The disclosure relates generally to a system and method for healthcare services marketplace.
A lot of important health information is stored in different, distinct public and private systems. The challenge is that these distinct systems do not communicate at all with each other or do not have common data formats. As a result, while there is a lot health information, it is not readable accessible or unified in a manner to make it more useful. It is desirable to provide a system that unifies these distinct public and private health information systems and it is to this end that the disclosure is directed.
The disclosure is particularly applicable to a web based healthcare service marketplace system and it is in this context that the disclosure will be described. It will be appreciated, however, that the system and method has greater utility.
The healthcare service marketplace system may unify the health information from different and distinct health systems into cases that are readily available to healthcare providers and approved family members/friends. Furthermore, Facebook posts, tweets, Foursquare check-ins, youtube videos and photos from flickr can provide important information about an ongoing health related matter. The system that may easily track health related events enables a stronger patient-provider relationship. A complete healthstream can often help avoid expensive tests and procedures. Patients are also given the option to anonymously share their healthstream events and cases to help educate others about cost effective treatment options.
The healthcare service marketplace system, and the healthstream generated by the system, provides a more complete view of health related events. The system provides a transparent health marketplace with clear service descriptions and posted prices.
The backend system 108 may also have a health marketplace engine 110, a request for quote engine 112 and a predictive pricing engine 113 that may be coupled together. Each of these components of the backend system may be implemented using one or more computing resources, such as one or more server computers, one or more cloud computing resources and the like. In one embodiment, the health marketplace engine 110, the request for quote engine 112 and the predictive modeling engine 113 may each be implemented in software in which each has a plurality of lines of computer code that are executed by a processor of the one or more computing resources of the backend system. In other embodiments, each of the health marketplace engine 110, the request for quote engine 112 and the predictive modeling engine 113 may be implemented in hardware such as a programmed logic device, a programmed processor or microcontroller and the like. The backend system 108 may be coupled to a store 114 that stores the various data and software modules that make up the healthcare system. The store 114 may be implemented as a hardware database system, a software database system or any other storage system.
The health marketplace engine 110 may allow practitioners that have joined the healthcare social community to reach potential clients in ways unimaginable even a few years ago. In addition to giving practitioners a social portal with which to communicate and market themselves with consumers, the marketplace gives each healthcare practitioner the ability to offer their services in an environment that is familiar to users of Groupon, Living Social, or other social marketplaces.
The request for quote engine 112, in the example shown in
The health marketplace system 110 may further have a health management engine 110a that may generate a healthstream for each member who is a user of the health system 100 and who has logged into the health system 100. The health management engine 110a and its functions described below may be implemented by a processor of the computing resources described above that is configured to perform the operations to the healthstream as described below. To perform the below operations, the health management engine 110a may further comprise a healthstream generator unit that processes the health related data and generates the healthstream, a third party unit that, using the APIs of the third party systems, imports the health related data of the user from the third party system and a user interface unit that generates the healthstream timeline user interface (an example of which is shown in
The healthstream groups health related information and events into a timeline that can be shared among a patient, healthcare provider(s), and approved family members/friends of each member/user of the system. The information for each user/member may be entered directly into the healthstream using the application 104. Alternatively or in addition, the information about the user/member may also be imported from entries made in other systems including a social networking system, such as Facebook®, a communications system, such as Twitter®, a system with check-ins, such as Foursquare® and other web sites. Although the keeping of a detailed health journal requires a lot of discipline and work and busy lives don't often have time to keep up with it, a lot of important health information about the user/member may be recorded all the time in social networks and web sites. The healthstream may provide users an easy way to import and organize information that has already been recorded in these other systems so that it can be visualized as a timeline of health information.
The health timeline (that is part of the healthstream), examples of the user interface of which are shown in
The system may allow a user/member to link an account in the health system, such as the health system provided by PokitDok, with other accounts that have been established by the user/member using a known OAuth authorization flow (further details of which may be found at http://en.wikipedia.org/wikiiOAuth which is incorporated herein by reference.) The OAuth flow links the accounts of the user (social network and web accounts) so that the system is able to gather health related information. Once the accounts are linked, the application 104 on the computing device may make API calls to each linked system to import health related posts into their healthstream. To determine which posts are health related, the system may parse each post and search for basic key words or even term frequency co-occurrences as well as crawling the profiles and information streams of the users whereas they are op-ting into the login into the system. Alternatively, the system may use well-known clustering around term frequency-inverse document frequency (tf-idf). For example, an example of an implementation of the above technique may be found at http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/query-dsl-mlt-query.html that is incorporated herein by reference.
