Predicting an Exciting Year for Our Health Informatics Community

Let me start by stating that predictions are not my thing.  I did not accurately predict many Oscar winners this year and I usually finish close to the bottom in any office hockey/baseball pool in which I participate.  I do feel confident, however, in predicting an exciting year for our health informatics community.  Why, given my track record, am I feeling so bold?  Consider the following:

We have a Federal Health Minister who ‘gets it’.  Dr. Philpott, a physician who has been using an EMR for years, has been consistent in her message that digital health is transforming the health system and that there is tremendous potential to do more.  She understands the power of technology and the challenges of implementing the changes that will enable more widespread use of it and she is encouraging us, as a community, to continue our efforts to accelerate the pace of change. 

We have federal funding being allocated to healthcare.  By the time you read this blog, Minister Morneau will have tabled Budget 2017 in the House of Commons.  This year’s federal budget is expected to be good news for the health sector after what many would describe as lean years.  In addition to dollars allocated to health in the budget, Ottawa and the provinces/territories (except Manitoba) have reached bilateral funding agreements that will result in billions of dollars being transferred from the federal coffers. 

We have an increasing number of Canadians who are empowered to be more proactive members of their care teams.  This is significant.  According to Canada Health Infoway public opinion research, Canadians are increasingly aware of the benefits of digital health and want access to these services and solutions – and they are getting them. The availability of digital health services for Canadians, for example, has more than doubled between 2014 and 2016.  

We have a health informatics community that is dedicated to transforming the health system.   Canada’s health informatics community is thriving.  There is a renewed energy and a feeling that we are at a tipping point, poised to transform the health system at an unprecedented pace.   We understand the potential, we understand the challenges, and we are committed to working together as governments, industry, organizations, and patients, to make a difference. 

So, my prediction: eHealth 2017 will be the best conference experience you will have this year.  The enthusiasm, the progress, the discussion and celebration will leave you excited, energized and smarter! Looking forward to seeing you at #eHealth2017!

The post Predicting an Exciting Year for Our Health Informatics Community appeared first on e-Health Annual Conference & Tradeshow 2017 | e-Health 2017 Toronto, ON.

e-Health Annual Conference & Tradeshow 2017 | e-Health 2017 Toronto, ON

Impact of Social Processes in Online Health Communities on Patient Empowerment in Relationship With the Physician: Emergence of Functional and Dysfunctional Empowerment

Background: Substantial research demonstrates the importance of online health communities (OHCs) for patient empowerment, although the impact on the patient-physician relationship is understudied. Patient empowerment also occurs in relationship with the physician, but studies of OHCs mostly disregard this. The question also remains about the nature and consequences of this empowerment, as it might be based on the limited validity of some information in OHCs. Objective: The main purpose of this study was to examine the impact of social processes in OHCs (information exchange with users and health professional moderators, social support, finding meaning, and self-expressing) on functional and dysfunctional patient empowerment in relationship with the physician (PERP). This impact was investigated by taking into account moderating role of eHealth literacy and physician’s paternalism. Method: An email list–based Web survey on a simple random sample of 25,000 registered users of the most popular general OHC in Slovenia was conducted. A total of 1572 respondents completed the survey. The analyses were conducted on a subsample of 591 regular users, who had visited a physician at least once in the past 2 years. To estimate the impact of social processes in OHC on functional and dysfunctional PERP, we performed a series of hierarchical regression analyses. To determine the moderating role of eHealth literacy and the perceived physician characteristics, interactions were included in the regression analyses. Results: The mean age of the respondents in the sample was 37.6 years (SD 10.3) and 83.3% were females. Factor analyses of the PERP revealed a five-factor structure with acceptable fit (root-mean-square error of approximation =.06). Most important results are that functional self-efficacy is positively predicted by information exchange with health professional moderators (beta=.12, P=.02), information exchange with users (beta=.12, P=.05), and giving social support (beta=.13, P=.02), but negatively predicted with receiving social support (beta=−.21, P<.001). Functional control is also predicted by information exchange with health professional moderators (beta=.16, P=.005). Dysfunctional control and competence are inhibited by information exchanges with health professionals (beta=−.12, P=.03), whereas dysfunctional self-efficacy is inhibited by self-expressing (beta=−.12, P=.05). The process of finding meaning likely leads to the development of dysfunctional competences and control if the physician is perceived to be paternalistic (beta=.14, P=.03). Under the condition of high eHealth literacy, the process of finding meaning will inhibit the development of dysfunctional competences and control (beta=−.17, P=.01). Conclusions: Social processes in OHCs do not have a uniform impact on PERP. This impact is moderated by eHealth literacy and physician paternalism. Exchanging information with health professional moderators in OHCs is the most important factor for stimulating functional PERP as well as diminishing dysfunctional PERP. Social support in OHCs plays an ambiguous role, often making patients behave in a strategic, uncooperative way toward physicians. Journal of Medical Internet Research

