Open vs. Closed Claims: Unlocking Opportunities for Healthcare Analytics

Q&A with Meg Richards, Executive Director of Solutions at Panalgo

In the complex healthcare analytics landscape, understanding the nuances of open and closed claims is critical for researchers and analysts. Open and closed claims each offer unique insights into the patient journey. Open claims, sourced from various clearinghouses and warehouses across the U.S., present a vast collection of data, while closed claims, adjudicated by insurers, provide a detailed and individualized perspective. Open claims are rather like a wide-angle view of the forest whereas closed claims are more like a view of the individual trees.

We caught up with Meg Richards, PhD, MPH and Executive Director of Solutions at Panalgo, to discuss the significance of open and closed claims in healthcare research, their strengths and limitations, and predictions for the future.

Q: What are administrative claims?

A: In healthcare, administrative claims are the bills submitted by physicians, hospitals, pharmacies, or other medical providers for office visits, hospital stays, other encounters, or sales of drugs and supplies.

Claims data refer to the information derived from the electronic processing of a healthcare claim. Whereas claims are handled primarily for the purpose of payment, the data obtained from these claims are also utilized for secondary healthcare research.

Q: Some administrative claims are ‘open’ whereas others are ‘closed.’ What’s the difference between open and closed claims?

A: Closed-payer claims data refers to information from payers that is provided directly by health insurance companies or a collection of employers sharing their employees’ health claims with consulting services, revealing (nearly) all of a patient’s healthcare activities within a fixed period of enrollment.

Open claims are captured through practice management systems (information systems that manage medical practices’ scheduling and billing), “switches” or “clearinghouses” (companies that route claims from healthcare providers to insurers), or pharmacy benefit managers (companies that provide the link between pharmacies and insurance companies).

Closed claims reveal a comprehensive view of a patient’s healthcare activities across geographies but are limited to a specific time period and payer. Conversely, open claims provide a higher-level glimpse into the patient across multiple data sources and longer time frames regardless of insurance provider but can be incomplete. For many years, closed claims have been the first choice for health economists and epidemiologists profiling a patient cohort’s experience from disease onset to diagnosis and treatment. Open claims were used more for market uptake characterization and clinical trial recruitment. However, as more data become available and methods to enhance the quality of the data mature, the distinguishing features and uses of open vs. closed claims can overlap.

Q: What type of claims should you use and when? When are closed claims the best choice for research and when are open claims the best choice?


Q: Is there a way to ‘engineer’ open claims data to make it more useful in characterizing the patient journey?

A: Open claims can be linked to closed claims to supply missing information. Duplicate patients can be identified and removed by matching patients with different IDs on gender, state, birth year, comorbidity score and other variables to drop all but one patient row. This may sound easy but is actually quite nuanced, and the robustness of the result has much to do with the quality of the underlying data sources being linked.

Q: What does the future look like for open and closed claims?

We’ll see more and more linkage and overlay of claims data (with lab data, and EHR data) in an effort to create a very complete picture of each and every patient.

Q: How can Panalgo help you with your healthcare analytics?

A: We have access to both open and closed claims and linked data sources to which we can provide streamlined and rapid deployment via our ‘Data on Demand’ program. You can analyze the data in our robust and rapid Instant Health Data (IHD) platform; or we can provide a trained analyst (Masters or PhD in epidemiology, HEOR, data science) to work with you, or on your behalf, in an analytics engagement. Panalgo offers bundled solutions of data, services and technology that is just right for you.

To find out more about Panalgo’s IHD platform and data on demand, contact us.