Risk factors for drug dependence among out-patients on opioid therapy in a large US health-care system.
OBJECTIVE
Our study sought to assess the prevalence of and risk factors for opioid drug dependence among out-patients on long-term opioid therapy in a large health-care system.


METHODS
Using electronic health records, we identified out-patients receiving 4+ physician orders for opioid therapy in the past 12 months for non-cancer pain within a large US health-care system. We completed diagnostic interviews with 705 of these patients to identify opioid use disorders and assess risk factors.


RESULTS
Preliminary analyses suggested that current opioid dependence might be as high as 26% [95% confidence interval (CI) = 22.0-29.9] among the patients studied. Logistic regressions indicated that current dependence was associated with variables often in the medical record, including age <65 [odds ratio (OR) = 2.33, P = 0.001], opioid abuse history (OR = 3.81, P < 0.001), high dependence severity (OR = 1.85, P = 0.001), major depression (OR = 1.29, P = 0.022) and psychotropic medication use (OR = 1.73, P = 0.006). Four variables combined (age, depression, psychotropic medications and pain impairment) predicted increased risk for current dependence, compared to those without these factors (OR = 8.01, P < 0.001). Knowing that the patient also had a history of severe dependence and opioid abuse increased this risk substantially (OR = 56.36, P < 0.001).


CONCLUSIONS
Opioid misuse and dependence among prescription opioid patients in the United States may be higher than expected. A small number of factors, many documented in the medical record, predicted opioid dependence among the out-patients studied. These preliminary findings should be useful in future research efforts.
Boscarino
Joseph A
JA
Center for Health Research, Geisinger Health System, Danville, PA 17822-4400, USA. jaboscarino@geisinger.edu
Rukstalis
Margaret
M
Hoffman
Stuart N
SN
Han
John J
JJ
Erlich
Porat M
PM
Gerhard
Glenn S
GS
Stewart
Walter F
WF
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000553:Ambulatory Care / Q000706:statistics & numerical data; D000701:Analgesics, Opioid / Q000009:adverse effects / Q000627:therapeutic use*; D002648:Child; D002649:Child Abuse / Q000706:statistics & numerical data; D002908:Chronic Disease; D019033:Delivery of Health Care, Integrated / Q000706:statistics & numerical data*; D003865:Major Depressive Disorder / Q000453:epidemiology; D011307:Drug Prescriptions / Q000706:statistics & numerical data; D004812:Epidemiologic Methods; D006304:Health Status; D006801:Humans; D008875:Middle Aged; D009293:Opioid-Related Disorders / Q000453:epidemiology* / Q000209:etiology; D010045:Outpatients / Q000706:statistics & numerical data*; D010146:Pain / Q000188:drug therapy* / Q000453:epidemiology; D011619:Psychotropic Drugs / Q000627:therapeutic use; D012720:Severity of Illness Index; D013313:Stress Disorders, Post-Traumatic / Q000453:epidemiology; D014481:United States / Q000453:epidemiology; D055815:Young Adult
D000701:Analgesics, Opioid; D011619:Psychotropic Drugs