This login gives the system access to the respective users information. In addition, users may be able to drag and drop entries to and from their healthstream to quickly manage what's permanently stored there as described below in more detail with reference to
In the health system, the timeline view generated for each user/member may support multiple cases in the timeline view. Each case may be like a directory on a filesystem where events may be stored together. For example, a mother may have cases defined for herself and for her young children that are not yet old enough to manage their own healthstream. When that mother uses the PokitDok healthstream, her checkins at the doctor's office will be imported into her case folder. When she posts about her child running a fever on facebook, that event will be imported into her child's case folder that may be done by utilizing the APIs provided by the various social networks and systems that can be linked to a PokitDok account. Each time a PokitDok user returns to the system, asynchronous tasks are queued to process the latest data from their linked accounts. The results of the above tasks may be presented in a list in the application. Each entry in that list may be manually added to a case using the drag and drop capabilities of HTML5. In addition, when possible, imported entries may be automatically added to cases by analyzing the imported content for health related keywords. For example, the keywords, key terms, key phrases, symptoms, or procesures can be of the kind but not limited to fever, pain, doctor, ACA, Obamacare, etc and anything that is health related as the system can link together the meanings via a graph inferred topology/medical type taxonomy much like DBPedia, MeSH (www.nlm.nih.gov/mesh/) may be used. For example, see http://dbpedia.org/About or http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245088/ for content references that allow for linked data mechanisms in this area. For example below is a piece of content that could be easily pulled into a health stream if the user selects the subject heart disease:
Aug 10—Increased #physicalactivity reduces heart disease risk, revs up energy, and improves your mood: http://owl.li/zG4BU #getmoving
The health system may support a variety of healthstream entry types. For example, when a checkin is added to the healthstream, a link to the location is stored along with geolocation information so it can be quickly displayed on a map view. As another example, when entries with photos are added to the healthstream, a link to the original photo is stored along with cached versions of the photo at various resolutions for display in different contexts. The healthstream may also include entries about medications that may be added to the timeline that include information about when a medication was started/stopped along with dosage details for the medication. In addition, doctor appointments may also be added to the healthstream. Furthermore, healthstream video entries contain links to the original video so that it may be embedded in the health timeline along with the other information. In addition to the specific healthstream entry types above, a generic entry type may be available that supports miscellaneous file attachments. For example, a user may have a PDF of blood results that were emailed to them that they want to add to their healthstream so that it can be shared with other health providers also on that case. The healthstream may allow a user to drag the PDF attachment from their email to the appropriate case in their timeline.
In the system 100, each of the entries for a user may be stored in the store 114 with a user's globally unique identifier and the identifiers of other PokitDok users that are allowed to view the information to provide, among other things, access control for the data in the healthstream of each user. In the system, each entry may default to being private among the users explicitly specified on the data. Users can choose to change the privacy level to ‘anonymous’ when they want to share information they've learned about a particular health issue with the community without revealing their identity.
Healthcare providers that are part of a healthstream case for a user can also add events to it. For example, a provider can review a user's healthstream when meeting with them and recommend a service they've posted on the health marketplace as part of their treatment plan.
This may add that service to the healthstream with a date/time stamp so the patient and other healthcare providers are all up-to-date with currently active treatments and medications. If multiple providers are participating on a case, email and short message system (SMS) alerts can be triggered to alert them that new information is available for their review.
and the direction of that relationship. The database schema shown in
While the foregoing has been with reference to a particular embodiment of the invention, it will be appreciated by those skilled in the art that changes in this embodiment may be made without departing from the principles and spirit of the disclosure, the scope of which is defined by the appended claims.
This application claims the benefit under 35 USC 119(e) and 35 USC 120 to U.S. Provisional Patent Application Ser. No. 61/887,904 filed on Oct. 7, 2013 and entitled “Healthcare Service Marketplace System and Method”, the entirety of which is incorporated herein by reference.
Number | Date | Country | |
---|---|---|---|
61887904 | Oct 2013 | US |