Cost-benefit analysis of a new alcohol biomarker, carbohydrate deficient transferrin, in a chronic illness primary care sample.
BACKGROUND
Carbohydrate Deficient Transferrin (CDT) is a new alcohol biomarker recently approved by the Food and Drug Administration for alcohol screening. Limited information is available on the economic benefits of alcohol biomarkers. Our objective was to conduct a cost-benefit analysis (CBA) of the CDT test in a primary care sample of patients being treated for diabetes and hypertension.


METHODS
A decision tree was created using data from national surveys, published literature, and two brief intervention trials conducted in primary care settings. The decision tree was used to estimate the costs and benefits of CDT under different scenarios.


RESULTS
For the base case, utilizing CDT in addition to patient self-report resulted in an increase from 28 to 53 problem drinking cases identified out of 70 cases screened. With increased detection and subsequent intervention, the average medical and legal costs were far lower in the CDT arm of the study. When these avoided costs were incorporated into the model, an overall savings of $212.30 per patient was realized with CDT testing. Monte Carlo analysis also indicated a trend toward cost savings, with a mean cost savings of approximately $353 and a range of $1,619 in savings to $450 in costs for 1,000 simulations of the decision tree model.


CONCLUSIONS
This CBA suggests that the addition of routine CDT screening to patient self-report may provide positive net economic benefits in primary care settings.
Dillie
Kathryn Sullivan
KS
Medical Scientist Training Program, Department of Family Medicine, University of Wisconsin, Madison, WI 53562, USA.
Mundt
Marlon
M
French
Michael T
MT
Fleming
Michael F
MF
D000328:Adult; D000428:Alcohol Drinking / Q000097:blood / Q000523:psychology; D000437:Alcoholism / Q000097:blood / Q000175:diagnosis*; D015415:Biomarkers / Q000032:analysis* / Q000097:blood; D002908:Chronic Disease; D017046:Cost Savings / Q000706:statistics & numerical data; D017281:Cost of Illness; D003362:Cost-Benefit Analysis; D003663:Decision Trees; D003920:Diabetes Mellitus / Q000097:blood; D005260:Female; D017048:Health Care Costs; D006304:Health Status; D006801:Humans; D006973:Hypertension / Q000097:blood; D008297:Male; D008403:Mass Screening / Q000191:economics* / Q000295:instrumentation / Q000706:statistics & numerical data; D009010:Monte Carlo Method; D011320:Primary Health Care / Q000191:economics; D012680:Sensitivity and Specificity; D014168:Transferrin / Q000031:analogs & derivatives* / Q000032:analysis
D015415:Biomarkers; D014168:Transferrin; C056759:carbohydrate-deficient transferrin