Using Predictive Analysis for Better Management of Patient Emergencies

Currently, we have a wealth of data in the healthcare sector, which when collected and analysed can provide great insights and can be helpful in streamlining healthcare services. And thanks to the current technology, we have the ability to collect data, analyse in real-time and use it quickly and efficiently. Currently, a number of big players in the healthcare sector are using the concept of predictive analysis to get great results, especially when it comes to emergency medical services.

Predictive Analysis is an exact science when it comes to predicting possible future outcomes. Basically, by utilizing the already available information we will be able to predict what might happen in the future. It should be noted here that this tool is no oracle; it doesn’t tell you what exactly is going to happen. It is just a tool that predicts the most probable outcomes based on the data provided, but with an acceptable level of reliability. So, this concept can be used for risk analysis too with very near accuracy levels.

Given the application of the concept of Predictive Analysis, it can be useful in streamlining many aspects of the healthcare industry, especially that of emergency medicine. Here are some of the areas where Predictive Analysis can be used for the better management of patient emergencies.

Even today, we hear stories of how high-risk patients are being turned away from ERs. Since the basic idea behind an ER is to provide priority services in cases of emergencies, turning high-risk patients away is a huge problem. On the other hand, accepting and immediately admitting each and every patient who comes to the ER can become a concern, especially on a hectic day. Too many patients can mean problems with allocation of resources in the correct manner and a general, all over chaos.

The only solution to this problem is the correct evaluation of each patient that comes to the ER. Doctors and nurses are only human and can only do so much in this matter. But providing them with an additional advantage of Predictive Analysis can help mitigate the problem of bad judgement to a great extent. Predictive Analysis tools can take the right decisions depending on the patient’s medical history, their previous visits to the ER and the availability of similar information from other, previous patients. Using all the available data and the tools of analysis, this technology can be employed to make the critical decision of who to admit into the ER.

Staff management is another problem that all hospitals seem to have these days, and it can be controlled to a great extent by using the technology of Predictive Analysis. Though hospitals have adequate human resources, allocation of these resources can become a complicated activity. For the normal human being it is not possible to predict when there might be an emergency influx of patients and when the requirement for the staff might peak. Improper allocation of staff results in deficiencies and increased stress on the available staff at peak times and wastage of financial resources and overtime when there is a lull.

So, how is Predictive Analysis useful? Predictive Analysis can be used to accurately predict the patient flow on a day to day basis. Using past history and current data, Predictive Analysis can predict peak days and lulls on a real-time basis. For example, it can take information regarding an epidemic in the locality to predict an increase in patient influx. Or it can analyse and predict the requirement of increase staff in the trauma department on special days like the 4th of July, etc. Thus, using the available data and analysing the past trends, technology can predict staff requirements to take better care of patient emergencies.

Looking at all the capabilities and advantages that Predictive Analysis can bring to the healthcare sector, especially emergency medicine, it is obvious that it is advantageous for the patient as well as the industry itself. Basically, when it comes to the patient, the experience of availing emergency medical services can be made better as well as cost-effective. Predictive Analysis can accurately predict when there is a need for emergency medical services and when there is not. So, the patient hasn’t turned away when the need is real, thus saving their life. One the other hand, the patient isn’t forced to avail emergency services when there is no need for them, thus saving their money.