Healthcare Predictive Analytics — Saves Lives by Delivering Personalized Care
For health care, predictive analytics will enable the best decisions for care to be provided both on individual and community levels. Being an important part of data science, healthcare predictive
modeling helps determine the trends and patterns of future outcomes by processing the past data.
In fact, the healthcare industry is witnessing a great shift from traditional practices of business intelligence towards the use of healthcare software solutions. It uses predictive analytics to serve variety of purposes such as –
· Analyzing and pinpointing patients who are at a high risk of hospital readmissions or certain diseases
· Reducing the length of stay for patients (e.g. after the hip/knee replacements)
· Appropriate allocation of resources when and where they are need the most
Healthcare Predictive Modeling — The Process
While adopting predictive modeling software, the hospital workflow should be clearly set. Here is a schematic illustration of its implementation –
· The primary step involves identification of problems that need to be addressed using predictive analytics.
· The next step requires exploration the raw data from the healthcare facility. Identifying variable predictors, measured for every individual entity.
· Collection of data based on identified predictors and transforming it into distinctive models through designed algorithms.
· Validation and verification of the model thereby tweaking them for improved accuracy
· Implementation of the designed model for the formation of healthcare predictive analytics.
Predictive Solutions — Its Key Benefits
While some of the reputed healthcare organizations opt for building their individual data analytics systems suiting their needs, others prefer to collaborate with the industry leaders for well-tailored healthcare software solutions. Of course, it promises to offer numerous advantages to the entire industry such as –
· A healthcare cost reduction approach — The healthcare industry rakes huge expenditure in delivering better medical services to their patients. However, the adoption of predictive analytics techniques is a healthcare cost reduction approach that enables implementation of patient-centered models. It helps improves the delivery of care and ensuring improved outcomes and patient satisfaction.
· Improvising the management of chronic diseases — Depending on historical health records, predictive analytics is capable of detecting patients with high-risk of chronic diseases.
· Prediction of out breaking diseases –The predictive analytics solutions also allows the healthcare and public health facilities predict any outbreaks of any particular disease on a community health.