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High rates and the risk factors for emergency room visits and hospitalization in Parkinson's disease
Parkinsonism and Related Disorders 19 (2013) 949e954
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Parkinsonism and Related Disorders journal homepage: www.elsevier.com/locate/parkreldis
High rates and the risk factors for emergency room visits and hospitalization in Parkinson’s disease Anhar Hassan a, g, *, Samuel S. Wu b, Peter Schmidt c, Yunfeng Dai b, Tanya Simuni d, Nir Giladi e, Bastiaan R. Bloem f, Irene A. Malaty a, Michael S. Okun a, on behalf of the NPF-QII Investigators a
Center for Movement Disorders & Neurorestoration, University of Florida, Gainesville, FL, USA Department of Biostatistics, University of Florida, Gainesville, FL, USA National Parkinson’s Foundation, Miami, FL, USA d Parkinson’s disease and Movement Disorders Center, Northwestern University Feinberg School of Medicine, Abbott Hall 11th Floor, 710 North Lake Shore Drive, Chicago, IL, USA e Movement Disorders Unit, Department of Neurology, Tel-Aviv Sourasky Medical Center, Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel f Radboud University Nijmegen Medical Center, Donders Institute for Brain, Cognition and Behavior, Department of Neurology, Nijmegen, Netherlands g Department of Neurology, Mayo Clinic, Rochester, MN, USA b c
a r t i c l e i n f o
a b s t r a c t
Article history: Received 2 November 2012 Received in revised form 2 June 2013 Accepted 13 June 2013
Background: Parkinson’s disease (PD) patients are hospitalized more frequently than their peers as a result of falls, psychosis, infections and other medical complications. However, patient-specific risk factors for hospitalization are unclear. Objective: To identify rates and risk factors for hospital encounters (Emergency Room [ER] visits or hospitalization) among people with PD. Methods: 3415 PD participants (mean age 67 10 years, disease duration 9 6 years, H&Y 2 47%, H&Y 3 26%) enrolled in the prospective international multicenter NPF-QII Study. One-year follow-up data was available for 1030 patients. Rates and risk factors for hospital encounters were determined at baseline and after one year follow-up. Results: Of 3415 PD participants at study entry, 1120 (33%) reported at least one hospital encounter. Associations were: longer timed up-and-go test (OR: 1.33), increased comorbidities (OR: 1.25), motor fluctuations (OR: 1.32), and deep brain stimulation (DBS) (OR: 2.49). Of these 1120 persons, 311 had follow-up data and 158 (51%) had a repeat encounter one year later, associated with higher H&Y stage, fluctuations, and lower health-related quality-of-life. Of 2295 participants without a hospital encounter at baseline, 719 had follow-up data and 178 (25%) had a first hospital encounter one year later. Risk factors were female gender, comorbidities, lower cognition, fluctuations, and DBS. Conclusions: One-third of people with PD had a hospital encounter each year, and one-half of those had a repeat encounter. These high rates correlated with disease severity, comorbidities and DBS. There is an urgent need to develop programs to reduce PD hospital encounters. Ó 2013 Elsevier Ltd. All rights reserved.
Keywords: Hospitalization Parkinson’s disease Admissions Emergency care Comorbidities
1. Background Parkinson’s disease (PD) is a progressive neurodegenerative disorder that worldwide affects approximately 4.5 million people aged 50 or older. The cost of PD care increases with the progression of disease [1,2]. Acute care encounters (emergency room visits and hospitalizations) for PD are the most costly units of health care
* Corresponding author. Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA. E-mail address: [email protected] (A. Hassan). 1353-8020/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.parkreldis.2013.06.006
delivery. Small previous studies reported that people with PD were hospitalized more than age-matched controls [3e6]. People with PD also have higher hospital related complication rates, and a substantial risk of deterioration of their PD symptoms, independent of the reason for admission [4,7,8]. The total cumulative effects of PD hospital encounters increases burden of care, hospital costs, morbidity and mortality [9]. To reduce this societal burden it will be important to identify risk factors for hospital encounters and also to identify potential interventions to mitigate these risks. Risk factor analysis will be best accomplished by studying hospital attendance in a
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prospective and clinically well-characterized population. Improved prospective characterization of populations is becoming increasingly important to inform early intervention, and this was recently illustrated by the pioneering work that linked forced expiratory volume to mortality in cystic fibrosis [10]. In PD, increasing disease burden in aging populations has been driving both economic and public health urgency because of a need to inform on the use of lower intensity interventions [11e14]. Thus, identifying potential modifiable risk factors leading to hospital encounters could reduce morbidity, mortality, and their associated costs. This PD study was modeled after the longitudinal study performed in cystic fibrosis.
