Chronic status patients in a university hospital: bed-day utilization and length of stay.

OBJECTIVE

To examine the lengths of stay of chronic status patients in an acute care hospital, to identify discharge stages that contribute to excessive stays, to estimate the length of stay at each discharge stage and to link hospital bed-day utilization by the discharge stage to the experience of the patient.

DESIGN

Two-year prospective cohort study. The number of hospital days retrospective to the date of the current admission were included in the analysis.

SETTING

University hospital.

PATIENTS

All 115 inpatients formally declared as achieving chronic status by July 31, 1987.

OUTCOME MEASURES

Lengths of stay (total days and days at acute and chronic status) for chronic status patients, including those still in hospital at the end of the study period. Each bed-day was assigned to a discharge stage that corresponded to the patient's status. The disposition of each patient by the end of the study period was reviewed.

RESULTS

The study population spent a total of 101 585 days in hospital. The total length of stay per patient was nearly four times that stated in the hospital's annual report, in which the figure was calculated only on the basis of discharge data. On average only 77.2 (8.7%) of the days were spent in acute care. The remaining days were at the chronic level: 24.1% were spent waiting for completion of an application to a long-term care facility, 25.3% for application approval and 41.9% for an available bed in the assigned long-term care institution. For 30 patients no initiation of the discharge process was ever undertaken. As the number of patients in each progressive discharge stage decreased, the wait per patient increased. By the end of the study period only 32 patients had been transferred to a public long-term care facility; 22 were still in hospital, and 35 had died waiting for placement.

CONCLUSIONS

Although considered to be a useful measure of hospital efficiency, length of stay determined from discharge data creates an iceberg effect when applied to chronic status patients in acute care hospitals. Lack of access to the assigned resource is the most important reason for a delay in discharge. Interventions, whether undertaken at the patient, hospital or provincial level, must to some degree address this issue. Further study is required to determine which risk factors will predict lags at each discharge stage. Since our discharge staging reflects not only the experience of the patient but also the utilization of hospital bed-days and access to provincial resources, it provides a common language for clinicians, hospital administrators and systems planners.