The Role of Predictive Analytics in Healthcare

MiMedx group vice president Kevin Lilly has more than 15 years of experience providing technology solutions to the healthcare industry. One of the companies that he had worked in prior to MiMedx was McKesson Technology Solutions. Kevin Lilly was the vice president for sales, analytics, and capacity management at McKesson for six years, where his work surpassed projected sales figures for the company’s analytics solutions.

Healthcare providers are under pressure to improve their patient outcomes. One tool they are using to reach that goal is predictive analytics. This innovation refers to pattern identification in collated data through artificial intelligence algorithms, that enables users to forecast likely future events.

Predictive analysis supports medical professionals in making informed choices ahead of these predicted events, and allocate the necessary resources. The use of this tool can help identify high-risk patients who require early health intervention. Acting on this data by reaching out to the patient can help tackle the ailment and bring the costs of caring down by preventing early readmission. Data analytics can also help provide a quick reaction, making a vital difference in a patient's health outcome.

Predictive analysis is also useful in medical imaging to improve the diagnosis of some ailments like cancer. This technology helps improve organizational efficiency among healthcare providers. It shows areas in which funding can improve outcomes, eliminate resource wastage, and improve administrative hindrances, like patient scheduling and congested workflow processes. Thus, the significance of predictive analysis in the medical field lies in being able to ensure that healthcare services are being improved, and expenses are being kept down.