A prediction model of patient satisfaction: policy evaluation and sensitivity analysis
Abstract China’s healthcare system has been challenged by patient dissatisfaction with primary care and an increased tendency toward visiting high-level general hospitals, which undermine the vision of a hierarchical diagnosis and treatment system. Using the game theory, we built a model that incorp...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Wang, Zi Yang [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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| Übergeordnetes Werk: |
Enthalten in: International journal of flexible manufacturing systems - [S.l.] : Proquest, 1988, 35(2022), 2 vom: 02. Juni, Seite 455-486 |
|---|---|
| Übergeordnetes Werk: |
volume:35 ; year:2022 ; number:2 ; day:02 ; month:06 ; pages:455-486 |
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| DOI / URN: |
10.1007/s10696-022-09448-9 |
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10.1007/s10696-022-09448-9 doi (DE-627)SPR051786338 (SPR)s10696-022-09448-9-e DE-627 ger DE-627 rakwb eng Wang, Zi Yang verfasserin aut A prediction model of patient satisfaction: policy evaluation and sensitivity analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract China’s healthcare system has been challenged by patient dissatisfaction with primary care and an increased tendency toward visiting high-level general hospitals, which undermine the vision of a hierarchical diagnosis and treatment system. Using the game theory, we built a model that incorporated patients’ preferences and use of healthcare facilities to predict the utilization of primary care at the population level. We modeled patient behavior as an incomplete information game, whose equilibrium represents patient choice. A discrete choice model was built to describe patient satisfaction to compare the expected and actual utility. We proposed the quick fictitious play algorithm for the game model that could improve computation efficiency, using survey data from Jilin Province in the year of 2008 and 2013 in estimation, and data from 2018 to test the model’s prediction accuracy, with a prediction error of approximately 5%. We subsequently used the prediction model to simulate various scenarios, to shed light on policy recommendations, to make a theoretical contribution that estimates patient utility under ordered multi-classification choice sets, and provided policy recommendations for proceeding toward a hierarchical diagnosis and treatment system. Hierarchical diagnosis and treatment (dpeaa)DE-He213 Patient satisfaction (dpeaa)DE-He213 Patient choice model (dpeaa)DE-He213 Patient utility (dpeaa)DE-He213 Song, Jie (orcid)0000-0003-2592-8238 aut Feng, Xing Lin aut Enthalten in International journal of flexible manufacturing systems [S.l.] : Proquest, 1988 35(2022), 2 vom: 02. Juni, Seite 455-486 (DE-627)27118101X (DE-600)1479530-9 1572-9370 nnns volume:35 year:2022 number:2 day:02 month:06 pages:455-486 https://dx.doi.org/10.1007/s10696-022-09448-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2009 GBV_ILN_2027 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4126 AR 35 2022 2 02 06 455-486 |
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10.1007/s10696-022-09448-9 doi (DE-627)SPR051786338 (SPR)s10696-022-09448-9-e DE-627 ger DE-627 rakwb eng Wang, Zi Yang verfasserin aut A prediction model of patient satisfaction: policy evaluation and sensitivity analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract China’s healthcare system has been challenged by patient dissatisfaction with primary care and an increased tendency toward visiting high-level general hospitals, which undermine the vision of a hierarchical diagnosis and treatment system. Using the game theory, we built a model that incorporated patients’ preferences and use of healthcare facilities to predict the utilization of primary care at the population level. We modeled patient behavior as an incomplete information game, whose equilibrium represents patient choice. A discrete choice model was built to describe patient satisfaction to compare the expected and actual utility. We proposed the quick fictitious play algorithm for the game model that could improve computation efficiency, using survey data from Jilin Province in the year of 2008 and 2013 in estimation, and data from 2018 to test the model’s prediction accuracy, with a prediction error of approximately 5%. We subsequently used the prediction model to simulate various scenarios, to shed light on policy recommendations, to make a theoretical contribution that estimates patient utility under ordered multi-classification choice sets, and provided policy recommendations for proceeding toward a hierarchical diagnosis and treatment system. Hierarchical diagnosis and treatment (dpeaa)DE-He213 Patient satisfaction (dpeaa)DE-He213 Patient choice model (dpeaa)DE-He213 Patient utility (dpeaa)DE-He213 Song, Jie (orcid)0000-0003-2592-8238 aut Feng, Xing Lin aut Enthalten in International journal of flexible manufacturing systems [S.l.] : Proquest, 1988 35(2022), 2 vom: 02. Juni, Seite 455-486 (DE-627)27118101X (DE-600)1479530-9 1572-9370 nnns volume:35 year:2022 number:2 day:02 month:06 pages:455-486 https://dx.doi.org/10.1007/s10696-022-09448-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2009 GBV_ILN_2027 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4126 AR 35 2022 2 02 06 455-486 |
