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Living Textbook of
Pragmatic Clinical Trials

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Rethinking Clinical Trials

A Living Textbook of Pragmatic Clinical Trials

  • Design
    • What is a Pragmatic Clinical Trial?
    • Decentralized Pragmatic Clinical Trials
    • Developing a Compelling Grant Application
    • Experimental Designs and Randomization Schemes
    • Endpoints and Outcomes
    • Analysis Plan
    • Using Electronic Health Record Data
    • Building Partnerships and Teams to Ensure a Successful Trial
    • Intervention Delivery and Complexity
    • Patient Engagement
  • Data, Tools & Conduct
    • Assessing Feasibility
    • Acquiring Real-World Data
    • Assessing Fitness-for-Use of Real-World Data
    • Study Startup
    • Participant Recruitment
    • Monitoring Intervention Fidelity and Adaptations
    • Patient-Reported Outcomes
    • Clinical Decision Support
    • Mobile Health
    • Electronic Health Records–Based Phenotyping
    • Navigating the Unknown
  • Dissemination & Implementation
    • Data Sharing and Embedded Research
    • Dissemination Approaches for Different Audiences
    • Implementation
    • End-of-Trial Decision-Making
  • Ethics & Regulatory
    • Privacy Considerations
    • Identifying Those Engaged in Research
    • Collateral Findings
    • Consent, Disclosure, and Non-Disclosure
    • Data and Safety Monitoring
    • Ethical Considerations of Data Sharing in Pragmatic Clinical Trials
    • Ethics for AI and ML
    • IRB Responsibilities and Procedures

Use of Medicare Data in PCTs

CHAPTER SECTIONS

Assessing Fitness for Use of Real-World Data Sources


Section 5

Use of Medicare Data in PCTs

Expand Contributors

Keith A. Marsolo, PhD
Lesley H. Curtis, PhD

Contributing Editor

Karen Staman, MS

As of 2023, about half of all Medicare beneficiaries were enrolled in Medicare Advantage (Biniek et al 2023)—approximately 30.8 million people (Ochieng et al 2023). Medicare Advantage is a private managed care alternative to the traditional fee-for-service Medicare. With Medicare Advantage, healthcare organizations receive a set amount of money to cover the healthcare costs of enrolled patients, and the amount is determined by the patient's risk score, which is based on patient characteristics and health conditions (Centers for Medicare & Medicaid Services 2024). Thus, Medicare Advantage plans have different incentives to document diagnoses for patients than fee-for-service plans, as diagnoses are linked to risk scores, which could lead to aggressive coding practices (Keating 2023). These differences can impact the reliability and relevance of the data used for PCTs.

Some important differences have been highlighted in examples from the literature, including differences in population, medication, preventive services, and across states and counties.

  • Population
    • Medicare Advantage plans include a higher share of members who require chronic disease management, and those with serious mental health conditions or substance abuse issues (Waddill 2021).
  • Medication use
    • Use of high-risk medications that should be avoided in older adults were lower in Medicare Advantage patients (Figueroa et al 2023).
  • Preventative services
    • Medicare Advantage plans are incentivized to enhance preventive services, such as screenings, including higher mammogram rates in older patients with dementia (Raver et al 2024).
    • Lung cancer screening is higher in patients who have Medicare Advantage (Hughes et al 2023).
  • Variation across states and counties
    • There is wide variation in enrollment rates across states and counties, which could be reflective of urban vs rural populations, the number of Medicare beneficiaries and their healthcare use patterns, and differences in the firms that offer Medicare Advantage across different geographic regions (Ochieng et al 2023).

Researchers should be aware that differences in the data from Medicare Advantage or fee-for-service Medicare claims could be reflective of a true pattern, an artifact of billing, enrolled population, or treatments and medications.

