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Mitigating data disruptions in open claims datasets

Healthcare data now accounts for approximately 30% of global data volume, with a projected compound annual growth rate of 36% by the end of 2025. With this surge in data, life sciences organisations have access to more information than ever before. However, this volume of data also comes with inevitable disruptions. Certain factors may enhance your analytical capabilities, including disruptions such as ownership diversity, evolving collection methods, and the emergence of new data aggregators—particularly the addition of new data suppliers.  Other disruptions, like industry-wide cyberattacks, or a data owner abruptly deciding to exit the commercial data space could impair decision-making.

This discussion focuses on open claims datasets, which are uniquely susceptible to certain types of disruptions due to their structure and sourcing. While closed claims and EMR databases may also experience disruptions, they typically differ in nature. For example, EMR data is often sourced from integrated systems like health plans or provider networks, where both Rx and medical data are captured together, making isolated Rx or Mx losses less likely. Additionally, product blocking and/or unblocking is generally not a concern in closed systems. You can learn more about open, closed and integrated claims datasets in our whitepaper, The claims conundrum: Integrating openness and precision for competitive advantage. 

Regardless of whether a disruption is perceived as positive or negative, it will impact your analyses and create extra work for you. Here are some common scenarios and their implications:

Open claims data disruptions and their effects

  • Rx data supplier loss/addition: May lead to shifts in market share, longitudinal trends, temporary spikes in new to brand prescriptions (NBRx) and changes in eligible patient cohorts
  • Medical claims (Mx) supplier loss/addition: Can affect diagnosis associations, medically-administered drug volume and share, new patient starts, and first diagnosis dates
  • Blocking/unblocking of products: May alter market share visibility, longitudinal analysis capabilities, and cause artificial spikes in NBRx
  • Partial losses: Some losses or gains are partial, for example select practices drop out of a medical claim supplier or new pharmacies or volume from existing stores become commercially available suddenly.  In these cases it can be more difficult to mitigate the impact particularly if the shift is sudden.

These disruptions can influence key metrics such as market share, line of therapy, treatment rates, triggers and market sizing.

Impact on key analytics

  • Market share: Variations in claims can shift market share. Changes in the medical claims sample could also disrupt the share by indication, even if the Rx volume remains unaffected. Disproportionate changes may affect both manufacturer’s and competitors
  • Treatment rate/line of therapy: The addition or loss of diagnosis, procedure or Rx claims may shift treatment start dates and therapy lines with respect to a time dimension – time to treatment initiation, time to advance line of therapy -  with the impact varying based on market dominance
  • NBRx/business source: New treatment (pharmacy or medical) data can cause temporary NBRx spikes due to missing historical context when the addition is point forward only. This normalises once history is restored. Rather than seeing an immediate spike this disruption will be reflected in a reset of trends at a new, lower, normal
  • Triggers: Claim volume changes can affect field alert counts and eligibility, requiring updated business rules to maintain accuracy
  • Market sizing: While typically based on projections rather than raw patient or claim counts, fluctuations in diagnosis, procedure, and prescription claims can still influence key metrics such as compliance and persistence. These shifts may reflect broader disruptions in the healthcare landscape, ultimately impacting the financial dynamics and completeness of market insights

How Symphony Health supports you through disruptions

At Symphony Health, an ICON plc company, we recognise that data disruptions are inevitable. Whether anticipated or unexpected, our commitment is to transparency and proactive communication. Transparency is an essential element in unlocking the full potential of healthcare data. While disruptions may be unavoidable it is possible to minimise their effects. 

We mitigate disruptions with:

  • Advance notifications and impact analyses for known disruptions
  • Timely alerts and post-event assessments for unforeseen events
  • Quality Control (QC) reports to monitor data volume changes
  • Ad hoc exclusion lists for pharmacy-related or facility-related disruptions.
  • Customisable business rules to mitigate disruption effects, such as:
    • Temporarily excluding affected patients or stores
    • Refining NBRx definitions to ensure accuracy
    • Maintaining historical data integrity

A collaborative partnership for resilience

Another way to minimise disruption is through a strong partnership with your data supplier. By aligning on metrics, sharing methodologies and implementing targeted checks, your data supplier can ensure the integrity and continuity of your open claims data. 

How to leverage your data 

Optimise your data and minimise the negative impact of disruption by taking the following steps:

  • If applicable and recommended, using Symphony’s patient, pharmacy, and physician activity panels to identify and filter data gaps
  • Adjusting business rules to minimise artificial trend breaks
  • Sharing key metrics and business rules to tailor impact analyses and reporting

Symphony Health is committed to data transparency and proactive support. 

Whether you're developing the business case for a supplier change or responding to an unexpected event, our team will ensure you have total confidence in your analytics. 

To learn more about how Symphony Health ensures transparency and supports your data strategy, contact us today.

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