Predictive analytics and Personalized Healthcare

The healthcare system is undergoing revolutionary changes with plenty of challenges to meet with the use of new and existing sources of data to deliver personalized care. Clinicians are required to not only make decisions about healthcare but incorporate volumes of health data generated and controlled by patients. Integrating the data into healthcare enables stakeholders to make better decisions, which is made possible with predictive analytics software.

The multiple benefits of predictive analytics

There are numerous benefits of implementing a predictive analytics solution, which include the ability to provide better patient care and significant reduction of costs. While the thought that healthcare could be reduced to algorithms may be intimidating, the reality is that predictive analytics is very promising with the ability to deliver accurate results. Predictive analytics is something doctors have been doing on a large scale for a long time. However, predictive analytics software it a step further and helps to better collate and measure previous data that was hard to obtain.

Combining data with existing sciences of clinical medicine enables a better understanding of the relationship between external factors and various aspects of human biology and medicine. This results in improved ability to deliver personalized care.

The role of historical data

A predictive analytics solution is the best way to allow patient care to be personalized for each individual by studying historical data. It helps physicians make better clinical decisions and avoid adverse events. These solutions like Jvion's RevEgis are designed to reduce readmission rates and help in chronic disease management and patient matching. The objective is to treat individual patient better by widening the data set.

The Role of Predictive Analytics in Hospital Acquired Infection Reduction

To avoid unnecessary costs and patient suffering, healthcare providers need to consider infection control solutions and have zero tolerance for hospital acquired conditions (HACs) that only result in patients suffering from infections that result in longer hospital stays. Predictive analytics is one of the ideal ways to help in hospital acquired infection reduction and reduce readmission rates. Infection control prevention solutions from healthcare technology provider Jvion utilize big data and deep machine algorithms to predict and prevent HACs and reduce patient suffering. 

Reduce Patient Suffering and Save Lives

An evidence based approach to infection control prevention is highly effective in reducing infection rates. Patient-centered care can be improved significantly with the use of predictive analytics so that preventative measures can be implemented. Jvion’s RevEgis is one of the solutions that can help predict disease and infection by analyzing phenotypes. The objective is to not only optimize the cost of care but reduce patient suffering and save lives. The well being of patients after they are discharged is now a key element of the Healthcare Reform Act. This is designed to prevent 30 day readmissions, which is something that hospitals are now well aware of since the Centers for Medicare and Medicaid Services (CMS) are set to reduce payments to hospitals with high readmission rates. 

Fraud, Waste & Abuse need not be a major concern with Jvion’s RevEgis

Healthcare fraud waste and abuse affects everyone either directly or indirectly where billions of dollars are lost annually. These losses in turn lead to skyrocketing healthcare costs and ever increasing insurance premiums. The sheer size of the healthcare sector and the money involved facilitates the need for a robust hospital fraud waste and abuse solution to reduce costs associated with the healthcare system.

Use an Intelligent Healthcare System

Unstructured Data use within healthcare holds the key to the development of intelligent healthcare systems. Clinical data is innately complex and 80 percent of all data remains unstructured. However, the important part is realizing value from big data. Healthcare fraud is a reality where individuals and organizations perpetrating fraud are a constantly evolving group looking to make the most of loopholes in the healthcare system. Equally important is healthcare abuse where a fraction of providers believe they can beat the system and earn profits through unwanted surgeries and exaggerated claims. Then again, waste is another major factor that indicates inefficiencies in administrative and operational levels.

  

Hospital Acquired Condition Prevention is Now Easier than Ever

Hospital acquired conditions have been a stone in the shoe of the healthcare industry. Inspite of extensive sterilization or quarantining, even a minor error can be disastrous for a patient. Considerable resources are being spent on pressure ulcer prevention, a technical name for bedsores. These resources could be optimized and can be allocated to other areas where the need is greater. Predicting hospital acquired infections is becoming more critical every day. Fortunately with RevEgis predicting hospital acquired conditions has become easier for healthcare providers.

What is RevEgis? It is a holistic software application that predicts patient conditions and possible risk factors. It is a data analytics system that incorporates deep machine learning to provide the most optimized solution for patients, as well as institutions. The software application is not a replacement formedical diagnoses but it helps healthcare providers make better clinical decisions. The resulting ability to predict hospital acquired infections helps save crucial hospital resources and lives.

re providers.

5 Ways That a Predictive Modeling Healthcare System Helps

The advancement in technology has led us to a point where the man-machine system has integrated into one seamless predictive algorithm. The ingenuity of the human mind in creating mind-boggling algorithms combined with the deep knowledge of medical science, and a yearning to create a better healthcare system gave birth to a new predictive software application. It is a software application that helpsoptimizestandards of medical management by combining healthcare benchmarks and hospital peer comparisons with the ability to develop a patient-centered approach. 

1.Preventing waste of resources by predicting underlying conditions leading to deteriorated health outcomes

2.Providing a clear picture of weak links and steps needed to improve performance

3.Improving inter-departmental collaboration and laying down organizational goals for healthcare providers

4.Providing a comprehensive and customized analysis of various demographics with goal oriented comparisons

5.Recognizing the innate factors that result in a deviation from the set standards and comprehend the effect of the new healthcare payment models

 The above factors are responsible for creating a holistic health care model focused on patientswhile providing an optimized system of management that saves valuable hospital resources and saves lives in turn.

Predictive Analytics Software Help Treat Healthcare Acquired Conditions Effectively

An algorithm that can be an all inclusive solution to the challenges in healthcare systems is surely an asset. Such a technology has been developed and is helpful in preventing complications including hospital-acquired conditions and infections contracted in a hospital setting. With new regulations in place predicting and preventing hospital-acquired conditions has become necessary for hospitals to avoid denial of complete reimbursements. Moreover, it is essential for the reputation of the hospital to achieve high levels of patient satisfaction.

Certain algorithms have been developed, that help predict hospital acquired infections before they occur by analyzing the patient phenotype and background. Pressure ulcer reduction is an important part of hospital acquired infection prediction as it is a commonly occurring condition among long-term patients. Using such predictive analytics software, pressure ulcers and other HAIs that plague the patients after discharge are reduced. Overall, the application's domain in prediction and analysis help doctors treats patients more effectively, and hospitals maintain their reputation while patients achieve better health outcomes. 

The Changing Future of the Healthcare System

The world is changing with time, and as Big Data takes its baby steps there are a few technologies that are way ahead of it. One of them is based on an evidence-based metrics healthcare system that derives its power from the genius of a medical mind and a deft programmer. It is a giant leap in the healthcare system. A healthcarepredictive analytics algorithm is the next step in achieving a risk-stratified model of care that aims at reducing the risk of infections while treating the original illness. An algorithm with the power to predict and self-correct is a break through achievement in coding as well as for the healthcare system.

It is essential to have a closed loop system in an algorithm to make it smart and unique. A healthcare predictive modeling system that works on a feedback loop can produce even better results with time as it gathers more and more data about the background of the patient. Hospitals can also benefit from new technologies including a healthcare provider fraud waste and abuse solution.