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At least 91 records · Page 5Linked to original sources
PubMed1995

Practical application of sharing surveillance data.

This article provides several practical and effective mechanisms for reporting meaningful information on nosocomial infections to critical care and other specific units. Roadblocks and a small sample of hospital practices for reporting unit-specific infections are described. Graphic presentations, especially line-stay histograms, are recommended.

Data Interpretation, Statistical↗
PubMed1997

Guaranteeing anonymity when sharing medical data, the Datafly System.

We present a computer program named Datafly that maintains anonymity in medical data by automatically generalizing, substituting, and removing information as appropriate without losing many of the details found within the data. Decisions are made at the field and record level at the time of database access, so the approach can be used on the fly in role-based security within an institution, and in batch mode for exporting data from an institution. Often organizations release and receive medical data with all explicit identifiers, such as name, address and phone number, removed in the incorrect belief that patient confidentiality is maintained because the resulting data look anonymous; however, we show the remaining data can often be used to re-identify individuals by linking or matching the data to other databases or by looking at unique characteristics found in the fields and records of the database itself. When these less apparent aspects are taken into account, each released record can be made to ambiguously map to many possible people, providing a level of anonymity determined by the user.

Confidentiality↗
PubMed1999

DNA fingerprinting data and the analysis of population genetic structure by comparing band-sharing patterns.

Genetic isolation among populations can be effectively investigated by multilocus DNA fingerprinting. If populations have diverged, it is expected that the mean proportion of bands shared by individuals from the same population, Bw, exceeds the corresponding mean, Bb, calculated from pairs of individuals from distinct populations. A problem arises in deciding whether any difference between Bw and Bb is statistically significant. In fact, any two band-sharing data (bij), contributing to Bw or Bb, are not independent if they share a common individual (like bij and bjl). This prevents a correct application of parametric tests, such as the Student's t-test. Recently, a modification of this test has been proposed that should avoid the independence problem. Using a large number of samples of fingerprints, simulated from an appropriate 'genetic' model, under a wide range of conditions, we compared the performances of the Student's t-test, the modified t-test and five new permutation tests, where individuals, rather than bij values, are permuted. We found that: (i) the Student's t-test can be very permissive, rejecting too often the null hypothesis when true, but is correct or conservative in certain cases; (ii) the modified t-test is extremely conservative when the null hypothesis is true and very inefficient otherwise; (iii) all five permutation tests are strictly correct, provided that individuals are ordered randomly on gels; and (iv) in this case, the permutation tests are equally efficient, and are not inferior to the Student's t-test when the latter is approximately correct and provides a fair benchmark.

DNA Fingerprinting↗
PubMed1998

Sharing and archiving data is fundamental to scientific progress.

The persuasive argument for sharing and archiving data is that scientists must build on the shoulders of other scientists, that science is cumulative and replicative, and that science must be open. Sharing and archiving data are just a small part of all that is implied by that principle, but it is inextricably part of our obligation as social and behavioral scientists to conduct our work in the open. Only then can others see and understand what we did, and only then will someone have a chance to confirm that we were right, or to prove that we were wrong. Moreover, data archiving and sharing create opportunities for addressing questions not envisioned by the initial investigators. Indeed, by supplementing or pooling archived data, new and original data sets can be created that permit analyses well beyond the purpose or scope of the initial data collection. Of course, the creativity and labor of initial investigators should be protected, and the privacy of research participants must be safeguarded. These protections and safeguards, however, are not antithetical to data archiving and sharing. They simply raise questions about when and how data archiving and sharing should take place. In our view, the benefits of properly archived and shared data for outweigh the potential for harm. As indicated above, this is a perspective shared by several funding agencies of behavioral and social research, including the NIA.

Data Collection↗
PubMed1993

HIPIN--a generic HIS/RIS-PACS interface based on clinical radiodiagnostic procedures.

Within the EurIPACS HIPIN topic a generic HIS/RIS-PACS interface will be designed, implemented and evaluated. It is generally agreed that integration with the HIS/RIS is essential for the acceptance of PACS in a clinical environment. An interface between HIS/RIS and PACS allows more efficient usage of both systems, better integration of data, better consistency checking on shared data and better security and error handling. Also the PACS performance is improved by using HIS/RIS information to steer the image migration within the PACS. In this paper the functional specifications of the interface are described. These specifications are based on descriptions of clinical radiodiagnostic procedures. The generic interface consists of a common part, and of site specific adapters. The common part is identical for all incarnations and performs message scheduling, processing and logging. The adapters are specific for each communication standard, e.g. ACR-NEMA or HL7, and for each hospital. The interface will be implemented at the radiology department of the Philipps University Hospital in Marburg (Germany) and at the orthopaedic and neuroradiology departments of the hospital of the Free University in Brussels (Belgium).

Computer Communication Networks↗
PubMedDate not supplied

Capturing and using clinical outcome data: implications for information systems design.

There is an urgent need to capture and record data related to clinical outcomes, but there are many barriers. The range of problems includes lack of agreement on conceptualization of the term "outcome," inadequate measures of outcomes, and inadequate information systems to capture and manipulate data that would reflect outcomes. This article focuses on information system requirements to capture, store, and utilize clinical outcome data. For greatest accuracy, outcome data should be captured as close to the source as possible, including direct data capture from patients themselves and from their families. To make maximum use of outcome data, systems must be designed to 1) store data in multipurpose databases; 2) share data across different platforms; 3) link outcome data to other data that might influence or explain outcomes; 4) allow querying of the data by authorized personnel; and 5) protect patient confidentiality.

Decision Support Systems, Management↗
PubMed1998

Pitfalls in neuroepidemiologic research.

In neuroepidemiologic research, there are many pitfalls to trap unwary investigators, whether the project is a survey, a case-control study, or some other type of study. We briefly discuss pitfalls relating to: research preliminaries (e.g., failure to decide on study objectives); personnel and training (e.g., deficient training); data collection (e.g., ineffective supervision); data ownership and data sharing (disagreement about how the data will be used), and report preparation (e.g., failure to interpret results in the context of uncertainties arising from the design and implementation of the research). Awareness of these pitfalls will reduce the likelihood of flawed or ineffective neuroepidemiologic research.

Data Collection↗