Traditionally, patients were at the mercy of healthcare systems that gave little opportunity to manage options. IoM-powered technology enables virtual doctors, retail medical clinics, and subscription-based healthcare options. The IoT will be valuable for healthcare as it can provide real-time access to patient data that doctors, hospitals, and pharmaceutical companies can use with permission to improve patient experiences and pave the way for recurring revenue opportunities across the entire health landscape.
Check out the infographic below for a snapshot on IoM and its impact on patients and the entire healthcare industry. Acquire more customers. Manage Recurring Revenue. Maximize Lifetime Value. Request a Demo. Webinar Whitepaper Collateral Infographics Videos. About the Author. Eileen Bernardo is the Content Marketing Manager at Aria Systems where she manages content creation for multiple projects. She has an M.
Read Eileen Bernardo's Posts. See why Aria Systems was named a leader in subscription billing platforms by Forrester Research. Recurring Revenue Management for Dummies. We are also a leader in participatory and open science approaches, and offer the option to publish new submissions immediately as preprints , which receive DOIs for immediate citation eg, in grant proposals , and for open peer-review purposes.
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Background: Demand for mental health services, especially for clinical high-risk and early psychosis, has increased, creating a need for new solutions to increase access to and quality of care. Smartphones and mobile technology are potential tools to support coordinated specialty care for early psychosis, given their potential to augment the six core roles of care: case management and team leadership, recovery-oriented psychotherapy, medication management, support for employment and education, coordination with primary care services, and family education and support.
However, the services smartphones are actually offering specifically for coordinated specialty care and the level of evidence are unknown. Objective: This study aimed to review the published literature on smartphone technology to enhance care for patients with prodromal and early course psychosis and schizophrenia and to analyze studies by type, aligned with coordinated specialty care domains. The eligible studies were reviewed and screened based on inclusion and exclusion criteria.
Results: The search uncovered unique results, of which 32 articles met the initial inclusion criteria; 21 eligible studies on 16 unique app platforms were identified. Feasibility studies showed a high user engagement and interest among patients, monitoring studies demonstrated a correlation between app assessments and clinical outcomes, and intervention studies indicated that these apps have the potential to advance care.
Eighteen studies reported on app use for the case management roles of coordinated specialty care. No app studies focused on employment and education, coordination with primary care services, and family education and support. Conclusions: Although the published literature on smartphone apps for prodromal and first-episode psychosis is small, it is growing exponentially and holds promise to augment both monitoring and interventions.
Although the research results and protocols for app studies are not well aligned with all coordinated specialty care roles today, high rates of adoption and feasibility suggest the potential for future efforts. These results will be used to develop coordinated specialty care—specific app evaluation scales and toolkits. Discover Social Media mentions by hovering over the donut.
Click the 'details' link for a full report. Background: The lack of continuity between health-related quality of life HRQoL instruments designed for children and adults hinders change analysis with a life course approach. Few studies have assessed the metric properties of EQ-5D-Y in children with specific chronic conditions, and none have done so for children with type I diabetes mellitus T1DM.
Objective: This study aimed to evaluate the acceptability, validity, reliability, and responsiveness of the EQ-5D-Y in children and adolescents with T1DM, when administered online. Methods: Participants with T1DM were consecutively recruited from July to December , from a list of potential candidates aged years, who attended outpatient pediatric endocrinology units. The EQ-5D-Y measures five dimensions, from which an equally weighted summary score was constructed range: Completion rate and distribution statistics were calculated.
Construct validity was evaluated through known group comparisons based on general health, acute diabetic decompensations, mental health, family function, and a multitrait, multimethod matrix between EQ-5D-Y and KIDSCREEN by using Spearman correlations. Construct validity hypotheses were stated a priori. Reliability was assessed with the intraclass correlation coefficient and responsiveness by testing changes over time and calculating the effect size.
Results: Of the participants, Results of the multitrait, multimethod matrix confirmed three of the four relationships hypothesized as substantial 0. The EQ-5D-Y summary score presented an intraclass correlation coefficient of 0. Statistically significant change between visits was observed in the improved subsample, with an effect size of 0.
Background: Rural and remote residents are more likely to smoke than those who live in major cities; however, recruitment of research participants from rural and remote areas can be challenging. The cost per participant recruited from rural and remote areas via online eg, social media and traditional strategies eg, print has implications for researchers on how to allocate resources to maximize the number of participants recruited.
Participant characteristics such as demographics, financial stress, mental health, and smoking-related factors may be associated with recruitment method ie, online vs traditional , and so it is important to understand whether certain subgroups are more likely to be recruited via a particular strategy. Objective: This study aimed to determine the cost per participant recruited and examine whether characteristics such as demographics, financial stress, mental health, and smoking-related factors may be associated with the recruitment method ie, online vs traditional.
Methods: Participants were recruited into a randomized trial that provided smoking cessation support. Eligible participants were aged 18 years or older; used tobacco daily; had access to video communication software, internet, and telephone; had an email address; and lived in a rural or remote area of New South Wales, Australia. This study describes the natural observed experience of recruiting participants via online and traditional methods into a smoking cessation trial.
Results: Over 17 months, participants were recruited into the smoking cessation trial. A total of Moreover, 1. Women had greater odds of being recruited via online methods than men odds ratio 2. No other characteristics were associated with the recruitment method. Conclusions: The cost per participant recruited via online and traditional strategies varied, with the range being smaller for online than traditional recruitment strategies.
