The world of analytics and big data is fast becoming one of the most important in IT. The increasing quantity of data available at our fingertips is completely transforming various industries, healthcare included. But how exactly does advanced analytics affect healthcare?
The Internet of Things, or IoT for short, has been the word on everybody’s lips in the last few years and we’re seeing more example of its application this year. The Internet of Things refers to the increasingly large number of internet enabled interconnected devices that range from everything from smart appliances that gather data about your habits to provide a personalized service to portable sensors that can track your vital signals and transfer them to someone with a online masters in health administration for evaluation. The advent of wearable technology will completely transform the way data is used by health professionals and online MHA degrees are already integrating them as part of their curricula.
One of the biggest reasons for the recent hike in healthcare costs can be directly correlated to abuse, fraud, and waste. More abundant and precise data will allow institutions to trim the fat, nip irregularities in the bud as soon as they’re noticed, and reduce the expansion of funds where it is not needed.
For instance, healthcare facilities will be able to detect anomalies such as overutilization of hospital resources over a short period of time, multiple prescriptions filled at the same time, and various doctors or patients receiving the same treatments from different institutions simultaneously.
Predictive analysis will allow healthcare facilities to compare data more efficiently and make corrections based on observations. This can only be done through the widespread adoption of electronic health records. The recent adoption of EHR’s by a larger number of institutions can be directly attributed to the 30 billion dollar stimulus package provided by the HITECH Act. The Act had a goal to give clinicians incentives to use the system.
Facilities are using comparative data from EHR’s to perform early diagnosis among other things. It can also be used to reduce mortality rates for diseases such as congestive heart failure. In the case of machine learning, a computer can analyze many more factors than a clinician can during examination and can look at predictive factors to better assess if a person might be afflicted with the disease or not. And since congestive heart disease mortality rates drop significantly when diagnosed earlier, the total number of people succumbing to the disease is expected to drop significantly in the next coming years.
The advent of Big Data is changing our world in more ways than one and there are few areas where this is truer than healthcare. Big data allows us to reduce administrative costs, fraud, and errors. Wearable technology allows clinicians to access vital data at all times. Big data also allows doctors to diagnose patients earlier and more efficiently, dropping mortality rates and providing more personalized service and treatment.