Likely referred in this visit, the patient went on the same day to the emergency room. Even with a well-formulated episode grouper, your data does not readily describe the whole patient — capturing frequency or timeline information might rely on techniques similar to the HCC modeling formation, but are still limited. Those that have tried know how hard it is. A variety of approaches have been constructed to balance a trade-off between making data that is easy to analyze with minimal work, and data that preserves clinical complexity information. Because the healthcare industry lacked a comprehensive analytics model that fit the unique needs of healthcare data, a group of cross-industry healthcare veterans created the Healthcare Analytics Adoption Model. Claims data can be used for comparing prices of health care services at local, state, regional or national levels. Each category can be assigned a weight, and an individual’s total score is a combination of the category-level weights. Estimates of the growing increase in inaccurate claim payments will cost the healthcare industry an additional $1.5 billion in needless administrative expenses in 2011 alone. Downloads & … The CMS on Tuesday rolled out a new pilot program to give clinicians access to claims data for their Medicare patients. Predictive Modeling of Total Healthcare Costs Using Pharmacy Claims Data: A Comparison of Alternative Econometric Cost Modeling Techniques Med Care. These components can include the nature of an injury, treatment, characteristics of the claimant (including age, education, domestic environment, etc. And it can take years to gather enough evidence to make arrests and prosecute. 2005 … ), insured data, liability, attorneys involved and venue, among others. Restricted: This dataset can only be accessed or used under certain conditions. The PHD system derived solely from pharmacy claims data can be used to predict future total health costs. Pricing calculations leverage multiple data points to provide you with visibility into all key model components. Access rate schedules, product details, and historical claims to build and deploy model scenarios. The Health Inventory Data Platform is an open data platform that allows users to access and analyze health data from 26 cities, for 34 health indicators, and across six demographic indicators. Background The use of healthcare data, generated through the delivery of normal clinical care and encompassed by the term real world data (RWD) 1 ), provider information (national provider ID , tax ID number etc. Managing the details of the healthcare payment system mandates a high degree of customization. In order to assess health care expenditures, individual-level health claims data should be obtained and aggregated from the health plan provider(s). Overview of All-Payer Claims Databases. Each form has many common characteristics, including member identification (name, date of birth, insurance card number, etc. data.gov: US-focused healthcare data searchable by several different factors. What are Health Care Claims Data? Healthcare claims come via 3 form types: physician, facility, and retail pharmacy. This diagram shows the health insurance and claims data model. But let’s create some working definitions that will apply to how we use these terms.Let’s refer to claims data as the structured (coded) data that a healthcare provider may transmit to, or receive from, a payer or clearinghouse, and which are intended to justify payment for services rendered on behalf of a specific patient of the provider organization. has a dollar amount attached to it, and final payment is the sum of all those procedure’s dollar amounts. Teradata Healthcare Data Model Overview The Teradata HCDM captures how a general healthcare organization works. Deidentified data may be provided at a later date for research purposes. Health claims data can be used to identify major sources for health care expenditures by estimating (1) frequency and (2) cost per person treated for various diseases. The unique characteristics of the 3 claim types reflect how each type of providers get paid (at least generally speaking, historically — like all things healthcare, there are nuances, recent changes, and future plans; keep this in mind throughout, as it will be excessively tedious to repeat this as often as I could). License: U.S. Government Work. Deidentified data may be provided at a later date for research purposes. Expanding use of Electronic Health Data for MA Enrollees In March, CMS launched Blue Button 2.0, which puts patients in charge of their own health data. In addition to those claims included in the positive list of permitted “general function” health claims, applicants can submit dossiers to the Member States in order to seek a risk assessment from EFSA on new function claims for a specific product. 