US20210158452A1

US20210158452A1 - Matching healthcare claim data for identifying and quantifying relationships between healthcare entities

Info

Publication number: US20210158452A1
Application number: US16/877,940
Authority: US
Inventors: David Muhlestein; Robert Richards
Original assignee: Leavitt Partners Insight LLC
Current assignee: Milliman Solutions LLC
Priority date: 2019-11-22
Filing date: 2020-05-19
Publication date: 2021-05-27
Also published as: US20210158913A1; US11562327B2; US11763262B2; US20210158942A1; US20210158945A1; US11756002B2; US20210158912A1; US20210158943A1; US20210158911A1; US11935008B2; US20210158295A1; US11544671B2; US11488109B2; US20210158944A1; US11481731B2

Abstract

Matching carrier claims to facilities based on billed claims data in a healthcare system. A method includes identifying a carrier claim processed by a practitioner and matching the carrier claim to a facility to generate a matched claim based on a claims factor. The method is such that the claims factor comprises one or more of a patient identifier, a date of service for a procedure billed on the carrier claim, a practitioner identifier associated with the practitioner, a facility identifier for an inpatient facility associated with the carrier claim if the carrier claim occurred during a hospitalization at the inpatient facility, a most common facility associated with the practitioner.

Description

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional Patent Application No. 62/939,349, filed Nov. 22, 2019, titled “IDENTIFICATION OF EMPLOYMENT RELATIONSHIPS BETWEEN HEALTHCARE PRACTITIONERS AND HEALTHCARE FACILITIES,” which is incorporated herein by reference in its entirety, including but not limited to those portions that specifically appear hereinafter, the incorporation by reference being made with the following exception: In the event that any portion of the above-referenced provisional application is inconsistent with this application, this application supersedes the above-referenced provisional application.

TECHNICAL FIELD

The disclosure relates generally to the analysis of healthcare systems and particularly to merging healthcare data.

BACKGROUND

The healthcare industry is extraordinarily complex. Specifically, in the United States, relationships between healthcare practitioners, clinics, facilities, groups, and systems are complex and interwoven such that it can be challenging to identify relationships between different entities. One practitioner may see patients that are part of different systems, health insurance networks, or groups. Further, the practitioner may be associated with more than one facility or clinic. The interwoven relationships between healthcare entities makes it challenging to determine if a certain practitioner is associated with or employed by a certain facility, clinic, group, or system. Additionally, other relationships between practitioners, facilities, clinics, groups, and systems throughout the healthcare industry are difficult to identify and quantify.
In some instances, it is necessary or beneficial to understand the relationships between healthcare entities. For example, a health insurance provider seeking to create an in-network selection of providers may need to know which practitioners are associated with which facilities, clinics, groups, or systems. Further for example, a manufacturer or seller of medical devices or pharmaceuticals may benefit from understanding the business relationships between practitioners, facilities, clinics, groups, and systems. In some instances, for example, the manufacturer or seller may sell a medical device or pharmaceutical to a single group, and this would in turn lead to distribution of that medical device or pharmaceutical to hundreds of practitioners associated with the group. These relationships between healthcare entities are nearly impossible to identify or quantify.
In light of the foregoing, disclosed herein are systems, methods, and devices for identifying relationships between healthcare entities.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive implementations of the present disclosure are described with reference to the following figures, wherein like reference numerals refer to like parts throughout the various views unless otherwise specified. Advantages of the present disclosure will become better understood with regard to the following description and accompanying drawings where:

FIG. 1 is a schematic diagram of a framework outlining affiliations between healthcare entities;

FIG. 2 is a schematic diagram of a system for data communication between a data merging component and internal and external data sources;

FIG. 3 is a schematic diagram of a system for performing electronic data security measures on data received from an external data source;

FIG. 4 is a schematic diagram of a data flow to a data merging component configured for merging carrier claims data and facility claims data;

FIG. 5 is a diagram of a file organization schematic for Provider Enrollment, Chain and Ownership System (PECOS) enrollment data;

FIG. 6 is a schematic flow chart diagram of a plurality of matching iterations to be completed in succession for matching carrier claims to one or more facilities, wherein each of the matching iterations comprises one or more claims factors for matching the carrier claims to the one or more facilities;

FIG. 7 is a data flow chart for identifying and quantifying a practitioner-clinic billing relationship;

FIG. 8 is a data flow chart for identifying and quantifying a practitioner-clinic enrollment relationship;

FIG. 9 is a data flow chart for identifying and quantifying clinic-group ownership relationship;

FIG. 10 is a data flow chart for identifying and quantifying a practitioner-facility procedure relationship;

FIG. 11 is a data flow chart for identifying and quantifying a practitioner-facility employment relationship;

FIG. 12 is a data flow chart for identifying and quantifying a facility-system ownership relationship;

FIG. 13 is a data flow chart for identifying and quantifying a facility-clinic location-based relationship;

FIG. 14 is a schematic flow chart diagram of a method for matching healthcare claims data; and

FIG. 15 is a schematic diagram illustrating components of an example computing device.