2.3. Statistical analysis
2. Methods
Results were similar when ER visits and hospitalization were analyzed individually (See online supplements e-Table 1, e-Table 2), therefore we report combined findings as a single outcome of “encounter” (either ER or hospitalization). For the cross-sectional analysis, 3415 participants (2100 male; 61%) were analyzed at their baseline visit. This cohort had a mean age 67.1 years (10.1) and mean disease duration 8.9 years (6.3). The vast majority was H&Y stage 2 (47%) or 3 (26%), and 10% had undergone DBS. Of these 3415, 1120 (33%) reported an ER visit or hospitalization (Table 1, Fig. 1. Additional data e-Table 3). The top two reasons for hospital encounters were injury or infection, although less than 40% reported a reason (e-Table 4). The frequencies of reasons for hospital admission were similar. After excluding those with DBS, 948 (31% of 3056) had an encounter. Hospital encounters associated by logistic regression with the clinical and demographic variables were: longer timed up-and-go test (OR: 1.33), higher number of co-morbidities (OR: 1.25), presence of motor fluctuations (OR: 1.32), and presence of DBS (OR: 2.49) as predictors of hospital encounters (Table 2). There were also significant variations across study centers in the hospital encounter rate, ranging from 16% to 44% (e-Table 3). The adjusted OR ranged from 1.05 to 5.46 compared to the center with the lowest risk, and was 2.0 for 12 centers compared to the center with the lowest risk (e-Table 5). Participants with prior DBS had a higher rate of hospitalization (48%) vs those without (31%, P < 0.0001). After excluding participants with DBS, the significant risk factors remained the same however, with very minor changes in odds ratios (Table 2). Participants with hospital encounters reported more comorbidities in our assessment than those without. There was significantly more frequent use of each type of medication, with the exception of stimulants and anticholinergic medications, and increased use of physical, occupational, speech therapies, and mental health services in participants reporting hospital encounters. In addition, they were significantly older, with longer disease duration (10 vs 8 years) and more advanced disease, worse cognition, more frequent falls, not living at home, required a care partner, reported a lower health-related quality of life, and had a higher caregiver burden (P < 0.0001 for all, Table 1). However, none of these factors was correlated with higher hospitalization rates after controlling for the factors listed in Table 2.
2.1. Study design We examined the information available from the on-going international multicenter National Parkinson Foundation Quality Improvement Initiative (NPF-QII), a long-term observational clinical study. NPF-QII prospectively collects detailed demographic and clinical data on PD patients attending NPF Centers of Excellence, and does this annually using methods described previously [15]. PD participants submit written informed consent to enroll in the study. Currently 19 centers are participating in the study and 18 centers contributed data to this analysis, located in the United States, Canada, Netherlands, and Israel. We analyzed the NPF-QII data to determine the frequency of ER visits and hospitalizations in our cohort (hereafter termed “encounters”) and correlated them with demographic and clinical variables in a cross-sectional analysis. We performed a longitudinal analysis for predictors of new encounters and repeat encounters. 2.2. Participants The NPF-QII study data was reviewed to identify all PD participants where information about hospital encounters (including admissions and ER visits) was available. There were 3415 participants that met these criteria for the crosssectional analysis. There were 1030 participants with complete follow-up data at both baseline and one year later for the longitudinal analysis at time of data analysis. Demographic and clinical data included gender, race, BMI, age at onset, age at diagnosis, disease duration, presence of tremor, motor fluctuations, Hoehn and Yahr (H&Y) stage, co-morbidities, ability to stand unaided, living situation, presence or absence of a regular care partner, exercise habits, medications, other treatments (physical therapy, occupational therapy, speech therapy), deep brain stimulation (DBS), timed up and go test (TUG) [16], Parkinson’s Disease Quality of Life Questionnaire (PDQ-39) [17], and Multidimensional Caregiver Strain Index (MCSI) [18] scores. In addition, we utilized MoCA estimate, a weighted cognitive score formed from a combination of immediate and delayed 5 word recall and semantic fluency (animals) scores, to optimally predict Montreal Cognitive Assessment (MoCA) [19] results. The PDQ-39 is a validated, widely used scale completed by the patient, and was used to assess health-related quality of life in this cohort. It includes 39 items subdivided into eight domains: mobility, activities of daily living, emotional well-being, stigma, social support, cognition, communication, and bodily discomfort [17]. The MCSI is an 18-item tool completed by the caregiver, measuring 6 domains of subjective response to stressors. Subscores include physical strain, social constraints, financial strain, time constraints, interpersonal strain, and elder demanding/manipulative [18]. The scale has not been validated in PD, but expert review recommended this was appropriate for the PD population [15]. Therapeutic interventions including 10 classes of medications commonly used in PD and five different allied health interventions were recorded by identifying if they are started, stopped or continued at the time of data collection. Full details on the data form and collection protocol have addressed previously [15]. Subject-reported comorbidities were assessed, with a history of cardiovascular issues, cancer, respiratory problems, arthritis, diabetes, other neurological, and “other” all assessed and ranked for severity by the patient. Falls were characterized by frequency, and exercise programs by hours per week. ER and hospital admission rates were examined both individually and as combined values. An ER visit was defined as an evaluation in the emergency department where the participant was discharged home. Hospitalization included any admission for either a PD-related or a non-PD related cause, and included elective admissions (e.g. DBS battery change). Subjects reported whether either event had occurred within in the prior 12 months. For the primary analysis, we compared patients with a history of ER visit or hospital admission at study entry vs those without, in order to identify candidate risk factors for these encounters. For secondary analysis, we examined the available data one year later to identify follow-up rates of hospital encounters.
