Telemedicine and e-Health最新文献

Background: e-Health programs to empower patients with advanced cancer and their family caregivers can improve their quality of life. Successful engagement with e-Health programs requires digital competence. People with lower digital competence might be less likely to participate and complete e-Health trials, affecting trial validity. The objective of this work was to explore how digital competences differ between individuals according to sociodemographic characteristics and how it influences participation and retention in a trial with an e-Health component. Methods: We analyzed data collected as part of the Dyadic Psychoeducational Interventions for patients with advanced cancer and their Informal Caregivers DIAdIC (DIAdIC) trial, in which a psychoeducational web and face-to-face program for patients with advanced cancer and their family caregivers were developed and tested. Recruitment log files were quantitatively assessed for nonparticipation reasons. Descriptive statistics outlined sociodemographic factors and digital competence. Multivariable linear regressions assessed digital competence. We reported unstandardized coefficients, 95% confidence intervals, and p-values. Logistic regressions examined retention rates. We reported odds ratios and 95% confidence intervals. Results: Among those refusing participation in the trial (N = 1752), 2.1% (n = 37) cited information and communication technology (ICT)-related factors. Enrolled patients reported lower digital competence than family caregivers (mean 3.07, SD 0.94 vs. 3.17, SD 0.090; p = 0.046). While digital competence varied by sociodemographic characteristics of patients and their family caregivers, digital competence did not significantly predict dropout. Conclusion: ICT-related factors were rarely mentioned as a reason for nonparticipation. Digital competence is associated with sex, age, trial location, educational attainment, and perception of income. e-Health-related factors or digital competence are no reasons for nonparticipation in studies with an e-Health component.

Introduction: Telemedicine has seen rapid growth, especially following the COVID-19 pandemic, providing diverse options for patient care. This study, grounded in the Technology Acceptance Model, examines and compares factors influencing women's usage intentions of telemedicine, considering their roles as both direct patients in gynecology and indirect patients in pediatrics. Methods: The study conducted a survey to collect data from women who have used telemedicine services (N = 758). Structural equation modeling was employed to assess the relationships between variables, including previous satisfaction, social media health content consumption, perceived ease of use (PEOU), perceived usefulness (PU), trust, and future usage intention. Results: The results demonstrate that social media health content consumption, PEOU, PU, and trust in telemedicine have significant direct effects on future usage intention. PEOU and trust mediate the relationships between social media consumption, previous satisfaction, and future usage intention. Notably, the study reveals differences in the factors influencing telemedicine usage between pediatrics and obstetrics/gynecology. Social media health content consumption positively affects usage intention for gynecological but not for pediatric. Trust in telemedicine significantly enhances usage intentions for gynecology but not for pediatrics. Conclusions: The findings reveal disparities in telemedicine usage patterns between obstetrics/gynecology and pediatrics. Practical implications suggest that telemedicine platforms should leverage social media to enhance health education and provide clear guidance, particularly for gynecological services. In addition, strengthening patient privacy protections is essential to build trust and promote telemedicine adoption.

Introduction: Online self-triage/symptom checkers are a relatively new e-Health modality. We aimed to evaluate the degree to which patient's chosen symptom during the use of an online self-triage tool was congruent with that chosen by a nurse performing phone triage. Methods: Patient encounters from September 1, 2022, to September 30, 2023, were reviewed for patients who completed both online self-triage and a subsequent nursing phone triage within 24 hours. The symptoms chosen by the patient for their self-triage encounter and the symptoms chosen by the nurse during the subsequent nurse triage were reviewed. The symptoms chosen in these two triage encounters were then compared for congruency. A subset of our database was evaluated for congruency between the self-triage and the nurse phone triage endpoint recommendations. Results: There were 5,443 encounters meeting inclusion criteria to study for congruency between self-triage and nurse triage symptom choice. The range of time between self-triage and nurse triage ranged from 0 min to 1,439 min (23.9 hours) with a median of 23 minutes between self and nurse triage encounters. Symptom congruency between the two methods found 74.2% (4,038) to be completely congruent while 989 (18.2%) were somewhat congruent. Only 7.6% (416) had no apparent congruency. Out of 1,705 self and nurse triage dyads eligible for study for agreement between endpoint recommendations, 244 (14.3%) were under-triaged, 1,110 (65.1%) were triaged to the same level of care and 351 (20.6%) were over-triaged. Conclusion: Congruency between symptoms chosen by the patient for triage and nurse triage were highly congruent with only 7.6% of the sample showing no apparent congruency between the self-triage symptom and the nurse triage symptom. When compared to nurse triage, most self-triage endpoint recommendations were either triaged to the same level of care or were over-triaged to a higher level of care.

