Factors influencing the prescription of drugs of different price levels.
OBJECTIVE
Socioeconomic factors have been suggested to influence the prescribing of newer and more expensive drugs. In the present study, individual and health care provider factors were studied in relation to the prevalence of differently priced drugs.


METHODS
Register data for dispensed drugs were retrieved for 18 486 individuals in a county council in Sweden. The prevalence of dispensed drugs was combined with data for the individual's gender, age, education, income, foreign background, and type of caregiver. For each of the diagnostic groups (chronic obstructive pulmonary disease [COPD], depression, diabetes, and osteoporosis), selected drugs were dichotomized into cost categories, lower and higher price levels. Univariate and multivariate logistic regressions were performed using cost category as the dependent variable and the individual and provider factors as independent variables.


RESULTS
In all four diagnostic groups, differences were observed in the prescription of drugs of lower and higher price levels with regard to the different factors studied. Age and gender affected the prescription of drugs of lower and higher price levels more generally, except for gender in the osteoporosis group. Income, education, foreign background, and type of caregiver affected prescribing patterns but in different ways for the different diagnostic groups.


CONCLUSIONS
Certain individual and provider factors appear to influence the prescribing of drugs of different price levels. Because the average price for the cheaper drugs versus more costly drugs in each diagnostic group was between 19% and 69%, there is a risk that factors other than medical needs are influencing the choice of drug.
School of Health and Caring Sciences, Linnaeus University, Kalmar, Sweden. birgitta.semark@lnu.se
Birgitta
B
Semark
Sven
S
Engström
Lars
L
Brudin
Sven
S
Tågerud
Kerstin
K
Fredlund
Lars
L
Borgquist
Göran
G
Petersson
D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000928:Antidepressive Agents / Q000191:economics; D050071:Bone Density Conservation Agents / Q000191:economics; D003362:Cost-Benefit Analysis; D016527:Drug Costs; D004363:Drug Utilization / Q000191:economics; D017723:Drug Utilization Review; D005260:Female; D006801:Humans; D007004:Hypoglycemic Agents / Q000191:economics; D007348:Insurance, Health / Q000191:economics; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D017891:Pharmacoepidemiology; D010818:Practice Patterns, Physicians' / Q000191:economics*; D055553:Prescription Drugs / Q000191:economics*; D012042:Registries; D019141:Respiratory System Agents / Q000191:economics; D012737:Sex Factors; D012959:Socioeconomic Factors; D013548:Sweden
D000928:Antidepressive Agents; D050071:Bone Density Conservation Agents; D007004:Hypoglycemic Agents; D055553:Prescription Drugs; D019141:Respiratory System Agents