Supplementing the background data on this patent, NewsRx reporters additionally obtained the inventors’ abstract data for this patent: “Disclosed herein are techniques, strategies, and units for figuring out and quantifying relationships between healthcare entities. In an embodiment, an employment relationship between a facility and a healthcare practitioner is recognized and quantified primarily based on the practitioner’s procedures and facility claims.
“Present understanding of the healthcare trade in
“Embodiments of the disclosure start on the stage of particular person practitioner billing and process codes and builds from there to determine and quantify relationships between different healthcare entities. By monitoring the relationships of particular person practitioners to greater stage entities, the connections between practitioners and a number of different entities may be recognized. That is an improved and extra streamlined methodology compared with viewing all organizations as discrete, mutually unique units of practitioners.
“Embodiments of the disclosure leverage a number of knowledge sources to exactly and fully describe relationships between healthcare entities. Relationships between practitioners and different healthcare entities can’t be seen as binary. There are a number of forms of affiliations between healthcare entities, and every affiliation could also be characterised by way of its energy. An affiliation reported as merely binary (i.e. sure/no, exists/doesn’t exist, and so forth) masks vital data.
“Embodiments of the disclosure interpret affiliation metrics primarily based on an individualized perspective. For instance, a doctor’s affiliation with a hospital has two views: the doctor’s perspective and the hospital’s perspective. The doctor could view the hospital as a crucial portion of the apply that allows the doctor to carry out sure procedures. The hospital could view the doctor as one in all many, and the doctor’s procedures carried out on the hospital could characterize a really small portion of all procedures carried out on the hospital. Understanding affiliations from each views is extra informative than viewing the affiliations from just one perspective.”
The claims provided by the inventors are:
“1. A way comprising: aggregating knowledge from a plurality of various knowledge sources, whereby the info contains uncooked claims knowledge ingested from an exterior knowledge supply, whereby no less than a portion of the uncooked claims knowledge is encrypted, and whereby the uncooked claims knowledge contains service claims, whereby the service claims comprise knowledge metrics that embody calendar yr, entity, practitioner identifier (ID), or facility identifier; executing an digital knowledge safety measure by de-encrypting the encrypted portion of the uncooked claims knowledge; producing an middleman file from the de-encrypted uncooked claims knowledge comprising a modeled model of the uncooked claims knowledge, whereby the modeled model of the uncooked claims knowledge is cleaned to remove superfluous knowledge; storing the middleman file in a database; partitioning the middleman file primarily based on a number of of the info metrics; figuring out a plurality of service claims processed by a practitioner for procedures carried out at a facility, whereby the plurality of service claims is recognized from throughout the partitioned model of the middleman file that’s saved within the database; executing a database merge course of to match the plurality of service claims to the power to generate matched claims; calculating a share of outpatient claims primarily based on a share of workplace claims carried out by the practitioner that didn’t happen on the facility; and calculating a stage of confidence that the practitioner is employed by the power primarily based on the matched claims and the share of outpatient claims; whereby the database merge course of contains a plurality of steps, and whereby every of the plurality of steps contains matching the plurality of service claims to the power primarily based on an recognized knowledge metric; whereby calculating the extent of confidence that the practitioner is employed by the power displays real-world associations between the practitioner and the power primarily based on real-world claims knowledge; and whereby the middleman file decreases the quantity of disc storage and/or Random Entry Reminiscence (RAM) wanted to calculate the extent of confidence that the practitioner is employed by the power primarily based on the real-world claims knowledge.
“2. The tactic of declare 1, whereby the uncooked claims knowledge additional contains facility claims and the strategy additional comprising figuring out a plurality of facility claims throughout the partitioned model of the middleman file that’s saved on the database, whereby the plurality of facility claims is related to the power, and whereby matching the plurality of service claims to the power contains matching the plurality of service claims to the plurality of facility claims to generate the matched claims.
“3. The tactic of declare 1, whereby calculating the share of outpatient claims contains collapsing the matched claims on a practitioner ID related to the practitioner.
“4. The tactic of declare 1, additional comprising collapsing the matched claims to group stage, whereby the power is a healthcare facility related to a gaggle.
“5. The tactic of declare 4, additional comprising calculating a share of employment by calculating a share of practitioners related to the group which might be employed by a facility related to the group.
“6. The tactic of declare 1, whereby the service claims additional comprise affected person identification, process, date of service, procedural code, inpatient facility, clinic identifier (ID), and whereby matching the plurality of service claims with the power contains matching primarily based on: in a primary matching iteration, a affected person identification for a affected person that acquired a process from the practitioner, a date of service for the process carried out, and a process code for the process; in a second matching iteration, the affected person identification, the date of service, and a practitioner ID (Nationwide Supplier Identifier) related to the practitioner; in a 3rd matching iteration, an inpatient facility related to a service declare if the service declare occurred throughout a hospitalization on the inpatient facility; in a fourth matching iteration, the date of service and a commonest facility related to the practitioner; and in a fifth matching iteration, the commonest facility related to the practitioner as decided primarily based on a clinic ID (Nationwide Supplier Identifier) in a service declare.
