Situation of Integrated Eldercare Services with Medical Care in China
Bibliographic record
Abstract
There are clinics around nursing homes in foreign countries or family doctors for every elderly. When a disease occurs, doctors can provide door to door service to help patients. Since the epidemic of coronavirus disease 2019, the elderly have been a high risk group of people infected with coronavirus disease 2019. In both the United States and Canada, the first recorded coronavirus disease 2019 deaths and outbreaks occurred in nursing homes with case fatality rates in these settings reported to be as high as 33.7 %. Due to the lack of adequate medical facilities and adequate medical staff to provide services, the elderly are more likely to be infected with the virus as a result of social interaction. All these show that foreign models can no longer meet the medical needs of the elderly. Therefore, we should take a different perspective and combine pension services with medical care. At present, China is exploring the mode of combination of medical and nursing services. In this study, we investigated the current situation of integrated medical and nursing services in China, exploring the transformation of primary medical institutions into medical and nursing service providers. The integrated eldercare services with medical care is that we make use of the existing medical resources to provide care services, which can meet the health needs of the elderly and reduce the infection rate of the elderly. Using a self-administered or interview questionnaire survey, we conducted t-test and one-way analysis of variance. It was found that the elderly are most satisfied with the geographical location (90.84 %) and medical services (90.82 %), and the most dissatisfied with consultation (87.66 %) and institutional fees (87.23 %). The elderly with the older age, the higher the monthly income of more than 3000 yuan, marriage and chronic diseases, are highly satisfied with their community health service institutions (p<0.05). Through one-way analysis of variance, there were significant differences in medical and health service demand among the groups with different monthly income (f=5.289 and 5.312, p<0.05), different occupation (f=5.574 and 2.325, p<0.05), and different ideal mode of providing for the aged (f=5.237, p=0.002<0.05). By independent sample t test, it was found that there were significant differences in basic medical service demand and health guidance service demand between people with chronic diseases and those without chronic diseases (p<0.05), and those who were willing and unwilling to use information technology for disease management (p<0.05). Through regression analysis, we can see that age (t=4.411, p<0.05) and income (t=2.061, p<0.05) have significant influence on basic medical service among the three variables of age, education and monthly income, and the coefficient is positive. Age (t=2.508, p<0.05) and income (t=3.143, p<0.05) had significant influence on rehabilitation guidance service, and the coefficient was positive. In summary, age, income, occupation, whether suffering from chronic diseases, whether they are willing to use information technology to detect and manage diseases and other factors, all affect the demand of the elderly for basic medical services and rehabilitation guidance services in medical service institutions. Through the research on the current situation of the integrated medical and nursing services in China, this study enriches the relevant evidence of the integrated medical and nursing services, and has a certain reference value for the relevant management departments to formulate policiesis.
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 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".