Evidence map›Paper›PMID 12463885›Full record

ArticleProceedings. AMIA Symposium2002

A security architecture for query tools used to access large biomedical databases.

Shawn N Murphy, Henry C Chueh

Abstract read
In one paragraph

Article in Proceedings. AMIA Symposium, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

69 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Trial
  4. Trial
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Nurse-sensitive indicators during COVID-19.International journal of nursing knowledge · 2022
    Article
  11. Sharing Time-to-Event Data with Privacy Protection.Proceedings. IEEE International Conference on Healthcare Informatics · 2022
    Article
  12. Observational
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Protecting patient privacy in survival analyses.Journal of the American Medical Informatics Association : JAMIA · 2020
    Article
  20. Toward a More Accurate Accrual to Clinical Trials: Joint Cohort Discovery Using Bloom Filters and Homomorphic Encryption.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020
    Article

9 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Shawn N MurphyLaboratory of Computer Science, Massachusetts General Hospital, Boston, MA, USA.
Henry C Chueh

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disseminating information from large biomedical databases can be crucial for research. Often this data will be patient-specific, and therefore require that the privacy of the patient be protected. In response to this requirement, HIPAA released regulations for the dissemination of patient data. In many cases, the regulations are so restrictive as to render data useless for many purposes. We propose in this paper a model for obfuscation of data when served to a client application, that will make it extremely unlikely that an individual will be identified. At Partners Healthcare Inc, with over 1.4 million patients and 400 research clinician users, we implemented this model. Based on the results, we believe that a web-client could be made generally available using the proposed data obfuscation scheme that could allow general usage of large biomedical databases of patient information without risk to patient privacy.

Indexed as

Computer SecurityConfidentialityMedical Records Systems, ComputerizedDatabases, FactualHumans

Identifiers

PMID12463885
PMCPMC2244204

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.