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Develop Service Line Strategies
Analyze the Competitive Landscape
Anticipate Future Patient Needs
Identify Sites To Capture Demand
Drive Loyalty Across the Patient Journey
Leverage Price Transparency Insights
Retain Patients in Your Network
Match Provider Supply to Demand
Acquire Commercial Patients
Capture Outpatient Demand
Target High-Value HCPs
Strengthen Provider Networks
We collect and organize the industry’s most comprehensive healthcare datasets.
See demand, supply and yield across the U.S. health economy
Validated Data for 2.9M Practitioners
Episodes of Care for 300M Patients
Negotiated Rates for Any Service at Any Location
Flexible solutions to fit your specific needs and workflow
Answer Key Questions in Seconds
Custom Enterprise-Level Analyses
Inform Data-Driven Strategies
Free resources to help health economy stakeholders use our products and data
Health Economy Survival Strategies
Product Guides and Feature Releases
How We Tackle Technical Problems
Data-Driven Benchmarking Tool
Strategic guidance and commentary from our CEO, Hal Andrews
Annual fact-based analysis of trends shaping the health economy
An essential resource to survive healthcare’s negative-sum game
As more employers expand coverage of women’s, maternal, and family health services and investments in “FemTech” mount, insight into the primary care behaviors of the target population would better inform investments in female-focused healthcare services.
Our previous research reveals that most Americans have not "caught up" from their lack of primary care utilization during the pandemic, except females ages 20-49. In aggregate, pre-pandemic U.S. primary care utilization peaked in October 2019, and primary care volumes in October 2021 were 24% lower than the peak. In contrast, primary care volumes for females ages 20-49 in October 2021 increased by 7% from October 2019.
In light of this difference, we decided to further examine utilization by females between 20-49 at the diagnosis level. We isolated the top primary care diagnoses shared across females ages 20-29, 30-39, and 40-49 in October 2019 and October 2021, since those months showed the highest primary care volumes. The visit type with the greatest percent change across age groups is encounters for communicable diseases, likely connected to COVID-19. Visits for screenings also increased across all age groups, indicating a return to preventive care (Figure 1). Notably, visits for anxiety and stress disorders increased across age groups from October 2019 to October 2020, and then declined from October 2020 to October 2021. Of note is that the utilization of screenings was significant in the 20-29 and 30-39 cohorts, but there was almost no change among the 40-49 cohort.
Our previous research also revealed the disproportionately high utilization of telehealth within the female 20-49 cohort for behavioral health. Since many behavioral health needs present in primary care settings, we segmented our analysis by visits for routine examinations versus visits for anxiety and stress disorders to evaluate whether the increase in primary care was attributed to rebounding preventive services or growing demand for behavioral health services.
We found that average monthly routine examination visits are exceeding pre-pandemic levels across the female age cohorts between 20-49, indicating a return to certain screenings and preventive services for this population segment (Figure 2), as visits related to behavioral health have returned to pre-pandemic levels.
In contrast to the clinical complexity that will present in patients who delayed seeking care during the last two years of the pandemic, females in the 20-49 cohort are seemingly prioritizing individual health in the wake of the pandemic. Every primary care provider targeting females in the 20-49 cohort, whether “FemTech” or retailers or health systems, should focus on understanding who these patients are, why they are utilizing more primary care, and where they access it. We will begin to explore the consumer attributes and localized behaviors of these patients in subsequent research.
Thanks to Kelly Boyce and Katie Patton for their research support.