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At least 19 recordsLinked to original sources
PubMed1991

Data collection in the Great Plains Genetics Service Network: using limited funds to collect data from centers with varying resources.

The Data Committee of the Great Plains Genetics Service Network (GPGSN) coordinates the collection of data relating to delivery of genetic services in eight states. These states are Iowa, Missouri, Arkansas, Oklahoma, Kansas, Nebraska, South Dakota and North Dakota. The funds allocated to this project by the GPGSN are limited. The distance between genetics service sites is great and the population density in the regions being served is low. The local resources available to the genetics services sites participating in data collection vary from robust to "bare-bones". The approach to solving the problem involved the following. First the committee the data items to be collected were identified and defined. Second, a standard format for transmitting the data to the GPGSN regional coordinating center in Iowa City was developed. Third, the services sites and their resources for collecting data were identified. Fourth, resources were allocated to different sites in a manner that seemed most able to help that center to contribute data to the regional center. Fifth, data were aggregated at the regional center and aggregated data reports were returned to collecting sites. Finally, items were modified in response to the feedback received from the genetics services sites. Although the philosophy is that data collection should be a by-product of providing quality genetic services, the region recognizes that service sites will need help to conform with regional standards. Therefore the region encourages each service site to develop its own method to collect data, and provides assistance to it in getting the data into the regional transmission format.(ABSTRACT TRUNCATED AT 250 WORDS)

Data Collection↗
PubMed2003

The effect of different methods of collecting data: mail, telephone and filter data collection issues in utility measurement.

When collecting data researchers can interview participants, conduct telephone interviews, or mailout questionnaires. Often mixed methods are used. Whether these methods produce equivalent data is under-researched in the health-related quality of life (HRQoL) field. In addition, the effect of using filter questions has not been researched among HRQoL multi-attribute utility instruments. This study randomly sampled from Melbourne, Australia, and employed a test-retest design to investigate whether mail or telephone interview made any difference to Assessment of Quality of Life (AQoL) instrument utility scores. A filter question AQoL version investigated the effect of filters on scores. There was no significant difference in standard AQoL scores between mail self-completion and telephone interview, regardless of which was administered first. Inclusion of filter questions encouraged respondents to select the best response category thereby screening out minor health conditions. The effect was to increase utility scores by 0.06 or 7%. This effect has not been previously reported in utility instruments and has profound implications for economic evaluations using cost-utility analysis; there are implications for researchers using filter questions in general. In conclusion, researchers should feel confident that utility scores elicited from the standard AQoL through self-completion mail and telephone interview administrations are directly comparable.

Adult↗
PubMed1983

A comparison of automated data collection and manual data collection for toxicology studies.

Automated data collection was compared with manual data collection in terms of accuracy and man-hours devoted to data manipulation and checking. The comparison was based on experience with an automated data collection system (DOLPHIN)TM1 developed at Toxigenics for use in conducting toxicological studies. It was found that on-line data collection increases the quality of the data gathered because: 1) it facilitates scientific observation by displaying historical data and statistics on changes since the last observation period; 2) it virtually eliminates errors due to oversight and transcription; 3) it allows more careful monitoring of the course of the study by providing immediate access to interim summary statistics; 4) it provides complete documentation of all changes made to the data after initial collection. In addition, automated data collection enables more rapid completion of the final report of results because: 1) fewer departmental transfers are required; 2) auditing by Quality Assurance (Q.A.) personnel is facilitated.

Data Collection↗
PubMedDate not supplied

Electronic data collection options for practice-based research networks.

