PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “data quality”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16Linked to original sources
PubMed2004

Improving data quality in community-based seafood consumption studies by use of two measurement tools.

A seafood consumption study w as conducted in Glynn County, Georgia, to address concern about bioaccumulation of mercury from a nearby hazardous waste site in people who ate potentially contaminated seafood from this area. Seafood consumption levels were ascertained with two data collection tools: a questionnaire and a dietary diary. The use of two instruments allowed for more detailed analysis to reveal discrepancies in responses between the two instruments, to improve reliability of study results, and to reduce recall bias. Implementation of the questionnaire was relatively easy and provided a broad characterization of consumption patterns in the area. The dietary diary was more time-consuming, resulting in a reduction in participation rates. It provided, however, more detailed information with which to address community concerns about adverse health effects from mercury exposure. Overall, individuals who participated in this study were able to make broad generalizations about the amount of seafood in their diet but were less accurate in estimating specific seafood consumption levels. In addition, the level of concordance between the questionnaire and the dietary diary was low with respect to seafood consumption levels. For investigators examining consumption patterns in a community, the decision to use a questionnaire, a dietary diary, or both will be influenced by the objectives of the study, the level of community concern, the number of study staff, and available resources.

Adolescent↗
PubMed1996

Breast cancer in New Zealand: trends, patterns, and data quality.

AIMS: To determine if incidence of cancer of the female breast in New Zealand is changing by age, ethnic group, and geographic region, and if there are differences in rates for stage of tumour by urban and rural residence. METHODS: Age-adjusted incidence rates for Maori and nonMaori were computed from all primary cancers of the breast registered in the National Cancer Registry, 1978-92. Analyses of time trends and geographic variations were conducted using standard statistical methods. RESULTS: There were steady, but nonsignificant, increases in the Maori and nonMaori incidence rates between 1978-92 which represents important increases in case numbers. The age-specific rates increased sharply from age 20, levelled out at age 45 and slowly increased through 85 years and older. There was a significant trend over time for the rate of "not staged" cases which was due to an artifact. No statistically significant variations in the age-adjusted rates by area (14 area health board districts, 4 regional health authorities), or by stage of tumour in three urban-rural groups were found. Maori women showed less shift in incidence rates from regional to local stage of tumour than nonMaori. The proportion of tumours reported without stage increased in the period 1988-92. A large proportion of cases had nonspecific morphology codes. CONCLUSIONS: There are small differences between rates of breast cancer in rural and urban residences in New Zealand, as compared to some other countries. The quality of the Cancer Registry as a basis for evaluating the planned breast cancer screening programme is adversely affected by the high proportion of cases found with no reported stage of tumour. The proportion of nonspecific morphologies in these data is also of concern. The recent passing of the Cancer Registry Act should ensure better reporting of morphologies.

Adult↗
PubMed2005

The OutPatient Experiences Questionnaire (OPEQ): data quality, reliability, and validity in patients attending 52 Norwegian hospitals.

OBJECTIVE: To describe the development and evaluation of the OutPatient Experiences Questionnaire (OPEQ) for somatic outpatients. DESIGN: Literature review, patient interviews, pretesting of questionnaire items, and a cross sectional survey. SETTING: Postal survey of adult outpatient clinics at 52 hospitals in all five regions of Norway during 2003 and 2004. SUBJECTS: 35,719 patients who had attended an outpatient clinic within the previous 3 weeks. RESULTS: 19,266 patients (53.9%) responded to the questionnaire. Low levels of missing data suggest that the questionnaire is acceptable to patients. Factor analysis of items applicable to all patients produced three factors: clinic access (two items), communication (six items), and organisation (four items). The remaining items contributed to the hypothesised scales of hospital standards (three items), information (six items), and pre-visit communication (three items). With the exception of the pre-visit communication scale, the levels of Cronbach's alpha were >0.7. With the exception of the hospital standards scale, all produced test-retest correlations that exceeded 0.7. Most of the results of validity testing were as hypothesised. Correlations between the OPEQ scores ranged from 0.30 (clinic access and hospital standards) to 0.73 (communication and information). As hypothesised, scores were significantly related to patient responses to questions about overall satisfaction, general health and age. CONCLUSIONS: The OPEQ is a self-administered questionnaire that includes the most important aspects of patient experience from an outpatient perspective. It has good evidence for internal consistency, test-retest reliability, and validity.

Adolescent↗
PubMed2000

Evaluation of coding data quality of the HCUP National Inpatient Sample.

