Missed Connections: The Adoption of Information Technology in Canadian Healthcare
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite the ambitious efforts of the provincial and federal governments in Canada to implement Electronic Health Record (EHR) systems, the level of health information exchange across organizations and care settings in Canada is among the lowest in surveyed countries. Some survey findings revealed that in primary care only 12 percent of physicians are notified electronically of patients’ interactions with hospitals or send and receive electronic referrals for specialist appointments. Fewer than three in ten primary care physicians have electronic access to clinical data about a patient who has been seen by a different health organization. Certainly, progress has been made, namely in the development of the infrastructure to store and share health information, as well as some use of information technology in primary care, but the delivery of healthcare in Canada has yet to take full advantage of the major potential benefits. The aims of EHR programs include reducing duplication of, and errors in, patient records; taking advantage of information and communications technology to improve patient outcomes – by delivering patient and medication data to where and when it is needed; and saving the time of patients and providers. In Canada, there will not be any large-scale benefits from gathering masses of health data until the information is shared among providers and institutions, such as between a family physician and a hospital. Leadership is required to drive continuous change and quality improvement toward integrated care. To do so, appropriate incentives are also required. Providers and provider teams need to be held accountable for improvements to happen. One key characteristic shared by many leading healthcare jurisdictions is the incentive to improve outcomes for patients at risk, in contrast to the fee-for-service reimbursement models that create incentives for higher treatment volumes. Leaders need to set goals and incentives for improved quality of outcomes and hold institutions and clinicians accountable for achieving those goals.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it