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Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings
Journal of Clinical Neuroscience xxx (xxxx) xxx
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Clinical study
Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings Michael Fana a,⇑, Gregory Everett a, Thomas Fagan a, Megan Mazzella a, Sulmaz Zahedi a, John M. Clements b a b
Central Michigan University College of Medicine, Mount Pleasant, MI, USA Michigan State University, Division of Public Health, College of Human Medicine, Flint, MI, USA
a r t i c l e
i n f o
Article history: Received 29 July 2019 Accepted 25 August 2019 Available online xxxx Keywords: Rural patients Urban patients Deep brain stimulation Hospital stay Routine disposition Hospital costs
a b s t r a c t Presently, disparities exist between race, sex, socioeconomic status, hospitals, income, comorbidities, and insurance profiles of patients undergoing DBS surgery. Here, we aim to highlight several variables and their predictive powers of DBS surgery outcomes as measured by discharge location, length of hospital stays, and total hospital charges. A retrospective cohort study using discharge data from NIS and HCUP for analyses and regression model statistics is performed. Comparative analyses demonstrate urban patients were more often non-routinely discharged, possessed private insurance, and accrued greater hospital costs compared to rural patients. Moreover, regression analyses predicts urban patients have 70% lower odds of routine discharge while those with a major loss of function prior to surgery also have 81% lower odds of routine discharge compared to those with minor loss of function. Ultimately, our study found urban patients or patients with major illnesses have higher hospital charges, longer hospitalization, and more often non-routinely discharged. Ó 2019 Elsevier Ltd. All rights reserved.
1. Introduction Deep brain stimulation (DBS) is a minimally invasive neurologic surgical intervention using implanted pacemakers to electrically stimulate deep brain structures such as the Globus pallidus internus or the subthalamic nucleus. It is often used as a treatment option for Parkinson’s disease but has applications for other movement disorders and neurological diseases such as Tourette’s, obsessive–compulsive disorder, major depression, and chronic pain [1]. The risks associated with DBS are low but may include intracranial bleeding, infection, malposition, and hardware issues, such as migration, disconnection, or malfunction [2]. Presently, several barriers exist to its therapeutic application, including the initial cost of the implanted hardware, which approximates $65,000 along with battery replacements as an added $10,000 to $20,000 in the first 36 months, and hospitals lacking necessary equipment and technology to offer the operation [3]. Several studies report disparities in the use of DBS between groups based on race, gender, and income status. For instance,
⇑ Corresponding author at: 1820 S Crawford Road Apt C2, Mount Pleasant, MI 48858, USA. E-mail address: [email protected] (M. Fana).
Willis et al. (2014) examined socioeconomic, clinical, and practice factors in 657,000 Medicare beneficiaries with Parkinson’s disease indicated for DBS surgery for patients from 2007 to 2009. They found that black and Asian populations were less likely to receive DBS than white patient populations. Furthermore, women had lower odds of receiving DBS than men and patients from higher socioeconomic societies were 40% more likely to receive DBS [4]. Another study conducted by Chan et al. (2014) found a significantly higher proportion of African Americans discharged with Parkinson’s without receiving DBS when compared to nonAfrican American counterparts [5]. In addition, previous studies suggest there are racial and ethnic disparities in neurologic health care access and utilization in the United States. A study by Saadi, Himmelstein, Woolhandler, and Mejia (2017) analyzed data from the 2006–2013 Medical Expenditure Panel Survey (MEPS) and concluded that those who identified as black or Hispanic and as having a neurologic disorder were less likely to receive outpatient-based neurology visits than their white counterparts [6]. Additionally, their analysis found gaps in care for poor, uninsured, and less-educated Americans. Hemming et al. (2011) examined potential disparities in those diagnosed with Parkinson’s disease and receiving treatment in tertiary Movement Disorder Centers. They found that African Americans had greater
https://doi.org/10.1016/j.jocn.2019.08.117 0967-5868/Ó 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: M. Fana, G. Everett, T. Fagan et al., Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.08.117
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M. Fana et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx
Parkinsonian disease severity and disability than whites, and significant differences in management were also seen based on race and socioeconomic status [7]. Sharma et al. (2013) analyzed correlations between adverse outcomes, complications, mortality, and extended hospital stay related to DBS in teaching and non-teaching hospitals. Elderly female patients with comorbidities and non-private insurance had poorer prognoses, particularly when undergoing surgery at low-volume centers with physicians managing low case volumes. Furthermore, high-volume and government-owned teaching hospitals in the Northeast were associated with a lower hospital cost and thus, potentially, lower costs for patients [8]. As suggested, many underlying factors exist which account for some of the variations observed in patient outcomes post-operatively for DBS surgery, namely: age, sex, race, post-operative conditions, insurance profile, income, and severity of illness. Our goal is to describe these factors in a national cohort and identify their impact on outcomes for patients from rural and urban locations. We examined DBS surgery outcomes for patients in rural and urban locations based on discharge records from the 2012 National Inpatient Sample (NIS). We hypothesize that patients from rural and urban geographic origins have different outcomes as measured by patient discharge location (i.e. routine being place of residence or home and non-routine being an institution), length of hospital stay, and total hospital charges after receiving DBS operations. 2. Methods This IRB exempt, retrospective cohort study examines disparities in outcomes of patients undergoing DBS surgery for Parkinson’s disease between groups based on urban or rural patient
location. We use discharge data from the 2012 National Inpatient Sample (NIS), Healthcare Cost and Utilization Project (HCUP), Agency for Healthcare Research and Quality [9]. The 2012 HCUP NIS database includes 7,296,968 discharge cases. Discharge records include up to 25 ICD-9 Diagnosis codes and 15 Healthcare Common Procedure Coding System (HCPCS) codes. We selected all discharges with an HCPCS DBS procedure code of 02.93 in any of the procedure code variables. The first diagnosis code is generally considered the primary diagnosis for that hospital stay. We included discharges for patients with a diagnosis of Parkinson’s (ICD-9: 332, 332.0, and 332.1). Subsequently, we excluded a Parkinson’s diagnosis of 332.1 as there was only one discharge with this diagnosis, and there were no codes of 332, the broader code for Parkinson’s Disease. Ultimately, our data includes only discharges with the ICD-9 code 332.0 – Parkinson’s Disease – Paralysis agitans. The use of NIS data requires a weighting procedure to make reliable national estimates [10]. Therefore, the final sample size is 3,005. All results reflect the use of the weighting procedure. Independent variables collected for analysis include the following: patient age (in years at admission), sex (male or female), number of chronic conditions at admission, insurance status (excluding self-pay, no charge, and others), patient location (rural and urban based on Ingram and Franco (2012)) [11], race (white and nonwhite), income (based on national quartiles), and severity of illness (categorized as: no class specified, minor loss of function, moderate loss of function, major loss of function, and extreme loss of function). We ran independent t-tests to compare means between groups for continuous variables and chi-square to test differences between proportions between groups (with z-test for proportions to test for differences in specific group category proportions). Finally, we ran regression models with routine disposition (binary logistic), total
Table 1 National Inpatient Sample Discharges with DBS Procedure and Parkinson’s Diagnosis, n = 3005#
Variable Dependent Variables Disposition of Patient Routine (Home or other place of residence) Not Routine (short-term stay, skilled nursing, etc.) Length of Stay – days^ Total Charges^ Independent Variables Age^ Sex Male Female Number of Chronic Conditions^ Insurance (n = 2,955) Public Insurance (Medicaid/Medicare) Private Insurance (including HMO) Patient Location (n = 2,990) Urban Rural Race (n = 2,835) White Non-white Income (n = 2,930) 1st Quartile (Lowest) 2nd Quartile 3rd Quartile 4th Quartile (Highest) Severity of Illness Subclass Minor loss of function Moderate loss of function Major loss of function Extreme loss of function * #
Total
Rural
Urban
# (%)
# (%)
# (%)
2,635 (87.7) 370 (12.3) 1.81, 2.28 $77,050, $46,280
475 (94.1) 30 (5.9) 1.54, 1.38 $66,873, $33,611
2145 (86.3)* 340 (13.7)* 1.86, 2.42 $79,111, $48,310
c2 = 23.20, p < 0.001
63.8, 9.5
64.6, 8.0
63.8, 9.8
t = 1.97, p = 0.051
1,000 (33.3) 2,005 (66.7) 3.6, 2.2
330 (65.3) 175 (34.7) 3.8, 2.4
1,665 (67.0) 820 (33.0) 3.5, 2.1
c2 = 0.518, p = 0.472
935 (31.6) 2,020 (68.4)
380 (75.2) 125 (24.8)
1,640 (67.2)* 800 (32.8)*
c2 = 12.54, p < 0.001
2,485 (83.1) 505 (16.9)
— —
— —
— —
2,375 (83.8) 460 (16.2)
415 (94.3) 25 (5.7)
1,955 (82.1)* 425 (17.9)*
c2 = 41.05, p < 0.001
540 650 805 935
225 (47.4) 185 (38.9) 55 (11.6) 10 (2.1)
315 465 750 925
c2 = 539.4, p < 0.001
375 (74.3) 115 (22.8) 15 (3.0) 0 (0.0)
1,900 (76.5) 510 (20.5) 60 (2.4) 15 (0.6)
(18.4) (22.2) (27.5) (31.9)
2,285 (76.0) 630 (21.0) 75 (2.5) 15 (0.5)
(12.8)* (18.9)* (30.5)* (37.7)*
Significance
t = -2.85, p = 0.004 t = -6.72, p < 0.001
t = 2.56, p = 0.010
c2 = 539.4, p < 0.001
In addition to significant Chi-square, column proportion difference between rural and urban is statistically significant at p < 0.05. Sample size unless otherwise indicated for specific variables, ^ mean, standard deviation.
