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What Is Claims Data?

By Steve Smith

The information presented here is true and accurate as of the date of publication. DeVry’s programmatic offerings and their accreditations are subject to change. Please refer to the current academic catalog for details.


April 3, 2024

4 min read

For healthcare organizations that provide care, pay for procedures, develop new drugs and medical devices or occupy other roles in the vast healthcare industry, medical data from patients and procedures is vital. This data is then used to make decisions about patient care and find ways to improve the business side of things. But where does this data come from?


In this article, we will discuss claims data, explaining what it is, its importance in the healthcare industry and the different types of claims data that there are. We’ll also take a look at who uses claims data and why as we help you develop a well-rounded understanding of claims data, its significance in the health information ecosystem and how it’s related to medical billing and coding. 

Who Uses Claims Data?

As we begin our “what is claims data” discussion, let’s look at who uses claims data and how. 

Healthcare providers, medical products manufacturers and marketers, biopharma companies, policymakers, public health agencies and payers all use claims data in a variety of ways. Their wide-ranging goals might be to increase drug safety, monitor disease outbreaks, increase cost efficiencies, reduce overall medical costs, measure treatment effectiveness or develop new therapies, products or protocols. 

Healthcare organizations may use claims data to trace referral patterns, improve the health of populations, stimulate revenue and develop or accelerate their strategies to bring new products to the marketplace. The Centers for Medicare and Medicaid Services (CMS) use claims data to make reports available to the public on a range of topics like hospitalization trends, vaccine statistics, Medicare provider utilization and payment data.

At times combining claims data with other real-world intelligence, researchers may apply the data in several different types of analyses: 

  • Optimizing outcomes and use of resources:

    In health economics and outcomes research (HEOR) that informs decision-making to improve the overall quality and efficiency of care delivery, policymakers, providers and payers may make use of the data to focus on patient outcomes as well as track the utilization of resources and costs.

  • Measuring patient responses:

    By analyzing data from patient populations, healthcare companies can evaluate the effectiveness of different interventions, assessing their performance in clinical practice and gaining insights into treatment outcomes and patient responses.

  • Guiding public health interventions:

    Organizations can use claims data, captured across different geographical regions, to monitor disease prevalence, incidence and distribution in populations. For example, in a flu outbreak, epidemiologists and researchers can use claims data to monitor trends in influenza diagnosis and treatment patterns, identify high-risk populations and target vaccination campaigns.

  • Understanding patient adherence:

    Gaining insight into the way patients do or don’t adhere to treatment plans is crucial for healthcare providers. Using claims data, they can evaluate the effectiveness of a treatment and identify areas where outcomes could be improved using patient engagement, education and support efforts. For patients with chronic conditions like diabetes, researchers can use claims data to monitor prescription refill patterns that may reveal gaps in their treatment.

  • Targeting care to at-risk populations:

    Researchers can use predictive data analysis models to close the gap between procedures and individual health profiles, gaining a more complete understanding of patient conditions. For example, claims data can be used to develop a study of hospital readmission rates among patients with specific conditions, identifying those who are at risk and enabling them to provide targeted care and support to reduce readmissions. 

What Is in Claims Data?

Claims data is important for insurance across many sectors, but what is claims data in healthcare? It’s the information entered into medical claims whenever a patient is seen by a physician, diagnosed with an illness or has a medical or surgical procedure, making it one of the most plentiful and useful sources of healthcare information. Claims data may also represent ancillary medical items like supplies or transportation. 

To understand what is in medical claims data, we have to look at a typical medical claims file, which is essential to the billing process and contains patient-specific details from each patient encounter. The information is divided into 2 parts: the claim header and claim detail.

Claim Header

The claim header contains a summary of the most pertinent information about the patient encounter, including details like:

  • The National provider identifier (NPI) is a unique, 10-digit identification number assigned to a physician or healthcare provider to help improve the efficiency of electronically transmitted health information.

  • The primary diagnosis code, which refers to the condition that requires the most resources from the healthcare provider during a patient’s hospital stay.

  • Whether or not there was an inpatient procedure, which is a medical procedure performed in hospitals with the expectation that the patient will stay in the hospital for at least one night. 

  • The diagnosis-related group (DRG), or category of patients with similar clinical diagnoses that help hospitals track costs and determine payer reimbursement rates. 

  • The patient’s insurance company, which identifies who is responsible for paying the medical claim. It could be a private insurer or one of the government-backed plans, such as Medicare.

  • The overall charge for the claim that the provider is asking the payer to reimburse them for.

