The use of big data to measure and document wounds is reducing clinical assessment time and improving wound care management.
FREMONT, CA: With more people suffering from chronic wounds, care management has become healthcare's most significant clinical concern. This also plagues healthcare providers, as injuries can quickly become problematic, leading to life-threatening infections and costly hospitalization. However, by taking advantage of big data, healthcare providers can identify, document and assess patients' wounds with a much higher level of precision, saving time and resources.
One of the most challenging problems in wound care is deciding the treatments. Due to the high inaccuracy of traditional wound evaluation techniques, it is extremely difficult to quantify changes in a wound's progress. In addition to the lack of an accurate metric for evaluating wounds, a tremendous amount of manual labor is also required to sift through wound data. But big data and predictive analytics provide a solution for this.
Forecasting wound closure trajectories accurately is complicated due to the incomplete information about wound dynamics. The ability to predict wound trajectories would significantly benefit care practitioners to identify high-risk wounds while also determining treatment efficacy. Here, the models based on big data and modern predictive analytical techniques can adapt to patient-specific variations and be more suited for inference in a clinical setting. The application of big data on wound trajectories can contribute to digital wound care management and see if wounds are being healed as expected. This allows the treatment strategy to be changed according to the progress in healing.
Arming clinicians with big data and an accurate predictive wound healing model would be significant in care management. This would allow timely diagnosis and reduced treatment costs.
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