Please cite this article as: M. Fana, G. Everett, T. Fagan et al., Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.08.117
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M. Fana et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx Table 2 Regressions Predicting Patient Disposition, Total Charges, and Length of Stay. Logistic Regression Predicting Routine Disposition Variable R-square Constant Age Female (Reference: Male) Number of Chronic Conditions Public Insurance (Reference: Private Insurance) Urban Patient Location (Reference: Rural) White Race (Reference: Non-white) Income (Reference: 1st Quartile – lowest) 2nd Quartile 3rd Quartile 4th Quartile (Highest) Severity of Illness Subclass (Reference: Minor loss) Moderate loss of function Major loss of function Extreme loss of function
b (SE) 0.114 5.28 (0.494)*** –0.026 (0.007)** –0.354 (0.122)*** –0.108 (0.0.28)*** –0.567 (0.161)*** 1.203 (0.240)*** 0.299 (0.158)
Odds Ratio (95% CI)
0.378 (0.198) 0.471 (0.192)* 0.195 (0.180)
1.46 (0.990, 2.15) 1.60 (1.10, 2.33) 1.22 (0.854, 1.72)
–0.314 (0.143)* 1.66 (0.293)*** –0.843 (0.566)
0.731 (0.552, 0.967) 0.190 (0.107, 0.337) 0.431 (0.142, 1.31)
0.702 (0.553, 0.891) 0.567 (0.413, 0.779) 0.300 (0.187, 0.481) 1.35 (0.990, 1.84)
Linear Regression Predicting Total Charges
Linear Regression Predicting Length of Stay
b (Standardized) 0.037 56,879*** 0.028 –0.012 0.017 –0.108*** 0.095*** –0.033 –0.022 — — — 0.136*** — —
b (Standardized) 0.225 2.116*** 0.075*** 0.012 0.012 0.001 0.047* –0.010 0.024 — — — 0.460*** — — —
*p < 0.05, **p < 0.01, ***p < 0.001.
charges (linear regression), and length of stay (linear regression) as the dependent variables. The results of these tests are displayed in Tables 1 and 2.
3. Results The descriptive results characterizing our cohort, as well as comparisons between urban and rural groups for each of our variables, are shown in Table 1. Results of the binary logistic regression and linear regression are included in Table 2. The mean age of patients in rural and urban populations undergoing DBS procedure is 63.8 ± 9.5. Altogether, no significant difference was found between male and female population sizes in urban and rural populations, however twice as many females were found to undergo the procedure (66.7% versus 33.3%). Finally, greater proportions of white people receive DBS compared to non-whites (83.8% versus 16.2%) (p < 0.001). Our primary analyses show several notable distinctions between rural and urban populations. First, urban patients were non-routinely discharged (i.e. did not go home or to place of residency) more often than rural patients (13.7% versus 5.9%, p < 0.001). Moreover, urban patients have a longer length of stay in hospitals post-operatively, by approximately 8 h, compared to rural patient populations (1.86 days versus 1.54 days, p = 0.004). Additionally, a wide discrepancy is found in total average charges between urban and rural populations of approximately $79,000 and $67,000 (p < 0.001), respectively. The results of our regression analyses identified several factors that impact patient disposition. First, urban patients are at 70% lower odds to be routinely discharged home compared to rural patients (OR = 0.300, 95% CI = 0.187–0.481). This result corresponds to our finding that there are significant differences in the proportions of urban and rural patients being non-routinely discharged. Next, compared to patients with minor loss of function prior to surgery, patients discharged with major loss of function prior to surgery have 81% lower odds of routine discharge (OR = 0.190, 95% CI = 0.107–0.337), while those with moderate loss of function prior to surgery have 26.9% lower odds of routine discharge (OR = 0.731, 95% CI = 0.552–0.967). Patients with public insurance (Medicaid or Medicare) have 43.3% lower odds of being routinely discharged compared to those with private insurance (OR = 0.567, 95% CI = 0.413–0.779). Females, when compared to males, have 30% lower odds of routine disposition (OR = 0.702,
95% CI = 0.553–0.891). Finally, younger patients are more likely to have routine disposition than older patients. With regards to finances and insurance, a greater proportion of urban patients had private insurance compared to rural patient populations (32.8% versus 24.8%). Income discrepancy is also present between rural and urban patients. Most rural patients (86.3%) receiving DBS surgery are in the lower 1st and 2nd quartile for income whereas most patients of urban geography are in the 3rd and 4th upper quartile of income (68.2%). Regression analysis of total hospital charges shows that patients with private insurance have higher total charges for DBS surgery compared to those with public insurance. Similarly, urban patients have slightly higher hospital charges compared to rural patients. Finally, patients with a more severe state of illness, as measured by loss of function, have higher charges for DBS operation. Lastly, regarding length of stay, our regression analysis indicated that older patients, urban patients, and those with greater severity of illness have a longer length of stay compared to patients that are younger, rural, and have lower severity of illness, respectively. It is also notable that we found no difference in the mean number of chronic conditions presented by patients of urban and rural populations. To summarize, our results demonstrate that urban patients were more often non-routinely discharged, possessed private insurance, had a higher average charge for operation, higher income, and longer length of hospital stay compared to rural patients. Urban patients had lower odds of routine discharge, as did those presenting with a major or moderate loss of function prior to surgery. Patients from urban locations are predicted to have higher charges for operation and longer hospital stays than their rural counterparts. We also identified the following factors that increased odds for routine discharge: rural patient location, public insurance, younger age, and female sex. On the other hand, patients with higher severity of illness are less likely routinely discharged.
