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At least 73 records · Page 4Linked to original sources
PubMed1994

Data quality in computerized patient records. Analysis of a haematology biopsy report database.

This paper addresses the problem of data quality in electronic patient records using a computerized haematology biopsy report system as an example. Physicians extracted five parameters from a traditional free text cytology report and encoded these parameters thus producing a computer processable report. The parameters were 1) the organ biopsied, 2) quality of specimen, 3) cytological diagnosis including 4) a modifier code for the main diagnosis code (i.e. status post chemotherapy, Y-code) and 5) an additional key describing the degree of remission obtained after chemotherapy of acute leukemias. From the various steps involved in generating the electronic record we selected two critical ones: encoding of free text terms by physician staff; entering of the coded terms into a computer by lab staff. We analyzed the rates of correct, incorrect and missing codes for each of the five parameters. Our findings indicate that in this model of an electronic patient record: 1) there is significant inaccuracy of physicians during the process of encoding the free text report with error rates between 3.2 and 28% and omission rates up to 64%. 2) lab staff entering these coded data into the computer introduce additional errors (0-7.8%) but rarely miss correctly encoded data (0-0.9%). 3) introducing a revised coding system data quality improved significantly (p < or = 0.001) with a fivefold increase of correct and a 75% reduction of missing codes. 4) the clinical relevance of the diagnoses encoded as perceived by clinicians is a significant factor affecting error and omission rates.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗
PubMedDate not supplied

From figures to facts: data quality managers emerge as knowledge leaders.

It is no surprise that data quality managers are being recognized as knowledge leaders--they turn patient care data into valuable information for research, quality reviews, and planning. This article explores how this position is emerging in the HIM field and becoming a key player in quality care.

Benchmarking↗
PubMed2004

Data quality management in pharmacovigilance.

Pharmacovigilance relies on information gathered from the collection of individual case safety reports and other pharmacoepidemiological data. Even given the inherent limitations of spontaneous reports, the usefulness of this data source can be improved with good data quality management. Although under-reporting cannot be remedied this way, the negative impact of incomplete reports, which is another serious problem in pharmacovigilance, can be reduced. Quality management consists of quality planning, quality control, quality assurance and quality improvements. The pharmacovigilance data processing cycle starts with data collection and, in computerised systems, data entry; the next step is data storage and maintenance; followed by data selection, retrieval and manipulation. The resulting data output is analysed and assessed. Finally, conclusions are drawn and decisions made. The increased knowledge feeds back into the data processing cycle. Focussing on the first three steps of the data processing cycle, the different quality dimensions associated with these steps are described in this review, together with examples relevant to pharmacovigilance data. Functioning, well documented, and transparent quality management systems will benefit not only those involved in data collection, management and output production, but, ultimately, also the pharmacovigilance end users, the patients.

Adverse Drug Reaction Reporting Systems↗
PubMed1998

Study finds purchasers aren't using providers' outcomes data, quality report cards.

Are your data collection efforts for naught? A recent study shows that employers and purchasers overlook provider outcomes data and quality report cards when choosing health plans and providers--opting instead for customer satisfaction, HEDIS, and cost data. Here are the details on the study, plus advice from one of the study's authors.

Consumer Behavior↗
PubMed1991

The time interval between death and next-of-kin contact and its effects on response rates and data quality.

The relation of the interval of time between death and next-of-kin contact to outcome variables including response rates and data quality was examined in a nationally representative sample of 17,713 deaths of persons 25 years of age or older that occurred in the United States in 1986. For most of the outcome variables examined, the length of time had little effect, although there was a small decrease in the response rate and a small increase in the refusal rate for contact 40 or more weeks after death. The small decrease in the response rate and small increase in the refusal rate for the longest interval examined held for most decedent background characteristics examined (age, race, cause of death, and type of informant.) Authorizations to contact health care facilities signed by the respondents decreased slightly as the interval increased. The rate of returned mailed questionnaires passing quality and consistency edits increased slightly with time since death. Substantive responses (versus blanks, don't knows, etc.) decreased as time since death increased. Certain questions such as those on income and birth control pill use showed a decrease in response with time since death. Overall, the effects of longer time intervals between death and next-of-kin contact were less than expected on response rates and data quality, although our findings may reflect the high overall response rate, 90.5%, leaving little opportunity for significant areas of nonresponse.

Adult↗
PubMedDate not supplied

Building data quality into clinical trials.

