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Results for “data quality”

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PubMed1997

Automating and improving the data quality of a nursing department quality management program at a university hospital.

BACKGROUND: The development and implementation of a relational database program for nursing quality management at a university hospital was stimulated by a lack of consistent data management and analysis tools in the existing noncomputerized program. PROGRAM DEVELOPMENT AND IMPLEMENTATION: An initial software prototype implemented in the critical care service included data collection instruments for five areas: medication errors, patient falls, returns to an intensive care unit within 48 hours, hospital-acquired skin breakdown, and unplanned extubations. Access to the database was limited and paper reports only were disseminated on a scheduled basis. In a second phase, the database is being deployed throughout the nursing department using a local area network. Nurse managers will enter and interact with the quality database online and have access to graphics, reports, and action plan development. POSSIBLE ERRORS: A wide range of potential errors influences decisions on how to collect, store, retrieve, and process quality management data. Each type of error affects the nurse manager's ability to identify significant patterns or trends that are amenable to intervention. There is no right way of constructing and implementing a quality improvement database; only an optimum balance between cost, complexity, and efficacy. SUMMARY AND CONCLUSIONS: Initial feedback from end uses has been positive. A three-year experience with a personal computer database suggests that the personal computer-based information technology is appropriate for small to medium applications and can support departmentwide CQI efforts. A case scenario using simulated data is included to illustrate the use of computerized reports in assessing and taking action on an increase in falls.

Accidental Falls↗
PubMed2006

Comparison of data quality for reports and ratings of ambulatory care by African American and White Medicare managed care enrollees.

OBJECTIVE: Compare missing data and reliability of health care evaluations between African Americans and Whites in Medicare managed care health plans. METHOD: Consumer Assessment of Healthcare Providers and Systems (CAHPS) 3.0 health plan survey data collected from 109,980 Medicare managed care enrollees (101,189 Whites, 8,791 African Americans) in 321 plans. Participants self-administered the survey and four single-item global ratings of care. RESULTS: Missing data rates were significantly higher for African Americans than Whites on all CAHPS items (p < .0001). Internal consistency reliability estimates for the CAHPS scales did not differ significantly between African Americans and Whites, but plan-level reliability estimates for the scales and global rating items were significantly lower for African Americans than Whites. DISCUSSION: Higher missing data rates and lower plan-level reliability estimates for African American Medicare managed care enrollees suggest caution in making race/ethnicity comparisons. Future efforts are needed to enhance the quality of data collected from older African Americans.

Adult↗
PubMed1993

Markers of data quality in computer audit: the Manchester Orthopaedic Database.

This study investigates the efficiency of the Manchester Orthopaedic Database (MOD), a computer software package for record collection and audit. Data is entered into the system in the form of diagnostic, operative and complication keywords. We have calculated the completeness, accuracy and quality (completeness x accuracy) of keyword data in the MOD in two departments of orthopaedics (Departments A and B). In each department, 100 sets of inpatient notes were reviewed. Department B obtained results which were significantly better than those in A at the 5% level. We attribute this to the presence of a systems coordinator to motivate and organise the team for audit. Senior and junior staff did not differ significantly with respect to completeness, accuracy and quality measures, but locum junior staff recorded data with a quality of 0%. Statistically, the biggest difference between the departments was the quality of operation keywords. Sample sizes were too small to permit effective statistical comparisons between the quality of complication keywords. In both departments, however, the poorest quality data was seen in complication keywords. The low complication keyword completeness contributed to this; on average, the true complication rate (39%) was twice the recorded complication rate (17%). In the recent Royal College of Surgeons of England Confidential Comparative Audit, the recorded complication rate was 4.7%. In the light of the above findings, we suggest that the true complication rate of the RCS CCA should approach 9%.

Data Collection↗
PubMed2000

[Longitudinal research in aging populations: participation and the quality of data collected with questionnaires].

In this article methods are discussed which may keep participation in a longitudinal study among elderly persons high, for example adaptation of the interviews and proxy interviews. The LASA sample is described from the start in 1992 until now. The non-response is evaluated and we found that refusals are particularly important in the first part of the longitudinal traject. Also data quality is studied in relation to the aging of the respondents. Although there are theoretical reasons to expect that aging may impair data quality, no support for this hypothesis was found in the present study. Data quality was stable during a period of six years. But data quality seemed poorer for those respondents who dropped out from the study. Item non-response and duration of the interview were higher for drop-outs.

Age Factors↗
PubMed2004

On the influence of training data quality in k-t BLAST reconstruction.

