Rehabilitation for total knee replacement (TKA) often involves in-person therapy sessions, which can be time consuming and costly. Digital rehabilitation has the potential to address these limitations, but most of these systems offer standardized protocols without considering the patient’s pain, participation, and speed of recovery. Furthermore, most digital systems lack human support in case of need. The aim of this study was to investigate the engagement, safety, and clinical effectiveness of a personalized and adaptative app-based human-supported digital monitoring and rehabilitation program. In this prospective multi-center longitudinal cohort study, 127 patients were included. Undesired events were managed through a smart alert system. Doctors were triggered when there was a suspicion of problems. The drop-out rate, complications and readmissions, PROMS, and satisfaction were collected through the app. There was only 2% readmission. Doctor actions through the platform potentially avoided 57 consultations (85% of alerts). The adherence to the program was 77%, and 89% of the patients would recommend the use of the program. Personalized human-backed-up digital solutions can help to improve the rehabilitation journey of patients after TKA, lower healthcare-related costs by lowering the complication and readmission rate, and improve patient reported outcomes.

Osteoarthritis (OA) poses a growing challenge for the aging population, especially in the hip and knee joints, contributing significantly to disability and societal costs. Exploring the integration of wearable technology, this study addresses the limitations of traditional rehabilitation assessments in capturing real-world experiences and dynamic variations. Specifically, it focuses on continuously monitoring physical activity in hip and knee OA patients using automated unsupervised evaluations within the rehabilitation process. We analyzed data from 1144 patients who used a mobile health application after surgery; the activity data were collected using the Garmin Vivofit 4. Several parameters, such as the total number of steps per day, the peak 6-minute consecutive cadence (P6MC) and peak 1-minute cadence (P1M), were computed and analyzed on a daily basis. The results indicated that cadence-based measurements can effectively, and earlier, differ among patients with hip and knee conditions, as well as in the recovery process. Comparisons based on recovery status and type of surgery reveal distinctive trajectories, emphasizing the effectiveness of P6MC and P1M in detecting variations earlier than total steps per day. Furthermore, cadence-based measurements showed a lower inter-day variability (40%) compared to the total number of steps per day (80%). Automated assessments, including P1M and P6MC, offer nuanced insights into the patients’ dynamic activity profiles.

Up to 25% of patients undergoing knee arthroplasty report chronic pain postoperatively. Early identification of high-risk individuals can enhance pain management strategies. This retrospective analysis investigates the incidence of severe postoperative pain and its associated risk factors among 740 patients who underwent total knee arthroplasty. Utilizing a digital application, patients provided comprehensive data encompassing pre- and postoperative pain levels, analgesic usage, and completed a chronic pain risk assessment. Participants were categorized into two distinct groups based on their pain status at three months post-op: Group D+ (14%), characterized by pain scores exceeding 40/100 and/or the utilization of level 2 or 3 analgesics, and Group D− (86%), who did not meet these criteria. An analysis of pain trajectories within these groups revealed a non-linear progression, with specific patterns emerging amongst those predisposed to chronic pain. Notably, patients with a trajectory towards chronic pain exhibited a plateau in pain intensity approximately three weeks post-surgery. Significant preoperative risk factors were identified, including elevated initial pain levels, the presence of comorbidities, pain in other body areas, heightened joint sensitivity and stiffness. This study highlights the utility of digital platforms in enhancing patient care, particularly through the continuous monitoring of pain. Such an approach facilitates the early identification of potential complications and enables timely interventions.

The COVID-19 pandemic highlighted the need for efficient use of hospital infrastructure. The hypothesis was that a rapid shift to outpatient surgery after hip or knee arthroplasty could be implemented without compromising quality of care. The aim of this study was to assess the safety, pain management and patient-reported outcomes before and after the implementation of an accelerated discharge program using a digital follow-up tool. A retrospective cohort design was used to compare 97 patients who received primary total hip or knee arthroplasty during the pandemic (early discharge) to comparable 194 pre-pandemic patients (normal discharge). Both cohorts had the same inclusion criteria and were closely monitored using the digital follow-up tool. The accelerated discharge program reduced length of stay from a median of 3 days (before the pandemic) to a median of 1 day (during the pandemic) (p < 0.001). The complication rate of 2% was the same for both groups (p > 0.05). Patient-reported outcomes for matched samples of hip (n = 100) and knee (n = 82) arthroplasty patients were similar before, at 6 weeks and 3 months after surgery for both groups (p > 0.05). There were no differences in pain and medication consumption for the first 6 weeks (p > 0.05). This study demonstrates that reducing length of stay from three to one night after total knee or hip arthroplasty, with the help of a digital follow-up tool, results in a stable rate of complications, readmission, and comparable clinical outcomes, while reducing the socio-economic burden on the health system.

Osteoarthritis (OA) poses a growing challenge for the aging population, especially in hip and knee joints, contributing significantly to disability and societal costs. Conventional clinical evaluations, typically performed in controlled settings, face difficulties in capturing the dynamic characteristics of rehabilitation and functioning in real-life scenarios. The study assessed the use of automated unsupervised evaluations in the rehabilitation process for patients after hip and knee replacements. We analyzed data from 1144 individuals who used a digital application after surgery, activity data were collected using the Garmin Vivofit 4. Several parameters such as the Peak 6-Minute Consecutive Cadence (P6MC) and Peak 1-Minute Cadence (P1M) were computed and analyzed on a daily basis. The results indicated that cadence measurements, specifically, can effectively differ among individuals with hip and knee conditions as well as the recovery process. Moreover, these metrics demonstrated a high level of responsiveness in monitoring the progress of recovery, surpassing the effectiveness of simply measuring the total number of steps taken. The study highlighted the capacity of technology-driven, patient-centered rehabilitation to improve accuracy, tailor therapy to individual patients, and increased patient involvement. This research also highlighted the significance of automated, unsupervised assessments in enhancing rehabilitation results for OA patients following hip and knee replacement, as tele-rehabilitation becomes increasingly important.