4 Ways Predictive Analytics Will Improve Healthcare
There are so many wonderful ways predictive analytics will improve healthcare. Here are some of the potential benefits to consider.
Medical care has relied on the education and expertise of doctors. Human error is common and 250,000 people per year die from medical errors. As the third-leading cause of death in the United States, limiting errors is a key focus in the healthcare industry.
Big data and predictive analytics will lead to healthcare improvement.
But how? Health IT Analytics previously published an excellent paper on some of the best use cases of predictive analytics in healthcare. We reviewed other papers on the topic and condensed the best benefits into this article.
1. Diagnoses Accuracy Will Improve
Diagnoses accuracy will improve, and this will occur with the help of predictive algorithms. Surveys will be incorporated, which will ask the person that enters the emergency room with chest pain an array of questions.
Algorithms could, potentially, use this information to determine if the patient should be sent home or if the patient is having a heart attack.
Patients will still have insight from doctors who will use the information to assist in a diagnosis. The predictive analytics are not designed to replace a doctor’s advice.
2. Early Diagnoses and Treatment Options
Big data will lead to early diagnoses, especially in deadly forms of cancer and disease. Annually, mesothelioma affects 2,000 to 3,000 people, but there’s a latency period that’s rarely less than 15 years and could be as long as 70 years.
Predictive analysis will allow for doctors to put all of a person’s history into an algorithm to better determine the patient’s risk of certain diseases.
And when a disease is found early on, treatment options are expanded. There are a variety of treatment options often available when a person is in good health. If doctors can predict a patient’s risk of cancer or certain illnesses, they can offer preventative care which may be able to slow the progression of the disease.
Babylon Health already has raised $60 million to create a chatbot that will use an AI chatbot to help with patient diagnoses.
3. Improve Patient Outcomes
One study suggests that patient outcomes will improve by 30% to 40%, with the cost of treatment will be reduced by 50%. Medical imaging diagnosis will improve with an enhancement in care delivery, too. The introduction of predictive analytics will allow patients to live longer and have a better medical outlook as a result.
Consumers will work with physicians in a collaborative manner to provide better overall health histories.
Doctors will be able to create models that help predict health risks using genome analysis and family history to help.
4. Changes for Hospitals and Insurance Providers
Hospitals and insurance providers will also see changes – initially bad changes. Through predictive analysis, patients will be able to seek diagnoses without going to the hospital. Wearables may be able to predict health issues that a person is likely to face.
Revenues will initially be lost by hospitals, insurance companies and pharmacies that have fewer patients and errors sending patients to facilities.
Hospitals and insurance companies will need to adapt to these changes or face losing profit and revenue in the process. Government funding may also increase in an effort to increase innovation in the market.
Predictive analytics has the potential to help people live longer with better treatment options and predictive preventative care.
Predictive Analytics is the Key Solution to Healthcare Challenges
Many healthcare challenges are still plaguing patients and healthcare providers around the United States. The good news is that new advances in predictive analytics are making it easier for healthcare providers to administer excellent care. Big data solutions will help healthcare providers lower healthcare costs and give patients excellent service that they expect and deserve.