Who's really hypertensive? - Quality control issues in the assessment of blood pressure for randomized trials

The characterization of blood pressure in treatment trials assessing the benefits of blood pressure lowering regimens is a critical factor for the appropriate interpretation of study results. With numerous operators involved in the measurement of blood pressure in many thousands of patients being screened for entry into clinical trials, it is essential that operators follow pre-defined measurement protocols involving multiple measurements and standardized techniques. Blood pressure measurement protocols have been developed by international societies and emphasize the importance of appropriate choice of cuff size, identification of Korotkoff sounds, and digit preference. Training of operators and auditing of blood pressure measurement may assist in reducing the operator-related errors in measurement. This paper describes the quality control activities adopted for the screening stage of the 2nd Australian National Blood Pressure Study (ANBP2). ANBP2 is cardiovascular outcome trial of the treatment of hypertension in the elderly that was conducted entirely in general practices in Australia. A total of 54 288 subjects were screened; 3688 previously untreated subjects were identified as having blood pressure >140/90 mmHg at the initial screening visit, 898 (24%) were not eligible for study entry after two further visits due to the elevated reading not being sustained. For both systolic and diastolic blood pressure recording, observed digit preference fell within 7 percentage points of the expected frequency. Protocol adherence, in terms of the required minimum blood pressure difference between the last two successive recordings, was 99.8%. These data suggest that adherence to blood pressure recording protocols and elimination of digit preferences can be achieved through appropriate training programs and quality control activities in large multi-centre community-based trials in general practice. Repeated blood pressure measurement prior to initial diagnosis and study entry is essential to appropriately characterize hypertension in these elderly patients.

Assessing the quality of risk factor survey data: lessons from the WHO MONICA Project

Background and purpose Survey data quality is a combination of the representativeness of the sample, the accuracy and precision of measurements, data processing and management with several subcomponents in each. The purpose of this paper is to show how, in the final risk factor surveys of the WHO MONICA Project, information on data quality were obtained, quantified, and used in the analysis. Methods and results In the WHO MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) Project, the information about the data quality components was documented in retrospective quality assessment reports. On the basis of the documented information and the survey data, the quality of each data component was assessed and summarized using quality scores. The quality scores were used in sensitivity testing of the results both by excluding populations with low quality scores and by weighting the data by its quality scores. Conclusions Detailed documentation of all survey procedures with standardized protocols, training, and quality control are steps towards optimizing data quality. Quantifying data quality is a further step. Methods used in the WHO MONICA Project could be adopted to improve quality in other health surveys.

Data quality initiatives - striving for continuous improvements

Although managers consider accurate, timely, and relevant information as critical to the quality of their decisions, evidence of large variations in data quality abounds. Over a period of twelve months, the action research project reported herein attempted to investigate and track data quality initiatives undertaken by the participating organisation. The investigation focused on two types of errors: transaction input errors and processing errors. Whenever the action research initiative identified non-trivial errors, the participating organisation introduced actions to correct the errors and prevent similar errors in the future. Data quality metrics were taken quarterly to measure improvements resulting from the activities undertaken during the action research project. The action research project results indicated that for a mission-critical database to ensure and maintain data quality, commitment to continuous data quality improvement is necessary. Also, communication among all stakeholders is required to ensure common understanding of data quality improvement goals. The action research project found that to further substantially improve data quality, structural changes within the organisation and to the information systems are sometimes necessary. The major goal of the action research study is to increase the level of data quality awareness within all organisations and to motivate them to examine the importance of achieving and maintaining high-quality data.

Perceptual quality metrics applied to still image compression

We present a review of perceptual image quality metrics and their application to still image compression. The review describes how image quality metrics can be used to guide an image compression scheme and outlines the advantages, disadvantages and limitations of a number of quality metrics. We examine a broad range of metrics ranging from simple mathematical measures to those which incorporate full perceptual models. We highlight some variation in the models for luminance adaptation and the contrast sensitivity function and discuss what appears to be a lack of a general consensus regarding the models which best describe contrast masking and error summation. We identify how the various perceptual components have been incorporated in quality metrics, and identify a number of psychophysical testing techniques that can be used to validate the metrics. We conclude by illustrating some of the issues discussed throughout the paper with a simple demonstration. (C) 1998 Elsevier Science B.V. All rights reserved.