DETAILED DESCRIPTION

Disclosed herein are systems, methods, and devices for merging healthcare claim data for identifying and quantifying relationships between healthcare entities. In an embodiment, carrier claims are matched with facilities and/or facility claims, and unmatched claims are assigned to certain providers. The matched claim data can be leveraged to identify various relationships between healthcare entities.
Current understanding of the healthcare industry in the United States is extremely fragmented. In some instances, it is difficult or impossible to identify systems of care including financial, employment, and enrollment relationships between healthcare entities. The healthcare industry uses multiple data sources for storing billing, procedure, and facility records. There is no one data source that is ideal or reliable for identifying the numerous relationships between healthcare entities. Because healthcare data is fragmented, it can be beneficial to match different types of healthcare data. The matched data can be assessed to identify and quantify relationships between different entities.
Embodiments of the disclosure leverage multiple data sources to describe relationships precisely and completely between healthcare entities. Relationships between practitioners and other healthcare entities cannot be viewed as binary. There are multiple types of affiliations between healthcare entities, and each affiliation may be characterized in terms of its strength. An affiliation reported as merely binary (i.e. yes/no, exists/does not exist, and so forth) masks important information.
Embodiments of the disclosure begin at the level of individual practitioner billing and procedure codes and build from there to identify and quantify relationships between other healthcare entities. By tracking the relationships of individual practitioners to higher level entities, the connections between practitioners and multiple other entities can be identified. This is an improved and more streamlined method when compared with viewing all organizations as discrete, mutually exclusive sets of practitioners.
Embodiments of the disclosure interpret affiliation metrics based on an individualized perspective. For example, a physician's affiliation with a hospital has two perspectives: the physician's perspective and the hospital's perspective. The physician may view the hospital as a necessary portion of the practice that enables the physician to perform certain procedures. The hospital may view the physician as one of many, and the physician's procedures performed at the hospital may represent a very small portion of all procedures performed at the hospital. Understanding affiliations from both perspectives is more informative than viewing the affiliations from only one perspective.
Embodiments of the disclosure describe affiliations in terms of real-world activities that link practitioners to other healthcare entities. This can be performed by assessing disparate data sources in terms of real-world actions or relationships. Some actions, such as referrals or billing of office claims, may come naturally from a single data source. Other actions, such as geographic practice locations and clinic ownership, require synthesis of multiple data sources. The goal is not merely to represent the data sources, but to leverage the data sources to represent the real world. This results in new metrics and relationships that did not exist before. In embodiments of the disclosure, raw data is manipulated to identify real-world relationships that could not previously be identified or quantified.
Embodiments of the disclosure state affiliations between healthcare entities through action. For example, rather than querying practitioners and other healthcare entities about how they believe they are affiliated, it is more accurate to assess actual behaviors that illuminate real-world relationships free from spin, bias, ignorance, misunderstanding, or self-reported outcomes.
Before the structures, systems, and methods for merging healthcare data are disclosed and described, it is to be understood that this disclosure is not limited to the particular structures, configurations, process steps, and materials disclosed herein as such structures, configurations, process steps, and materials may vary somewhat. It is also to be understood that the terminology employed herein is used for the purpose of describing particular embodiments only and is not intended to be limiting since the scope of the disclosure will be limited only by the appended claims and equivalents thereof.
In describing and claiming the subject matter of the disclosure, the following terminology will be used in accordance with the definitions set out below.
It must be noted that, as used in this specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise.
As used herein, the terms “comprising,” “including,” “containing,” “characterized by,” and grammatical equivalents thereof are inclusive or open-ended terms that do not exclude additional, unrecited elements or method steps.
As used herein, the phrase “consisting of” and grammatical equivalents thereof exclude any element or step not specified in the claim.
As used herein, the phrase “consisting essentially of” and grammatical equivalents thereof limit the scope of a claim to the specified materials or steps and those that do not materially affect the basic and novel characteristic or characteristics of the claimed disclosure.
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers are used throughout the drawings to refer to the same or like parts. It is further noted that elements disclosed with respect to embodiments are not restricted to only those embodiments in which they are described. For example, an element described in reference to one embodiment or figure, may be alternatively included in another embodiment or figure regardless of whether or not those elements are shown or described in another embodiment or figure. In other words, elements in the figures may be interchangeable between various embodiments disclosed herein, whether shown or not.
Referring now to the figures, FIG. 1 illustrates a framework 100 that outlines affiliations between healthcare entities. The framework 100 is built from the ground up and begins with the practitioner 102. The practitioner may be affiliated with facilities 110 and/or clinics 106. A facility 110 may be affiliated with a system 118. A clinic 106 may be affiliated with a group 114. There may be affiliations between systems 118 and groups 114 and between facilities 110 and clinics 106.
In an embodiment of the framework 100, a distinction is drawn between systems 118 that may own facilities 150, and groups 114 that may own clinics 106. This distinction is made for illustrative purposes and to increase the accuracy of conclusions drawn from assessing healthcare affiliations. In some instances, this distinction does not exist in the real world, and systems 118 and groups 114 functionally operate as the same entities. This serves as justification for the ground-up approach that permits individual practitioner behaviors to be leveraged to describe the relationships of higher-level entities with one another.
The practitioner 102 is a healthcare practitioner such as a physician (Doctor of Medicine), physician assistant, nurse practitioner, podiatrist, dentist, chiropractor, psychologist, optometrist, nurse midwife, clinical social worker, and so forth. The practitioner 102 may be a single person licensed to provide healthcare advice or guidance, perform procedures, prescribe medications, and so forth. The practitioner 102 may be a solo practitioner, may be associated with a group of other practitioners 102 in a clinic 106 or other group setting, may be employed by a facility 110 such as a hospital, may be employed as an in-house practitioner, and so forth. In some instances, it can be beneficial to identify and quantify the practitioner's 102 relationships with other entities such as clinic 106, facilities 150, groups 114, and systems 118.
The practitioner 102 may be associated with a practitioner ID 104. In some embodiments, the practitioner ID is an individual NPI (National Provider Identifier). In the United States, an individual National Provider Identifier (NPI) is a Health Insurance Portability and Accountability Act (HIPAA) administrative standard. An individual NPI is a unique identification number for covered healthcare providers. In the United States, covered healthcare providers, health plans, and healthcare clearinghouses are directed to use NPIs in administrative and financial transactions. It should be appreciated that the practitioner 104 may be associated with any unique identifier and does not need to be associated with a National Provider Identifier. The use of some other unique identifier does not depart from the scope of the disclosure. The practitioner ID 104 is a unique code associated with the practitioner 102. It should be appreciated that the practitioner ID 104 is any unique code associated with the practitioner 102 and can include other codes without departing from the scope of the disclosure.
The clinic 106 is a group of practitioners, a single practitioner, or some other entity that is primarily focused on the care of outpatients. The clinic 106 may be an outpatient clinic, an ambulatory care clinic, a physical therapy clinic, a specialist clinic, an urgent care clinic, an employer-funded in-house healthcare clinic, and so forth. The clinic 106 may be a group of practitioners that practice together at the same physical location or at different physical locations. The clinic 106 may include one or more practitioners 102 that practice telehealth care over the phone, over video communications, or by some other form of communication. The clinic 106 may be privately operated or publicly managed and funded. The clinic 106 may be suited for covering primary healthcare needs or specialized outpatient healthcare needs for populations of communities, in contrast with larger hospitals that offer specialized treatments and admit inpatients for overnight stays. The clinic 106 is not limited to only providing outpatient care.
The clinic 106 may be associated with a clinic ID 108. In some embodiments, the clinic ID 108 is an organization NPI (National Provider Identifier). In the United States, an organization National Provider Identifier (NPI) is a Health Insurance Portability and Accountability Act (HIPAA) administrative standard. An organization NPI is a unique identification number for covered healthcare clinics. The clinic ID 108 is a unique code associated with the clinic 106. If the clinic 106 has multiple geographic locations, then each of the multiple geographic locations for the clinic 106 may have a unique clinic ID 108. In some instances, two or more locations for the same clinic 106 share a clinic ID 108. It should be appreciated that the clinic 106 may be associated with any unique identifier and does not need to be associated with an organization NPI. The use of some other unique identifier does not depart from the scope of the disclosure.
The facility 110 is a physical or virtual healthcare location where an individual can receive care from a practitioner 102. The facility 110 may include hospitals, ambulatory surgical centers, birth centers, blood banks, dialysis centers, hospice centers, imaging and radiology centers, mental health and addiction treatment centers, nursing homes, orthopedic and other rehabilitation centers, telehealth systems, and so forth. In some implementations, it is not necessary to provide a formal definition for a facility 110 versus a clinic 106, and this distinction can be drawn based on the factual circumstances of various healthcare entities.
In an example embodiment, the facility 110 is linked to a facility ID 112. In some embodiments, the facility ID 112 is a Centers for Medicare and Medicaid Services (CMS) Certification Number, which is referred to as a CCN. In the United States, the CCN is the facility's 110 unique identification code that is linked to the facility's 110 provider agreement for Medicare billing. In some instances, the CCN is referred to as the facility's 110 “provider number.” The facility ID 112 is used for submitting and reviewing the facility's 110 cost reports. It should be appreciated that the facility 110 may be associated with any unique identifier and does not need to be associated with a CCN. The use of some other unique identifier does not depart from the scope of this disclosure.
The group 114 is a healthcare entity that owns one or more clinics 106. The group 114 may alternatively be referred to as a “provider group.” In some instances, there is no real-world distinction between groups 114 and systems 118, and this distinction is made in the systems, methods, and devices disclosed herein for the purpose of improving analytics on various healthcare entities. In some instances, a single healthcare entity may be referred to as a group 114 and as a system 118 for purposes of improving the analytics described herein.
