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. 2025 Apr 16;11:20552076251335379. doi: 10.1177/20552076251335379

Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data

Daisuke Shigemi 1,2,, Rena Toriumi 2, Ai Ohta 2, Saki Nakamura 2, Shunji Suzuki 1
PMCID: PMC12035017  PMID: 40297374

Abstract

Objective

Asynchronous consultations in telehealth provide the convenience of not requiring an appointment. However, some patients may choose to visit a medical facility instead of waiting for a response, and the time delay could negatively affect user satisfaction. This study investigated the relationship between response time and both hospital visits prior to response confirmation, as well as user satisfaction with the service in asynchronous consultations.

Methods

We collected data from a telehealth consulting service in Japan (Sanfujin-ka Online) between July 2021 and June 2023, including consultation content, response times, and post-consultation questionnaires. The primary outcome was hospital visits before response confirmation, and the secondary outcome was satisfaction with the service. A chi-square test and multivariable logistic regression analysis were performed to assess the relationship between response time and these outcomes.

Results

This study included data from 7394 online consultations, with 99.8% of responses provided within 24 h. The multivariable logistic regression analysis revealed no significant association between response time and hospital visits before response confirmation, after adjusting for user age and consultation content. Furthermore, no significant difference was found between the primary outcome and the intention to reuse the service. After using the service, there were no contacts from users or medical institutions related to unexpected sudden changes or serious illnesses.

Conclusion

The response time was not associated with hospital visits before response confirmation in asynchronous online consultation service, which are generally responded to within 24 h, in obstetrics and gynecology.

Keywords: Asynchronous consultations, eHealth, gynecology, obstetrics, telehealth

Introduction

Telehealth in obstetrics and gynecology has been rapidly implemented, driven by recent advancements in information and communication technology (ICT) and the coronavirus disease 2019 (COVID-19) pandemic. 1 Several studies have demonstrated its positive impact on pregnant women's health, including improvements in health behaviors, weight management, mental health issues, and the management of diabetes and hypertensive disorders during pregnancy.27

Online health consultation services have become one of the most prominent forms of telehealth in obstetrics and gynecology, with significant knowledge and experience accumulated over recent years.813 These services can be categorized into two types: synchronous and asynchronous. Synchronous services involve real-time virtual communication with healthcare professionals, while asynchronous services, also known as store-and-forward telehealth, allow healthcare providers to respond later via electronic devices. 14 Asynchronous consultations offer the convenience of not requiring an appointment, which benefits users. However, concerns have been raised that patients may not wait for a response and instead visit a medical facility and that the time delay could negatively impact user satisfaction. These issues have not yet been thoroughly explored in the literature.

We hypothesized that longer response times would be associated with an increase in hospital visits before receiving a response and lower satisfaction with asynchronous online health consultation services. This study analyzed data from a Japanese healthcare company offering an online health consultation service in obstetrics and gynecology.

Methods

Recruitment and data description

This study analyzed data from Kids Public Inc., a Japanese healthcare company that provides an online consultation service in obstetrics and gynecology (Sanfujin-ka Online). The service allows women to consult specialized doctors and midwives about their obstetric and gynecologic concerns, both synchronously and asynchronously, without providing medical services such as diagnosis or prescriptions. As Kids Public Inc. partners with corporations and local governments, all users can access the service free of charge. For asynchronous consultations, responses are typically provided within 24 h. Users were explicitly informed in the terms of use and on the consultation submission screen that “responses may take up to 24 h” and that “this service is not intended to assess the urgency of consultations.” They used the service after agreeing to these terms and conditions.

We collected data from Kids Public Inc.'s asynchronous consultation service between July 2021 and June 2023. The inclusion criteria for the analyzed data were all asynchronous consultations received from users aged 18 years or older during the study period. There were no exclusion criteria. The data included consultation content, response times, and post-consultation questionnaires. The web-based survey was developed by Kids Public Inc., with some authors contributing to its development as members of the company. The survey was not pilot-tested. This voluntary survey was automatically emailed to users one hour after receiving their consultation responses, and users were able to send responses by logging into the service page until the third day of the month following the date of consultation. It was password-protected, and users could complete it online. Response data were automatically recorded in a database. Cookies were not used in the survey, and the IP address of the user's computer was not used. There were no incentives offered to respondents, and they were allowed to skip questions. The survey collected information including hospital visits before receiving a response and user satisfaction with the service. A confirmation screen appeared before the user could submit a response, and the survey never displayed a second time once the user had sent it. All users were required to be over 18 years old, and consent for the anonymous use of their data was obtained from all participants at the time of consultation. The survey used in this study has been included as a Supplemental file.