Hospital admissions and ER visits were analyzed individually and also as a single outcome termed “encounter”. A two-sample t-test for continuous variables and chisquare test for the categorical variable was used to compare between those who had ER visits vs those who did not, and between those hospitalized vs those who were not. For risk factor correlations, multivariate logistic regression with backward selection was performed to identify risk factors for the encounter at baseline. The above analyses were repeated excluding those patients who had DBS. Two more logistic regressions were conducted to identify risk factors for new ER visit or hospitalization after one year, stratified by whether the patients had an encounter at baseline.
3. Results
4. Longitudinal analysis 4.1. Repeat ER visit/hospitalizations Of the 1120 participants hospitalized at baseline, follow-up data was thus far available for 311 (28%) after one-year follow-up at the time of the data analysis (Fig. 1). Of these 311, 158 (51%) reported a repeat hospital encounter after one year. Multivariate logistic regression suggested that higher H&Y stage was the major risk factor associated with a repeat hospital encounter. The
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Table 1 Summary of baseline demographic and clinical data for PD patients with a hospital encounter vs those without.a Overall (N ¼ 3415)
Variable
Demographic variables Age Male, n (%) White, n (%) Disease duration Social variables Patient can stand unaided Living at home No regular care partner PD diagnosis/stage Hoehn & Yahr stage
Rest tremor present Motor fluctuations Clinical outcomes Standardized TUG Immediate word recall Delayed word recall Verbal fluency MoCA estimate Number of comorbidities Medications
Other treatments Physical therapy, n (%) Occupational therapy, n (%) Speech therapy, n (%) Social worker/counseling, n (%) Mental health Tx or referral, n (%) DBS, n (%) PDQ39 summary index MCSI index a
1 2 3 4e5
No 1 med Multi-meds
Hospital encounter
P-value
Yes (N ¼ 1120)
No (N ¼ 2295)
67.1 10.1 2100 3180 8.9 6.3
68.7 10.2 680 (61%) 1058 (96%) 10.1 6.5
66.3 9.9 1420 (62%) 2122 (94%) 8.4 6.1
<0.0001 0.475 0.013 <0.0001
3060 3267 507
958 (87%) 1033 (92%) 152 (14%)
2102 (94%) 2234 (97%) 355 (16%)
<0.0001 <0.0001 <0.0001
393 1608 871 274 2280 1664
91 (9%) 419 (41%) 356 (35%) 152 (15%) 719 (64%) 609 (55%)
302 (14%) 1189 (56%) 515 (24%) 122 (6%) 1561 (69%) 1055 (46%)
<0.0001
0.0 1.0 4.4 1.0 2.9 1.4 18.0 6.7 24.3 3.6 1.9 1.4 104 781 2524
0.3 1.0 4.2 1.0 2.8 1.4 16.8 6.3 23.7 3.7 2.3 1.4 20 (2%) 207 (19%) 890 (80%)
0.2 0.9 4.4 0.9 3.0 1.4 18.6 6.8 24.6 3.5 1.7 1.3 84 (4%) 574 (25%) 1634 (71%)
<0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
1303 451 452 328 328 356 25.3 16.0 19.2 16.6
560 (50%) 236 (21%) 209 (19%) 142 (13%) 155 (14%) 172 (15%) 29.5 16.1 23.0 16.5
743 (32%) 215 (9%) 243 (11%) 186 (8%) 173 (8%) 184 (8%) 23.3 15.5 17.1 16.3
<0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
0.017 <0.0001
See Supplementary online tables for more detailed comparison results, such as PDQ39 and MCSI subscales and event rates by study centers.
odds of having an event after one year for those with H&Y stages 1, 2, and 3 were 0.13 (95% CI: 0.03e0.54), 0.21 (0.09e0.49), and 0.33 (0.14e0.74) times lower than those with H&Y stage 4e5, respectively. In addition, presence of motor fluctuations (OR 1.76; 95% CI: 1.06e2.92) and poor quality of life (OR 1.02; 95% CI 1.01e1.03) were also associated with repeat hospital encounters (Table 3). A twosample comparison identified the following PD characteristics for hospital encounter at one-year follow-up: advanced age, inability
Fig. 1. Flowchart illustrating numbers of people with PD patients at baseline and oneyear follow-up, and those with and without hospital encounters.
