Net Health, a leading provider of cloud-based software and analytics for specialty medical providers, recently announced two pioneering predictive analytic capabilities embedded in the workflow of Net Health® Wound Care’s widely used electronic health record (EHR) platform.
Offering artificial intelligence-based capabilities, the Net Health Wound Care software platform now includes the Risk of Amputation Indicator, developed to reduce the risk of amputations, and the Wound Healing Velocity Indicator, created to predict wound healing rates. Both capabilities will offer the insights needed to provide optimal patient therapies, implement effective interventions, and plan treatment paths to improve outcomes.
These new predictive analytics capabilities are made possible by Net Health’s database – the world’s largest, most comprehensive database of wound care episodes covering 4.7 million wounds over more than 20 years. The algorithms behind the healing prediction and amputation risk indicators are trained on this database. Additionally, the algorithms are tested on the database and have been proven to significantly outperform other published models.
The Risk of Amputation Indicator is a predictive analytics tool that informs clinicians of the likelihood that a wound could lead to amputation by highlighting obstacles to recovery. The indicator is backed by a robust predictive model powered by decades of wound care insights. The Risk of Amputation Indicator considers approximately 175 parameters related to the patient and their wound(s). It provides clinicians with real-time predictions, giving them the knowledge needed to intervene and prevent unnecessary amputations.
The Wound Healing Velocity Indicator informs clinicians of the likelihood that a specific patient’s wound will heal within four, eight, twelve, or sixteen weeks. Unlike subjective assessments that vary significantly among clinicians or facilities, Net Health’s new indicator tool offers a real-time snapshot of a wound’s likelihood of healing based on an analysis of millions of wound care episodes and factors in hundreds of parameters that affect healing time.
The Net Health Wound Care application also offers insight into wound- and patient-specific information that is helping or hurting a patient’s chance of healing. Pairing these predictive insights can help clinicians make more timely interventions to optimize a patient’s healing outcome. The data used to develop the two indicators were tested as part of a recent pilot program involving several Net Health Wound Care clients. Clinicians using the platform provided several insights helping to validate the concept and inform updates and features to ensure optimal value for clinicians.
“Wound care clinicians work tirelessly to help their patients,” said Josh Budman, vice president of Analytics. “But wound care is complex – there are multiple factors that can prolong or interrupt healing. What clinicians need is accurate information and guidance about the wounds they are treating. Predictive models and machine learning represent the next level in the evolution of wound care technology. Coupling that capability with the EHR most wound care clinicians trust and rely on provides a powerful tool to help patients get better faster.”