International journal of medical informatics
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To assess the role of speech recognition (SR) technology in clinicians' documentation workflows by examining use of, experience with and opinions about this technology. ⋯ While concerns about SR usability and accuracy persist, clinicians expressed positive opinions about its impact on workflow and efficiency. Faster and better approaches are needed for clinical documentation, and SR is likely to play an important role going forward.
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The United Nations' Sustainable Development Goal #3.8 targets 'access to quality essential healthcare services'. Clinical practice guidelines are an important tool for ensuring quality of clinical care, but many challenges prevent their use in low-resource settings. Monitoring the use of guidelines relies on cumbersome clinical audits of paper records, and electronic systems face financial and other limitations. Here we describe a unique approach to generating digital data from paper using guideline-based templates, rubber stamps and mobile phones. ⋯ The use of templates improves paper-based documentation of patient care, a first step towards improving the quality of care. Rubber stamps provide a simple and low-cost method to print templates on demand. In combination with ubiquitously available mobile phones, information entered on paper can be easily and rapidly digitized. This 'frugal innovation' in m-Health can empower small, private sector facilities, where large numbers of urban patients seek healthcare, to generate digital data on routine outpatient care. These data can form the basis for evidence-based quality improvement efforts at large scale, and help deliver on the SDG promise of quality essential healthcare services for all.
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We aimed to construct a mortality prediction model using the random forest (RF) algorithm for acute kidney injury (AKI) patients in the intensive care unit (ICU), and compared its performance with that of two other machine learning models and the customized simplified acute physiology score (SAPS) II model. ⋯ There is great potential for the RF model in mortality prediction for AKI patients in ICU. The RF model may be helpful to aid ICU clinicians to make timely clinical intervention decisions for AKI patients, which is critical to help reduce the in-hospital mortality of AKI patients. A prospective study is necessary to evaluate the clinical utility of the RF model.
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Adverse events in healthcare are often collated in incident reports which contain unstructured free text. Learning from these events may improve patient safety. Natural language processing (NLP) uses computational techniques to interrogate free text, reducing the human workload associated with its analysis. There is growing interest in applying NLP to patient safety, but the evidence in the field has not been summarised and evaluated to date. ⋯ NLP can generate meaningful information from unstructured data in the specific domain of the classification of incident reports and adverse events. Understanding what or why incidents are occurring is important in adverse event analysis. If NLP enables these insights to be drawn from larger datasets it may improve the learning from adverse events in healthcare.
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This paper has two objectives. First, it categorizes the Twitter handles tweeted flu related information based on the amount of replies and mentions within the Twitter network. The collected Twitter accounts are categorized as media, health related individuals, organizations, government, individuals with no background with media or medical field, in order to test the relationship between centrality measures of the accounts and their categories. The second objective is to examine the relationship between the importance of the Twitter accounts in the network, centrality measures, and specific characteristics of each account, including the number of tweets and followers as well as the number of accounts followed and liked. ⋯ Health campaigns are recommended to focus on recruiting influential Twitter accounts and encouraging them to retweet or mention in order to produce better results in disseminating information. Although some individual social media users were valuable assets in terms of spreading information about flu, media and organization handles were more reliable information distributors. Thus, health information practitioners are advised to design health campaigns better utilizing media and organizations rather than individuals to achieve consistent and efficient campaign outcomes.