Publicação
Pre-triage decision support improvement in maternity care by means of data mining
| Resumo: | A triage system aims to make a correct characterization of the condition of patients. Because conventional triage systems like Manchester Triage System (MTS) are not suitable for maternity care, a decision model for pre-triaging patients in emergency (URG) and consultation (ARGO) classes was built and incorporated into a Decision Support System (DSS) implemented in Centro Materno Infantil do Norte (CMIN). Complementarily, DSS produces several indicators to support clinical and management decisions. A recent data analysis revealed a bias in the classification of URG cases. Frequently, cases classified as URG correspond to ARGO. This misclassification has been studied by means of Data Mining (DM) techniques in order to improve the pre-triage model and to discover knowledge for developing a new triage system based on waiting times and on a 5-scale of classes. This chapter presents a kind of sensitivity analysis combining input variables in six scenarios and considering four different DM techniques. CRISP-DM methodology was used to conduct the project. |
|---|---|
| Autores principais: | Pereira, Eliane |
| Outros Autores: | Brandão, Andreia; Salazar, Maria; Portela, Filipe; Santos, Manuel; Machado, José Manuel; Abelha, António |
| Assunto: | Triage Decision support Maternity care Data mining |
| Ano: | 2015 |
| País: | Portugal |
| Tipo de documento: | capítulo de livro |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| _version_ | 1867439664716054528 |
|---|---|
| author | Pereira, Eliane |
| author2 | Brandão, Andreia Salazar, Maria Portela, Filipe Santos, Manuel Machado, José Manuel Abelha, António |
| author2_role | author author author author author author |
| author_facet | Pereira, Eliane Brandão, Andreia Salazar, Maria Portela, Filipe Santos, Manuel Machado, José Manuel Abelha, António |
| author_role | author |
| contributor_name_str_mv | RepositóriUM - Universidade do Minho |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Pereira, Eliane\"},{\"Person.name\":\"Brandão, Andreia\"},{\"Person.name\":\"Salazar, Maria\"},{\"Person.name\":\"Portela, Filipe\"},{\"Person.name\":\"Santos, Manuel\"},{\"Person.name\":\"Machado, José Manuel\"},{\"Person.name\":\"Abelha, António\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | RepositóriUM - Universidade do Minho |
| datacite.creators.creator.creatorName.fl_str_mv | Pereira, Eliane Brandão, Andreia Salazar, Maria Portela, Filipe Santos, Manuel Machado, José Manuel Abelha, António |
| datacite.date.Accepted.fl_str_mv | 2015-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2014-11-24T14:13:21Z |
| datacite.date.embargoed.fl_str_mv | 2014-11-24T14:13:21Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Triage Decision support Maternity care Data mining |
| datacite.titles.title.fl_str_mv | Pre-triage decision support improvement in maternity care by means of data mining |
| dc.contributor.none.fl_str_mv | RepositóriUM - Universidade do Minho |
| dc.creator.none.fl_str_mv | Pereira, Eliane Brandão, Andreia Salazar, Maria Portela, Filipe Santos, Manuel Machado, José Manuel Abelha, António |
| dc.date.Accepted.fl_str_mv | 2015-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2014-11-24T14:13:21Z |
| dc.date.embargoed.fl_str_mv | 2014-11-24T14:13:21Z |
| dc.format.none.fl_str_mv | application/msword |
| dc.identifier.none.fl_str_mv | https://hdl.handle.net/1822/31201 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | IGI Global |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Triage Decision support Maternity care Data mining |
| dc.title.fl_str_mv | Pre-triage decision support improvement in maternity care by means of data mining |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_3248 |
| description | A triage system aims to make a correct characterization of the condition of patients. Because conventional triage systems like Manchester Triage System (MTS) are not suitable for maternity care, a decision model for pre-triaging patients in emergency (URG) and consultation (ARGO) classes was built and incorporated into a Decision Support System (DSS) implemented in Centro Materno Infantil do Norte (CMIN). Complementarily, DSS produces several indicators to support clinical and management decisions. A recent data analysis revealed a bias in the classification of URG cases. Frequently, cases classified as URG correspond to ARGO. This misclassification has been studied by means of Data Mining (DM) techniques in order to improve the pre-triage model and to discover knowledge for developing a new triage system based on waiting times and on a 5-scale of classes. This chapter presents a kind of sensitivity analysis combining input variables in six scenarios and considering four different DM techniques. CRISP-DM methodology was used to conduct the project. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | bookPart |
