Telemedicine and e-Health最新文献

{"title":"A Retrospective Secondary Data Analysis of Telemedicine Service Utilization (2020-2023) Among Patients Covered By The Universal Coverage Scheme in Thailand.","authors":"Nitichen Kittiratchakool, Thanayut Saeraneesopon, Chotika Suwanpanich, Thanakit Athibodee, Patiphak Namahoot, Tanasak Kaewchompoo, Piyada Gaewkhiew, Suthasinee Kumluang, Tanainan Chuanchaiyakul, Sichen Liu, Wanrudee Isaranuwatchai","doi":"10.1089/tmj.2024.0140","DOIUrl":"https://doi.org/10.1089/tmj.2024.0140","url":null,"abstract":"<p><p><b>Objective:</b> The National Health Security Office in Thailand introduced a telemedicine program called \"Telehealth/Telemedicine\" in December 2020, which aimed to reimburse telemedicine services for patients with stable chronic diseases under the Universal Coverage Scheme (UCS). The current study investigated patient characteristics and trends in telemedicine service utilization under the UCS in Thailand and examined the impact of COVID-19 outbreaks on telemedicine services. <b>Methods:</b> A retrospective secondary data analysis using e-claim data from December 1, 2020, to April 18, 2023, was conducted. The analytical methods included descriptive analysis and an interrupted time series analysis. <b>Results:</b> During ∼29 months, 110,153 unique patients used telemedicine services, leading to a total of 259,047 visits. The average age was 54 years, and most of patients were female (57%). Hypertension was the most common diagnosis for patients receiving telemedicine services. Patients with mental health conditions often engaged in telemedicine consultation with drug delivery. During the Delta and Omicron outbreaks, telemedicine service utilization significantly increased compared with that in any nonpandemic periods within the 29-month timeframe (odds ratio [OR]: 3.85, <i>p</i>-value <0.01; OR: 2.55, <i>p</i>-value <0.01). <b>Conclusions:</b> The study findings highlight the initial trend of telemedicine services in Thailand from the start of the COVID-19 pandemic to the beginning of the post-COVID-19 period. As telemedicine will play a critical role in the future of health care, this information can support the scale-up of telemedicine, including monitoring and evaluation plans, to help improve the efficiency of the system.</p>","PeriodicalId":54434,"journal":{"name":"Telemedicine and e-Health","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142127363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patient- and Provider-Level Factors Associated with Patient Portal Usage Among Medicaid Recipients.","authors":"Omolola E Adepoju, Summer Chavez, Gabriella Tavera, Andy Castaneda","doi":"10.1089/tmj.2024.0194","DOIUrl":"10.1089/tmj.2024.0194","url":null,"abstract":"<p><p><b>Background:</b> Patient portals can improve access to electronic health information and enhance patient engagement. However, disparities in patient portal utilization remain, affecting disadvantaged communities disproportionately. This study examined patient- and provider-level factors associated with portal usage among Medicaid recipients in a large federally qualified health center (FQHC) network in Texas. <b>Methods:</b> Deidentified electronic medical records of patients 18 years or older from a large Texas FQHC network were analyzed. The dependent variable was a binary flag indicating portal usage during the study period. Independent variables included patient- and provider-level factors. Patient-level factors included sociodemographic, geographic, and clinical characteristics. Provider characteristics included primary service line, provider type, provider language, and years in practice. Because the analysis was at the individual level, a multivariable logistic regression model focused on adjusted associations between independent variables and portal usage. <b>Results:</b> The analytic sample consisted of 9,271 individuals. Compared with individuals 18-39 years, patients 50 years and older had lower odds (50-64 OR: 0.60, <i>p</i> < 0.001; 65+ OR: 0.51, <i>p</i> < 0.001) of portal usage. Males were less likely to use portals (OR: 0.44, <i>p</i> = 0.03), and compared to Non-Hispanic Whites, Non-Hispanic Black (OR: 0.86, <i>p</i> = 0.02) and Hispanics (OR: 0.83, <i>p</i> < 0.001) were significantly less likely to use portals. Individuals with 1 or more telemedicine consults had a two-times greater odds of portal usage (OR: 1.97, <i>p</i> < 0.001). Compared to individuals who had clinic visits in December 2018, portal usage was significantly higher in the pandemic months (March 2020-November 2020, all <i>p</i>'s < 0.01). Importantly, the behavioral health service line had the greatest odds (OR: 1.52, <i>p</i> < 0.001), whereas the dental service line had the lowest odds (OR: 0.69, <i>p</i> = 0.01) compared to family practice. No other provider characteristics were significant. <b>Conclusion:</b> Our finding of significant patient-level factors is important and can contribute to developing appropriate patient-focused health information technology approaches to ensure equitable access and maximize the potential benefits of patient portals in health care delivery.</p>","PeriodicalId":54434,"journal":{"name":"Telemedicine and e-Health","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141472681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of m-Health-Based Interventions on Blood Pressure: An Updated Systematic Review with Meta-Analysis.","authors":"Antonio Cleilson Nobre Bandeira, Paulo Urubatan Gama de Melo, Eduardo Braghini Johann, Raphael Mendes Ritti-Dias, Cassiano Ricardo Rech, Aline Mendes Gerage","doi":"10.1089/tmj.2023.0545","DOIUrl":"10.1089/tmj.2023.0545","url":null,"abstract":"<p><p><b>Background:</b> In recent years, the integration of mobile health (m-Health) interventions has garnered increasing attention as a potential means to improve blood pressure (BP) management in adults. This updated systematic review with meta-analysis aimed to identify the effect of m-Health-based interventions on BP in adults and to evaluate the effect of m-Health on BP according to the characteristics of subjects, interventions, and countries. <b>Methods:</b> The search was carried out in PubMed, Embase, ResearchGate, and Cochrane databases in January 2022. Study selection and data extraction were performed by two independent reviewers. For analysis, random effects models were used with a confidence interval (CI) of 95% and <i>p</i> < 0.05. <b>Results:</b> Fifty studies were included in this review and in the meta-analysis. Interventions with m-Health reduced systolic BP in 3.5 mmHg (95% CI -4.3; -2.7; <i>p</i> < 0.001; <i>I</i>² = 85.8%) and diastolic BP in 1.8 mmHg (95% CI -2.3; -1.4; <i>p</i> < 0.001; <i>I</i>² = 78.9%) compared to usual care. The effects of m-Health interventions on BP were more evident in men and in older adults, in interventions lasting 6-8 weeks, with medication reminders, with the possibility of insertion of BP values (<i>p</i> < 0.05). <b>Conclusion:</b> The results of this study support the effectiveness of m-Health in reducing BP when compared to standard care. However, these effects are dependent on the characteristics of the subjects and interventions. Given the substantial heterogeneity among the results of this systematic review with meta-analysis, its interpretation should be cautious. Future research on this topic is warranted.</p>","PeriodicalId":54434,"journal":{"name":"Telemedicine and e-Health","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141472700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Telemedicine in Post-Exposure Prophylaxis to Biological Material During the COVID-19 Pandemic: Impact on Care and Outcome Indicators.","authors":"Flávio Henrique de Holanda Lins, Maria Júlia Gonçalves de Mello, Tiago Pessoa Lima, Suely Arruda Vidal","doi":"10.1089/tmj.2024.0041","DOIUrl":"10.1089/tmj.2024.0041","url":null,"abstract":"<p><p><b>Introduction:</b> The restrictions on face-to-face care for exposure to biological material during the COVID-19 pandemic required alternatives to maintain outpatient assistance. This study evaluated the impact of telemedicine on care and outcome indicators of a reference service for exposure to biological material during the COVID-19 pandemic. <b>Methods:</b> This pre- and post-study compared the effectiveness of telemedicine in the Hospital Correia Picanço in