Over the past century, we have seen huge developments in healthcare practices and technologies. One of the most exciting changes that are happening now is applying data analytics in the healthcare industry. This development can potentially help save lives on a grand scale in the near future.
Maryville University’s discussion about data analytics reveals how it’s more than just numbers on a screen. The science also explores how to maintain and protect databases, visualize information for sharing and decision-making, and use existing data to predict the future. In healthcare, data analytics makes use of patient data and analyzes it to draw insights that could help prevent the spread of epidemics, reduce healthcare costs, work towards curing certain diseases, and much more.
These three steps show how data analytics, along with Electronic Health Records (EHR) systems, work to help enhance the quality and efficiency of healthcare services:
1. Have all your data in one place: The benefits of ditching paper charting in favor of EHR systems are huge, but switching to EHR isn’t merely an eco-friendly option for hospitals. It also means a boost in efficiency and profitability. When all patients’ health data is stored in a portable tablet or smartphone, it’s easier for doctors and nurses to keep track of and analyze treatments. Seattle Children’s Hospital uses this technology for its young patients. They can get health data in seconds, rather than minutes for the 350,000 patients it sees on a yearly basis. Data analytics works to provide better insights on how their patients’ treatments are similar for better decision-making in the future.
2. Be able to monitor from a distance: With EHR systems in place, doctors can make use of the way devices collect and transmit data to connect with patients outside of the hospital. Applications and programs can track and record patient vital signs and symptoms, and data analytics can comb through thousands of individual health data points to sort and prioritize this information for physicians. The frequency of physical visits to the hospital should decrease and free up time for medical practitioners.
3. Predict and diagnose early: Perhaps the most crucial contribution of data analytics is the possibility of making earlier diagnoses on a mass scale. Through the information from the EHR, analytic tools can detect warning signs and patterns, such as a patient’s family history or how frequently they visit the hospital. Recommending lifestyle changes or predicting health outcomes for individuals based on their EHR can reduce doctor and hospital visits. This could have major implications about how medicine is practiced in general—moving from a reactive practice to a more regular proactive analysis. Catching diseases before they appear will also cost less compared to diagnosing and treating them later on. This is crucial because trends in the United States have shown that we are spending more than we should and healthcare expenses are far too high.
Overall, the integration of EHR and analytics into healthcare has the potential to deliver a major shift in providing early diagnoses, as well as reducing costs. With this technology, healthcare services in the future can become more oriented toward prevention rather than the cure. Healthcare can become cheaper and more accessible as more doctors and medical practitioners continue to make sense of big data with the right tools.