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At least 19 recordsLinked to original sources
PubMed1998

The Genome Sequence DataBase (GSDB): improving data quality and data access.

In 1997 the primary focus of the Genome Sequence DataBase (GSDB; www. ncgr.org/gsdb ) located at the National Center for Genome Resources was to improve data quality and accessibility. Efforts to increase the quality of data within the database included two major projects; one to identify and remove all vector contamination from sequences in the database and one to create premier sequence sets (including both alignments and discontiguous sequences). Data accessibility was improved during the course of the last year in several ways. First, a graphical database sequence viewer was made available to researchers. Second, an update process was implemented for the web-based query tool, Maestro. Third, a web-based tool, Excerpt, was developed to retrieve selected regions of any sequence in the database. And lastly, a GSDB flatfile that contains annotation unique to GSDB (e.g., sequence analysis and alignment data) was developed. Additionally, the GSDB web site provides a tool for the detection of matrix attachment regions (MARs), which can be used to identify regions of high coding potential. The ultimate goal of this work is to make GSDB a more useful resource for genomic comparison studies and gene level studies by improving data quality and by providing data access capabilities that are consistent with the needs of both types of studies.

Base Sequence↗
PubMed1995

Data quality assurance, monitoring, and reporting.

In conclusion, the quality assurance and monitoring program is an integral and continuing part of study operations. A system must be devised and implemented by the coordinating center investigators, with the endorsement of the study leadership and support of the field site and resource center personnel. Proactive mechanisms for promoting high-quality data acquisition and reporting must be implemented. Data quality monitoring must address the entire process by which the data are gathered, transmitted, stored, and analyzed. Data quality should be monitored continually, with summary reports prepared and distributed to the study leadership. Appropriate training and certification enhance data quality, and site visits allow data collection and storage processes to be observed directly. The quality assurance and monitoring system must be documented. It should be flexible enough so that new means of quality assurance or monitoring can be added when necessary during the course of the study. At the completion of the study, quality monitoring results should be summarized in a final report regarding the level of quality achieved by the study investigators and personnel. Finally, for a quality assurance and monitoring program to be successful, the coordinating center investigators and personnel must provide prompt feedback and suggestions for corrective action whenever a data quality problem is discovered. This need can be met only when the coordinating center staff understand data quality goals and are up to date with all phases of data management and reporting. Delays in initiating any stage of data management and quality monitoring may result in uncorrectable data problems. Thus, knowledgeable and efficient coordinating center personnel are essential to achieving good data quality studywide.

Clinical Trials as Topic↗
PubMed1996

Extreme longevity in five countries: presentation of trends with special attention to issues of data quality.

"Data on the maximum age at death and other indicators of extreme longevity are assembled for five countries (Sweden, England & Wales, France, Japan, and the United States) over various time periods. The raw data are shown in both graphical and tabular formats. Two types of measures are presented: the extreme ages at death reported for a given year (i.e., the maximum, second, third, and fourth highest), and the upper percentiles of the age distribution of deaths by year. The analysis demonstrates that the upper tail of the age distribution of deaths has moved steadily higher over a period of at least 130 years in Sweden. Similar trends are observed (over shorter time periods) for other countries, although in many cases it is argued that the raw data are flawed due to misstatement (in particular, exaggeration) of age at death." (SUMMARY IN FRE)

Americas↗
PubMed2005

Assessing immunization data quality from routine reports in Mozambique.

BACKGROUND: Worldwide immunization coverage shows an increase in the past years but the validity of the official reports for measuring change over time has been questioned. Facing this problem, donor supported initiatives like the Global Alliance for Vaccine and Immunizations, have been putting a lot of effort into assessing the quality of data used, since accurate immunization information is essential for the Expanded Program on Immunization managers to track and improve program performance. The present article, discusses the practices on record keeping, reporting and the support mechanism to ensure data quality in Mozambique. METHODS: A process evaluation study was carried out in Mozambique in one district (Cuamba) in Niassa Province, between January and March 2003. The study was based on semi-structured interviews, participant observation and review of the data collection materials. RESULTS: Differences were found for all vaccine types when comparing facility reports with the tally sheets. The same applies when comparing facility reports with district reports. The study also showed that a routine practice during supervision visits was data quality assessment for the outpatient services but none related to data consistency between the tally sheets and the facility report. For the Expanded Program on Immunization, supervisors concentrated more on the consistency checks between data in the facility reports and the number of vaccines received during the same period. Meetings were based on criticism, for example, why health workers did not reach the target. Nothing in terms of data quality was addressed nor validation rules. CONCLUSION: In this paper we have argued that the quality of data, and consequently of the information system, must be seen in a broader perspective not focusing only on technicalities (data collection tools and the reporting system) but also on support mechanisms. Implications of a poor data quality system will be reflected in the efficiency of health services facing increased demands, with stagnant or decreasing resources.

Child↗
PubMed2001

Non-invasive methods for measuring data quality in general practice.