4. Discussion We conducted a retrospective cohort study of patients receiving DBS surgery for Parkinson’s disease to determine disparities in outcomes based rural and urban patient location. In addition, we considered the influence of sex, race, loss of function prior to surgery, age, insurance and income. Here, we will discuss the implications of these results and situate these findings relative to other research.
Please cite this article as: M. Fana, G. Everett, T. Fagan et al., Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.08.117
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M. Fana et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx
We found that rural patients discharged had greater odds of routine discharge compared to urban patients, however few investigations have been made into the possible etiology behind the discrepancy. Nonetheless, in some post-surgical circumstances, patients can return home after hospitalization and continue with care provided by family, while many others will require postacute care (PAC) for rehabilitation and recuperation to help improve patient recovery. Forms of PAC include inpatient rehabilitation, skilled nursing facilities, long-term care hospitals, and home health care. Some studies suggest that inpatient rehabilitation is the superior option amongst other PAC discharge locations for recovery [12]. One theory for the difference in routine discharge between rural and urban patients is that while rural patients qualify for post-operative care at rehabilitation facilities, they may be sent home with the assumption that such centers exist in their hometown. However, many rural areas have less access to established care centers [13]. Furthermore, the distance that rural patients would need to travel to reach a nearby center is likely too far for practical use of service given the likelihood that these centers are commonly established in more urban areas. Clearly, several PAC options are not available for patients from rural areas due to lack of services situated in their areas and the long distances patients must travel. These factors may make it less likely that rural patients pursue post-discharge care. Interestingly, we found that women made up a greater proportion of our cohort. Prior research has also shown that women receive more DBS surgery treatment for Parkinson’s disease despite the 1.5–2 times increased frequency of Parkinson’s disease in men. Postulated explanations for this difference are as follows: more toxin exposure, head trauma, mitochondrial dysfunction, or X-linked genetic factors in men or greater neuroprotection by estrogen in women [14]. Furthermore, there are differences in the presentation of Parkinson’s disease between men and women; women are diagnosed on average 2.1 years later than men (53.4 vs. 51.3 years, respectively) and more often present with tremors as opposed to bradykinesia and rigidity [15]. The delay in disease onset could be due in part to the high levels of striatal dopamine from estrogen activity. This may result in the lower incidence and higher age of onset in women as well as the more frequent tremors [16]. Moreover, men list more symptoms on average than women; meanwhile, women are more likely to report that their symptoms cause anxiety and depression. Therefore, there is a propensity for greater social acceptance of the disease and report of its symptoms by female patients which may explain why women opt for DBS surgery procedures more often than men. Nevertheless, studies of post-operative assessments of mental health for DBS surgery for men and women showed no difference between the sexes [15]. In one study by Accolla et al. (2007), no differences were found between men and women for DBS surgery pre-operative severity of disease (i.e. tremor, rigidity, or ADLs) [17]. However, women were found to have more severe dyskinesias and non-responsive bradykinesias. This may bring in to question the efficacy of DBS surgery treatment for men and women, however a cohort study by Chandran et al. (2014) has shown that subthalamic DBS surgery is equally efficacious in both men and women [18]. Therefore, women are likely to be treated more often because of the more severe dyskinesia symptoms and are prone to experiencing less emotional well-being. As a result, earlier surgical treatment for women may be more beneficial and may explain the findings here of more women receiving DBS surgery treatment. Regarding race, we found that white patients received DBS surgery more often than non-white patients. Similarly, studies such as those highlighted before by Willis et al. (2014) have also found white people to receive DBS surgery more often than black populations for Parkinson’s disease.4 This may be due to black people having higher rates of cognitive impairments, dementia, or other
comorbidities among the elderly with Parkinson’s disease that may be contraindicated for DBS surgery [19]. Moreover, minority patients with Parkinson’s disease are more likely to receive care from a provider that is unlikely or unable to perform or refer their patient to a clinic for DBS surgery operation. In fact, according to a Nationwide Inpatient Sample of the 2.4 million Parkinson’s disease discharges from 2002 to 2009, 4.7% of them were African American while only 0.1% of DBS surgery for Parkinson’s disease discharges were African American [5]. Factors such as younger age, male sex, increasing income quartile, larger hospital, teaching hospital, urban setting, hospitals with greater discharges for Parkinson’s disease, and increased country-wide density of neurologists increased the chances of DBS surgery operation. Meanwhile, non-use of DBS surgery was predicted with African American race, Medicaid coverage, and increasing co-morbidity scores. Many African American patients are discharged with Parkinson’s disease whose patient characteristics would predict the use of DBS surgery, and who would benefit from the DBS surgery, but are nonetheless approximately eight times less likely to get this treatment. Medicare coverage amongst African American populations appears to predispose them to the DBS surgery non-use decision [5]. Other factors may include disparities in access to care, cultural biases or beliefs, and socioeconomic status, which require further investigations. Our research also identified that patients with severe preoperative loss of function are at lower odds for routine discharge, likely because they are at higher risk of further injury postoperatively. This is not surprising giving the need for close monitoring of such patients post-operatively until they are deemed appropriate for routine discharge. We have also uncovered an association between the severity of a DBS surgery patient’s illness and their total charges for treatment. This is consistent with our initial expectations; more severely ill patient populations generally require more comprehensive care [20]. It is worth mentioning that DBS surgery itself is a safe treatment option and operation for patients with Parkinson’s disease. This surgical procedure has been used for the past 20 years with great success. In one study by Chen (2018), a surgeon’s post-operative patient outcomes were followed between 2004 and 2017 for 103 patients. Major complaints by the surgeon’s patients were fever, constipation, nausea, headache, and wound pain, all concerns that are not atypical to general postoperative and post-anesthesia side effects. Some rare postoperative intracranial hemorrhages and epidural hematomas were identified as well [21]. Therefore, this operation is generally a safe procedure for which patients can be routinely discharged, but we speculate that patients of urban populations may utilize the option by their surgeon for post-operative non-routine discharge as a precautionary measure. We observed young patients are routinely discharged more often compared to older patients. Available data involving the elderly on post-operative DBS complications and outcomes are conflicting. Although there is no specific age cut-off, most clinical studies have excluded patients older than 75 years old. In one study by DeLong et al. (2014), the stepwise effect of increasing age on short term complications following DBS surgery was evaluated [22]. It was found that older patients (i.e. older than 75 years) showed a similar 90-day complication risk compared with younger counterparts. Whereas another study by Bouwyn et al. (2016) compared early post-operative outcomes in patients younger than 65 years old versus patients older than 65 years old and it was found that DBS surgery had a more negative impact on cognitive functions in elderly patients [23]. Therefore, it may be the case that increased rates of post-operative complications and outcomes in the older populations could be causing this increase in non-routine disposition when compared to younger populations.
