May 27, 2022
7 minutes read
Predictive analytics can seriously change the medical industry shortly. Based on the use of big data, this technology will help, for example, prevent the occurrence of chronic diseases in patients and correctly allocate doctors’ resources. For the industry, the load can be reduced, and, in general, its work can be made more predictable.
Predictive analytics in general allows company management to make more accurate and correct decisions and reduce risks based on predictable data.
At the same time, the predicted estimate does not indicate the future for sure but only shows the probabilities of the occurrence of certain events. Still, forecasting accuracy can be improved by using machine learning and enriching the accumulated data with additional data, such as weather, seasonality, and so on, depending on the analytics object.
In healthcare, patient data analysis and risk assessment, image analysis, and diagnostics are the areas of most significant interest. For example, predictive analysis in healthcare can help prevent chronic diseases based on data from medical records and other indicators.
According to the MIT Technology Review, 93% of healthcare organizations name artificial intelligence and predictive analysis as one of the most critical development priorities, and 78% of healthcare organizations in the world are already implementing or planning to implement such solutions.
Predictive (or forecasting) analytics, as it comes out of its name, predicts unknown events in the future, answering the question “What can happen?” based on the analysis of accumulated information. Many methods are used here: mathematical statistics, modeling, machine learning, and other areas of data science, as well as data mining.
For example, predictive analytics of current and past performance of production equipment will determine in advance the time of its preventive maintenance to avoid the breakdown of expensive equipment.
In medicine, predictive analytics in healthcare plays a significant role. It can make a diagnosis based on the symptoms of the disease, identify factors that provoke the disease, determine the propensity for the condition in the future, form recommendations, and prescribe medicines for the treatment and prevention of diseases. However, in this case, the incorrect configuration of the machine learning module can lead to tragic consequences.
The coronavirus pandemic has given a massive impetus to the development of medical technology. This area was previously considered promising, but now its relevance has become apparent to the whole world. Health care has to adapt to the situation and overcome its rigidity. Therefore, in the next few years, we should expect explosive growth in the MedTech market. The possibility of remote sale of medicines has already appeared, and some restrictions on telemedicine have been lifted. Predictive analytics in healthcare in the fight against the epidemic plays an important role: it helps analyze data and develop better treatment regimens.
It is unlikely that artificial intelligence will replace the doctor in the foreseeable future. Still, the fact that it will give a considerable impetus to the development of medicine is already apparent. Today, it is already expanding the capabilities of geneticists, developers of medical equipment, and drugs.
Today we have unique, previously inaccessible tools and data. We can digitize and quantify virtually any aspect of the human body.
By analogy with Google Maps, which provides a satellite view of the area, viewing traffic jams and virtual walks through the city’s streets, today predictive analytics in healthcare can create a “medical map” of the human body. It will contain information about its external features, anatomical structure (these data is obtained by scanning), physiological processes (sensors tell us about them), DNA, RNA, and biochemical indicators.
We can quantify the environment. Previously, this was basically impossible, but today this information is relatively easy to obtain. All this provides excellent value for predictive analytics in medicine, as it can significantly improve healthcare quality in the foreseeable future.
In many countries, predictive analytics in medicine today already solves the problems of receiving and distributing calls, tracking the location of ambulance teams and their condition, gives recommendations on the shortest path to patient addresses. It also takes on the tasks of supporting decision-making during hospitalization, statistical processing of information, and conformity assessment standards of medical care to assess the effectiveness of the entire service in the region.
Specialized applications also keep records of medicines and the cost of gasoline for ambulances. They calculate the cost of air ambulance flights and provide information support for the work of medical teams.
Here are the main benefits that are already available today in the work of ambulance services using predictive analytics in healthcare:
Thus, in specialized applications, in a few clicks, you can receive information with a call forecast by the hour, the required number of dispatchers, and a heat map of call distribution. This solution will reduce the processing time of all incoming calls.
Healthcare companies are beginning to use the opportunities provided by predictive analytics in healthcare actively. Here are the benefits they can get in the near future.
Cloud platforms are starting to emerge for processing big data from the analysis of patients’ clinical, social, and behavioral characteristics. Over time, a common platform will bring such data together and be able to share it with all participants in the system: hospitals and healthcare providers. One company cites the following benefits of using predictive analytics in healthcare:
Equally important is the use of predictive analytics in processing prescriptions for home-delivered and retail pharmacies. Companies will use powerful analytics tools to process big data. They analyze information about individual patients so effectively that they will soon be able to notify medical staff of severe side effects of a drug long before it is even prescribed to the patient.
This will lead to significant positive changes in the health of people:
As we can see, predictive analytics can really change healthcare for the better very soon. It is a powerful tool that we have yet to learn how to use effectively. For it to bring maximum benefit, we recommend contacting professionals who have sufficient experience and expertise in this area. To learn more about our team and the projects we have implemented in the field of predictive medical analytics, don’t hesitate to get in touch with us. We will gladly answer all your questions.
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