Journal of medical Internet research
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J. Med. Internet Res. · Jan 2014
The psychometric properties of CollaboRATE: a fast and frugal patient-reported measure of the shared decision-making process.
Patient-centered health care is a central component of current health policy agendas. Shared decision making (SDM) is considered to be the pinnacle of patient engagement and methods to promote this are becoming commonplace. However, the measurement of SDM continues to prove challenging. Reviews have highlighted the need for a patient-reported measure of SDM that is practical, valid, and reliable to assist implementation efforts. In consultation with patients, we developed CollaboRATE, a 3-item measure of the SDM process. ⋯ The fast and frugal nature of CollaboRATE lends itself to routine clinical use. Further assessment of CollaboRATE in real-world settings is required.
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J. Med. Internet Res. · Jan 2014
An internet-based epidemiological investigation of the outbreak of H7N9 Avian influenza A in China since early 2013.
In early 2013, a new type of avian influenza, H7N9, emerged in China. It quickly became an issue of great public concern and a widely discussed topic on the Internet. A considerable volume of relevant information was made publicly available on the Internet through various sources. ⋯ Findings from our Internet-based investigation were similar to those from the conventional field study in most epidemiological and clinical aspects of the outbreak. Importantly, publicly available Internet data are open to any interested researchers and can thus greatly facilitate the investigation and control of such outbreaks. With improved efforts for Internet data provision, Internet-based investigation has a great potential to become a quick, economical, novel approach to investigating sudden issues of great public concern that involve a relatively small number of cases like this H7N9 outbreak.
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J. Med. Internet Res. · Jan 2014
Importance of Internet surveillance in public health emergency control and prevention: evidence from a digital epidemiologic study during avian influenza A H7N9 outbreaks.
Outbreaks of human infection with a new avian influenza A H7N9 virus occurred in China in the spring of 2013. Control and prevention of a new human infectious disease outbreak can be strongly affected by public reaction and social impact through the Internet and social media. ⋯ The first 3 days of an epidemic is a critical period for the authorities to take appropriate action through Internet surveillance to prevent and control the epidemic, including preparation of personnel, technology, and other resources; information release; collection of public opinion and reaction; and clarification, prevention, and control of rumors. Internet surveillance can be used as an efficient and economical tool to prevent and control public health emergencies, such as H7N9 outbreaks.
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Mobile phones with operating systems and capable of running applications (smartphones) are increasingly being used in clinical settings. Medical calculating applications are popular mhealth apps for smartphones. These include, for example, apps that calculate the severity or likelihood of disease-based clinical scoring systems, such as determining the severity of liver disease, the likelihood of having a pulmonary embolism, and risk stratification in acute coronary syndrome. However, the accuracy of these apps has not been assessed. ⋯ The results suggest that most medical calculating apps provide accurate and reliable results. The free apps that were 100% accurate and contained the most functions desired by internists were CliniCalc, Calculate by QxMD, and Medscape. When using medical calculating apps, the answers will likely be accurate; however, it is important to be careful when calculating MELD scores or Child-Pugh scores on some apps. Despite the few errors found, greater scrutiny is warranted to ensure full accuracy of smartphone medical calculator apps.
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Clinicians face difficult treatment decisions in contexts that are not well addressed by available evidence as formulated based on research. The digitization of medicine provides an opportunity for clinicians to collaborate with researchers and data scientists on solutions to previously ambiguous and seemingly insolvable questions. But these groups tend to work in isolated environments, and do not communicate or interact effectively. ⋯ Each type of domain expert can contribute skills unavailable to the other groups. "Health hackathons" and "data marathons", in which diverse participants work together, can leverage the current ready availability of digital data to discover new knowledge. Utilizing the complementary skills and expertise of these talented, but functionally divided groups, innovations are formulated at the systems level. As a result, the knowledge discovery process is simultaneously democratized and improved, real problems are solved, cross-disciplinary collaboration is supported, and innovations are enabled.