telemedicine in total knee arthroplasty using wearable technology

Conditions: Knee Arthritis

Summary: subjectivity, cost-effectiveness, and inconsistent reporting limit monitoring after total knee arthroplasty (tka). this prospective study leverages machine learning wearable technology to remotely monitor patients before and after tka with fidelity and reliability, without sacrificing safe triage needing increased perioperative attention. patients will download a mobile app that pairs with a "smart" knee sleeve to (1) monitor activity via daily step count, (2) solicit patient-reported outcomes, (3) calculate max flexion, and (4) provide physical therapy compliance data. the primary objective of this study is to determine validity and acceptability of the technology; secondary objectives include perioperative benchmarking with characterization of post-operative recovery trajectories.

monitoring of pre-operative status and post-operative recovery from elective orthopaedic surgery is critical to delivering safe, value-based care. measurement after tka has traditionally been accomplished through clinician in-office assessments, validated surveys, or both; subjectivity, cost-effectiveness, and inconsistent reporting limit these assessments. leveraging now ubiquitous smartphone technology and smart wearable technology with machine learning software offers the opportunity to remotely monitor patients before and after surgery. this provides surgeons, hospitals, and stakeholders the opportunity to objectively quantify (1) patient compliance, (2) value of a given surgical procedure with unprecedented benchmarking, and, more importantly, (3) the better triage of those needing increased perioperative attention. regardless of the orthopaedic procedure, a motion-based machine learning software application to commercial mobile and wearable technology readily and inexpensively unlocks the potential of delivering value-based care through the low maintenance acquisition of both precision, small data that may then be extrapolated to population-level revelations from big data regardless of the joint or extremity. with the rise of telemedicine, clinical validation of the technology is of mutual interest to orthopaedic patients, surgeons, administrators, payers, and policymakers.

Eligibility criteria:
inclusion criteria: 1. patients undergoing primary tka for osteoarthritis 2. patients who have an ios smartphone and carry it with them daily 3. patients who reside in a home and not a facility or rehabilitation center 4. patients under the age of 80 years 5. patients who preoperatively have not used any assist devices for more than a year due to the non-affected joint or other functional reasons, including back pain. exclusion criteria: 1. patients receiving treatment for inflammatory arthritis 2. patients receiving active or maintenance treatment for cancer or solid organ and/or marrow transplant 3. patients with any other medical issues limiting mobility and function, including cardiopulmonary, gastrointestinal, and hematologic comorbidities 4. patients indicated for tka for post-traumatic or inflammatory arthritis 5. patients who have ever had a periprosthetic joint infection of any joint 6. patients who have a history of native septic arthritis in the operative joint 7. patients who were functionally immobilized or residing anywhere other than a home (nursing facility, rehabilitation centers) 8. patients who preoperatively used an assist device for more than a year (i.e. cane, walker) 9. patients over the age of 80 years.

Keywords: wearable mhealth