Mayo Clinic Proceedings: Innovations, Quality & Outcomes (Dec 2022)

Postsurgical Remote Patient Monitoring Outcomes and Perceptions: A Mixed-Methods Assessment

  • Aaron Spaulding, PhD,
  • Erica Loomis, MD,
  • Emily Brennan, MPH,
  • Diane Klein, BA,
  • Karlyn Pierson, MAN, RN,
  • Rochelle Willford, RN,
  • M. Susan Hallbeck, PhD,
  • Janani Reisenauer, MD

Journal volume & issue
Vol. 6, no. 6
pp. 574 – 583

Abstract

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Objective: To determine how postsurgical remote patient monitoring (RPM) influences readmissions and emergency visits within 30 days of discharge after operation and to understand patient and surgeon perspectives on postsurgical RPM. Patients and Methods: This study was conducted at a US tertiary academic medical center between April 1, 2021, and December 31, 2021. This mixed-methods evaluation included a randomized controlled trial evaluation of RPM after operation and a qualitative assessment of patients’ and surgeons’ perceptions of RPM’s acceptability, feasibility, and effectiveness. Results: A total of 292 patients participated in the RPM trial, and 147 were assigned to the RPM intervention. Despite a good balance between the groups, results indicated no difference in primary or secondary outcomes between the intervention and control groups. The qualitative component included 11 patients and 9 surgeons. The overarching theme for patients was that the program brought them peace of mind. Other main themes included technological issues and perceived benefits of the RPM platform. The major themes for surgeons included identifying the best patients to receive postsurgical RPM, actionable data collection and use, and improvements in data collection needed. Conclusion: Although quantitative results indicate no difference between the groups, postsurgical RPM appears well-accepted from the patient’s perspective. However, technological issues could eliminate the benefits. Hospitals seeking to implement similar programs should carefully evaluate which populations to use the program in and seek to collect actionable data.