Today, information has become an important factor in the development of companies. It is no longer essential only to have capital to invest, but also to have a real and essential knowledge of the context in which they are developed, in order to be able to foresee and generate the best action strategies that allow the company to grow and maintain itself in a sustainable way.
Health sector companies, as well as many other types of organizations, have also gradually adapted to information systems and technologies, which allow them to grow and above all, provide better and more varied services. It is a fact that decision-making in this as in many sectors of the industry, suddenly become complex, and very often exceed the cognitive capacities of any individual, due to the large number of variables involved and their subtle interdependencies.
It is also known that human intuitive judgment and decision making is not always optimal, as it is affected by complexity and stress. Disciplines such as statistics, economics, and operations research have developed various methods for the rational choice of solutions. In our days, these methods have been enhanced with the contribution of computer science, psychology and artificial intelligence; all this encompassed in a set of software tools that we now know as Decision Support Information Systems (DSS for its acronym in English). These new information tools, increasingly integrated, require a specific qualification from professionals, whatever their level of responsibility. Information,As a basic element in any decision-making, it is not the exclusive property of managers, just like the task of designing, implementing, using and exploiting systems, it is not that of computer scientists. The latter gives true value to these systems.
A DSS is then an interactive computer system that helps users to judge and decide on activities, since it provides different sources of information, intelligent access to relevant knowledge, helps in the decision process or simply provides a heuristic approach to problems. formally intractable. The appropriate application of decision support tools increases productivity, efficiency, effectiveness and competitiveness; and brings as a consequence, the assurance of planning, organization and investment. With a DSS, a desired output can be modified and then the “critical success factors” that allow reaching that goal can be adjusted (“goal seek” sensitivity analysis). In the same way, the reverse process can also be done:modify some factors and see if the desired output falls within the range that can be assimilated by the company (“what if” sensitivity analysis).
Seeing it this way, a DSS is an important information technology for the manager, which can be used to provide timely data and analysis to support their decisions, based not on simple judgment or intuition, but on information generated through deductive methods and analytical.
In the health sector, a DSS allows knowing the movement of admitted patients, classifies them by different variables, can use a disease encoder (such as the WHO-world health organization), etc. And based on the above information, a hospital director can better plan her resources and establish strategies that keep the institution "competitive". But not only that, it can also be fed with biomedical signals directly (from the office) or remotely (from other medical institutions or from the patients' homes) and, entering databases of expert systems that can analyze and compare, show if a patient requires hospitalization, special treatment or complementary tests.
The integration of medical sciences with the development of telecommunications and informatics and their application in the different activities of the health sector, makes it possible to conceptualize the term of:
Telemedicine:
Such as the distribution of health services, in which distance is a critical factor, where health professionals use information and communications technology to exchange valid information for the diagnosis, treatment and prevention of diseases or damage, research and evaluation; and for the continuing education of public health providers, all in the interest of developing the health of the individual and their community. WHO 1998.
In this document, we show some examples and areas in which decision support systems have been applied in telemedicine.
Some specific cases in which a DSS can be used are presented by Julián Maya Londoño, in one of them, there is an automated system for calculating the severity index, based on the deviations of key physiological variables of the patient. This system is used to predict the risk of death and stratify risk groups. Its name is MPM Mortality Probability. Evaluates the patient at 0, 24, 48 and 72 hours or when sepsis occurs
Other cases
TISS: Therapeutic Intervention Scoring System It is an automated system for assessing the patient based on the therapeutic interventions that are applied, with the aim of assessing his condition and optimally distributing the human resources dedicated to his care.
ASTHMA: Treatment of Asthma and Chronic Obstructive Pulmonary Disease. (COPD). It provides complete treatment that includes, among others, drug doses, volume of fluid to be administered and specific therapeutic measures for asthmatic or COPD patients.
The previous cases give a great idea of what can be achieved in Telemedicine, having a good information system type DSS and the appropriate transducers, both in the capture of information and in the reporting of results.
