Explore the vast range of titles available.

Policy makers and funding agencies require relevant information on current practices of the use of telemedicine infrastructure and services. Several metrics have been used to describe average use of telemedicine services. None are adequate. To identify and assess a new metric-consultations per site per week (C/S/W). To determine existing usage, all papers and abstracts published between January 2005 and December 2009 in the Journal of Telemedicine and Telecare and Telemedicine Journal and eHealth were reviewed. Pilot studies, research projects, services reporting less than one year's data and teleradiology services were excluded. In total, 210 reports of telemedicine services were identified, 77 of which provided sufficient data to calculate C/S/W. Average use was low, 1.8±3.5 (median 0.7) C/S/W, with 61% of services reporting less than 1 C/S/W and 71% reporting 2 or fewer C/S/W. Studies reporting on data from 2006 to 2009 showed less use (average 1.5±2.3; median 0.7 C/S/W) than earlier reports from 1996 to 2005 (1.7±2.5; median 0.7 C/S/W). The use of this new metric, C/S/W, is proposed as a standard measure of telemedicine service use. The generally low results opens debate about how well current clinical services are used.

BackgroundOne-quarter of U.S. patients do not have a primary care provider or do not have complete access to one. Work and personal responsibilities also compete with finding convenient, accessible care. Telehealth services facilitate patients’ access to care, but whether patients are satisfied with telehealth is unclear.ObjectiveWe assessed patients’ satisfaction with and preference for telehealth visits in a telehealth program at CVS MinuteClinics.DesignCross-sectional patient satisfaction survey.ParticipantsPatients were aged ≥18 years, presented at a MinuteClinic offering telehealth in January–September 2014, had symptoms suitable for telehealth consultation, and agreed to a telehealth visit when the on-site practitioner was busy.Main MeasuresPatients reported their age, gender, and whether they had health insurance and/or a primary care provider. Patients rated their satisfaction with seeing diagnostic images, hearing and seeing the remote practitioner, the assisting on-site nurse’s capability, quality of care, convenience, and overall understanding. Patients ranked telehealth visits compared to traditional ones: better (defined as preferring telehealth), just as good (defined as liking telehealth), or worse. Predictors of preferring or liking telehealth were assessed via multivariate logistic regression.Key resultsIn total, 1734 (54 %) of 3303 patients completed the survey: 70 % were women, and 41 % had no usual place of care. Between 94 and 99 % reported being “very satisfied” with all telehealth attributes. One-third preferred a telehealth visit to a traditional in-person visit. An additional 57 % liked telehealth. Lack of medical insurance increased the odds of preferring telehealth (OR = 0.83, 95 % CI, 0.72–0.97). Predictors of liking telehealth were female gender (OR = 1.68, 1.04–2.72) and being very satisfied with their overall understanding of telehealth (OR = 2.76, 1.84–4.15), quality of care received (OR = 2.34, 1.42–3.87), and telehealth’s convenience (OR = 2.87, 1.09–7.94)ConclusionsPatients reported high satisfaction with their telehealth experience. Convenience and perceived quality of care were important to patients, suggesting that telehealth may facilitate access to care.

