Continuity and Coordination of Cancer Care: A Mixed Methods Study of a Web-Based Communication System
Bibliographic record
Abstract
With advances in cancer screening and an ageing population, there are more patients with complex health needs, requiring the involvement of multiple health care providers. Previous research has documented problems related to care coordination and communication between primary care providers (PCPs) and cancer specialists, leading to fragmentation of care, poor patient experience, increased stress, and duplication of services. This dissertation examined whether a web-based asynchronous system (“eOncoNote”) could facilitate communication between PCPs and cancer specialists (oncologists and oncology nurses) and assist with coordination. The focus of this dissertation was on patients in the treatment and survivorship phases of cancer care, involving those who were receiving treatment for breast or prostate cancer, and those who had completed treatment for breast or colorectal cancer and were transferred to their PCP for follow-up. A hybrid type 1 effectiveness-implementation study was conducted, with the effectiveness aim addressed through a pragmatic randomized controlled trial (pRCT). Implementation was assessed using quantitative and qualitative methods. Data collection included patient questionnaires, system usage metrics, hospital electronic medical record (EMR) data, PCP surveys, and qualitative interviews with patients, PCPs, and cancer specialists. The pRCT results did not show an intervention effect on the primary outcome of team and cross-boundary continuity of care or the secondary outcomes of depression and patient experience with their health care. However, there was an intervention effect on the secondary outcome of anxiety. Thirty-nine percent of the PCPs responded to the cancer specialist’s initial eOncoNote message and nearly all of those sent only one message. Most of the PCPs who completed the survey reported no additional benefits of using eOncoNote, emphasizing the need for EMR integration. In the qualitative interviews, both patients and health care providers described the important role patients and caregivers play in care coordination. Patients were often unaware of the communication between their health care providers and assumed they were communicating. Health care providers reported challenges incorporating eOncoNote into their workflow and emphasized the need for a unified approach to clinical communication. Future studies should examine opportunities for EMR integration and whether additional interventions could support communication between PCPs and cancer specialists.
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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 | 0.040 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".