The impact of non-fee-for-service reimbursement on chronic disease surveillance using administrative data.
OBJECTIVE
Use of physician service claims and other administrative data is increasingly being advocated for chronic disease surveillance. However, such data may be vulnerable to reimbursement policy changes. We sought to determine how non-fee-for-service (non-FFS) primary care affects the detection of diabetes using physician claims data.


METHODS
Ontarians over age 66 with diabetes and receiving care in a non-FFS setting were identified using prescription claims for glucose-lowering drugs written by non-FFS physicians. We compared the date of incident treatment in this cohort with the diagnosis date in the Ontario Diabetes Database, a validated administrative data algorithm to detect persons with diabetes. We assessed the rate of detection and, among detected cases, whether detection was late (more than 6 months after the index prescription). Survival methods were used to assess detection over time.


RESULTS
Only 49.7% of prescription-defined diabetes cases were detected within six months of the index prescription; 23.7% remained undetected after up to nine years of follow-up. Detected individuals had higher rates of hospitalization for vascular complications than missed cases (15.1% vs 4.8%, p < 0.0001), suggesting that they were at a more advanced stage of disease.


CONCLUSIONS
Non-FFS reimbursement arrangements for primary care physicians appear to undermine the utility of administrative data for chronic disease surveillance, leading to both decreased sensitivity and biased detection. Provisions for alternative means to collect diagnostic information should be considered as these arrangements are introduced.
Alshammari
Abdulmuhsen M
AM
Department of Medicine, University of Toronto, Toronto, ON.
Hux
Janet E
JE
D000368:Aged; D003920:Diabetes Mellitus / Q000188:drug therapy / Q000453:epidemiology*; D006801:Humans; D007345:Insurance Claim Review; D009864:Ontario; D011159:Population Surveillance / Q000379:methods*; D012051:Reimbursement Mechanisms