Meaningful data begin with the collection process. Pharmaceutical companies are using several different strategies in clinical trials to ensure the highest quality of data. This article will examine these approaches, with an emphasis on case report form development through database release.

Abstracting and Indexing↗
PubMed2004

Data quality aspects of a database for abdominal septic shock patients.

Since many years, medical researchers have investigated the mechanisms that may cause a septic shock. Despite many approaches that analyzed smaller parts of the relevant data or single variables, respectively, no larger database with all the possible relevant data existed. Our work was to bridge this gap. We built a large database for abdominal septic shock patients. While building it, we were confronted with many problems concerning the database realization and the data quality. Thus, we will demonstrate how we built our database and how we assured data quality. This is of interest for all medical or computer scientists who are concerned with building medical databases with retrospective data, e.g. for data mining purposes.

Abdomen↗
PubMed2001

Is shorter always better? Relative importance of questionnaire length and cognitive ease on response rates and data quality for two dietary questionnaires.

In this study, the authors sought to determine the effects of length and clarity on response rates and data quality for two food frequency questionnaires (FFQs): the newly developed 36-page Diet History Questionnaire (DHQ), designed to be cognitively easier for respondents, and a 16-page FFQ developed earlier for the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. The PLCO Trial is a 23-year randomized controlled clinical trial begun in 1992. The sample for this substudy, which was conducted from January to April of 1998, consisted of 900 control and 450 screened PLCO participants aged 55-74 years. Controls received either the DHQ or the PLCO FFQ by mail. Screenees, who had previously completed the PLCO FFQ at baseline, were administered the DHQ. Among controls, the response rate for both FFQs was 82%. Average amounts of time needed by controls to complete the DHQ and the PLCO FFQ were 68 minutes and 39 minutes, respectively. Percentages of missing or uninterpretable responses were similar between instruments for questions on frequency of intake but were approximately 3 and 9 percentage points lower (p < or = 0.001) in the DHQ for questions on portion size and use of vitamin/mineral supplements, respectively. Among screenees, response rates for the DHQ and the PLCO FFQ were 84% and 89%, respectively, and analyses of questions on portion size and supplement use showed few differences. These data indicated that the shorter FFQ was not better from the perspective of response rate and data quality, and that clarity and ease of administration may compensate for questionnaire length.

Aged↗
PubMed1997

Data quality of administratively collected hospital discharge data for liver cirrhosis epidemiology.

We estimated the validity, i.e., whether the diagnostic criteria were fulfilled for the patients registered with the diagnosis of liver cirrhosis in a Danish hospital discharge registry, and the completeness, i.e., whether all patients with liver cirrhosis were included in the registry. Information in the regional hospital discharge registry in the Country of Aarhus, Denmark was compared with hospital records and information in a pathology registry. 85.4% of the patients registered with a diagnosis of liver cirrhosis fulfilled the diagnostic criteria for the diagnosis (validity). 93.2% of the patients registered with biopsy proven liver cirrhosis in the pathology registry were found in the discharge registry (completeness) with a diagnosis of liver cirrhosis. The hospital discharge registry showed relatively few misclassifications and the Danish National Registry of Patients (NRP), which is based on the regional registries, may provide a unique study base for future research.

Biopsy↗
PubMed1998

The Primary Care Assessment Survey: tests of data quality and measurement performance.

OBJECTIVES: The authors examine the data quality and measurement performance of the Primary Care Assessment Survey (PCAS), a patient-completed questionnaire that operationalizes formal definitions of primary care, including the definition recently proposed by the Institute of Medicine Committee on the Future of Primary Care. METHODS: The PCAS measures seven domains of care through 11 summary scales: accessibility (organizational, financial), continuity (longitudinal, visit-based), comprehensiveness (contextual knowledge of patient, preventive counseling), integration, clinical interaction (clinician-patient communication, thoroughness of physical examinations), interpersonal treatment, and trust. Data from a study of Massachusetts state employees (n = 6094) were used to evaluate key measurement properties of the 11 PCAS scales. Analyses were performed on the combined population and for each of the 16 subgroups defined according to sociodemographic and health characteristics. RESULTS: The 11 PCAS scales demonstrated consistently strong measurement characteristics across all subgroups of this adult population. Tests of scaling assumptions for summated rating scales were well satisfied by all Likert-scaled measures. Assessment of data completeness, scale score dispersion characteristics, and inter-scale correlations provide strong evidence for the soundness of all scales, and for the value of separately measuring and interpreting these concepts. CONCLUSIONS: With public and private sector policies increasingly emphasizing the importance of primary care, the need for tools to evaluate and improve primary care performance is clear. The PCAS has excellent measurement properties, and performs consistently well across varied segments of the adult population. Widespread application of an assessment methodology, such as the PCAS, will afford an empiric basis through which to measure, monitor, and continuously improve primary care.