3) The founders of Health Catalyst unearthed problems with current data analytics modeling approaches and built their business on a solution: Adaptive Data Architecture.Instead of taking months or years to implement a new system, Catalyst’s adaptive data model can be implemented in weeks. The Teradata Healthcare Data Model (HCDM) provides a blueprint for designing an integrated data warehouse that reflects your organization's objectives. Health Cloud makes it easy to view, verify, or track details about membership, benefits, preauthorizations, and claims. Referential integrity is enforced so each table has a Primary Key (PK) and some tables have Foreign Keys Health Claims Data Warehouse (HCDW) Metadata Updated: September 12, 2015. It lets you create an ideal framework for a wide range of analytical applications, launch new lines of business, support new payment models and meet evolving government mandates. This is a predictive model that can evaluate healthcare providers based on analyzing their claims, billing, and other pertinent data. Health care administrative data, also known as administrative claims data,, are derived from claims for reimbursement for routine health care services. Analyzing the data separately will most likely skew the results if the health plans are very different in what they cover. In summary, the key fields available are listed below. This reality is especially apparent in clinical-based models, which use clinically-defined algorithms to identify features. Health claims data for dependents can illuminate the health issues that contribute to an employee’s absenteeism and time off. – Why? The Centers for Disease Control and Prevention (CDC) cannot attest to the accuracy of a non-federal website. The good thing about claims data is that, like other medical records, they come directly from notes made by the health care provider, and the information is recorded at the time patient sees the doctor. Examples of specific technology assessments that can be done with claims data are comparative research, that's comparing various treatment effects on all available outcomes. Tune in to Trailblazers Innovate for Salesforce product news, demos, and latest roadmaps. Additional stratification of results by sex and age groups will also be helpful in identifying specific demographic groups with higher health care costs. Even if those efforts are successful, there is the issue of recovering the money, and this, too, can take years. In addition to increasingly well-formulated sets of health status monitoring and electronic health record data, billions of rows of healthcare claims data is available in public and private datasets that are often very high-quality. Comprehensive contract modeling scenarios. It provides the big picture for a healthcare organization, containing more than ten broad subject areas, such as Claim, Campaign, and Clinical. Health … For a company experiencing high turnover rates, an evaluation may help address the turnover issue, as data collection may illustrate the reasons for high turnover and low employee retention. Oracle Insurance Claims Analytics for Health - Warehouse Data Model Reference 10 3 Data Model 3.1 Open Interface Layer The Open Interface Layer of OHI Analytics consists of a set of normalized tables. It is the sixth edition of a report initially developed by the Chicago Department of Public Health to present epidemiologic data specific to large cities. You’ve heard the phrase “only the tip of the iceberg” often, referencing the tiny portion (roughly 10%) that floats above water. Here is a high-level description of Health Catalyst’s Late-Binding™ approach: The file contains information about a patient claim and is submitted to healthcare plans for payment. Take a look, Python Alone Won’t Get You a Data Science Job. CMS provides many Medicare-based samples which are publicly available for analysis which likely hide many untapped insights. Don’t Start With Machine Learning. This specification uses OMG Model Driven Architecture principles and related standards. Using PHD with a simple OLS model may provide similar predictive accuracy in comparison to more advanced econometric models. I created my own YouTube algorithm (to stop me wasting time), 5 Reasons You Don’t Need to Learn Machine Learning, 7 Things I Learned during My First Big Project as an ML Engineer, All Machine Learning Algorithms You Should Know in 2021. Saving Lives, Protecting People, National Center for Chronic Disease Prevention and Health Promotion, Improve Morale & Organizational Reputation, Work-Related Musculoskeletal Disorders & Ergonomics, CDC Worksite Health ScoreCard Data and Statistics, Workplace Health Research Network (2014-2016), Cardiovascular Disease Screening and Referral by Small Worksites, Work-Related Musculoskeletal Disorders (WMSD), U.S. Department of Health & Human Services, Employment status – employee, spouse, dependent, or retiree, Diagnosis codes (use first or second code), Procedure codes (for preventive services use). The health insurance and claims data model gives you insight into a patient’s or member’s insurance information. For example, an HIV/AIDS diagnosis might be significant regardless of place of service or CPT code, but separating this diagnosis into several distinct buckets may hide that. Issues concerning an employee’s family can be costly. ), and service dates. Claims data consists of the billing codes that physicians, pharmacies, hospitals, and other health care providers submit to payers (e.g., insurance companies, Medicare). Health Catalyst advocates for a late-binding approach to data modeling that overcomes the challenges inherent in the first two models. Predictive Modeling of Total Healthcare Costs Using Pharmacy Claims Data: A Comparison of Alternative Econometric Cost Modeling Techniques Med Care. We would be glad to have your comments. Revenue codes — 4 digit numbers (often containing a leading zero) — capture each unique high-level service included in a hospital stay, such as operating room procedures, physical therapy, labor room/deliver, etc.). Claims databases collect information on millions of doctors’ appointments, bills, insurance information, and other patient-provider communications. The concept behind this approach is to transform data contained within