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Automated patient self-scheduling: case study.

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Automated self-scheduling adoption grew to 15% in a physician group. Younger, commercially insured patients preferred it, showing fewer missed appointments but more cancellations.

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Area of Science:

  • Health Informatics
  • Digital Health
  • Patient Engagement

Background:

  • The increasing adoption of digital health tools necessitates understanding patient engagement with automated systems.
  • Community-based physician groups affiliated with academic health systems are exploring innovative patient service models.

Purpose of the Study:

  • To evaluate the uptake, user demographics, and appointment outcomes associated with automated self-scheduling.
  • To provide insights for organizations considering the implementation of digital self-scheduling platforms.

Main Methods:

  • A case study analyzing 1,995,909 appointments booked between January 2019 and June 2021.
  • Involved over 30 practice sites within a community-based physician group.
  • Examined patient characteristics, self-scheduling usage rates, and appointment outcomes (kept, missed, canceled).

Main Results:

  • Automated self-scheduling uptake increased from 4% to 15% of kept appointments during the study period.
  • Younger patients and those with commercial insurance were more likely to utilize self-scheduling.
  • Self-scheduled appointments had lower rates of no-shows but higher cancellation rates compared to traditionally booked appointments.

Conclusions:

  • Automated self-scheduling demonstrates growing patient adoption, particularly among specific demographics.
  • The system influences appointment management, reducing missed appointments while increasing cancellations.
  • Findings offer valuable data for healthcare organizations planning to implement or scale digital self-scheduling solutions.