The demand for receiving more at a lower cost is a daily mantra. That goal doesn’t just affect individuals, but industries as well. The healthcare industry is certainly one that has that aim. Of course, just saying the words doesn’t make everything fall into place. Much understanding and work needs to be put into action before change occurs. This is where healthcare analytics is called upon to head up the transformation.
The data that is generated throughout medical offices, specialists and healthcare professionals is both vast in nature and deeply complex. Organizing the information is just scratching the surface; the need to discern multifaceted patterns is where the strength of knowledge and action can take place, and where analytics is housed.
However, there are steps that must be taken before analysis is implemented, simply stated: data must be collected, shared, and then analyzed. At present, many offices are collecting data electronically known as the electronic health records (EHR). The data sharing is happening thanks to the health information exchange (HIE).
Because these terms may be new to you, let’s go into a little more in depth. An EHR is a patient’s file that contains medical history, but isn’t in a traditional paper format, and is instead stored as a computer file. This enables the healthcare provider to share the information with other providers, which eliminates human or timely errors that might otherwise occur from transfers of hard copies.
HIE is the secure electronic exchange of a patient’s EHR between healthcare providers as a means of improving the, “speed, quality, safety and cost of patient care.” When a patient or provider isn’t called upon to transfer a medical file in person, by fax or mail, yet is accessible to appropriate entities, privacy can be better maintained, and there is a lesser likelihood of unintentional mistakes. The exchange happens in two ways: the first is a healthcare professional forwarding specific information on a patient to another provider. The second way is a healthcare professional being able to look up the information on a patient, such as in an emergency room visit, and know fundamental information in order to treat that patient most effectively.
Once data is collected and shared, the next step is to analyze it, which is where the true value of information is realized. But this doesn’t come without a combined support found with business intelligence (BI) and data warehousing. Technically speaking, many consider analytics to be a section within BI, yet analytics is such a significant subset, that it is partitioned separately from many of the other business requirements. Analytics is described as the, “data, statistical, and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.”
Real life application of analytics has far reaching capabilities. Looking at an individual patient who goes into a hospital for emergency care, he/she would no longer be a blank page to all the attending professionals, but with the aid of the HIE, he/she would receive much more accurate and timely treatment.
As unique as we all like to believe we are, humans are creatures of patterns. Patterns that are created by how our bodies are built; how they are injured and heal; how our minds process stress and pain; and how to predict the future. All the data that has been collected is analyzed to find the patterns that may not be plausible for a human to identify, but these facts and figures point out when someone fits into parameters of previous patients that showed related symptoms. Because it is impossible for doctors to memorize every possible condition known, having real-time analytic answers provided will ensure better care. This method of managing patient treatment can eliminate the need for some testing or medicines in order to discover the root of the issue.
Also, by reducing unnecessary costs on procedures, the overall cost of healthcare can be greatly reduced. Obviously, there will be basic tests that should always be conducted, but by the process of elimination, a health professional may not be required to conduct avoidable services if a more precise and predictive hypothesis is presented to them. Essentially, it is taking some of the guessing out of the game.
Analytics can also be used to understand what is going on within a community. Known as population health management, it is the ability to predict health crises and other visits or hospitalizations. This is accomplished by way of care teams that provide improved access to care, enable patients to better self-manage their health and reduce the frequency of emergency room visits. This would then cut costs to both patient and professional, and not divert necessary personnel to the handling of more trivial matters.
Overall, being able to predict the future of where and when staff should be available, how to best provide care for all patients and to do so in the safest and most timely manners, and meet the basic standard of getting more for less. This applies to people no matter whether they are sitting in a doctor’s office, a specialist’s office, or a hospital.