BACKGROUND: Medicare's introduction of the Prospective Payment System for hospitals has shortened hospital stays and, as a consequence, has increased the use of post-hospital care. Medicare coverage provides for various types of post-hospital care. This paper examines the characteristics of patients, cities, and hospitals associated with discharge to these different types of post-hospital care. METHODS: A Total of 2248 consecutive Medicare patients having one of five diagnosis related groups (DRGs), who were about to be discharged from 52 hospitals in three cities in 1988-1989, were enrolled in the study. These DRGs comprised approximately one-eighth of all Medicare hospital discharges and 40% of all Medicare-paid post-hospital care. Patients were interviewed in person before discharge and again 6 weeks after discharge. Clinical severity measures were developed from information abstracted from each patient's medical record. For each DRG, multinomial logit regression equations were developed to identify factors associated with the choice of one of four possible discharge locations: home with no formal care, home health care, nursing home care, or rehabilitation. RESULTS: Discharge location could be predicted correctly in 52 to 71% of cases, depending on the DRG. This level of predictive accuracy was significantly greater than relying on the modal discharge location, which accounted for 33 to 62% of cases. Most of the predictive power came from information gathered at the discharge interview. The variables associated significantly with the discharge location varied with the DRG and location examined. Living alone and functional dependency at discharge were the significant predictors found most often. CONCLUSIONS: Rather than assuming that everyone is discharged to the modal location, patient discharge location can be predicted. Much of the explanation can be traced to a few variables such as functional status and living situation. The lack of greater accuracy suggests that factors other than those identified as important by clinical panels are involved in discharge planning for Medicare patients.
BACKGROUND: Medicare's introduction of the Prospective Payment System for hospitals has shortened hospital stays and, as a consequence, has increased the use of post-hospital care. Medicare coverage provides for various types of post-hospital care. This paper examines the characteristics of patients, cities, and hospitals associated with discharge to these different types of post-hospital care. METHODS: A Total of 2248 consecutive Medicare patients having one of five diagnosis related groups (DRGs), who were about to be discharged from 52 hospitals in three cities in 1988-1989, were enrolled in the study. These DRGs comprised approximately one-eighth of all Medicare hospital discharges and 40% of all Medicare-paid post-hospital care. Patients were interviewed in person before discharge and again 6 weeks after discharge. Clinical severity measures were developed from information abstracted from each patient's medical record. For each DRG, multinomial logit regression equations were developed to identify factors associated with the choice of one of four possible discharge locations: home with no formal care, home health care, nursing home care, or rehabilitation. RESULTS: Discharge location could be predicted correctly in 52 to 71% of cases, depending on the DRG. This level of predictive accuracy was significantly greater than relying on the modal discharge location, which accounted for 33 to 62% of cases. Most of the predictive power came from information gathered at the discharge interview. The variables associated significantly with the discharge location varied with the DRG and location examined. Living alone and functional dependency at discharge were the significant predictors found most often. CONCLUSIONS: Rather than assuming that everyone is discharged to the modal location, patient discharge location can be predicted. Much of the explanation can be traced to a few variables such as functional status and living situation. The lack of greater accuracy suggests that factors other than those identified as important by clinical panels are involved in discharge planning for Medicare patients.
Authors: J T Schousboe; M L Paudel; B C Taylor; A M Kats; B A Virnig; B E Dowd; L Langsetmo; K E Ensrud Journal: Osteoporos Int Date: 2016-10-14 Impact factor: 4.507
Authors: Ling Na; Sean Hennessy; Dawei Xie; Debra Saliba; Qiang Pan; Pui L Kwong; Jibby E Kurichi; Hillary R Bogner; Joel E Streim Journal: Am J Phys Med Rehabil Date: 2018-06 Impact factor: 2.159
Authors: Melinda Beeuwkes Buntin; Anita Datar Garten; Susan Paddock; Debra Saliba; Mark Totten; José J Escarce Journal: Health Serv Res Date: 2005-04 Impact factor: 3.402