Medical inpatients at risk of extended hospital stay and poor discharge health status: detection with COMPRI and INTERMED

OBJECTIVE: To detect the patients in medical wards at risk of extended LOS and poor discharge health status with the use of complexity prediction instrument (COMPRI) and interdisciplinary medicine (INTERMED) instruments.

METHODS: STUDY 1: In a sample of 275 consecutively admitted medical inpatients, a hierarchical cluster analysis on INTERMED variables was performed. The clusters were compared on length of hospital stay (LOS) and Short Form 36 (SF-36) at discharge. STUDY 2: Receiver operating characteristic (ROC) analysis was used to optimal cut-off points for the COMPRI and INTERMED. Patients detected with COMPRI and INTERMED were then compared with undetected patients on LOS and SF-36.

RESULTS: STUDY 1: In concordance with previous findings, a cluster of patients with high biopsychosocial vulnerability was identified with significantly higher scores on LOS (p <.05) and lower scores on SF-36 (p <.001) than patients in other clusters. STUDY 2: A cut-off point for the COMPRI of 5/6 was found to detect patients at risk of long LOS. A cut off score for the INTERMED of 20/21 was found to detect patients at risk of poor discharge health status. Patients detected with COMPRI and INTERMED had a significantly longer LOS (p <.001) and a poorer discharge health status (SF-36 MCS: p <.001; SF-36 PCS: p =.05) than nondetected patients. Of the detected patients, 37% had an extended hospital stay and poor discharge health status; of the nondetected patients, this was only 7%.

CONCLUSIONS: The COMPRI-INTERMED can help to detect complex patients admitted to medical wards within the first days of admission, and rule out those with a small chance of poor outcomes.