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10.1007/s10696-022-09448-9 doi (DE-627)SPR051786338 (SPR)s10696-022-09448-9-e DE-627 ger DE-627 rakwb eng Wang, Zi Yang verfasserin aut A prediction model of patient satisfaction: policy evaluation and sensitivity analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract China’s healthcare system has been challenged by patient dissatisfaction with primary care and an increased tendency toward visiting high-level general hospitals, which undermine the vision of a hierarchical diagnosis and treatment system. Using the game theory, we built a model that incorporated patients’ preferences and use of healthcare facilities to predict the utilization of primary care at the population level. We modeled patient behavior as an incomplete information game, whose equilibrium represents patient choice. A discrete choice model was built to describe patient satisfaction to compare the expected and actual utility. We proposed the quick fictitious play algorithm for the game model that could improve computation efficiency, using survey data from Jilin Province in the year of 2008 and 2013 in estimation, and data from 2018 to test the model’s prediction accuracy, with a prediction error of approximately 5%. We subsequently used the prediction model to simulate various scenarios, to shed light on policy recommendations, to make a theoretical contribution that estimates patient utility under ordered multi-classification choice sets, and provided policy recommendations for proceeding toward a hierarchical diagnosis and treatment system. Hierarchical diagnosis and treatment (dpeaa)DE-He213 Patient satisfaction (dpeaa)DE-He213 Patient choice model (dpeaa)DE-He213 Patient utility (dpeaa)DE-He213 Song, Jie (orcid)0000-0003-2592-8238 aut Feng, Xing Lin aut Enthalten in International journal of flexible manufacturing systems [S.l.] : Proquest, 1988 35(2022), 2 vom: 02. Juni, Seite 455-486 (DE-627)27118101X (DE-600)1479530-9 1572-9370 nnns volume:35 year:2022 number:2 day:02 month:06 pages:455-486 https://dx.doi.org/10.1007/s10696-022-09448-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2009 GBV_ILN_2027 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4126 AR 35 2022 2 02 06 455-486 |
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10.1007/s10696-022-09448-9 doi (DE-627)SPR051786338 (SPR)s10696-022-09448-9-e DE-627 ger DE-627 rakwb eng Wang, Zi Yang verfasserin aut A prediction model of patient satisfaction: policy evaluation and sensitivity analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract China’s healthcare system has been challenged by patient dissatisfaction with primary care and an increased tendency toward visiting high-level general hospitals, which undermine the vision of a hierarchical diagnosis and treatment system. Using the game theory, we built a model that incorporated patients’ preferences and use of healthcare facilities to predict the utilization of primary care at the population level. We modeled patient behavior as an incomplete information game, whose equilibrium represents patient choice. A discrete choice model was built to describe patient satisfaction to compare the expected and actual utility. We proposed the quick fictitious play algorithm for the game model that could improve computation efficiency, using survey data from Jilin Province in the year of 2008 and 2013 in estimation, and data from 2018 to test the model’s prediction accuracy, with a prediction error of approximately 5%. We subsequently used the prediction model to simulate various scenarios, to shed light on policy recommendations, to make a theoretical contribution that estimates patient utility under ordered multi-classification choice sets, and provided policy recommendations for proceeding toward a hierarchical diagnosis and treatment system. Hierarchical diagnosis and treatment (dpeaa)DE-He213 Patient satisfaction (dpeaa)DE-He213 Patient choice model (dpeaa)DE-He213 Patient utility (dpeaa)DE-He213 Song, Jie (orcid)0000-0003-2592-8238 aut Feng, Xing Lin aut Enthalten in International journal of flexible manufacturing systems [S.l.] : Proquest, 1988 35(2022), 2 vom: 02. Juni, Seite 455-486 (DE-627)27118101X (DE-600)1479530-9 1572-9370 nnns volume:35 year:2022 number:2 day:02 month:06 pages:455-486 https://dx.doi.org/10.1007/s10696-022-09448-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2009 GBV_ILN_2027 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4126 AR 35 2022 2 02 06 455-486 |
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10.1007/s10696-022-09448-9 doi (DE-627)SPR051786338 (SPR)s10696-022-09448-9-e DE-627 ger DE-627 rakwb eng Wang, Zi Yang verfasserin aut A prediction model of patient satisfaction: policy evaluation and sensitivity analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract China’s healthcare system has been challenged by patient dissatisfaction with primary care and an increased tendency toward visiting high-level general hospitals, which undermine the vision of a hierarchical diagnosis and treatment system. Using the game theory, we built a model that incorporated patients’ preferences and use of healthcare facilities to predict the utilization of primary care at the population level. We modeled patient behavior as an incomplete information game, whose equilibrium represents patient choice. A discrete choice model was built to describe patient satisfaction to compare the expected and actual utility. We proposed the