Recife (Pernambuco, Brazil) before (August 2018 to January 2019 [P1]) and during the COVID-19 pandemic (August 2020 to January 2021 [P2]). Individuals above 18 years old exposed to biological material who sought the service during P1 or P2 were included in the study. <b>Results:</b> A total of 4,494 cases were assessed (1,997 in P1 and 2,497 in P2), mostly because of sexual exposure (62.3%). The mean age was 32.2 ± 9.2 years, most individuals were male (64.9%), originated from Recife (56.6%), and the education level was up to 12 years (53.7%). P2 presented 43% more attendances and shorter intervals between the exposure and first attendance (51%), first testing (28%), and discharge (10%) than P1 (<i>p</i> < 0.05), and cases had no difference in discharge rate (<i>p</i> = 0.339). Cases of sexual exposure had the highest dropout rate in both periods. <b>Conclusion:</b> Telemedicine maintained similar outcomes to face-to-face care and improved the indicators, increasing the mean monthly attendance and reducing the time between exposure and follow-up.</p>","PeriodicalId":54434,"journal":{"name":"Telemedicine and e-Health","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141447633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Deblurring in Teledermatology: Deep Learning Models Restore the Accuracy of Blurry Images' Classification.","authors":"Hsu-Hang Yeh, Benny Wei-Yun Hsu, Sheng-Yuan Chou, Ting-Jung Hsu, Vincent S Tseng, Chih-Hung Lee","doi":"10.1089/tmj.2023.0703","DOIUrl":"10.1089/tmj.2023.0703","url":null,"abstract":"<p><p><b>Background:</b> Blurry images in teledermatology and consultation increased the diagnostic difficulty for both deep learning models and physicians. We aim to determine the extent of restoration in diagnostic accuracy after blurry images are deblurred by deep learning models. <b>Methods:</b> We used 19,191 skin images from a public skin image dataset that includes 23 skin disease categories, 54 skin images from a public dataset of blurry skin images, and 53 blurry dermatology consultation photos in a medical center to compare the diagnosis accuracy of trained diagnostic deep learning models and subjective sharpness between blurry and deblurred images. We evaluated five different deblurring models, including models for motion blur, Gaussian blur, Bokeh blur, mixed slight blur, and mixed strong blur. <b>Main Outcomes and Measures:</b> Diagnostic accuracy was measured as sensitivity and precision of correct model prediction of the skin disease category. Sharpness rating was performed by board-certified dermatologists on a 4-point scale, with 4 being the highest image clarity. <b>Results:</b> The sensitivity of diagnostic models dropped 0.15 and 0.22 on slightly and strongly blurred images, respectively, and deblurring models restored 0.14 and 0.17 for each group. The sharpness ratings perceived by dermatologists improved from 1.87 to 2.51 after deblurring. Activation maps showed the focus of diagnostic models was compromised by the blurriness but was restored after deblurring. <b>Conclusions:</b> Deep learning models can restore the diagnostic accuracy of diagnostic models for blurry images and increase image sharpness perceived by dermatologists. The model can be incorporated into teledermatology to help the diagnosis of blurry images.</p>","PeriodicalId":54434,"journal":{"name":"Telemedicine and e-Health","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141460710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Types and Effects of Telenursing in Home Health Care: A Systematic Review and Meta-Analysis.","authors":"Minji Mun, Youngsun Park, Jinkyoung Hwang, Kyungmi Woo","doi":"10.1089/tmj.2023.0188","DOIUrl":"10.1089/tmj.2023.0188","url":null,"abstract":"<p><p><b><i>Purpose:</i></b> <i>This systematic review aimed to identify the types and effectiveness of telenursing in home health care (HHC) compared to conventional HHC.</i> <b><i>Methods:</i></b> <i>This study followed the Preferred Reporting Items for Systematic Review and Meta-Analysis 2020 guidelines. A random-effects meta-analysis was performed. The risk of bias was assessed using the Risk of Bias 2.0 tool. The quality of bias was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation system.