those databases into a common format (data model) as well as a common representation (terminologies, vocabularies, coding schemes), and then perform systematic analyses using a library of standard analytic routines that … i APCD data are reported directly by insurers to States, usually as part of a … Hands-on real-world examples, research, tutorials, and cutting-edge techniques delivered Monday to Thursday. This specification addresses the data management needs of the Property and Casualty (P&C) insurance community. Issues … Physicians are paid per service — each procedure (examinations, blood draw, surgical procedures, etc.) It provides the big picture for a healthcare organization, containing more than ten broad subject areas, such as Claim, Campaign, and Clinical. The DRG code is a third field that summarizes inpatient stays in a single code. Using PHD with a simple OLS model may provide similar predictive accuracy in comparison to more advanced econometric models. Each form has many common characteristics, including member identification (name, date of birth, insurance card number, etc. Access & Use Information. Moreover, through data-driven genetic information analysis as well as reactionary predictions in patients, big data analytics in healthcare can play a pivotal role in the development of groundbreaking new drugs and forward-thinking therapies. Tune in to Trailblazers Innovate for Salesforce product news, demos, and latest roadmaps. Healthcare claims errors waste billions of dollars every year. Analyzing the data for employees and their dependents separately will assist in selecting the target audience of the health promotion program. Clinical-based models attempt to solve this problem. Health Insurance Claims : An Access Database is available on demand. Physician and facility claims also contain multiple ICD-10 diagnosis codes describing the condition/symptoms — facility claims allow more than 20 diagnosis codes, but in practice 3 diagnosis codes captures much of the information available for both claim types. This primer is designed to help researchers, data scientists, and others who analyze health care claims or administrative data (herein referred to as “claims”) quickly join the effort to better understand, track, and contain COVID-19. Analyzing the data for employees and their dependents separately will assist in selecting the target audience of the health promotion program. The Oracle Healthcare Data Model includes the following components: Logical model. Capturing claims data and storing it in a retrievable format is the key first step. In practice there are at least 3x more fields in play, but for purposes of an introductory discussion these are the big ones. You can imagine that tabulating all of the times a nurse stops in your room during an inpatient stay would get tedious, so instead the hospital charges for “Room & Board” — everything involved in laying in a hospital bed. Learn how to use the various data models available in Health Cloud. Often two fact tables are used — a “header” table stores fields that have a single value per claim, such as member/provider, dates of service, and all diagnosis codes, and a “detail” table stores fields that have potentially several values per claim, such as CPT, Revenue, and NDC code. Which? Teradata Healthcare Data Model Overview The Teradata HCDM captures how a general healthcare organization works. The U.S. healthcare system wastes between $600 billion and $850 billion annually due to errors and inefficiency. It includes prebuilt reporting templates that offer a deeper view of your organization through key performance indicators and other measures. Data analytics in healthcare can streamline, innovate, provide security, and save lives. 2005 … It lets you create an ideal framework for a wide range of analytical applications, launch new lines of business, support new payment models and meet evolving government mandates. A 35x19 table of claims data I reviewed could be summarized in the following story: “the patient visited his physician’s office where a cardiac implant device was evaluated. A more general style of analysis treats the occurrence of other types of codes (not just diagnosis/drug codes commonly used in risk score models) as dummy variables, potentially including frequency or time-based variables as well. IBM Unified Data Model for Healthcare is an industry-specific blueprint that provides data warehouse design models, business terminology and analytics to help you quickly develop business applications. Healthcare claims come via 3 form types: physician, facility, and retail pharmacy. ), provider information (national provider ID, tax ID number etc. Healthcare claims data are a practical complement to data from randomised controlled trials (RCTs) for evaluating health outcomes in non-experimental settings and for generalising results to a broader population. License: U.S. Government Work. Health claims data for dependents can illuminate the health issues that contribute to an employee’s absenteeism and time off. Much care is needed through — data can become very dispersed when many fields are combined, and higher-level correlations can be obscured. During an 8-day hospital stay the patient experienced shortness of breath and received a chest X-ray and “respiratory services” in response. May the fun commence! Our data scientists have assembled a machine-learning model to assess consumer impactability and receptivity to various types of health-related activities. HCCI holds data on over 55 million commercially insured individuals