AIM: To develop non-invasive methods of measuring the quality of data recorded in general practice. METHODS: Laboratory and pharmaceutical claims data from fourteen practices (44 doctors) from the FirstHealth network of general practices were examined to determine the extent to which valid minimum bounds on expected rates of diagnosis coding could be established. These were compared with recorded rates in patient notes to measure completeness of diagnosis recording. Data completeness was measured for demographic data and a marker for the accuracy of gender coding was developed from diagnosis data. RESULTS: Minimum rates of diagnosis could be established for asthma, diabetes (NIDDM and IDDM), ischaemic heart disease, hypothyroidism, bipolar affective disorder and Parkinson's disease. Minimum bounds for the number of patients requiring monitoring of warfarin and digoxin levels were also established. These expected minimum rates were combined with measures of completeness of age, gender, ethnicity and smoking data, and a gender coding accuracy measure, to produce a set of fourteen data quality indicators. Pass/fail thresholds on each indicator were set and each of the fourteen practices was scored on the number of passes they achieved. The scores ranged from three to nine out of fourteen passses. CONCLUSIONS: Non-invasive data quality measures may be useful in providing feedback to general practitioners as part of a data quality improvement cycle. The sensitivity of this method will decline as data quality improves.

Data Collection↗
PubMed1980

Pathology data quality assurance and data retrieval at the National Center for Toxicological Research.

Automated experimental and pathology data collection and reporting systems are utilized at the National Center for Toxicological Research to increase the efficiency of the variety of research studies being performed. In order for the ED01 study to be conducted in an effective manner, usage of these automated systems was considered advantageous due to the study size, approximately 24,000 mice. The large volume of pathology and other experiment data generated in the study required detailed quality assurance and data retrieval, and the use of automated systems allowed this to be performed much more easily than with manual methods. This paper addresses the methods employed to ensure quality and to provide the data retrieval capabilities necessary for conducting and analyzing the ED01 study.

Government Agencies↗
PubMed2004

An eight-step method for assessing diagnostic data quality in practice: chronic obstructive pulmonary disease as an exemplar.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is an important cause of mortality and morbidity. Its management is shifting from the secondary to the primary care setting. The quality of data is known to vary between practices, and individual practices need to be able to assess their data quality. OBJECTIVES: To measure the quality of diagnostic data in COPD. SUBJECTS: 10 975 patients registered with a computerised general practice in the south of England, and 190 patients likely to have COPD. METHODS: An eight-step method was developed: (1) research the expected prevalence of the diagnosis and define audit criteria; (2) find out how the diagnosis might be coded--look at the terminology and the codes presented by the computer interface; (3) examine the characteristics of the practice population; (4) calculate the prevalence and infer its reliability; (5) investigate the completeness; (6) accuracy; (7) currency and consistency; and (8) calculate sensitivity and positive predictive value of the data. RESULTS: The prevalence of COPD in the literature ranges between 3% and 10%. The coding for bronchitis and COPD is complex and it is easy to select an incorrect code. The test population is younger but of similar social class to the national average. The prevalence of COPD in this study was 1.3%. The data were incomplete and some were inaccurate; patients with COPD had to be identified from additional searches. The sensitivity of the use of the diagnostic code was 79%, and the positive predictive value 75.3%. CONCLUSIONS: The method provides a tool to help practices and localities assess their diagnostic data quality.

Adolescent↗
PubMed2000

Effect of discharge letter-linked diagnosis registration on data quality.

OBJECTIVE: Diagnostic data are essential for the assessment of medical practice: they are needed for retrieval of clinical cases and describing co-morbidity and complications. In most Western countries, diagnosis registration in hospital information systems is based mainly on completing forms after patient discharge. As this registration plays no role in patient care, data quality is usually unsatisfactory. To improve data quality, we redesigned the process of diagnosis registration at a paediatric department, and now paediatricians provide diagnoses with codes in a separate registration heading of the discharge letter. We compared the quality of this discharge letter-linked diagnosis registration with the quality of the previous form based registration. DESIGN: Retrospective study with blinded before and after measurement. Re-abstracted diagnosis descriptions of the text of discharge letters were taken as gold standard. SETTING: A paediatric department in an academic medical centre. STUDY PARTICIPANTS: From each registration period, 60 admissions were selected randomly. Mean age of the patients was 4.5 (SD +/- 5.5) and 5.2 (SD +/- 5.2) years for the old and new situation respectively. Mean length of stay was 8.8 (SD +/- 11.0) and 7.2 (SD +/- 12.4) days. INTERVENTION: Discharge letter-linked diagnosis registration. MAIN OUTCOME MEASURES: Completeness and accuracy, both at three-digit level of ICD-9-CM. RESULTS: Completeness of form-based diagnosis registration was 51% (95% CI, 44-58%) and of discharge letter-linked diagnosis registration 54% (95% CI, 47-60%). Accuracy was 65% (95% CI, 58-72%) and 67% (95% CI, 60-74%) respectively. CONCLUSIONS: The discharge letter-linked diagnosis registration does not provide a better basis for assessment of medical practice than the form based diagnosis registration.