The group 114 may be associated with a group ID 116. In some embodiments, the group ID 116 is a PAC ID (Practice Access Code ID) assigned by PECOS (Provider Enrollment, Chain and Ownership System). The PECOS is a system used in the United States and enables practitioners and other healthcare facilities to register with the Centers for Medicare and Medicare Services. PECOS is the Provider, Enrollment, Chain, and Ownership System. The system 118 may further be associated with the group ID 116. In some cases, a group 114 and a system 118 are the same entity and are associated with the same group ID 116. In some cases, a group 114 and a system 118 are separate entities to the degree that the group 114 is associated with its own group ID 116 and the system 118 is associated with its own system ID 120.
The system 118 is a healthcare entity that owns one or more facilities 110. In some instances, there is no real-world distinction between groups 114 and systems 118, and this distinction is made in the systems, methods, and devices disclosed herein for the purpose of improving analytics on various healthcare entities. In some instances, a single healthcare entity may be referred to as a group 114 and as a system 118 for purposes of improving the analytics described herein.
There are numerous metrics that can be calculated based on the relationships between practitioners 102, clinics 106, facilities 110, groups 114, and systems 118. In some cases, the metrics are determined based on claims billed by any of the entities described in FIG. 1. Some basic affiliation metrics that can be calculated include practitioner billing metrics, clinic billing metrics, practitioner enrollment metrics, clinic enrollment metrics, practitioner-group billing metrics, group billing metrics, practitioner-facility procedure volume metrics, facility procedure volume metrics, practitioner-facility employment metrics, facility-clinic distance metrics, and others. The practitioner billing metric is the proportion of a practitioner's total office claims billed to a certain clinic associated with a specific clinic ID 108. The clinic billing metric is the proportion of total office claims billed under a clinic performed by a given practitioner. The practitioner enrollment metric is the clinics at which a practitioner is enrolled in the PECOS. The clinic enrollment is the practitioner(s) enrolled in the PECOS under a clinic. The practitioner-group billing is the proportion of the practitioner's office claims billed under any of the group's clinics. The group billing is the proportion of all office claims billed under any of the group's clinics that were performed by a specific practitioner. The practitioner-facility procedure volume is the proportion of a practitioner's total procedure claims performed at each facility. The facility-procedure volume is the proportion of the procedures performed at the facility performed by each practitioner. The practitioner-facility employment is the level of confidence that the practitioner is employed by a given facility. The facility or clinic distance is the distance between a clinic and a facility in miles or some other distance measurement.
FIG. 2 is a schematic diagram of a system 200 for data communication between a data merging component 202 and internal and external data sources. The data merging component 202 manipulates and matches data from multiple sources to generate matched data. The matched data can then be analyzed to identify and quantify relationships between different healthcare entities. The data merging component 202 performs these calculations based on real-world claim data and/or enrollment data that can be stored in a combination of internal and external data sources. The data merging component 202 may communicate with one or more of an internal data source 204 and an external data source 206. The internal data source 204 may be a database, data store, or other memory device that is “internal” to the data merging component 202 or is managed by the same entity as the data merging component 202. The external data source 206 may be a database, data store, or other memory device that is “external” to the data merging component 202 or is managed by some other entity such that the data merging component 202 must access that data by way of an Application Program Interface (API), by receiving a file, by accessing an external server, and so forth.
In an embodiment, the data merging component 202 communicates directly with an external data source 206 that is managed or owned by a third-party entity. In an embodiment, the external data source 206 is owned and managed by the Medicare system operated by the United States government, or by some other entity that has been tasked with managing data for the Medicare system. In an embodiment, the external data source 206 is a relational database, and the data merging component 202 communicates with the relational database by way of an Application Program Interface (API). In an embodiment, the external data source 206 is an encrypted hard-drive that has been shared with the data merging component 202. In an embodiment, the external data source 206 is a virtual data center, and the data merging component 202 accesses the data on a virtual server after signing in or undergoing some other authentication step.
In an embodiment, the data merging component 202 communicates with an internal data source 204 that is not managed by some other third-party entity. The internal data source 204 may include a file that has been downloaded or otherwise received from some third-party entity, such as the Medicare system. After the file has been downloaded, the file can be managed and manipulated by the data merging component 202. The internal data source 204 may include an encrypted hard-drive or downloaded encrypted file that is provided by a third-party, such as the Medicare system.
The data merging component 202 may receive and translate information from multiple different sources. In an example implementation, the data merging component 202 receives enrollment information from a central data warehouse that may be operated internally or by a third-party. The data merging component 202 further receives claims data from a different source, for example via a secure connection to a virtual data store by way of an API, by accessing an encrypted hard drive, or accessing an encrypted file that has been downloaded by way of a network connection.
In an embodiment, the data stored in the internal data source 204 has been “cleaned” or pared down to only include necessary or critical information. This can be beneficial to ensure the totality of the data is a usable size that can be efficiently queried, analyzed, and manipulated. For example, the raw data retrieved from the external data source 206 may include numerous data fields that are not necessary for identifying a certain relationship between healthcare entities. The unnecessary data may be eliminated, and only the necessary data may be stored on the internal data source 204. In an embodiment, the raw data is cleaned and stored in a relational database.
In an embodiment, the data merging component 202 analyzes information stored in the internal data source 204 and/or the external data source 206 by identifying relationships between individual practitioners 102 and their associated clinics 106 and groups 114. In an example use-case, the data merging component 202 identifies that Doctor A is performing work for Clinic B. The data merging component 202 then identifies all of the practitioners that associate with Clinic B and assesses the carrier claims billed by those practitioners. The data merging component 202 aggregates the claim information for all practitioners in Clinic B and combines the information in an effort to answer specific questions, such as whether a certain practitioner is employed by a facility.
The data merging component 202, or some other module or component in communication with the data merging component 202, may create intermediary files or tables within a relational database. The intermediary files or tables may include certain information columns that are pertinent to answer a specific question, such as identifying or quantifying a relationship between two or more healthcare entities. This can be beneficial to ensure that each intermediary file or table is no bigger than it needs to be to include all necessary information for answering the specific question. This decreases the amount of disc storage and/or Random Access Memory (RAM) needed to analyze the information and calculate the answer to the specific question.
FIG. 3 is a schematic diagram of a system 300 for performing electronic data security measures on data received from the external data source 206. The data merging component 202 receives claims data (see 302) from an external data source 206. The claims data may include carrier claims, facility claims, and other claims generated or processed by private or public healthcare entities. Claims data includes sensitive information such as protected personal information (PPI) and personal identifiable information (PII), and therefore, the claims data must be encrypted or otherwise secured.
In an embodiment, the data merging component 202 receives claims data by securely communicating with a virtual data center (see 310). The virtual data center may be provided by a private or public healthcare entity. In an embodiment, an account is created for a user associated with the data merging component 202, and the user can sign into the virtual data center with the account. The user can then access the data stored in the virtual data center 310 by way of the account. The data may be encrypted or non-encrypted based on the security measures of the virtual data center. In an embodiment, the data is non-encrypted when viewed by way of a network connection, and the data is encrypted if downloaded for offline use and manipulation. If the data is downloaded in an encrypted form, then the data must be de-encrypted prior to analysis and manipulation.
In an embodiment, the data merging component 202 receives claims data by way of an encrypted hard-drive. The encrypted hard-drive may be provided by the source of the data, such as private or public healthcare entity. In an embodiment, the data merging component 202 receives claims data by way of an encrypted file that has been downloaded by way of a network connection. The data merging component 202 undergoes an electronic data security measure 308 by de-encrypting the claims data (see 312).
FIG. 4 is a schematic diagram of a data flow 400 for merging carrier claims 402 and facility claims 404. The data merging component 202 receives claim information and matches carrier claims 402 to facility claims 404 to generate matched claims.
A carrier claim 402 is a non-institutional medical billing claim submitted by or on behalf of a practitioner 102. The carrier claim 402 may be billed for outpatient or inpatient services. The carrier claims 402 used by the data merging component 202 may include carrier claims 402 submitted through the Medicare system implemented in the United States and may additionally include carrier claims for private entities such as private health insurance agencies. If the carrier claims 402 include Medicare claims, then the carrier claim may be submitted on the health insurance claim form CMS-1500 used by the United States Medicare system.
Carrier claims 402 include information about a service provided by a practitioner 102 in an outpatient or inpatient setting. In some instances, only a portion of the information included in the carrier claim 402 is relevant to the analysis of whether a relationship exists between two or more healthcare entities. Carrier claims 402 may include a patient identifier (ID) 406, which may include a numerical or alphanumerical code assigned to the patient, and may further include the patient's name, address, or other contact information. Carrier claims 402 further include a practitioner ID 104 which may specifically include an individual NPI. The carrier claim 402 may include a clinic ID 108, or some other information identifying the name, location, or contact information of the clinic under which the service was performed. The carrier claim 402 includes an indication of the date of service 408 when the service was performed or on what date the service began if the service extended over multiple days. The carrier claim 402 includes an indication of the place of service 410, and this may be a numerical or alphanumerical code identifying a type of facility, and may also include a name, address, or other contact information for the facility. The carrier claim 402 includes one or more billing codes 412 identifying the services or procedures that were performed by the practitioner 102. The billing code 412 may include a Healthcare Common Procedure Coding System (HCPCS) code. The carrier claim 402 may further include an indication of the days or units 414 indicating a duration of time the procedure occurred.