Please cite this article as: M. Fana, G. Everett, T. Fagan et al., Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.08.117
M. Fana et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx
Furthermore, we found significantly more urban patients to have private insurance which is a trend consistent with typical urban and rural insurance distribution found in other studies. For instance, in one study by Kirby and Muhuri (2018), data was examined from the Medical Expenditure Panel Survey Household Component (MEPS-HC) [24]. It was found that overall, non-metro residents were less likely to have private insurance and more likely to have public insurance. Moreover, residents of non-adjacent counties with urban populations<20,000 had the highest rate of public coverage. This may be correlated to the higher incomes of urban patients which may provide greater purchasing power for a catered and more encompassing private insurance coverage. Accordingly, we found in our studies that urban patients treated with DBS surgery were more likely to be in the upper 3rd and 4th quartiles of income. This is consistent with typical urban and rural income trends overall for the typical demographic affected by Parkinson’s disease [25]. Finally, we found that urban patients tend to have a longer length of hospital stay than those from rural areas. We speculate that the reason behind this may be due to the increased logistical difficulty of longer hospital stays for patients traveling from a rural to urban area for DBS surgery treatment. It may also be due to a possible correlation between rural patient residency and lower income which would further exacerbate the financial strain of extended hospital stays in a location far from home and local or family support systems. Nonetheless, further investigation would be required to determine the likely multitude of factors for this difference. Moreover, we found that older patients treated with DBS surgery generally have a longer hospital stay for their treatment. This correlation between advanced age and increased length of hospital stay is in-line with the expectation that older patients are at greater risk for treatment complications or poor outcomes. Although much of the impetus behind increased length of stay in older patient populations treated with DBS surgery may be precautionary, it would require further analysis into the correlation between complication rates and advanced age in patients treated with DBS surgery. Lastly, we observed that more severely ill patients treated with DBS surgery tend to have a longer length of hospital stay. This aligns with current literature findings for DBS surgery patients in which severity of illness is generally associated with longer hospital stays, both of which also correspond to increased hospital charges [26,27].
5. Conclusion The overall goal of this study was to determine if disparities in outcomes of DBS surgery exist between patient groups based on urban and rural residency. Our study found that rural patients had shorter hospital stays and increased odds of routine charge. Meanwhile, urban patients and patients presenting with major illnesses had longer hospital stays, were less often routinely discharged, and had greater total charges. This study highlights some of the disparities between rural and urban patients receiving DBS surgery for Parkinson’s disease and suggests that patients in rural locations who may benefit from this operation would require careful pre-surgical and discharge planning to address barriers that might exist due to location, availability of resources, finances, or possible patient biases. Some solutions could include outreach programs for educating patients in rural towns of DBS surgery as a possible treatment option and establishing rehabilitation centers in such towns or regional areas for post-operative care. Future research should investigate variables besides those analyzed here as our data accounts for 11%, 4%, and 22% of the variation seen in routine discharge, total charges, and length of hospital stay, respectively. Other factors to study may include distances to rehabilita-
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tion centers, cost of post-operative care, patient living conditions, and extent of insurance coverage for patients of rural and urban settings, as these likely play an integral part of the decisionmaking process for electing DBS surgery treatment. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgement N/A. References [1] Clair A, Haynes W, Mallet L. 2018. Recent advances in deep brain stimulation in psychiatric disorders. F1000Res. 7:699. [2] Fenoy A, Simpson R. Risks of common complications in deep brain stimulation surgery: management and avoidance. J Neurosurg. 2014;120(1):132–9. [3] Rossi P, Giordano J, Okun M. The Problem of Funding Off-label Deep Brain Stimulation. JAMA Neurol. 2017;74(1):9–10. [4] Willis A, Schootman M, Kung N, Wang X, Perlmutter J, Racette B. Disparities in deep brain stimulation surgery among insured elders with Parkinson disease. Neurology 2014;82(2):163–71. [5] Chan A, McGovern R, Brown L, et al. Disparities in Access to Deep Brain Stimulation Surgery for Parkinson Disease. JAMA Neurol. 2014;71(3):291. [6] Saadi A, Himmelstein DU, Woolhandler S, Mejia NI. Racial disparities in neurologic health care access and utilization in the United States. Neurology 2017;88(24):2268–75. [7] Hemming J, Gruber-Baldini A, Anderson K, et al. Racial and Socioeconomic Disparities in Parkinsonism. Arch Neurol. 2011;68(4):498–503. [8] Sharma M, Ambekar S, Guthikonda B, Wilden J, Nanda A. Regional trends and the impact of various patient and hospital factors on outcomes and costs of hospitalization between academic and nonacademic centers after deep brain stimulation surgery for Parkinson’s disease: a United States Nationwide Inpatient Sample analysis from 2006 to 2010. Neurosurg Focus 2013;35(5):E2. [9] HCUP National Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). Rockville, MD: Agency for Healthcare Research and Quality; 2012. [10] [10] Houchens R, Ross D, Elixhauser A. 2015. Final report on calculating National Inpatient Sample (NIS) variances for data years 2012 and later. Rockville, MD, USA: U.S. Agency for Healthcare Research and Quality, 2015; HCUP Methods Series Report. https://www.hcup-us.ahrq.gov/reports/ methods/methods.jsp [11] Ingram DD, Franco SJ. NCHS urban-rural classification scheme for counties. Vital Health Stat. 2012;2(154):1–65. [12] Kane R. Finding the Right Level of Posthospital Care. JAMA 2011;305(3):284. [13] Burke RE, Jones CD, Coleman EA, Falvey JR, Stevens-Lapsley JE, Ginde AA. Use of post-acute care after hospital discharge in urban and rural hospitals. Am J Accountable Care 2017;5(1):16–22. [14] Wooten GF, Currie LJ, Bovbjerg VE, Lee JK, Patrie J. Are men at greater risk for Parkinson’s disease than women? J Neurol Neurosurg Psychiatry 2004;75 (4):637–9. [15] Miller I, Cronin-Golomb A. Gender differences in Parkinson’s disease: Clinical characteristics and cognition. Mov Disord 2010;25(16):2695–703. [16] Haaxma C, Bloem B, Borm G, et al. Gender differences in Parkinson’s disease. J Neurol Neurosurg Psychiatry 2007;78:819–24. [17] Accolla E, Caputo E, Cogiamanian F, et al. Gender differences in patients with Parkinson’s disease treated with subthalamic deep brain stimulation. Mov Disord. 2007;22(8):1150–6. [18] Chandran S, Krishnan S, Rao R, Sarma SG, Sarma PS, Kishore A. Gender influence on selection and outcome of deep brain stimulation for Parkinson0 s disease. Ann Indian Acad Neurol. 2014;17(1):66–70. [19] Weuve J, Barnes LL, Mendes de Leon CF, Rajan KB, Beck T, Aggarwal NT, et al. Cognitive aging in black and white Americans: cognition, cognitive decline, and incidence of Alzheimer disease dementia. Epidemiology 2018;29 (1):151–9. [20] James F, Power N, Laha S. Decision-making in intensive care medicine – a review. J Intensive Care Soc. 2017;19(3):247–58. [21] Chen P. Will deep brain stimulation increase the incidence of induced psychosis? Post-operation follow-ups for 1 hundred patients from 2004– 2017. Biomedicine (Taipei) 2018;8(4):21. [22] DeLong M, Huang K, Gallis J, et al. Effect of Advancing Age on Outcomes of Deep Brain Stimulation for Parkinson Disease. JAMA Neurol. 2014;71 (10):1290. [23] Bouwyn J, Derrey S, Lefaucheur R, et al. Age Limits for Deep Brain Stimulation of Subthalamic Nuclei in Parkinson’s Disease. J Parkinsons Dis. 2016;6 (2):393–400.
Please cite this article as: M. Fana, G. Everett, T. Fagan et al., Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.08.117
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[24] Kirby JB, Muhuri P. 2018. Statistical Brief #512: Insurance and Access to Care in Urban and Rural Areas, 2014-2015. https://meps.ahrq.gov/data_files/ publications/st512/stat512.shtml; Accessed 20 February 2019. [25] Bishaw A, Posey KG. 2016. A Comparison of Rural and Urban America: Household Income and overty. https://www.census.gov/newsroom/blogs/ random-samplings/2016/12/a_comparison_of_rura.html; Accessed 26 June 2019.
[26] Mikos A, Pavon J, Bowers D, et al. Factors related to extended hospital stays following deep brain stimulation for Parkinson’s disease. Parkinsonism Relat Disord. 2010;16(5):324–8. [27] Lagoe R, Johnson P, Murphy M. Inpatient hospital complications and lengths of stay: a short report. BMC Res Notes 2011;4(1).