</i> <b><i>Results:</i></b> <i>A total of 17 studies published between 2003 and 2022 were included in the review. The majority of the targeted health conditions of the patients were chronic obstructive pulmonary disease or congestive heart failure (70%). We categorized telenursing interventions according to different technology (</i>N<i> = 4) and nursing (</i>N<i> = 7) types. Among the identified types of nursing, fundamental nursing to monitor patients' symptoms was the most representative. Telemonitoring was found to be the most common technology type, followed by synchronous technology using video or telephone. The telenursing outcomes, including health care utilization, physiological/psychological outcomes, and quality of life, varied. In the meta-analysis, participants who received telenursing reported fewer hospital admissions (standardized mean difference [SMD]: -0.18; confidence interval [95% CI]: -0.43 to -0.02) and emergency department visits (SMD: -0.28; 95% CI: -0.45 to -0.10).</i> <b><i>Conclusion:</i></b> <i>Telenursing in HHC tends to improve the quality of life and could result in many benefits, including a reduction in health care utilization and facilitating the management of chronic diseases. These results ultimately represent the potential effectiveness of telenursing in community health care settings.</i></p>","PeriodicalId":54434,"journal":{"name":"Telemedicine and e-Health","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10245037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Telemental Health Uptake and Associated Health Care Resource Implications among Mississippi Medicaid Enrollees with Major Depression.","authors":"Yunxi Zhang, Maria T Peña, Lincy S Lal, Yueh-Yun Lin, Richard L Summers, Chandra Saurabh, J Michael Swint","doi":"10.1089/tmj.2024.0112","DOIUrl":"10.1089/tmj.2024.0112","url":null,"abstract":"<p><p><b>Objective:</b> Investigate the association between Telemental Health (TMH) uptake and sociodemographic characteristics, and how TMH uptake relates to health care resource utilization and Medicaid expenditures among Mississippi Medicaid enrollees with major depression. <b>Methods:</b> A retrospective cohort study was conducted (2019-2020), comparing those who utilized TMH and those who did not. <b>Results:</b> Among the 21,239 identified enrollees, 806 (3.79%) utilized TMH. The TMH cohort was more likely to be of older age, non-Hispanic White, comprehensive managed care organization enrollees, rural residents, and from areas with a higher area deprivation index, and have higher Charlson comorbidity index scores. The TMH cohort also exhibited higher mental health-related and all-cause outpatient and emergency department utilization, along with higher Medicaid expenditures. <b>Conclusion:</b> As the first study investigating telehealth utilization among Mississippi Medicaid enrollees, this study highlights sociodemographic disparities in telehealth adoption. Addressing barriers hindering telehealth adoption among vulnerable populations and ensuring the availability of quality data are vital for future research.</p>","PeriodicalId":54434,"journal":{"name":"Telemedicine and e-Health","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141460709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interdependence on Technology and Voltage!","authors":"Charles R Doarn","doi":"10.1089/tmj.2024.0447","DOIUrl":"https://doi.org/10.1089/tmj.2024.0447","url":null,"abstract":"","PeriodicalId":54434,"journal":{"name":"Telemedicine and e-Health","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142301102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Telepharmacy in Indonesia: Navigating Knowledge, Perception, and Readiness Among 6,000 Pharmacists and Related Sociodemographic Determinants.","authors":"Ikhwan Yuda Kusuma, Hiba F Muddather, Arie Arizandi Kurnianto, Muh Akbar Bahar, Khamdiyah Indah Kurniasih, Kevin Efrain Tololiu, Zsuzsanna Schelz, István Zupkó, Maria Matuz, Ria Benkő","doi":"10.1089/tmj.2023.0657","DOIUrl":"10.1089/tmj.2023.0657","url":null,"abstract":"<p><p><b>Introduction:</b> Telepharmacy can improve the delivery of