The facility claims 404 may include similar information. If the facility claims 404 include Medicare claims, then the facility claims may be submitted on the health insurance claim form UB-40 used by the United States Medicare system. The facility claims 404 may include, for example, the patient ID 406, practitioner ID 104, facility ID 112, date of service 408, place of service 410, billing code 412, days or units 414, and an indication of the type of visit 416. The facility ID 112 identifies the facility at which the procedure was performed, and may take the form of an NPI, CMS Certification Number or CCN, or some other way of identifying the name, location, and contact information of the facility. The indication of the type of visit 416 may be a numerical code indicating whether the visit was an emergency, an outpatient visit, an inpatient visit, and so forth.
Carrier claims 402 may include additional information not illustrated in FIG. 4, For example, carrier claims 402 may include an indication of whether the bill is being submitted through a government-funded plan such as Medicare, Medicaid, Tricare, or CHAMPVA, or a private health insurance plan. The carrier claim 402 may include insurance information, such as the insured's ID number, name, address, birth date, policy name, group number, policy number, whether there is an additional health benefit plan, and so forth. The patient ID 406 information may include the patient's name, address, telephone number, and so forth. The carrier claim 402 may include an indication of whether the patient's condition is related to employment, an automobile accident, or some other accident. The date of service 408 information may include an indication of what date the current illness, injury, pregnancy, or other condition began. The date of service 408 may further include other applicable dates. The carrier claim 402 may include information about what dates the patient was unable to work in his or her current occupation, dates of hospitalization related to the current services, charges made to an outside lab in relation to the current services, and so forth. The carrier claim 402 may include information about a referring provider or other source, such as the referring provider's individual NPI. The billing code 412 may include a diagnosis code or an indication of the nature of illness or injury and may further include a CPT or HCPCS code indicating the procedures, services, or supplies used in connection with the billed claim. For each billing code 412 listed in the carrier claim 402, there is also an indication of the date of service, the place of service, the diagnosis pointer, the charges, the days or units, and the rendering provider's practitioner ID 104 for that service, procedure, or supply. The carrier claim 402 may further include a federal tax ID number for the practitioner 102, a patient account number relating to the practitioner's practice, a total charge and the amount paid. The carrier claim 402 additionally includes information on the facility where the service, procedure, or supply was administered to the patient. The information on the facility may include the name, address, contact information, or a clinic ID 108 or facility ID 112 related to the facility.
Facility claims 404 may include additional information not illustrated in FIG. 4. The facility claims 404 may include all of the information listed above with reference to the carrier claims 402. The facility claims 404 may additionally include information on when the patient was admitted to the facility, the condition codes pertaining to why the patient was admitted to the facility, and the dates the patient was in-patient or out-patient at the facility. The facility claim 404 may include numerous practitioner IDs 104 pertaining to each of the numerous practitioners 102 who assisted in the patient's care while the patient was at the facility 110. Each service, procedure, or supply administered to the patient during the patient's stay at the facility 110 may linked to a certain practitioner 102.
FIG. 5 is a schematic diagram of PECOS enrollment 502 information relationships. In the United States, the PECOS is used to track the status of healthcare practitioners, and the relationships those healthcare practitioners have with other entities, such as clinics 106, facilities 110, and groups 114. In the PECOS, a practitioner 102 is assigned a practitioner ID 104 in the form of an individual NPI. Additionally, other entities are assigned identification numbers. A clinic 106 is assigned a clinic ID 108 in the form of an organization NPI. A facility 110 is assigned a facility ID 112 in the form of a CMS Certification Number (CCN). A group 114 is assigned a group ID 116 in the form of a PAC ID.
Within PECOS, a practitioner 102 can assign rights to another entity, such as a clinic 106, facility 110, and/or group 114 by storing a reassignment file that links the practitioner's 102 practitioner ID 104 to the clinic ID 108, the facility ID 112, and/or the group ID 116, as applicable. The practitioner 102 can enroll under another entity, such as the clinic 106, the facility 110, and/or the group 114. The practitioner 102 can submit an indication to PECOS that the practitioner 102 is professionally associated with a clinic 106, facility 110, and/or group 114.
In an example, a practitioner is an emergency medicine physician employed by a hospital. The physician is enrolled in PECOS and supplies an individual NPI, assigned previously by the National Plan and Provider Enumeration System (NPPES). A PECOS Associate Control (PAC) ID is assigned to the practitioner, and an enrollment ID is assigned to each of the practitioner's enrollments. Additionally, the hospital is enrolled in PECOS as a facility and supplies an NPI previously assigned. A PECOS Associate Control (PAC) ID is assigned to the facility, and an enrollment ID is assigned to each of the facility's enrollments. The physician may indicate within PECOS that the physician has assigned rights to the hospital, or that the physician is otherwise associated with the hospital, by linking one or more of his or her enrollment IDs with one or more enrollment IDs of the hospital in a reassignment file.
The PECOS enrollment 502 information is not always accurate. The enrollment information within PECOS is often stale with respect to real-world relationships. For example, a practitioner may transition from being employed by a hospital to operating as a sole proprietor. This change is reflected in PECOS only if the practitioner or some other entity indicates within PECOS that the change has occurred. In such an instance, PECOS is not reliable to indicate the real-world professional relationships for that practitioner. In such an instance, the carrier claims submitted by the practitioner can be analyzed in lieu of the information in PECOS, and the analysis gleaned from the carrier claims can be used to override the information in PECOS to identify the practitioner's real-world relationships.
FIG. 6 is a schematic flow chart diagram of a data flow 600 for matching carrier claims 402 to facilities 110 and/or facility claims 404 to generate a matched data set. A computer does this by matching, in steps or stages, various data points in a carrier claim to data points in a facility. In an embodiment, the facility claims 404 are processed with facility IDs 112 and the carrier claims 402 are processed with the practitioner's practitioner ID 104. The data flow 600 illustrates a plurality of matching iterations that may be completed in succession. In an embodiment, one matching iteration is completed, and a subsequent matching iteration is performed only on the remaining unmatched carrier claims that were not matched in the prior matching iteration. In an embodiment, each of the matching iterations comprises one or more metrics or variables that are used for the process of matching the facility IDs 112 and practitioner IDs 104 in furtherance of generating a matched data set, and these metrics or variables are illustrated in FIG. 6. The matched data set can be used to identify relationships between various healthcare entities.
In the data flow 600, the first metrics used in the merge process includes the patient, service date, and the billing code 412. The billing code 412 may be an HCPCS (Healthcare Common Procedure Coding System) code (see 602). In the United States, HCPCS codes are used for billing Medicare and Medicaid patients. The HCPCS codes are a collection of codes that represent procedures, supplies, products, and services which may be provided to Medicare beneficiaries and to individuals enrolled in private health insurance programs. The data flow 600 continues and the next metrics used in the merge process includes the patient, service data, and the practitioner's practitioner ID 104 (see 604). The data flow 600 continues and the next metric used in the merge process includes the inpatient location if the carrier claim 402 occurs during a hospitalization at the facility 110 (see 606). The next metrics used in the merge process includes the service date and the practitioner's most common facility (see 608). The next metric used in the merge process includes the most common facility for the practitioner based on the clinic ID 108 in the carrier claim 402 (see 610). The next metric used in the merge process is, again, the service date and the practitioner's most common facility (see 612). The next metrics used in the merge process include the service date and the practitioner's most common facility within a two-week time period (see 614). The next metrics used in the merge process include, again, the service date and the practitioner's most common facility (see 616). The next metric used in the merge process includes the practitioner's most common provider within a two-week period using the previously joined facilities (see 618). The next metric used in the merge process is the facility most closely attached to the clinic ID 108 based on the carrier claim 402 (see 620).
FIG. 7 is a schematic diagram of a data framework for identifying a billing relationship between a practitioner 102 and a clinic 106. The analysis described in connection with FIG. 7 can be used to determine at what clinic(s) 106 a practitioner 102 is billing for services. The billing relationship between practitioners 102 and clinics 106 is based on office-based carrier claims 402. In the United States, when a practitioner 102 bills Medicare for office-based services, a clinic ID 108 is provided on the carrier claim 402. The practitioner-clinic billing 704 relationship may be analyzed and quantified based on the data associated with carrier claims 402. The practitioner-clinic billing 704 relationship is measured by calculating the percentage of a practitioner's 102 total office-based claims that are billed under the clinic ID 108 associated with the clinic 106. If a practitioner 102 bills more frequently under a first clinic than a second clinic, the practitioner 102 is more strongly affiliated with the first clinic.
FIG. 8 is a schematic diagram of a dataflow for identifying an enrollment relationship between practitioners 102 and clinics 106. The analysis described in connection with FIG. 8 can be used to determine under what clinic(s) 106 the practitioner 102 is enrolled. This is referred to as the practitioner-clinic enrollment 708 relationship. In the United States, individuals and organizations participating in Medicare enroll in PECOS (Provider Enrollment and Chain/Ownership System). PECOS is a system by which practitioners 102 can enroll in the Medicare healthcare system in the United States. A practitioner 102 may enroll under PECOS using a practitioner ID 104 and may designate enrollment under one or more clinic IDs 108 associated with clinics 106 or other organizations. When a practitioner 102 enrolls in PECOS, the practitioner 102 is assigned a group ID 116 and/or system ID 120 (in some embodiments, the group ID 116 and the system ID 120 are the same identifier because the group and system are the same entity) which serves as a unique individual professional identification for interactions with PECOS enrollment 504.