eHealth is developing rapidly and brings with it a promise to reduce social health inequalities (SHIs). Yet, it appears that it also has the potential to increase them. The general objective of this review was to set out how to ensure that eHealth contributes to reducing SHIs rather than exacerbating them. This review has three objectives: (1) identifying characteristics of people at risk of experiencing social inequality in health; (2) determining the possibilities of developing eHealth tools that avoid increasing SHI; and (3) modeling the process of using an eHealth tool by people vulnerable to SHI. Following the EPPI approach (Evidence for Policy and Practice of Information of the Institute of Education at the University of London), two databases were searched for the terms SHIs and eHealth and their derivatives in titles and abstracts. Qualitative, quantitative, and mixed articles were included and evaluated. The software NVivo (QSR International) was employed to extract the data and allow for a metasynthesis of the data. Of the 73 articles retained, 10 were theoretical, 7 were from reviews, and 56 were based on empirical studies. Of the latter, 40 used a quantitative approach, 8 used a qualitative approach, 4 used mixed methods approach, and only 4 were based on participatory research-action approach. The digital divide in eHealth is a serious barrier and contributes greatly to SHI. Ethnicity and low income are the most commonly used characteristics to identify people at risk of SHI. The most promising actions for reducing SHI via eHealth are to aim for universal access to the tool of eHealth, become aware of users' literacy level, create eHealth tools that respect the cultural attributes of future users, and encourage the participation of people at risk of SHI. eHealth has the potential to widen the gulf between those at risk of SHI and the rest of the population. The widespread expansion of eHealth technologies calls for rigorous consideration of interventions, which are not likely to exacerbate SHI.

Recent eHealth developments have elevated the importance of assessing the extent to which technology has empowered patients and improved health, particularly among the most vulnerable populations. With noted disparities across racial and social groups in chronic health outcomes, such as cancer, obesity, and diabetes, it is essential that researchers examine any differences in the implementation, uptake, and impact of eHealth strategies across groups that bear a disproportionate burden of disease. The goal was to examine eHealth use by sociodemographic factors, such as race/ethnicity, socioeconomic status (SES), age, and sex. We drew data from National Cancer Institute's 2012 Health Information National Trends Survey (HINTS) (N=3959) which is publicly available online. We estimated multivariable logistic regression models to assess sociodemographic predictors of eHealth use among adult Internet users (N=2358) across 3 health communication domains (health care, health information-seeking, and user-generated content/sharing). Among online adults, we saw no evidence of a digital use divide by race/ethnicity. However, there were significant differences in use by SES, particularly for health care and health information-seeking items. Patients with lower levels of education had significantly lower odds of going online to look for a health care provider (high school or less: OR 0.50, 95% CI 0.33-0.76) using email or the Internet to communicate with a doctor (high school or less: OR 0.46, 95% CI 0.29-0.72), tracking their personal health information online (high school or less: OR 0.53, 95% CI 0.32-0.84), using a website to help track diet, weight, and physical activity (high school or less: OR 0.64, 95% CI 0.42-0.98; some college: OR 0.67, 95% CI 0.49-0.93), or downloading health information to a mobile device (some college: OR 0.54, 95% CI 0.33-0.89). Being female was a consistent predictor of eHealth use across health care and user-generated content/sharing domains, whereas age was primarily influential for health information-seeking. This study illustrates that lower SES, older, and male online US adults were less likely to engage in a number of eHealth activities compared to their counterparts. Future studies should assess issues of health literacy and eHealth literacy and their influence on eHealth engagement across social groups. Clinical care and public health communication efforts attempting to leverage Web 2.0 and 3.0 platforms should acknowledge differential eHealth usage to better address communication inequalities and persistent disparities in health.

The use of telehealth and telemedicine offers powerful tools for delivering clinical care, conducting medical research, and enhancing access to infectious diseases physicians. The Infectious Diseases Society of America (IDSA) has prepared a position statement to educate members on the use of telehealth and telemedicine technologies. The development of telehealth and telemedicine programs requires the consideration of several issues such as HIPAA, state and local licensure requirements, credentialing and privileging, scope of care, quality, and responsibility and liability. IDSA supports appropriate use of telehealth and telemedicine to provide timely, cost-effective specialty care to resource-limited populations.

Congress and many state legislatures are considering expanding access to telemedicine. To inform this debate, we analyzed Medicare fee-for-service claims for the period 2004-14 to understand trends in and recent use of telemedicine for mental health care, also known as telemental health. The study population consisted of rural beneficiaries with a diagnosis of any mental illness or serious mental illness. The number of telemental health visits grew on average 45.1 percent annually, and by 2014 there were 5.3 and 11.8 telemental health visits per 100 rural beneficiaries with any mental illness or serious mental illness, respectively. There was notable variation across states: In 2014 nine had more than twenty-five visits per 100 beneficiaries with serious mental illness, while four states and the District of Columbia had none. Compared to other beneficiaries with mental illness, beneficiaries who received a telemental health visit were more likely to be younger than sixty-five, be eligible for Medicare because of disability, and live in a relatively poor community. States with a telemedicine parity law and a pro-telemental health regulatory environment had significantly higher rates of telemental health use than those that did not.