Comparison of Different Recruitment Methods for Sexual and Reproductive Health Research: Social Media–Based Versus Conventional Methods

Background: Prior research about the sexual and reproductive health of young women has relied mostly on self-reported survey studies. Thus, participant recruitment using Web-based methods can improve sexual and reproductive health research about cervical cancer prevention. In our prior study, we reported that Facebook is a promising way to reach young women for sexual and reproductive health research. However, it remains unknown whether Web-based or other conventional recruitment methods (ie, face-to-face or flyer distribution) yield comparable survey responses from similar participants. Objective: We conducted a survey to determine whether there was a difference in the sexual and reproductive health survey responses of young Japanese women based on recruitment methods: social media–based and conventional methods. Methods: From July 2012 to March 2013 (9 months), we invited women of ages 16-35 years in Kanagawa, Japan, to complete a Web-based questionnaire. They were recruited through either a social media–based (social networking site, SNS, group) or by conventional methods (conventional group). All participants enrolled were required to fill out and submit their responses through a Web-based questionnaire about their sexual and reproductive health for cervical cancer prevention. Results: Of the 243 participants, 52.3% (127/243) were recruited by SNS, whereas 47.7% (116/243) were recruited by conventional methods. We found no differences between recruitment methods in responses to behaviors and attitudes to sexual and reproductive health survey, although more participants from the conventional group (15%, 14/95) chose not to answer the age of first intercourse compared with those from the SNS group (5.2%, 6/116; P=.03). Conclusions: No differences were found between recruitment methods in the responses of young Japanese women to a Web–based sexual and reproductive health survey.
Journal of Medical Internet Research

Newsroom: Selfcare koppelt met Apple Health en Google Fit

eHealth en mHealth nieuws uit Nederland en het buitenland: alles over gezondheidsapps, wearables, persoonlijk gezondheidsdossier, fitness en wellness.

Het bericht Newsroom: Selfcare koppelt met Apple Health en Google Fit verscheen eerst op SmartHealth.


Inspiring Bold Action in Canada’s Digital Health Community

Brent Diverty is the Vice President, Programs for the Canadian Institute for Health Information (CIHI) and an e-Health 2017Ambassador. In his role at CIHI, Brent oversees CIHI’s extensive data holdings, which span the continuum of health care services and also contain related financial, pharmaceutical and workforce data.  Connect with him on Twitter @BDiverty   

I’m thrilled to once again be an Ambassador for e-Health, and on behalf of CIHI, proud to co-host #eHealth2017.  As an international leader in health data and information, CIHI has a responsibility to provide and publicly report on the health system.  Co-hosting eHealth 2017 along with COACH and Infoway provides us with a great opportunity to work alongside our colleagues to inspire the type of bold action needed to accelerate improvements in health care and outcomes.

I’ve been participating in e-Health for several years, and my own experience has always been a rewarding one. Each year I am inspired by the insights I gain and the renewed connections I make.  This year I’m certain will be no exception.  Whether moderating or participating on a panel, exploring the trade show or pitching ideas at the Hacking Health @ e-Health 2017, there are countless opportunities to learn about advancements and challenge your thinking.   

Consider, for example, predictive analytics and their potential to transform health care.  This is one of the topics we will be exploring at the opening plenary session on June 5 which I’ll be moderating.   In preparation for the session, I spoke with keynote speakers Anne Merklinger of Own the Podium and Canadian Tire’s Paul Robinson about the transformative power of predictive analytics and why you can trust them to make evidence-based investment decisions. We all agreed they offer untapped potential for health care in Canada. We hope this discussion, and the many others you hear this year at eHealth 2017, will inspire you to take bold action in your own organization.

Join us this year. Add your voice and expertise as we learn from—and celebrate—our past successes and be inspired by some of the best that Canada’s digital health community has to offer.    

