Changing Practice Patterns of Deep Brain Stimulation in Parkinson's Disease and Essential Tremor in the USA
ABSTRACT Randomized controlled studies have shown deep brain stimulation (DBS) to be an effective treatment for Parkinson's disease (PD). Outside of large-center studies, little is known about trends in DBS use in the USA.
We employ the Nationwide Inpatient Sample to look at changes in DBS utilization over time.
We identified all individuals with PD (332.0) and essential tremor (ET) (333.1) who underwent DBS (02.93) from 1998 to 2007. We examined demographics, hospital status, comorbidities, and in-hospital systemic/technical complications. DBS patients from 2000 and 2007 were compared using χ(2) tests.
PD patients from the 2007 sample who underwent DBS were older (p = 0.01). Both ET and PD patients had significantly more comorbidities in 2007 (p < 0.001). In-hospital complications decreased from 3.8 to 2.8%. DBS was performed in medium- or high-volume centers in 70% of cases in 2000 and in 50% in 2007. In all groups, a majority of cases (range 65-71%) underwent DBS at hospitals in the western and southern USA.
Patients who underwent DBS in the 2007 sample were older and had more comorbidities than those in the 2000 sample; in-hospital complications remained low. Understanding trends in DBS is helpful in assessing how the technology is adopted and what relationships should be further explored.
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ABSTRACT: IMPORTANCE African American individuals experience barriers to accessing many types of health care in the United States, resulting in substantial health care disparities. To improve health care in this patient population, it is important to recognize and study the potential factors limiting access to care. OBJECTIVE To examine deep brain stimulation (DBS) use in Parkinson disease (PD) to determine which factors, among a variety of demographic, clinical, and socioeconomic variables, drive DBS use in the United States. DESIGN, SETTING, AND PARTICIPANTS We queried the Nationwide Inpatient Sample in combination with neurologist and neurological surgeon countywide density data from the Area Resource File. We used International Classification of Diseases, Ninth Revision codes to identify discharges of patients at multicenter, all-payer, nonfederal hospitals in the United States diagnosed with PD (code 332.0) who were admitted for implantation of intracranial neurostimulator lead(s) (code 02.39), DBS. MAIN OUTCOMES AND MEASURES We analyzed factors predicting DBS use in PD using a hierarchical logistic regression analysis including patient and hospital characteristics. Patient characteristics included age, sex, comorbidity score, race, income quartile of zip code, and insurance type. Hospital characteristics included teaching status, size, regional location, urban vs rural setting, experience with DBS discharges, year, and countywide density of neurologists and neurological surgeons. RESULTS Query of the Nationwide Inpatient Sample yielded 2 408 302 PD discharges from 2002 to 2009; 18 312 of these discharges were for DBS. Notably, 4.7% of all PD discharges were African American, while only 0.1% of DBS for PD discharges were African American. A number of factors in the hierarchical multivariate analysis predicted DBS use including younger age, male sex, increasing income quartile of patient zip code, large hospitals, teaching hospitals, urban setting, hospitals with higher number of annual discharges for PD, and increased countywide density of neurologists (P < .05). Predictors of nonuse included African American race (P < .001), Medicaid use (P < .001), and increasing comorbidity score (P < .001). Countywide density of neurological surgeons and Hispanic ethnicity were not significant predictors. CONCLUSIONS AND RELEVANCE Despite the fact that African American patients are more often discharged from hospitals with characteristics predicting DBS use (ie, urban teaching hospitals in areas with a higher than average density of neurologists), these patients received disproportionately fewer DBS procedures compared with their non-African American counterparts. Increased reliance on Medicaid in the African American population may predispose to the DBS use disparity. Various other factors may be responsible, including disparities in access to care, cultural biases or beliefs, and/or socioeconomic status.01/2014; 71(3). DOI:10.1001/jamaneurol.2013.5798
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ABSTRACT: This article focuses on the evolution of deep brain stimulation (DBS) targets within the brain, beginning with the discovery of DBS's potential in non-Parkinson disease movement disorders. DBS has gained in popularity and applicability for a growing number of neuropathologic conditions with neural network disorders and dysfunction. Targets within the brain have been based frequently on historical sites used for ablative surgeries in years past, derived from experiment and experience but also have arisen via elucidation of neural networks, transmitter function and location, disease neuropathology, and also, fortuitous discovery.Neurologic Clinics 08/2013; 31(3):809-26. DOI:10.1016/j.ncl.2013.03.008 · 1.61 Impact Factor
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ABSTRACT: Object The aim of this study was to analyze the incidence of adverse outcomes, complications, inpatient mortality, length of hospital stay, and the factors affecting them between academic and nonacademic centers after deep brain stimulation (DBS) surgery for Parkinson's disease (PD). The authors also analyzed the impact of various factors on the total hospitalization charges after this procedure. Methods This is a retrospective cohort study using the Nationwide Inpatient Sample (NIS) from 2006 to 2010. Various patient and hospital variables were analyzed from the database. The adverse discharge disposition and the higher cost of hospitalization were taken as the dependent variables. Results A total of 2244 patients who underwent surgical treatment for PD were identified from the database. The mean age was 64.22 ± 9.8 years and 68.7% (n = 1523) of the patients were male. The majority of the patients was discharged to home or self-care (87.9%, n = 1972). The majority of the procedures was performed at high-volume centers (64.8%, n = 1453), at academic institutions (85.33%, n = 1915), in urban areas (n = 2158, 96.16%), and at hospitals with a large bedsize (86.6%, n = 1907) in the West or South. Adverse discharge disposition was more likely in elderly patients (OR > 1, p = 0.011) with high comorbidity index (OR 1.508 [95% CI 1.148-1.98], p = 0.004) and those with complications (OR 3.155 [95% CI 1.202-8.279], p = 0.033). A hospital with a larger annual caseload was an independent predictor of adverse discharge disposition (OR 3.543 [95% CI 1.781-7.048], p < 0.001), whereas patients treated by physicians with high case volumes had significantly better outcomes (p = 0.006). The median total cost of hospitalization had increased by 6% from 2006 through 2010. Hospitals with a smaller case volume (OR 0.093, p < 0.001), private hospitals (OR 11.027, p < 0.001), nonteaching hospitals (OR 3.139, p = 0.003), and hospitals in the West compared with hospitals in Northeast and the Midwest (OR 1.885 [p = 0.033] and OR 2.897 [p = 0.031], respectively) were independent predictors of higher hospital cost. The mean length of hospital stay decreased from 2.03 days in 2006 to 1.55 days in 2010. There was no difference in the discharge disposition among academic versus nonacademic centers and rural versus urban hospitals (p > 0.05). Conclusions Elderly female patients with nonprivate insurance and high comorbidity index who underwent surgery at low-volume centers performed by a surgeon with a low annual case volume and the occurrence of postoperative complications were correlated with an adverse discharge disposition. High-volume, government-owned academic centers in the Northeast were associated with a lower cost incurred to the hospitals. It can be recommended that the widespread availability of this procedure across small, academic centers in rural areas may not only provide easier access to the patients but also reduces the total cost of hospitalization.Neurosurgical FOCUS 11/2013; 35(5):E2. DOI:10.3171/2013.8.FOCUS13295 · 2.14 Impact Factor