PURPOSE: We wanted to describe the potential benefits and problems associated with selected electronic methods of collecting data within practice-based research networks (PBRNs). METHODS: We considered a literature review, discussions with PBRN researchers, industry information, and personal experience. This article presents examples of selected PBRNs' use of electronic data collection. RESULTS: Collecting research data in the geographically dispersed PBRN environment requires considerable coordination to ensure completeness, accuracy, and timely transmission of the data, as well as a limited burden on the participants. Electronic data collection, particularly at the point of care, offers some potential solutions. Electronic systems allow use of transparent decision algorithms and improved data entry and data integrity. These systems may improve data transfer to the central office as well as tracking systems for monitoring study progress. PBRNs have available to them a wide variety of electronic data collection options, including notebook computers, tablet PCs, personal digital assistants (PDAs), and browser-based systems that operate independent of or over the Internet. Tablet PCs appear particularly advantageous for direct patient data collection in an office environment. PDAs work well for collecting defined data elements at the point of care. Internet-based systems work well for data collection that can be completed after the patient visit, as most primary care offices do not support Internet connectivity in examination rooms. CONCLUSIONS: When planning to collect data electronically, it is important to match the electronic data collection method to the study design. Focusing an inappropriate electronic data collection method onto users can interfere with accurate data gathering and may also anger PBRN members.

Biomedical Research↗
PubMedDate not supplied

A comparison of frequency, interval, and time-sampling methods of data collection.

Data representing high, medium, and low response rates in constant and nonconstant patterns were generated by electromechanical equipment to determine whether the same data collected by time-sampling, interval recording, and frequency recording would be represented similarly by each method. Results indicated: (1) that time-sampling provided an extremely inaccurate estimate of responding, and (2) that interval recording accurately represented responding of low and medium rates, but grossly underestimated high-rate responding.

Journal Article↗
PubMed2004

Promoting the use of environmental data collected by concerned citizens through information and communication technologies.

Public participation within environmental monitoring may contribute to increasing the knowledge on the state of the environment at the same time it promotes citizens' involvement in environmental protection. However, the use of voluntary collected data is limited due to a lack of confidence in data collection procedures. Additionally, data quality is often unknown and the data are usually dispersed and non-structured. Information and communication technologies (ICT) may promote the use of voluntary collected data through the development of a collaborative system that incorporates tools and methodologies to facilitate data collection, access and validation. Furthermore, the use of ICT may promote public involvement within environmental monitoring, since it facilitates communication among all the stakeholders. This paper analyses the role of ICT in developing a system for environmental collaborative monitoring intending to promote the use of volunteer collected data. It starts by analysing the role of volunteers within environmental monitoring and continues analysing the potential of ICT to take advantage of the benefits of using data collected by citizens. A collaborative system that allows the public to express its knowledge on the state of the environment is described. Special emphasis is given to tools that explore non-traditional types of environmental data such as images, sounds and videos in association with spatial information. To illustrate the above mentioned concepts, a case study for beach quality monitoring developed within the Senses@Watch project, is described.

Communication↗
PubMed1994

[Classification, a suitable method for nursing research--practical advice for data collection and data analysis].

Arranging subjective data in rank order is a simple method for making comparisons of judgements and evaluating them. Since it is difficult to find practical instructions for this which can be easily understood, this paper uses data obtained in a study of patients' opinions about their privacy. Results are analysed, presented and explained. The method is appropriate for a wide range of research in which individuals are asked for opinions.

Data Collection↗
PubMed1996

Designing a computerized data collection tool for access management.

Collecting data for continuing quality improvement can be a barrier for staff. Data collection can be stressful and time consuming. If not carefully planned it may not provide desired information. Satellite Dialysis Centers recently developed a new data collection tool for vascular access management that was incorporated into our clinical information system. The goal of this project was to collect meaningful accurate information concerning vascular access in a manner that would not increase the dialysis staff work load. This article will outline the measures taken by Satellite Dialysis Centers to automate data collection concerning dialysis access management, including how desired data were identified and strategies for ensuring data entry compliance.

Arteriovenous Shunt, Surgical↗
PubMed1996

Survey data collection: operationalizing the research design.