Data analysis

We conducted an analysis of anonymized data to examine the relationship between response time and both hospital visits before response confirmation and user satisfaction with the service. In this study, the main exposure variable was response time, the primary outcome was hospital visits before response confirmation, and the secondary outcome was satisfaction with the service. Missing values in participants’ characteristics information were treated as missing, and only available data were used for outcome analysis. Response time was categorized as 0–5, 6–11, 12–17, 18–23, and  ≥ 24 h. The intention to reuse, as reported in post-consultation questionnaires, was used as a surrogate measure to evaluate users’ satisfaction. The response options were “Would use again,” “Would somewhat use again,” “Would not really use again,” and “Would not use again.” In the responses to the question about the intention to reuse, the top two responses out of four options were defined as “satisfied.” We considered that the types of consultations received and the characteristics of users differ between obstetrics and gynecology, and analyzed them separately in two groups. A chi-square test was used to compare group proportions, and a multivariable logistic regression analysis was performed with the outcomes as the dependent variables. Other collected information, including user age (categorized as 18–19, 20–29, 30–39, 40–49, 50–59, and  ≥ 60 years), situation (pregnant, postpartum [within 1 year after delivery], or other), image attachment at the time of consultation, and consultation topics, was used as covariates to adjust for user background. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. The model's goodness of fit was assessed using the Hosmer–Lemeshow test. Additionally, all variables included in the multivariable analysis were evaluated for correlations, and the absence of multicollinearity was confirmed.

All statistical analyses were performed using Stata software (version 16.0; StataCorp LP, College Station, TX, USA). All 95% CI and p values were based on two-sided hypothesis tests, where p < 0.05 was considered to denote statistical significance.

Ethical statement

The current study was approved by the Central Ethics Committee and Certified Institutional Review Board of Nippon Medical School (the ethics approval number: M-2024-187). We obtained web-based opt-in consent from participants at each consultation, confirming their agreement to the use of their data for research purposes in a non-identifiable form. However, this was not a written consent. At the time of study initiation, the Institutional Review Board determined that obtaining individual written informed consent was not required. This study adhered to the STROBE guideline and followed the CHERRIES checklist, a valuable guideline for reporting results of web-based surveys. 15

Results

We collected 5010 consultations in obstetrics (2333 during pregnancy and 2677 postpartum) and 2384 consultations in gynecology from July 2021 to June 2023. Table 1 shows the characteristics of the eligible consultations. The overall mean age was 32.3 years in obstetrics and 35.2 years in gynecology. In obstetrics, the most common consultation topics in pregnant cases were general health concerns, medication use, threatened miscarriage, threatened premature labor, and, in postpartum cases, general health concerns, medication use, irregular menstruation, and uterine subinvolution, in descending order. In gynecology, the most frequent topics were irregular menstruation, abnormal uterine bleeding, infertility, and dysmenorrhea, also in descending order.

Table 1.

Participants’ characteristics of each asynchronous online consultation.

Obstetrics Gynecology
Age, years N Percent n Percent
 18–19 7 0.14 54 2.27
 20–29 1380 27.54 621 26.05
 30–39 3334 66.55 1027 43.08
 40–49 287 5.73 481 20.18
 ≥50 2 0.04 201 8.43
Perinatal situation
 Pregnant, weeks
 <16 864 37.03 - -
 16–27 821 35.19 - -
 28–36 467 20.02 - -
 ≥37 2 0.09 - -
 missing 179 7.67 - -
 Postpartum, months
 0–2 976 36.46 - -
 3–5 573 21.40 - -
 6–8 319 11.92 - -
 9–11 243 9.08 - -
 ≥12 546 20.40 - -
 missing 20 0.75 - -
Total 5010 100 2384 100

Table 2 presents the response times for all consultations. In obstetrics, 37% of responses were provided within 0–5 h, 35% within 6–11 h, 20% within 12–17 h, 8% within 18–23 h, and 0.2% took over 24 h. In gynecology, 39% of responses were provided within 0–5 h, 35% within 6–11 h, 20% within 12–17 h, 7% within 18–23 h, and 0.1% took over 24 h.

Table 2.

Response time among all consultations.

Obstetrics Gynecology
Number Percent Number Percent
Response time, hours
 0–5 1860 37.13 922 38.67
 6–11 1727 34.47 828 34.73
 12–17 1022 20.40 465 19.51
 18–23 391 7.80 167 7.01
 ≥24 10 0.20 2 0.08
Total 5010 100 2384 100

Table 3 shows the association between response time and hospital visits before response confirmation among consultations with completed questionnaires. The post-use survey response rate was 40.0%. In both obstetrics and gynecology, the largest group received responses within 0–5 h (37.9% and 40.1%, respectively). No significant differences in the incidence of hospital visits were observed between different response times (p = 0.773 and p = 0.257). In addition, there were no contacts from users or medical institutions related to unexpected sudden changes or serious illnesses after using the service.

