Original Research

US National Practice Patterns in Ambulatory Operative Management of Lateral Epicondylitis

Author and Disclosure Information

Lateral epicondylitis is a common cause of elbow pain, frequently responsive to nonoperative management. There are multiple operative techniques for persistently symptomatic patients who have exhausted conservative therapies. Little is known regarding US national trends in operative management of lateral epicondylitis.

We conducted a study to investigate changes in use of ambulatory procedures for lateral epicondylitis. Cases of lateral epicondylitis were identified using the National Survey of Ambulatory Surgery and were analyzed for trends in demographics and use of ambulatory surgery.

Between 1994 and 2006, the population-adjusted rate of ambulatory surgical procedures increased from 7.29 to 10.44 per 100,000 capita. The sex-adjusted rate of surgery for lateral epicondylitis increased by 85% among females and decreased by 31% among males. Most patients were between ages 40 and 49 years, and the largest percentage increase in age-adjusted rates was found among patients older than 50 years (275%) between 1994 and 2006. Use of regional anesthesia increased from 17% in 1994 to 30% in 2006. Private insurance remained the most common payer.

Awareness of the increasing use of ambulatory surgery for lateral epicondylitis may lead to changes in health care policies and positively affect patient care.


 

References

First described by Runge1 in 1873 and later termed lawn-tennis arm by Major2 in 1883, lateral epicondylitis is a common cause of elbow pain, affecting 1% to 3% of the general population each year.3,4 Given that prevalence estimates are up to 15% among workers in repetitive hand task industries,5-7 symptoms of lateral epicondylitis are thought to be related to recurring wrist extension and alternating forearm pronation and supination.8 Between 80% and 90% of patients with lateral epicondylitis experience symptomatic improvement with conservative therapy,9-11 including rest and use of nonsteroidal anti-inflammatory medications,12 physical therapy,13,14 corticosteroid injections,10,15,16 orthoses,17,18 and shock wave therapy.19 However, between 4% and 11% of patients with newly diagnosed lateral epicondylitis do not respond to prolonged (6- to 12-month) conservative treatment and then require operative intervention,11,20,21 with some referral practices reporting rates as high as 25%.22

Traditionally, operative management of lateral epicondylitis involved open débridement of the extensor carpi radialis brevis (ECRB).11,20 More recently, the spectrum of operations for lateral epicondylitis has expanded to include procedures that repair the extensor origin after débridement of the torn tendon and angiofibroblastic dysplasia; procedures that use fasciotomy or direct release of the extensor origin from the epicondyle to relieve tension on the common extensor; procedures directed at the radial or posterior interosseous nerve; and procedures that use arthroscopic techniques to divide the orbicular ligament, reshape the radial head, or release the extensor origin.23 There has been debate about the value of repairing the ECRB, lengthening the ECRB, simultaneously decompressing the radial nerve or resecting epicondylar bone, and performing the procedures percutaneously, endoscopically, or arthroscopically.24-28 Despite multiple studies of the outcomes of these procedures,11,29-31 little is known regarding US national trends for operative treatment of lateral epicondylitis. Understanding national practice patterns and disease burden is essential to allocation of limited health care resources.

We conducted a study to determine US national trends in use of ambulatory surgery for lateral epicondylitis. We focused on age, sex, surgical setting, anesthetic type, and payment method.

Methods

As the National Survey of Ambulatory Surgery32 (NSAS) is an administrative dataset in which all data are deidentified and available for public use, this study was exempt from requiring institutional review board approval.

NSAS data were used to analyze trends in treatment of lateral epicondylitis between 1994 and 2006. NSAS was undertaken by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC) to obtain information about the use of ambulatory surgery in the United States. Since the early 1980s, ambulatory surgery has increased in the United States because of advances in medical technology and cost-containment initiatives.33 The number of procedures being performed in ambulatory surgery centers increased from 31.5 million in 1996 to 53.3 million in 2006.34 Funded by the CDC, NSAS is a national study that involves both hospital-based and freestanding ambulatory surgery centers and provides the most recent and comprehensive overview of ambulatory surgery in the United States.35 Because of budgetary limitations, 2006 was the last year in which data for NSAS were collected. Data for NSAS come from Medicare-participating, noninstitutional hospitals (excluding military hospitals, federal facilities, and Veteran Affairs hospitals) in all 50 states and the District of Columbia with a minimum of 6 beds staffed for patient use. NSAS used only short-stay hospitals (hospitals with an average length of stay for all patients of less than 30 days) or hospitals that had a specialty of general (medical or surgical) or children’s general. NSAS was conducted in 1994, 1996, and 2006 with medical information recorded on patient abstracts coded by contract staff. NSAS selected a sample of ambulatory surgery visits using a systematic random sampling procedure, and selection of visits within each facility was done separately for each location where ambulatory surgery was performed. In 1994, 751 facilities were sampled, and 88% of hospitals responded. In 1996, 750 facilities were sampled, and 91% of hospitals responded. In 2006, 696 facilities were sampled, and 75% responded. The surveys used International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes36 to classify medical diagnoses and procedures. To produce an unbiased national estimate, NCHS used multistage estimate procedures, including inflation by reciprocals of the probabilities of sample selection, population-weighting ratio adjustments, and adjustment for no response.37

Demographic and medical information was obtained for people with an ICD-9-CM diagnosis code of lateral epicondylitis (726.32), using previously described techniques.38 Data were then recorded for age, sex, facility type, insurance type, anesthesia type, diagnoses, and procedures.

Descriptive statistics consisted of means and standard deviations for continuous variables and frequency and percentages for discrete variables. Because NSAS data were collected on the basis of a probabilistic sample scheme, they were analyzed using a sampling weighting method. Sampling weights (inverse of selection probability) provided by the CDC were used to account for unequal sampling probabilities and to produce estimates for all visits in the United States. A Taylor linearization model provided by the CDC estimates was used to calculate standard error and confidence intervals (CIs) of the data. Standard error is a measure of sampling variability that occurs by chance because only a sample rather than the entire universe is surveyed. To define population parameters, NCHS chose 95% CIs along with a point estimate. Direct statistical comparison between years cannot be performed because of sampling differences in the database compared between years. The CIs, however, can suggest statistical differences if the data are nonoverlapping. US census data were used to obtain national population estimates for each year of the study (1994, 1996, 2006).39 Rates were presented as number of procedures per 100,000 standard population. For age, a direct adjustment procedure was used, and the US population in 2000 was selected as the standard population. Applying sex-specific rates to the standard population and dividing by the total in the standard population, we calculated sex-adjusted rates for each year. All data were analyzed using SPSS Version 20 software.

Pages

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