to stand unaided, not living at home, presence of a care partner, poor cognition, longer TUG, lower quality of life, higher PDQ-39 score (lower quality of life), and a higher caregiver burden (e-Table 6). 4.2. Initial ER visit/hospitalizations Among the 2295 (67% of 3415) participants who did not report either an ER visit or hospitalization at baseline, follow-up one-year data was thus far available for 719 patients (31%) (Fig. 1). The demographics of this subgroup included for the secondary analyses were 436 (61%) male, mean age 66.8years 9.6, mean disease duration 9.8years 6.4, 57% H&Y stage 2 and 24% H&Y stage 3. Of these 719 participants, 178 (25%) had a new ER visit/hospitalization after one year (e-Table 7). Those who had their first hospital encounter had a significantly higher history of falling and number of co-morbidities (both P < 0.0001) than those who remained out of hospital at follow-up. Multivariate logistic regression suggested that female gender (OR: 1.59; 95% CI: 1.10e2.30), higher number of co-morbidities (OR: 1.24; 95% CI: 1.08e1.41), lower MoCA estimate score (OR: 1.09; 95% CI: 1.04e1.15), and DBS (OR: 3.03; 95% CI: 1.76e5.24) remained significant predictors of a new encounter (Table 3). Similar to the baseline population, significant demographic and clinical differences were found between patients with new hospital encounters and those without after one year. Again, these did not substantially increase hospital encounter rates after considering the above significant risk factors.
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Table 2 Logistic regression analysis results on risk of hospital encounter at baseline. Parameter
Effect
Including DBS patients (N ¼ 3415) Adjusted odds ratio
Standardized TUG Number of comorbidities Does patient have motor fluctuations DBS
Yes vs no Yes vs no
Estimate
95% CI
1.33 1.25 1.32 2.49
1.18 1.16 1.06 1.79
Overall, subjects reporting a hospital encounter at baseline were 2.05 times (95% CI: 1.74e2.43) more likely to report an encounter after one year, compared to those who did not have an ER or hospital admission at baseline. The overall rate for hospital encounters in Year 1 was 33% (336/1030), similar to baseline. 5. Discussion Several important and previously unrecognized findings regarding PD hospital encounters emerged from this prospective longitudinal cohort. PD participants had a high rate of ER visits or hospital admissions (33%) in both years of the study. At one-year follow-up, repeat hospital encounter rates were much higher (51%) than first ever hospital presentations (25% rate). The risk of one or more hospital encounters was associated with more severe PD and presence of motor fluctuations. The association with a prolonged TUG test is important as this correlates to impaired balance, falls and poor cognition in PD [20]. Though DBS surgery was associated with hospital encounters, non-DBS patients also had high rates of hospitalization and a similar risk factor profile. Importantly, these findings were clinically relevant as hospital encounters were highly correlated to a worse QOL. While many risk factors could be targeted for prevention strategies, the main theme driving hospital encounters in this large PD cohort was disease severity. Our data would suggest that to reduce or to delay hospital encounters, future therapies will need to target strategies aimed at slowing PD clinical disability. For example, first ever hospital encounters appear to be associated with falls and number of co-morbidities, so targeting these factors in people with PD may be a platform for future research aimed at reducing hospital encounters. Ten percent of participants in the NPF-QII cohort had DBS surgery. We would speculate that this percentage was reflective of care provided within specialized PD centers. The association of DBS and hospital encounters was high (48%) and not unanticipated. DBS
1.51 1.35 1.64 3.47
Excluding DBS patients (N ¼ 3056) P-value
Adjusted odds ratio Estimate
95% CI
<0.0001 <0.0001 0.011 <0.0001
1.35 1.26 1.26
1.18 1.16 1.00
P-value
1.53 1.37 1.58
<0.0001 <0.0001 0.047
surgery and battery replacements will both require hospitalization, and additionally hardware related issues and infections will increase the risk of hospitalization. However the hospital encounter rate was still high for non-DBS patients (31%). Thus, an important clinically relevant observation for hospital based practitioners will be to appreciate that the majority of ER visits for DBS patients are not DBS-related, a conclusion previously reached in a recent small study [21]. The NPF-QII study facilitated a unique look at longitudinal hospitalization data derived from PD patients. To our knowledge, this is the largest cohort of PD participants followed prospectively and drawn from a “naturalistic” setting. The increased rate of hospitalization occurred despite care being provided at an NPF peerreviewed Centers of Excellence. New presentations to the hospital were also associated with more advanced disease, higher comorbidities and DBS, as well as cognitive impairment and female gender. There is a complex interplay of gender and medical attendance that has been reported previously in the literature, and our data supports previous observations showing an increased tendency for female admissions [22,23]. Longitudinal data will be necessary to truly determine if care provided in specialized PD Centers of Excellence can be shown to reduce rates of repeat hospital encounters. The increased utilization of rehabilitative therapies and mental health services in patients with hospital encounters likely reflects inpatient practices. Patients that were hospitalized for falls, infection, or altered mental status are often referred for these services during and after presentation. Higher rates of hospital encounters at one-year follow-up, after an encounter at baseline, were associated with higher H&Y stage, thus suggesting that people with advanced PD are at particular risk for repeat hospitalization. There was some variation in center practice (e.g. admission for parenteral antiparkinsonism medications) that may have explained differences in hospital and ER odds ratio when comparing the centers [24]. However these specific practices were not recorded on the datasheet. In future studies, a comparison of the variables