See you at #eHealth2017

The post Inspiring Bold Action in Canada’s Digital Health Community appeared first on e-Health Annual Conference & Tradeshow 2017 | e-Health 2017 Toronto, ON.

e-Health Annual Conference & Tradeshow 2017 | e-Health 2017 Toronto, ON

Readability Formulas and User Perceptions of Electronic Health Records Difficulty: A Corpus Study

Background: Electronic health records (EHRs) are a rich resource for developing applications to engage patients and foster patient activation, thus holding a strong potential to enhance patient-centered care. Studies have shown that providing patients with access to their own EHR notes may improve the understanding of their own clinical conditions and treatments, leading to improved health care outcomes. However, the highly technical language in EHR notes impedes patients’ comprehension. Numerous studies have evaluated the difficulty of health-related text using readability formulas such as Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG), and Gunning-Fog Index (GFI). They conclude that the materials are often written at a grade level higher than common recommendations. Objective: The objective of our study was to explore the relationship between the aforementioned readability formulas and the laypeople’s perceived difficulty on 2 genres of text: general health information and EHR notes. We also validated the formulas’ appropriateness and generalizability on predicting difficulty levels of highly complex technical documents. Methods: We collected 140 Wikipedia articles on diabetes and 242 EHR notes with diabetes International Classification of Diseases, Ninth Revision code. We recruited 15 Amazon Mechanical Turk (AMT) users to rate difficulty levels of the documents. Correlations between laypeople’s perceived difficulty levels and readability formula scores were measured, and their difference was tested. We also compared word usage and the impact of medical concepts of the 2 genres of text. Results: The distributions of both readability formulas’ scores (P<.001) and laypeople’s perceptions (P=.002) on the 2 genres were different. Correlations of readability predictions and laypeople’s perceptions were weak. Furthermore, despite being graded at similar levels, documents of different genres were still perceived with different difficulty (P<.001). Word usage in the 2 related genres still differed significantly (P<.001). Conclusions: Our findings suggested that the readability formulas’ predictions did not align with perceived difficulty in either text genre. The widely used readability formulas were highly correlated with each other but did not show adequate correlation with readers’ perceived difficulty. Therefore, they were not appropriate to assess the readability of EHR notes. Journal of Medical Internet Research

Factors Associated With Dropout During Recruitment and Follow-Up Periods of a mHealth-Based Randomized Controlled Trial for Mobile.Net to Encourage Treatment Adherence for People With Serious Mental Health Problems

Background: Clinical trials are the gold standard of evidence-based practice. Still many papers inadequately report methodology in randomized controlled trials (RCTs), particularly for mHealth interventions for people with serious mental health problems. To ensure robust enough evidence, it is important to understand which study phases are the most vulnerable in the field of mental health care. Objective: We mapped the recruitment and the trial follow-up periods of participants to provide a picture of the dropout predictors from a mHealth-based trial. As an example, we used a mHealth-based multicenter RCT, titled “Mobile.Net,” targeted at people with serious mental health problems. Methods: Recruitment and follow-up processes of the Mobile.Net trial were monitored and analyzed. Recruitment outcomes were recorded as screened, eligible, consent not asked, refused, and enrolled. Patient engagement was recorded as follow-up outcomes: (1) attrition during short message service (SMS) text message intervention and (2) attrition during the 12-month follow-up period. Multiple regression analysis was used to identify which demographic factors were related to recruitment and retention. Results: We recruited 1139 patients during a 15-month period. Of 11,530 people screened, 36.31% (n=4186) were eligible. This eligible group tended to be significantly younger (mean 39.2, SD 13.2 years, P<.001) and more often women (2103/4181, 50.30%) than those who were not eligible (age: mean 43.7, SD 14.6 years; women: 3633/6514, 55.78%). At the point when potential participants were asked to give consent, a further 2278 refused. Those who refused were a little older (mean 40.2, SD 13.9 years) than those who agreed to participate (mean 38.3, SD 12.5 years; t1842=3.2, P<.001). We measured the outcomes after 12 months of the SMS text message intervention. Attrition from the SMS text message intervention was 4.8% (27/563). The patient dropout rate after 12 months was 0.36% (4/1123), as discovered from the register data. In all, 3.12% (35/1123) of the participants withdrew from the trial. However, dropout rates from the patient survey (either by paper or telephone interview) were 52.45% (589/1123) and 27.8% (155/558), respectively. Almost all participants (536/563, 95.2%) tolerated the intervention, but those who discontinued were more often women (21/27, 78%; P=.009). Finally, participants’ age (P<.001), gender (P<.001), vocational education (P=.04), and employment status (P<.001) seemed to predict their risk of dropping out from the postal survey. Conclusions: Patient recruitment and engagement in the 12-month follow-up conducted with a postal survey were the most vulnerable phases in the SMS text message-based trial. People with serious mental health problems may need extra support during the recruitment process and in engaging them in SMS text message-based trials to ensure robust enough evidence for mental health care. ClinicalTrial: International Standard Randomized Controlled Trial Number (ISRCTN): 27704027; (Archived by WebCite at Journal of Medical Internet Research

Effects on Engagement and Health Literacy Outcomes of Web-Based Materials Promoting Physical Activity in People With Diabetes: An International Randomized Trial

