Harvard & Inovalon Medicare Research Collaboration

Harvard and Inovalon are collaborating to unlock insights on the characteristics of MA vs FFS beneficiaries before and after initial Medicare enrollment at age 65.

Download White Papers

Real-World Insights from Harvard Medical School and Inovalon

Given the dramatic growth of Medicare Advantage (MA) – enrollment increased from 17% of Medicare beneficiaries in 2000 to 48% in 2023 – it is increasingly important for MA plans to understand who is going to be enrolling and how that is likely to impact resource needs, costs, and quality performance.

Harvard Medical School and Inovalon partnered to conduct a first-of-its-kind analysis to characterize the emerging Medicare population during the one-year period before and after enrolling at age 65.

The insights and analysis from this partnership include:

A simple bar chart with increasing bars and a line graph above them, highlighting quality improvement solutions with three circles marking key data points on the upward trend.

Quality of care before and after the age of 65 under MA versus FFS.

Simple line drawing of three people standing together, with five colored circles above, symbolizing teamwork—ideal for addressing staff burnout or promoting collaboration among healthcare staff.

Medicare members' demographics and socioeconomic characteristics before and after transitioning from commercial insurance plans to Medicare.

An illustration of two hands shaking, forming the shape of a heart. The soft blue and beige gradients symbolize unity, support, partnership, and meaningful connections in careers.

Healthcare utilization before and after the age of 65 under MA versus FFS.

bar graph icon

How MA addressed health inequities based on race, income, and other social drivers of health.

How It Helps

The data used to produce these insights is informing new algorithms to help health plans better target their offerings to new and existing members.

A simple graphic of a magnifying glass focusing on a line graph, with vertical bar chart elements in the background, symbolizing data analysis or analytics.

Predict retention risk and personalize marketing offers

Access customized market insights to project enrollment flows into specific product lines and understand what attracts and retains new enrollees.

A simplified line graph with four data points, each connected by a line, overlays a bar chart with increasing bars from left to right, illustrating upward growth or progress using real world data.

Project new enrollees’ resource needs

Project healthcare utilization and costs for strategic resource planning and to better meet members' unique needs.

A simple five-pointed star with a blue outline and a pale, gradient fill, centered on a light gray background—ideal for representing clinical data extraction software.

Improve star ratings

Understand how new enrollees will affect your rating and performance on individual quality measures and the new Excellent Health Outcomes for All (EHO4all) and reward factor.

Icon of a document with text lines and a magnifying glass showing a dollar sign, symbolizing how billing providers leverage RCM tech for efficient financial review or analysis.

Benchmark against competitors

Benchmark your MA plan performance against competitor MA plans in your market region.

Icon of a person inside a circle with crosshairs and dotted lines around it, symbolizing targeting, focus, or user identification. The background is a soft gradient of pastel colors.

Evaluate competitive position

Improve your competitive position by better understanding who is switching between MA and FFS.

Outline of three people, with the center figure enlarged by a magnifying glass—symbolizing selection or recruitment—highlighting the power of data linking in identifying top talent.

Identify social needs of new enrollees

Understand your new and current members’ social drivers of health, to drive impact on reducing health disparities and lowering overall costs.

Meet the Experts

A man with short hair, a beard, and wearing a plaid shirt and t-shirt smiles slightly at the camera. The black and white image, shown in a circular frame, captures an authentic look reminiscent of real world data portraits.

Boris Vabson, Ph.D.

Seidman Fellow
Harvard Medical School

A man with short hair and glasses smiles at the camera. He is wearing a jacket over a sweater and shirt. The blurred foliage background evokes the nuanced perspective of Real World Data. The image is in black and white with a circular frame.

Yalun Su

Student Affiliate, HMR Lab,
Harvard Medical School

A man wearing glasses, a suit, and a tie is smiling at the camera. The background features a blurred urban street scene, emphasizing the subject. This black and white image, cropped into a circle, captures a professional in the realm of Real World Data.

Zarek Brot-Goldberg, Ph.D.

Faculty Affiliate, HMR Lab,
Harvard Medical School

A black-and-white portrait of a smiling woman with curly hair, wearing a blazer and earrings, in front of a blurred background with window panes, reflecting her expertise in Real World Data.

Christie Teigland, Ph.D.

VP, Research Science and Advanced Analytics, Inovalon

Black and white portrait of a man wearing glasses, a suit, checkered shirt, and polka-dot tie, posed in front of a subtle floral patterned background—capturing the precision and detail of Real World Data in classic style.

Zulkarnain Pulungan, Ph.D.

AVP, Research Science and
Advanced Analytics, Inovalon

Black and white photo of a man with a shaved head, wearing a collared shirt and a slight smile, looking slightly upwards. The softly blurred indoor background lends an authentic touch, evoking the nuance of Real World Data.

Barton Jones

Sr. Director, Research Science and Advanced Analytics,  Inovalon

A man in a suit and tie smiles while looking slightly to the side. The black-and-white photo, presented in a circular frame, evokes professionalism—perfect for topics like Real World Data. The softly blurred background adds a refined touch.

Iman Mohammadi, Ph.D.

Director, Research Science and Advanced Analytics, Inovalon

White Papers

Real-World Insights from Harvard Medical School and Inovalon
A person holds a tablet displaying real world data charts and graphs in a meeting room with two colleagues. One gestures while others listen. An icon of a document is shown in the foreground.

Harvard-Inovalon Medicare Study: Who Enrolls in Medicare Advantage vs. Medicare Fee-for-Service

While almost half of all Medicare beneficiaries are now enrolled in Medicare Advantage (MA), surprisingly little is known about how those who enroll …

Download White Paper
An older woman with short gray hair, wearing a green blouse, smiles while reading Real World Data at a table. A circular icon with a document symbol is overlaid in the lower right corner.

Healthcare Utilization After the Age of 65 Under MA vs. FFS

While Medicare Advantage (MA) now covers over half of Medicare beneficiaries and accounts for over $350 billion in expenditures annually…

Download White Paper
A doctor with a stethoscope smiles and talks to an older woman in a yellow shirt during a consultation, highlighting the use of Real World Data. An icon of a document appears in the lower right corner.

Quality of Care After the Age of 65 Under MA vs. FFS

While Medicare Advantage (MA) now covers over half of Medicare beneficiaries, including a disproportionate share of those facing socioeconomic disadvantage…

Download White Paper
A pair of eyeglasses rests on printed charts and a keyboard, with a pen nearby—capturing the essence of Real World Data. A blue icon of a document is overlaid in the lower right corner.

Harvard-Inovalon Medicare Study: The Importance of Plan Design in Medicare Advantage

For the past 40 years, Medicare beneficiaries have been able to freely choose between two different types of
insurance coverage…

Download White Paper

News & Insights

View articles, press releases, journals, and other newsworthy highlights from this partnership.

Discover More RWD Insights

Explore research and publications from our HEOR experts and extensive primary source, real-world data.

See More Research