Fall incidence in hospitalized patients and prediction of its risk factors using a weighted Poisson model
Aim Falls in hospital as a major cause of disability and death threaten patients’ safety and quality of life. We studied fall incidence in hospital, and predicted its risk factors using weighted Poisson (WP) model versus other models. Method This cross-sectional study was performed on the patients r...
Gespeichert in:
| Veröffentlicht in: | Journal of public health 2022-12, Vol.30 (12), p.2971-2980 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 2980 |
|---|---|
| container_issue | 12 |
| container_start_page | 2971 |
| container_title | Journal of public health |
| container_volume | 30 |
| creator | Yaghoubi, Siamak Gooraji, Somayeh Ahmadi Habibi, Maryam Torkaman, Farideh |
| description | Aim
Falls in hospital as a major cause of disability and death threaten patients’ safety and quality of life. We studied fall incidence in hospital, and predicted its risk factors using weighted Poisson (WP) model versus other models.
Method
This cross-sectional study was performed on the patients referred to two central hospitals in Qazvin, Iran between 2017 and 2019. The data were collected using the Morse scale and fall reporting forms in the hospital patient safety units (288 falls). Factors including age, gender, time of fall, fall location, cause of fall and its complications, drugs administrated, disease history, post-fall care measures, presence of companion, and length of hospital stay were assessed. The WP model was compared with other models.
Results
Fall incidence was 2.5 per 1000 patient days. Among them, 62.5% were elderly (mean age 65.7 ± 19.21 yr). Using the WP model, age, gender, fall location and fall cause, drugs administered, post-fall care measures (
P
|
| doi_str_mv | 10.1007/s10389-021-01476-3 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2737601307</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2737601307</sourcerecordid><originalsourceid>FETCH-LOGICAL-c293t-b1301640854ad95960bbce27b2d86a46f615015464daa61c270899cbfbfe0f433</originalsourceid><addsrcrecordid>eNp9kE1LwzAYx4MoOKdfwFPAczQvbdocZTgVBnrQc0jTZMvskppkiH56Myt48_S88H-BHwCXBF8TjJubRDBrBcKUIEyqhiN2BGaEE4YoZe0xmFEiWkRaxk7BWUpbjBljVMyAW6phgM5r1xuvTdngJqTRZTW4L9PDUWVnfE5Q-XJE0zudXfAwWOjKN7r0Bq3SOcQE98n5NVTww7j1Jhfzc3ApFfEu9GY4BydWDclc_M45eF3evSwe0Orp_nFxu0KaCpZRRxgmvMJtXale1ILjrtOGNh3tW64qbjmpMakrXvVKcaJpg1shdGc7a7CtGJuDqyl3jOF9b1KW27CPvlRK2rCG41LQFBWdVDqGlKKxcoxup-KnJFgekMoJqSxI5Q9SeYhmkykVsV-b-Bf9j-sbgYp57Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2737601307</pqid></control><display><type>article</type><title>Fall incidence in hospitalized patients and prediction of its risk factors using a weighted Poisson model</title><source>SpringerNature Journals</source><creator>Yaghoubi, Siamak ; Gooraji, Somayeh Ahmadi ; Habibi, Maryam ; Torkaman, Farideh</creator><creatorcontrib>Yaghoubi, Siamak ; Gooraji, Somayeh Ahmadi ; Habibi, Maryam ; Torkaman, Farideh</creatorcontrib><description>Aim
Falls in hospital as a major cause of disability and death threaten patients’ safety and quality of life. We studied fall incidence in hospital, and predicted its risk factors using weighted Poisson (WP) model versus other models.
Method
This cross-sectional study was performed on the patients referred to two central hospitals in Qazvin, Iran between 2017 and 2019. The data were collected using the Morse scale and fall reporting forms in the hospital patient safety units (288 falls). Factors including age, gender, time of fall, fall location, cause of fall and its complications, drugs administrated, disease history, post-fall care measures, presence of companion, and length of hospital stay were assessed. The WP model was compared with other models.
Results
Fall incidence was 2.5 per 1000 patient days. Among them, 62.5% were elderly (mean age 65.7 ± 19.21 yr). Using the WP model, age, gender, fall location and fall cause, drugs administered, post-fall care measures (
P
< 0.001), and the presence of companion were identified as risk factors for falling (
P
< 0.001) Older females, those without a companion, and those without post-fall care measures and with medication history were at a higher risk. Falls from bed were the prevalent type of fall (IRR = 1.65). Falls in the internal ward were lower than in other wards (IRR = 0.67).
