An integrated approach for deeper insight with both open and closed claims data
Determining the right data and how to leverage it for your business objectives can be complex. No single dataset can meet all your needs in every situation, but choosing the right foundational dataset is essential to achieving your desired outcomes.
However, with the increasing financial scrutiny and policy pressure on the pharmaceutical industry, there is a growing need for robust patient longitudinality that also allows for a holistic and comprehensive view of the complete healthcare journey. With either an open OR closed dataset, this lofty goal is becoming increasingly overwhelming.
Open and closed datasets refer to how the data is collected and how much and to what degree, you have visibility into the patient journey. In a previous blog, Navigating the complexities of healthcare data types, Symphony Health, an ICON plc company, discussed choosing between standalone open claims and closed claims as the foundation for analytic needs and various use cases, each offering unique benefits and applications. In this blog, we will summarise open and closed as standalone foundations but will also explore a third option of integrating both open and closed claims in a singular dataset.
Open and closed claims: Two foundational data types
Open claims
Open claims are derived from multiple types of sources and can highlight a patient’s activities over a longer timeframe, regardless of a patient’s insurance provider. Therefore, open claims allow for broader longitudinality and transparency regarding payer identity and influence on the financial aspects of treatment. There is also minimal lag time between healthcare events and their appearance in the data in open claims. These advantages make open claims more advantageous for:
- Analysing healthcare trends across diverse populations
- Identifying broad utilisation trends
- Examining sub-national trends at geographically granular levels
- Revealing the effects of managed care utilisation management tactics
- Informing sales and marketing operations in real time
However, due to the way in which open claims are collected, the user might see gaps where patient events occurred outside of the data sample network. Additionally, in a market or therapeutic area where a therapy is considered a specialty product, these therapies are often blocked in open claims by contractual negotiations between the manufacturer and the specialty pharmacy or by specialty pharmacy preference for the therapeutic category. While proven techniques exist to close data gaps and construct stable patient cohorts to mitigate the risk of missing data, an additional layer of complexity is added to any analysis.
Closed claims
Closed claims are derived from a singular source, the patient’s health insurance plan, revealing nearly all a patient’s healthcare activities during a specific enrolment period. To this end, closed claims facilitate highly accurate insights into healthcare utilisation and outcomes, providing a more detailed and patient-centric view that is ideal for precise analysis. Closed claims are therefore more advantageous for:
- Health Economics Outcomes Research (HEOR)
- Comparative effectiveness
- Clinical trial design
- Clinical operations
- Patient journeys / natural histories
Closed claims, however, are not without their own limitations. Due to the way in which the data is collected, the closed claims dataset sample size is much smaller and the window of time available for the patient's healthcare journey is shortened, making longitudinality challenging. Additionally, there is a greater lag time between the healthcare event and their appearance in the data, creating frustration when using closed claims for activities around product launch.
Integrating open and closed: Best of both worlds?
An integrated open and closed foundational approach involves using both open and closed claims datasets for their respective strengths, using them separately and sequentially, and taking insights from one dataset type as the starting point for new questions explored in the other. This approach enables users to leverage the same integrated version of diverse data sources for more nuanced analyses, such as the need for precision around outcomes or utilisation seen in closed claims, along with the payer impact, longitudinality, and in-depth patient exploration seen in open claims.
An integrated open and closed data solution serves multiple purposes across commercial analytics and reporting, Health Economics and Outcomes Research (HEOR), Medical Affairs, Real-World Evidence (RWE), pipeline management and business development teams, allowing for more seamless collaboration and reduction in resources through the usage of a singular dataset.
Benefits of an integrated open and closed claims foundation:
- Specialty product visibility: An integrated open and closed dataset would provide visibility into blocked products, making patient journeys more transparent and providing deeper understanding of writer and market utilisation and share dynamics.
- Reduced data bias: Standalone open or closed claims solutions may have limited and/ or unequal coverage across payment types, which may inherently and unintentionally cause a regional and/or socioeconomic bias in the patient cohort selected. Leveraging an integrated solution will reduce these unintended biases and allow the end user to be confident the results are representative of the US population.
- Mapping patient treatment pathways: Patients enrolled in a pharmacy plan do not always have the same medical plan, meaning that a single closed claim dataset will showcase their medical benefit history while enrolled but it may not always provide insights into a patient’s pharmacy benefit (or vice versa). Open claims also hold the potential for gaps in diagnoses or treatments for patients. The combination of the two sources minimises those gaps allowing for a more comprehensive view of the treatment patterns and therapy progression.