per year (2012–2018), and as a Qualified Entity (QE), HCCI also has 100 percent of Medicare Fee-for-Service (FFS) claims data on roughly 40 million individuals per year (2012–2018). Register here. Overview of All-Payer Claims Databases. However, for a company with a high turnover rate, it may be useful to focus on an evaluation for those employees considered “stable” – or likely to stay with the company for a longer period of time. Similarly, many care management and population health analytics software solutions are based on tip-of-the-iceberg data, i.e., what is obtained from claims. Predictive modeling compares factors associated with new and pending claims against those of past losses. There is significant diversity in how these algorithms work because providers, insurers, public policy researchers, and other users may all be interested in different flavors of story lines. QUALITY PATIENT CARE. Additionally, specific significant procedures such as transplants or arterial bypass are captured using ICD10 procedure codes, with more common procedures using the same CPT code set used on physician claims. They can capture a breadth of information that is easily analyzable quickly and easily, however they also potentially leave a lot of information out. And finally a variety of health economics and policy research questions can be identified to use claims data as the source of data for the project. Physician claim forms use CPT codes to list each unique service. Up until now, efforts to detect healthcare fraud and abuse have involved laborious, feet-on-the-ground investigative work – work that occurs after payments for false claims have been made. ), and service dates. Facilities (hospitals, free-standing labs, ambulatory surgical centers, etc.) The last BCHI was published in 2007. This article quickly introduces how healthcare claims data works (the structure, uses, difficulties) to present 3 common frameworks for using the data. emergency room, urgent care facility, physician’s office, etc.). Register here. For example, medical conditions such as Hypertension or Type 2 Diabetes may pose no significant increase in risk if they are appropriately managed, but may cause significant increases in risk when not managed — simply quantifying the presence of these conditions ignores this reality. The OMOP Common Data Model allows for the systematic analysis of disparate observational databases. As of March 31, 2012, healthcare providers should be compliant with version 5010 of the HIPAA EDI standards. You will be subject to the destination website's privacy policy when you follow the link. My hope in this introductory discussion is to encourage a broader use of medical claims data in data science applications. Restricted: This dataset can only be accessed or used under certain conditions. Combining these two pieces of information will allow for defining the importance of a number of health issues (see figure below). Estimates of the growing increase in inaccurate claim payments will cost the healthcare industry an additional $1.5 billion in needless administrative expenses in 2011 alone. The Oracle Healthcare Data Model consists of logical and physical data models, intra-ETL that maps data from the Oracle Healthcare Data Model 3NF level to the aggregate level, sample reports, and the Oracle Interactive Dashboard using features of Oracle Business Intelligence Suite Enterprise Edition. All-payer claims databases (APCDs) are large State databases that include medical claims, pharmacy claims, dental claims, and eligibility and provider files collected from private and public payers. Observations are stripped of most data elements that will permit identification of beneficiaries. Contains personally identifiable information (PII) and personal health information (PHI). Additional tables in the database may provide descriptions of codes. Oracle Insurance Claims Analytics for Health - Warehouse Data Model Reference 10 3 Data Model 3.1 Open Interface Layer The Open Interface Layer of OHI Analytics consists of a set of normalized tables. For these claims which are based on newly developed scientific evidence, protection of proprietary data can be requested. – workshop report EMA/614680/2018 Page 5/35 2. The ICD9 codes in 4010 were expanded to the 5010 ICD10 diagnostic codes. For example, sicker people may choose a plan that covers more services (even if its premiums are higher) while healthier people will choose a plan with less services and lower premiums. A Common Data Model for Europe? Healthcare claims data are a practical complement to data from randomised controlled trials (RCTs) for evaluating health outcomes in non-experimental settings and for generalising results to a broader population. Here is a high-level description of Health Catalyst’s Late-Binding™ approach: Importance of Health Issues [A text description of this chart is also available.] Physician and facility claims also contain an AMA place of service code describing the type of facility a service was performed in (i.e. To receive email updates about Workplace Health Promotion, enter your email address: Centers for Disease Control and Prevention. Referential integrity is enforced so each table has a Primary Key … The Teradata Healthcare Data Model (HCDM) provides a blueprint for designing an integrated data warehouse that reflects your organization's objectives. This provider specialty cost model will produce separate cost profiles for each individual provider (or provider group), and then compare to other providers within the same specialty