Hysterectomy and Predictors for Opioid Prescription in a Chronic Pain Clinic Sample

Beth D. Darnall, Hong Li
In: Pain Medicine · 2011 · vol. 12(2) , pp. 196–203 · doi:10.1111/j.1526-4637.2010.01038.x · PMID:21223499 · W2113546635
article OA: bronze CC0 ⤵ 3 in-corpus citations
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This study found that hysterectomy and high pain-related dysfunction independently predicted opioid prescription in women aged 18-45 at a chronic pain clinic.

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Abstract

OBJECTIVES: To describe the prevalence of hysterectomy for women aged 18-45 seeking treatment at a chronic pain clinic, to describe patient characteristics (pain intensity, age, smoking status, hormone replacement status, and psychosocial factors) based on opioid and hysterectomy status, and to determine whether hysterectomy status predicted receipt of opioid prescription. DESIGN: Retrospective cross-sectional chart review. PARTICIPANTS: Total 323 new female patients aged 18-45 who completed the Brief Pain Inventory-Short Form at initial evaluation at a chronic pain clinic during a 12-month period (July 2008-June 2009). MEASURES: Data were collected from the Brief Pain Inventory and medical charts. Variables included opioid prescription, average pain intensity, pain type, age, hysterectomy status, smoking status, and pain-related dysfunction across domains measured by the Brief Pain Inventory. The association of opioid prescription with hysterectomy and other factors were determined by logistic regression. RESULTS: Prevalence of hysterectomy was 28.8%. Average pain intensity was not associated with either hysterectomy or opioid prescription status. However, hysterectomy and high levels of pain-related dysfunction were significantly and independently associated with opioid prescription after adjusting for age and pain intensity. More than 85% of women with hysterectomy and high pain-related dysfunction had opioid prescription. CONCLUSIONS: Hysterectomy may confer risk for pain-related dysfunction and opioid prescription in women 45 and younger. More research is needed to understand 1) how patient characteristics influence prescribing patterns and 2) the specific medical risks and consequences of chronic opioid therapy in this population.

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