Effectiveness of Outpatient Chronic Pain Management for Middle-Aged Patients by Internet Hospitals: Retrospective Cohort Study
Bibliographic record
Abstract
Background: Chronic pain is widespread and carries a heavy disease burden, and there is a lack of effective outpatient pain management. As an emerging internet medical platform in China, internet hospitals have been successfully applied for the management of chronic diseases. There are also a certain number of patients with chronic pain that use internet hospitals for pain management. However, no studies have investigated the effectiveness of pain management via internet hospitals. Objective: The aim of this retrospective cohort study was to explore the effectiveness of chronic pain management by internet hospitals and their advantages and disadvantages compared to traditional physical hospital visits. Methods: This was a retrospective cohort study. Demographic information such as the patient's sex, age, and number of visits was obtained from the IT center. During the first and last patient visits, information on outcome variables such as the Brief Pain Inventory (BPI), medical satisfaction, medical costs, and adverse drug events was obtained through a telephone follow-up. All patients with chronic pain who had 3 or more visits (internet or offline) between September 2021, and February 2023, were included. The patients were divided into an internet hospital group and a physical hospital group, according to whether they had web-based or in-person consultations, respectively. To control for confounding variables, propensity score matching was used to match the two groups. Matching variables included age, sex, diagnosis, and number of clinic visits. Results: A total of 122 people in the internet hospital group and 739 people in the physical hospital group met the inclusion criteria. After propensity score matching, 77 patients in each of the two groups were included in the analysis. There was not a significant difference in the quality of life (QOL; QOL assessment was part of the BPI scale) between the internet hospital group and the physical hospital group (P=.80), but the QOL of both groups of patients improved after pain management (internet hospital group: P<.001; physical hospital group: P=.001). There were no significant differences in the pain relief rate (P=.25) or the incidence of adverse events (P=.60) between the two groups. The total cost (P<.001) and treatment-related cost (P<.001) of the physical hospital group were higher than those of the internet hospital group. In addition, the degree of satisfaction in the internet hospital group was greater than that in the physical hospital group (P=.01). Conclusions: Internet hospitals are an effective way of managing chronic pain. They can improve patients' QOL and satisfaction, reduce treatment costs, and can be used as part of a multimodal strategy for chronic pain self-management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".