Table 3.

Association between response time and hospital visit among consultations with questionnaire response.

Obstetrics Gynecology
Hospital visit Total p-value Hospital visit Total p-value
Response time, hours No Yes 0.773 No Yes 0.257
 0–5 707 50 (6.6%) 757 352 33 (8.6%) 385
 6–11 640 40 (5.9%) 680 316 16 (4.8%) 332
 12–17 364 28 (7.1%) 392 162 11 (6.4%) 173
 18–23 150 13 (8.0%) 163 65 4 (5.8%) 69
 ≥ 24 4 0 (0.0%) 4 0 0 (0.0%) 0
Total 1865 131 (6.6%) 1996 895 64 (6.7%) 959

Table 4 shows the results of the multivariable logistic regression analysis of the primary outcomes. No significant association between response time and the outcome incidence was observed after adjusted by user age and contents of consultation.

Table 4.

The multivariable logistic regression analysis of hospital visit depending on response time.

Obstetrics Gynecology
Response time, hours OR 95% CIs OR 95% CIs
0–5 ref. ref.
6–11 0.92 0.58–1.47 0.52 0.26–1.03
12–17 1.14 0.68–1.94 0.65 0.29–1.42
18–23 1.27 0.65–2.49 0.52 0.15–1.78
≥24 1(omitted) 1(omitted)

CI: confidence interval; OR: odds ratio.

The results were adjusted for covariates, including user age, situation (pregnant, postpartum, other), image attachment and consultation topics.

Table 5 shows the association between the users’ satisfaction and hospital visits before response confirmation. No significant difference was observed between the primary outcome and the users’ satisfaction (99.2% vs 99.6% in obstetrics and 100% vs 99.3% in gynecology).

Table 5.

Association between users’ satisfaction and hospital visit before response confirmation.

Obstetrics Gynecology
Users’ satisfaction Total p-value Users’ satisfaction Total p-value
Hospital visit No Yes 0.458 No Yes 0.663
 No 8 1854 (99.57%) 1862 6 884 (99.33%) 890
 Yes 1 130 (99.24%) 131 0 63 (100%) 63
Total 9 1984 (99.55%) 1993 6 947 (99.37%) 953

The intention to reuse, as reported in post-consultation questionnaires, was used as a surrogate measure to evaluate users’ satisfaction. The response options were “Would use again,” “Would somewhat use again,” “Would not really use again,” and “Would not use again.” In the responses to the question about intention to reuse, the top two responses out of four options were defined as “satisfied.”

Discussion

Principal findings and comparison with prior work

We analyzed data from 7394 online consultations, and 99.8% of responses were provided within 24 h. No significant association between response time and hospital visits before response confirmation was observed after adjusting for user age and consultation content. Additionally, there was no significant difference between the primary outcome and the intention to reuse the service.

Previous studies on asynchronous online consultations are scarce, and no studies were identified that analyzed the relationship between response time and consultation behavior or satisfaction. A review on asynchronous technologies in mental health care reported that asynchronous telepsychiatry provides positive outcomes in the clinician-to-patient model with demonstrated feasibility, outcomes, and patient satisfaction. 16 However, the review study did not specifically examine variations in response times. Based on the results of the present study, asynchronous online consultations are unlikely to increase visits to medical institutions before receiving a response, as long as responses are generally provided within 24 h and this expectation is clearly communicated to users. On the other hand, some users visited medical institutions before receiving a response, despite the short response time. The reasons for this are unclear, but it is speculated that some users expected a response within a few hours, or that sudden changes in their condition occurred after submitting their consultations. Developing a system to better understand the reasons for such visits would be valuable for future research.

We hypothesized that different consultation topics might have varying levels of urgency, potentially leading to differences in the proportion of medical visits before receiving a response. However, in the present study, even after adjusting for consultation topics, no significant association was found between response time and visits to medical facilities. The online consultation service clearly informed users that consultations related to urgent medical needs or acute and serious conditions were not appropriate for this platform. This clear communication may have helped manage users’ expectations, contributing to the observed results. 17 Furthermore, this pre-adjustment of users’ expectations may have prevented a noticeable decline in post-use satisfaction, regardless of whether a medical visit occurred before receiving a response.

The strength of this study lies in its novel analysis of the relationship between response time and medical visits in asynchronous telemedicine consultations—a topic with few prior studies. This paper offers valuable insights for the future growth of telehealth. Additionally, the lack of a clear relationship between response time and user satisfaction suggests that other factors may play a more significant role in determining satisfaction. Future research should aim to identify these factors and explore how the healthcare provider's response contributes to user comfort and overall satisfaction. In addition, we would like to conduct more long-term prognostic studies.

