Patients’ and Providers’ Perspectives on and Needs of Telemonitoring to Support Clinical Management and Self-care of People at High Risk for Preeclampsia: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Preeclampsia is one of the leading causes of maternal mortality worldwide, with a global prevalence at 2%-8% of pregnancies. Patients at high risk for preeclampsia (PHRPE) have an increased risk of complications, such as fetal growth restriction, preterm delivery, abnormal clotting, and liver and kidney disease. Telemonitoring for PHRPE may allow for timelier diagnosis and enhanced management, which may improve maternal and perinatal outcomes. OBJECTIVE: The objective of this study is to determine the perceptions and needs of PHRPE and their health care providers with respect to telemonitoring through semistructured interviews with both groups. This study explored (1) what the needs and challenges of monitoring PHRPE are during pregnancy and in the postpartum period and (2) what features are required in a telemonitoring program to support self-care and clinical management of PHRPE. METHODS: This study used a qualitative descriptive approach, and thematic analysis was conducted. PHRPE and health care providers from a high-risk obstetrical clinic in a large academic hospital in Toronto, Canada, were asked to participate in individual semistructured interviews. Two researchers jointly developed a coding framework and separately coded each interview to ensure that the interviews were double-coded. The software program NVivo version 12 was used to help organize the codes. RESULTS: In total, 7 PHRPE and 5 health care providers, which included a nurse practitioner and physicians, participated in the semistructured interviews. Using thematic analysis, perceptions on the benefits, barriers, and desired features were determined. Perceived benefits of telemonitoring for PHRPE included close monitoring of home blood pressure (BP) measurements and appropriate interventions for abnormal BP readings; the development of a tailored telemonitoring system for pregnant patients; and facilitation of self-management. Perceived barriers to telemonitoring for PHRPE included financial and personal barriers, as well as the potential for increased clinician workload. Desired features of a secure platform for PHRPE included the facilitation of self-management for patients and decision making for clinicians, as well as the inclusion of evidence-based action prompts. CONCLUSIONS: The perceptions of patients and providers on the use of telemonitoring for PHRPE support the need for a telemonitoring program for the management of PHRPE. Recommendations from this study include the specific features of a telemonitoring program for PHRPE, as well as the use of frameworks and design processes in the design and implementation of a telemonitoring program for PHRPE.
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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 | 0.013 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".