An Internet Hospital Plus Home Nursing Model for Chronic Disease Patients: Mixed-Methods Study in Tianjin, China
Bibliographic record
Abstract
Background: Internet hospitals and "Internet + nursing services" represent emerging medical and nursing models in China. These platforms integrate online systems with offline care to extend services beyond traditional hospital settings. With the rapid expansion of internet hospitals, a new model-internet hospital plus home nursing-has developed. However, research on its implementation and effectiveness remains limited. Objective: This study evaluates the implementation of the internet hospital plus home nursing model by analyzing workload, patient satisfaction, and nurses' perceptions, aiming to provide a strategic reference for its further development. Methods: Data from 2459 patients who used internet hospital plus home nursing services were collected from a hospital database. The frequency of applications and service timeliness were analyzed using χ2 tests. Patient diagnoses, service types, and geographic distribution were summarized using frequency tables and visualization techniques. A simulation approach, along with the Mann-Whitney U test, was used to compare the costs of transferring patients to hospitals versus providing home nursing. Multiple linear regression identified factors associated with cost differences. Patient satisfaction across different stages was compared using a U test, and nurses' attitudes were assessed via a questionnaire. Results: The majority of patients were aged 60 years and older (2120/2459, 86.2%). A significant difference in application frequency was observed across age groups (χ²4=29.86; P<.001). Oncology patients were the most common users (1468/7415, 19.8%) and intravenous blood collection was the most frequent service (4899/7415, 66.1%). Most patients resided within 6 regions near the physical hospital (2119/2459, 86.2%). All patients received services within 2 days of appointment, with waiting times significantly influenced by appointment timing (χ²1 = 290.88; P<.001). Cost distributions varied significantly by gender, age, service frequency, distance, and service type (all P<.001), with service type and distance identified as key cost determinants (P<.001). Patient satisfaction was consistently high across periods, with no significant difference (Mann-Whitney U=5,090,149; P=.38). Nurses expressed positive perceptions of the model. Conclusions: The internet hospital plus home nursing model effectively combines online diagnosis with in-home care, creating a closed-loop service that improves accessibility-particularly for older adults and mobility-impaired patients. Pilot implementations in Tianjin demonstrated benefits in convenience, accessibility, and cost-effectiveness, alongside high patient satisfaction and nursing staff approval. Given the aging population, this model holds significant potential for broader adoption. To ensure sustainable development, enhanced safety mechanisms and policy support are recommended. As an integrated health care model with Chinese characteristics, it also offers valuable insights for the global digital health sector.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 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".