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At least 415 records · Page 23Linked to original sources
PubMed2002

Impact of prostate volume evaluation by different observers on CT-based post-implant dosimetry.

PURPOSE: An analysis of computed tomography (CT)-based dosimetry was performed to evaluate the variability of different observers' judgements in marking the prostate gland on CT films, and its effect on the parameters that characterise the prostate implantation quality. Accuracy of data entry by the first author in the process of dosimetry procedure has also been evaluated. MATERIALS AND METHODS: Four observers were asked to evaluate the prostate volume on CT films for six different patients. Each observer repeated the evaluation six times. The sample of patients has a prostate volume in the range of 21.4-42.0 cc derived from transrectal ultrasound volume study. After an average period of 6 weeks of the I-125 implantation, all patients had CT scans. CT-based post-implant dosimetry was performed and the dose volume histograms DVHs were calculated to report the re-constructed prostate volume, Vp100, Vp150, Vp90 and D90. Comparison between the four observers' output was performed. RESULTS: Comparison between the four observers shows that each observer has a different way of estimating the prostate on CT films. Observers' precision also varies according to the prostate volume and the image quality. This can cause a variation in the resulting D90 value by up to 50%. Analysis of data entry shows a high degree of accuracy. The error of digitizing the prostate is +/-0.19 cc. This is correlated to an error of +/-0.78 Gy of the D90. CONCLUSION: The evaluation of prostate gland volume on CT films varies between different observers. This has an effect on the dosimetric indices that characterise the implant quality in particular the D90.

Humans↗
PubMed2003

Reliability of voluntary and compulsory databases and registries in the United States.

In the United States, there are several transplant registries and databases. Most are voluntary and may be organ specific, disease or condition specific, organ and disease specific, or specific for a certain demographic patient group. There is one compulsory and comprehensive registry, the Scientific Registry of Transplant Recipients (SRTR). These databases all have strengths and weaknesses. There is no doubt, however, that they contribute significantly to the scientific analyses of transplant outcomes and complications and provide important data through publications and presentations that can improve patient care and influence local, regional, and national transplant policies. Audits can and should be performed to guarantee the reliability of the data and accuracy of the conclusions drawn from this data as was done by the European Liver Transplant Registry.

Databases, Factual↗
PubMed1992

Improving dental epidemiologic data collection with computers.

A computerized dental data recording system (DDRS) was developed for the New England Elder Dental Study to improve data quality and increase field staff efficiency. The DDRS displays video screens similar to traditional paper forms to record data on coronal and root caries, dentate and denture status, subacute bacterial endocarditis screening, gingival bleeding, calculus, and periodontal attachment level. DDRS provides facilities for date and exam-component time tracking, on-line contextual comments, random record retrieval, editing, data backup, and data output in various data formats. This study compared the DDRS with a paper-form system for data entry accuracy. Dental caries and periodontal disease measurement data from 38 subjects were recorded on paper forms and independently entered using DDRS. The DDRS identified 150 illogical data errors, 39 inconsistent data errors, 7 invalid data and 34 miscellaneous data errors. Four technicians with field experience using both paper forms and DDRS reported time savings using DDRS in the field. DDRS has the potential for additional time savings by minimizing the time for data coding, cleaning, and management. Results demonstrate that DDRS could improve the quality of oral epidemiologic data by mandating strict adherence to protocols, preventing errors, and increasing field efficiency.

Computers↗
PubMed2001

The importance of traceability for public health and consumer protection.

Since the 1980s, concerns about the safety and quality of food have increased at both governmental and consumer levels. The importance of traceability of animals and animal products has grown as food production and marketing have been removed from direct consumer control. Product traceability, which requires a transparent chain of custody to maintain credibility and to complete information transfer functions, has two components, namely: a unique identification system, and a credible and verifiable mechanism for identity preservation. Traceability systems can be subdivided into the following four categories: country of origin; retail; processor; and farm-to-retail identity. Although the availability of computers and electronic data devices can enhance the speed and accuracy of data acquisition and manipulation, a common set of developmental criteria exists, irrespective of data-handling processes. As data management technologies become more powerful and less costly, product traceability requirements will multiply. Public and private sectors should seize these opportunities to improve public health and quality parameters, or risk a narrowing of their markets.

Animal Identification Systems↗
PubMed1989

Accuracy of recalled smoking data.

