X-Med software Platform
This solution allows the centralisation of all the user's clinical information. It respects the specificities of consultation or hospitalisation episodes.
The electronic health record is an integrated and distributed system of clinical information associated with a set of applications that handle it.
The set of these applications constitute the clinical information systems and allow, for instance, to assist in the provision of health care; to aid clinical decision making; to evaluate the quality of the care provided; to aid in the management and planning of health care; aid in research; aid in medical training.
Medical Area:
- Concentrates the medical records made in the context of providing care to users;
- Access to External Prescription of Medicines;
- Definition of diary by specialty;
- Registration of diagnoses and procedures;
- Rehabilitation prescription;
- Internal prescription (of medicines, treatments and consumables);
- Internal prescription of MCDT (analyses, exams, etc.);
- Possibility of creating customised records;
- Evaluation scales.
Nursing Area:
- Definition of diary by nurse's speciality;
- Register of procedures carried out in the nursing with possible connection to the invoicing area;
- Register of vital signs (configurable);
- Registration of capillary glycaemia (configurable);
- Registration of clinical analysis results (configurable);
- Evaluation scales;
- Shift information panel;
- Work plan;
- Possibility of creating customised records;
- Wound registration.
Rehabilitation Area and Psychosocial area.
Individual Integrated Plan:
- Record of Multidisciplinary meetings;
- Identification of problems with the definition of objectives and interventions;
- Evaluation of the attainment and redefinition of objectives.
Evaluation Scales (configurable):
- Braden Scale;
- Morse Scale;
- Barthel Index;
- Katz Index;
- Lawton and Brody Scale;
- Modified Ashworth Scale;
- Functional Indecency Measure (FIM);
- Hamilton Depression Scale;
- Hamilton Anxiety Scale;
- APGAR Family;
- Gijón Scale;
- Pressure Ulcer Status Scale;
- Mini Mental State Examination (MMSE);
- Among others.
Shared information between areas:
- Clinical Episode - Reason for Admission or Consultation;
- Register of exams;
- Patient Summary - Relevant Clinical History, Pathologies, Allergies, Intolerances;
- Alert Management - Alteration of medication, occurrence register, etc...
X-Med Data Analysis
With the massive amount of data that is produced on a daily basis, it is necessary to apply practices that allow this information to be analysed in a strategic manner.
In this way, the user can optimise their access and understand the data much more quickly, without having to filter it manually.
And this intelligent analysis technology is not only limited to technology areas, but is also expanding to other niches, such as medicine.
Data Analysis is a process of reviewing information to achieve a certain goal, performing a more detailed treatment on the structure and basis of the data studied.
In this case, it is a research strategy, which aims to work with the files in an intelligent way, to understand the behaviour of this information and of the users who entered it into the system.
In a first moment, its main objective is to assist in the decision making of a certain company. However, extending its application to areas such as health, Data Analytics can be applied in medical routines to promote higher quality services.
Its elaboration can be done individually or collectively, depending on the complexity of the available data. Thus, if the project was collective, the execution of each phase can be the responsibility of a different collaborator, to optimise the process.
In this way, it is possible to appropriately mine the information, to organise it and enable its optimised analysis.
It is also common for Data Analytics to be organized in the following sequence of steps:
- Input: starts the project by establishing the requirements to collect the data;
- Preparation: establishes the insights used to consider the information, that is, metrics for comparison;
- Exploration: research and investigation phase;
- Enrichment: analysis of the collected data;
- Data Science: or data science, consists of using more advanced scientific methods to obtain information that is more difficult to extract;
- Business Intelligence: applying data in a specialized software;
- Report Generation: gathers results for conference.
- Each institution can apply Data Analytics in a way that meets its needs, with one or more phases.