Please cite this article as: M. Fana, G. Everett, T. Fagan et al., Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.08.117
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Clinical study
Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings Michael Fana a,⇑, Gregory Everett a, Thomas Fagan a, Megan Mazzella a, Sulmaz Zahedi a, John M. Clements b a b
Central Michigan University College of Medicine, Mount Pleasant, MI, USA Michigan State University, Division of Public Health, College of Human Medicine, Flint, MI, USA
a r t i c l e
i n f o
Article history: Received 29 July 2019 Accepted 25 August 2019 Available online xxxx Keywords: Rural patients Urban patients Deep brain stimulation Hospital stay Routine disposition Hospital costs
a b s t r a c t Presently, disparities exist between race, sex, socioeconomic status, hospitals, income, comorbidities, and insurance profiles of patients undergoing DBS surgery. Here, we aim to highlight several variables and their predictive powers of DBS surgery outcomes as measured by discharge location, length of hospital stays, and total hospital charges. A retrospective cohort study using discharge data from NIS and HCUP for analyses and regression model statistics is performed. Comparative analyses demonstrate urban patients were more often non-routinely discharged, possessed private insurance, and accrued greater hospital costs compared to rural patients. Moreover, regression analyses predicts urban patients have 70% lower odds of routine discharge while those with a major loss of function prior to surgery also have 81% lower odds of routine discharge compared to those with minor loss of function. Ultimately, our study found urban patients or patients with major illnesses have higher hospital charges, longer hospitalization, and more often non-routinely discharged. Ó 2019 Elsevier Ltd. All rights reserved.
1. Introduction Deep brain stimulation (DBS) is a minimally invasive neurologic surgical intervention using implanted pacemakers to electrically stimulate deep brain structures such as the Globus pallidus internus or the subthalamic nucleus. It is often used as a treatment option for Parkinson’s disease but has applications for other movement disorders and neurological diseases such as Tourette’s, obsessive–compulsive disorder, major depression, and chronic pain [1]. The risks associated with DBS are low but may include intracranial bleeding, infection, malposition, and hardware issues, such as migration, disconnection, or malfunction [2]. Presently, several barriers exist to its therapeutic application, including the initial cost of the implanted hardware, which approximates $65,000 along with battery replacements as an added $10,000 to $20,000 in the first 36 months, and hospitals lacking necessary equipment and technology to offer the operation [3]. Several studies report disparities in the use of DBS between groups based on race, gender, and income status. For instance,
⇑ Corresponding author at: 1820 S Crawford Road Apt C2, Mount Pleasant, MI 48858, USA. E-mail address: [email protected] (M. Fana).
Willis et al. (2014) examined socioeconomic, clinical, and practice factors in 657,000 Medicare beneficiaries with Parkinson’s disease indicated for DBS surgery for patients from 2007 to 2009. They found that black and Asian populations were less likely to receive DBS than white patient populations. Furthermore, women had lower odds of receiving DBS than men and patients from higher socioeconomic societies were 40% more likely to receive DBS [4]. Another study conducted by Chan et al. (2014) found a significantly higher proportion of African Americans discharged with Parkinson’s without receiving DBS when compared to nonAfrican American counterparts [5]. In addition, previous studies suggest there are racial and ethnic disparities in neurologic health care access and utilization in the United States. A study by Saadi, Himmelstein, Woolhandler, and Mejia (2017) analyzed data from the 2006–2013 Medical Expenditure Panel Survey (MEPS) and concluded that those who identified as black or Hispanic and as having a neurologic disorder were less likely to receive outpatient-based neurology visits than their white counterparts [6]. Additionally, their analysis found gaps in care for poor, uninsured, and less-educated Americans. Hemming et al. (2011) examined potential disparities in those diagnosed with Parkinson’s disease and receiving treatment in tertiary Movement Disorder Centers. They found that African Americans had greater
https://doi.org/10.1016/j.jocn.2019.08.117 0967-5868/Ó 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: M. Fana, G. Everett, T. Fagan et al., Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.08.117
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Parkinsonian disease severity and disability than whites, and significant differences in management were also seen based on race and socioeconomic status [7]. Sharma et al. (2013) analyzed correlations between adverse outcomes, complications, mortality, and extended hospital stay related to DBS in teaching and non-teaching hospitals. Elderly female patients with comorbidities and non-private insurance had poorer prognoses, particularly when undergoing surgery at low-volume centers with physicians managing low case volumes. Furthermore, high-volume and government-owned teaching hospitals in the Northeast were associated with a lower hospital cost and thus, potentially, lower costs for patients [8]. As suggested, many underlying factors exist which account for some of the variations observed in patient outcomes post-operatively for DBS surgery, namely: age, sex, race, post-operative conditions, insurance profile, income, and severity of illness. Our goal is to describe these factors in a national cohort and identify their impact on outcomes for patients from rural and urban locations. We examined DBS surgery outcomes for patients in rural and urban locations based on discharge records from the 2012 National Inpatient Sample (NIS). We hypothesize that patients from rural and urban geographic origins have different outcomes as measured by patient discharge location (i.e. routine being place of residence or home and non-routine being an institution), length of hospital stay, and total hospital charges after receiving DBS operations. 2. Methods This IRB exempt, retrospective cohort study examines disparities in outcomes of patients undergoing DBS surgery for Parkinson’s disease between groups based on urban or rural patient
location. We use discharge data from the 2012 National Inpatient Sample (NIS), Healthcare Cost and Utilization Project (HCUP), Agency for Healthcare Research and Quality [9]. The 2012 HCUP NIS database includes 7,296,968 discharge cases. Discharge records include up to 25 ICD-9 Diagnosis codes and 15 Healthcare Common Procedure Coding System (HCPCS) codes. We selected all discharges with an HCPCS DBS procedure code of 02.93 in any of the procedure code variables. The first diagnosis code is generally considered the primary diagnosis for that hospital stay. We included discharges for patients with a diagnosis of Parkinson’s (ICD-9: 332, 332.0, and 332.1). Subsequently, we excluded a Parkinson’s diagnosis of 332.1 as there was only one discharge with this diagnosis, and there were no codes of 332, the broader code for Parkinson’s Disease. Ultimately, our data includes only discharges with the ICD-9 code 332.0 – Parkinson’s Disease – Paralysis agitans. The use of NIS data requires a weighting procedure to make reliable national estimates [10]. Therefore, the final sample size is 3,005. All results reflect the use of the weighting procedure. Independent variables collected for analysis include the following: patient age (in years at admission), sex (male or female), number of chronic conditions at admission, insurance status (excluding self-pay, no charge, and others), patient location (rural and urban based on Ingram and Franco (2012)) [11], race (white and nonwhite), income (based on national quartiles), and severity of illness (categorized as: no class specified, minor loss of function, moderate loss of function, major loss of function, and extreme loss of function). We ran independent t-tests to compare means between groups for continuous variables and chi-square to test differences between proportions between groups (with z-test for proportions to test for differences in specific group category proportions). Finally, we ran regression models with routine disposition (binary logistic), total
Table 1 National Inpatient Sample Discharges with DBS Procedure and Parkinson’s Diagnosis, n = 3005#
Variable Dependent Variables Disposition of Patient Routine (Home or other place of residence) Not Routine (short-term stay, skilled nursing, etc.) Length of Stay – days^ Total Charges^ Independent Variables Age^ Sex Male Female Number of Chronic Conditions^ Insurance (n = 2,955) Public Insurance (Medicaid/Medicare) Private Insurance (including HMO) Patient Location (n = 2,990) Urban Rural Race (n = 2,835) White Non-white Income (n = 2,930) 1st Quartile (Lowest) 2nd Quartile 3rd Quartile 4th Quartile (Highest) Severity of Illness Subclass Minor loss of function Moderate loss of function Major loss of function Extreme loss of function * #
Total
Rural
Urban
# (%)
# (%)
# (%)
2,635 (87.7) 370 (12.3) 1.81, 2.28 $77,050, $46,280
475 (94.1) 30 (5.9) 1.54, 1.38 $66,873, $33,611
2145 (86.3)* 340 (13.7)* 1.86, 2.42 $79,111, $48,310
c2 = 23.20, p < 0.001
63.8, 9.5
64.6, 8.0
63.8, 9.8
t = 1.97, p = 0.051
1,000 (33.3) 2,005 (66.7) 3.6, 2.2
330 (65.3) 175 (34.7) 3.8, 2.4
1,665 (67.0) 820 (33.0) 3.5, 2.1
c2 = 0.518, p = 0.472
935 (31.6) 2,020 (68.4)
380 (75.2) 125 (24.8)
1,640 (67.2)* 800 (32.8)*
c2 = 12.54, p < 0.001
2,485 (83.1) 505 (16.9)
— —
— —
— —
2,375 (83.8) 460 (16.2)
415 (94.3) 25 (5.7)
1,955 (82.1)* 425 (17.9)*
c2 = 41.05, p < 0.001
540 650 805 935
225 (47.4) 185 (38.9) 55 (11.6) 10 (2.1)
315 465 750 925
c2 = 539.4, p < 0.001
375 (74.3) 115 (22.8) 15 (3.0) 0 (0.0)
1,900 (76.5) 510 (20.5) 60 (2.4) 15 (0.6)
(18.4) (22.2) (27.5) (31.9)
2,285 (76.0) 630 (21.0) 75 (2.5) 15 (0.5)
(12.8)* (18.9)* (30.5)* (37.7)*
Significance
t = -2.85, p = 0.004 t = -6.72, p < 0.001
t = 2.56, p = 0.010
c2 = 539.4, p < 0.001
In addition to significant Chi-square, column proportion difference between rural and urban is statistically significant at p < 0.05. Sample size unless otherwise indicated for specific variables, ^ mean, standard deviation.
