Implementation of an Automated Text Message–Based System for Tracking Patient-Reported Outcomes in Spine Surgery: An Overview of the Concept and Our Early Experience

Alexander Perdomo-Pantoja, Safwan Alomari, Daniel Lubelski, Ann Liu, Trevor DeMordaunt, Ali Bydon, Timothy F. Witham, Nicholas Theodore

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: Text message–based interventions have been demonstrated to be a valuable monitoring tool across various conditions. Here, we aimed to describe our early experience using a newly developed text message–based platform designed to track symptoms in spine surgery patients. Methods: We used the Informed Mindset Medical (IMM) platform to automatically send text messages with secure and encrypted hyperlinks to enrolled patients. Patient symptoms were monitored using well-standardized functional assessments. Limited patient data and responses were stored on a Health Insurance Portability and Accountability Act–compliant SQL cloud-based server database. Results: In 3 months, 101 patients scheduled for elective spine surgery accepted participation in our pilot study. Overall, 71.2% of the enrolled patients responded to at least 1 preoperative baseline questionnaire. The response rates were similar across attendings, questionnaire bundles (cervical vs. thoracolumbar), genders, and age groups. The overall preoperative IMM pain scores were found to correlate positively with the preoperative electronic medical record pain rates. Similarly, the overall preoperative IMM and electronic medical record pain scores correlated positively with the IMM-collected Neck Disability Index/Oswestry Disability Index scores. From an initial 71.2%, the response rate decreased to 54.9% for the 6-week follow-up questionnaires. Conclusions: Our preliminary findings support the reliability of this text message–based strategy to monitor symptoms in spine surgery patients. Further studies are warranted to explore strategies to increase the response rate and expand this platform's clinical and research applicability.

Original languageEnglish (US)
Pages (from-to)e746-e753
JournalWorld neurosurgery
Volume158
DOIs
StatePublished - Feb 2022

Keywords

  • Automated text messaging
  • Pain scoring
  • Remote monitoring
  • Self-assessment
  • Spine surgery
  • Symptom surveillance

ASJC Scopus subject areas

  • Clinical Neurology
  • Surgery

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