Adult↗
PubMed1986

Impact of the medical record credential on data quality.

This research study was funded by the Foundation of Record Education of the American Medical Record Association. The Department of Medical Record Administration at the University of Illinois, Chicago, was awarded the grant in the summer of 1984. The purpose of the study was to evaluate the quality of coded and abstracted medical record data and to determine if a relationship existed between data quality and the professional credentials of the individuals who manage and/or supervise the collection of these data. The study consisted of three phases: a telephone interview conducted of 83 hospitals, recoding and reabstracting of medical records performed by the staffs of 59 hospitals, and 34 random on-site visits for a reliability check. Data was collected and analyzed from each of the three phases of the study.

Abstracting and Indexing↗
PubMed1994

Data quality in hospital strategic information systems: a summary of survey findings.

Fundamental changes in health care financing and delivery have resulted in an unprecedented need for data and information. The application of computer technology to daily hospital operations has gone far toward aiding various kinds of organizational decision making. The quality of those decisions, however, is dependent upon the quality of the data delivered by the various information systems used in the course of health care delivery and management. What remains unknown is the extent to which poor data quality occurs and what actions are taken to measure and control data quality in information systems used for strategic decision making. This article summarizes the results of a survey that was conducted for the purpose of explaining what information systems are important to hospital administrators in their strategic decision making, the frequency with which strategic decision makers encounter data quality problems, and what, if any, actions are taken to prevent, control, or correct apparent data quality problems.

Attitude of Health Personnel↗
PubMed1997

Data quality objectives for surface-soil cleanup operation using in situ gamma spectrometry for concentration measurements.

In situ gamma spectrometry is an efficient method for monitoring the progress of cleanup activities for radioactive contaminants in surface soil and for evaluating the attainment of cleanup standards. However, desired data precision and accuracy must be specified for such a detection system prior to the operation to ensure that the level of uncertainty associated with the concentration measurements is acceptable. A method for developing data quality objectives is described in this paper for in situ gamma spectrometry to achieve numerical goals for data precision and accuracy for cleanup operations. Concentration measurement for a radionuclide at its cleanup level must have a precision commensurate with the importance of cleanup decisions. The 95% lower limit of detection of the system is suggested to be about one tenth the expected system response at the cleanup level. The count time required to achieve the preferred 95% lower limit of detection, and hence the desired precision, can then be determined. The accuracy error arises from the overall calibration factor, which relates the detector responses (e.g., count rate) to physical quantities of interest (e.g., radionuclide soil concentration). The major source of error for the calibration factor using in situ gamma spectrometry is the misidentification of the type of the depth profile of radionuclide concentration in soil. If surrogate radionuclides are used, such as 241Am for plutonium, the variation in the concentration ratio would be another significant source of error. Soil sampling programs performed prior to a cleanup operation will greatly reduce the accuracy error for an in situ detection system, and the analysis of system errors may determine the degree of sampling required. The planning of such a program is discussed in the study. Uncertainty analysis using a Latin Hypercube sampling technique for the calibration factor is also demonstrated. The quantitative result of the uncertainty analysis is useful for determining a nuclide's maximum peak count rate using gamma spectrum that ensures the attainment of the cleanup standard for that nuclide with a pre-specified confidence level (e.g., 95%). The cleanup operation of 239,240Pu in surface soil in the safety shot areas at the Nevada Test Site serves as an example to illustrate the data quality objectives development.

Americium↗
PubMed1999

[Evaluation of population data quality and coverage of registration of deaths for the Brazilian regions].

OBJECTIVE: The evaluation of the quality of population data and coverage of death statistics for all Federal Brazilian Units by sex in 1990. METHODS: The population data came from censuses and the recorded death data from "Fundação Instituto Brasileiro de Geografia e Estatística" and the Health Ministry. The population data were evaluated by applying classical demographic methods. Three techniques were chosen to evaluate the extent of death registration coverage. RESULTS: The degree of precision of the age statement for the majority of the Brazilian regions improved the status from "low precision" or "moderate" to "precise" during the 80's. The coverage of deaths in 1990 was classified as "good" or "satisfactory" for all Federal Units in the South, Southeast and Centre-West and for the Northeastern States below Rio Grande do Norte. All the remaining states were classified as "regular" or "unsatisfactory". CONCLUSIONS: There was a significant improvement in the quality of the census population data and an increase in the coverage of death. It is possible to obtain get reliable mortality indicators for many Brazilian States.