Validity of recalled cigarette data was assessed among 87 middle-aged adults by comparing recall to longitudinal records. Agreement on smoking status and amount smoked 20 years ago occurred for 87 per cent and 71 per cent of subjects, respectively. Corresponding proportions for 32-year recall were 84 per cent and 55 per cent. Gender did not influence recall accuracy. Ex-smokers tended to make the most errors. Accuracy of recalled smoking information 20 years ago was comparable to that of alcohol status and consumption frequency category.

Female↗
PubMed1997

Principals of design and evaluation of an information system for a department of respiratory medicine.

OBJECTIVES: To evaluate a departmental computer system. DESIGN: a. Direct comparison of the time taken to use a manual system with the time taken to use a computer system for lung function evaluation, loan of equipment and production of correspondence. b. Analysis of the accuracy of data capture before and after the introduction of the computer system. c. Analysis of the comparative running costs of the manual and computer systems. SETTING: Within a department of respiratory medicine serving a hospital of 1323 beds. MAIN OUTCOME MEASURES: a. Time taken to perform functions with the assistance of computerised methods, in comparison to the manual method used alone. b. Accuracy of data capture. c. Relative running costs. RESULTS: a. The computer system (CS) was significantly faster than the manual system (MS) for lung function evaluation (CS = 7.63 min/test, MS = 12.25 min/test), loan of equipment (CS = 0.40 min/loan, MS = 2.07 min/loan), and checking for overdue equipment (CS = 0.49 s/record, MS = 9 s/record). The production of correspondence was slightly slower with the computer (CS = 9.30 min/letter, MS = 8.54 min/letter). b. All outpatient episodes, but only 43 of 65 (66%) of in-patient episodes, were captured. Lung function and managerial report data were accurate using both manual and computerised methods. The manual system for equipment loans was inefficient, and use of the computer resulted in the recovery of 221 nebulisers. c. Development costs for 1988-1990 were high (72,178 pounds). Only 1200 pounds to 1845 pounds per year was recovered directly from staff time saved by the computer but larger savings resulted from changes in work practice (4049-4765 pounds). After 10 years the projected deficit is 10,000 pounds per annum in running costs. CONCLUSIONS: In comparison with the manual methods, the computer system has shown significant advantages which provide accurate information, with significant favourable effects on working practices. In evaluating computer systems used in clinical practice it is essential to ensure that the projected work practice benefits are achieved without unacceptable costs in staff time, inaccurate data and high financial outlay.

Computer Systems↗
PubMed2006

Brief report: beyond clinical experience: features of data collection and interpretation that contribute to diagnostic accuracy.

BACKGROUND: Clinical experience, features of data collection process, or both, affect diagnostic accuracy, but their respective role is unclear. OBJECTIVE, DESIGN: Prospective, observational study, to determine the respective contribution of clinical experience and data collection features to diagnostic accuracy. METHODS: Six Internists, 6 second year internal medicine residents, and 6 senior medical students worked up the same 7 cases with a standardized patient. Each encounter was audiotaped and immediately assessed by the subjects who indicated the reasons underlying their data collection. We analyzed the encounters according to diagnostic accuracy, information collected, organ systems explored, diagnoses evaluated, and final decisions made, and we determined predictors of diagnostic accuracy by logistic regression models. RESULTS: Several features significantly predicted diagnostic accuracy after correction for clinical experience: early exploration of correct diagnosis (odds ratio [OR] 24.35) or of relevant diagnostic hypotheses (OR 2.22) to frame clinical data collection, larger number of diagnostic hypotheses evaluated (OR 1.08), and collection of relevant clinical data (OR 1.19). CONCLUSION: Some features of data collection and interpretation are related to diagnostic accuracy beyond clinical experience and should be explicitly included in clinical training and modeled by clinical teachers. Thoroughness in data collection should not be considered a privileged way to diagnostic success.

Clinical Competence↗
PubMed2006

Eyetrack (ET) vs the conventional paper record (CPR): a study comparing the accuracy and speed of data retrieval from glaucoma patient records.