Table 3 Logistic regression analysis results on risk of repeat hospital encounter after one year (with prior encounter at baseline) and risk of initial encounter after one year (no encounter at baseline). Parameter
Effect
Including DBS patients
Excluding DBS patients
Adjusted odds ratio
Repeat encounter PDQ-39 summary index (%) Hoehn & Yahr stage
Does Pt. have motor fluctuations Initial encounter MoCA estimate Number of comorbidities Gender DBS
P-value
Estimate
95% CI
1 vs 4e5 2 vs 4e5 3 vs 4e5 Yes vs no
1.02 0.13 0.21 0.33 1.76
1.01 0.03 0.09 0.14 1.06
1.04 0.54 0.49 0.74 2.92
M vs F Yes vs no
0.92 1.24 0.63 3.03
0.87 1.08 0.43 1.76
0.97 1.41 0.91 5.24
Adjusted odds ratio
P-value
Estimate
95% CI
0.01 0.01 0.00 0.01 0.03
1.03 0.18 0.22 0.55 1.91
1.01 0.04 0.08 0.22 1.04
1.05 0.80 0.56 1.40 3.50
0.0037 0.0242 0.00 0.21 0.04
0.001 0.002 0.01 <0.0001
0.92 1.30 0.63
0.87 1.14 0.43
0.97 1.49 0.94
0.001 0.0001 0.02
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between all the centers would be of interest. In particular, to identify the centers with the highest and lowest risks of ER and hospital encounters, and whether these relate to patient- or centerspecific factors. There were a number of important limitations in this study. There was no control data for comparison in the NPF-QII study, but future recommendations for NPF-QII might be to collect normal controls. The reasons for hospital encounters were not detailed on the NPF-QII case report form, and only the most recent reason underpinning a hospital encounter was captured. This may have led to recall bias for hospital encounters. A follow-up study should be designed to review medical records and to attempt to uncover the reasons for ER visits and hospital admissions. People with PD attending an outpatient clinic tend in general to be more mobile and have a lower H&Y stage, and these findings could have introduced a potential bias in the data (under-representing sicker people with PD). It should be noted that participants included in NPF-QII represented a select group of people with PD attending specialist centers of care, as reflected by the rate of DBS (10%). Thus this cohort may have had more advanced disease and more complex medical issues than centers without this demographic. Despite these limitations, the extremely large sample of participants and the study findings remain important and compelling. It has been proposed that preventing the first hospitalization will reduce costs to the health care system, especially with the known association of hospital admissions and increased ER visits [25]. Further, once hospitalized, people with PD are at greater risk for hospital morbidity and mortality [4,7,8]. The increased risk for a person with PD in the hospital has been thought to be related to the complexity of medication regimens and challenges for the nursing staff who on average are not familiar with the special needs required for optimal PD care [5,24]. More efforts to improve access to care, and to deliver PD care outside of the hospital setting will be critical to relieving the burden on the health care system. The findings in this study on motor fluctuations and mobility would suggest that aggressive optimization of PD medications and the use of interdisciplinary services such as physical therapy could possibly reduce the hospitalization burden. We would suggest that the difference in rates of hospital encounters between the centers could provide important clues to improving care. The difference in rates could be explained by the complexity of patients in each center or alternatively by the type of care provided (e.g. urgent walk-in clinics). Also, the use of elective admissions at some centers (i.e. for inpatient therapy, or intravenous pharmacotherapy) should be studied as this practice, which is discouraged by insurance carriers, will increase hospital encounter rates. The identification of center differences could drive an improvement for PD care. 6. Conclusions People with PD attending NPF Centers of Excellence have high rates of ER visits and hospitalization (one-third of participants). Hospital encounters were associated with more advanced disease, more co-morbidities, reduced mobility and lower quality of life. Prior hospital encounters predicted a higher future encounter rate in the following year (one-half of participants). Previous studies have suggested that access to urgent outpatient neurology or movement disorders clinics may be an effective means to reduce PD hospitalizations, however we did not study this point. Identifying and addressing modifiable risk factors may have the potential to reduce hospital encounters and thus also reduce hospital related complications in PD. The greater challenge for future research will be to slow the progression of clinical disability in PD as a strategy to potentially reduce hospital encounters.