Abstracting and Indexing↗
PubMedDate not supplied

Reversal of the decline in breastfeeding in Peninsular Malaysia? Ethnic and educational differentials and data quality issues.

Data from the First and Second Malaysian Family Life Surveys in 1976 and 1988, respectively, are analyzed to examine long-term trends in breastfeeding in Peninsular Malaysia, educational and ethnic differences therein, and the quality of retrospective data on infant feeding. The steady decrease between the mid-1950's and mid-1970's in breastfeeding was reversed to become a nearly monotonic increase since 1975. Part of the change is attributable to the changing composition of the Malaysian population. Over time, the percentages of births to subgroups with higher rates of breastfeeding--particularly Malays and more highly educated women--have increased. However, there is also evidence of changes in rates of breastfeeding within these subgroups. Many Malaysian infants have a total duration of breastfeeding (including with supplementation) considerably shorter than WHO's recommended four months of exclusive (unsupplemented) breastfeeding. Moreover, nearly all breastfed infants are first given supplementary food or beverage shortly after birth. Breastfeeding promotion efforts in Malaysia need to emphasize the appropriate timing of and types of supplementary feeding.

Adolescent↗
PubMedDate not supplied

Defining and improving data quality in medical registries: a literature review, case study, and generic framework.

Over the past years the number of medical registries has increased sharply. Their value strongly depends on the quality of the data contained in the registry. To optimize data quality, special procedures have to be followed. A literature review and a case study of data quality formed the basis for the development of a framework of procedures for data quality assurance in medical registries. Procedures in the framework have been divided into procedures for the co-ordinating center of the registry (central) and procedures for the centers where the data are collected (local). These central and local procedures are further subdivided into (a) the prevention of insufficient data quality, (b) the detection of imperfect data and their causes, and (c) actions to be taken / corrections. The framework can be used to set up a new registry or to identify procedures in existing registries that need adjustment to improve data quality.

Critical Care↗
PubMed1989

Monitoring data quality through comparisons between data systems.

Since its creation in 1960, the National Center for Health Statistics (NCHS) has placed a high value on the quality of the information and statistics collected and published by its data systems. An important component of a comprehensive data quality monitoring system for a statistical agency such as NCHS is the comparison of statistics between data systems. Between-data-systems comparisons are used to monitor the consistency and comparability of statistics across data systems and between NCHS data systems and outside sources of data. This paper focuses on between-data-systems comparisons and describes a number of methodological analyses that can be used to evaluate data quality. The methodological analyses presented include the evaluation of time trends, the estimation of survey method effects, the evaluation of response error, the measurement of definitional and concept effects, and the detection of inconsistencies between data systems. The paper concludes with a discussion of the complexities of the between-data-systems comparisons and an assessment of the net benefits from such comparisons.

Data Collection↗
PubMed2003

Effects of atmospheric ozone on microarray data quality.

A data anomaly was observed that affected the uniformity and reproducibility of fluorescent signal across DNA microarrays. Results from experimental sets designed to identify potential causes (from microarray production to array scanning) indicated that the anomaly was linked to a batch process; further work allowed us to localize the effect to the posthybridization array stringency washes. Ozone levels were monitored and highly correlated with the batch effect. Controlled exposures of microarrays to ozone confirmed this factor as the root cause, and we present data that show susceptibility of a class of cyanine dyes (e.g., Cy5, Alexa 647) to ozone levels as low as 5-10 ppb for periods as short as 10-30 s. Other cyanine dyes (e.g., Cy3, Alexa 555) were not significantly affected until higher ozone levels (> 100 ppb). To address this environmental effect, laboratory ozone levels should be kept below 2 ppb (e.g., with filters in HVAC) to achieve high quality microarray data.

Artifacts↗
PubMed2006

The effect of data quality at the time of introduction of population-based screening on the estimate of programme impact using surrogate outcome measures.

OBJECTIVE: The aim of this study was to examine the availability and quality of surrogate outcome measure data to enable the evaluation of the breast screening programme. As the observed effect on mortality of a screening programme occurs many years after the introduction of screening, surrogate outcome measures offer an attractive alternative, allowing estimates of the effect to be calculated earlier. METHODS: The exercise was undertaken by the Oxford Cancer Intelligence Unit and the Cancer Screening Evaluation Unit in collaboration with cancer registries in England, Scotland and Wales. RESULTS: The conclusion of the exercise was that, in general, the available data quality was insufficient to allow a precise estimate of the overall mortality reduction from breast screening to be made using surrogate measures. CONCLUSIONS: When a screening programme is started, it is vital that forward planning is undertaken to ensure that the necessary information is ready to be collected before the start of the programme. The use of surrogate measures is dependent on high-quality data in the uninvited group of women (pre-screening or from a staggered start over areas), and improving data quality over time after the start of the programme is of very limited value for a surrogate measures approach. The collection of appropriate high-quality information before the programme starts is, therefore, critical to measuring the success of the programme. Cancer registries and staff within the screening programme need to be ready to collect the appropriate data before the introduction of a screening programme. The exercise undertaken therefore has important implications where new screening programmes are being considered.

Breast Neoplasms↗