PURPOSE: To compare patient data retrieval between electronic patient record systems (Eyetrack) and conventional paper records (CPRs). METHODS: A total of 20 long term glaucoma patient records held on Eyetrack were randomised into two collections with 10 CPRs and 10 Eyetrack records in each collection. The Eyetrack records of one collection were the CPRs of the other collection and vice versa. Four doctors, as two groups, were assessed on a separate collection of records. The time taken to answer 10 questions and the accuracy were assessed. Comparison was made of the answers between the two formats. A month later each group was assessed on the 10 CPRs of the other collection. An expert Eyetrack user was assessed on only the 20 Eyetrack notes. Comparison was made between the 20 CPRs the doctors were assessed on and the 20 eyetrack records. RESULTS: In the first comparison, the mean time for all the doctors to answer the questions on a CPR was 324.4(+/-106.0) s compared to 104.8(+/-34.0) s for Eyetrack(Mann-Whitney, P<0.01). Mean accuracy for a CPR was 84.0%(+/-13.0%) compared to 98.0%(+/-4.0%) for Eyetrack(Mann-Whitney, P<0.01). Comparing the expert Eyetrack user with the CPR showed a mean time for Eyetrack of 96.6(+/-34.8) s compared with 283.7(+/-63.9) s for CPR(Mann-Whitney, P<0.0001). Mean accuracy for Eyetrack was 97.5%(+/-7.2%) compared to 82.0%(+/-8.7%) for CPRs(Mann-Whitney, P<0.0001). CONCLUSIONS: An improvement of 3 min 40 s per record was observed with Eyetrack. Accuracy was also improved. Similar results were also found comparing an expert Eyetrack user with CPRs.

Glaucoma↗
PubMed2005

Accuracy of diabetes diagnosis in health insurance claims data in Taiwan.

BACKGROUND AND PURPOSE: There are limited data from Taiwan about the accuracy of National Health Insurance (NHI) claims data. This study assessed the accuracy of NHI claims data for diabetes and its associated factors. METHODS: Insurance claims data for patients with a diagnosis of diabetes were extracted from the records of the Bureau of National Health Insurance, including detailed files of the outpatient, emergency, inpatient and pharmacy treatment records from January 1, 2000 to December 31, 2000. A stratified, 2-staged, probability proportional to size and equal probability method was used to sample 9000 diabetes patients. The accuracy of the diabetes diagnosis was assessed based on patient responses to questionnaire items. Subjects with negative or uncertain questionnaire answers who had hypoglycemic agents in pharmacy claims data were also classified as diabetic. RESULTS: A total of 1350 questionnaires were returned and an accurate diagnosis was verified from data in 1007 (74.6%) of these subjects. Univariate analysis showed that level of accreditation of the hospital, age, gender, follow-up department, type of complication, number of outpatient visits, emergent visit, as well as hospitalization were significant factors associated with an accurate diagnosis of diabetes. Multivariate logistic regression analysis revealed that number of outpatient visits, hospitalization, age, and the level of accreditation of the hospital were significant independent factors. The odds ratio of an accurate diagnosis increased with the number of outpatient visits and hospitalization. The probability of accurate diagnosis of diabetes among patients with >/= 4 outpatient visits was 99.16 times greater than that of patients with </= 1 outpatient visit. The probability of accurate diagnosis in patients with >/= 1 hospitalization was 5.26 times that of patients who had not been hospitalized. CONCLUSIONS: This study found that the accuracy of diabetes diagnosis in NHI claims data in Taiwan was 74.6%. Further attention to the association of inaccurate claims in cases with infrequent outpatient visits, young age and those attending non-accredited hospitals is needed in order to address the efficiency of diagnosis and surveillance of diabetes in Taiwan.

Adult↗
PubMed2003

Using disease registries for pharmacoepidemiological research: a case study of data from a cystic fibrosis registry.

