Causation between Pathway Completion and Reduced Hospital Stay in Patients with Lung Cancer: a Retrospective Cohort Study Using Propensity Score Matching
We have previously demonstrated that clinical pathway completion helps reduce hospital stays. However, our previous results showed only a correlation, not causation. Therefore, the current study’s aim was to analyze the causation between clinical pathway completion and reduced hospital stays for pat...
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| Veröffentlicht in: | Journal of medical systems 2020-06, Vol.44 (6), p.105-105, Article 105 |
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| description | We have previously demonstrated that clinical pathway completion helps reduce hospital stays. However, our previous results showed only a correlation, not causation. Therefore, the current study’s aim was to analyze the causation between clinical pathway completion and reduced hospital stays for patients with lung cancer. Data were collected from April 2013 to March 2018 from the electronic medical records of the University of Miyazaki Hospital. We used propensity score matching to extract records from 227 patients. Patients were further divided into a pathway completed group and a pathway not completed group; 74 patients in each group were available for data analysis. Our main analysis involved estimating the discharge curve, which was comprised of the in-hospital rate and hospital stay. Additional analyzes were performed to compare the frequency of medical treatments registered in the clinical pathway but not implemented (termed deviated medical treatments). The occurrence of these treatments meant that the clinical pathway was not completed. The main results indicated a decrease in the in-hospital rate of the completion group, compared with the not completed group. The
p
value of the log-rank test was |
| doi_str_mv | 10.1007/s10916-020-01570-1 |
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p
value of the log-rank test was <0.001 for total patients and patients who underwent resection, and 0.017 for patients who did not undergo resection. Additional results indicated that a number of intravenous drips were not implemented, despite their registration on clinical pathways. Our results indicate that clinical pathway completion contributes to improved efficiency and safety. This simplified procedure is expected to be applicable to other diseases and clinical indicators.</description><identifier>ISSN: 0148-5598</identifier><identifier>EISSN: 1573-689X</identifier><identifier>DOI: 10.1007/s10916-020-01570-1</identifier><identifier>PMID: 32318867</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Causality ; Causation ; Cohort analysis ; Critical Pathways - organization & administration ; Data analysis ; Efficiency, Organizational ; Electronic health records ; Electronic medical records ; Female ; Health Informatics ; Health Sciences ; Hospital Information Systems - organization & administration ; Humans ; Intravenous administration ; Japan ; Length of Stay - statistics & numerical data ; Lung cancer ; Lung Neoplasms - therapy ; Male ; Matching ; Medical treatment ; Medicine ; Medicine & Public Health ; Patients ; Propensity Score ; Quality Improvement - organization & administration ; Rank tests ; Retrospective Studies ; Statistics for Life Sciences ; Systems-Level Quality Improvement</subject><ispartof>Journal of medical systems, 2020-06, Vol.44 (6), p.105-105, Article 105</ispartof><rights>The Author(s) 2020</rights><rights>The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-ae210f24bebf14369249c40af7137edaadb8c5fb0ba65a00214b6057cf02ae513</citedby><cites>FETCH-LOGICAL-c474t-ae210f24bebf14369249c40af7137edaadb8c5fb0ba65a00214b6057cf02ae513</cites><orcidid>0000-0001-7514-0049</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/s10916-020-01570-1$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10916-020-01570-1$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32318867$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Furuhata, Hiroki</creatorcontrib><creatorcontrib>Araki, Kenji</creatorcontrib><creatorcontrib>Ogawa, Taisuke</creatorcontrib><title>Causation between Pathway Completion and Reduced Hospital Stay in Patients with Lung Cancer: a Retrospective Cohort Study Using Propensity Score Matching</title><title>Journal of medical systems</title><addtitle>J Med Syst</addtitle><addtitle>J Med Syst</addtitle><description>We have previously demonstrated that clinical pathway completion helps reduce hospital stays. However, our previous results showed only a correlation, not causation. Therefore, the current study’s aim was to analyze the causation between clinical pathway completion and reduced hospital stays for patients with lung cancer. Data were collected from April 2013 to March 2018 from the electronic medical records of the University of Miyazaki Hospital. We used propensity score matching to extract records from 227 patients. Patients were further divided into a pathway completed group and a pathway not completed group; 74 patients in each group were available for data analysis. Our main analysis involved estimating the discharge curve, which was comprised of the in-hospital rate and hospital stay. Additional analyzes were performed to compare the frequency of medical treatments registered in the clinical pathway but not implemented (termed deviated medical treatments). The occurrence of these treatments meant that the clinical pathway was not completed. The main results indicated a decrease in the in-hospital rate of the completion group, compared with the not completed group. The
p
value of the log-rank test was <0.001 for total patients and patients who underwent resection, and 0.017 for patients who did not undergo resection. Additional results indicated that a number of intravenous drips were not implemented, despite their registration on clinical pathways. Our results indicate that clinical pathway completion contributes to improved efficiency and safety. 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of medical systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Furuhata, Hiroki</au><au>Araki, Kenji</au><au>Ogawa, Taisuke</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Causation between Pathway Completion and Reduced Hospital Stay in Patients with Lung Cancer: a Retrospective Cohort Study Using Propensity Score Matching</atitle><jtitle>Journal of medical systems</jtitle><stitle>J Med Syst</stitle><addtitle>J Med Syst</addtitle><date>2020-06-01</date><risdate>2020</risdate><volume>44</volume><issue>6</issue><spage>105</spage><epage>105</epage><pages>105-105</pages><artnum>105</artnum><issn>0148-5598</issn><eissn>1573-689X</eissn><abstract>We have previously demonstrated that clinical pathway completion helps reduce hospital stays. However, our previous results showed only a correlation, not causation. Therefore, the current study’s aim was to analyze the causation between clinical pathway completion and reduced hospital stays for patients with lung cancer. Data were collected from April 2013 to March 2018 from the electronic medical records of the University of Miyazaki Hospital. We used propensity score matching to extract records from 227 patients. Patients were further divided into a pathway completed group and a pathway not completed group; 74 patients in each group were available for data analysis. Our main analysis involved estimating the discharge curve, which was comprised of the in-hospital rate and hospital stay. Additional analyzes were performed to compare the frequency of medical treatments registered in the clinical pathway but not implemented (termed deviated medical treatments). The occurrence of these treatments meant that the clinical pathway was not completed. The main results indicated a decrease in the in-hospital rate of the completion group, compared with the not completed group. The
p
value of the log-rank test was <0.001 for total patients and patients who underwent resection, and 0.017 for patients who did not undergo resection. Additional results indicated that a number of intravenous drips were not implemented, despite their registration on clinical pathways. Our results indicate that clinical pathway completion contributes to improved efficiency and safety. This simplified procedure is expected to be applicable to other diseases and clinical indicators.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>32318867</pmid><doi>10.1007/s10916-020-01570-1</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0001-7514-0049</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Causality Causation Cohort analysis Critical Pathways - organization & administration Data analysis Efficiency, Organizational Electronic health records Electronic medical records Female Health Informatics Health Sciences Hospital Information Systems - organization & administration Humans Intravenous administration Japan Length of Stay - statistics & numerical data Lung cancer Lung Neoplasms - therapy Male Matching Medical treatment Medicine Medicine & Public Health Patients Propensity Score Quality Improvement - organization & administration Rank tests Retrospective Studies Statistics for Life Sciences Systems-Level Quality Improvement |
| title | Causation between Pathway Completion and Reduced Hospital Stay in Patients with Lung Cancer: a Retrospective Cohort Study Using Propensity Score Matching |
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