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PubMed2004

Wisconsin hospitals share performance data online.

Performance data is no longer a closely-held secret, as thousands of hospitals are reporting this information to the CMS and other quality improvement initiatives. The Wisconsin Hospital Association has tapped into this flow of data to build a website that allows hospitals in that state to compare their performance directly to other facilities.

Benchmarking↗
PubMedDate not supplied

Trends in injuries, illnesses, and policies in Canadian healthcare workplaces.

BACKGROUND: Analysis of workers' compensation data and occupational health and safety trends in healthcare across Canada was conducted to provide insight concerning workplace injuries and prevention measures undertaken in the healthcare sector. METHODS: Timeloss claims data were collected for 1992-2002 from the Association of Workers' Compensation Boards of Canada. Labour Force data from Statistics Canada were used to calculate injury rates. The Occupational Health and Safety Agency for Healthcare in British Columbia coordinated with provincial occupational health and safety agencies in Ontario, Quebec and Nova Scotia to analyze injury data and collate prevention measures in their regions. RESULTS: The national timeloss injury rate declined from 4.3 to 3.7 injuries per 100 person-years since 1998. Musculoskeletal injuries consistently comprised the majority of timeloss claims. Needlestick injuries, infectious diseases and stress-related claims infrequently resulted in timeloss claims although they are known to cause great concern in the workplace. Prevention measures taken in the various provinces related to safer equipment (lifts and electric beds), return-to-work programs, and violence prevention initiatives. Different eligibility criteria as well as adjudication policies confounded the comparison of injury rates across provinces. DISCUSSION: Since 2000, all provinces experienced healthcare restructuring and increased workload in an aging workforce. Despite these increased risks, injury rates have decreased. Attribution for these trends is complex, but there is reason to believe that focus on prevention can further decrease injuries. While occupational health is a provincial jurisdiction, harmonizing data in addition to sharing data on successful prevention measures and best practices may improve workplace conditions and thereby further reduce injury rates for higher risk healthcare sector occupations.

Accidents, Occupational↗
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↗
PubMed2006

Concept of sample in OMICS technology.

Fundamental biological processes can now be studied by applying the full range of OMICS technologies (genomics, transcriptomics, proteomics, metabolomics, and beyond) to the same biological sample. Clearly, it would be desirable if the concept of sample were shared among these technologies, especially as up until the time a biological sample is prepared for use in a specific OMICS assay, its description is inherently technology independent. Sharing a common informatic representation would encourage data sharing (rather than data replication), thereby reducing redundant data capture and the potential for error. This would result in a significant degree of harmonization across different OMICS data standardization activities, a task that is critical if we are to integrate data from these different data sources. Here, we review the current concept of sample in OMICS technologies as it is being dealt with by different OMICS standardization initiatives and discuss the special role that the newly formed Genomic Standards Consortium (GSC) might have to play in this domain.

Animals↗
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↗