The utility of administrative data for measuring adherence to cancer surveillance care guidelines.
BACKGROUND
Adherence to professional society guidelines for follow-up or surveillance care in cancer survivors usually is measured with medical record review. Administrative data represent an alternative approach that may encompass larger numbers of patients with relatively low incremental costs.


OBJECTIVE
We sought to determine the feasibility of using claims data to measure guideline adherence.


METHODS
By reviewing paper and electronic medical records and claims data of 429 patients with 1 of 5 common cancers who received treatment with curative intent, we compared specific procedure receipt as well as guideline adherence classification as derived from claims and medical record data. Concordance was measured via kappa statistics.


METHODS
Care in the initial 18-month follow-up period was characterized as less than recommended, recommended, or greater than recommended per practice guidelines in both medical record and administrative data.


RESULTS
Matching rates for individual procedures varied and were generally highest for certain laboratory tests and lowest for physical examinations. There were generally good-to-excellent levels of agreement (kappa=0.34-0.96) between a patient's classification in claims data and medical record data. No consistent differences in agreement were observed according to insurance type.


CONCLUSIONS
In general, claims data capturing procedures and visit use for characterizing guideline adherence was comparable with what was documented in the medical record and suggests that if validated in other settings, administrative data could be used to describe patterns of follow up care.
Cooper
Gregory S
GS
Case Western Reserve University, Cleveland, Ohio 44106-5066 and Henry Ford Health System, Detroit, Michigan, USA. Greg.Cooper@cwru.edu
Schultz
Lonni
L
Simpkins
Janine
J
Lafata
Jennifer Elston
JE
D003131:Combined Modality Therapy; D005260:Female; D019983:Guideline Adherence; D006801:Humans; D007345:Insurance Claim Review; D008297:Male; D016347:Medical Records Systems, Computerized; D008875:Middle Aged; D009369:Neoplasms / Q000145:classification / Q000175:diagnosis / Q000628:therapy*; D011159:Population Surveillance / Q000379:methods*; D017410:Practice Guidelines as Topic; D012042:Registries; D012720:Severity of Illness Index