Claim Detail

The claim detail includes any information about secondary diagnoses or procedures that happened during an inpatient stay. Each new claim detail contains:

  • The date the service was provided.

  • Procedure codes, such as CPT® codes tell payers very specifically what procedures were performed.

  • Corresponding diagnosis codes such as ICD-10 or ICD-11 that describe patient illness, injury or symptoms.

  • National drug code (NDC), if applicable. This 11-digit number is used to identify and report any drugs related to the claim to the FDA. These numbers provide transparency about the drug name and the manufacturer, as well as the strength, dosage and package size. Medicare will not reimburse hospital claims that do not include the NDCs for drugs given to patients during their stay.

  • NPI number of the attending physician.

  • The charge for the service.

The Importance of Claims Data

The importance of claims data is clearly demonstrated in the advantages that it brings to the medical billing and data analytics processes:

  • Standardization:

    Because of the standardized structure of medical codes, claims data can help improve payment accuracy and speed up medical claims processing. In analytics, the use of claims data can help streamline data processing and deliver cleaner results for analysts.

  • Sample size:

    Because of the amount of the data generated, research and development analysts can rely on large sample sizes for claims data. The vast amount of data contained in a payer database helps contribute to statistical significance and holistic research. 

  • Journey tracking:

    The ability to source data based on payers or providers allows patients’ journeys to be tracked across the full range of healthcare settings and types of insurance coverage, enabling a more holistic view of patient care.

  • Cost efficiency:

    Compared with other data collection methods, payer claims data is more cost-effective to use. This is mostly due to its availability and broad usefulness, which may render additional data collection efforts unnecessary. 

  • Structure:

    Because claims data is so fully structured, the process of de-identifying patient information for privacy and security purposes is simplified. 

Types of Claims Data

Representing different stages of the billing process, 2 different types of medical claims data allow researchers and life sciences organizations to examine different aspects of healthcare utilization. Both types of data can be used over a broad spectrum of research related to patient outcomes, and can be even more insightful when combined. 

Open claims data

Open claims are healthcare transactions that are still in progress. In this type of claim, the healthcare services have been provided by a physician, hospital or surgery center, but it’s still being reviewed by the payer. 

Consisting of information from medical and pharmacy claims, open claims data is generally used by organizations concerned with gathering large volumes of data that is clinical in nature (diagnoses, procedures, patient encounters, etc.), regardless of a patient’s insurance provider. 

Open claims encompass multiple sources of data and patient touch points with no limitation on time frame. The almost real-time availability of open claims data allows for timely reporting and tracking and is a key differentiator when compared with its closed-claims counterpart.

Closed claims data

Data from closed claims that have been processed, reviewed and reimbursed tells a more complete story of a patient’s healthcare journey and the total cost of their care. Insurance providers are the primary source of this data, which captures every aspect of a patient’s care during a specific time frame. This includes all medical and pharmacy transactions, providing a valuable examination of the diagnoses, actions and decisions associated with a patient’s journey. It is used by analysts who are concerned mainly with the economic, rather than clinical, aspects of healthcare.

Considering a Career in Health Information Technology?

If you want to work with healthcare data, improve the quality of patient care or contribute to the efficiency of the medical billing process, DeVry can help you get started on your journey. 

With coursework covering medical terminology, anatomy, international classification of diseases coding, health insurance and reimbursement and other relevant topics, our online Undergraduate Certificate in Medical Billing and Coding programs can help you prepare to pursue medical billing and coding career roles such as Billing Specialist, Insurance Claims Specialist, Medical Records and Health Information Technician or Coding Professional.

You can earn our Undergraduate Certificate in Medical Billing and Coding in as little as 10 months on an accelerated schedule, or follow a normal schedule and complete the program in 1 year and 2 months.1 Our Undergraduate Certificate in Medical Billing and Coding – Health Information Coding (HIC) can be earned in as little as 1 year and 2 months on an accelerated schedule, or 1 year and 6 months on a normal one.

And when you study with DeVry, our shared commitment to your success comes with access to Career Services support to help with your job search and building your resume. Classes start soon. 

1Normal schedule does not include breaks and assumes 2 semesters of year-round, full-time enrollment in 6-13 credit hours a semester per 12 month period. Accelerated schedule does not include breaks and assumes 3 semesters of year-round, full-time enrollment in 6-13 credit hours a semester per 12 month period.

2Normal schedule does not include breaks and assumes 2 semesters of year-round, full-time enrollment in 3-13 credit hours a semester per 12 month period. Accelerated schedule does not include breaks and assumes 3 semesters of year-round, full-time enrollment in 3-13 credit hours a semester per 12 month period.

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