BACKGROUND: The Epidemiologic Registry of Cystic Fibrosis (ERCF) was a multicentre, longitudinal follow-up project of cystic fibrosis patients enrolled at some 200 centres in nine European countries between 1994 and 1999. PURPOSE: We aimed to assess and improve the quality of a subset of data from the ERCF relating to seven English centres (1184 patients), prior to using the data for a long-term cost-effectiveness analysis of dornase alfa (Pulmozyme). Specifically we wanted to assess the completeness and accuracy of the data and the comparability of cases across centres. METHODS: We used a subset of ERCF data relating to seven UK cystic fibrosis (CF) centres. Following initial data editing, key variable data from a sample of patients from five centres were subjected to a detailed verification of ERCF data against original data sources available in the centres. Disagreements between ERCF reports and original data sources were identified and corrected in the study dataset. In addition, centre staff were questioned about relevant clinical and recording practices. RESULTS: Thanks to detailed routine data checking procedures on key variables operated by the ERCF, the rates of disagreement between ERCF data and original data as identified in our verification process on the assessed variables are generally low (0.4-3.7%). Some outcome variables (deaths, hospitalisations) seem to be under-reported by some centres. Episodes of pulmonary exacerbation are difficult to identify and also to verify. Twenty-four patients were registered twice (consecutively in two different centres). There were some differences between centres in their interpretation of recording rules. CONCLUSIONS: Researchers seeking to use disease registry data should consider detailed data quality review processes. Apart from data accuracy, reliable definitions of both critical events as well as their timing are important. The degree of under-reporting, particularly of outcome variables, should be estimated. Information on local clinical and reporting practices is necessary to interpret multi-centre data. Data protection issues may limit the possibilities for detailed data quality assessments of secondary data, as does the accessibility of original data for verification purposes. Our experiences and recommendations may be valuable for those intending to use disease registry data as well as those devising and operating such registries.

Adult↗
PubMed2000

Determining the quality of breast cancer care: do tumor registries measure up?

BACKGROUND: Hospital tumor registries, which provide data that inform health services research and cancer control policies, may be a source of information about quality of cancer care. However, the accuracy of data from such registries is unknown. OBJECTIVE: To determine the accuracy of tumor registry data by comparing it with data collected from numerous sources for a breast cancer quality improvement project. DESIGN: Retrospective cohort study. SETTING: Three teaching hospitals with tumor registries in the New York metropolitan area that had participated in the quality improvement project. PATIENTS: All women with newly diagnosed primary breast cancer (stage I or stage II) who were surgically treated at the study hospitals between 1 November 1994 and 31 August 1996. MEASUREMENTS: Sensitivity and specificity were calculated, and data from the quality improvement project were used as the gold standard. RESULTS: The tumor registries and the quality improvement project had similar information on tumor stage and surgery type. Sensitivity ranged from 0.91 to 0.96, and specificity ranged from 0.93 to 0.97. When both sources were used to calculate quality measures, the overall rate of radiation therapy after breast-conserving surgery was 80% in the quality improvement project and 48% in the tumor registries (sensitivity, 0.58; specificity, 0.94). For receipt of adjuvant systemic treatment, the rate was 78% in the quality improvement project and 22% in the tumor registries (sensitivity, 0.27; specificity, 0.97). CONCLUSIONS: Data from tumor registries provide accurate measures for hospital-based surgical treatments but not for outpatient treatments. Unverified tumor registry data should not be used to measure quality of care.

Ambulatory Care↗
PubMed1998

Automatic registration of pelvic computed tomography data and magnetic resonance scans including a full circle method for quantitative accuracy evaluation.

The purpose of this study is to develop a method for registration of CT and MR scans of the pelvis with minimal user interaction and to obtain a means for objective quantification of the registration accuracy of clinical data without markers. CT scans were registered with proton density MR scans using chamfer matching on automatically segmented bone. A fixed threshold was used to segment CT, while morphological filters were used to segment MR. The method was tested with transverse and coronal MR scans of 18 patients and sagittal MR scans of 8 patients. The registration accuracy was estimated by comparing (triangulating) registrations of a single CT scan with MR in different orientations in a "full circle." For example, CT is first matched on transverse MR, next transverse MR is matched independently on coronal MR, and finally coronal MR is matched independently on CT. The product of the three transformations is the identity if all matching steps are perfect. Deviations from identity occur both due to random errors and due to some types of systematic errors. MR was registered on MR (to close the "circle") by minimization of rms voxel value differences. CT-MR registration takes about 1 min, including user interaction. The random error for CT-MR registration with transverse or coronal MR was 0.5 mm in translation and 0.4 degree in rotation (standard deviation) for each axis. A systematic registration error of about 1 mm was demonstrated along the MR frequency encoding direction, which is attributed to the chemical shift. In conclusion, the presented algorithm efficiently and accurately registers pelvic CT and MR scans on bone. The "full circle" method provides an estimate of the registration accuracy on clinical data.

Algorithms↗
PubMedDate not supplied

Bioanalytic considerations for pharmacokinetic and biopharmaceutic studies.