Please cite this article as: M. Fana, G. Everett, T. Fagan et al., Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.08.117
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M. Fana et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx Table 2 Regressions Predicting Patient Disposition, Total Charges, and Length of Stay. Logistic Regression Predicting Routine Disposition Variable R-square Constant Age Female (Reference: Male) Number of Chronic Conditions Public Insurance (Reference: Private Insurance) Urban Patient Location (Reference: Rural) White Race (Reference: Non-white) Income (Reference: 1st Quartile – lowest) 2nd Quartile 3rd Quartile 4th Quartile (Highest) Severity of Illness Subclass (Reference: Minor loss) Moderate loss of function Major loss of function Extreme loss of function
b (SE) 0.114 5.28 (0.494)*** –0.026 (0.007)** –0.354 (0.122)*** –0.108 (0.0.28)*** –0.567 (0.161)*** 1.203 (0.240)*** 0.299 (0.158)
Odds Ratio (95% CI)
0.378 (0.198) 0.471 (0.192)* 0.195 (0.180)
1.46 (0.990, 2.15) 1.60 (1.10, 2.33) 1.22 (0.854, 1.72)
–0.314 (0.143)* 1.66 (0.293)*** –0.843 (0.566)
0.731 (0.552, 0.967) 0.190 (0.107, 0.337) 0.431 (0.142, 1.31)
0.702 (0.553, 0.891) 0.567 (0.413, 0.779) 0.300 (0.187, 0.481) 1.35 (0.990, 1.84)
Linear Regression Predicting Total Charges
Linear Regression Predicting Length of Stay
b (Standardized) 0.037 56,879*** 0.028 –0.012 0.017 –0.108*** 0.095*** –0.033 –0.022 — — — 0.136*** — —
b (Standardized) 0.225 2.116*** 0.075*** 0.012 0.012 0.001 0.047* –0.010 0.024 — — — 0.460*** — — —
*p < 0.05, **p < 0.01, ***p < 0.001.
charges (linear regression), and length of stay (linear regression) as the dependent variables. The results of these tests are displayed in Tables 1 and 2.
3. Results The descriptive results characterizing our cohort, as well as comparisons between urban and rural groups for each of our variables, are shown in Table 1. Results of the binary logistic regression and linear regression are included in Table 2. The mean age of patients in rural and urban populations undergoing DBS procedure is 63.8 ± 9.5. Altogether, no significant difference was found between male and female population sizes in urban and rural populations, however twice as many females were found to undergo the procedure (66.7% versus 33.3%). Finally, greater proportions of white people receive DBS compared to non-whites (83.8% versus 16.2%) (p < 0.001). Our primary analyses show several notable distinctions between rural and urban populations. First, urban patients were non-routinely discharged (i.e. did not go home or to place of residency) more often than rural patients (13.7% versus 5.9%, p < 0.001). Moreover, urban patients have a longer length of stay in hospitals post-operatively, by approximately 8 h, compared to rural patient populations (1.86 days versus 1.54 days, p = 0.004). Additionally, a wide discrepancy is found in total average charges between urban and rural populations of approximately $79,000 and $67,000 (p < 0.001), respectively. The results of our regression analyses identified several factors that impact patient disposition. First, urban patients are at 70% lower odds to be routinely discharged home compared to rural patients (OR = 0.300, 95% CI = 0.187–0.481). This result corresponds to our finding that there are significant differences in the proportions of urban and rural patients being non-routinely discharged. Next, compared to patients with minor loss of function prior to surgery, patients discharged with major loss of function prior to surgery have 81% lower odds of routine discharge (OR = 0.190, 95% CI = 0.107–0.337), while those with moderate loss of function prior to surgery have 26.9% lower odds of routine discharge (OR = 0.731, 95% CI = 0.552–0.967). Patients with public insurance (Medicaid or Medicare) have 43.3% lower odds of being routinely discharged compared to those with private insurance (OR = 0.567, 95% CI = 0.413–0.779). Females, when compared to males, have 30% lower odds of routine disposition (OR = 0.702,
95% CI = 0.553–0.891). Finally, younger patients are more likely to have routine disposition than older patients. With regards to finances and insurance, a greater proportion of urban patients had private insurance compared to rural patient populations (32.8% versus 24.8%). Income discrepancy is also present between rural and urban patients. Most rural patients (86.3%) receiving DBS surgery are in the lower 1st and 2nd quartile for income whereas most patients of urban geography are in the 3rd and 4th upper quartile of income (68.2%). Regression analysis of total hospital charges shows that patients with private insurance have higher total charges for DBS surgery compared to those with public insurance. Similarly, urban patients have slightly higher hospital charges compared to rural patients. Finally, patients with a more severe state of illness, as measured by loss of function, have higher charges for DBS operation. Lastly, regarding length of stay, our regression analysis indicated that older patients, urban patients, and those with greater severity of illness have a longer length of stay compared to patients that are younger, rural, and have lower severity of illness, respectively. It is also notable that we found no difference in the mean number of chronic conditions presented by patients of urban and rural populations. To summarize, our results demonstrate that urban patients were more often non-routinely discharged, possessed private insurance, had a higher average charge for operation, higher income, and longer length of hospital stay compared to rural patients. Urban patients had lower odds of routine discharge, as did those presenting with a major or moderate loss of function prior to surgery. Patients from urban locations are predicted to have higher charges for operation and longer hospital stays than their rural counterparts. We also identified the following factors that increased odds for routine discharge: rural patient location, public insurance, younger age, and female sex. On the other hand, patients with higher severity of illness are less likely routinely discharged.