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Acknowledgments The National Parkinson Centers of Excellence included in the study were: University of Florida, Markham Stouffville Hospital, Struthers Parkinson’s Center, Oregon Health & Science University, Northwestern University, Pennsylvania Hospital, Baylor College of Medicine, BIDMC, The University of Kansas Medical Center, Johns Hopkins, The Parkinson’s Institute, Medical College of Georgia, University of South Florida, Vanderbilt, Mt. Sinai, Muhammad Ali Parkinson Center, Tel Aviv Sourasky Medical Center and Nijmegen Parkinson Center. Dr Hassan made substantial contributions to conception and design, analysis and interpretation of data; drafting the article and final approval of the version to be published. Dr Wu made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Mr Schmidt made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Mr Dai made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Dr Simuni made substantial contributions to acquisition of data, analysis and interpretation of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Dr Giladi made substantial contributions to acquisition of data, analysis and interpretation of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Dr Bloem made substantial contributions to acquisition of data, analysis and interpretation of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Dr Malaty made substantial contributions to acquisition of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Dr Okun made substantial contributions to conception and design, analysis and interpretation of data; drafting the article, revising it critically for important intellectual content; and final approval of the version to be published. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.parkreldis.2013.06.006. References [1] Dodel RC, Singer M, Köhne-Volland R, Szucs T, Rathay B, Scholz E, et al. The economic impact of Parkinson’s disease. An estimation based on a 3-month prospective analysis. Pharmacoeconomics 1998;14:299e312. [2] Lindgren P, von Campenhausen S, Spottke E, Siebert U, Dodel R. Cost of Parkinson’s disease in Europe. Eur J Neurol 2005;12:68e73. [3] Guttman M, Slaughter PM, Theriault ME, DeBoer DP, Naylor CD. Burden of parkinsonism: a population-based study. Mov Disord 2003;18:313e9. [4] Woodford H, Walker R. Emergency hospital admissions in idiopathic Parkinson’s disease. Mov Disord 2005;20:1104e8. [5] Aminoff MJ, Christine CW, Friedman JH, Chou KL, Lyons KE, Pahwa R, et al. Management of the hospitalized patient with Parkinson’s disease: current state of the field and need for guidelines. Parkinsonism Relat Disord 2011;17: 139e45. [6] Gerlach OHH, Winogrodzka A, Weber WEJ. Clinical problems in the hospitalized Parkinson’s disease patient: systematic review. Mov Disord 2011;26: 197e208. [7] Guttman M, Slaughter PM, Theriault ME, DeBoer DP, Naylor CD. Parkinsonism in Ontario: comorbidity associated with hospitalization in a large cohort. Mov Disord 2004;19:49e53.
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[17] Jenkinson C, Peto V, Fitzpatrick R, Greenhall R, Hyman N. Self-reported functioning and well-being in patients with Parkinson’s disease: comparison of the short-form health survey (SF-36) and the Parkinson’s disease questionnaire (PDQ-39). Age Ageing 1995;24:505e9. [18] Stull DE. The multidimensional caregiver strain index (MCSI): its measurement and structure. J Clin Geropsychol 1996;2:175e96. [19] Dalrymple-Alford JC, MacAskill MR, Nakas CT, Livingston L, Graham C, Crucian GP, et al. well-suited screen for cognitive impairment in Parkinson disease. Neurology 2010 Nov 9;75(19):1717e25. [20] Herman T, Giladi N, Hausdorff JM. Properties of the ‘timed up and go’ test: more than meets the eye. Gerontology 2011;57:203e10. [21] Resnick AS, Foote KD, Rodriguez RL, Malaty IA, Moll JL, Carden DL, et al. The number and nature of emergency department encounters in patients with deep brain stimulators. J Neurol 2010;257:122e31. [22] Schappert SM. Ambulatory care visits to physician offices, hospital outpatient departments, and emergency departments: United States, 1997. Vital Health Stat 13 1999;143(i–iv):1e39. [23] Pinkhasov RM, Wong J, Kashanian J, Lee M, Samadi DB, Pinkhasov MM, et al. Are men shortchanged on health? Perspective on health care utilization and health risk behavior in men and women in the United States. Int J Clin Pract 2010;64:475e87. [24] Chou KL, Zamudio J, Schmidt P, Price CC, Parashos SA, Bloem BR, et al. Hospitalization in Parkinson disease: a survey of National Parkinson Foundation centers. Parkinsonism Relat Disord 2011;17:440e5. [25] Klein C, Prokhorov T, Miniovitz A, Dobronevsky E, Rabey JM. Admission of parkinsonian patients to a neurological ward in a community hospital. J Neural Transm 2009;116:1509e12.
