Patient, staff, and clinician perspectives on implementing electronic communications in an interdisciplinary rural family health practice
Bibliographic record
Abstract
Aim To conduct an environmental scan of a rural primary care clinic to assess the feasibility of implementing an e-communications system between patients and clinic staff. BACKGROUND: Increasing demands on healthcare require greater efficiencies in communications and services, particularly in rural areas. E-communications may improve clinic efficiency and delivery of healthcare but raises concerns about patient privacy and data security. METHODS: We conducted an environmental scan at one family health team clinic, a high-volume interdisciplinary primary care practice in rural southwestern Ontario, Canada, to determine the feasibility of implementing an e-communications system between its patients and staff. A total of 28 qualitative interviews were conducted (with six physicians, four phone nurses, four physicians' nurses, five receptionists, one business office attendant, five patients, and three pharmacists who provide care to the clinic's patients) along with quantitative surveys of 131 clinic patients. Findings Patients reported using the internet regularly for multiple purposes. Patients indicated they would use email to communicate with their family doctor for prescription refills (65% of respondents), appointment booking (63%), obtaining lab results (60%), and education (50%). Clinic staff expressed concerns about patient confidentiality and data security, the timeliness, complexity and responsibility of responses, and increased workload. CONCLUSION: Clinic staff members are willing to use an e-communications system but clear guidelines are needed for successful adoption and to maintain privacy of patient health data. E-communications might improve access to and quality of care in rural primary care practices.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".