Background: Developing accessible Web-based materials to support diabetes self-management in people with lower levels of health literacy is a continuing challenge. Objective: The objective of this international study was to develop a Web-based intervention promoting physical activity among people with type 2 diabetes to determine whether audiovisual presentation and interactivity (quizzes, planners, tailoring) could help to overcome the digital divide by making digital interventions accessible and effective for people with all levels of health literacy. This study also aimed to determine whether these materials can improve health literacy outcomes for people with lower levels of health literacy and also be effective for people with higher levels of health literacy. Methods: To assess the impact of interactivity and audiovisual features on usage, engagement, and health literacy outcomes, we designed two versions of a Web-based intervention (one interactive and one plain-text version of the same content) to promote physical activity in people with type 2 diabetes. We randomly assigned participants from the United Kingdom, Austria, Germany, Ireland, and Taiwan to either an interactive or plain-text version of the intervention in English, German, or Mandarin. Intervention usage was objectively recorded by the intervention software. Self-report measures were taken at baseline and follow-up (immediately after participants viewed the intervention) and included measures of health literacy, engagement (website satisfaction and willingness to recommend the intervention to others), and health literacy outcomes (diabetes knowledge, enablement, attitude, perceived behavioral control, and intention to undertake physical activity). Results: In total, 1041 people took part in this study. Of the 1005 who completed health literacy information, 268 (26.67%) had intermediate or low levels of health literacy. The interactive intervention overall did not produce better outcomes than did the plain-text version. Participants in the plain-text intervention group looked at significantly more sections of the intervention (mean difference –0.47, 95% CI –0.64 to –0.30, P<.001), but this did not lead to better outcomes. Health literacy outcomes, including attitudes and intentions to engage in physical activity, significantly improved following the intervention for participants in both intervention groups. These improvements were similar across higher and lower health literacy levels and in all countries. Participants in the interactive intervention group had acquired more diabetes knowledge (mean difference 0.80, 95% CI 0.65-0.94, P<.001). Participants from both groups reported high levels of website satisfaction and would recommend the website to others. Conclusions: Following established practice for simple, clear design and presentation and using a person-based approach to intervention development, with in-depth iterative feedback from users, may be more important than interactivity and audiovisual presentations when developing accessible digital health interventions to improve health literacy outcomes. ClinicalTrial: International Standard Randomized Controlled Trial Number (ISRCTN): 43587048; (Archived by WebCite at Journal of Medical Internet Research

Zembro-horloge completeert assortiment persoonsalarmering van Livv Mobile Health

De aanbieder van oplossingen voor zorg op afstand Livv Mobile Health biedt vanaf februari 2017 de alarmeringsoplossing van de Belgische zorgondernemer Zembro aan. Met de toevoeging van het Zembro-horloge aan haar assortiment zorgt Livv dat ook gebruikers zonder smartphone of telefoon met ingebouwde alarmknop hulp kunnen inroepen wanneer die nodig is. De Zembro is een […]

Personal Health Records: A Systematic Literature Review

Background: Information and communication technology (ICT) has transformed the health care field worldwide. One of the main drivers of this change is the electronic health record (EHR). However, there are still open issues and challenges because the EHR usually reflects the partial view of a health care provider without the ability for patients to control or interact with their data. Furthermore, with the growth of mobile and ubiquitous computing, the number of records regarding personal health is increasing exponentially. This movement has been characterized as the Internet of Things (IoT), including the widespread development of wearable computing technology and assorted types of health-related sensors. This leads to the need for an integrated method of storing health-related data, defined as the personal health record (PHR), which could be used by health care providers and patients. This approach could combine EHRs with data gathered from sensors or other wearable computing devices. This unified view of patients’ health could be shared with providers, who may not only use previous health-related records but also expand them with data resulting from their interactions. Another PHR advantage is that patients can interact with their health data, making decisions that may positively affect their health. Objective: This work aimed to explore the recent literature related to PHRs by defining the taxonomy and identifying challenges and open questions. In addition, this study specifically sought to identify data types, standards, profiles, goals, methods, functions, and architecture with regard to PHRs. Methods: The method to achieve these objectives consists of using the systematic literature review approach, which is guided by research questions using the population, intervention, comparison, outcome, and context (PICOC) criteria. Results: As a result, we reviewed more than 5000 scientific studies published in the last 10 years, selected the most significant approaches, and thoroughly surveyed the health care field related to PHRs. We developed an updated taxonomy and identified challenges, open questions, and current data types, related standards, main profiles, input strategies, goals, functions, and architectures of the PHR. Conclusions: All of these results contribute to the achievement of a significant degree of coverage regarding the technology related to PHRs.
Journal of Medical Internet Research