Evidence map›Paper›PMID 29854172›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2017

Modes of De-identification.

Mehmet Kayaalp

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. The Detection of Date Shifting in Real-World Data.Applied clinical informatics · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Neonatal NIRS monitoring: recommendations for data capture and review of analytics.Journal of perinatology : official journal of the California Perinatal Association · 2021
    Review
  15. Article
  16. Article
  17. Customization scenarios for de-identification of clinical notes.BMC medical informatics and decision making · 2020
    Article
  18. Balancing Personal Privacy and Public Safety During COVID-19: The Case of South Korea.IEEE access : practical innovations, open solutions · 2020
    Article
  19. Aging Well: Using Precision to Drive Down Costs and Increase Health Quality.Advances in geriatric medicine and research · 2019
    Article
  20. Article
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

1 author.

Mehmet KayaalpLister Hill National Center for Biomedical Communications U.S. National Library of Medicine, National Institutes of Health, Bethesda, Maryland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

De-identification of protected health information is an essential method for protecting patient privacy. Most institutes require de-identification of patient data prior to conducting scientific studies; therefore, it is important for clinical scientists to be cognizant of all modes of de-identification and all services provided by their de-identification tools. In this article, we discuss eight different modes of de-identification that yield de-identified data at different levels of quality. Most of these modes can be used in combination to achieve the best performance.

Indexed as

ConfidentialityData AnonymizationData AccuracyElectronic Health RecordsHumansMethods

Identifiers

PMID29854172
PMCPMC5977668

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.