| fulltext.url.fl_str_mv | https://repositorium.uminho.pt/bitstreams/24c9478d-9a00-4fcd-af0f-f96a5ab37c6c/download |
| id | rum_02c96c0ce9d97d32dfcd93b93072e721 |
| identifier.url.fl_str_mv | https://hdl.handle.net/1822/31201 |
| instacron_str | repositorium |
| institution | Universidade do Minho |
| instname_str | Universidade do Minho |
| language | eng |
| network_acronym_str | rum |
| network_name_str | RepositóriUM - Universidade do Minho |
| oai_identifier_str | oai:repositorium.uminho.pt:1822/31201 |
| organization_str_mv | urn:organizationAcronym:repositorium |
| person_str_mv | Pereira, Eliane Brandão, Andreia Salazar, Maria Portela, Filipe Santos, Manuel Machado, José Manuel Abelha, António |
| publishDate | 2015 |
| publisher.none.fl_str_mv | IGI Global |
| reponame_str | RepositóriUM - Universidade do Minho |
| repository_id_str | urn:repositoryAcronym:rum |
| service_str_mv | urn:repositoryAcronym:rum |
| spelling | engIGI GlobalporA triage system aims to make a correct characterization of the condition of patients. Because conventional triage systems like Manchester Triage System (MTS) are not suitable for maternity care, a decision model for pre-triaging patients in emergency (URG) and consultation (ARGO) classes was built and incorporated into a Decision Support System (DSS) implemented in Centro Materno Infantil do Norte (CMIN). Complementarily, DSS produces several indicators to support clinical and management decisions. A recent data analysis revealed a bias in the classification of URG cases. Frequently, cases classified as URG correspond to ARGO. This misclassification has been studied by means of Data Mining (DM) techniques in order to improve the pre-triage model and to discover knowledge for developing a new triage system based on waiting times and on a 5-scale of classes. This chapter presents a kind of sensitivity analysis combining input variables in six scenarios and considering four different DM techniques. CRISP-DM methodology was used to conduct the project.application/mswordporPre-triage decision support improvement in maternity care by means of data miningPereira, ElianeBrandão, AndreiaSalazar, MariaPortela, FilipeSantos, ManuelMachado, José ManuelAbelha, AntónioHostingInstitutionOrganizationalRepositóriUM - Universidade do Minhoe-mailmailto:repositorium@usdb.uminho.ptrepositorium@usdb.uminho.ptISBNIsPartOf978-1-4666-6477-7DOIIsPartOf10.4018/978-1-4666-6477-7.ch0092014-11-24T14:13:21Z20152015-01-01T00:00:00ZHandlehttps://hdl.handle.net/1822/31201http://purl.org/coar/access_right/c_abf2open accessTriageDecision supportMaternity careData mining550912 bytesliteraturehttp://purl.org/coar/resource_type/c_3248book parthttp://purl.org/coar/access_right/c_abf2application/mswordfulltexthttps://repositorium.uminho.pt/bitstreams/24c9478d-9a00-4fcd-af0f-f96a5ab37c6c/download |
| spellingShingle | Pre-triage decision support improvement in maternity care by means of data mining Pereira, Eliane Triage Decision support Maternity care Data mining |
| status | SINGLETON |
| subject.fl_str_mv | Triage Decision support Maternity care Data mining |
| title | Pre-triage decision support improvement in maternity care by means of data mining |
| title_full | Pre-triage decision support improvement in maternity care by means of data mining |
| title_fullStr | Pre-triage decision support improvement in maternity care by means of data mining |
| title_full_unstemmed | Pre-triage decision support improvement in maternity care by means of data mining |
| title_short | Pre-triage decision support improvement in maternity care by means of data mining |
| title_sort | Pre-triage decision support improvement in maternity care by means of data mining |
| topic | Triage Decision support Maternity care Data mining |
| topic_facet | Triage Decision support Maternity care Data mining |
| url | https://hdl.handle.net/1822/31201 |
| visible | 1 |