Investigating Digital Patient-Reported Outcome Measures in Patient-Centered Diabetes Specialist Outpatient Care (DigiDiaS): Protocol for a Multimethod Prospective Observational Study
Bibliographic record
Abstract
BACKGROUND: Living with type 1 diabetes is challenging, and to support self-management, repeated consultations in specialist outpatient care are often required. The emergence of new digital solutions has revolutionized how health care services can be patient centered, providing unprecedented opportunities for flexible, high-quality care. However, there is a lack of studies exploring how the use of digital patient-reported outcome measures (PROMs) for flexible specialist care affects diabetes self-management. To provide new knowledge on the relevance of using PROMs in standard care, we have designed a multimethod prospective study. OBJECTIVE: The overall aim of this protocol is to describe our prospective multimethod observational study designed to investigate digital PROMs in a routine specialist outpatient setting for flexible patient-centered diabetes care (DigiDiaS). METHODS: This protocol outlines the design of a multimethod prospective observational cohort study that includes data from electronic health records, self-reported questionnaires, clinical consultation field observations, and individual in-depth interviews with patients and diabetes health care personnel. All patients with type 1 diabetes at a designated outpatient clinic were invited to participate and use the digital PROM implemented in clinical care. Both users and nonusers of the digital PROM were eligible for the prospective study, allowing for a comparison of the two groups. Data were collected at baseline and after 12 months, including self-management as the primary outcome assessed using the Patient Activation Measure, along with the secondary outcomes of digital health literacy, quality of life, health economy, and clinical variables such as glycated hemoglobin. RESULTS: The digital solution was implemented for routine clinical care in the department in November 2021, and data collection for the prospective study started in October 2022. As of September 6, 2023, 84.6% (186/220) of patients among those in the digital PROM and 15.5% (34/220) of patients among the nonusers have consented to participate. We expect the study to have enough participants by the autumn of 2023. With 1 year of follow-up, the results are expected by spring 2025. CONCLUSIONS: In conclusion, a multimethod prospective observational cohort study can offer valuable insights into the relevance, effectiveness, and acceptability of digital tools using PROMs in diabetes specialist care. Such knowledge is crucial for achieving broad and successful implementation and use of these tools in a large diabetes outpatient clinic. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52766.
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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 | 0.080 | 0.056 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".