Contributing Changes to the Increasing Adoption Rates of Healthcare Data Analytics
Healthcare data analytics is a set of activities used to process data that is collected within the healthcare environment. In the United States, the healthcare data analytics industry is expected to reach a value of $31 billion by 2022, with an increasing number of hospitals and healthcare organizations leveraging big data for a variety of applications. Increasing adoption rates of healthcare data analytics is a result of three ongoing changes that are taking place in global technology:
- Data is becoming more available. For the past two decades, humans have increased the total number of data produced and stored at exponential rates and the healthcare industry is no exception. Regulations such as the electronic medical records (EMR) mandate have resulted in the widespread digitization of patient data in the past decade, and the increasing presence of connected devices and embedded computers in health care environments are also being leveraged to collect clinical patient data.
- Data storage is becoming more available. Advances in data storage technology have made it easier for more healthcare organizations to access the data storage needed to leverage healthcare data analytics at an affordable price. In the past, a hospital would have to undertake huge up-front costs to build and manage its own data center. Today, the cost per gigabyte of data storage has fallen considerably from where it was 10 or 20 years ago, and healthcare organizations can also outsource big data storage to cloud service providers who provide flexible and effectively limitless storage at an affordable price point.
- Data processing is becoming more available. Advances in computer processing power and data processing algorithms mean that computers can now process greater volumes of data in less time than ever before, generating insights and information along the way that would be impossible for a human analyst to substantiate in a reasonable period.
The increased availability of data, the ability to store large volumes of data and the ability to process large volumes of data are driving increased data collection in health care environments and enabling rapid innovation in healthcare data analytics.