Conclusion
The WP model is suggested as an appropriate model to predict fall risk factors. Fall rate may be reduced by combining information on risk factors with the strategies of training nurses or caregivers, or making possible changes in patients’ environment.</description><identifier>ISSN: 2198-1833</identifier><identifier>EISSN: 1613-2238</identifier><identifier>DOI: 10.1007/s10389-021-01476-3</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Age ; Drugs ; Epidemiology ; Falls ; Gender ; Health Promotion and Disease Prevention ; Medicine ; Medicine & Public Health ; Original Article ; Patient safety ; Patients ; Public Health ; Quality of life ; Risk analysis ; Risk factors ; Safety</subject><ispartof>Journal of public health, 2022-12, Vol.30 (12), p.2971-2980</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-b1301640854ad95960bbce27b2d86a46f615015464daa61c270899cbfbfe0f433</citedby><cites>FETCH-LOGICAL-c293t-b1301640854ad95960bbce27b2d86a46f615015464daa61c270899cbfbfe0f433</cites><orcidid>0000-0003-3768-2650</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10389-021-01476-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10389-021-01476-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Yaghoubi, Siamak</creatorcontrib><creatorcontrib>Gooraji, Somayeh Ahmadi</creatorcontrib><creatorcontrib>Habibi, Maryam</creatorcontrib><creatorcontrib>Torkaman, Farideh</creatorcontrib><title>Fall incidence in hospitalized patients and prediction of its risk factors using a weighted Poisson model</title><title>Journal of public health</title><addtitle>J Public Health (Berl.)</addtitle><description>Aim
Falls in hospital as a major cause of disability and death threaten patients’ safety and quality of life. We studied fall incidence in hospital, and predicted its risk factors using weighted Poisson (WP) model versus other models.
Method
This cross-sectional study was performed on the patients referred to two central hospitals in Qazvin, Iran between 2017 and 2019. The data were collected using the Morse scale and fall reporting forms in the hospital patient safety units (288 falls). Factors including age, gender, time of fall, fall location, cause of fall and its complications, drugs administrated, disease history, post-fall care measures, presence of companion, and length of hospital stay were assessed. The WP model was compared with other models.
Results
Fall incidence was 2.5 per 1000 patient days. Among them, 62.5% were elderly (mean age 65.7 ± 19.21 yr). Using the WP model, age, gender, fall location and fall cause, drugs administered, post-fall care measures (
P
< 0.001), and the presence of companion were identified as risk factors for falling (
P
< 0.001) Older females, those without a companion, and those without post-fall care measures and with medication history were at a higher risk. Falls from bed were the prevalent type of fall (IRR = 1.65). Falls in the internal ward were lower than in other wards (IRR = 0.67).
Conclusion
The WP model is suggested as an appropriate model to predict fall risk factors. Fall rate may be reduced by combining information on risk factors with the strategies of training nurses or caregivers, or making possible changes in patients’ environment.</description><subject>Age</subject><subject>Drugs</subject><subject>Epidemiology</subject><subject>Falls</subject><subject>Gender</subject><subject>Health Promotion and Disease Prevention</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Original Article</subject><subject>Patient safety</subject><subject>Patients</subject><subject>Public Health</subject><subject>Quality of life</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Safety</subject><issn>2198-1833</issn><issn>1613-2238</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kE1LwzAYx4MoOKdfwFPAczQvbdocZTgVBnrQc0jTZMvskppkiH56Myt48_S88H-BHwCXBF8TjJubRDBrBcKUIEyqhiN2BGaEE4YoZe0xmFEiWkRaxk7BWUpbjBljVMyAW6phgM5r1xuvTdngJqTRZTW4L9PDUWVnfE5Q-XJE0zudXfAwWOjKN7r0Bq3SOcQE98n5NVTww7j1Jhfzc3ApFfEu9GY4BydWDclc_M45eF3evSwe0Orp_nFxu0KaCpZRRxgmvMJtXale1ILjrtOGNh3tW64qbjmpMakrXvVKcaJpg1shdGc7a7CtGJuDqyl3jOF9b1KW27CPvlRK2rCG41LQFBWdVDqGlKKxcoxup-KnJFgekMoJqSxI5Q9SeYhmkykVsV-b-Bf9j-sbgYp57Q</recordid><startdate>20221201</startdate><enddate>20221201</enddate><creator>Yaghoubi, Siamak</creator><creator>Gooraji, Somayeh Ahmadi</creator><creator>Habibi, Maryam</creator><creator>Torkaman, Farideh</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>L6V</scope><scope>M0S</scope><scope>M1P</scope><scope>M7S</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><orcidid>https://orcid.org/0000-0003-3768-2650</orcidid></search><sort><creationdate>20221201</creationdate><title>Fall incidence in hospitalized patients and prediction of its risk factors using a