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Parkinsonism and Related Disorders journal homepage: www.elsevier.com/locate/parkreldis
High rates and the risk factors for emergency room visits and hospitalization in Parkinson’s disease Anhar Hassan a, g, *, Samuel S. Wu b, Peter Schmidt c, Yunfeng Dai b, Tanya Simuni d, Nir Giladi e, Bastiaan R. Bloem f, Irene A. Malaty a, Michael S. Okun a, on behalf of the NPF-QII Investigators a
Center for Movement Disorders & Neurorestoration, University of Florida, Gainesville, FL, USA Department of Biostatistics, University of Florida, Gainesville, FL, USA National Parkinson’s Foundation, Miami, FL, USA d Parkinson’s disease and Movement Disorders Center, Northwestern University Feinberg School of Medicine, Abbott Hall 11th Floor, 710 North Lake Shore Drive, Chicago, IL, USA e Movement Disorders Unit, Department of Neurology, Tel-Aviv Sourasky Medical Center, Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel f Radboud University Nijmegen Medical Center, Donders Institute for Brain, Cognition and Behavior, Department of Neurology, Nijmegen, Netherlands g Department of Neurology, Mayo Clinic, Rochester, MN, USA b c
a r t i c l e i n f o
a b s t r a c t
Article history: Received 2 November 2012 Received in revised form 2 June 2013 Accepted 13 June 2013
Background: Parkinson’s disease (PD) patients are hospitalized more frequently than their peers as a result of falls, psychosis, infections and other medical complications. However, patient-specific risk factors for hospitalization are unclear. Objective: To identify rates and risk factors for hospital encounters (Emergency Room [ER] visits or hospitalization) among people with PD. Methods: 3415 PD participants (mean age 67 10 years, disease duration 9 6 years, H&Y 2 47%, H&Y 3 26%) enrolled in the prospective international multicenter NPF-QII Study. One-year follow-up data was available for 1030 patients. Rates and risk factors for hospital encounters were determined at baseline and after one year follow-up. Results: Of 3415 PD participants at study entry, 1120 (33%) reported at least one hospital encounter. Associations were: longer timed up-and-go test (OR: 1.33), increased comorbidities (OR: 1.25), motor fluctuations (OR: 1.32), and deep brain stimulation (DBS) (OR: 2.49). Of these 1120 persons, 311 had follow-up data and 158 (51%) had a repeat encounter one year later, associated with higher H&Y stage, fluctuations, and lower health-related quality-of-life. Of 2295 participants without a hospital encounter at baseline, 719 had follow-up data and 178 (25%) had a first hospital encounter one year later. Risk factors were female gender, comorbidities, lower cognition, fluctuations, and DBS. Conclusions: One-third of people with PD had a hospital encounter each year, and one-half of those had a repeat encounter. These high rates correlated with disease severity, comorbidities and DBS. There is an urgent need to develop programs to reduce PD hospital encounters. Ó 2013 Elsevier Ltd. All rights reserved.
Keywords: Hospitalization Parkinson’s disease Admissions Emergency care Comorbidities
1. Background Parkinson’s disease (PD) is a progressive neurodegenerative disorder that worldwide affects approximately 4.5 million people aged 50 or older. The cost of PD care increases with the progression of disease [1,2]. Acute care encounters (emergency room visits and hospitalizations) for PD are the most costly units of health care
* Corresponding author. Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA. E-mail address: [email protected] (A. Hassan). 1353-8020/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.parkreldis.2013.06.006
delivery. Small previous studies reported that people with PD were hospitalized more than age-matched controls [3e6]. People with PD also have higher hospital related complication rates, and a substantial risk of deterioration of their PD symptoms, independent of the reason for admission [4,7,8]. The total cumulative effects of PD hospital encounters increases burden of care, hospital costs, morbidity and mortality [9]. To reduce this societal burden it will be important to identify risk factors for hospital encounters and also to identify potential interventions to mitigate these risks. Risk factor analysis will be best accomplished by studying hospital attendance in a
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prospective and clinically well-characterized population. Improved prospective characterization of populations is becoming increasingly important to inform early intervention, and this was recently illustrated by the pioneering work that linked forced expiratory volume to mortality in cystic fibrosis [10]. In PD, increasing disease burden in aging populations has been driving both economic and public health urgency because of a need to inform on the use of lower intensity interventions [11e14]. Thus, identifying potential modifiable risk factors leading to hospital encounters could reduce morbidity, mortality, and their associated costs. This PD study was modeled after the longitudinal study performed in cystic fibrosis.
