BACKGROUND: Patients who left against medical advice (AMA) may be at higher risk for a hospital readmission if the unauthorized discharge was premature. The objective of this study is to examine the relationship between discharges AMA from nonfederal acute care hospitals and cardiovascular disease (CVD) hospital readmissions while addressing bias due to potential confounding, selection, and hospital-level clustering. METHODS: This cross-sectional study used hospital discharge data covering the period between 2000 and 2005. The outcome variables captured readmissions for a CVD-related condition following an index CVD-related discharge. The covariate of interest was an indicator for a discharge AMA in the index hospitalization. The relationship between discharges AMA and 7-day, 31-day, and 180-day readmissions was examined using multivariate models with adjustment for clustering and selection bias. RESULTS: The sample included 348,572 patients, of which 7001 (2%), 19,779 (6%), and 48,855 (14%) were readmitted within 7, 31, and 180 days, respectively. The percentage of patients who were readmitted (7 days; 31 days; 180 days) was higher among the AMA group versus the non-AMA group (2.2% vs. 1%, P < 0.002; 1.3% vs. 1%, P < 0.001; 1.2% vs. 1%, P = 0.02). The adjusted odds of a CVD-related readmission to the same hospital within 7 days, 31 days, and 180 days were 154% (P < 0.001), 51% (P < 0.001), and 19% (P = 0.004) higher, respectively, for patients who left AMA. Results were robust in examining readmissions to any hospital as well as corrections for observable selection bias through propensity score analysis. CONCLUSIONS: A discharge AMA among patients with a discharge diagnosis for CVD during the index hospitalization was predictive of CVD-related readmissions. The strength of the association between a discharge AMA and readmission was greatest within the first week after discharge.
BACKGROUND:Patients who left against medical advice (AMA) may be at higher risk for a hospital readmission if the unauthorized discharge was premature. The objective of this study is to examine the relationship between discharges AMA from nonfederal acute care hospitals and cardiovascular disease (CVD) hospital readmissions while addressing bias due to potential confounding, selection, and hospital-level clustering. METHODS: This cross-sectional study used hospital discharge data covering the period between 2000 and 2005. The outcome variables captured readmissions for a CVD-related condition following an index CVD-related discharge. The covariate of interest was an indicator for a discharge AMA in the index hospitalization. The relationship between discharges AMA and 7-day, 31-day, and 180-day readmissions was examined using multivariate models with adjustment for clustering and selection bias. RESULTS: The sample included 348,572 patients, of which 7001 (2%), 19,779 (6%), and 48,855 (14%) were readmitted within 7, 31, and 180 days, respectively. The percentage of patients who were readmitted (7 days; 31 days; 180 days) was higher among the AMA group versus the non-AMA group (2.2% vs. 1%, P < 0.002; 1.3% vs. 1%, P < 0.001; 1.2% vs. 1%, P = 0.02). The adjusted odds of a CVD-related readmission to the same hospital within 7 days, 31 days, and 180 days were 154% (P < 0.001), 51% (P < 0.001), and 19% (P = 0.004) higher, respectively, for patients who left AMA. Results were robust in examining readmissions to any hospital as well as corrections for observable selection bias through propensity score analysis. CONCLUSIONS: A discharge AMA among patients with a discharge diagnosis for CVD during the index hospitalization was predictive of CVD-related readmissions. The strength of the association between a discharge AMA and readmission was greatest within the first week after discharge.
Authors: Allan Garland; Clare D Ramsey; Randy Fransoo; Kendiss Olafson; Daniel Chateau; Marina Yogendran; Allen Kraut Journal: CMAJ Date: 2013-08-26 Impact factor: 8.262
Authors: Allen Kraut; Randy Fransoo; Kendiss Olafson; Clare D Ramsey; Marina Yogendran; Allan Garland Journal: BMC Health Serv Res Date: 2013-10-14 Impact factor: 2.655
Authors: Eberechukwu Onukwugha; Elijah Saunders; C Daniel Mullins; Françoise G Pradel; Marni Zuckerman; F Ellen Loh; Matthew R Weir Journal: BMJ Open Date: 2012-07-30 Impact factor: 2.692
Authors: Lian Leng Low; Nan Liu; Sijia Wang; Julian Thumboo; Marcus Eng Hock Ong; Kheng Hock Lee Journal: PLoS One Date: 2016-12-09 Impact factor: 3.240