weighted Poisson model</title><author>Yaghoubi, Siamak ; Gooraji, Somayeh Ahmadi ; Habibi, Maryam ; Torkaman, Farideh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-b1301640854ad95960bbce27b2d86a46f615015464daa61c270899cbfbfe0f433</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Age</topic><topic>Drugs</topic><topic>Epidemiology</topic><topic>Falls</topic><topic>Gender</topic><topic>Health Promotion and Disease Prevention</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Original Article</topic><topic>Patient safety</topic><topic>Patients</topic><topic>Public Health</topic><topic>Quality of life</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Safety</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yaghoubi, Siamak</creatorcontrib><creatorcontrib>Gooraji, Somayeh Ahmadi</creatorcontrib><creatorcontrib>Habibi, Maryam</creatorcontrib><creatorcontrib>Torkaman, Farideh</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Engineering Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Engineering Database</collection><collection>Environmental Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><jtitle>Journal of public health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yaghoubi, Siamak</au><au>Gooraji, Somayeh Ahmadi</au><au>Habibi, Maryam</au><au>Torkaman, Farideh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fall incidence in hospitalized patients and prediction of its risk factors using a weighted Poisson model</atitle><jtitle>Journal of public health</jtitle><stitle>J Public Health (Berl.)</stitle><date>2022-12-01</date><risdate>2022</risdate><volume>30</volume><issue>12</issue><spage>2971</spage><epage>2980</epage><pages>2971-2980</pages><issn>2198-1833</issn><eissn>1613-2238</eissn><abstract>Aim
Falls in hospital as a major cause of disability and death threaten patients’ safety and quality of life. We studied fall incidence in hospital, and predicted its risk factors using weighted Poisson (WP) model versus other models.
Method
This cross-sectional study was performed on the patients referred to two central hospitals in Qazvin, Iran between 2017 and 2019. The data were collected using the Morse scale and fall reporting forms in the hospital patient safety units (288 falls). Factors including age, gender, time of fall, fall location, cause of fall and its complications, drugs administrated, disease history, post-fall care measures, presence of companion, and length of hospital stay were assessed. The WP model was compared with other models.
Results
Fall incidence was 2.5 per 1000 patient days. Among them, 62.5% were elderly (mean age 65.7 ± 19.21 yr). Using the WP model, age, gender, fall location and fall cause, drugs administered, post-fall care measures (
P
< 0.001), and the presence of companion were identified as risk factors for falling (
P
< 0.001) Older females, those without a companion, and those without post-fall care measures and with medication history were at a higher risk. Falls from bed were the prevalent type of fall (IRR = 1.65). Falls in the internal ward were lower than in other wards (IRR = 0.67).
Conclusion
The WP model is suggested as an appropriate model to predict fall risk factors. Fall rate may be reduced by combining information on risk factors with the strategies of training nurses or caregivers, or making possible changes in patients’ environment.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s10389-021-01476-3</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-3768-2650</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2198-1833 |
| ispartof | Journal of public health, 2022-12, Vol.30 (12), p.2971-2980 |
| issn | 2198-1833 1613-2238 |
| language | eng |
| recordid | cdi_proquest_journals_2737601307 |
| source | SpringerNature Journals |
| subjects | Age Drugs Epidemiology Falls Gender Health Promotion and Disease Prevention Medicine Medicine & Public Health Original Article Patient safety Patients Public Health Quality of life Risk analysis Risk factors Safety |
| title | Fall incidence in hospitalized patients and prediction of its risk factors using a weighted Poisson model |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T12%3A27%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Fall%20incidence%20in%20hospitalized%20patients%20and%20prediction%20of%20its%20risk%20factors%20using%20a%20weighted%20Poisson%20model&rft.jtitle=Journal%20of%20public%20health&rft.au=Yaghoubi,%20Siamak&rft.date=2022-12-01&rft.volume=30&rft.issue=12&rft.spage=2971&rft.epage=2980&rft.pages=2971-2980&rft.issn=2198-1833&rft.eissn=1613-2238&rft_id=info:doi/10.1007/s10389-021-01476-3&rft_dat=%3Cproquest_cross%3E2737601307%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2737601307&rft_id=info:pmid/&rfr_iscdi=true |