- Improved longitudinal analysis: As a standalone dataset, closed claims provide activity only within the time period in which the patient is enrolled in a health plan, making longitudinal analysis challenging over a longer period of time. An integrated foundation, however, supplements with open claims data to fill in the gaps before and after the snapshot captured in closed claims. This more comprehensive data timeline allows for a more robust longitudinal analysis, enabling insights into more complex therapeutic conditions and the ability to follow patients for longer terms.
- Market Demand & Product Lifecycle: Open claims data provides real-time visibility into market demand, while closed claims data offers historical context. Together, they help pharmaceutical manufacturers forecast demand more accurately and make informed decisions about inventory, production planning, and product lifecycle management.
- Sales Performance Analysis: By tracking claims data across different markets and geographies, manufacturers can measure the commercial success of their products without the concern for data blocking which limits visibility to certain products in the open claims data. This enables better tracking of product share by providers and accounts across payment types and subtypes (not a payer name level).
Tradeoffs of an integrated open and closed claims foundation:
While inheriting the benefits from each parent dataset, it is important for the user to be aware that the integrated dataset is not without its own unique set of limitations and these tradeoffs should be considered when making a choice for a foundational dataset with which to address unmet needs.
- Payer data restrictions: It's essential to understand that payers sharing their data must keep their financial relationships with providers confidential. This restriction has operational implications, such as excluding the payers’ names from the closed data foundation. Consequently, the same level of payer detail is also absent from an integrated foundation, which complicates payer analyses and enhances the need for an additional payer data asset that contains a subset of the data from the integrated foundation.
- NPI Restrictions: Closed claims have a restriction on providing visibility to the financial relationship between a payer and a provider. There are data suppliers that choose to remove NPI from the foundational closed data because of the limited payer sample in the data, while other closed claims suppliers will provide that field with rigorous use case restrictions requiring users of the data to not attempt to determine the financial relationship between the payer and provider. It is important to understand if these same restrictions would apply to the integrated data foundation you are considering.
- Timeline considerations: Open claims data can be captured in near real-time, though closed claims usually lag around 60-90 days from the healthcare event based on the way data is captured and managed. When integrating open and closed claims, the resulting dataset will feature both events that happen shortly before the delivery date, alongside those that conclude several months earlier. To draw more accurate conclusions when analysing trends, it's essential to consider this timing discrepancy.
- Analytical readiness: The integrated open and closed claims foundation should be in a state that is ready for analyses. The user must consider cleansing, deduplication and standardisation efforts on the part of the data supplier. If this data cleaning hasn’t been completed prior to delivery, the user will have to invest considerable effort and resource allocation to ensure analytical readiness.
- Key variables necessary: Open claims use the NCPDP D.0 format, while closed claims do not, limiting visibility into common fields for integrated data. Open claims also leverage the 837 and 835 formats, whereas closed claims are encounter-based with less data richness. It is important to assess what key variables would be necessary for each business case and determine availability in the integrated foundation you are considering.
Building on your data foundation
Even with a solid data foundation of open, closed, or an integrated solution depending on your specific need, the fact remains that no one dataset will address everything. Further integrating your foundation with additional data assets promotes even more precise analytics and actionable insights to inform strategic decisions, clinical protocols, physician targeting and recruitment efforts, and commercial or epidemiology and outcomes-based reporting.
For example, when integrating your foundation with Social Determinants of Health (SDoH) and lab data, users can better target patients for more accurate cohort selections, which supports more personalised treatment strategies. In addition, the ability to track long-term health outcomes and treatment effectiveness, particularly in pharmaceutical research and clinical trials, supports comprehensive outcomes research.
Choosing a data provider
For professionals in the pharmaceutical industry, the choice between open, closed and integrated datasets as your foundation depends on the nature of the research questions and business objectives and is key to your overall success. Similarly, choosing a transparent data partner with a robust data ecosystem and a consultative approach is just as crucial.
Introducing PatientSourceDuo from Symphony Health, an ICON plc company
We are excited to announce that we will be integrating our comprehensive longitudinal open claims with PatientSourceComplete, our deidentified closed claims data that covers the entire continuum of care during a patient's enrolment in their insurance plan. Come March 2025, PatientSourceDuo, our integrated claims solution, will empower you to make more informed decisions, streamline operations and ultimately improve patient outcomes.
PatientSourceDuo embodies Symphony Health’s core values—reliability, flexibility, collaboration and transparency.
To find out more about PatientSourceDuo and how Symphony Health can address your data needs, connect with us today.