Adolescent↗
PubMed2001

Scalp electrode impedance, infection risk, and EEG data quality.

OBJECTIVES: Breaking the skin when applying scalp electroencephalographic (EEG) electrodes creates the risk of infection from blood-born pathogens such as HIV, Hepatitis-C, and Creutzfeldt-Jacob Disease. Modern engineering principles suggest that excellent EEG signals can be collected with high scalp impedance ( approximately 40 kOmega) without scalp abrasion. The present study was designed to evaluate the effect of electrode-scalp impedance on EEG data quality. METHODS: The first section of the paper reviews electrophysiological recording with modern high input-impedance differential amplifiers and subject isolation, and explains how scalp-electrode impedance influences EEG signal amplitude and power line noise. The second section of the paper presents an experimental study of EEG data quality as a function of scalp-electrode impedance for the standard frequency bands in EEG and event-related potential (ERP) recordings and for 60 Hz noise. RESULTS: There was no significant amplitude change in any EEG frequency bands as scalp-electrode impedance increased from less than 10 kOmega (abraded skin) to 40 kOmega (intact skin). 60 Hz was nearly independent of impedance mismatch, suggesting that capacitively coupled noise appearing differentially across mismatched electrode impedances did not contribute substantially to the observed 60 Hz noise levels. CONCLUSIONS: With modern high input-impedance amplifiers and accurate digital filters for power line noise, high-quality EEG can be recorded without skin abrasion.

Artifacts↗
PubMed1989

Assessing data quality: a computerized approach.

With the growing reliance on large health care data bases, the need to verify data quality increases as well. Because of the considerable costs involved in checks using primary data collection, a computerized methodology for performing such checks is suggested. The technique seems appropriate for any situation where two data collection systems (i.e. hospital discharge abstracts and physician claims for payment) relate to the same event, such as a patient's hospitalization. After reviewing other approaches, this paper suggests linking physician claims for performing particular surgical procedures with hospital discharge abstracts for the stay in which the surgery took place. Physician and hospital data for adults age 25 and over in Manitoba from 1 April, 1979 to 31 March, 1984 were used to address the questions: 1. How well can the two data sets be linked? 2. Given linkage of the two data sets, how much agreement is there as to procedure and diagnosis? Linkage between hospital and physician data was excellent (over 95%) for 5 out of 11 surgical procedures (hysterectomy, prostatectomy, total hip replacement, coronary artery bypass surgery, and heart valve replacement); there was over 90% perfect agreement for three other procedures (cholecystectomy, cataract surgery and total knee replacement). Problems with matching the Manitoba Health Services Commission tariffs (on physician claims) with ICD-9-CM operation codes (on hospital data) led to only 77% perfect agreement for vascular surgery and 84% for gallbladder and biliary tract operations other than cholecystectomy; over 10% of the cases linked on surgeon and date but not on the designated procedures.(ABSTRACT TRUNCATED AT 250 WORDS)

Data Collection↗
PubMed2004

Assessing DTI data quality using bootstrap analysis.

Diffusion tensor imaging (DTI) is an established method for characterizing and quantifying ultrastructural brain tissue properties. However, DTI-derived variables are affected by various sources of signal uncertainty. The goal of this study was to establish an objective quality measure for DTI based on the nonparametric bootstrap methodology. The confidence intervals (CIs) of white matter (WM) fractional anisotropy (FA) and Clinear were determined by bootstrap analysis and submitted to histogram analysis. The effects of artificial noising and edge-preserving smoothing, as well as enhanced and reduced motion were studied in healthy volunteers. Gender and age effects on data quality as potential confounds in group comparison studies were analyzed. Additional noising showed a detrimental effect on the mean, peak position, and height of the respective CIs at 10% of the original background noise. Inverse changes reflected data improvement induced by edge-preserving smoothing. Motion-dependent impairment was also well depicted by bootstrap-derived parameters. Moreover, there was a significant gender effect, with females displaying less dispersion (attributable to elevated SNR). In conclusion, the bootstrap procedure is a useful tool for assessing DTI data quality. It is sensitive to both noise and motion effects, and may help to exclude confounding effects in group comparisons.

Adult↗