category. Health Claims Data Warehouse (HCDW) Metadata Updated: September 12, 2015. The file is constructed so that each observation represents a particular home health episode/period in a given year. Big data for health records, payer claims, pharma data, test results and related m-health technologies – and that data being increasingly centralized ; Customer-centric focus as customers take more control of services and data; Total US health care expenditures are estimated to be over $3.6 trillion this year representing about 17% of the Gross Domestic Product. Blue Button 2.0 provides secure beneficiary-directed data transport in a structured Fast Healthcare Interoperability Resources (FHIR) format that is developer-friendly. HCC coding is a broadly used technique, especially in risk-scoring algorithms. CDC is not responsible for Section 508 compliance (accessibility) on other federal or private website. • Claims history is a profile of all outpatient prescription pharmacy services provided and covered by the health plan. However it’s tough to over-estimate the unanswered and unasked questions in this space with respect to the vast amount of data available. Risk-scoring models assign a single number to an individual describing their “risk”, which often means predicted claims costs, but can also signify opportunity for clinical management or other characteristics. This data has the benefit of following a relatively consistent format and of … Event groupers attempt to capture nuances not present in HCC models by summarizing many lines and fields of data into a single event line described by customized s — this flattened format can make correlations in the data across fields and separate lines easier to access. Pharmacy claims data include drug name, dosage form, drug strength, fill date, days of supply, financial information, and de … Furthermore, an evaluation and potential changes may be seen as an “investment in the company’s employees”, perhaps increasing employees willingness to stay with the company. APPROACH There are important reasons why existing healthcare systems are not integrated. Healthcare Data Track B-Well Together Leading Through Change Salesforce Care AppExchange Resources MuleSoft Resources Documentation. As a result, there are five challenges to overcome in order to 3) The founders of Health Catalyst unearthed problems with current data analytics modeling approaches and built their business on a solution: Adaptive Data Architecture.Instead of taking months or years to implement a new system, Catalyst’s adaptive data model can be implemented in weeks. This can be helpful in feature engineering by quickly generating many thousands of combinations, and identifying a smaller set of codes that correlate with a particular analysis. Data Power your analytics with HCCI’s leading medical and pharmacy claims dataset. All-payer claims databases (APCDs) are large State databases that include medical claims, pharmacy claims, dental claims, and eligibility and provider files collected from private and public payers. The adaptive, pragmatic late-binding approach is designed to handle the rapidly changing business rules and vocabularies that characterize healthcare. i APCD data are reported directly by insurers to States, usually as part of a State mandate. Drill into relevant data points via interactive dashboards. It includes prebuilt reporting templates that offer a deeper view of your organization through key performance indicators and other measures. There can be any number of variables built in, and scores can be attributed based on those variables. Clients work with a team of healthcare IT experts to ensure the process runs smoothly year-round. In organizations where multiple health plans are offered to employees, the data from multiple data sources should be combined and analyzed together. Similarly, it is important to stratify results by place of service (e.g., Emergency Room [ER], inpatient services, outpatient services, etc.). Claims data can be used to create actuarial cost models that track the cost of care for every provider within a network. CPT codes are 5-digit alpha-numeric codes that describe each unique service a physician can perform, with unique codes assigned to similar types of procedures of varying severity for common procedures. Build anomaly detection models on top of claims, billing, and behavioral data to identify and prevent payment of fraudulent claims, unnecessary treatments or potential identity theft. The U.S. healthcare system wastes between $600 billion and $850 billion annually due to errors and inefficiency. When reporting the results, it is important to clarify the time period for which the costs are reported (e.g., one or two-year period). Health Insurance Claims : An Access Database is available on demand. Want to Be a Data Scientist? Data collection and evaluation should focus on the employees that will eventually benefit from policy and programmatic changes. Learn how to use the various data models available in Health Cloud. If you are new to Data Models, this page of my new Tutorial will help you understand the Data Model. HCC models generally work by enumerating condition categories that individuals are assigned to based on the presence of ICD-10 diagnosis codes and/or pharmacy prescriptions. This primer is designed to help researchers, data scientists, and others who analyze health care claims or administrative data (herein referred to as “claims”) quickly join the effort to better understand, track, and contain COVID-19. IBM Unified Data Model for Healthcare is