Medical Claims Data

Medical claims data refers to a large-scale electronic record of information that lists doctor’s appointments, medical bills, insurance claims, and other crucial patient communication. Datarade helps you find medical claims data APIs, datasets, and databases. Learn more →
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HealthVerity
Based in USA
HealthVerity
HealthVerity is a data provider offering Alternative Data, Healthcare Provider (HCP) Data, Medical Claims Data, Patient Data, and Research Data. They are hea...
Definitive Healthcare
Based in USA
Definitive Healthcare
Definitive Healthcare is a data provider offering Healthcare Provider (HCP) Data, Medical Claims Data, Medical Imagery Data, and Patient Data. They are headq...
Advera Health Analytics
Based in USA
Advera Health Analytics
Advera Health Analytics is a data provider offering Medical Claims Data and Pharma Data. They are headquartered in United States of America.
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The Ultimate Guide to Medical Claims Data 2021

Learn about medical claims data analytics, sources, and collection.

What is Medical Claims Data?

Medical claims data, also known as administrative data, is information that is amassed consistently for clinical purposes as a part of every healthcare meeting. Medical claims data gives a detailed view of patient information that entails diagnosis, treatments, and billed and paid medical bills. This data that medical personnel store in electronic health records (EHR) is crucial as far as analyzing and improvement of healthcare delivery systems is concerned. It provides the basis for evidence-based healthcare practices.

How is Medical Claims Data collected?

Just like other medical records, medical claims data is collected directly from the notes that are captured by a healthcare provider when a patient visits a health center. The majority of the medical provider’s billing mechanisms apply standardized forms of predefined codes that point out the healthcare services offered. This uniformity in the cataloging of healthcare services within a wide range of service providers allows the medical claims data to be easily collected and compared. As far as protecting the privacy of patients, before the data is available for use in further research and analysis, personally identifiable information from the records is scraped out. After de-identification, all that’s left is the categorization of data based on several variables such as patient age, gender, diagnostic information, or any other data about the history of the patient.

What are the attributes of Medical Claims Data?

Medical claims data core attributes state whose and what information the medical practitioner should include in the dataset. In answering the “whose information” question, claims data usually entails people who have health insurance covers, receive health care, and file a claim. As for the “what information” question, the majority of claims data capture the patient’s characteristics, provider identifiers, treatment and diagnostic information, and billing information. Other than the ‘whose’ and ‘what’ question, claims data attributes answer several questions concerning the patient’s diagnostic codes, service codes, and pharmaceutical codes. Diagnostic code is information in the claim data that gives details about the clinical conditions of the patient. Service code is the information concerning the performed procedures or delivered services. The pharmaceutical code identifies data that is related to dispensed medications.

What is Medical Claims Data used for?

Even though medical claims data usually have less information as compared to other medical records, it nonetheless offers a source of information to users. Firstly, because this claims data is routinely collected and computerized by medical personnel, it gives a good source from which to calculate quality indicators of a health system. When stakeholders compile this information, they can use it to analyze the key trends and progress in the quality of health delivery. Secondly, because medical claims data usually falls under the paradigm of big data analytics, it means that the available bulk information can be used to draw up comparisons of the working of various health systems and test the hypotheses about varying demographics.

How can users assess the quality of Medical Claims Data?

The users of medical claim data can assess the quality of this data by determining the accuracy of the provided information. Users should doubt the accuracy of medical claims data if there are glaring errors in the data provided. As such, users of this information should look out for incorrect or incomplete documentation, illegibility of care provider notes, missing reports from the lab, or varying levels of abstractor skills. Furthermore, users can assess the quality of administrative data by evaluating how best the data counters the challenge of integrating the information from multiple sources and whether it provides the means to describe the utilization or appropriateness of care.

Who are the best Medical Claims Data providers?

Finding the right Medical Claims Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular Medical Claims Data providers that you might want to buy Medical Claims Data from are HealthVerity, Definitive Healthcare, Advera Health Analytics, Apixio, and Komodo Health.

How can I get Medical Claims Data?

You can get Medical Claims Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Medical Claims Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Medical Claims Data APIs, feeds and streams to download the most up-to-date intelligence.

What are similar data types to Medical Claims Data?

Medical Claims Data is similar to Medical Imagery Data, Electronic Health Record (EHR) Data, Healthcare Provider (HCP) Data, Pharma Data, and Patient Data. These data categories are commonly used for Medical Claims Data analytics.