When a practitioner ID 104 or a clinic ID 108 is enrolled in PECOS enrollment 504, the NPI is assigned a unique enrollment identification (ID). An enrollment ID can be used by a practitioner 102 to reassign billing rights to an organization enrollment. A reassignment constitutes an enrollment relationship between a practitioner 102 and an organization such as a clinic 106. Further in the Medicare systems in the United States, each clinic 106 is enrolled under a group ID 116 and/or system ID 120. Because each clinic 106 is associated with a PAC ID, and the PAC ID is additionally associated with a group or system, the enrollment relationship between practitioners 102 and clinics 106 rolls up to groups 114 and systems 118 that are associated with PAC IDs.
A practitioner 102 may reassign to multiple organization enrollments under different group IDs 116 and/or system IDs 120. In practice, these enrollments are sometimes retained after a practitioner transitions to a new practice or clinic 106. Because some enrollments may be “stale” and may no longer reflect the practitioner's 102 actual real-world associations, some enrollments may be discarded. Further, some enrollments may be used only infrequently. This may be the case when, for example, a practitioner 102 who reassigned rights to a specific clinic or group to have the ability to perform procedures for particular patients. In current Medicare systems in the United States, there is no information available on how frequently an enrollment relationship is used by a practitioner 102 other than through billing relationships as discussed in connection with FIG. 7. For this reason, enrollment relationships may be used only to roll clinic 106 locations up to groups 114 or systems 118 when necessary.
In an embodiment, an enrollment relationship between a practitioner 102 and a clinic 106 is identified by retrieving distinct practitioner ID 104 and clinic ID 108 relationships from enrollment and reassignment files over time. This analysis can result in determining a practitioner enrollment metric and a clinic enrollment metric. The practitioner enrollment metric identifies one or more clinics 106 at which a practitioner 102 in enrolled in Medicare in the United States. The clinic enrollment metric identifies one or more practitioners 102 that have enrolled in Medicare under a certain clinic 106.
FIG. 9 is a schematic diagram of a data flow for analyzing ownership relationships between clinics 106 and groups 114. The analysis discussed in connection with FIG. 9 can be used to identify group(s) 114 that own one or more clinics 106. This is referred to as the clinic-group ownership 710. In the framework 100 described herein, clinics 106 are owned by groups 114. A group 114 is represented by a group ID 116. In many cases, a clinic ID 108 associated with a clinic 106 appears in an enrollment file for the group 114 with the group ID 116 stated explicitly.
In some cases, the clinic ID 108 for a clinic 106 is not included in PECOS enrollment 504. In these cases, a group ID 116 may be inferred based on enrollment relationships of practitioners 102 to clinics 106. In an embodiment, when more than 50% of practitioners 102 (weighted by the practitioners 102 billing relationship to the clinic 106) enroll under a group ID 116, that group ID 116 is imputed to the owner of the clinic ID 108 for the clinic 106. Alternatively, a group ID 116 may be imputed to the owner of the clinic ID 108 for the clinic 106 if the group ID's 116 squared proportion of provider enrollments exceeds 50% of the sum of the squared proportions of all enrollments for the clinics' 106 billing practitioners 102 (weighted by the practitioners 102 billing relationship to the clinic 106). A portion of these cases have a perfect ownership relationship wherein all billing practitioners reassign to the same group ID 116. In some cases, a clinic 106 has less than perfect ownership when the group ID 116 is imputed to the clinic 106.
In an embodiment, the clinic-group ownership 710 is determined based on carrier claims 402 and data retrieved from the PECOS enrollment 504. In some cases, the clinic ID 108 for the clinic 106 may be identified based on clinic enrollment to retrieve the group ID 116. Where no enrollment exists for the clinic 106, a method includes using reassignments indicated in PECOS enrollment 504 of the practitioners 102 to impute a group ID 116 to the clinic 106. In an embodiment, the reassigned group IDs 116 for practitioners 102 billing carrier claims 402 under a clinic ID 108 are identified using the enrollment and reassignment files. The proportion of all clinic ID 108 and group ID 116 combinations represented by each combination are calculated. The proportions may be weighted by the practitioner's 102 billing relationships and by the number of claims a practitioner 102 bills at the clinic 106. The level of concentration each practitioner 102 shares with each clinic ID 108 is calculated by taking the sum of the squared proportions.
In an embodiment, a certain group ID 116 and clinic ID 108 combination is selected if the combination has more than 50% of the reassignments of the clinic's 106 practitioners. This can be determined by using the enrollment and reassignment files to identify the reassigned group IDs 116 of practitioners 102 who bill carrier claims 402 under a clinic ID 108. In an embodiment, a certain group ID 116 and clinic ID 108 combination is selected if the combination has a squared proportion greater than 50% of the concentration of a practitioner's 102 shares within the clinic 106. This can be calculated by taking the sum of the squared proportions as done in the Herfindahl-Hirschman Index.
The metrics pertaining to the clinic-group ownership 710 include practitioner group billing and group billing. The practitioner group billing is the proportion of the practitioner's 102 office claims billed under any of a group's 114 clinics 106. The group billing is the proportion of all office claims billed under any of the group's 114 clinics 106 that were performed by a specific practitioner 102.
FIG. 10 is a schematic diagram of a method for identifying and quantifying the practitioner-facility relationship with respect to procedures. The analysis discussed in connection with FIG. 10 can be used to determine at what facilities 110 a practitioner 102 is performing procedures. This is referred to as the practitioner-facility procedures 714 metric. When a practitioner 102 performs a procedure at a facility 110, a facility claim 404 is submitted that includes the practitioner's 102 practitioner ID 104, and clinic ID 108 for an associated clinic 106, and a CMS Certification Number (facility ID). In some embodiments, the facility ID 112 is a CMS provider number. The proportion of procedures performed by a practitioner at a certain facility 110 is quantified based on the relationship in the claims between practitioner IDs and facility IDs. Further, the proportion of the facility's 110 procedure volume that were performed by a certain practitioner 102 is quantified based on the relationship in the claims between practitioner IDs 104 and facility IDs 112. These procedure volumes provide a link between practitioners 102 and facilities 110 apart from any official ownership or employment relationships.
The raw data input includes all facility claims 404 files such as inpatient, outpatient, hospice, and so forth. The practitioner-facility procedure 714 is determined by identifying the distinct NPIs that participated in each claim. This can be performed for each claim in a given year. Participating entities are denoted in the attending, operating, rendering, and other identifier fields within the facility claims 404. An identifier (e.g., a National Provider Identifier (NPI)) can appear in more than one of these fields and the duplicates should be handled when calculating the practitioner-facility procedures 714 metric. For each pair including a participating practitioner 102 and a facility 110, the number of claims represented by the pair is counted. The claim numbers by distinct pair are summed across all claim files. This process may be repeated for each year of available claims data.
The practitioner-facility procedures 714 metrics results in a practitioner facility procedure volume metric and a facility procedure volume metric. The practitioner facility procedure volume metric is the proportion of a practitioner's total procedure claims performed at a certain facility. A practitioner's procedure claim is a claim in which the practitioner participated in the procedure. The facility procedure volume is the proportion of procedures performed at a certain facility by each of one or more practitioners using the certain facility.
FIG. 11 is a schematic diagram of a data flow for identifying employment relationships between practitioners and facilities. The analysis discussed in connection with FIG. 11 can be used to determine what facilities directly employ a practitioner. This is referred to as the practitioner-facility employment 716 metric. When a practitioner is directly employed by a facility, the practitioner's billed claims will likely be processed by the facility. In such an instance, the facility might submit a bill including facility charges and practitioner charges, and the practitioner does not send a separate bill. This billing relationship impacts the dynamic between the practitioner and the facility, and further impacts the dynamics between the practitioner and other entities such as healthcare groups, healthcare systems, health insurance agencies, patients, and so forth. Therefore, it can be important to understand whether a practitioner 102 has a direct employment relationship with a facility 110.
In some cases, a practitioner 102 is employed directly by a facility 110. This is distinct from practitioners 102 who practice exclusively at the facility 110. In an embodiment, to determine employment, office-based claims with facility IDs (Centers for Medicare and Medicaid Services (CMS) Certification Numbers) 112 are matched using a multiple step matching process. The proportion of a practitioner's total carrier claims 402 performed in a facility is calculated based on the result of the multiple step matching process.
In some instances, a practitioner 102 is paid less on an office-based claim if there is a facility fee associated with the claim. This occurs because the facility 110 is also billing for the service. The total of the practitioner's fee and the facility fee in these cases is generally higher than the practitioner's fee would be alone at a non-facility setting. Identifying this scenario can lead to concluding that practitioners 102 billing office claims at a facility 110 are employed by the facility. When performing this analysis on typical real-world data, the analysis confirms that a majority of practitioners bill all carrier claims 402 or no carrier claims 402 under a facility 110. In an embodiment, practitioners with claims that are all matched to a facility are deemed employed by that facility.
The practitioner-facility employment 716 determination can be performed based on a claims analysis file. The claims analysis file is generated based on claims analytics and practitioner affiliations. The claims analytics and practitioner affiliations are identified based on billed claims. In an embodiment, the practitioner-facility employment 716 determination is calculated at least in part based on the result of a multiple step data merging process for matching facility claims 404 (facility IDs) to carrier claims 402. The data merging process occurs by attempting to match unmatched carrier claims 402 from a prior step to practitioners using one or more of the following variables. A possible variable is the patient, service data, and HCPCS (Healthcare Common Procedure Coding System) code. The HCPCS code may alternatively be referred to as a “procedure code” herein. A further possible variable is the patient, service date, and practitioner NPI. A further possible variable is the match based on inpatient location if the carrier claim occurs during a hospitalization and is then matched to that facility. A further possible variable is the service date and the practitioner's most common facility. A further possible variable is the most common facility based on the clinic ID in the carrier claim 402. A further possible variable is the service date and the practitioner's most common facility. A further possible variable is the service date and the practitioner's most common facility within a two-week range. A further possible variable is the service date and the practitioner's most common facility. A further possible variable is the practitioner's most common provider within two weeks using the previously joined facilities. A further possible variable is the facility that is most closely attached with the clinic ID from the carrier claim.
In an embodiment, the facility claims 404 (facility IDs accessible via PECOS enrollment 504) are matched to carrier claims 402 using the following 10-step merge process. The merge occurs by attempting to match unmatched carrier claims 402 from the prior step to practitioners 102 using the following variables:

- a. Patient, service date, and HCPCS code;
- b. Patient, service date, and practitioner's practitioner ID;
- c. Inpatient location if the carrier claim occurs during a hospitalization at the facility;
- d. Service date and practitioner's most common facility;
- e. Most common facility based on the clinic ID in the carrier claim;
- f. Service date and the practitioner's most common facility (again);
- g. Service date and the practitioner's most common facility within a two-week time period;
- h. Service date and the practitioner's most common facility (again);
- i. Practitioner's most common provider within two weeks, using the previously joined facilities; and
- j. The facility most closely attached to the clinic ID from the carrier claim.

When the data has been merged, a method may further include calculating the percentage of a practitioner's 102 office claims that occurred at a facility 110 by collapsing the practitioner's practitioner ID 104 and the facility's clinic ID 108. In an embodiment, office claims that have a place of service code equal to eleven (office-based claims) or twenty-two (hospital outpatient department claims) are used to determine employment. The proportion of such claims that have place of service code twenty-two represents the strength of the practitioner's 102 employment relationship with the facility 110. A method may further include collapsing to the clinic 106 or group 114 level and saving a percent of the group's 114 practitioners 102 that are employed by facilities or systems. This can be performed for all years of available claims.
The merge process for matching carrier claims 402 to a facility 110 and/or facility claims 404 is a novel data manipulation process that is performed on a very large set of data. The number of carrier claims 402, facilities 110, and facility claims 404 can be enormous for a singular calendar year. This number of claims is impossible for a single human or group of humans to process, and particularly within the same calendar year of the billed claims. The merge process is a novel set of rules specifying how a computer should match carrier claims 402 to a facility 110 and or to facility claims 404.
In an embodiment, the carrier claims 402, the facility IDs 112, and the facility claims 404 are stored in a database. The data (i.e., the combination of the carrier claims 402, the facility IDs 112, and the facility claims 404) is typically retrieved from larger files or data stores and includes superfluous information that is not necessary for identifying and quantifying the practitioner-facility employment 716 relationship. The data is therefore cleaned prior to storage in the database. The data is cleaned such that 10-step matching process can be performed on a manageable sum of data. In an embodiment, the data is equivalent to about 1 terabyte (TB) of data per claim year.
In an embodiment, the cleaned data is linked to a database platform. The database platform is in communication with a user interface (UI) such that the data can be viewed seamlessly. The data can be partitioned within the database based on calendar year, entity, practitioner 102, facility 110, facility ID 112, carrier claim 402, facility claim 404, and so forth. The database platform is built on highly modeled, as opposed to raw, data sources.
In an embodiment, as information stored in the database is changed, the practitioner-facility employment 716 metric is reevaluated. A change to the information stored in the database may reflect that a new facility 110 is added, a new practitioner 102 is added, there is a new relationship between a practitioner and a facility, there are new claims submitted, and so forth. The practitioner-facility employment 716 metric may be reevaluated to determine whether a new employment relationship has been formed, an employment relationship has been discontinued, or an employment relationship has changed. This reevaluation can be performed in real-time as the data as changed and can therefore provide an up-to-date and reliable representation of the real-world relationships between practitioners and facilities. Conducting this analysis by hand (by the human mind) in real-time would be so impractical that it could be considered impossible.
FIG. 12 is a schematic diagram of a data framework for identifying and quantifying the ownership relationship between a facility 110 and a system 118. The analysis described in connection with FIG. 12 can be used to determine what system owns a facility, and which facilities are owned by the system. The resulting metric is referred to as the facility-system ownership 718 metric.
The ownership relationship between a system 118 and one or more facilities 110 can be assessed using the enrollment file and claims-based link between clinic IDs and facility IDs. A facility claim 404 can include clinic IDs 108 and facility IDs 112 for the facilities 110 at which a practitioner 102 performs procedures. The distinct combinations of clinic ID 108 and facility ID 112 allow for a link between these two identifiers. In some instances, multiple clinic IDs 108 roll up to one system ID 120, and this typically indicates a different department within the facility or a change of ownership. In some instances, multiple facility IDs 112 link to the same clinic ID 108, and this typically occurs when a facility 110 makes a transition, such as an acute care hospital gaining critical access status. However, in most instances, clinic IDs 108 and facility IDs 112 match one-to-one. Using all facility ID 112 to clinic ID 108 matches and the PECOS enrollment 504 file (which contains enrollment of clinic IDs 108 under corresponding system IDs 120), a facility ID 112 can be rolled up to a system ID 120 in an ownership relationship. Further research can be performed to identify parent companies.
In an embodiment, the data inputs for identifying the facility-system ownership 718 relationship is the facility claims 404 for a facility 110 and the PECOS enrollment 504 file for the facility 110 and/or system 118. A method for determining the facility-system ownership 718 relationship includes one or more of the following steps. The method includes using the facility claims 404 to match facility IDs 112 to clinic IDs 108 for each claim year. The method includes using enrollment information from the PECOS enrollment 504 file to match clinic IDs 108 to system IDs 120. The method includes handling duplications such as system IDs 120 that may be owned by common parent organizations.
The facility system-ownership 718 relationship can be leveraged to identify multiple metrics, including the practitioner-system employment metric, the practitioner-system procedure volume metric, and the system procedure volume metric. The practitioner-system employment metric is a level of confidence that a practitioner 102 is employed by a system 118. The practitioner-system procedure volume is a proportion of all procedure claims in which the practitioner 102 participated that were performed at the system 118. The system procedure volume is a proportion of all procedures performed at a system 118 in which the practitioner 102 participated.
FIG. 13 is a schematic diagram of a data framework for identifying and quantifying the geographic proximity between a facility 110 and a clinic 106. The analysis described in connection with FIG. 13 can be used to determine how the geographic proximity of facilities 110 and clinics 106 that are affiliated under group IDs 116 and/or system IDs 120. This determination is referred to as the facility-clinic location 726 metric.
When facilities 110 and clinics 106 do not have an identity relationship by using a clinic ID 108 equal to a facility ID 112 of the same type (for example, a common NPI), the facilities and clinics may still be geographically located at the same location or in close geographic proximity to one another. This geographic proximity, together with other kinds of affiliation, can provide an indication of which entities within a network are likely to be operating together, even if the entities are not billing together or enrolling together under PECOS enrollment 504. A geographic distance measure can shed light on which practitioners 102 have an office at a given facility 110 in a geographic sense, even if not in an official sense. Address geocoding can be read from the NPPES (National Plan & Provider Enumeration System) and Provider of Services 724 files to assess geographic proximity.
In an embodiment, the data input for determining the facility-clinic location 726 metric is the carrier claims 402 of a practitioner 102, the facility claims 710 of a facility 110, and information pulled from PECOS enrollment 504. The information stored in carrier claims 402 can be assessed to identify whether there is a clinic-group ownership 710 relationship. The facility claims 404 can be assessed to identify whether there is a facility-system ownership 718 relationship. The information pulled from the PECOS enrollment 504 can be assessed to identify whether there is a clinic-group ownership 710 relationship, whether there is a facility-system ownership 718 relationship, whether there is a group-system identity 720 relationship, and/or whether there is a facility-clinic identity 722 relationship. The information stored in the NPPES and Provider of Services 724 files can be assessed, along with the other assessment to identify the facility-clinic location 726 relationship.
In an embodiment, a method for determining a facility-clinic location 726 relationship includes the following steps. The method includes, for clinics 106 and facilities 110 that have a common group ID 116 and/or system ID 120 ownership, use geocoding of addresses in the NPPES, Provider of Services 724 file (for facilities 110) and the NPPES registry (for clinics 106) to assess the geographic proximity between the clinics 106 and the facilities 110. The resulting facility-clinic location 726 metric is an indication of a geographic distance between a clinic 106 and a facility 110. The distance may be recorded in miles, kilometers, or some other suitable measurement.
FIG. 14 is a schematic flow chart diagram of a method 1400 for matching healthcare claims data. The method 1400 may be performed by a computing resource configurable to execute instructions stored in non-transitory computer readable storage media. In an embodiment, the method 1400 is executed by the data merging component 202.
The method 1400 begins and a computing resource identifies at 1402 a carrier claim processed by a practitioner. The step of identifying the carrier claim may include identifying a plurality of carrier claims processed by the practitioner over a time period, for example over one calendar year. The step of identifying the carrier claim may further include identifying only carrier claims in which the practitioner performed a procedure at a facility or clinic. The method 1400 continues and a computing resource matches at 1404 the carrier claim to a facility to generate a matched claim based on a claims factor. The step of matching the carrier claim to the facility may include matching a plurality of carrier claims to one or more facilities as deemed appropriate based on the claims factor. The step of matching the carrier claim to the facility may further include matching a plurality of carrier claims to a plurality of facility claims, wherein the facility claims are processed by the facility over the time period.
The method 1400 continues and a computing resources matches at 1404 the carrier claim to the facility based on one or more of the following claims factors (see 1406), including: a patient identifier, a date of service for a procedure billed on the carrier claim, a practitioner identifier associated with the practitioner, a facility identifier for an inpatient facility associated with the carrier claim if the carrier claim occurred during a hospitalization at the inpatient facility, or a most common facility associated with the practitioner.
Referring now to FIG. 15, a block diagram of an example computing device 1500 is illustrated. Computing device 1500 may be used to perform various procedures, such as those discussed herein. Computing device 1500 can perform various monitoring functions as discussed herein, and can execute one or more application programs, such as the application programs or functionality described herein. Computing device 1500 can be any of a wide variety of computing devices, such as a desktop computer, in-dash computer, vehicle control system, a notebook computer, a server computer, a handheld computer, tablet computer and the like.
Computing device 1500 includes one or more processor(s) 1504, one or more memory device(s) 1504, one or more interface(s) 1506, one or more mass storage device(s) 1508, one or more Input/output (I/O) device(s) 1510, and a display device 1530 all of which are coupled to a bus 1512. Processor(s) 1504 include one or more processors or controllers that execute instructions stored in memory device(s) 1504 and/or mass storage device(s) 1508. Processor(s) 1504 may also include various types of computer-readable media, such as cache memory.
Memory device(s) 1504 include various computer-readable media, such as volatile memory (e.g., random access memory (RAM) 1514) and/or nonvolatile memory (e.g., read-only memory (ROM) 1516). Memory device(s) 1504 may also include rewritable ROM, such as Flash memory.
Mass storage device(s) 1508 include various computer readable media, such as magnetic tapes, magnetic disks, optical disks, solid-state memory (e.g., Flash memory), and so forth. As shown in FIG. 15, a particular mass storage device 1508 is a hard disk drive 1524. Various drives may also be included in mass storage device(s) 1508 to enable reading from and/or writing to the various computer readable media. Mass storage device(s) 1508 include removable media 1526 and/or non-removable media.
I/O device(s) 1510 include various devices that allow data and/or other information to be input to or retrieved from computing device 1500. Example I/O device(s) 1510 include cursor control devices, keyboards, keypads, microphones, monitors or other display devices, speakers, printers, network interface cards, modems, and the like.
Display device 1530 includes any type of device capable of displaying information to one or more users of computing device 1500. Examples of display device 1530 include a monitor, display terminal, video projection device, and the like.
Interface(s) 1506 include various interfaces that allow computing device 1500 to interact with other systems, devices, or computing environments. Example interface(s) 1506 may include any number of different network interfaces 1520, such as interfaces to local area networks (LANs), wide area networks (WANs), wireless networks, and the Internet. Other interface(s) include user interface 1518 and peripheral device interface 1522. The interface(s) 1506 may also include one or more user interface elements 1518. The interface(s) 1506 may also include one or more peripheral interfaces such as interfaces for printers, pointing devices (mice, track pad, or any suitable user interface now known to those of ordinary skill in the field, or later discovered), keyboards, and the like.
Bus 1512 allows processor(s) 1504, memory device(s) 1504, interface(s) 1506, mass storage device(s) 1508, and I/O device(s) 1510 to communicate with one another, as well as other devices or components coupled to bus 1512. Bus 1512 represents one or more of several types of bus structures, such as a system bus, PCI bus, IEEE bus, USB bus, and so forth.