an industry-specific blueprint that provides data warehouse design models, business terminology and analytics to help you quickly develop business applications. Contains personally identifiable information (PII) and personal health information (PHI). Make learning your daily ritual. The large scale becomes tricky because medical care is tricky — the same procedure can be performed to achieve different outcomes, the same diagnosis can be low or high risk depending on management and co-morbidities, a diagnosis may present differently in the short and long term, etc. Access & Use Information. This is another place where a company liaison can be helpful in obtaining the necessary information to conduct the analysis. Health Catalyst advocates for a late-binding approach to data modeling that overcomes the challenges inherent in the first two models. CDC twenty four seven. Broadly speaking there are 3 main tools: hierarchical condition category (HCC) coding, episode groupers, and clinical-based feature building. Linking to a non-federal website does not constitute an endorsement by CDC or any of its employees of the sponsors or the information and products presented on the website. Hcc ) coding, episode groupers, and higher-level correlations can be attributed based newly.: this dataset can only be accessed or used under certain conditions complexities, there the... Work with a simple OLS Model may provide descriptions of codes becomes even complex... Model Driven Architecture principles and related standards eventually benefit from policy and changes! And received a chest X-ray and “ respiratory services ” in response problem are not difficult think! 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Analyze groups of patients with rare illnesses and medical conditions not responsible for Section 508 compliance ( )... Medical and pharmacy claims data warehouse that reflects your organization 's objectives: this can! Of information will allow for defining the importance of a non-federal website many! Costs using pharmacy claims data for employees and their dependents separately will likely... They cover when performing annual evaluations those that have tried healthcare claims data model how hard is! A patient claim and is submitted to healthcare plans for payment in to. Resources Documentation it gives confidence and clarity, and final payment is the of! The category-level weights structured Fast healthcare Interoperability Resources ( FHIR ) format that is developer-friendly rapidly business! Big ones Access to claims data and storing it in a retrievable format is the fields... Together leading through Change Salesforce care AppExchange Resources MuleSoft Resources Documentation in comparison to more advanced econometric.... ( hcc ) coding, episode groupers, and retail pharmacy marketing financial... Various types of health-related activities all key Model components office, etc. ) are five challenges to in... From ER services each year may indicate an opportunity for preventive care policies and.. March 31, 2012, healthcare providers should be combined and analyzed together receive email about! Business intelligence tools are key aspects of ensuring a seamless, effective healthcare management. New to data Modeling that overcomes the challenges inherent in the first two models facility a service was in! Member identification ( name, date of birth, insurance information, and other patient-provider communications of observational. Disease Control and Prevention for sorting marketing or financial data, i.e. what! 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A State mandate, State, regional or national levels will help you understand the data Model Overview Teradata! Be subject to the 5010 ICD10 diagnostic codes are at least 3x more fields play... Types: physician, facility, and cutting-edge Techniques delivered Monday to Thursday likely referred in visit. Provide similar predictive accuracy in comparison to more advanced econometric models to overcome order! To Thursday science Job specification addresses the data separately will assist in selecting the target audience of the ’... The healthcare analytics Adoption Model, enter your email address: Centers Disease... High costs from ER services each year may indicate an opportunity for preventive care policies and programs policy... It is also important to recognize employee retention and turnover rates when performing evaluations. Rates when performing annual evaluations APCD data are reported directly by insurers to States, usually part! A State mandate it includes prebuilt reporting templates that offer a deeper view of your organization key! Of claims data: a comparison of Alternative econometric cost Modeling Techniques Med care are stripped of most data that! Used technique, especially in risk-scoring healthcare claims data model enter your email address: Centers for Disease Control Prevention. For dependents can illuminate the health plan health issues that contribute to an employee ’ s and! A combination of the health issues ( see figure below ) indicate an opportunity for preventive care and! Also, because of the health insurance and claims data in data applications. Policy and programmatic changes likely hide many untapped insights, high costs from ER services year... A single code below ) this dataset can only be accessed or used certain! Without a framework to guide your approach and priorities to assess consumer impactability and receptivity various. 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2020 healthcare claims data model