The correct evaluation of pharmacokinetic and biopharmaceutic data can only be achieved if accurate analytic data are obtained. The accuracy of analytic data depends on the criteria used to validate the method. Consequently, careful scrutiny of drug stability, assay sensitivity, selectivity, recovery, linearity, precision, and accuracy is necessary for the proper interpretation of data. The importance of method validation and its influence on pharmacokinetic and biopharmaceutic data evaluation and interpretation will be discussed.

Biopharmaceutics↗
PubMed2004

Improved prediction of recurrence after curative resection of colon carcinoma using tree-based risk stratification.

BACKGROUND: Patients who are at high risk of recurrence after undergoing curative (R0) resection for colon carcinoma may benefit most from adjuvant treatment and from intensive follow-up for early detection and treatment of recurrence. However, in light of new clinical evidence, there is a need for continuous improvement in the calculation of the risk of recurrence. METHODS: Six hundred forty-one patients with R0-resected colon carcinoma who underwent surgery between January 1, 1984 and December 31, 1996 were recruited from the Erlangen Registry of Colorectal Carcinoma. The study end point was time until first locoregional or distant recurrence. The factors analyzed were: age, gender, site in colon, International Union Against Cancer (UICC) pathologic tumor classification (pT), UICC pathologic lymph node classification, histologic tumor type, malignancy grade, lymphatic invasion, venous invasion, number of examined lymph nodes, number of lymph node metastases, emergency presentation, intraoperative tumor cell spillage, surgeon, and time period. The resulting prognostic tree was evaluated by means of an independent sample using a measure of predictive accuracy based on the Brier score for censored data. Predictive accuracy was compared with several proposed stage groupings. RESULTS: The prognostic tree contained the following variables: pT, the number of lymph node metastases, venous invasion, and emergency presentation. Predictive accuracy based on the validation sample was 0.230 (95% confidence interval [95% CI], 0.227-0.233) for the prognostic tree and 0.212 (95% CI, 0.209-0.215) for the UICC TNM sixth edition stage grouping. CONCLUSIONS: The prognostic tree showed superior predictive accuracy when it was validated using an independent sample. It is interpreted easily and may be applied under clinical circumstances. Provided that their classification system can be validated successfully in other centers, the authors propose using the prognostic tree as a starting point for studies of adjuvant treatment and follow-up strategies.

Adenocarcinoma↗
PubMed2001

Adaptive double data entry: a probabilistic tool for choosing which forms to reenter.

Several recent articles have supported differing opinions about the value and cost of double data entry in specific clinical trials. The cost of the reentry, combined with the low error rate typical in controlled clinical trials suggests to some that single data entry may be sufficient, with the cost of reentry allocated to more productive quality assurance tools. In this article, an alternative approach to limiting costs and maintaining the quality of entered data is offered. The technique is a formal, adaptive method for choosing a subset of forms to be reentered. The idea behind the approach is to decide whether a given form should be reentered on a form-by-form basis for each data entry person, using an estimated probability that the form contains an error as a guideline. The method automatically adapts to each data entry person and to temporal changes in accuracy within data entry person. The estimated probability is based on a lagged set of the most recently double-data-entered forms. A simple simulation shows that much of the reentry can be avoided while still detecting many of the errors. A real data example demonstrates that the procedure can be effective in practice as well. Control Clin Trials 2001;22:2-12

Algorithms↗
PubMed2002

The accuracy of medicare claims data in identifying Alzheimer's disease.

We linked Medicare claims data to information on 417 patients with a clinical diagnosis of Alzheimer's disease in the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) to determine what proportion of them were identified as having Alzheimer's disease (AD) in Medicare claims records. Seventy-nine percent of these patients were identified as having AD using 5 years of claims data; 87% were identified as demented when a broader set of ICD-9-CM codes was used. An Anderson-Gill counting process approach was used to model the "hazard" of patients being identified as having AD in Medicare claims data. CERAD patients with mild dementia were less likely to be identified in the claims data as having AD. Once identified in Medicare claims as having AD, patients were more likely to be so identified again. When using only the physician supplier and institutional outpatient files, approximately 75% of CERAD patients were identified as having AD; hospital files used alone identified less than one-third (29%) of the CERAD patients as having AD. The data indicate that at least 3 consecutive years of physician supplier and physician outpatient claim files should be used to identify Medicare beneficiaries with AD using Medicare claims.

Aged↗