EXAMPLES

The following examples pertain to further embodiments.
Example 1 is a method. The method includes identifying a carrier claim processed by a practitioner and matching the carrier claim to a facility to generate a matched claim based on a claims factor. The method is such that the claims factor comprises one or more of a patient identifier; a date of service for a procedure billed on the carrier claim; a practitioner identifier associated with the practitioner; a facility identifier for an inpatient facility associated with the carrier claim if the carrier claim occurred during a hospitalization at the inpatient facility; or a most common facility associated with the practitioner.
Example 2 is a method as in Example 1, wherein identifying the carrier claim comprises identifying a plurality of carrier claims processed by the practitioner over a time period, and wherein the method further comprises identifying a plurality of facility claims processed by the facility over the time period.
Example 3 is a method as in any of Examples 1-2, wherein matching the carrier claim to the facility comprises matching at least one of the plurality of carrier claims to at least one of the plurality of facility claims based on the claims factor to generate one or more matched claims.
Example 4 is a method as in any of Examples 1-3, further comprising: calculating a percentage of outpatient claims based on a percentage of office claims performed by the practitioner that did not occur at the facility by collapsing the one or more matched claims on a practitioner identifier associated with the practitioner; and calculating a level of confidence the practitioner is employed by the facility based on the one or more matched claims and the percentage of outpatient claims.
Example 5 is a method as in any of Examples 1-4, further comprising: collapsing the one or more matched claims to a group level, wherein the facility is a healthcare facility associated with a healthcare group; and calculating a percentage of employment by calculating a percentage of practitioners associated with the healthcare group that are employed by a facility associated with the healthcare group.
Example 6 is a method as in any of Examples 1-5, wherein matching the carrier claim to the facility comprises matching based on: in a first matching iteration, a patient identifier for a patient that received a procedure from the practitioner, a date of service for the procedure performed, and a procedure code for the procedure; in a second matching iteration, the patient identifier, the date of service, and an practitioner ID (National Provider Identifier) associated with the practitioner; in a third matching iteration, an inpatient facility associated with a carrier claim if the carrier claim occurred during a hospitalization at the inpatient facility; in a fourth matching iteration, the date of service and a most common facility associated with the practitioner; and in a fifth matching iteration, the most common facility associated with the practitioner as determined based on an clinic ID (National Provider Identifier) in a carrier claim.
Example 7 is a method as in any of Examples 1-6, wherein matching the carrier claim to the facility comprises matching based on: in a sixth matching iteration, the date of service and the most common facility associated with the practitioner; in a seventh matching iteration, the date of service and recent most common facility associated with the practitioner based on claims processed by the practitioner in a recent time period; in an eighth matching iteration, the date of service and the most common facility associated with the practitioner; in a ninth matching iteration, a most common facility associated with the practitioner using previously joined facilities; and in a tenth matching iteration, a facility most closely link to the clinic ID based on the carrier claim.
Example 8 is a method as in any of Examples 1-7, wherein matching the carrier claim to the facility comprises matching a plurality of carrier claims billed by the practitioner over a time period to one or more facilities.
Example 9 is a method as in any of Examples 1-8, wherein: matching the plurality of carrier claims to the one or more facilities comprises performing a plurality of independent matching iterations in succession, wherein the plurality of independent matching iterations comprises the first matching iteration, the second matching iteration, the third matching iteration, the fourth matching iteration, the fifth matching iteration, the sixth matching iteration, the seventh matching iteration, the eight matching iteration, the ninth matching iteration, and the tenth matching iteration; and for each matching iteration of the plurality of independent matching iterations, matching previously unmatched carrier claims of the plurality of carrier claims to a facility of the one or more facilities based on one or more claims factors in an instant matching iteration.
Example 10 is a method as in any of Examples 1-9, wherein the claims factor comprises each of: the patient identifier, wherein the patient identifier is associated with a patient that received a procedure from the practitioner; the date of service for the procedure billed on the carrier claim; a procedure code for the procedure billed on the carrier claim; the practitioner identifier associated with the practitioner, wherein the practitioner identifier is an individual National Provider Identifier; the facility identifier for the inpatient facility if the procedure billed on the carrier claim occurred during a hospitalization at the inpatient facility, wherein the facility identifier is a CMS Certification Number; the most common facility associated with the practitioner based on a plurality of carrier claims billed by the practitioner; a clinic identifier associated with the facility, wherein the clinic identifier is an organization National Provider Identifier; and a facility most commonly linked to the clinic identifier based on the plurality of carrier claims billed by the practitioner.
Example 11 is a system comprising one or more processors for executing instructions stored in non-transitory computer readable storage media, wherein the instructions comprise any of the method steps in Examples 1-10.
Example 12 is non-transitory computer readable storage media storing instructions for execution by one or more processors, wherein the instructions comprise any of the method steps in Examples 1-10.
In the above disclosure, reference has been made to the accompanying drawings, which form a part hereof, and in which is shown by way of illustration specific implementations in which the disclosure may be practiced. It is understood that other implementations may be utilized, and structural changes may be made without departing from the scope of the present disclosure. References in the specification to “one embodiment,” “an embodiment,” “an example embodiment,” etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.
Implementations of the systems, devices, and methods disclosed herein may comprise or utilize a special purpose or general-purpose computer including computer hardware, such as, for example, one or more processors and system memory, as discussed herein. Implementations within the scope of the present disclosure may also include physical and other computer-readable media for carrying or storing computer-executable instructions and/or data structures. Such computer-readable media can be any available media that can be accessed by a general purpose or special purpose computer system. Computer-readable media that store computer-executable instructions are computer storage media (devices). Computer-readable media that carry computer-executable instructions are transmission media. Thus, by way of example, and not limitation, implementations of the disclosure can comprise at least two distinctly different kinds of computer-readable media: computer storage media (devices) and transmission media.
Computer storage media (devices) includes RAM, ROM, EEPROM, CD-ROM, solid state drives (“SSDs”) (e.g., based on RAM), Flash memory, phase-change memory (“PCM”), other types of memory, other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium, which can be used to store desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer.
An implementation of the devices, systems, and methods disclosed herein may communicate over a computer network. A “network” is defined as one or more data links that enable the transport of electronic data between computer systems and/or modules and/or other electronic devices. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computer, the computer properly views the connection as a transmission medium. Transmissions media can include a network and/or data links, which can be used to carry desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer. Combinations of the above should also be included within the scope of computer-readable media.
Computer-executable instructions comprise, for example, instructions and data which, when executed at a processor, cause a general-purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions. The computer executable instructions may be, for example, binaries, intermediate format instructions such as assembly language, or even source code. Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the described features or acts described above. Rather, the described features and acts are disclosed as example forms of implementing the claims.
Those skilled in the art will appreciate that the disclosure may be practiced in network computing environments with many types of computer system configurations, including, an in-dash vehicle computer, personal computers, desktop computers, laptop computers, message processors, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile telephones, PDAs, tablets, pagers, routers, switches, various storage devices, televisions, and the like. The disclosure may also be practiced in distributed system environments where local and remote computer systems, which are linked (either by hardwired data links, wireless data links, or by a combination of hardwired and wireless data links) through a network, both perform tasks. In a distributed system environment, program modules may be located in both local and remote memory storage devices.
Further, where appropriate, functions described herein can be performed in one or more of: hardware, software, firmware, digital components, or analog components. For example, one or more application specific integrated circuits (ASICs) can be programmed to carry out one or more of the systems and procedures described herein. Certain terms are used throughout the description and claims to refer to particular system components. The terms “modules” and “components” are used in the names of certain components to reflect their implementation independence in software, hardware, circuitry, sensors, or the like. As one skilled in the art will appreciate, components may be referred to by different names. This document does not intend to distinguish between components that differ in name, but not function.
It should be noted that the sensor embodiments discussed above may comprise computer hardware, software, firmware, or any combination thereof to perform at least a portion of their functions. For example, a sensor may include computer code configured to be executed in one or more processors and may include hardware logic/electrical circuitry controlled by the computer code. These example devices are provided herein purposes of illustration and are not intended to be limiting. Embodiments of the present disclosure may be implemented in further types of devices, as would be known to persons skilled in the relevant art(s).
At least some embodiments of the disclosure have been directed to computer program products comprising such logic (e.g., in the form of software) stored on any computer useable medium. Such software, when executed in one or more data processing devices, causes a device to operate as described herein.
While various embodiments of the present disclosure have been described above, it should be understood that they have been presented by way of example only, and not limitation. It will be apparent to persons skilled in the relevant art that various changes in form and detail can be made therein without departing from the spirit and scope of the disclosure. Thus, the breadth and scope of the present disclosure should not be limited by any of the above-described exemplary embodiments but should be defined only in accordance with the following claims and their equivalents. The foregoing description has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the disclosure to the precise form disclosed. Many modifications and variations are possible in light of the above teaching. Further, it should be noted that any or all of the aforementioned alternate implementations may be used in any combination desired to form additional hybrid implementations of the disclosure.
Further, although specific implementations of the disclosure have been described and illustrated, the disclosure is not to be limited to the specific forms or arrangements of parts so described and illustrated. The scope of the disclosure is to be defined by the claims appended hereto, any future claims submitted here and in different applications, and their equivalents.