Quality ICD-9-CM coding depends on the selection of the appropriate diagnosis codes and the proper sequencing of the codes. A simple, diagnosis code-sequencing error was selected to evaluate the quality of diagnosis coding within the National Inpatient Sample of the Healthcare Costs and Utilization Project. The source of coding variation originates at the hospital level. Coding error rates were found to vary widely among states, hospitals within states, geographic location, and hospital characteristics. Coding errors were significantly different among patient demographic groups and whether the state used billing versus abstract data.

Abstracting and Indexing↗
PubMed2004

Comparison of spatial interpolation methods for the estimation of air quality data.

We recognized that many health outcomes are associated with air pollution, but in this project launched by the US EPA, the intent was to assess the role of exposure to ambient air pollutants as risk factors only for respiratory effects in children. The NHANES-III database is a valuable resource for assessing children's respiratory health and certain risk factors, but lacks monitoring data to estimate subjects' exposures to ambient air pollutants. Since the 1970s, EPA has regularly monitored levels of several ambient air pollutants across the country and these data may be used to estimate NHANES subject's exposure to ambient air pollutants. The first stage of the project eventually evolved into assessing different estimation methods before adopting the estimates to evaluate respiratory health. Specifically, this paper describes an effort using EPA's AIRS monitoring data to estimate ozone and PM10 levels at census block groups. We limited those block groups to counties visited by NHANES-III to make the project more manageable and apply four different interpolation methods to the monitoring data to derive air concentration levels. Then we examine method-specific differences in concentration levels and determine conditions under which different methods produce significantly different concentration values. We find that different interpolation methods do not produce dramatically different estimations in most parts of the US where monitor density was relatively low. However, in areas where monitor density was relatively high (i.e., California), we find substantial differences in exposure estimates across the interpolation methods. Our results offer some insights into terms of using the EPA monitoring data for the chosen spatial interpolation methods.

Air Pollutants↗
PubMed1996

Measurement and data quality in longitudinal research.

The importance of paying attention to scale levels is emphasized and it is pointed out that Steven's hierarchy of ratio, interval, ordinal, and nominal scales is too narrow; other important scale properties have to be considered. For instance, sometimes a carefully constructed variable on a nominal scale contains more information than a variable at a higher scale level. Direct versus indirect measurement and relative versus absolute measurement are also discussed and the effects of errors of measurement on the results are considered. It is not infrequent in a longitudinal setting to disregard sampling considerations, which can be very unfortunate. Such considerations, as well as the use of modern sampling theory, can considerably enhance the quality of a longitudinal study. Finally, a number of conclusions and recommendations are given for the carrying out of longitudinal research in relation to measurement issues.

Adolescent↗
PubMed2002

Data quality and the spatial analysis of disease rates: congenital malformations in New York State.

Spatial analyses of disease rates are increasing as the hardware and software used in disease surveillance and cluster investigations become more accessible and easier to use. The results of these analyses should be interpreted with caution since inconsistencies in health outcome reporting and population estimates may lead to erroneous conclusions. In this report we provide an example, using data on congenital malformations in New York State, to show how under-reporting of malformations by some New York City hospitals can lead to apparent clusters of malformations in other areas of the state where reporting is more complete. We illustrate how spatial analysis techniques can be used to locate under-reporting problems and determine the extent to which the problem exists.

Congenital Abnormalities↗
PubMed1994

Data quality of bedside monitoring in an intensive care unit.

Computerized record keeping promises complete, accurate and legible documentation. Reliable measurements are a prerequisite to fulfill these expectations. We analyzed the physiological variables provided by bedside monitoring devices in 657 bedside visits performed by an experienced Intensive Care nurse during 75 Intensive Care rounds. We registered which variables were displayed. If a variable was displayed, we assessed whether it could be used for documentation or should be rejected. If a value was rejected the reason was registered as: the measurement was not intended (superfluous display), the current clinical situation did not allow proper measurement, or other reasons. Basic variables (vital signs and respiration related variables) were displayed in more then 90%, specific variables (e.g. intracranial pressure) were displayed in less than 50% of the situations. Displayed variables were superfluous on an average of 11% because measurement was not intended. Variables like heart rate, temperature, airway pressure, minute volume of ventilation, arrhythmia, pulmonary arterial pressure, non-invasive blood pressure, and intracranial pressure provide high quality measured values (acceptance of more than 90%). Invasive arterial pressure, central venous pressure, respiration rate and oxygen saturation (via pulse oximetry) provided lower quality values with a rejection rate higher than 10%. Inappropriate sensor technology to match the clinical environment seems to be the root cause. In future the request for automatic documentation will increase. In order to avoid additional staff workload and to ensure reliable documentation, sensor technology especially related to respiration rate, blood pressure measurements, and pulse oximetry should be improved.