“7. The tactic of declare 6, whereby matching the plurality of service claims with the power additional contains matching primarily based on: in a sixth matching iteration, the date of service and the commonest facility related to the practitioner; in a seventh matching iteration, the date of service and up to date commonest facility related to the practitioner primarily based on claims processed by the practitioner in a latest time interval; in an eighth matching iteration, the date of service and the commonest facility related to the practitioner; in a ninth matching iteration, a commonest facility related to the practitioner utilizing beforehand joined amenities; and in a tenth matching iteration, a facility most intently hyperlink to the clinic ID primarily based on the service declare.
“8. The tactic of declare 1, additional comprising calculating a stage of confidence that the practitioner is employed by the power for annually there can be found service claims and aggregating the extent of confidence for annually to calculate an aggregated stage of confidence that the practitioner is employed by the power.
“9. The tactic of declare 1, whereby the service claims additional comprise affected person identification, process, date of service, procedural code, inpatient facility, clinic identifier (ID), and whereby the plurality of steps for the database merge course of contains matching primarily based on a number of of: a affected person identification for a affected person that acquired a process from the practitioner; a date of service for the process; a process code for the process; a practitioner ID (Nationwide Supplier Identifier) related to the practitioner; an inpatient facility related to a service declare if the service declare occurred throughout a hospitalization on the inpatient facility; a commonest facility that’s mostly related to the practitioner; a clinic ID (Nationwide Supplier Identifier) related to the power; or a facility mostly linked to the clinic ID primarily based on the service claims.
“10. The tactic of declare 1, whereby the service claims additional comprise affected person identification, process, date of service, procedural code, inpatient facility, clinic identifier (ID), and whereby the database merge course of for matching the plurality of service claims with the power contains matching primarily based on every of: a affected person identification for a affected person that acquired a process from the practitioner; a date of service for the process; a process code for the process; a practitioner ID (Nationwide Supplier Identifier) related to the practitioner; an inpatient facility related to a service declare if the service declare occurred throughout a hospitalization on the inpatient facility; a commonest facility that’s mostly related to the practitioner; a clinic ID (Nationwide Supplier Identifier) related to the power; and a facility mostly linked to the clinic ID primarily based on the service claims.
“11. The tactic of declare 1, additional comprising figuring out that the practitioner is employed by the power in response to figuring out that every one service claims billed by the practitioner are matched to the power.
“12. A system comprising a number of processors configured to execute directions saved in non-transitory pc readable storage media, the directions comprising: aggregating knowledge from a plurality of various knowledge sources, whereby the info contains uncooked claims knowledge ingested from an exterior knowledge supply, whereby no less than a portion of the uncooked claims knowledge is encrypted, and whereby the uncooked claims knowledge contains service claims, whereby the service claims comprise knowledge metrics that embody calendar yr, entity, practitioner identifier (ID), or facility identifier; executing an digital knowledge safety measure by de-encrypting the encrypted portion of the uncooked claims knowledge; producing an middleman file from the de-encrypted uncooked claims knowledge comprising a modeled model of the uncooked claims knowledge, whereby the modeled model of the uncooked claims knowledge is cleaned to remove superfluous knowledge; storing the middleman file in a database; partitioning the middleman file primarily based on a number of of the info metrics; figuring out a plurality of service claims processed by a practitioner for procedures carried out at a facility, whereby the plurality of service claims is recognized from throughout the partitioned model of the middleman file that’s saved within the database; executing a database merge course of to match the plurality of service claims to the power to generate matched claims; calculating a share of outpatient claims primarily based on a share of workplace claims carried out by the practitioner that didn’t happen on the facility; and calculating a stage of confidence that the practitioner is employed by the power primarily based on the matched claims and the share of outpatient claims; whereby the database merge course of contains a plurality of steps, and whereby every of the plurality of steps contains matching the plurality of service claims to the power primarily based on an recognized knowledge metric; whereby calculating the extent of confidence that the practitioner is employed by the power displays real-world associations between the practitioner and the power primarily based on real-world claims knowledge; and whereby the middleman file decreases the quantity of disc storage and/or Random Entry Reminiscence (RAM) wanted to calculate the extent of confidence that the practitioner is employed by the power primarily based on the real-world claims knowledge.”
There are extra claims. Please go to full patent to learn additional.
For the URL and extra data on this patent, see: Muhlestein, David. Identification of employment relationships between healthcare practitioners and healthcare amenities.
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