The role of discriminant analysis in the refinement of customer satisfaction assessment
OBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatie...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Universidade de São Paulo
2000-01-01
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| Series: | Revista de Saúde Pública |
| Subjects: | |
| Online Access: | http://www.scielosp.org/scielo.php?script=sci_arttext&pid=S0034-89102000000600010 |
| _version_ | 1830513705635282944 |
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| author | Verdessi BD Jara G Fuentes R Gonzalez JC Espejo F Azevedo AC de |
| author_facet | Verdessi BD Jara G Fuentes R Gonzalez JC Espejo F Azevedo AC de |
| author_sort | Verdessi BD |
| collection | DOAJ |
| description | OBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatient care units in Valparaíso, Chile, one of primary care (n=100) and the other of secondary care (n=249). Two cutting points were considered in the dependent variable (final satisfaction score): satisfied versus unsatisfied, and very satisfied versus all others. Results were compared with empirical measures (proportion of satisfied individuals, proportion of unsatisfied individuals and size of the median). RESULTS: The response rate was very high, over 97.0% in both units. A new variable, medical attention, was revealed, as explaining satisfaction at the primary care unit. The proportion of the total variability explained by the model was very high (over 99.4%) in both units, when comparing satisfied with unsatisfied customers. In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). It measured the contribution of each independent variable to the explanation of the variation of the dependent one. |
| first_indexed | 2024-12-22T02:50:00Z |
| format | Article |
| id | doaj.art-901e93bbf46b4ef288c93244fc2e3ac8 |
| institution | Directory Open Access Journal |
| issn | 0034-8910 1518-8787 |
| language | English |
| last_indexed | 2024-12-22T02:50:00Z |
| publishDate | 2000-01-01 |
| publisher | Universidade de São Paulo |
| record_format | Article |
| series | Revista de Saúde Pública |
| spelling | doaj.art-901e93bbf46b4ef288c93244fc2e3ac82022-12-21T18:41:24ZengUniversidade de São PauloRevista de Saúde Pública0034-89101518-87872000-01-01346623630The role of discriminant analysis in the refinement of customer satisfaction assessmentVerdessi BDJara GFuentes RGonzalez JCEspejo FAzevedo AC deOBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatient care units in Valparaíso, Chile, one of primary care (n=100) and the other of secondary care (n=249). Two cutting points were considered in the dependent variable (final satisfaction score): satisfied versus unsatisfied, and very satisfied versus all others. Results were compared with empirical measures (proportion of satisfied individuals, proportion of unsatisfied individuals and size of the median). RESULTS: The response rate was very high, over 97.0% in both units. A new variable, medical attention, was revealed, as explaining satisfaction at the primary care unit. The proportion of the total variability explained by the model was very high (over 99.4%) in both units, when comparing satisfied with unsatisfied customers. In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). It measured the contribution of each independent variable to the explanation of the variation of the dependent one.http://www.scielosp.org/scielo.php?script=sci_arttext&pid=S0034-89102000000600010Discriminant analysisCustomer satisfactionPatient satisfactionTotal quality managementQuality assurance in health careQuality assurance health careQuality controlQuality of health care |
| spellingShingle | Verdessi BD Jara G Fuentes R Gonzalez JC Espejo F Azevedo AC de The role of discriminant analysis in the refinement of customer satisfaction assessment Revista de Saúde Pública Discriminant analysis Customer satisfaction Patient satisfaction Total quality management Quality assurance in health care Quality assurance health care Quality control Quality of health care |
| title | The role of discriminant analysis in the refinement of customer satisfaction assessment |
| title_full | The role of discriminant analysis in the refinement of customer satisfaction assessment |
| title_fullStr | The role of discriminant analysis in the refinement of customer satisfaction assessment |
| title_full_unstemmed | The role of discriminant analysis in the refinement of customer satisfaction assessment |
| title_short | The role of discriminant analysis in the refinement of customer satisfaction assessment |
| title_sort | role of discriminant analysis in the refinement of customer satisfaction assessment |
| topic | Discriminant analysis Customer satisfaction Patient satisfaction Total quality management Quality assurance in health care Quality assurance health care Quality control Quality of health care |
| url | http://www.scielosp.org/scielo.php?script=sci_arttext&pid=S0034-89102000000600010 |
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