Data Collection↗
PubMed2004

Effect of environment and research participant characteristics on data quality.

The purpose of this study, a component of a randomized clinical trial, was to assess the influence of the emergency department environment and participant characteristics on the accuracy of self-reported health care utilization. Interviews of 612 seniors aged 65 to 93 were conducted in two emergency departments. The research assistant, upon completion of each interview, rated characteristics of the emergency department and compared participants' self-reports of emergency department use and hospitalization during the previous 4 weeks with data from hospital records: 3.6% overreported and 2.2% underreported visits to the emergency department. Regarding hospitalizations, 2.6% overreported and 1.2% underreported. Discrepancies were associated with male gender, cognitive deficits, and risk status. Inconsistencies were not related to any of the environmental variables. These findings suggest that seniors without cognitive decline report reliable data even in a potentially challenging environment.

Aged↗
PubMed1992

Improvements in data quality in the USRDS database: determining treatment modalities.

Past USRDS estimates of the prevalent ESRD population have exceeded the counts reported by the HCFA Annual Facility Surveys. One expects the USRDS estimates to be lower because the Facility Surveys include non-Medicare patients generally not in the USRDS database. The methodology for determining the treatment histories of patients has been modified to define lost to follow-up periods as periods of at least one year during which the patient has no dialysis data and does not have a functioning transplant. Patients are not counted as prevalent when they are in such a lost to follow-up period. This change brings the USRDS year end prevalent counts down to about 94 percent of the Facility Survey counts of total dialysis patients and slightly over the Facility Survey counts of Medicare dialysis patients. This change raises prevalent mortality rates by about seven percent over the rates reported in the 1991 USRDS Annual Data Report. We expect to make further refinements in this methodology.

Data Collection↗
PubMedDate not supplied

Assessing data quality of peptide mass spectra obtained by quadrupole ion trap mass spectrometry.

An algorithm is introduced to assess spectral quality for peptide CID spectra acquired by a quadrupole ion trap mass spectrometer. The method employs a quadratic discriminant function calibrated with manually classified 'bad' and 'good' quality spectra, producing a single 'spectral quality' score. Many spectra examined that do not have significant matches are assessed to have good spectral quality, indicating that advances in search methods may yield substantial improvements in results.

Amino Acid Sequence↗
PubMed2004

Small area population estimates project: data quality of administrative datasets.

The Office for National Statistics (ONS) has set up a project to investigate the feasibility of producing postcensal small area population estimates on a nationally consistent basis for England and Wales. Research has taken place to identify datasets that could potentially be used within a method to produce small area population estimates. Following an evaluation of a number of different administrative datasets, the most suitable have been short-listed for further consideration. This article presents the findings of the evaluation, based on 2001 data, and summarises the characteristics of these short-listed data sources. This article does not cover the methods that are being evaluated as part of the feasibility assessment.

Adolescent↗
PubMed1983

Data quality. An illustration of its potential impact upon a diagnosis-related group's case mix index and reimbursement.

The Health Care Finance Administration has developed a Medicare reimbursement methodology that will include an adjustment factor for hospital case mix. The patient classification scheme proposed for use in determining a hospital's case mix is the AUTOGRP Diagnosis-Related Groups (DRG) methodology developed at Yale University. The reliability of a case mix measure calculated using the DRG methodology is dependent on complete and accurate diagnostic and surgical data. The source of this data for the HCFA data base (MEDPAR) is the Medicare billing form, which is based on the patient medical record. Data from the MEDPAR file, the original medical record discharge order, and a reabstracted record are compared and analyzed for their effect upon DRG classification and the resultant Medicare reimbursement ceiling for one large teaching hospital. The study results show widely divergent diagnostic and surgical data that results in a significant variation in DRG classification and reimbursement ceilings.

Costs and Cost Analysis↗
PubMed1994

Umbilical cord blood gas analysis at delivery: a time for quality data.

