Designing a Future eHealth Service for Posthospitalization Self-management Support in Long-term Illness: Qualitative Interview Study
Bibliographic record
Abstract
BACKGROUND: For patients with noncommunicable diseases (NCDs; eg, heart failure [HF] and colorectal cancer [CRC]), eHealth interventions could meet their posthospital discharge needs and strengthen their ability to self-manage. However, inconclusive evidence exists regarding how to design eHealth services to meet the complex needs of patients. To foster patient acceptability and ensure the successful development and implementation of eHealth solutions, it is beneficial to include different stakeholders (ie, patients and health care professionals) in the design and development phase of such services. The involvement of different stakeholders could contribute to ensuring feasible, acceptable, and usable solutions and that eHealth services are developed in response to users' supportive care needs when transitioning to home after hospitalization. This study is the first step of a larger complex intervention study aimed at meeting the postdischarge needs of 2 NCD populations. OBJECTIVE: This study aimed to explore the perspectives of patients with HF and CRC and health care professionals on patient self-management needs following hospital discharge and investigate how a future nurse-assisted eHealth service could be best designed to foster patient acceptability, support self-management, and smooth the transition from hospital to home. METHODS: A qualitative, explorative, and descriptive approach was used. We conducted 38 semistructured interviews with 10 patients with HF, 9 patients surgically treated for CRC with curative intent, 6 registered nurses recruited as nurse navigators of a planned eHealth service, and 13 general practitioners experienced in HF and CRC treatment and follow-up care. Patients were recruited conveniently from HF and CRC outpatient clinics, and the nurses were recruited from the cardiology and gastro-surgical departments at a university hospital in the southwest of Norway. The general practitioners were recruited from primary care in surrounding municipalities. Semistructured interview guides were used for data collection, and the data were analyzed using thematic analysis. RESULTS: In total, 3 main themes were derived from the data analysis: expecting information, reassurance, and guidance when using eHealth for HF and CRC self-management; expecting eHealth to be comprehensible, supportive, and knowledge promoting; and recognizing both the advantages and disadvantages of eHealth for HF and CRC self-management. The data generated from this interview study depicted the diverse needs for self-management support of patients with CRC and HF after hospital discharge. In addition, valuable suggestions were identified regarding the design and content of the eHealth service. However, participants described both possible advantages and disadvantages of a remote eHealth service. CONCLUSIONS: This study is the first step in the development of an eHealth service for posthospitalization self-management support for long-term illnesses. It concerns patients' supportive care needs and user requirements of an eHealth service. The findings of this study may add value to the planning and development of eHealth interventions for patients with NCDs.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".