Finally, trials that include both Medicare Advantage and fee-for-service Medicare populations would need to purchase both sets of data, which can be expensive depending on the number of years of data needed. The alternative to purchasing both sets of data is to push trial data into the Virtual Research Data Center and pay a flat fee for access to both, which comes with some logistical challenges but is worth considering.

Previous Section Next Section

SECTIONS

CHAPTER SECTIONS

sections

  1. Introduction
  2. Defining Fitness for Use
  3. Evaluating Fitness for Use
  4. Data Quality Measures
  5. Use of Medicare Data in PCTs
  6. Data Source Accuracy: Case Study from TRANSLATE-ACS
  7. Data Provenance
  8. Operationalizing Fitness-for-Use Assessments

REFERENCES

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Biniek JF, Freed M, Damico A, Neuman T. 2023. Half of All Eligible Medicare Beneficiaries Are Now Enrolled in Private Medicare Advantage Plans. KFF. https://www.kff.org/policy-watch/half-of-all-eligible-medicare-beneficiaries-are-now-enrolled-in-private-medicare-advantage-plans/. Accessed April 15, 2024.

Centers for Medicare & Medicaid Services. 2024. Capitation and Pre-payment. https://www.cms.gov/priorities/innovation/key-concepts/capitation-and-pre-payment. Accessed April 15, 2024.

Figueroa JF, Dai D, Feyman Y, et al. 2023. Use of high-risk medications among older adults enrolled in Medicare Advantage plans vs traditional Medicare. JAMA Netw Open. 6(6):e2320583. doi:10.1001/jamanetworkopen.2023.20583. PMID: 37368399.

Hughes DR, Chen J, Wallace AE, et al. 2023. Comparison of lung cancer screening eligibility and use between commercial, medicare, and medicare advantage enrollees. J Am Coll Radiol. 20(4):402-410. doi: 10.1016/j.jacr.2022.12.022. PMID: 37001939.

Keating NL. 2023. Challenges and opportunities to address aggressive coding practices by Medicare advantage plans. Ann Intern Med. 176(7):987–988. doi:10.7326/M23-0534. PMID: 37276598.

Ochieng N, Biniek JF, Freed M, Damico A, Neuman T. 2023. Medicare advantage in 2023: Enrollment update and key trends. Kaiser Family Foundation. https://www.kff.org/medicare/issue-brief/medicare-advantage-in-2023-enrollment-update-and-key-trends/. Accessed June 26, 2024.

Raver E, Xu WY, Jung J, Lee S. 2024. Breast cancer screening among Medicare Advantage enrollees with dementia. BMC Health Serv Res. 24(1):283. doi: 10.1186/s12913-024-10740-7. PMID: 38443911.

Waddill K. 2021. Medicare Advantage Plans Draw More Members with Chronic Diseases. TechTarget. https://healthpayerintelligence.com/news/medicare-advantage-plans-draw-more-members-with-chronic-diseases. Accessed April 15, 2024.


Version History

October 21, 2024: Made nonsubstantive changes to the text (changes made by D. Seils).

Published October 11, 2024

current section :

Use of Medicare Data in PCTs

  1. Introduction
  2. Defining Fitness for Use
  3. Evaluating Fitness for Use
  4. Data Quality Measures
  5. Use of Medicare Data in PCTs
  6. Data Source Accuracy: Case Study from TRANSLATE-ACS
  7. Data Provenance
  8. Operationalizing Fitness-for-Use Assessments

Citation:

Marsolo K, Curtis L. Assessing Fitness for Use of Real-World Data Sources: Use of Medicare Data in PCTs. In: Rethinking Clinical Trials: A Living Textbook of Pragmatic Clinical Trials. Bethesda, MD: NIH Pragmatic Trials Collaboratory. Available at: https://rethinkingclinicaltrials.org/chapters/conduct/assessing-fitness-for-use-of-real-world-data-sources/use-of-medicare-data-in-pcts/. Updated December 3, 2025. DOI: 10.28929/260.

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