Influence of hospital-level practices on readmission after ischemic stroke.
OBJECTIVE
To inform stroke quality improvement initiatives by determining the relationship between hospital-level stroke practices and readmission after accounting for patient-level factors.


METHODS
Retrospective cohort study of adult patients hospitalized for ischemic stroke (principal ICD-9-CM codes 433.x1, 434.x1, and 436) in 5 states from 2003 to 2009 from State Inpatient Databases. The primary outcome was any unplanned readmission within 30 days. Multilevel logistic regression was used to estimate the association between hospital-level practice patterns of care (diagnostic testing, procedures, intensive care unit, tissue plasminogen activator, and therapeutic modalities) and readmission after adjustment for patient factors and whether individual patients received a given practice.


RESULTS
Thirty-day unplanned readmission occurred in 15.2% of stroke admissions; the median hospital readmission rate was 13.6% (interquartile range 9.8%-18.2%). Of the 25 hospital practice patterns of care analyzed, 3 practices were associated with readmission: hospitals with higher use of occupational therapy and higher proportion of transfers from other hospitals had lower adjusted readmission rates, whereas hospitals with higher use of hospice had higher predicted readmission rates. Readmission rates in lowest vs highest utilizing quintile were as follows: occupational therapy 16.2% (95% confidence interval [CI] 14.5%-18.0%) vs 12.3% (95% CI 11.3%-13.2%); transfers 13.8% (95% CI 13.2%-14.5%) vs 12.5% (95% CI 11.6%-13.5%); and hospice 13.1% (95% CI 12.3%-14.0%) vs 14.8% (95% CI 13.5%-16.1%).


CONCLUSIONS
Hospital practices have a role in stroke readmission that is complex and poorly understood. Further work is needed to identify specific strategies to reduce readmission rates and to ensure that public reporting of readmission rates will not result in adverse unintended consequences.
From the Department of Veterans Affairs (J.F.B.), VA Center for Clinical Management and Research, Ann Arbor VA Healthcare System, MI; Stroke Program (J.F.B., L.E.S., E.E.A., D.L.B.), University of Michigan, Ann Arbor; and Department of Epidemiology (M.J.R.), Michigan State University, East Lansing. jamesbur@umich.edu.
James F
JF
Burke
From the Department of Veterans Affairs (J.F.B.), VA Center for Clinical Management and Research, Ann Arbor VA Healthcare System, MI; Stroke Program (J.F.B., L.E.S., E.E.A., D.L.B.), University of Michigan, Ann Arbor; and Department of Epidemiology (M.J.R.), Michigan State University, East Lansing.
Lesli E
LE
Skolarus
From the Department of Veterans Affairs (J.F.B.), VA Center for Clinical Management and Research, Ann Arbor VA Healthcare System, MI; Stroke Program (J.F.B., L.E.S., E.E.A., D.L.B.), University of Michigan, Ann Arbor; and Department of Epidemiology (M.J.R.), Michigan State University, East Lansing.
Eric E
EE
Adelman
From the Department of Veterans Affairs (J.F.B.), VA Center for Clinical Management and Research, Ann Arbor VA Healthcare System, MI; Stroke Program (J.F.B., L.E.S., E.E.A., D.L.B.), University of Michigan, Ann Arbor; and Department of Epidemiology (M.J.R.), Michigan State University, East Lansing.
Mathew J
MJ
Reeves
From the Department of Veterans Affairs (J.F.B.), VA Center for Clinical Management and Research, Ann Arbor VA Healthcare System, MI; Stroke Program (J.F.B., L.E.S., E.E.A., D.L.B.), University of Michigan, Ann Arbor; and Department of Epidemiology (M.J.R.), Michigan State University, East Lansing.
Devin L
DL
Brown
D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D010351:Patient Discharge / Q000706:statistics & numerical data*; D010359:Patient Readmission / Q000706:statistics & numerical data*; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data; D012307:Risk Factors; D020521:Stroke / Q000453:epidemiology / Q000628:therapy*; D014481:United States