What is Predictive Clinical Analysis

What will happen next to the patient? This is the question that can be answered with the help of predictive analytics. Using various means, such as AI and big data, predictive analytics tools do exactly what their name says: they determine the probability of shifts in a patient’s condition including the chance of any adverse effects.

To make accurate forecasts about a patient’s reaction to treatment or risk of developing a certain disease, various types of data are analyzed using complex algorithms.  

Here is a real-life example: researchers at Michigan State University are creating an app that can catch early signs of Alzheimer’s disease by scanning speech and vocabulary patterns.

How Predictive Analytics is Used in Home Care and Senior Living Space

Let’s see how home care providers and senior living facilities can benefit from using predictive analytics tech.

Better Quality of Personalized Care

A one-size-fits-all approach does not work well when it comes to health care. Each patient is unique and requires individual solutions.

Predictive analytics allows caregivers to provide personalized care by adding a patient’s clinical data as a variable into the algorithm. Such custom-tailored treatment is more effective and has less chance of producing adverse effects.

When using real-time data, predictive analytics tools can act as an early warning system and help caregivers act proactively, reducing the possibility of negative developments.

When combined with a client-side app, such tools can inform and educate patients, giving them advice based on the data they collect.

Time Saving and Less Strain on Staff

Current technology allows caregivers to accumulate an unprecedented amount of patients’ clinical data. In fact, it is so abundant that merely navigating through it may become a challenge.

According to research, physicians spend 62% of their time per patient reviewing electronic health records (EHRs) with clinical review being the most time-consuming part. When assisted by AI analytics tools, this process is 18% faster without sacrificing accuracy.

Such assistance allows for reducing staff workload while maintaining the highest level of care quality.

New Operational Management Approach

Predictive analytics insights can help the managers of home care providers and senior living facilities to take a new human resource approach by predicting future workload and giving recommendations on staff optimization to reach staff-to-patient ratio.

Other predictive models can be used to forecast possible future changes in patient numbers by analyzing population and demographic data, reportable diseases, and even seasonal sickness patterns.

Risks and Challenges of Predictive Clinical Analytics

Whether with the help of predictive analytics tools or without it, the final decision on diagnosis and treatment is up to actual humans. With such tools becoming more widespread, some ethical questions arise.

For instance, to what degree should physicians rely on advice provided by an algorithm – a complex one, but an algorithm, nevertheless? Will these tools be perceived as “safety nets” by some physicians and won’t they affect their decision-making process, making them take higher risks?

Privacy is another major concern. Predictive analytics tools’ effectiveness directly depends on the amount of clinical data they process. However, collecting and analyzing this data may impose security risks.

The lack of legislation regulating the way predictive analytics tools are used also adds a level of uncertainty into the mix.

However, the numerous benefits of predictive clinical analytics are undeniable, and there is no doubt that this sector will continue evolving.

Want to discuss the future of predictive clinical analytics with market leaders? Join a panel discussion at the HCT Expo in September!