This article describes how indigenous interviewers were used to collect data about the health needs and resources in a black South African township. The survey was done during the dismantling of the apartheid political system of South Africa. The political unrest, distrust, and tension were barriers to carrying out a survey and threatened the quality of the data collection. A vulnerability of survey research is the difficulty in controlling the variables of the community and the interviewer during the process of data collection. How this survey was carried out, in this unstable setting, influenced the quality of the data and the validity and reliability of the research. The data-collection requirements were carried out in a way that was functional in the real-world setting while maintaining research standards. The criteria used for hiring interviewers and the content and delivery of training were effective in this tense, educationally disadvantaged community setting. Methods that were used to motivate and supervise interviewers were successful and are recommended for use in similar survey research.

Black or African American↗
PubMed2001

[Quality assurance of data collection and data processing in epidemiologic study data].

Quality assurance of the data generating processes in epidemiologic studies is a prerequisite for the internal validity of study results. This paper presents practical aspects of such a quality assurance system pertaining to the planning, data gathering, data entry and data processing phase of a study. It is concerned with data obtained in the framework of a project rather than with data accumulating continuously in private practices, research institutes or veterinary faculties. During the planning phase of a project, standard operating protocols should be developed that assure a reliable performance of observation, coding and data entry. The data base structure, consisting of tables, input validation rules and queries, should be predefined and well documented. A data safety concept will provide the necessary integrity, physical safety and availability of the data. The paper presents technical solutions to common data processing problems with emphasis on re-coding and relational data base facilities (Microsoft-ACCESS) using a hypothetical study on risk factors for mastitis.

Animals↗
PubMed1989

An evaluation of population pharmacokinetics in therapeutic trials. Part III. Prospective data collection versus retrospective data assembly.

The ability to estimate population pharmacokinetic parameters of alprazolam from fragmentary clinical data collected during clinical efficacy trials was evaluated in this series of studies. In the first study modifications to the protocol and case report forms were employed to allow for the prospective collection of accurate dosing and blood sampling time data. In the second study only total daily dose and measured drug concentration data were recorded. Dosage and blood sampling time data were assembled retrospectively by assuming strict adherence to protocol guidelines. Comparisons of the results of these analyses demonstrate the marked impact of prospective data collection efforts on data quality and the ability to determine subsequent pharmacokinetic parameters. Analysis of the prospectively collected data yielded pharmacokinetic estimates for alprazolam that were nearly identical to previously reported values obtained according to traditional methods, whereas the analysis of retrospectively collected data yielded biased estimates of the mean pharmacokinetic parameters and markedly upward biased estimates of both interindividual and residual variability. These analyses demonstrate the ability to estimate population pharmacokinetic parameters from data collected during clinical efficacy trials, provided that critical issues pertaining to the design and use of data collection forms to enhance data quality and the education of patients and staff are satisfactorily addressed.

Adult↗
PubMed2002

Analysis of environmental and biologic methyl parathion data to improve future data collection.

The Agency for Toxic Substances and Disease Registry analyzed concurrently collected data on environmental methyl parathion (MP) and urinary p-nitrophenol (PNP) at the request of the U.S. Environmental Protection Agency (U.S. EPA). The purpose of the analysis was to assess whether individuals' age or level of residential MP contamination might predict their urinary PNP level. Unlicensed pesticide applicators had sprayed residences in Mississippi with MP, which is approved as a pesticide only for outdoor agricultural use. Data were received from Mississippi for MP wipe sample levels for 409 homes and urinary PNP levels for 929 residents of the residences sampled. In addition to descriptive and bivariate analyses, ordinal logistic regression was performed after categorizing the data. Interpretation of results was limited by several identified data gaps and pre-existing data-quality issues. On the basis of the lessons learned from identified data gaps, specific recommendations were made to the U.S. EPA for improving future data collection methods for more meaningful exposure assessment in similar environmental contaminations. The recommended changes were successfully incorporated in subsequent data collected by other states that had experienced similar residential MP spraying.

Agriculture↗
PubMed2004

Online data collection from video game players: methodological issues.

