Analysis of Value Dimensions in Public Satisfaction with Primary Health Care: Prospective Observational Study
| Autor: | S. D. Mazunina, S. B. Petrov, K. I. Melkonian, D. V. Veselova |
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| Jazyk: | ruština |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Кубанский научный медицинский вестник, Vol 30, Iss 2, Pp 44-53 (2023) |
| Druh dokumentu: | article |
| ISSN: | 1608-6228 2541-9544 |
| DOI: | 10.25207/1608-6228-2023-30-2-44-53 |
| Popis: | Background. Artificial neural network models can be used to analyze and predict structural components within the value dimension of the main processes in an outpatient clinic as indicators of patient satisfaction.Objective — to form and test the methodology for analyzing and predicting structural components within the value dimension of the main processes in an outpatient clinic, as indicators of patient satisfaction with availability and quality of medical care, using artificial intelligence.Methods. The results of questionnaires administered to 525 patients were used to analyze their satisfaction with GP appointments. A network ensemble consisting of radial basis network and multilayer perceptron was chosen as the basis for a neural network model. The model testing involved five outpatient clinics in Kirov. The total number of respondents comprised 217 patients. Statistical processing included data description and analysis. Qualitative attributes were represented by relative values (P, %). The statistical significance of differences in qualitative data was assessed using the Chi-square test. The correlation between the observed and predicted data was assessed by means of nonparametric Spearman correlation analysis. The value of p |
| Databáze: | Directory of Open Access Journals |
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