Multi-dimensional health data
Decision-making in the field of medicine focuses on the best possible management of the patient. Traditionally decisions are based on experts’ knowledge, therapeutic possibilities, professional standards, or patients’ requests. Now that we are in the midst of digital transformation, this is changing. Achieving healthcare goals increasingly depends on using intelligent medical data. In a digital healthcare environment, the decision-making depends on the intelligent use of medical data. Of course, integrated data can serve as a source of valuable information increasing the intensity of the decision-making process. In the course of clinical decision-making, physicians may encounter various difficulties that may result in poor decisions. Difficulty depends on the availability of data or its volume when important information may be omitted or ignored. This results in inefficient and costly work, as well as compromised clinical outcomes. It should be noted, however, that social interactions play a key role, and therefore, leaving all decisions and actions to artificial intelligence would probably not be the best idea. Nevertheless, the ever-growing, massive amount of health data, which comes from a variety of sources, including electronic medical records and image databases, is beginning to play a prominent role during patient-centered decision-making.
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Does decision-making require support?
The healthcare sector is under constant pressure to reduce costs. This may be very difficult without any support. Digital technologies can make a necessary difference to improve the quality and speed of decisions to a great extent. Now that technological solutions appear more and more frequently and permanently accompany us in our everyday life i.e mobile devices, connected sensors, or digital applications, it is only logical to take advantage of this data. However, it is important to remember that the use of such a solution is not that simple as it may seem. Decisions can sometimes turn out to be inappropriate or ill-suited. That can be the outcome of unsuitable data capacity or a lack of proper organizational structure. Therefore, a digital platform where the data is prepared in a user-friendly way is needed.
Final thoughts
The importance of analytics now and in the future is enormous. We now have countless amounts of both operational and clinical data. This means that we can develop, for example, actionable clinical intelligence. Why is this development of analytics in healthcare so rapid? The reason for this is an increasing amount of diverse and complex data that requires analytics solutions. Studies show that big data analytics significantly impact health outcomes, reduce hospital readmissions and improve financial reporting. An increasing number of sources including IoT devices, electronic health records, social media make it possible to identify patterns directly from the information. This will result in predicting, inferring, and planning care strategies that would not otherwise be possible.
