Resource Use Patterns in US Telehealth Services: Machine Learning and Clustering Analysis Across 4 Specialties - Summary - MDSpire

Resource Use Patterns in US Telehealth Services: Machine Learning and Clustering Analysis Across 4 Specialties

  • By

  • Aysenur Betul Cengil

  • Burak Eksioglu

  • Sandra Duni Eksioglu

  • Corey Hayes

  • Cari Bogulski

  • Mir Ali

  • May 7, 2026

  • 0 min

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Objective:

To identify factors influencing resource use in health care facilities in the U.S. and compare patterns across telehealth and office visits, focusing on patient-to-provider ratios and appointment durations.

Key Findings:
  • Telehealth visits were associated with lower patient-to-provider ratios and shorter appointment durations compared to office visits.
  • Patient- and facility-related factors significantly impacted resource use across care settings.
  • Clusters of health care facilities exhibited meaningful differences in telehealth adoption and performance metrics over time.
Interpretation:

The findings suggest that telehealth can enhance resource efficiency, with implications for improving care delivery and planning in health care systems.

Limitations:
  • The study focused on specific specialties, which may limit generalizability to other areas of health care.
  • Data were sourced from a single platform, potentially introducing bias based on the patient population represented.
Conclusion:

The study provides insights into telehealth adoption and resource utilization, informing stakeholders for sustainable integration of telehealth services.

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