4. Discussion We conducted a retrospective cohort study of patients receiving DBS surgery for Parkinson’s disease to determine disparities in outcomes based rural and urban patient location. In addition, we considered the influence of sex, race, loss of function prior to surgery, age, insurance and income. Here, we will discuss the implications of these results and situate these findings relative to other research.
Please cite this article as: M. Fana, G. Everett, T. Fagan et al., Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.08.117
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We found that rural patients discharged had greater odds of routine discharge compared to urban patients, however few investigations have been made into the possible etiology behind the discrepancy. Nonetheless, in some post-surgical circumstances, patients can return home after hospitalization and continue with care provided by family, while many others will require postacute care (PAC) for rehabilitation and recuperation to help improve patient recovery. Forms of PAC include inpatient rehabilitation, skilled nursing facilities, long-term care hospitals, and home health care. Some studies suggest that inpatient rehabilitation is the superior option amongst other PAC discharge locations for recovery [12]. One theory for the difference in routine discharge between rural and urban patients is that while rural patients qualify for post-operative care at rehabilitation facilities, they may be sent home with the assumption that such centers exist in their hometown. However, many rural areas have less access to established care centers [13]. Furthermore, the distance that rural patients would need to travel to reach a nearby center is likely too far for practical use of service given the likelihood that these centers are commonly established in more urban areas. Clearly, several PAC options are not available for patients from rural areas due to lack of services situated in their areas and the long distances patients must travel. These factors may make it less likely that rural patients pursue post-discharge care. Interestingly, we found that women made up a greater proportion of our cohort. Prior research has also shown that women receive more DBS surgery treatment for Parkinson’s disease despite the 1.5–2 times increased frequency of Parkinson’s disease in men. Postulated explanations for this difference are as follows: more toxin exposure, head trauma, mitochondrial dysfunction, or X-linked genetic factors in men or greater neuroprotection by estrogen in women [14]. Furthermore, there are differences in the presentation of Parkinson’s disease between men and women; women are diagnosed on average 2.1 years later than men (53.4 vs. 51.3 years, respectively) and more often present with tremors as opposed to bradykinesia and rigidity [15]. The delay in disease onset could be due in part to the high levels of striatal dopamine from estrogen activity. This may result in the lower incidence and higher age of onset in women as well as the more frequent tremors [16]. Moreover, men list more symptoms on average than women; meanwhile, women are more likely to report that their symptoms cause anxiety and depression. Therefore, there is a propensity for greater social acceptance of the disease and report of its symptoms by female patients which may explain why women opt for DBS surgery procedures more often than men. Nevertheless, studies of post-operative assessments of mental health for DBS surgery for men and women showed no difference between the sexes [15]. In one study by Accolla et al. (2007), no differences were found between men and women for DBS surgery pre-operative severity of disease (i.e. tremor, rigidity, or ADLs) [17]. However, women were found to have more severe dyskinesias and non-responsive bradykinesias. This may bring in to question the efficacy of DBS surgery treatment for men and women, however a cohort study by Chandran et al. (2014) has shown that subthalamic DBS surgery is equally efficacious in both men and women [18]. Therefore, women are likely to be treated more often because of the more severe dyskinesia symptoms and are prone to experiencing less emotional well-being. As a result, earlier surgical treatment for women may be more beneficial and may explain the findings here of more women receiving DBS surgery treatment. Regarding race, we found that white patients received DBS surgery more often than non-white patients. Similarly, studies such as those highlighted before by Willis et al. (2014) have also found white people to receive DBS surgery more often than black populations for Parkinson’s disease.4 This may be due to black people having higher rates of cognitive impairments, dementia, or other
comorbidities among the elderly with Parkinson’s disease that may be contraindicated for DBS surgery [19]. Moreover, minority patients with Parkinson’s disease are more likely to receive care from a provider that is unlikely or unable to perform or refer their patient to a clinic for DBS surgery operation. In fact, according to a Nationwide Inpatient Sample of the 2.4 million Parkinson’s disease discharges from 2002 to 2009, 4.7% of them were African American while only 0.1% of DBS surgery for Parkinson’s disease discharges were African American [5]. Factors such as younger age, male sex, increasing income quartile, larger hospital, teaching hospital, urban setting, hospitals with greater discharges for Parkinson’s disease, and increased country-wide density of neurologists increased the chances of DBS surgery operation. Meanwhile, non-use of DBS surgery was predicted with African American race, Medicaid coverage, and increasing co-morbidity scores. Many African American patients are discharged with Parkinson’s disease whose patient characteristics would predict the use of DBS surgery, and who would benefit from the DBS surgery, but are nonetheless approximately eight times less likely to get this treatment. Medicare coverage amongst African American populations appears to predispose them to the DBS surgery non-use decision [5]. Other factors may include disparities in access to care, cultural biases or beliefs, and socioeconomic status, which require further investigations. Our research also identified that patients with severe preoperative loss of function are at lower odds for routine discharge, likely because they are at higher risk of further injury postoperatively. This is not surprising giving the need for close monitoring of such patients post-operatively until they are deemed appropriate for routine discharge. We have also uncovered an association between the severity of a DBS surgery patient’s illness and their total charges for treatment. This is consistent with our initial expectations; more severely ill patient populations generally require more comprehensive care [20]. It is worth mentioning that DBS surgery itself is a safe treatment option and operation for patients with Parkinson’s disease. This surgical procedure has been used for the past 20 years with great success. In one study by Chen (2018), a surgeon’s post-operative patient outcomes were followed between 2004 and 2017 for 103 patients. Major complaints by the surgeon’s patients were fever, constipation, nausea, headache, and wound pain, all concerns that are not atypical to general postoperative and post-anesthesia side effects. Some rare postoperative intracranial hemorrhages and epidural hematomas were identified as well [21]. Therefore, this operation is generally a safe procedure for which patients can be routinely discharged, but we speculate that patients of urban populations may utilize the option by their surgeon for post-operative non-routine discharge as a precautionary measure. We observed young patients are routinely discharged more often compared to older patients. Available data involving the elderly on post-operative DBS complications and outcomes are conflicting. Although there is no specific age cut-off, most clinical studies have excluded patients older than 75 years old. In one study by DeLong et al. (2014), the stepwise effect of increasing age on short term complications following DBS surgery was evaluated [22]. It was found that older patients (i.e. older than 75 years) showed a similar 90-day complication risk compared with younger counterparts. Whereas another study by Bouwyn et al. (2016) compared early post-operative outcomes in patients younger than 65 years old versus patients older than 65 years old and it was found that DBS surgery had a more negative impact on cognitive functions in elderly patients [23]. Therefore, it may be the case that increased rates of post-operative complications and outcomes in the older populations could be causing this increase in non-routine disposition when compared to younger populations.
