Analytics is an important tool for all businesses in industries including the healthcare industry. Analytics is the discovery, interpretation, and communication of meaningful patterns in data. These patterns once recognized, helps in both large scale and small scale day to day decision making. Analytics is especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance.
Organizations apply analytics to business data to describe, predict, and improve business performance and in healthcare analytics is applied to track, predict, and manage data leading to better patient care.
There are sub areas in analytics and they are: predictive analytics, prescriptive analytics, enterprise decision management, descriptive analytics, cognitive analytics, retail analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix modeling, web analytics, call analytics, speech analytics, sales force sizing and optimization, price and promotion modeling, predictive science, credit risk analysis, and fraud analytics.
In recent years, Healthcare Analytics has been seen as the next big invention and the advancement that will take the healthcare industry to the next level. However, as with every major step done on a large scale, there have been some setbacks. Many systems have been attempting to implement healthcare analytics in a haphazard and inferior way. For example, many vendors have been selling short-term point solutions which address just a narrow set of needs and do not establish a fundamental approach to analytics that will be sustainable and thrive as more and bigger data is being analyzed.
Healthcare Analytics and Process Improvement
Process improvement is an ongoing practice in the healthcare industry that continues to garner attention and the use of healthcare analytics in process improvement cannot be overemphasized. Process Improvement in Healthcare can result in increased patient satisfaction, more efficient care, better population health, development of the skill of employees in all levels of a healthcare organization, reduced cost of care and an all-around increase in productivity. In other words, Process Improvement is a proactive well thought our task of identifying, analyzing and improving upon existing business process within an organization for optimization and to meet new standards of quality and quotas. What better way to identify these patterns than with healthcare analytics? In using healthcare analytics for process improvement, there are different approaches to be considered but it often involves a systematic approach which follows a specific methodology. Many industries and organizations devote a huge chunk of their strategic plan to process improvement. Some examples are benchmarking or lean manufacturing, each of which focuses on different areas of improvement and uses different methods to achieve the best results in the manufacturing industry. Processes can either be modified or complemented with subprocesses or even eliminated for the ultimate goal of improvement.
Healthcare Analytics and Data Mining
Healthcare analytics helps in simplifying and fine-tuning the process of data mining. Data mining is very important in the healthcare industry as it enables health systems to systematically use data and analytics to identify inefficiencies and best practices that improve care and reduce cost. So data mining and healthcare analytics work hand in hand. Some medical and research experts in the healthcare industry believe the opportunities to improve care and reduce costs concurrently could apply to as much as 30% of overall healthcare spending. This could be a win/win overall for the entire industry. However, due to the complexity of healthcare and a slower rate of technology adoption, the healthcare industry lags behind other industries in implementing effective data mining and analytic strategies. In the healthcare industry, data mining has for the most part, been just an academic exercise with only a few pragmatic and real-life success stories, however, with the proper use of analytics, this can be improved upon.
These points above go to show how important healthcare analytics is for the doctors, clinicians, healthcare researchers and the industry as a whole.