Introduction: Long waiting lists for elective medical consultations present significant challenges within health care systems globally. Remote consultation (teleconsultation) between a primary care physician and a specialist doctor can resolve some of these demands, reducing waiting lists. This study aims to evaluate the effectiveness of teleconsultations in reducing unnecessary specialist referrals and waitlist time within the referral process with primary care doctors. Methods: A retrospective cohort study was conducted from January 2017 to December 2019. The regulation process of specialized consultations waiting lists was made by two groups: (1) those regulated by RegulaSUS associated with the provision of teleconsultation and (2) those regulated by the usual procedures of the Ambulatory Regulation Center of the State of Rio Grande do Sul (contemporaneous controls group). The primary outcome evaluated the proportion of patients managed within primary health care (PHC) without requiring in-person specialist care, and the waitlist times during the regulation process were compared between the different groups. Results: The analysis encompassed 245,643 referral requests for specialized consultations across 23 medical specialties. The RegulaSUS project reduced the need for in-person specialized medical consultation by 29% (31.6% vs. 44.5%, p < 0.001). The median waitlist time was 1,140.4 (interquartile range [IQR], 1,393.6-476.6) days in individuals in the RegulaSUS and 1,271.0 (IQR, 778.4-1,723.0) control (p < 0.0001). Discussion: The RegulaSUS teleconsultations demonstrated an effective approach to increasing the resolution of primary care physicians, reducing unnecessary specialist referrals, and reducing waitlist time for specialized medical consultations. This initiative is a model for efficient referral management, prioritizing patients needing specialized care while optimizing health care resource allocation in PHC settings.

Objective: To characterize organizational and financial factors associated with hospital telemedicine utilization reporting. Methods: We used an explanatory sequential mixed methods design to quantitatively analyze hospital-level data from Medicare Cost Reports (2017-2021) and the American Hospital Association Annual Survey (AHAAS) (2020-2021) to assess telemedicine utilization reporting. Semistructured interviews were conducted with key informants from various health care sectors to contextualize quantitative findings. Results: Among 4,224 nonfederal acute care hospitals in our sample, most were urban (50.7%), not-for-profit (60.3%), and nonteaching hospitals (91.4%). For-profit, southern, and western hospitals were more likely to report telemedicine utilization data to the AHAAS compared to other ownership status and region categories. Qualitative interviews identified six domains that support enhanced telemedicine reporting: (1) resource and infrastructure availability, (2) organizational reporting issues, (3) survey design, (4) reconcilable vendor documentation, (5) lack of reporting requirements, and (6) lack of standardized definitions of telemedicine and telemedicine utilization. Conclusions: Addressing telemedicine reporting barriers is essential for accurate telemedicine utilization measurement and improved health care delivery. Future research should advance robust methodologies for capturing telemedicine utilization and explore the impact of reporting incentives and mandates on data completeness.

Background: Missed appointments adversely affect clinical outcomes, clinic efficiency, and quality of care and could worsen the impact of pediatric workforce shortages on health care access. Telemedicine has the potential to reduce missed appointments. However, interventions that do not account for neighborhood factors could widen disparities. We analyzed the relationship between missed appointments and type of pediatric appointment and the role of telemedicine and neighborhood factors. Methods: This retrospective cohort study used three data sources: (1) electronic health records, (2) American Community Survey, and (3) Housing and Urban Development crosswalk data. The analyses were restricted to pediatric patients (<18 years) with completed or missed outpatient visits (March 2020-December 2022). The outcome was missed appointments. The primary predictors were pediatric visit type, appointment modality, census tract (CT) residential segregation, and CT poverty level. Generalized estimating equations were used. Results: The final sample size was 90,712 appointments for 32,305 unique patients. The overall no-show rate was 20.75%. The no-show rate for general pediatrics was 20.36% and 27.82% for specialty appointments. In multivariable analyses, there was an increased likelihood of missed appointments for pediatric subspecialty appointments compared to general pediatrics (Odds Ratio (OR): 1.62; 95% Confidence Interval (CI): 1.51, 1.74). Telemedicine appointments were associated with a decreased likelihood of missed appointments compared to in-person appointments (OR: 0.41; 95% CI:0.39, 0.44). There was a positive interaction between appointment type and pediatrics visit type with a larger effect for subspecialty visits. Conclusions: Tailored interventions that integrate telemedicine uptake and contextual factors have the potential to reduce missed appointments.

