“It’s important to think about healthcare being on the precipice of what I think of as an industrial revolution,” says Dr. Jim Weinstein, president and CEO of Dartmouth-Hitchcock Health System, on predictive analytics in the healthcare industry.
Revolutionising Healthcare using Big Data
The basis of most medical research and discovery has been the collection and analysis of data: who gets sick, how they get sick and why. This has been the foundation of medical research for years.
With the advent of the analytics revolution, with sensors in every smartphone and doctors able to share information across various platforms, the vast quantity and improved quality of the data available is greater than ever before. This means that the potential for scientific advances in medicine is growing exponentially.
Helping Healthcare Practitioners Diagnose
Healthcare institutions such as hospitals and smaller private practitioners, keep detailed reports of their patients, their symptoms, outcome of different tests and effect of various treatment plans. These reports and the continuous influx of new observations are ideal for predictive analytic models and the learning algorithms comprising them. The models, based on this data, are able to assign probabilities and predict the likelihood of a patient suffering from a specific illness. This aids healthcare practitioners and increases the accuracy of their diagnoses, thereby reducing the number of mistreated patients.
Optimising Treatment Plans with Analytics
This data could be further capitalised on by designing optimal treatment plans for patients. The predictive models are able to analyse how, hundreds or even thousands, of different types of patients react to similar treatment plans and based on these observations suggest a plan that is ideal for a particular patient. The suggested plan will have the highest probability of success, in the shortest period of time.
Applying Preventative Measures
Our predictive analytics team can also help the public-health sector by improving preventative measures against the development and contraction of illnesses. By analysing medical records, as well as additional information such as a person’s genome composition, we can identify people who have a high risk of developing certain illnesses. When such cases are unveiled, the patient can be notified and encouraged to make beneficial lifestyle changes. These changes could significantly mitigate contraction levels or even help the person avoid the illness entirely.
Accelerating Discoveries in Healthcare
There are numerous powerful data mining techniques, which are specifically designed to discover new correlations between numerous variables in big data. These could be deployed to analyse healthcare data and potentially reveal new relationships with serious healthcare implications, undiscovered yet, due to their unintuitive nature or previous limitations of data mining technology.