In the design of an information system “medicine by-design” it is necessary to widen the focus on the data by associating new dimensions.
The current clinical systems are focused on the introduction, storage and representation of the data. This is either neutral or, at most, divided into categories, e.g. diagnosis, vital parameters, medication and so on.
In order to realize new functions, in addition to the traditional one, it is necessary to take a further step forward and engage on three key aspects:
- The interpretation of data
- Its correlation with other data, even of different categories
- Data analysis.
Let’s see in detail what this methodology actually means.
In order to interpret the data, it is necessary, first of all, to know its medical meaning. Blood pressure, for example, is not just a pair of values, expressed in mmHg, but expresses the intensity of the force with which the blood pushes on the arterial walls, divided by the area of the wall. The pressure is determined by several factors, including the contraction force of the heart, systolic output, heart rate, peripheral resistance and others.
Each data, in medicine, has a precise meaning. Designing a system without knowing the meaning of the data is equivalent to creating a mere container of information, i.e. the digital transposition of the pre-printed modules that are still used in many hospitals.
The data must then be correlated with other data, not just the previous ones, as all systems available today do. It is certainly useful to see the trend of a data, but it is not enough. The age and sex of the patient, his diagnosis, his values and therapy are elements with which the data must be correlated in order to proceed to the next step: the analysis.
The interpretation of data and their correlation determine, through a process of analysis based on clinical knowledge, new information and allow the development of functions to assist the doctor in his work of diagnosis and patient care.
This approach allows you to develop functions for:
- Represent the information in multidimensional dashboards where the correlations between the data are evident
- Select or suggest actions to be taken, perhaps by narrowing (filtering) the catalogues from which to make choices
- Highlight conditions of possible criticality or risk
- Check the correct introduction of data.
Many examples can be given, among them:
- Check if a drug is “suitable” or “compatible” with the patient, depending on age, clinical condition, etc.
- Report if the patient is at risk of a complication, for example deep vein thrombosis (DVT) and suggest the necessary actions to reduce the onset
- Remember the prescription of some tests for monitoring drug therapy.
In other words, it is a matter of developing “clinical logic” to “increase” the diagnostic and therapeutic capacity of the doctor, obtaining three important results:
- Increasing the efficiency of doctors and nurses who have to dedicate less time to the use of the information system that, foreseeing what they have to do, is able to minimize the interaction with the user interface
- Increase effectiveness and clinical outcomes by increasing awareness of possible choices and the effects these may have on the patient’s prognosis
- Reduce clinical risk by avoiding preventable risks and medical errors.
It is an approach that completely overturns the principles and the way a clinical software is developed and forces everyone, users and technicians, to get out of their “comfort zone” to create a class of innovative software.
The process, complex, can of course be approached in stages, introducing some new functions, perhaps targeted for particular pathologies or care settings, so as to prove concretely what the benefits that this approach can allow.
It’s time to start developing “medicine by design” software!
2 – End
Digital-health 