Women have greater odds of being recruited via online strategies into rural smoking cessation trials. Background: Cognitive behavioral therapy CBT for young people is increasingly being provided using technology-assisted formats. Although there is increasing evidence regarding the efficacy of such approaches, as illustrated by quantitative systematic reviews, the literature has also highlighted challenges with implementation factors, including high attrition rates and variable user engagement.
To date, no such qualitative synthesis exists.follow site
How the Internet and social media are changing healthcare | Digital Trends
Objective: The primary aim of this review was to systematically identify and synthesize the qualitative literature concerning the experiences of young people who have used tech-assisted CBT. This involved line-by-line coding of the results sections of included studies and an inductive analysis on identified themes, followed by the generation of analytical themes through a process of iteration and interpretation of the descriptive themes.
The inclusion criteria were 1 studies involving school-aged young people over preschool age 6 years but under the age of 18 years, 2 use of any form of tech-assisted CBT for any time period, 3 a stated focus of qualitative data to document the experiences of participants, and 4 studies published in English.
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The exclusion criteria were 1 interventions only provided face-to-face with no technological component, 2 only focused on the performance of the technology rather than participant experience, and 3 numerical data that sought to represent qualitative data. Results: A total of 14 studies were included in this review. In addition, these analytical themes contained the following subthemes: positive experiences, tech-assisted CBT versus face-to-face CBT, understanding of a CBT model, process of change, skills development, application to everyday life settings, parental involvement, character relatedness, playability, negative experiences, and broad content.
The use of gaming environments, relatable characters, concrete metaphors, and age-appropriate narratives contributed to these positive experiences. Evidence suggests that technology can help to mediate face-to-face relationships with therapists and help young people to understand the CBT model. Clear barriers also emerged, including over-reliance on reading and writing skills and dissatisfaction with overly generalized content and comparison with commercial technologies.
Background: There is a considerable shortfall in specialized health care professionals worldwide to deliver health services, and this shortfall is especially pronounced in low-middle-income countries. This has led to the implementation of task-shifted interventions, in which specific tasks are moved away from highly qualified health workers to health workers with less training.
The World Health Organization WHO has published recommendations for such interventions, but guidelines for software and systems supporting such interventions are not included. Objective: The objective of this study was to formulate a number of software requirements for computer systems supporting task-shifted interventions. As the treatment of mental health problems is generally considered to be a task for highly trained health care professionals, it poses interesting case studies for task-shifted interventions.
These 9 software requirements were used to implement a system for the provision of a psychosocial depression intervention with mobile Android interfaces to structure interventions and collect data, and Web interfaces for supervision and support of the health care workers delivering the intervention.
The system was tested in a 2-arm pilot study with 33 patients and 11 health workers. In all, 8 of these 11 health workers participated in a usability study subsequent to the pilot. Results: The qualitative and quantitative feedback obtained with the System Usability Scale suggest that the system was deemed to have a usability of between OK and Good. This was reinforced by answers obtained with perceived usefulness and ease of use questionnaires, which indicated some users felt that they had issues around correct use of the system and perceived ability to become skillful at using the system.
Conclusions: Overall, these high-level requirements adequately captured the functionality required to enable the health workers to provide the intervention successfully. Nevertheless, the analysis of results indicated that some improvements were required for the system to be useable in a task-shifted intervention. The most important of these were better access to a training environment, access for supervisors to metadata such as duration of sessions or exercises to identify issues, and a more robust and human-error—proof approach to the availability of patient data on the mobile devices used during the intervention.
Evaluating Health Information
Background: The widespread adoption of digital health interventions for chronic disease self-management has catalyzed a paradigm shift in the selection of methodologies used to evidence them. Recently, the application of digital health research analytics has emerged as an efficient approach to evaluate these data-rich interventions.
However, there is a growing mismatch between the promising evidence base emerging from analytics mediated trials and the complexity of introducing these novel research methods into evaluative practice. Objective: This study aimed to generate transferable insights into the process of implementing research analytics to evaluate digital health interventions. We sought to answer the following two research questions: 1 how should the service of research analytics be designed to optimize digital health evidence generation?
Methods: We conducted a qualitative multilevel embedded single case study of implementing research analytics in evaluative practice that comprised a review of the policy and regulatory climate in Ontario macro level , a field study of introducing a digital health analytics platform into evaluative practice meso level , and interviews with digital health innovators on their perceptions of analytics and evaluation microlevel.
Results: The practice of research analytics is an efficient and effective means of supporting digital health evidence generation. The introduction of a research analytics platform to evaluate effective engagement with digital health interventions into a busy research lab was ultimately accepted by research staff, became routinized in their evaluative practice, and optimized their existing mechanisms of log data analysis and interpretation.
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The capacity for research analytics to optimize digital health evaluations is highest when there is 1 a collaborative working relationship between research client and analytics service provider, 2 a data-driven research agenda, 3 a robust data infrastructure with clear documentation of analytic tags, 4 in-house software development expertise, and 5 a collective tolerance for methodological change.
Conclusions: Scientific methods and practices that can facilitate the agile trials needed to iterate and improve digital health interventions warrant continued implementation.