A DSS in collaboration between companies and private entities
There are systems such as the one implemented by "ITC" (University Institute of knowledge technology), designed within a framework of scientific and technological independence; offers private companies a collaboration offer without prior conditions and open equally to all companies interested in commercially exploiting this Interdisciplinary technology.
The Complutense University has research teams, at the forefront in their own disciplines, which within the framework of the Institute collaborate with each other, and with researchers from other private and public centers. This multidisciplinary collaboration is making technologically cutting-edge projects viable, which require a high degree of specialization in scientific disciplines that until now have been separated and dispersed by the different university departments.
It is a priority objective to actively promote the projection of scientific and technological advances on economic activity; seek the approach of the university structure to the demands of our society.
Among the disciplines from which information is shared are:
- artificial and human vision neural networks multisensory information integration natural language processing knowledge representation reasoning and inference models and mechanisms teaching and learning robotics knowledge networks image treatment data treatment statistical analysis Harkov field random models
Observing in detail the case of ITC, it raises both information systems and decision support as strategic alliances that allow us to be at the forefront and above all informed. These are 2 essential situations in the management of companies.
In another case, the Cuban Ministry of Health operates a telemedicine system with which it intends:
- Create a National Telediagnostic Network that allows remote diagnosis, through the transmission of images between different units of the same province, from one province to another and to reference centers in the country Contribute to the organization of reference and diagnostic centers as part of the national telemedicine network that can provide value-added telediagnosis services abroad Create databases of images and study of cases of interest in image and diagnosis files in the reference center for consultation of specialists and future research and publication of catalogs and other publications.
In this case, as in most of those involved in telemedicine, the images and information in general are contrasted with databases that contain an entire classification and definition of conditions; in an effort for the explicit administration of knowledge and the establishment of expert systems based on it.
One last case to be mentioned in this document is that of the "UP", which is a pocket laptop designed to:
- i) manage data collection functioning as an «electronic patient card»; ii) support basic monitoring data analysis procedures (data review, statistics, etc.) as tools to help decision-making in the daily adjustment of the therapy; and iii) access to telemedicine functions, such as sending data and messaging with the ETM. The data collection procedures refer to the following components:
- blood glucose (value and time of the measurement); This data can be registered via keyboard or directly from a commercial glucose meter; insulin (dose and measurement time); diet (type of meals, amount of calories, time of intake); physical activity (level and duration); and other events such as ketonuria, fever medication, etc.
What is shown in this case, they mention something that is a generalized trend in telemedicine systems, and that they refer to equipment that transmits data that at the same time function as monitors of vital functions in organisms and that when being well synchronized and using the appropriate software, they are able to detect "risk" situations such as possible heart attacks, with enough anticipation to actually "help" the patient.
Conclusion:
Decision support systems have come to revolutionize the way companies can capture, analyze and display the information they already have. Of course, the human point of view will never be omitted, because thanks to it the parameters and the extent to which they should be compared can be specified; But this will always be a solution to handling so much information and the different ways it is related. In the medical sector of our country, there is a higher incidence of the use of information systems to support areas such as: electronic health record and health information systems, doctor's office, home and community health care systems, telemedicine, bioinformatics and tele monitoring.
Bibliography:
InfoMed; 1999-2000, "Telematic Health Network in Cuba".
Maya Londoño, Julián; 2002 September; Information Systems to aid in Decision Making (DSS); I Ibero-American Conference on Telemedicine and Medical Informatics, Cartagena de Indias;
Jáñez Escalada Luis, Ruiz Gallego-Largo Trinidad, Serradilla Francisco, Rubio de Lemus María de Jesús; 2002; University Institute of Knowledge Technology. Complutense University of Madrid;
Pérez Me Hernando, Gómez Aguilera EJ, Del Pozo Guerrero F; 1977; DIABTel: Telemedicine service for monitoring diabetic patients;
Notimex; 04 February 2004; E-Mexico National System
