Factors contributing to practice variation in post-stroke rehabilitation.
OBJECTIVE
To analyze geographic variability in the utilization and cost of post-stroke medical care using multiple linear regression.


METHODS
A 20 percent random sample of Medicare beneficiaries with an admission to an acute care hospital for stroke during the first six months of 1991, supplemented by data from their Medicare claims and beneficiary records, the Medicare Cost Reports for hospitals and nursing homes, and the Area Resource File.


METHODS
Weighted least squares regression is used to analyze variations in post-stroke practice patterns across 151 MSAs (Metropolitan Statistical Areas). Average post-stroke costs, utilization rates, and facility lengths of stay are regressed on patient and market characteristics.


METHODS
For a six-month post-stroke interval, beneficiary-level post-stroke costs and service utilization are averaged by MSA. Variables describing market conditions are then added to these MSA-level records.


RESULTS
Patient variables rarely explain more than a third of practice variation, and often they explain substantially less than that. Market variables (with some exception) tend to be relatively less important. Finally, one-half to two-thirds of the practice variation across MSAs is unexplained by the patient and market factors measured in our data.


CONCLUSIONS
A substantial portion of inter-MSA variability in utilization and intensity of post-stroke rehabilitation services cannot be explained by differences in patient characteristics. Given the large practice differences observed across MSAs, it seems unlikely that unmeasured patient differences can account for much more of the practice differences.
Lee
A J
AJ
Health Economics Research, Inc., Waltham, MA 02154, USA.
Huber
J H
JH
Stason
W B
WB
D000368:Aged; D000369:Aged, 80 and over; D002561:Cerebrovascular Disorders / Q000534:rehabilitation*; D005260:Female; D017048:Health Care Costs; D006302:Health Services Research; D006760:Hospitalization / Q000191:economics*; D006801:Humans; D016018:Least-Squares Analysis; D007902:Length of Stay; D016014:Linear Models; D008297:Male; D008389:Marketing of Health Services; D006278:Medicare; D010818:Practice Patterns, Physicians' / Q000191:economics* / Q000706:statistics & numerical data*; D012111:Residence Characteristics; D014481:United States