Background E-consultation is expected to improve the information level of patients, affect patients’ subsequent judgments of medical services, and guide patients to make a reasonable medical selection in the future. Thus, it is important to understand the influence mechanism of e-consultation on patients’ medical selection. Objective This study aims to explore the changes in first-visit patients’ understanding of disease and medical resources after e-consultation as well as the choice of follow-up medical services. Methods Patients’ medical selection before and after e-consultation was compared using a scenario survey. Based on the service characteristics of the e-consultation platform, representative simulation scenarios were determined, and parallel control groups were set up considering the order effect in comparison. Finally, a total of 4 scenario simulation questionnaires were designed. A total of 4164 valid questionnaires were collected through the online questionnaire collection platform. Patients’ perception of disease severity, evaluation of treatment capacity of medical institutions, selection of hospitals and doctors, and other outcome indicators were tested to analyze the differences in patients’ evaluation and choice of medical services before and after e-consultation. Additionally, the results’ stability was tested by regression analysis. Results In scenario 1 (mild case), before e-consultation, 14.1% (104/740) of participants considered their conditions as not serious. After e-consultation, 69.5% (539/775) of them considered their diseases as not serious. Furthermore, participants’ evaluation of the disease treatment capacity of medical institutions at all levels had improved after using e-consultation. In scenario 3 (severe case), before e-consultation, 54.1% (494/913) of the participants believed their diseases were very serious. After e-consultation, 16.6% (157/945) considered their diseases were very serious. The evaluation of disease treatment capacity of medical institutions in nontertiary hospitals decreased, whereas that of tertiary hospitals improved. In both mild and severe cases, before e-consultation, all of the participants were inclined to directly visit the hospital. After e-consultation, more than 71.4% (553/775) of the patients with mild diseases chose self-treatment, whereas those with severe diseases still opted for a face-to-face consultation. After e-consultation, patients who were set on being treated in a hospital, regardless of the disease severity, preferred to select the tertiary hospitals. Of the patients with mild diseases who chose to go to a hospital, 25.7% (57/222) wanted to consult online doctors face-to-face. By contrast, 56.4% (506/897) of the severe cases wanted to consult online doctors face-to-face. Conclusions E-consultation can help patients accurately enhance their awareness of the disease and guide them to make a more reasonable medical selection. However, it is likely that e-consultation makes online medical services centralized. Additionally, the guiding effect of e-consultation is limited, and e-consultation needs to be combined with other supporting systems conducive to medical selection to play an improved role.
Unbalanced distribution of medical resources is becoming a big challenge, particularly in selecting doctors. E-consultation could provide patients with more choices of doctors and break out the constraints of time and space. But the acceptance of e-consultation is still poor and the mechanism of adoption is unclear. This study aimed to identify the factors influencing the public intention to use e-consultation and explore the effect path of factors and behavior intention. The hypotheses of our research model were developed based on technology acceptance model and perceived risk theory. A Web-based survey was conducted by Sojump and the 29 items questionnaire with 5-point Likert scales completed by 934 respondents. Structural equation modeling was used to analyze the data. Item evaluation and reliability, validity, path loading, goodness of fit, and multiple-group analysis were used to check moderation effects. Standardized factor loadings of items were between 0.551 and 0.873. Composite reliability of 9 constructs ranged from 0.706 to 0.840. Average variance extracted ranged from 0.387 to 0.640. The fitness indices showed that the collected data fitted well with the research model. Perceived usefulness was the strongest positive factor effecting behavior intention (β=0.399, P<0.001). Perceived ease of use had no statistically significant effect on behavior intention (β=0.117, P=0.066) but a positive effect on perceived usefulness (β=0.537, P<.001). Perceived risk could be well explained by financial risk (β=0.972, P<.001), privacy risk (β=0.774, P<.001), social risk (β=0.871, P<.001), time risk (β=0.894, P<0.001), and psychological risk (β=0.774, P<.001). Perceived risk had negative effects on perceived usefulness (β=-0.375, P<0.001) and behavior intention (β=-0.297, P<.001). Personal innovativeness had a positive influence on perceived ease of use (β=0.241, P<.001) and a slight effect on behavior intention (β=0.124, P=0.001). Age(CMIN=133.457, P<.001) and usage experience(CMIN=82.495, P=.019) had a significantly slight moderation effect on the paths. Perceived usefulness and perceived risk have significant effects on public intention to use e-consultation. Therefore, platform and manufacturer must improve the function of e-consultation, which will promote the public intention to use e-consultation fundamentally. And to control the perceived risk of public, government should play an important role in enforcing management of e-consultation markets and approving corresponding medical insurance policies. Besides, personal innovativeness had an effect on behavior intention. And the path of factors had differences among different characteristic people. Therefore, it is necessary to adjust the strategies to fit more groups better.
BACKGROUND E-consultation enables patients to communicate with doctors about the symptom, development, treatment, and other information on their diseases. E-consultation is expected to improve the information level of patients, affect patients’ subsequent judgments of medical services, and become one of the means to guide patients to make a reasonable medical selection in the future. However, e-consultation use is low at this stage, and research on its influence mechanism on patients’ medical selection is also limited. Thus, the procedure of how to effectively apply e-consultation to guide patients to seek reasonable medical services is still unsatisfactory. OBJECTIVE To explore the changes in first-visit patients’ understanding of disease and medical resources after e-consultation, as well as the choice of follow-up medical services. METHODS Based on the expected utility theory, information asymmetry theory, and advantageous selection theory, the theoretical hypothesis that e-consultation affects first-visit patients’ medical selection was developed. The patients’ medical selection before and after e-consultation was compared using a scenario survey. Based on the service characteristics of the e-consultation platform, representative simulation scenarios were determined, and parallel control groups were set up considering the order effect in comparison. Finally, a total of four scenario simulation questionnaires were designed. A total of 4,164 valid questionnaires were collected through the online questionnaire collection platform. Patients’ perception of disease severity, evaluation of treatment capacity of medical institutions, selection of hospitals and doctors, and other outcome indicators were tested to analyze the differences in patients’ evaluation and choice of medical services before and after e-consultation. Additionally, the results’ stability was tested by regression analysis. RESULTS In the mild cases, before e-consultation, only 14.4% of patients considered their conditions as not serious. After e-consultation, 71.5% considered their diseases as mild, and participants’ evaluation of the disease treatment capacity of medical institutions at all levels had improved. In the severe cases, before e-consultation, 55.4% of the participants believed their diseases were very serious. After e-consultation, 25.1% considered their diseases were very serious. The evaluation of disease treatment capacity of medical institutions in non-tertiary hospitals decreased, whereas that of tertiary hospitals was improved. In both the mild and severe cases, before e-consultation, all of the participants were inclined to directly visit the hospital. After e-consultation, more than 70% of the mild patients chose self-treatment, whereas the severe cases still opted for a face-to-face consultation. After e-consultation, patients who were set on being treated in a hospital, regardless of the disease severity, preferred to select the tertiary hospitals. Of the mild patients who chose to go to a hospital, 28.6% wanted to consult online doctors face-to-face. In contrast, 59.3% of the severe cases wanted to consult online doctors face-to-face. CONCLUSIONS E-consultation can help patients accurately enhance their awareness of the disease and guide them to make a more reasonable medical selection. However, it is likely that e-consultation makes online medical services centralized. Additionally, the guiding effect of e-consultation is limited, and e-consultation needs to be combined with other supporting systems conducive to medical selection to play an improved role.
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