pharmaceutical care services to patients. However, there are limited data regarding the knowledge, perceptions, and readiness (KPR) for telepharmacy in Indonesia. In this cross-sectional survey study, we assessed KPR and associated factors among Indonesian pharmacists, aiming to implement telepharmacy services in the future. <b>Methods:</b> Eligible participants were recruited from all provinces of Indonesia through a 24-item instrument. KPR scores were classified as low, moderate, and high. Sociodemographic characteristics and KPR of participants were summarized using descriptive statistics. Bivariate/multivariate ordinal logistic regression analyses were conducted to identify independent determinants of KPR. An adjusted odds ratio (AOR) with a 95% confidence interval (CI) was calculated for each determinant. <b>Results:</b> A total of 6,059 pharmacists provided responses. Overall, 58.28% had a high knowledge score, and 63.51% expressed moderate perceptions toward telepharmacy services. Moreover, 70.21% showed a moderate level of readiness. Gender (male; AOR: 1.21 [95% CI: 1.06-1.39]), stable internet access (AOR: 0.75 [95% CI: 0.64-0.86]), and central region (AOR: 1.13 [95% CI: 0.99-1.29]) were significantly associated with perception toward telepharmacy. Readiness was significantly associated with age (17-25 years; AOR: 0.73 [95% CI: (0.60-0.89]), gender (male; AOR: 0.83 [95% CI: 0.72-0.95]), stable internet access (AOR: 0.75 [95% CI: 0.64-0.89]), education level (master/doctoral; AOR: 1.33 [95% CI: 1.06-1.67]), and central region (AOR: 1.29 [95% CI: 1.12-1.49]). Interestingly, knowledge levels were not significantly correlated with specific factors. <b>Conclusions:</b> Participants demonstrated high knowledge, without significant influencing factors. However, they showed moderate perceptions and readiness levels, influenced by sociodemographic factors, including gender, age, education level, internet access, and regional disparities. Therefore, targeted interventions (e.g., telepharmacy training and regional outreach) are imperative to enhancing perceptions and readiness, fostering the effective integration of telepharmacy services, and advancing pharmaceutical care in Indonesia.</p>","PeriodicalId":54434,"journal":{"name":"Telemedicine and e-Health","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141452197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Family Support in Transgender and Gender-Diverse Young Adults Seeking Telehealth for Hormone Therapy.","authors":"Jae Downing, Michael Cunetta, Gina M Sequeira, Jerrica Kirkley, Moira Kyweluk","doi":"10.1089/tmj.2023.0423","DOIUrl":"10.1089/tmj.2023.0423","url":null,"abstract":"<p><p><b>Background:</b> Family support (FS) is a key social determinant of health for transgender and gender-diverse (TGD) young adults. We examined the association between FS and health outcomes in young adults seeking gender-affirming hormone therapy (GAHT) from a US telehealth service. <b>Methods:</b> Cross-sectional data from TGD young adults ages 18-24 (<i>n</i> = 7,740) who provided demographic information and information on FS at intake were analyzed. Relationships between FS, geography, insurance status, rates of depression, and smoking status were examined. <b>Results:</b> Less than half of respondents reported having FS. Patients with FS reported lower rates of depression and higher incidence of previous gender-affirming medical care (e.g., hormone therapy, surgeries), had lower rates of being uninsured, and were more likely to reside in the Northeast or Western United States. Young adults assigned female at birth had higher rates of FS. <b>Conclusion:</b> FS may mitigate mental health disparities in TGD young adults including rates of depression. FS and insurance status are closely related in a geographically diverse population seeking telehealth services. The finding underscores the importance of FS as a social determinant of health and the unique characteristics of patients seeking telehealth services.</p>","PeriodicalId":54434,"journal":{"name":"Telemedicine and e-Health","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141447631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}