Background: Telehealth has grown as a common treatment modality for substance use disorders following expanded telehealth flexibilities during the COVID-19 pandemic. Telehealth can increase access to treatment in rural areas, where there are limited local addiction providers. Methods: We conducted a cross-sectional survey of adults in telehealth treatment for opioid use disorder and compared satisfaction with care and provider-patient relationship quality between participants in rural and nonrural areas. Results: Respondents scored a mean of 4.51 ± 0.694 on the Telemedicine Satisfaction Questionnaire (range: 1-5) and 27.12 ± 5.633 on the Provider-Patient Depth of Relationship Questionnaire (range: 0-32), indicating high overall satisfaction and a deep provider-patient relationship. There were no significant differences based on rural residence. Conclusions: Based on high patient satisfaction, our findings support the future expansion of telemedicine treatment platforms across rural and nonrural areas to address the substantial unmet need for substance use treatment across the United States.

Background: Mississippi faces significant health disparities and barriers to health care access, particularly in its most rural areas. Telehealth offers a promising solution to address these challenges, but its adoption remains uneven. The purpose of this study was to investigate the potential factors associated with self-reported telehealth utilization among adult Mississippi residents, focusing on individual-, household-, and area-level characteristics. Methods: Data were collected from a state-representative survey of adult Mississippi residents (N = 821) using both online- and phone-based platforms, supplemented with secondary internet quality and local health care access data. A two-stage hurdle regression model was used to examine factors associated with telehealth use and conditional on any use, utilization frequency. A regression estimating associations with the use of in-person medical care was also estimated for comparison purposes. Results: Telehealth use was significantly associated with specific health conditions and health insurance status. However, local internet quality did not significantly impact the likelihood of telehealth use aside from a marginally significant association with local upload speed. Findings suggest that other demographic- and health-related factors may play a more prominent role. We also find differential telehealth utilization rates by region, suggesting that area-level characteristics like health care infrastructure may affect telehealth use likelihood. Conclusions: Telehealth adoption in Mississippi is associated with individual factors like health and insurance status rather than broadband access alone. Efforts to expand telehealth use should also address noninfrastructure barriers, such as digital literacy and awareness, particularly in rural and underserved populations.

Background: Telemedicine has been safely used across various surgical specialties at different stages of outpatient care, with effectiveness measured by clinical outcomes, cost savings, and user satisfaction. When employed for communication between physicians at a referral center and lower-complexity hospitals, it enables quick specialist evaluations for patients with relative emergencies. This study describes the experience of a tertiary care service in managing thoracic surgical conditions through telemedicine case discussions. Methods: This prospective study, from March 2022 to February 2023, focused on teleconsultations with hospitals in the referral area of a public academic hospital. Consultations were conducted synchronously and asynchronously via a proprietary platform. Data were collected on the originating hospital, patient demographics, admission date, diagnosis, and clinical summary. Cost savings were calculated by estimating avoided round-trip ambulance transportation. The analysis included data from the public health system's referral records. Results: Out of 4,386 evaluation requests, 341 (7.7%) were discussed with a thoracic surgery specialist. Of these, 181 (53%) were managed without patient transfer, and 53 required rediscussion to revisit the initial medical approach. Immediate transfer, outpatient evaluation, or surgery was recommended in 160 cases. Conclusion: The incorporation of telemedicine into interhospital regulation of thoracic surgical diseases effectively reduced unnecessary patient transfers while providing the originating service with valuable information for managing specialty-specific situations.

Introduction: Assessing treatment acceptability is critical to understanding patient experiences in clinical trials, especially in telehealth settings where exposure and engagement experiences are unique. However, the use of patient-reported acceptability outcomes in mental health-focused trials has been mixed, with most published studies relying on objective behavior (e.g., dropout rates) or fit-for-use measures, rather than instruments rooted in a specific theoretical model. This study introduces the Program Acceptability Tool for Telehealth (PATT), a novel, theoretically grounded instrument designed to capture patient-reported acceptability in telehealth-based trials. Methods: Here, we describe the initial development and validation of the PATT, including its performance with 123 caregivers participating in an ongoing clinical trial that includes multiple types of interventions and support programs focused on caregiver well-being. Results: The final 12-item PATT demonstrated robust psychometric properties, including high internal consistency (α = 0.82-0.90) and content validity. Convergent validity was established through significant correlations between PATT scores and behavioral engagement metrics. Conclusions: Our findings suggest that the PATT is a reliable, valid tool for capturing patient acceptability, offering a nuanced perspective on program, process, and impact-related experiences. Further validation studies are recommended to confirm the PATT's utility in broader applications.