Background Consumer e-Health is a potential solution to the problems of accessibility, quality and costs of delivering public healthcare services to patients. Although consumer e-Health has proliferated in recent years, it remains unclear if patients are willing and able to accept and use this new and rapidly developing technology. Therefore, the aim of this research is to study the factors influencing patients’ acceptance and usage of consumer e-health innovations. Methods A simple but typical consumer e-health innovation – an e-appointment scheduling service – was developed and implemented in a primary health care clinic in a regional town in Australia. A longitudinal case study was undertaken for 29 months after system implementation. The major factors influencing patients’ acceptance and use of the e-appointment service were examined through the theoretical lens of Rogers’ innovation diffusion theory. Data were collected from the computer log records of 25,616 patients who visited the medical centre in the entire study period, and from in-depth interviews with 125 patients. Results The study results show that the overall adoption rate of the e-appointment service increased slowly from 1.5% at 3 months after implementation, to 4% at 29 months, which means only the ‘innovators’ had used this new service. The majority of patients did not adopt this innovation. The factors contributing to the low the adoption rate were: (1) insufficient communication about the e-appointment service to the patients, (2) lack of value of the e-appointment service for the majority of patients who could easily make phone call-based appointment, and limitation of the functionality of the e-appointment service, (3) incompatibility of the new service with the patients’ preference for oral communication with receptionists, and (4) the limitation of the characteristics of the patients, including their low level of Internet literacy, lack of access to a computer or the Internet at home, and a lack of experience with online health services. All of which are closely associated with the low socio-economic status of the study population. Conclusion The findings point to a need for health care providers to consider and address the identified factors before implementing more complicated consumer e-health innovations.

Many eHealth technologies are not successful in realizing sustainable innovations in health care practices. One of the reasons for this is that the current development of eHealth technology often disregards the interdependencies between technology, human characteristics, and the socioeconomic environment, resulting in technology that has a low impact in health care practices. To overcome the hurdles with eHealth design and implementation, a new, holistic approach to the development of eHealth technologies is needed, one that takes into account the complexity of health care and the rituals and habits of patients and other stakeholders. The aim of this viewpoint paper is to improve the uptake and impact of eHealth technologies by advocating a holistic approach toward their development and eventual integration in the health sector. To identify the potential and limitations of current eHealth frameworks (1999-2009), we carried out a literature search in the following electronic databases: PubMed, ScienceDirect, Web of Knowledge, PiCarta, and Google Scholar. Of the 60 papers that were identified, 44 were selected for full review. We excluded those papers that did not describe hands-on guidelines or quality criteria for the design, implementation, and evaluation of eHealth technologies (28 papers). From the results retrieved, we identified 16 eHealth frameworks that matched the inclusion criteria. The outcomes were used to posit strategies and principles for a holistic approach toward the development of eHealth technologies; these principles underpin our holistic eHealth framework. A total of 16 frameworks qualified for a final analysis, based on their theoretical backgrounds and visions on eHealth, and the strategies and conditions for the research and development of eHealth technologies. Despite their potential, the relationship between the visions on eHealth, proposed strategies, and research methods is obscure, perhaps due to a rather conceptual approach that focuses on the rationale behind the frameworks rather than on practical guidelines. In addition, the Web 2.0 technologies that call for a more stakeholder-driven approach are beyond the scope of current frameworks. To overcome these limitations, we composed a holistic framework based on a participatory development approach, persuasive design techniques, and business modeling. To demonstrate the impact of eHealth technologies more effectively, a fresh way of thinking is required about how technology can be used to innovate health care. It also requires new concepts and instruments to develop and implement technologies in practice. The proposed framework serves as an evidence-based roadmap.

