Data Security in Electronic Health Records
Bibliographic record
Abstract
Traditionally, patient information has been recorded on paper and stored in file folders at healthcare facilities and within physicians’ offices. The implementation of electronic health records (EHRs), the lifetime record of an individual’s health and health services delivered, allows for information to be stored on computers and offers the opportunity to store considerably more data, in much less space, with new efficiencies and value added as information is easier to access, legible, timely, non-redundant and readily available. However, there are many issues to consider with the implementation of a fully shared EHR. The protection of the information contained in the record is of the utmost importance as individuals stand to become quite vulnerable if that personal health information is compromised or accessed by unauthorized users. Therefore, one of the goals of this chapter is to uncover ways in which personal health information is being protected in EHR systems. The second objective, a broader one, examines what regulations, legislation and policies are in place that remove some of the uncertainty and risk and make the use of shared information safe and secure. Many of the techniques and technologies used so far are adopted from the corporate world, where data security has been an issue for some time. Current legislation in the United States and Canada at both the federal and state/provincial levels has addressed the general principles of data security and privacy but are still lacking in specifics with regard to cross-jurisdictional sharing of health information and the implementation and use of EHRs. Many of the researchers and studies on the subject find this to be one of the most important areas of concern moving forward. The opportunities for EHR implementation and use are exciting as they have the strong potential to improve both individual health care and population health, but without proper regulation and policies in place it is possible that the risks may outweigh the benefits.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".