Evaluation of real-time use of electronic patient-reported outcome data by nurses with patients in home dialysis clinics
Bibliographic record
Abstract
BACKGROUND: Internationally, the use of patient-reported outcomes (PROs) is increasing. Electronic PROs (ePROs) offer immediate access of such reports to healthcare providers. The objectives of this study were to assess nurses' perspectives on the usefulness and impact of ePRO administration in home dialysis clinics and assess patient perceptions of satisfaction with nursing care following use of ePROs. METHODS: A concurrent, longitudinal, mixed methods study was conducted over 6 months during home dialysis outpatient clinic visits in two cities. Patients (n = 99) provided ePROs using tablet computers when they visited the clinic on two consecutive occasions approximately 3 months apart. Results were scored, printed, and given to nurses before patient appointments. Patients completed satisfaction items from the Comox Valley Nursing Centre Client questionnaire following their appointments. All clinic nurses (n = 11) participated and they were each interviewed twice, three months and six months after the start of the study. RESULTS: The five themes that emerged from the interviews with the nurses include: enhancing focus of the nurses, directing interdisciplinary follow-up, offering support to patients through the process, interpreting results from the visual display, and integrating into workflow. Scores on the Client Questionnaire suggested that patients believed that they received excellent care (97%), and that the nurses perfectly understood their needs (90.9%). However, their satisfaction with care did not change over time when ePRO data was repeatedly provided to their nurses. CONCLUSIONS: Nurses reported that sharing ePRO data in real-time informed their practice. Although there was no statistically significant change in patient satisfaction scores over time, some patients reported changes and benefits from the use of ePROs. Further research is needed to provide guidance about how ePRO data could enhance person-centered care.
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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 | 0.018 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".