quick fictitious play algorithm for the game model that could improve computation efficiency, using survey data from Jilin Province in the year of 2008 and 2013 in estimation, and data from 2018 to test the model’s prediction accuracy, with a prediction error of approximately 5%. We subsequently used the prediction model to simulate various scenarios, to shed light on policy recommendations, to make a theoretical contribution that estimates patient utility under ordered multi-classification choice sets, and provided policy recommendations for proceeding toward a hierarchical diagnosis and treatment system. Hierarchical diagnosis and treatment (dpeaa)DE-He213 Patient satisfaction (dpeaa)DE-He213 Patient choice model (dpeaa)DE-He213 Patient utility (dpeaa)DE-He213 Song, Jie (orcid)0000-0003-2592-8238 aut Feng, Xing Lin aut Enthalten in International journal of flexible manufacturing systems [S.l.] : Proquest, 1988 35(2022), 2 vom: 02. Juni, Seite 455-486 (DE-627)27118101X (DE-600)1479530-9 1572-9370 nnns volume:35 year:2022 number:2 day:02 month:06 pages:455-486 https://dx.doi.org/10.1007/s10696-022-09448-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2009 GBV_ILN_2027 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4126 AR 35 2022 2 02 06 455-486 |
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Abstract China’s healthcare system has been challenged by patient dissatisfaction with primary care and an increased tendency toward visiting high-level general hospitals, which undermine the vision of a hierarchical diagnosis and treatment system. Using the game theory, we built a model that incorporated patients’ preferences and use of healthcare facilities to predict the utilization of primary care at the population level. We modeled patient behavior as an incomplete information game, whose equilibrium represents patient choice. A discrete choice model was built to describe patient satisfaction to compare the expected and actual utility. We proposed the quick fictitious play algorithm for the game model that could improve computation efficiency, using survey data from Jilin Province in the year of 2008 and 2013 in estimation, and data from 2018 to test the model’s prediction accuracy, with a prediction error of approximately 5%. We subsequently used the prediction model to simulate various scenarios, to shed light on policy recommendations, to make a theoretical contribution that estimates patient utility under ordered multi-classification choice sets, and provided policy recommendations for proceeding toward a hierarchical diagnosis and treatment system. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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Abstract China’s healthcare system has been challenged by patient dissatisfaction with primary care and an increased tendency toward visiting high-level general hospitals, which undermine the vision of a hierarchical diagnosis and treatment system. Using the game theory, we built a model that incorporated patients’ preferences and use of healthcare facilities to predict the utilization of primary care at the population level. We modeled patient behavior as an incomplete information game, whose equilibrium represents patient choice. A discrete choice model was built to describe patient satisfaction to compare the expected and actual utility. We proposed the quick fictitious play algorithm for the game model that could improve computation efficiency, using survey data from Jilin Province in the year of 2008 and 2013 in estimation, and data from 2018 to test the model’s prediction accuracy, with a prediction error of approximately 5%. We subsequently used the prediction model to simulate various scenarios, to shed light on policy recommendations, to make a theoretical contribution that estimates patient utility under ordered multi-classification choice sets, and provided policy recommendations for proceeding toward a hierarchical diagnosis and treatment system. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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Abstract China’s healthcare system has been challenged by patient dissatisfaction with primary care and an increased tendency toward visiting high-level general hospitals, which undermine the vision of a hierarchical diagnosis and treatment system. Using the game theory, we built a model that incorporated patients’ preferences and use of healthcare facilities to predict the utilization of primary care at the population level. We modeled patient behavior as an incomplete information game, whose equilibrium represents patient choice. A discrete choice model was built to describe patient satisfaction to compare the expected and actual utility. We proposed the quick fictitious play algorithm for the game model that could improve computation efficiency, using survey data from Jilin Province in the year of 2008 and 2013 in estimation, and data from 2018 to test the model’s prediction accuracy, with a prediction error of approximately 5%. We subsequently used the prediction model to simulate various scenarios, to shed light on policy recommendations, to make a theoretical contribution that estimates patient utility under ordered multi-classification choice sets, and provided policy recommendations for proceeding toward a hierarchical diagnosis and treatment system. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 |
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