Extending Joint Replacement Care Beyond the Clinic: A Practical Guide to RTM After Discharge

Total joint replacement, particularly hip and knee arthroplasty, is among the most frequently performed surgical procedures in adults in the United States, with more than one million cases each year.¹ Despite its prevalence, total joint replacement remains a costly intervention, with a notable risk of unplanned revisits or readmissions.² Many patients are now discharged the same day, recovering not in a hospital bed, but at home—sometimes within hours of surgery. 

While this shift to recovery-at-home can improve operational efficiency and free up much-needed hospital beds, it also introduces a new issue for healthcare providers and the recovering patient: the most critical phase of recovery is happening outside the clinic, where clinicians have historically had little visibility or influence.

Remote therapeutic monitoring (RTM) is emerging as a powerful way to close this gap, giving clinicians visibility into recovery as it happens and enabling more connected, proactive care. With RTM, healthcare organizations can deliver joint replacement care that is more connected, effective, scalable, and aligned with the future of rehabilitation.

<sup>1. Maradit Kremers H, Larson DR, Crowson CS, et al. Prevalence of total hip and knee replacement in the United States. J Bone Joint Surg 2015; 97: 1386–1397.
2. Williams SN, Wolford ML, Bercovitz A. Hospitalization for total knee replacement among inpatients aged 45 and over: United States, 2000–2010. Hyattsville, MD: National Center for Health Statistics, 2015.</sup>

Download this white paper to learn:

• How remote therapeutic monitoring (RTM) supports recovery after joint replacement surgery.

• Unique benefits like visibility into early recovery and patient adherence that RTM can deliver to both private practices and health systems.

• How Medbridge RTM and One Care help organizations deliver connected care to joint replacement patients without adding complexity to clinical workflows.