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Africa
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Creating Value Today with AI
Published in Tom Lawry, Hacking Healthcare, 2022
Example: Researchers at MIT and the Beth Israel Deaconess Medical Center are creating a better electronic health record by combining machine learning and human-computer interactions. The system they have developed unifies looking up medical records and documenting patient information into a single, interactive interface. Driven by AI, this “smart” EHR automatically displays customized, patient-specific medical records when a clinician needs them. It also provides autocomplete for clinical terms and auto-populates fields with patient information to help doctors work more efficiently.6
Common and Assistive Technology to Support People with Specific Learning Disabilities to Access Healthcare
Published in Christopher M. Hayre, Dave J. Muller, Marcia J. Scherer, Everyday Technologies in Healthcare, 2019
Dianne Chambers, Sharon Campbell
Accessibility of web-based content is an area that should be considered, and there are a number of tools that developers/website owners can use to ensure that they are meeting the needs of all users of a website. The World Wide Web Consortium (W3C) Web Accessibility Initiative (WAI) released updated guidelines, which include reference to the success criteria for people with learning disabilities (W3C WAI, 2018). The updated Web Content Accessibility Guidelines (WCAG) 2.1 suggest that developers include autocomplete features in commonly used fields, appropriate text spacing (or the ability to work with style sheets) in relation to line height, paragraph, letter and word spacing and provide timeout warnings for users. All of these considerations are relevant to people accessing healthcare on a computer or tablet device, including tasks such as making appointments and filling in electronic forms.
Integrating a web-based survey application into Qualtrics to collect risk location data for HIV prevention research
Published in AIDS Care, 2022
Our tool has several strengths compared with other approaches. First, it uses the Place Autocomplete feature to provide a type-ahead search box that is responsive to addresses, intersections, and landmarks (i.e., the name of a church, park, store, restaurant, etc.), which improves accuracy. After the location is entered, the map re-centers. Participants can also use the navigation features to refine their search and the street-view feature to visually confirm their selection before submitting their response. Only the final location is stored in the database and all data are automatically geocoded, which improves accuracy and eliminates data entry and geocoding errors. Because participants can navigate to non-exact but approximate locations to prevent disclosure of sensitive locations, it also preserves confidentiality. To further protect confidentiality, there is an option to remove the map view and/or the street view images from the survey display. Our data collection tool also allows the survey developer to specify a default zoom level for each survey, which reduces navigation difficulties.