OBJECTIVES: To address the practical problems of routine umbilical cord blood sampling, to determine the ranges for pH, PCO2 and base deficit and to examine the relationships of these parameters between cord vessels. DESIGN: An observational study of umbilical cord artery and vein blood gas results. SETTING: A large district general hospital in the UK. SUBJECTS: One thousand nine hundred and forty-two cord results from 2013 consecutive pregnancies of 34 weeks or more gestation, monitored by fetal scalp electrode during labour. RESULTS: Only 1448 (74.6%) of the 1942 supposedly paired samples had validated pH and PCO2 data both from an artery and the vein; 54 (2.8%) had only one blood sample available, 90 (4.6%) had an error in the pH or PCO2 of one vessel and in 350 (18%) pairs the differences between vessels indicated that they were not sampled from artery and vein as intended. Only 60% of the cases with an arterial pH less than 7.05 had evidence of a metabolic acidosis (base deficit in the extracellular fluid 10 mmol/l or more). Of all the cases, 2.5% had a venous-arterial pH difference greater than 0.22 units. CONCLUSIONS: Both artery and vein cord samples must be taken and the results screened to ensure separate vessels have been sampled. Interpretation of the results requires the examination of PCO2 and base deficit of the extracellular fluid from each vessel as well as the pH. Confusion about the value of cord gas measurements may be due to the use of erroneous data and inadequate definitions of acidosis which do not differentiate between respiratory and metabolic components.

Carbon Dioxide↗
PubMed1999

How OASIS data quality affects you!

In general, each of these methods require time and energy from staff members and therefore affect both clinicians and the home health agency. Because the assessor is usually a field nurse or therapist, field staff are very vulnerable to a top down audit approach unless staff are included in the development cycle to achieve a non-threatening quality improvement process. Furthermore, an understanding of the research concepts provides agencies with a creative opportunity to develop their own audit processes. In addition, these concepts offer an awareness as to why HCFA may have chosen the specific areas and methods they have recommended to use when identifying errors. HCFA encourages agencies to consider different methodologies and approaches and to use what works best in order to ensure data accuracy. This is one of the first times in which HCFA has given so much latitude to agencies and their staff. It is hoped that this article fosters interest and insight as to why field staff should actively become involved in audit processes that check their skills and accuracy, which directly correlates to such a huge impact on all involved. In order to improve reliability, an agency should try to minimize external sources of variation and standardize the conditions under which measurement occurs. Initial and ongoing training sessions for staff on each of the OASIS data elements can establish higher reliability and can be streamlined and targeted on areas that staff have the most questions and areas that audits indicate high error rates with data inaccuracies. It is important to remember that each OASIS question has been proven to be valid and reliable; therefore, the only variable left is the source, i.e., those who use the instrument to determine where data inaccuracies could be generated (the field assessor, data entry staff, vendor transmitters, etc.). Agencies should develop the audit functions that will best meet their needs, and minimize the workload for all involved in finding these data inaccuracies.

Centers for Medicare and Medicaid Services, U.S.↗
PubMed2003

Impact of differential response rates on the quality of data collected in the CTS physician survey.

Survey administrators face trade-offs between expending additional survey resources to maximize response rates versus using fewer resources and accepting lower response rates. Using data from the Community Tracking Study's Physician Survey, we examined how survey estimates and data quality changed as additional respondents completed the survey. Results showed that improvements in response rates over the range examined (i.e., up to 65%) did not change estimates appreciably nor affect data quality. As long as these results are not overstated to imply that extremely low response rates are credible, this study may permit researchers to disseminate interesting results in peer-reviewed journals even when the response rate falls slightly short of current standards. It must also be emphasized, however, that we were unable to measure the nonresponse effect of those who were never interviewed. Achieving a response rate significantly above 65% might have changed the survey results appreciably.

Data Collection↗
PubMed2000

SF-36 health survey: tests of data quality, scaling assumptions, and reliability in a community sample of Chinese Americans.

BACKGROUND: Chinese Americans are one of the fastest growing ethnic groups in the United States; however, language and cultural obstacles have challenged health workers and policy makers seeking to understand the health status and needs of this population. OBJECTIVES: This study is the first to use a large-scale probability design to evaluate the 36-item Short-Form Health Survey (SF-36) in a Chinese population (n = 1,501). METHODS: Using the International Quality of Life Assessment Project protocols, we examine summated-rating scaling assumptions, item-internal consistency, item-discriminant validity, and reliability. RESULTS: Similar to previous studies, our tests indicated that the SF-36 generally met minimum psychometric criteria with high reliability and satisfactory scaling success rates for most scales. However, the performance of the vitality and mental health scales was less satisfactory with regard to discriminant validity and scaling success rates. Notably, our results indicate that VT3 and VT4 ("feel worn out" and "tired", respectively) formed a separate "fatigue" cluster more highly correlated with the mental health scale. However, MH4 and MH5 ("downhearted and blue" [reverse coded] and "been a happy person") were more highly correlated with the vitality scale, suggesting that it may be more meaningful to reorganize the vitality and mental health items along the dimensions of well-being and distress. CONCLUSIONS: These results are interpreted within a cultural framework; however, additional work is needed to better understand the relationship between vitality and mental health for Chinese Americans.

Adolescent↗