digital predictive recovery

How digital predictive recovery can support orthopedic recovery and improve patient outcomes

Creating a patient baseline and capturing more accurate data with digital platforms can better guide medical practitioners in making effective clinical device decisions.

For patients with orthopedic trauma, current treatment plans are usually very rigid and don’t provide individualized treatment options during their recovery period. The individual treatment of patients is of high demand but is still lacking in many healthcare institutions. Additionally, a major challenge is a lack of long-term individual baseline data that would enable accurate and objective assessments of functional recovery.

Clinical outcome measures are often based on observing patients’ motor behaviors. These assessments are time-consuming and impractical to administer regularly. Outcome measures are too often collected only at baseline and at discharge. This means the lack of long-term baseline data prevents doctors from examining the need to adjust the treatment later and maximize recovery.

Digital platforms and machine learning (ML) in orthopedics can collect movement, pain, and other health data to create an accurate baseline for patients. Machine learning can use this baseline to estimate postoperative recovery and complications, the level of treatment modalities to be provided, and guide the medical practitioners in making effective clinical device decisions.

Why data before surgery is important

There is evidence that preoperative exercise can aid postoperative recovery after major joint replacement surgery, provided that this is offered to the vulnerable patient. Additionally, there is high-quality evidence that postoperative exercise training and rehabilitation should be initiated as soon as possible after surgery and be aimed at least at regaining functional mobility.

Another 2022 study also demonstrates the proven benefits of exercise rehabilitation for musculoskeletal injuries and recovery from surgery. Yet, patient adherence to such programs is reported to be less than 35%. 

Currently, most postoperative orthopedic surgery rehabilitation occurs in the outpatient setting or at home. This leads doctors and clinicians to rely on reports from outpatient physical therapy or subjective methods such as patient-reported outcomes measures (PROMs) to measure recovery.

Automated data collection saves time and improves accuracy

Studies have already demonstrated that using digital health interventions (DHI) can help identify postoperative adherence and complications earlier, improve recovery, and provide follow-up options that are acceptable to patients.

Smartphone apps and machine learning platforms offer a way to remotely monitor patients and objectively measure and predict their recovery.

Sensors embedded in mobile phones and wearable technology can capture many different data points remotely, passively, and continuously. These data points include activity data, pain data, medication data, test exercise data, and outcome score data. This gives doctors the chance to track physiological parameters and enable patients to self-report symptoms and signs, which can indicate their postoperative status.

Benefits of recovery prediction

Doctors can produce individualized risk and recovery predictions and near real-time treatment recommendations using real-world data from patients. Additionally, the platforms often enable automated follow-ups, timely interventions, and daily pain management, which shorten recovery time and lower the risk of complications.

When using digital platforms in pre-op and post-op recovery, clinic visits for patients are reduced to minimal levels, decreasing the strain on doctors and the healthcare system. This is significant given the predicted doctor shortage. By 2034, the AAMC predicts shortages of between 17,800 and 48,000 primary care physicians. It’s crucial to begin working toward a solution as soon as possible, and digital platforms can offer a lifeline to healthcare institutions.

Finally…

At Kunto Solutions, we’ve developed an app and cloud-based backend solution to give doctors and healthcare teams access to rich and objective data insights for better patient management and ongoing assessment over the course of care. Our remote patient monitoring platform automates the collection of objective and fact-based data from your patients’ smartphones – without the need for additional devices.

Additionally, we are developing a medical device called Kunto Recovery, which creates insight into a patient’s progress based on smartphone data, and will provide support for forecasting and modeling for optimal treatment and rehabilitation decisions.

Kunto Solutions ensures that all data is secure and we are subject to European privacy laws, such as GDPR. Kunto Research is our data collection platform for clinical trials. Kunto Recovery is our medical device software under development that will meet the required Quality Management System (ISO 13485) as well as the regulatory requirements set by EU medical device regulation (2017/745).