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Does scoring patient complexity using COMPRI predict the length of hospital stay? A multicentre case–control study in Japan

OBJECTIVE: To clarify the factors associated with prolonged hospital stays, focusing on the COMplexity PRediction Instrument (COMPRI) score’s accuracy in predicting the length of stay of newly hospitalised patients in general internal medicine wards. DESIGN: A case–control study. SETTING: Three gene...

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Autores principales: Yokokawa, Daiki, Shikino, Kiyoshi, Kishi, Yasuhiro, Ban, Toshiaki, Miyahara, Shigeyoshi, Ohira, Yoshiyuki, Yanagita, Yasutaka, Yamauchi, Yosuke, Hayashi, Yasushi, Ishizuka, Kosuke, Hirose, Yuta, Tsukamoto, Tomoko, Noda, Kazutaka, Uehara, Takanori, Ikusaka, Masatomi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024233/
https://www.ncbi.nlm.nih.gov/pubmed/35450890
http://dx.doi.org/10.1136/bmjopen-2021-051891
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author Yokokawa, Daiki
Shikino, Kiyoshi
Kishi, Yasuhiro
Ban, Toshiaki
Miyahara, Shigeyoshi
Ohira, Yoshiyuki
Yanagita, Yasutaka
Yamauchi, Yosuke
Hayashi, Yasushi
Ishizuka, Kosuke
Hirose, Yuta
Tsukamoto, Tomoko
Noda, Kazutaka
Uehara, Takanori
Ikusaka, Masatomi
author_facet Yokokawa, Daiki
Shikino, Kiyoshi
Kishi, Yasuhiro
Ban, Toshiaki
Miyahara, Shigeyoshi
Ohira, Yoshiyuki
Yanagita, Yasutaka
Yamauchi, Yosuke
Hayashi, Yasushi
Ishizuka, Kosuke
Hirose, Yuta
Tsukamoto, Tomoko
Noda, Kazutaka
Uehara, Takanori
Ikusaka, Masatomi
author_sort Yokokawa, Daiki
collection PubMed
description OBJECTIVE: To clarify the factors associated with prolonged hospital stays, focusing on the COMplexity PRediction Instrument (COMPRI) score’s accuracy in predicting the length of stay of newly hospitalised patients in general internal medicine wards. DESIGN: A case–control study. SETTING: Three general internal medicine wards in Chiba Prefecture, Japan. PARTICIPANTS: Thirty-four newly hospitalised patients were recruited between November 2017 and December 2019, with a final analytic sample of 33 patients. We included hospitals in different cities with general medicine outpatient and ward facilities, who agreed to participate. We excluded any patients who were re-hospitalised within 2 weeks of a prior discharge. PRIMARY AND SECONDARY OUTCOME MEASURES: Patients’ COMPRI scores and their consequent lengths of hospital stay. RESULTS: The 17 patients (52%) allocated to the long-term hospitalisation group (those hospitalised ≥14 days) had a significantly higher average age, COMPRI score and percentage of participants with comorbid chronic illnesses than the short-term hospitalisation group (<14 days). A logistic regression model (model A, comprising only the COMPRI score as the explanatory variable) and a multiple logistic regression model (model B, comprising variables other than the COMPRI score as explanatory variables) were created as prediction models for the long-term hospitalisation group. When age ≥75 years, a COMPRI score ≥6 and a physician with 10 years’ experience were set as explanatory variables, model A showed better predictive accuracy compared with model B (fivefold cross-validation, area under curve of 0.87 vs 0.78). The OR of a patient with a COMPRI score of ≥6 joining the long-term hospitalisation group was 4.25 (95% CI=1.43 to 12.63). CONCLUSIONS: Clinicians can use the COMPRI score when screening for complexity assessment to identify hospitalised patients at high risk of prolonged hospitalisation. Providing such patients with multifaceted and intensive care may shorten hospital stays.