The paper outlines the advantages and disadvantages of using the Internet to collect data concerning both online and offline gamers. Drawing from experience of a number of studies carried out online by the authors and by reviewing the available literature, the authors discuss the main issues concerning data collected from video game players. The paper examines a number of areas, including recruiting and utilizing participants, validity, suitable methods of data collection (i.e., questionnaire studies, online tests, participant observation, online interviews), and ethical issues. It is concluded that online research methods can be a useful way of examining the psychosocial aspects of video game playing.

Data Collection↗
PubMed2005

Using qualitative interviews in CAM research: a guide to study design, data collection and data analysis.

Qualitative methods, such as the in-depth interview, offer a potentially powerful means of uncovering the complex experiences of patients, carers and clinicians within treatment and decision-making processes. In the context of complementary and alternative medicine (CAM), qualitative interview-based projects allow for subjectivity and complexity within human experience, making them a powerful tool for increasing our knowledge of important processes within CAM. However, qualitative interview-based projects are often poorly designed, carried out and analysed. This article provides a guide for CAM researchers on how to use qualitative interviews to produce meaningful, and methodologically sound, research findings.

Complementary Therapies↗
PubMed1980

[Electronic data processing in anaesthesia. Development of a data collection form and organisation of data collection (author's transl)].

We report on the development of a data collection form for anaesthesia. The difference between this form and the previously published recommendations is that it does not require any coding of data prior to collection. The anaesthetist completing the form needs no knowledge of data processing. Qualitative data have only to be marked, while quantitative data must be entered as such. So far, more than 90,000 anaesthesias have been collected with the form presented, therefore usefulness may be assumed.

Anesthesiology↗
PubMed1991

Collecting data for clinical indicators.

The Joint Commission for Accreditation of Healthcare Organizations is currently testing clinical indicators that will become an important part of hospital quality assurance programs. Implementation of clinical indicators may necessitate more extensive data collection than is now being done. This article reviews important considerations in the development of a data collection system that facilitates the evaluation of indicators of clinical performance. The evolution of the system currently used by the Nutritional Support Service at Pennsylvania Hospital is provided.

Data Collection↗
PubMed2004

Studies in emergency department data collection: shared versus split responsibility for patient enrollment.

OBJECTIVES: To compare patient enrollment in six clinical studies using shared coverage (24 emergency department [ED] rooms-two students share enrollment responsibility) with enrollment using split coverage (12 rooms each per student). The academic associate (AA) program uses undergraduate students to collect data for clinical studies in the ED by providing double coverage 16 hours/day, seven days/week. Prior studies have shown that this system captures >85% of eligible patients. Methods to obtain closer to 100% enrollment are desired. METHODS: During consecutive 15-day periods with the same 24 AAs, the daily ED census, hours of AA coverage, and enrollment in each of six studies were evaluated prospectively in the ED. Data are presented as means with 95% confidence intervals (CIs). RESULTS: There was no difference between the shared and split enrollment periods with respect to hours of AA coverage (30.3 vs. 30.7 hours/day; p = 0.7) or average daily ED census (133.7 vs. 141.8; p = 0.15). Overall, the percentages of ED patients recruited for study participation were not different depending on whether the split versus shared recruitment strategy was used (907 patients recruited out of 2005 ED patients (45.2%; 95% CI = 43.0 to 47.4) vs. 937 of 2127 (44.0%; 95% CI = 41.9 to 46.1). The 95% CI for the 1.2% difference was -1.8% to 4.2%. Patient enrollments in six individual studies were similar regardless of recruitment strategy. Following the 30-day trial, AAs were surveyed: 17 of 24 (71%) found the split strategy to be "more helpful in enrolling subjects," and 20 of 24 (83%) found split strategy helped them "keep better track" of patients. CONCLUSIONS: Study subject enrollment was not affected by the use of either the shared or split responsibility strategy for recruitment. Students generally preferred the split strategy because it was more helpful and easier to monitor. Therefore, this may be the best option for similar student-oriented data collection programs.

Data Collection↗