PRO-based follow-up as a means of self-management support – an interpretive description of the patient perspective
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: There is an increasing focus on the use of patient-reported outcome (PRO) measures to improve the quality and effectiveness of health care. PRO-based follow-up is a new model of service delivery, where the patient's PRO measures are used as the very basis for outpatient follow-up. OBJECTIVES: This study aimed to explore how patients with epilepsy experience the use of PRO-based follow-up in three outpatient clinics in the Central Denmark Region. We also sought to explain how these experiences relate to self-management. METHODS: Interpretive description was the methodological approach. We conducted in-depth individual interviews with 29 patients referred to PRO-based follow-up, each of whom had completed at least two PRO questionnaires. Participants were sampled based on purposive and theoretical sampling. RESULTS: PRO-based follow-up may support patients' self-management by a) increasing awareness of psychosocial problems, b) improving communication, c) increasing understanding of symptoms, d) facilitating change in health behavior and e) strengthening autonomy. Inhibitors for PRO measures as a means of self-management support were identified as a) feelings of rejection and disconnection, b) incomprehension of purpose of PRO-based follow-up, c) PRO measures being too standardized and negative and d) lack of confidence in own ability to assess PRO questionnaires. CONCLUSION: The findings demonstrate broad variation in the influences of PRO measures on patient's self-management in life with epilepsy. Sense of ownership may explain this variation. We suggest supplementary clinical initiatives in order to enhance the benefits from PRO-based follow-up, particularly on how patients are allocated to this health care service.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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