METHODS OF SUPPORTING THE DECISION-MAKING ON THE POSSIBILITY OF PROVIDING GENERAL MEDICAL, THERAPEUTIC AND DENTAL SERVICES ON THE BASIS OF CIVIL LAW

The article proposes a method for semantic analysis (parsing) of natural language general contracts for the provision of medical services and derivative contracts – contracts for the provision of therapeutic services and contracts for the provision of dental services – which forms the input data for the method of decision support for the provision of general medical services on the basis of civil law, for the method of decision support for the provision of therapeutic services on the basis of civil law, and also for the method of decision support for the provision of dental services on the basis of civil law. The developed method of semantic analysis (parsing) of natural language contracts differs from the known ones in that it is based on the requirements of the current civil law regarding medical decision-making. Since in order to determine the possibility/impossibility of making a medical decision, it is only necessary to know whether each essential condition is present or absent in the contract, the method of contract parsing is simple and straightforward. The simplicity of this method ensures high speed and low cost of parsing natural language contracts. The article develops methods for supporting decision-making on the possibility of providing medical services, therapeutic services and dental services on the basis of civil law, which reflect the peculiarities of making a decision on the provision or non-provision of certain medical services based on compliance with the requirements of civil law to such services and to the execution of a civil law contract for the provision of such services, ensures adaptation to the specifics of the subject area, and allows preventing negative consequences for the clinic and its patients (for example, prevent the impossibility of bringing the guilty party to justice), and is the theoretical basis for the development of information technology to support medical decision-making based on civil law.