Scenario Modeling in Health System Management Perm Region (Part 2)
In continuation of the article, the authors of the study devoted to the problems of scenario modeling and solving specific problems of management and development of the health care system of the Perm Territory, built the author’s dynamic multivariate model, which was based on an authoritative approa...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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North-West institute of management of the Russian Presidential Academy of National Economy and Public Administration
2021-05-01
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| Series: | Управленческое консультирование |
| Subjects: | |
| Online Access: | https://www.acjournal.ru/jour/article/view/1668 |
| _version_ | 1797290563444146176 |
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| author | A. N. Tsatsulin B. A. Tsatsulin |
| author_facet | A. N. Tsatsulin B. A. Tsatsulin |
| author_sort | A. N. Tsatsulin |
| collection | DOAJ |
| description | In continuation of the article, the authors of the study devoted to the problems of scenario modeling and solving specific problems of management and development of the health care system of the Perm Territory, built the author’s dynamic multivariate model, which was based on an authoritative approach and consists of a set of five structural simultaneous equations. As a result, each equation of the system is a linear form of recursive regression, where the independent variable as a factor-factor taken into account in one equation becomes a depend- ent variable as an effective factor-factor. In order to eliminate the phenomenon of autocor- relation of residual values, the method of time lagging was used. To estimate the parameters of the reduced form of structural simultaneous equations, the two-step least squares method was used as a special case of the maximum likelihood method. The obtained parameter esti- mates on the whole turned out to be effective with moderate consistency and satisfactory bias. The constructed model made it possible to carry out a short-term forecast of the most important target socio-economic indicator of the success of healthcare development in the region until 2023. The authors considered the national goal as such a priority indicator — the expected (future) life expectancy of the population of the study area. At the end of the article, conclusions were drawn and the prospects for further scientific research of the authors were outlined. |
| first_indexed | 2024-03-07T19:24:15Z |
| format | Article |
| id | doaj.art-b91ba18a01f24906b724f23b22979dc5 |
| institution | Directory Open Access Journal |
| issn | 1726-1139 1816-8590 |
| language | English |
| last_indexed | 2024-03-07T19:24:15Z |
| publishDate | 2021-05-01 |
| publisher | North-West institute of management of the Russian Presidential Academy of National Economy and Public Administration |
| record_format | Article |
| series | Управленческое консультирование |
| spelling | doaj.art-b91ba18a01f24906b724f23b22979dc52024-02-29T09:36:17ZengNorth-West institute of management of the Russian Presidential Academy of National Economy and Public AdministrationУправленческое консультирование1726-11391816-85902021-05-01039810910.22394/1726-1139-2021-3-98-1091439Scenario Modeling in Health System Management Perm Region (Part 2)A. N. Tsatsulin0B. A. Tsatsulin1North-West Institute of Management of RANEPABaltic Academy of Tourism and EntrepreneurshipIn continuation of the article, the authors of the study devoted to the problems of scenario modeling and solving specific problems of management and development of the health care system of the Perm Territory, built the author’s dynamic multivariate model, which was based on an authoritative approach and consists of a set of five structural simultaneous equations. As a result, each equation of the system is a linear form of recursive regression, where the independent variable as a factor-factor taken into account in one equation becomes a depend- ent variable as an effective factor-factor. In order to eliminate the phenomenon of autocor- relation of residual values, the method of time lagging was used. To estimate the parameters of the reduced form of structural simultaneous equations, the two-step least squares method was used as a special case of the maximum likelihood method. The obtained parameter esti- mates on the whole turned out to be effective with moderate consistency and satisfactory bias. The constructed model made it possible to carry out a short-term forecast of the most important target socio-economic indicator of the success of healthcare development in the region until 2023. The authors considered the national goal as such a priority indicator — the expected (future) life expectancy of the population of the study area. At the end of the article, conclusions were drawn and the prospects for further scientific research of the authors were outlined.https://www.acjournal.ru/jour/article/view/1668management decisionforecastplanscenarioriskthreatprobabilitynational economyhealth care systemforthcoming (expected) life expectancyeconometric modelstatistical estimationrandom component |
| spellingShingle | A. N. Tsatsulin B. A. Tsatsulin Scenario Modeling in Health System Management Perm Region (Part 2) Управленческое консультирование management decision forecast plan scenario risk threat probability national economy health care system forthcoming (expected) life expectancy econometric model statistical estimation random component |
| title | Scenario Modeling in Health System Management Perm Region (Part 2) |
| title_full | Scenario Modeling in Health System Management Perm Region (Part 2) |
| title_fullStr | Scenario Modeling in Health System Management Perm Region (Part 2) |
| title_full_unstemmed | Scenario Modeling in Health System Management Perm Region (Part 2) |
| title_short | Scenario Modeling in Health System Management Perm Region (Part 2) |
| title_sort | scenario modeling in health system management perm region part 2 |
| topic | management decision forecast plan scenario risk threat probability national economy health care system forthcoming (expected) life expectancy econometric model statistical estimation random component |
| url | https://www.acjournal.ru/jour/article/view/1668 |
| work_keys_str_mv | AT antsatsulin scenariomodelinginhealthsystemmanagementpermregionpart2 AT batsatsulin scenariomodelinginhealthsystemmanagementpermregionpart2 |