Misclassification and selection bias when identifying Alzheimer's disease solely from Medicare claims records.
BACKGROUND
Medicare claims as the basis for health condition adjustments is becoming a method of choice in capitation reimbursement. A recent study has found that claims-based beneficiary classification for Alzheimer's disease produces lower prevalence estimates and higher average costs than previous healthcare cost studies in this population. These sets of studies differ in data sources, period length, and in their specification of dementia.


OBJECTIVE
Participants in the Medicare Alzheimer's Disease Demonstration (MADDE) provide a sample of persons known to have some form of dementia. This group is used to test the adequacy of claims data for identifying eligible cases and any bias in expenditure differences between those flagged or not flagged by a claim in a given period.


METHODS
A prospective cohort design using up to 36 months of claims data.


METHODS
The demonstration enrolled 4166 participants in treatment, and 3942 in a control group in eight communities across the US. Cases were combined in this analysis.


METHODS
Persons with available Medicare Part A & B claims data: those receiving care under fee for service reimbursement were used in the analysis. A total of 5379 MADDE cases received fee for service care during 1991 and 1992, the period of primary interest in the analysis.


METHODS
Client health and functional status interviews and Medicare Part A & B claims.


RESULTS
Less than 20% of MADDE participants were classified with Dementia of the Alzheimer type (DAT) from a single year of claims although 68% had a DAT diagnosis from a referring physician. Annualized expenditures were 1.7 times higher among those with DAT from claims compared with those known otherwise to have dementia but who had not been identified with this condition from Medicare claims.


CONCLUSIONS
Underclassification of dementia from claims records can be partially remedied by increasing the period during which claims are compiled, but additional diagnostic sources will likely be needed to increase prevalence counts closer to 100% of true cases. Risk adjustment based on a single year of reported claims expenditures may overpay providers, at least in the short term, because payment incentives will likely increase prevalence reporting.
Newcomer
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Department of Social and Behavioral Science and the Institute for Health & Aging, University of California, San Francisco 94143-0612, USA.
Clay
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Luxenberg
J S
JS
Miller
R H
RH
D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000145:classification* / Q000175:diagnosis / Q000191:economics; D003953:Diagnosis-Related Groups / Q000191:economics / Q000706:statistics & numerical data; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data*; D008297:Male; D008329:Managed Care Programs / Q000191:economics / Q000706:statistics & numerical data; D006278:Medicare / Q000191:economics / Q000706:statistics & numerical data*; D008875:Middle Aged; D015983:Selection Bias; D014481:United States