This work investigated how the quality of prior information (i.e., data acquired during the training stage) influences k-t BLAST reconstruction. The impact of several factors, such as the amount of training data, the presence of spatial misregistration in the training data, and the effects of filtering, was investigated with simulations and in vivo data. It is shown that k-t BLAST outperforms sliding window reconstruction, even with very limited training data. By increasing the amount of training data, reconstruction error continues to decrease, albeit by a diminishing amount. However, an increased amount of training data also increases susceptibility to misregistration of the training data. Filtering of the training data with the goal of reducing truncation artifacts had only minor impact on reconstruction errors. Considering the balance among obtaining the most benefit from the training data, minimizing susceptibility to misregistration, and keeping data acquisition to a minimum, it is concluded that in cardiac imaging the training datasets should be limited to 10-20 profiles in k-space for a typical field of view. The training data may be acquired in a separate breathhold without much penalty, if care is taken to minimize misregistration, such as with a navigator.

Adult↗
PubMed1999

Cross-cultural research: trying to do it better. 2. Enhancing data quality.

OBJECTIVE: To describe the dilemmas for cross-cultural research in translating study instruments and implementing quality assurance methods, drawing on strategies utilised in the Mothers in a New Country (MINC) Study. METHOD: To translation of study instruments in the MINC Study included: forward and back translations, a bilingual group review process, consultation with bilingual content experts, piloting of different versions of translations, a process for exploring unresolved difficulties and caution in interpreting unusual study findings. Interview quality was assessed by: 1. An ongoing review of interviewer-prepared English coding schedules to ensure completeness of data and identify problems with interview administration. 2. Analysis of fully translated transcripts of six randomly selected early interviews to assess the accuracy and consistency with which questions were asked. 3. A comparison of data sources for 45 randomly selected interviews (original language interview schedules, English coding schedules and translated interview transcripts) to determine the rate and nature of discrepancies. RESULTS: Translation strategies that went beyond simple forward and back translations achieved more reliable and appropriate translations. The complexity of language and cultural differences sometimes still meant less than satisfactory results. Interview tapes played an important quality assurance role, enabling feedback to the interviewers and providing a basis of comparison for identification of data discrepancies. IMPLICATIONS: Ensuring good data quality in cross-cultural research is both critically important and difficult. Open discussion of the problems and concerted efforts to deal with them would benefit future research.

Attitude to Health↗
PubMed1996

Declining induced abortion rate in Finland: data quality of the Finnish abortion register.

BACKGROUND: Induced abortion rates have declined in Finland since 1973. A possible explanation offered has been that of deteriorating data collection. METHODS: To assess the completeness of the Register, we compared the information from a consecutive sample of hospital records (N = 482) to the Finnish Abortion Register in 18 hospitals in three counties. A smaller consecutive sample (N = 345) was collected from the same hospitals to assess the validity of the Register information. RESULTS: Only five abortions (1 percent) found in the hospitals were not reported in the Abortion Register. A total of 95 percent of all the length of pregnancy (definition problems), the classification of the abortion procedure, and social class (out-of-date classifications). Furthermore, early complications were poorly reported. CONCLUSIONS: The data from the Finnish Abortion Register are a reliable source for monitoring trends in the abortion rate and its variation by subgroups, but are an unreliable source for the study of the medical aspects of induced abortion.

Abortion, Induced↗
PubMed1999

The monitoring of racial/ethnic status in the USA: data quality issues.

This paper reviews the assessment of racial and ethnic identification in the major data collection systems of the US Department of Health and Human Services. It evaluates the quality of the available data and outlines recommendations for improving the collection of racial data and enhancing our understanding of the role of race in health. Special attention is also given to the role of socioeceonomic status in understanding racial differences in health and the assessment of racial status in data systems in the UK.

Data Collection↗
PubMed2003

Identification of land use with water quality data in stormwater using a neural network.

To control stormwater pollution effectively, development of innovative, land-use-related control strategies will be required. An approach that could differentiate land-use types from stormwater quality would be the first step to solving this problem. We propose a neural network approach to examine the relationship between stormwater water quality and various types of land use. The neural network model can be used to identify land-use types for future known and unknown cases. The neural model uses a Bayesian network and has 10 water quality input variables, four neurons in the hidden layer, and five land-use target variables (commercial, industrial, residential, transportation, and vacant). We obtained 92.3 percent of correct classification and 0.157 root-mean-squared error on test files. Based on the neural model, simulations were performed to predict the land-use type of a known data set, which was not used when developing the model. The simulation accurately described the behavior of the new data set. This study demonstrates that a neural network can be effectively used to produce land-use type classification with water quality data.