Claims

What is claimed is:

1. A method comprising:

identifying a carrier claim processed by a practitioner; and

matching the carrier claim to a facility to generate a matched claim based on a claims factor;

wherein the claims factor comprises one or more of:

a patient identifier;

a date of service for a procedure billed on the carrier claim;

a practitioner identifier associated with the practitioner;

a facility identifier for an inpatient facility associated with the carrier claim if the carrier claim occurred during a hospitalization at the inpatient facility; or

a most common facility associated with the practitioner.

2. The method of claim 1, wherein identifying the carrier claim comprises identifying a plurality of carrier claims processed by the practitioner over a time period, and wherein the method further comprises identifying a plurality of facility claims processed by the facility over the time period.

3. The method of claim 2, wherein matching the carrier claim to the facility comprises matching at least one of the plurality of carrier claims to at least one of the plurality of facility claims based on the claims factor to generate one or more matched claims.

4. The method of claim 3, further comprising:

calculating a percentage of outpatient claims based on a percentage of office claims performed by the practitioner that did not occur at the facility by collapsing the one or more matched claims on a practitioner identifier associated with the practitioner; and

calculating a level of confidence the practitioner is employed by the facility based on the one or more matched claims and the percentage of outpatient claims.

5. The method of claim 4, further comprising:

collapsing the one or more matched claims to a group level, wherein the facility is a healthcare facility associated with a healthcare group; and

calculating a percentage of employment by calculating a percentage of practitioners associated with the healthcare group that are employed by a facility associated with the healthcare group.

6. The method of claim 1, wherein matching the carrier claim to the facility comprises matching based on:

in a first matching iteration, a patient identifier for a patient that received a procedure from the practitioner, a date of service for the procedure performed, and a procedure code for the procedure;

in a second matching iteration, the patient identifier, the date of service, and an practitioner ID (National Provider Identifier) associated with the practitioner;

in a third matching iteration, an inpatient facility associated with a carrier claim if the carrier claim occurred during a hospitalization at the inpatient facility;

in a fourth matching iteration, the date of service and a most common facility associated with the practitioner; and

in a fifth matching iteration, the most common facility associated with the practitioner as determined based on an clinic ID (National Provider Identifier) in a carrier claim.

7. The method of claim 6, wherein matching the carrier claim to the facility comprises matching based on:

in a sixth matching iteration, the date of service and the most common facility associated with the practitioner;

in a seventh matching iteration, the date of service and recent most common facility associated with the practitioner based on claims processed by the practitioner in a recent time period;

in an eighth matching iteration, the date of service and the most common facility associated with the practitioner;

in a ninth matching iteration, a most common facility associated with the practitioner using previously joined facilities; and

in a tenth matching iteration, a facility most closely link to the clinic ID based on the carrier claim.

8. The method of claim 7, wherein matching the carrier claim to the facility comprises matching a plurality of carrier claims billed by the practitioner over a time period to one or more facilities.

9. The method of claim 8, wherein:

matching the plurality of carrier claims to the one or more facilities comprises performing a plurality of independent matching iterations in succession, wherein the plurality of independent matching iterations comprises the first matching iteration, the second matching iteration, the third matching iteration, the fourth matching iteration, the fifth matching iteration, the sixth matching iteration, the seventh matching iteration, the eight matching iteration, the ninth matching iteration, and the tenth matching iteration; and

for each matching iteration of the plurality of independent matching iterations, matching previously unmatched carrier claims of the plurality of carrier claims to a facility of the one or more facilities based on one or more claims factors in an instant matching iteration.

10. The method of claim 1, wherein the claims factor comprises each of:

the patient identifier, wherein the patient identifier is associated with a patient that received a procedure from the practitioner;

the date of service for the procedure billed on the carrier claim;

a procedure code for the procedure billed on the carrier claim;

the practitioner identifier associated with the practitioner, wherein the practitioner identifier is an individual National Provider Identifier;

the facility identifier for the inpatient facility if the procedure billed on the carrier claim occurred during a hospitalization at the inpatient facility, wherein the facility identifier is a CMS Certification Number;

the most common facility associated with the practitioner based on a plurality of carrier claims billed by the practitioner;

a clinic identifier associated with the facility, wherein the clinic identifier is an organization National Provider Identifier; and

a facility most commonly linked to the clinic identifier based on the plurality of carrier claims billed by the practitioner.

11. A system comprising one or more processors for executing instructions stored in non-transitory computer readable storage media, the instructions comprising:

identifying a carrier claim processed by a practitioner; and

wherein the claims factor comprises one or more of:

a patient identifier;

a date of service for a procedure billed on the carrier claim;

a practitioner identifier associated with the practitioner;

a most common facility associated with the practitioner.

12. The system of claim 11, wherein the instructions are such that identifying the carrier claim comprises identifying a plurality of carrier claims processed by the practitioner over a time period, and wherein the method further comprises identifying a plurality of facility claims processed by the facility over the time period.

13. The system of claim 12, wherein the instructions are such that matching the carrier claim to the facility comprises matching at least one of the plurality of carrier claims to at least one of the plurality of facility claims based on the claims factor to generate one or more matched claims.

14. The system of claim 13, wherein the instructions further comprise:

15. The system of claim 14, wherein the instructions further comprise:

16. The system of claim 11, wherein the instructions are such that matching the carrier claim to the facility comprises matching based on:

17. The system of claim 16, wherein the instructions are such that matching the carrier claim to the facility comprises matching based on:

18. The system of claim 17, wherein the instructions are such that matching the carrier claim to the facility comprises matching a plurality of carrier claims billed by the practitioner over a time period to one or more facilities.

19. The system of claim 18, wherein the instructions are such that:

20. The system of claim 11, wherein the claims factor comprises each of:

the date of service for the procedure billed on the carrier claim;

a procedure code for the procedure billed on the carrier claim;

21. Non-transitory computer readable storage media storing instructions for execution by one or more processors, the instructions comprising:

identifying a carrier claim processed by a practitioner; and

wherein the claims factor comprises one or more of:

a patient identifier;

a date of service for a procedure billed on the carrier claim;

a practitioner identifier associated with the practitioner;

a most common facility associated with the practitioner.

22. The non-transitory computer readable storage media of claim 21, wherein the instructions are such that identifying the carrier claim comprises identifying a plurality of carrier claims processed by the practitioner over a time period, and wherein the method further comprises identifying a plurality of facility claims processed by the facility over the time period.

23. The non-transitory computer readable storage media of claim 22, wherein the instructions are such that matching the carrier claim to the facility comprises matching at least one of the plurality of carrier claims to at least one of the plurality of facility claims based on the claims factor to generate one or more matched claims.

24. The non-transitory computer readable storage media of claim 23, wherein the instructions further comprise:

25. The non-transitory computer readable storage media of claim 24, wherein the instructions further comprise:

26. The non-transitory computer readable storage media of claim 21, wherein the instructions are such that matching the carrier claim to the facility comprises matching based on:

27. The non-transitory computer readable storage media of claim 26, wherein the instructions are such that matching the carrier claim to the facility comprises matching based on:

28. The non-transitory computer readable storage media of claim 27, wherein the instructions are such that matching the carrier claim to the facility comprises matching a plurality of carrier claims billed by the practitioner over a time period to one or more facilities.

29. The non-transitory computer readable storage media of claim 28, wherein the instructions are such that:

30. The non-transitory computer readable storage media of claim 21, wherein the claims factor comprises each of:

the date of service for the procedure billed on the carrier claim;

a procedure code for the procedure billed on the carrier claim;