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

• Published in: BMJ open Vol. 12; no. 4; p. e051891
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: England British Medical Journal Publishing Group 21.04.2022; BMJ Publishing Group LTD; BMJ Publishing Group
• Series: Original research
• Subjects: Age; Aged; Case-Control Studies; Emergency medical care; general medicine (see internal medicine); General practice / Family practice; Hospitalization; Hospitals; Humans; Illnesses; Internal medicine; Japan; Length of Stay; Medical history; Medicine; Older people; Patient Discharge; Patients; Physicians; primary care; Japan; Netherlands; Europe; internal medicine; primary care; general medicine (see internal medicine)
• ISSN: 2044-6055; 2044-6055
• DOI: 10.1136/bmjopen-2021-051891

ObjectiveTo 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.DesignA case–control study.SettingThree general internal medicine wards in Chiba Prefecture, Japan.ParticipantsThirty-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 measuresPatients’ COMPRI scores and their consequent lengths of hospital stay.ResultsThe 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).ConclusionsClinicians 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.