Agriculture↗
PubMed2005

Scaling and assessment of data quality.

The various physical factors affecting measured diffraction intensities are discussed, as are the scaling models which may be used to put the data on a consistent scale. After scaling, the intensities can be analysed to set the real resolution of the data set, to detect bad regions (e.g. bad images), to analyse radiation damage and to assess the overall quality of the data set. The significance of any anomalous signal may be assessed by probability and correlation analysis. The algorithms used by the CCP4 scaling program SCALA are described. A requirement for the scaling and merging of intensities is knowledge of the Laue group and point-group symmetries: the possible symmetry of the diffraction pattern may be determined from scores such as correlation coefficients between observations which might be symmetry-related. These scoring functions are implemented in a new program POINTLESS.

Algorithms↗
PubMed2003

An empirical exploration of data quality in DNA-based population inventories.

I present data from 21 population inventory studies - 20 of them on bears - that relied on the noninvasive collection of hair, and review the methods that were used to prevent genetic errors in these studies. These methods were designed to simultaneously minimize errors (which can bias estimates of abundance) and per-sample analysis effort (which can reduce the precision of estimates by limiting sample size). A variety of approaches were used to probe the reliability of the empirical data, producing a mean, per-study estimate of no more than one undetected error in either direction (too few or too many individuals identified in the laboratory). For the type of samples considered here (plucked hair samples), the gain or loss of individuals in the laboratory can be reduced to a level that is inconsequential relative to the more universal sources of bias and imprecision that can affect mark-recapture studies, assuming that marker systems are selected according to stated guidelines, marginal samples are excluded at an early stage, similar pairs of genotypes are scrutinized, and laboratory work is performed with skill and care.

Animals↗
PubMed1991

Case finding, data quality aspects and comparability of myocardial infarction registers: results of a south German register study.

The population-based Augsburg Coronary Event Register (330,000 residents, age 25-74 years) has registered a total of 1012 cases of acute myocardial infarction (AMI) in 1985 and 1021 AMI in 1986 and categorized them on the basis of the current WHO diagnostic algorithm for AMI. The register is designed for longitudinal comparisons of annual AMI risk (incidence, attack rate, death rate), and the risk to the AMI patients themselves (28-day case fatality). The methodology and specific issues encountered during registration and data evaluation are described. With an estimated 95% completeness of case finding, the quality control data review which the register conducts annually shows a consistency of specific data structures which indicate stable case finding and validation procedures. However, local conditions which affect case finding and data completeness per case are responsible for the creation of subsets of AMI which are in turn distinguished by differences in diagnostic category structures. With regard to the study objectives, the differences among subsets appear to have the least effect on rate calculations if DEFINITE and POSSIBLE AMI are combined. The implications of methodological variations and subset differences within and across registers on annual rate calculations and result comparisons are discussed.

Adult↗
PubMed2000

A summary of river water quality data collected within the Land-Ocean Interaction Study: core data for eastern UK rivers draining to the North Sea

A numerical summary of the water quality of rivers draining into the North Sea from the eastern UK is presented using core information collected within the Land-Ocean Interaction Study (LOIS) and a companion study by the Institute of Hydrology. The analysis is based on weekly monitoring for periods from 1993 to 1999 for major, minor, nutrient, trace and other water quality determinand chemistry. The data cover rivers ranging from the rural Tweed in southeastern Scotland, to the urban and industrially impacted Wear and Humber rivers in the north and central England and two agriculturally impacted rivers in the south of England (Great Ouse and Thames). Within the analysis, monthly averaged concentrations are plotted to show the seasonality. The summary provides specific information on the water quality of UK rivers which is of use in developing European and global initiatives for assessing pollutant inputs to estuarine, coastal and open-sea environments.

Journal Article↗
PubMed2001

A reappraisal of saprobic values and indicator weights based on Slovenian river quality data.

The saprobic values and indicator weights used in the Slovenian saprobic system are reappraised using data from the 1990 to 95 river quality surveys of Slovenia. The conceptual basis of the reappraisal is described and then formulated mathematically. The analysis is based on 1,106 biological samples and covers 300 taxa. The results are expressed in terms of revised saprobic values and indicator weights that mirror the ones previously assigned by ecological experts. The most significant differences between original and revised values are highlighted and discussed. It is concluded that: (a) the revised values and weights are more representative of their 'true' values than are the original values and weights, but that it would be premature to consider them definitive; (b) the analytical method provides a sound data-based approach to the revision of saprobic values and indicator weights; and (c) the method could help to improve and harmonise the various saprobic systems currently in use across Europe.

Calibration↗