Limitations

This study has several limitations. First, the generalizability of the findings may be limited due to the use of data from a single service provider specializing in the provision of online consultation services. However, since the users came from over 200 municipalities and businesses across various regions of Japan, the diversity of the user base suggests a reasonable degree of generalizability for physicians and organizations specializing in providing such services. In addition, second, the age range of the users was restricted. Since most participants were in their 20s to 40s, it remains unclear whether these results can be extended to younger individuals in their teens or to those in their 50s and older. Third, the survey response rate was 40.0% (2955/7394), which may not fully capture the behavioral patterns of all service users. In addition, the primary outcome was collected solely through self-reports in the questionnaire, which may introduce recall bias. However, as the questionnaire was sent one hour after the physician's response, and most participants completed it within a day, the potential impact of recall bias was presumed to be small. Fourth, this study is likely influenced by potential selection bias and adherence bias. Generally, users who were more satisfied with the response or had higher digital literacy were more likely to complete the questionnaire. While it is challenging to eliminate the influence of digital literacy, as the use of digital devices is almost essential for online consultations, it can also be interpreted that the results reflect a realistic outcome since individuals who use such services tend to have higher digital literacy. 18 Nonetheless, it is desirable to establish mechanisms in the future to collect broader feedback, including from users who may have been less satisfied with the service. Additionally, it will be important to pursue a service design that is easy to use regardless of digital literacy. Lastly, because the post-use questionnaire was not pilot-tested, the survey questions were not validated to ensure accurate reporting of patients’ hospital visits.

Conclusions

Our analysis suggests that response time may not be associated with hospital visits before response confirmation in asynchronous online consultation service, which are generally responded to within 24 h, in obstetrics and gynecology. In addition, the user's intention to reuse the service may not be associated with hospital visits before response confirmation in situations where user expectations are properly managed.

Supplemental Material

sj-docx-1-dhj-10.1177_20552076251335379 - Supplemental material for Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data

Supplemental material, sj-docx-1-dhj-10.1177_20552076251335379 for Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data by Daisuke Shigemi, Rena Toriumi, Ai Ohta, Saki Nakamura and Shunji Suzuki in DIGITAL HEALTH

sj-docx-2-dhj-10.1177_20552076251335379 - Supplemental material for Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data

Supplemental material, sj-docx-2-dhj-10.1177_20552076251335379 for Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data by Daisuke Shigemi, Rena Toriumi, Ai Ohta, Saki Nakamura and Shunji Suzuki in DIGITAL HEALTH

sj-docx-3-dhj-10.1177_20552076251335379 - Supplemental material for Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data

Supplemental material, sj-docx-3-dhj-10.1177_20552076251335379 for Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data by Daisuke Shigemi, Rena Toriumi, Ai Ohta, Saki Nakamura and Shunji Suzuki in DIGITAL HEALTH

Acknowledgements

We would like to thank all obstetricians and midwives affiliated with Kids Public, Inc. and all study participants for their contributions to the study. We acknowledge the use of ChatGPT for English language editing assistance in the preparation of this manuscript.

Statements and declarations

Ethical considerations: The current study was approved by the Central Ethics Committee and Certified Institutional Review Board of Nippon Medical School. Consent for the anonymous use of data was obtained from all participants at the time of consultation.

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: DS, RT, AO, and SN were employed by Kids Public Inc, Japan. Other author reports no conflicts of interest.

Data availability: The datasets analyzed during the current study are not publicly available for ethical reasons as the data are participants-specific; however, datasets may be available from the corresponding author on reasonable request.

Supplemental material: Supplemental material for this article is available online.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

sj-docx-1-dhj-10.1177_20552076251335379 - Supplemental material for Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data

Supplemental material, sj-docx-1-dhj-10.1177_20552076251335379 for Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data by Daisuke Shigemi, Rena Toriumi, Ai Ohta, Saki Nakamura and Shunji Suzuki in DIGITAL HEALTH

sj-docx-2-dhj-10.1177_20552076251335379 - Supplemental material for Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data

Supplemental material, sj-docx-2-dhj-10.1177_20552076251335379 for Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data by Daisuke Shigemi, Rena Toriumi, Ai Ohta, Saki Nakamura and Shunji Suzuki in DIGITAL HEALTH

sj-docx-3-dhj-10.1177_20552076251335379 - Supplemental material for Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data

Supplemental material, sj-docx-3-dhj-10.1177_20552076251335379 for Evaluation of response time in asynchronous telehealth services in obstetrics and gynecology: A cross-sectional study using a telehealth service user data by Daisuke Shigemi, Rena Toriumi, Ai Ohta, Saki Nakamura and Shunji Suzuki in DIGITAL HEALTH


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