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Dec 31, 2023

Radnet Q4 2023 Earnings Report

RadNet reported record revenue and adjusted EBITDA, released 2024 financial guidance, and formed a new digital health reporting segment.

Key Takeaways

RadNet reported a revenue of $420.4 million for Q4 2023, a 9.5% increase from Q4 2022. The company experienced a net loss of $1.9 million, and adjusted earnings per share was $0.20. They are also forming a new Digital Health reporting segment.

Record revenue and Adjusted EBITDA in Q4 enabled RadNet to exceed its 2023 full-year revised guidance ranges.

The core Imaging Center segment experienced same-center procedural volume growth of 5.5% and revenue growth of 8.6% compared to Q4 2022.

RadNet carefully managed liquidity and financial leverage, with net debt to Adjusted EBITDA falling below 2.0x at year-end 2023 and a cash balance of $342 million.

The company projects to open approximately a dozen new facilities during 2024 and expects to continue expanding existing health system joint ventures and partnerships.

Total Revenue
$420M
Previous year: $384M
+9.5%
EPS
$0.2
Previous year: $0.11
+81.8%
Imaging centers
366
Previous year: 357
+2.5%
Gross Profit
$31.1M
Previous year: $54.3M
-42.7%
Cash and Equivalents
$343M
Previous year: $127M
+169.7%
Free Cash Flow
$48.9M
Total Assets
$2.89B
Previous year: $2.43B
+18.6%

Radnet

Radnet

Forward Guidance

RadNet anticipates significant growth in both the Imaging Center and Digital Health segments in 2024.

Positive Outlook

  • Benefit from a continued focus on same-center performance.
  • Benefit from tuck-in acquisitions.
  • Benefit from increased reimbursement.
  • Benefit from expanded and new health system joint ventures.
  • Benefit from de novo center openings.

Challenges Ahead

  • Continued commitment to capital expenditures in 2024, primarily on de novo center openings.
  • Substantial investment in the development of DeepHealth OS cloud-based operating system.
  • Generative AI modules that could lower costs and increase efficiency in areas of patient scheduling.
  • Generative AI modules that could lower costs and increase efficiency in areas of pre-authorization.
  • Generative AI modules that could lower costs and increase efficiency in areas of insurance verification and revenue cycle.