Please cite this article as: M. Fana, G. Everett, T. Fagan et al., Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.08.117
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Furthermore, we found significantly more urban patients to have private insurance which is a trend consistent with typical urban and rural insurance distribution found in other studies. For instance, in one study by Kirby and Muhuri (2018), data was examined from the Medical Expenditure Panel Survey Household Component (MEPS-HC) [24]. It was found that overall, non-metro residents were less likely to have private insurance and more likely to have public insurance. Moreover, residents of non-adjacent counties with urban populations<20,000 had the highest rate of public coverage. This may be correlated to the higher incomes of urban patients which may provide greater purchasing power for a catered and more encompassing private insurance coverage. Accordingly, we found in our studies that urban patients treated with DBS surgery were more likely to be in the upper 3rd and 4th quartiles of income. This is consistent with typical urban and rural income trends overall for the typical demographic affected by Parkinson’s disease [25]. Finally, we found that urban patients tend to have a longer length of hospital stay than those from rural areas. We speculate that the reason behind this may be due to the increased logistical difficulty of longer hospital stays for patients traveling from a rural to urban area for DBS surgery treatment. It may also be due to a possible correlation between rural patient residency and lower income which would further exacerbate the financial strain of extended hospital stays in a location far from home and local or family support systems. Nonetheless, further investigation would be required to determine the likely multitude of factors for this difference. Moreover, we found that older patients treated with DBS surgery generally have a longer hospital stay for their treatment. This correlation between advanced age and increased length of hospital stay is in-line with the expectation that older patients are at greater risk for treatment complications or poor outcomes. Although much of the impetus behind increased length of stay in older patient populations treated with DBS surgery may be precautionary, it would require further analysis into the correlation between complication rates and advanced age in patients treated with DBS surgery. Lastly, we observed that more severely ill patients treated with DBS surgery tend to have a longer length of hospital stay. This aligns with current literature findings for DBS surgery patients in which severity of illness is generally associated with longer hospital stays, both of which also correspond to increased hospital charges [26,27].
5. Conclusion The overall goal of this study was to determine if disparities in outcomes of DBS surgery exist between patient groups based on urban and rural residency. Our study found that rural patients had shorter hospital stays and increased odds of routine charge. Meanwhile, urban patients and patients presenting with major illnesses had longer hospital stays, were less often routinely discharged, and had greater total charges. This study highlights some of the disparities between rural and urban patients receiving DBS surgery for Parkinson’s disease and suggests that patients in rural locations who may benefit from this operation would require careful pre-surgical and discharge planning to address barriers that might exist due to location, availability of resources, finances, or possible patient biases. Some solutions could include outreach programs for educating patients in rural towns of DBS surgery as a possible treatment option and establishing rehabilitation centers in such towns or regional areas for post-operative care. Future research should investigate variables besides those analyzed here as our data accounts for 11%, 4%, and 22% of the variation seen in routine discharge, total charges, and length of hospital stay, respectively. Other factors to study may include distances to rehabilita-
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tion centers, cost of post-operative care, patient living conditions, and extent of insurance coverage for patients of rural and urban settings, as these likely play an integral part of the decisionmaking process for electing DBS surgery treatment. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgement N/A. References [1] Clair A, Haynes W, Mallet L. 2018. Recent advances in deep brain stimulation in psychiatric disorders. F1000Res. 7:699. [2] Fenoy A, Simpson R. Risks of common complications in deep brain stimulation surgery: management and avoidance. J Neurosurg. 2014;120(1):132–9. [3] Rossi P, Giordano J, Okun M. The Problem of Funding Off-label Deep Brain Stimulation. JAMA Neurol. 2017;74(1):9–10. [4] Willis A, Schootman M, Kung N, Wang X, Perlmutter J, Racette B. Disparities in deep brain stimulation surgery among insured elders with Parkinson disease. Neurology 2014;82(2):163–71. [5] Chan A, McGovern R, Brown L, et al. Disparities in Access to Deep Brain Stimulation Surgery for Parkinson Disease. JAMA Neurol. 2014;71(3):291. [6] Saadi A, Himmelstein DU, Woolhandler S, Mejia NI. Racial disparities in neurologic health care access and utilization in the United States. Neurology 2017;88(24):2268–75. [7] Hemming J, Gruber-Baldini A, Anderson K, et al. Racial and Socioeconomic Disparities in Parkinsonism. Arch Neurol. 2011;68(4):498–503. [8] Sharma M, Ambekar S, Guthikonda B, Wilden J, Nanda A. Regional trends and the impact of various patient and hospital factors on outcomes and costs of hospitalization between academic and nonacademic centers after deep brain stimulation surgery for Parkinson’s disease: a United States Nationwide Inpatient Sample analysis from 2006 to 2010. Neurosurg Focus 2013;35(5):E2. [9] HCUP National Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). Rockville, MD: Agency for Healthcare Research and Quality; 2012. [10] [10] Houchens R, Ross D, Elixhauser A. 2015. Final report on calculating National Inpatient Sample (NIS) variances for data years 2012 and later. Rockville, MD, USA: U.S. Agency for Healthcare Research and Quality, 2015; HCUP Methods Series Report. https://www.hcup-us.ahrq.gov/reports/ methods/methods.jsp [11] Ingram DD, Franco SJ. NCHS urban-rural classification scheme for counties. Vital Health Stat. 2012;2(154):1–65. [12] Kane R. Finding the Right Level of Posthospital Care. JAMA 2011;305(3):284. [13] Burke RE, Jones CD, Coleman EA, Falvey JR, Stevens-Lapsley JE, Ginde AA. Use of post-acute care after hospital discharge in urban and rural hospitals. Am J Accountable Care 2017;5(1):16–22. [14] Wooten GF, Currie LJ, Bovbjerg VE, Lee JK, Patrie J. Are men at greater risk for Parkinson’s disease than women? J Neurol Neurosurg Psychiatry 2004;75 (4):637–9. [15] Miller I, Cronin-Golomb A. Gender differences in Parkinson’s disease: Clinical characteristics and cognition. Mov Disord 2010;25(16):2695–703. [16] Haaxma C, Bloem B, Borm G, et al. Gender differences in Parkinson’s disease. J Neurol Neurosurg Psychiatry 2007;78:819–24. [17] Accolla E, Caputo E, Cogiamanian F, et al. Gender differences in patients with Parkinson’s disease treated with subthalamic deep brain stimulation. Mov Disord. 2007;22(8):1150–6. [18] Chandran S, Krishnan S, Rao R, Sarma SG, Sarma PS, Kishore A. Gender influence on selection and outcome of deep brain stimulation for Parkinson0 s disease. Ann Indian Acad Neurol. 2014;17(1):66–70. [19] Weuve J, Barnes LL, Mendes de Leon CF, Rajan KB, Beck T, Aggarwal NT, et al. Cognitive aging in black and white Americans: cognition, cognitive decline, and incidence of Alzheimer disease dementia. Epidemiology 2018;29 (1):151–9. [20] James F, Power N, Laha S. Decision-making in intensive care medicine – a review. J Intensive Care Soc. 2017;19(3):247–58. [21] Chen P. Will deep brain stimulation increase the incidence of induced psychosis? Post-operation follow-ups for 1 hundred patients from 2004– 2017. Biomedicine (Taipei) 2018;8(4):21. [22] DeLong M, Huang K, Gallis J, et al. Effect of Advancing Age on Outcomes of Deep Brain Stimulation for Parkinson Disease. JAMA Neurol. 2014;71 (10):1290. [23] Bouwyn J, Derrey S, Lefaucheur R, et al. Age Limits for Deep Brain Stimulation of Subthalamic Nuclei in Parkinson’s Disease. J Parkinsons Dis. 2016;6 (2):393–400.
Please cite this article as: M. Fana, G. Everett, T. Fagan et al., Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.08.117
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[24] Kirby JB, Muhuri P. 2018. Statistical Brief #512: Insurance and Access to Care in Urban and Rural Areas, 2014-2015. https://meps.ahrq.gov/data_files/ publications/st512/stat512.shtml; Accessed 20 February 2019. [25] Bishaw A, Posey KG. 2016. A Comparison of Rural and Urban America: Household Income and overty. https://www.census.gov/newsroom/blogs/ random-samplings/2016/12/a_comparison_of_rura.html; Accessed 26 June 2019.
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Please cite this article as: M. Fana, G. Everett, T. Fagan et al., Procedural outcomes of deep brain stimulation (DBS) surgery in rural and urban patient population settings, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2019.08.117