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Record W107836202

Electronic health records as a threat to privacy.

2005· article· en· W107836202 on OpenAlexaffabout
Glenn Griener

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsProvincial Laboratory of Public HealthUniversity of Alberta
Fundersnot available
KeywordsInternet privacyGovernment (linguistics)SketchHealth carePatient portalPublic relationsElectronic health recordMasking (illustration)PharmacyBusinessMedicinePolitical scienceComputer scienceLawNursing
DOInot available

Abstract

fetched live from OpenAlex

Introduction Governments across Canada are investing millions of dollars into the creation of electronic health records systems. While these systems offer great promise of improving the nation's health care system, they also pose considerable risks to individual privacy. In this brief paper I hope to do two things. First, I hope to foster a clearer understanding of the risks. The risks are often misrepresented or misunderstood because of some prevalent misconceptions about the nature of the proposed electronic systems. For that reason, some explanation of the systems is needed. I use Alberta's Electronic Health Record as an exemplar. Once the nature of the risk is delineated, I sketch some of the steps which I believe are necessary for dealing with them. Alberta's Electronic Health Record--Wrestling with Misconceptions Discussion of a provincial or national electronic health record (EHR) often conjures up the image of a massive new database created by the government and containing a lifetime of one's health information. This picture is undoubtedly fostered by the loose descriptions which are so often offered by proponents of such systems. But it is mistaken on at least two significant counts. In the first place, there is no new warehouse of information. Rather, the Alberta's EHR is an electronic network that links the patient records which are collected and maintained by health professionals and by regional health authorities. The EHR provides a portal through which this information can flow from one care provider to another. Pharmacist Kumar, who operates a community pharmacy, can use his computer to obtain information about a patient from Dr. Lee's record. A crucial point to emphasize is that professional responsibility is maintained by those who have traditionally had responsibility for the collection, use and disclosure of health information. I will return to this point below. A second common misconception is that all information collected by any health professional will be made available through the data exchange system. This need not be the case, and at the present time it is not the case. For instance, the information which is currently available through the Alberta Electronic Health Record is merely a subset of the information which is available within Capital Health's netCARE. (1) And the information which is available through netCARE is itself just a subset of information which physicians and clinics in the region maintain within their own records. Simply stated, much of the health information collected in a variety of settings is not available through current electronic health records. Security and Electronic Health Records The creation of a network linking databases full of health information, information which most people find to be among the most sensitive, creates some new risks. Hackers may invade the system and view individuals' health information or--far worse--change it. Health records may be lost through computer failures. But electronic databases loaded with important personal information are now ubiquitous, and dangers such as these threaten all of them. We have developed confidence in our ability to deal effectively with these hazards. Why should we doubt our ability to manage threats to electronic health records using the state-of-the-art technology and practices developed for other arenas of the electronic environment? Electronic Health Records and Professional Responsibility As noted earlier, the EHR is not a massive new record; rather, it is a portal for the transfer of patient information. Information is collected and recorded by one health care provider and flows through this network to other health care providers. In one sense, the advent of the system changes nothing. Health care providers--be they individual professionals or large regional authorities--maintain responsibility for their patients' health information. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.435
Threshold uncertainty score0.865

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.029
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0120.029
Scholarly communication0.0210.010
Open science0.0030.006
Research integrity0.0200.013
Insufficient payload (model declined to judge)0.0130.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.342
GPT teacher head0.538
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2005
Admission routes2
Has abstractyes

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