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spelling pubmed-90242332022-05-06 Does scoring patient complexity using COMPRI predict the length of hospital stay? A multicentre case–control study in Japan Yokokawa, Daiki Shikino, Kiyoshi Kishi, Yasuhiro Ban, Toshiaki Miyahara, Shigeyoshi Ohira, Yoshiyuki Yanagita, Yasutaka Yamauchi, Yosuke Hayashi, Yasushi Ishizuka, Kosuke Hirose, Yuta Tsukamoto, Tomoko Noda, Kazutaka Uehara, Takanori Ikusaka, Masatomi BMJ Open General practice / Family practice OBJECTIVE: To clarify the factors associated with prolonged hospital stays, focusing on the COMplexity PRediction Instrument (COMPRI) score’s accuracy in predicting the length of stay of newly hospitalised patients in general internal medicine wards. DESIGN: A case–control study. SETTING: Three general internal medicine wards in Chiba Prefecture, Japan. PARTICIPANTS: Thirty-four newly hospitalised patients were recruited between November 2017 and December 2019, with a final analytic sample of 33 patients. We included hospitals in different cities with general medicine outpatient and ward facilities, who agreed to participate. We excluded any patients who were re-hospitalised within 2 weeks of a prior discharge. PRIMARY AND SECONDARY OUTCOME MEASURES: Patients’ COMPRI scores and their consequent lengths of hospital stay. RESULTS: The 17 patients (52%) allocated to the long-term hospitalisation group (those hospitalised ≥14 days) had a significantly higher average age, COMPRI score and percentage of participants with comorbid chronic illnesses than the short-term hospitalisation group (<14 days). A logistic regression model (model A, comprising only the COMPRI score as the explanatory variable) and a multiple logistic regression model (model B, comprising variables other than the COMPRI score as explanatory variables) were created as prediction models for the long-term hospitalisation group. When age ≥75 years, a COMPRI score ≥6 and a physician with 10 years’ experience were set as explanatory variables, model A showed better predictive accuracy compared with model B (fivefold cross-validation, area under curve of 0.87 vs 0.78). The OR of a patient with a COMPRI score of ≥6 joining the long-term hospitalisation group was 4.25 (95% CI=1.43 to 12.63). CONCLUSIONS: Clinicians can use the COMPRI score when screening for complexity assessment to identify hospitalised patients at high risk of prolonged hospitalisation. Providing such patients with multifaceted and intensive care may shorten hospital stays. BMJ Publishing Group 2022-04-21 /pmc/articles/PMC9024233/ /pubmed/35450890 http://dx.doi.org/10.1136/bmjopen-2021-051891 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle General practice / Family practice
Yokokawa, Daiki
Shikino, Kiyoshi
Kishi, Yasuhiro
Ban, Toshiaki
Miyahara, Shigeyoshi
Ohira, Yoshiyuki
Yanagita, Yasutaka
Yamauchi, Yosuke
Hayashi, Yasushi
Ishizuka, Kosuke
Hirose, Yuta
Tsukamoto, Tomoko
Noda, Kazutaka
Uehara, Takanori
Ikusaka, Masatomi
Does scoring patient complexity using COMPRI predict the length of hospital stay? A multicentre case–control study in Japan
title Does scoring patient complexity using COMPRI predict the length of hospital stay? A multicentre case–control study in Japan
title_full Does scoring patient complexity using COMPRI predict the length of hospital stay? A multicentre case–control study in Japan
title_fullStr Does scoring patient complexity using COMPRI predict the length of hospital stay? A multicentre case–control study in Japan
title_full_unstemmed Does scoring patient complexity using COMPRI predict the length of hospital stay? A multicentre case–control study in Japan
title_short Does scoring patient complexity using COMPRI predict the length of hospital stay? A multicentre case–control study in Japan
title_sort does scoring patient complexity using compri predict the length of hospital stay? a multicentre case–control study in japan
topic General practice / Family practice
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024233/
https://www.ncbi.nlm.nih.gov/pubmed/35450890
http://dx.doi.org/10.1136/bmjopen-2021-051891
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