Abstract: A computer-implemented method includes displaying a number of questions on a stack of overlapping graphical objects that dynamically indicates a status of the number of remaining questions, determining an output based on answers input by a user, and displaying an indication of the output.

Abstract: A system obtains patient data, de-identifies each patient with a unique patient key (UPK) and joins the patient data without linking to personal identities of the patients. The system further receives a search query from a user device, identifies a group of UPKs associated with patient data that satisfies criteria of the search query based on values for associated healthcare attributes, and clusters the group of UPKs with respect to healthcare events. The system then ranks the healthcare events of the clusters and sends a query result including healthcare data that is generated based on the ranking, where the query result conceals any personal identity of any of the patients.

Abstract: A computer-implemented method includes displaying a number of questions on a stack of overlapping graphical objects that dynamically indicates a status of the number of remaining questions, determining an output based on answers input by a user, and displaying an indication of the output.

Abstract: Disclosed are systems and techniques for providing a master health entity index and a data analysis mechanism designed for entity cohort discovery and entity profiling. The entity can be a healthcare facility that diagnoses or treats health conditions and diseases (e.g., hospital, clinic), individuals (e.g., providers, patients, caregivers), healthcare data (e.g., medical conditions, treatments, diagnostic studies, health outcomes), etc. For example, a data analysis mechanism may identify distinctive patient cohorts based on what happened to patients in a hospital and why the occurrence happened, glean insight from the activities of the distinctive patient cohorts, and assist with additional patients with the gleaned insight.

Abstract: Introduced are methods and systems for gathering information from a healthcare consumer using context-based questions, and progressively presenting information associated with a ranked list of suggested healthcare providers. First, the server gathers information associated with the healthcare consumer using context-based questions. Each question is formulated based on the answers the healthcare consumer has provided to previous questions, so that minimal and necessary questions are asked. Second, the server progressively sends to a healthcare consumer device, information associated with a ranked list of suggested healthcare providers. The first information tier sent to the healthcare consumer device includes a graphic representing the match strength between the healthcare consumer and the healthcare provider, and the number of similar healthcare consumers the healthcare provider has treated. Based on the healthcare consumer interest, the server displays additional information to the healthcare consumer.

Abstract: A multi-layer display includes a substrate and an array of quantum dots arranged as pixels. Each pixel includes multiple subpixels. Each subpixel of a pixel is configured to emit a respective one of multiple colors when excited. A projector projects a monochromatic image at the multi-layer display to photoexcite selectable ones of the subpixels to cause the selectable subpixels to project a multi-color version of the image. The multi-layer display may be transparent, and the projector may direct the monochromatic image at a front surface of the multi-layer display, at an angle, to permit an observer to view the multi-color image superimposed over a real-world environment of the observer. In another embodiment, a rear surface of the multi-layer display includes a mirror-like coating, and the projector directs the monochromatic image at the rear surface to superimpose the multi-color image over a mirror image of the observer.

Abstract: Disclosed are methods and systems for identifying and profiling focus areas of healthcare providers. Embodiments include technology that identifies focus areas automatically from healthcare information such as diagnoses and procedures. As such, healthcare providers that frequently diagnose and/or treat patients for similar conditions may be automatically grouped into the same cluster. Expert knowledge may then be used to label a cluster as a focus area.

Abstract: Introduced are methods and systems for gathering information from a healthcare consumer using context-based questions, and progressively presenting information associated with a ranked list of suggested healthcare providers. First, the server gathers information associated with the healthcare consumer using context-based questions. Each question is formulated based on the answers the healthcare consumer has provided to previous questions, so that minimal and necessary questions are asked. Second, the server progressively sends to a healthcare consumer device, information associated with a ranked list of suggested healthcare providers. The first information tier sent to the healthcare consumer device includes a graphic representing the match strength between the healthcare consumer and the healthcare provider, and the number of similar healthcare consumers the healthcare provider has treated. Based on the healthcare consumer interest, the server displays additional information to the healthcare consumer.

Abstract: Disclosed are systems and techniques for providing a master health entity index and a data analysis mechanism designed for entity cohort discovery and entity profiling. The entity can be a healthcare facility that diagnoses or treats health conditions and diseases (e.g., hospital, clinic), individuals (e.g., providers, patients, caregivers), healthcare data (e.g., medical conditions, treatments, diagnostic studies, health outcomes), etc. For example, a data analysis mechanism may identify distinctive patient cohorts based on what happened to patients in a hospital and why the occurrence happened, reconstruct timelines of healthcare events from fragmented medical data, and leverage the existing electronic health data to generate comprehensive profiles of healthcare entities.

Abstract: Disclosed are systems and techniques for providing a master health entity index and a data analysis mechanism designed for entity cohort discovery and entity profiling. The entity can be a health care facility that diagnosis or treats health conditions and diseases (e.g., hospital, clinic), individuals (e.g., providers, patients, care givers), healthcare data (e.g., medical conditions, treatments, diagnostic studies, health outcomes), etc. For example, a data analysis mechanism may identify distinctive patient cohorts based on what happened to patients in a hospital and why the occurrence happened, reconstruct timelines of healthcare events from fragmented medical data, and leverage the existing electronic health data to generate comprehensive profiles of healthcare entities.

Abstract: Disclosed are systems and techniques for providing a master health entity index and a data analysis mechanism designed for entity cohort discovery and entity profiling. The entity can be a healthcare facility that diagnoses or treats health conditions and diseases (e.g., hospital, clinic), individuals (e.g., providers, patients, caregivers), healthcare data (e.g., medical conditions, treatments, diagnostic studies, health outcomes), etc. For example, a data analysis mechanism may identify distinctive patient cohorts based on what happened to patients in a hospital and why the occurrence happened, glean insight from the activities of the distinctive patient cohorts, and assist with additional patients with the gleaned insight. .