examined in vivo responses of fish to natural hormones, organochlorines, or alkylphenolic compounds. Of the studies reviewed, approximately 40% received a score of "2-Reliable with Restrictions," while approximately 60% received a score of "3-Not Reliable," where reliability was interpreted to include scientific integrity, technical credibility, endpoint relevance, and regulatory compliance. The most common deficiencies were inadequate methods, lack of suitable controls, exceeding aqueous solubility, inappropriate statistics, and unsupported conclusions. Based on the Relevance Index, few of the studies examined attained the level of quality necessary to identify the study results as providing an acceptable basis for evaluation of endocrine modulation potential directly resulting from identified deficiencies in meeting the established study reliability criteria.

Animals↗
PubMed2006

A statistical evaluation of recent full reference image quality assessment algorithms.

Measurement of visual quality is of fundamental importance for numerous image and video processing applications, where the goal of quality assessment (QA) algorithms is to automatically assess the quality of images or videos in agreement with human quality judgments. Over the years, many researchers have taken different approaches to the problem and have contributed significant research in this area and claim to have made progress in their respective domains. It is important to evaluate the performance of these algorithms in a comparative setting and analyze the strengths and weaknesses of these methods. In this paper, we present results of an extensive subjective quality assessment study in which a total of 779 distorted images were evaluated by about two dozen human subjects. The "ground truth" image quality data obtained from about 25,000 individual human quality judgments is used to evaluate the performance of several prominent full-reference image quality assessment algorithms. To the best of our knowledge, apart from video quality studies conducted by the Video Quality Experts Group, the study presented in this paper is the largest subjective image quality study in the literature in terms of number of images, distortion types, and number of human judgments per image. Moreover, we have made the data from the study freely available to the research community. This would allow other researchers to easily report comparative results in the future.

Algorithms↗
PubMed2000

Video technology. Use in nursing research.

Video technology is becoming more popular as a research tool because it has unique features that capture accurately and comprehensively the nature of nursing phenomena. Video technology is used extensively in nursing as an educational tool or intervention, a means of monitoring quality assurance standards, and as tool to collect research data. Videotaping is useful because is provides continuous multi-media, multisensory information about the subject and its context. Credibility for video data is based on the question of to what extent do the data or results adequately represent true behavior. The three main issues in video research that impact the credibility of data are observer bias, participant reactivity to knowledge of being videotaped, and maintenance of consistent data quality. Not all threats to credibility can be overcome. The key is to acknowledge insurmountable problems, to consider their limitations in data analysis, and to evaluate and report their effects.

Bias↗
PubMed2003

The UMD-p53 database: new mutations and analysis tools.

The tumor suppressor gene TP53 (p53) is the most extensively studied gene involved in human cancers. More than 1,400 publications have reported mutations of this gene in 150 cancer types for a total of 14,971 mutations. To exploit this huge bulk of data, specific analytic tools were highly warranted. We therefore developed a locus-specific database software called UMD-p53. This database compiles all somatic and germline mutations as well as polymorphisms of the TP53 gene which have been reported in the published literature since 1989, or unpublished data submitted to the database curators. The database is available at www.umd.necker.fr or at http://p53.curie.fr/. In this paper, we describe recent developments of the UMD-p53 database. These developments include new fields and routines. For example, the analysis of putative acceptor or donor splice sites is now automated and gives new insight for the causal role of "silent mutations." Other routines have also been created such as the prescreening module, the UV module, and the cancer distribution module. These new improvements will help users not only for molecular epidemiology and pharmacogenetic studies but also for patient-based studies. To achieve theses purposes we have designed a procedure to check and validate data in order to reach the highest quality data.

Databases, Genetic↗
PubMedDate not supplied

Quantification of statistical type I and II errors in correlation analysis of simulated functional magnetic resonance imaging data.

The potential of statistical analyses of functional magnetic resonance images using various threshold strategies in combination with correlation analysis was studied by simulating brain activation. Differences in statistical Type I (alpha) and II (beta) errors are substantial for the various thresholds. Absolute thresholds and individualized thresholds based on the assumption of a gaussian noise distribution are producing constant alpha-errors and thus do not sufficiently improve discrimination of "truly" activated pixels even for very high contrast-to-noise ratios (CNR). Only relative threshold strategies related to the maximum correlation coefficient and thus the individual data quality and activation level, i.e., a data-driven approach, can perfectly discriminate true positives, at least for CNR > 2.5. To further improve discrimination of activated and non-activated pixel in studies with lower CNR, additional prior knowledge would be necessary. From the data presented, one would also expect that the best performing threshold strategy in this simulation study would perform best under in vivo conditions.

Biometry↗
PubMed1990

The U.S. Federal Highway Administrations receiving water impact methodology.

This paper presents the final results of the application of a probabilistic approach for evaluating the water quality impact of highway stormwater runoff to receiving waters. A brief review of the development of the probabilistic characterization of runoff water quality data is presented along with a description of the probabilistic stream impact method. In this paper we present the interactive Decision Support program that takes the procedure user through the Federal Highway Administration's highway runoff analysis procedure. The procedure requires the input of fixed site data, rainfall and streamflow statistics, highway runoff water quality, and target concentrations. The methodology user is provided guidance in entering the required data. Output of the procedure is a return frequency of the exceedances of the target concentration. This methodology is intended for planning level analyses.

Environmental Monitoring↗
PubMed2025

Spatial transcriptomics-aided localization for single-cell transcriptomics with STALocator.

Single-cell RNA-sequencing (scRNA-seq) techniques can measure gene expression at single-cell resolution but lack spatial information. Spatial transcriptomics (ST) techniques simultaneously provide gene expression data and spatial information. However, the data quality of the spatial resolution or gene coverage is still much lower than the quality of the single-cell transcriptomics data. To this end, we develop a ST-Aided Locator for single-cell transcriptomics (STALocator) to localize single cells to corresponding ST data. Applications on simulated data showed that STALocator performed better than other localization methods. When applied to the human brain and squamous cell carcinoma data, STALocator could robustly reconstruct the relative spatial organization of critical cell populations. Moreover, STALocator could enhance gene expression patterns for Slide-seqV2 data and predict genome-wide gene expression data for fluorescence in situ hybridization (FISH) and Xenium data, leading to the identification of more spatially variable genes and more biologically relevant Gene Ontology (GO) terms compared with the raw data. A record of this paper's transparent peer review process is included in the supplemental information.

Single-Cell Analysis↗