As for all individuals, the Internet is important in the everyday life of older adults. Research on older adults' use of the Internet has merely focused on users versus nonusers and consequences of Internet use and nonuse. Older adults are a heterogeneous group, which may implicate that their use of the Internet is diverse as well. Older adults can use the Internet for different activities, and this usage can be of influence on benefits the Internet can have for them. The aim of this paper was to describe the diversity or heterogeneity in the activities for which older adults use the Internet and determine whether diversity is related to social or health-related variables. We used data of a national representative Internet panel in the Netherlands. Panel members aged 65 years and older and who have access to and use the Internet were selected (N=1418). We conducted a latent class analysis based on the Internet activities that panel members reported to spend time on. Second, we described the identified clusters with descriptive statistics and compared the clusters using analysis of variance (ANOVA) and chi-square tests. Four clusters were distinguished. Cluster 1 was labeled as the \"practical users\" (36.88%, n=523). These respondents mainly used the Internet for practical and financial purposes such as searching for information, comparing products, and banking. Respondents in Cluster 2, the \"minimizers\" (32.23%, n=457), reported lowest frequency on most Internet activities, are older (mean age 73 years), and spent the smallest time on the Internet. Cluster 3 was labeled as the \"maximizers\" (17.77%, n=252); these respondents used the Internet for various activities, spent most time on the Internet, and were relatively younger (mean age below 70 years). Respondents in Cluster 4, the \"social users,\" mainly used the Internet for social and leisure-related activities such as gaming and social network sites. The identified clusters significantly differed in age (P<.001, ω =0.07), time spent on the Internet (P<.001, ω =0.12), and frequency of downloading apps (P<.001, ω =0.14), with medium to large effect sizes. Social and health-related variables were significantly different between the clusters, except social and emotional loneliness. However, effect sizes were small. The minimizers scored significantly lower on psychological well-being, instrumental activities of daily living (iADL), and experienced health compared with the practical users and maximizers. Older adults are a diverse group in terms of their activities on the Internet. This underlines the importance to look beyond use versus nonuse when studying older adults' Internet use. The clusters we have identified in this study can help tailor the development and deployment of eHealth intervention to specific segments of the older population.

Background Mobile health (mHealth) is a rapidly emerging field with the potential to assist older adults in the management of chronic pain (CP) through enhanced communication with providers, monitoring treatment-related side effects and pain levels, and increased access to pain care resources. Little is currently known, however, about older adults’ attitudes and perceptions of mHealth or perceived barriers and facilitators to using mHealth tools to improve pain management. Methods We conducted six focus groups comprised of 41 diverse older adults (≥60 years of age) with CP. Participants were recruited from one primary care practice and two multiservice senior community day-visit centers located in New York City that serve older adults in their surrounding neighborhoods. Focus group discussions were recorded and transcribed, and transcriptions were analyzed using direct content analysis to identify and quantify themes. Results Focus group discussions generated 38 individual themes pertaining to the use of mHealth to help manage pain and pain medications. Participants had low prior use of mHealth (5% of participants), but the vast majority (85%) were highly willing to try the devices. Participants reported that mHealth devices might help them reach their healthcare provider more expeditiously (27%), as well as help to monitor for falls and other adverse events in the home (15%). Barriers to device use included concerns about the cost (42%) and a lack of familiarity with the technology (32%). Facilitators to device use included training prior to device use (61%) and tailoring devices to the functional needs of older adults (34%). Conclusions This study suggests that older adults with CP are interested and willing to use mHealth to assist in the management of pain. Participants in our study reported important barriers that medical professionals, researchers, and mHealth developers should address to help facilitate the development and evaluation of age-appropriate, and function-appropriate, mHealth devices for older persons with CP.