2.3. Statistical analysis
2. Methods
Results were similar when ER visits and hospitalization were analyzed individually (See online supplements e-Table 1, e-Table 2), therefore we report combined findings as a single outcome of “encounter” (either ER or hospitalization). For the cross-sectional analysis, 3415 participants (2100 male; 61%) were analyzed at their baseline visit. This cohort had a mean age 67.1 years (10.1) and mean disease duration 8.9 years (6.3). The vast majority was H&Y stage 2 (47%) or 3 (26%), and 10% had undergone DBS. Of these 3415, 1120 (33%) reported an ER visit or hospitalization (Table 1, Fig. 1. Additional data e-Table 3). The top two reasons for hospital encounters were injury or infection, although less than 40% reported a reason (e-Table 4). The frequencies of reasons for hospital admission were similar. After excluding those with DBS, 948 (31% of 3056) had an encounter. Hospital encounters associated by logistic regression with the clinical and demographic variables were: longer timed up-and-go test (OR: 1.33), higher number of co-morbidities (OR: 1.25), presence of motor fluctuations (OR: 1.32), and presence of DBS (OR: 2.49) as predictors of hospital encounters (Table 2). There were also significant variations across study centers in the hospital encounter rate, ranging from 16% to 44% (e-Table 3). The adjusted OR ranged from 1.05 to 5.46 compared to the center with the lowest risk, and was 2.0 for 12 centers compared to the center with the lowest risk (e-Table 5). Participants with prior DBS had a higher rate of hospitalization (48%) vs those without (31%, P < 0.0001). After excluding participants with DBS, the significant risk factors remained the same however, with very minor changes in odds ratios (Table 2). Participants with hospital encounters reported more comorbidities in our assessment than those without. There was significantly more frequent use of each type of medication, with the exception of stimulants and anticholinergic medications, and increased use of physical, occupational, speech therapies, and mental health services in participants reporting hospital encounters. In addition, they were significantly older, with longer disease duration (10 vs 8 years) and more advanced disease, worse cognition, more frequent falls, not living at home, required a care partner, reported a lower health-related quality of life, and had a higher caregiver burden (P < 0.0001 for all, Table 1). However, none of these factors was correlated with higher hospitalization rates after controlling for the factors listed in Table 2.
2.1. Study design We examined the information available from the on-going international multicenter National Parkinson Foundation Quality Improvement Initiative (NPF-QII), a long-term observational clinical study. NPF-QII prospectively collects detailed demographic and clinical data on PD patients attending NPF Centers of Excellence, and does this annually using methods described previously [15]. PD participants submit written informed consent to enroll in the study. Currently 19 centers are participating in the study and 18 centers contributed data to this analysis, located in the United States, Canada, Netherlands, and Israel. We analyzed the NPF-QII data to determine the frequency of ER visits and hospitalizations in our cohort (hereafter termed “encounters”) and correlated them with demographic and clinical variables in a cross-sectional analysis. We performed a longitudinal analysis for predictors of new encounters and repeat encounters. 2.2. Participants The NPF-QII study data was reviewed to identify all PD participants where information about hospital encounters (including admissions and ER visits) was available. There were 3415 participants that met these criteria for the crosssectional analysis. There were 1030 participants with complete follow-up data at both baseline and one year later for the longitudinal analysis at time of data analysis. Demographic and clinical data included gender, race, BMI, age at onset, age at diagnosis, disease duration, presence of tremor, motor fluctuations, Hoehn and Yahr (H&Y) stage, co-morbidities, ability to stand unaided, living situation, presence or absence of a regular care partner, exercise habits, medications, other treatments (physical therapy, occupational therapy, speech therapy), deep brain stimulation (DBS), timed up and go test (TUG) [16], Parkinson’s Disease Quality of Life Questionnaire (PDQ-39) [17], and Multidimensional Caregiver Strain Index (MCSI) [18] scores. In addition, we utilized MoCA estimate, a weighted cognitive score formed from a combination of immediate and delayed 5 word recall and semantic fluency (animals) scores, to optimally predict Montreal Cognitive Assessment (MoCA) [19] results. The PDQ-39 is a validated, widely used scale completed by the patient, and was used to assess health-related quality of life in this cohort. It includes 39 items subdivided into eight domains: mobility, activities of daily living, emotional well-being, stigma, social support, cognition, communication, and bodily discomfort [17]. The MCSI is an 18-item tool completed by the caregiver, measuring 6 domains of subjective response to stressors. Subscores include physical strain, social constraints, financial strain, time constraints, interpersonal strain, and elder demanding/manipulative [18]. The scale has not been validated in PD, but expert review recommended this was appropriate for the PD population [15]. Therapeutic interventions including 10 classes of medications commonly used in PD and five different allied health interventions were recorded by identifying if they are started, stopped or continued at the time of data collection. Full details on the data form and collection protocol have addressed previously [15]. Subject-reported comorbidities were assessed, with a history of cardiovascular issues, cancer, respiratory problems, arthritis, diabetes, other neurological, and “other” all assessed and ranked for severity by the patient. Falls were characterized by frequency, and exercise programs by hours per week. ER and hospital admission rates were examined both individually and as combined values. An ER visit was defined as an evaluation in the emergency department where the participant was discharged home. Hospitalization included any admission for either a PD-related or a non-PD related cause, and included elective admissions (e.g. DBS battery change). Subjects reported whether either event had occurred within in the prior 12 months. For the primary analysis, we compared patients with a history of ER visit or hospital admission at study entry vs those without, in order to identify candidate risk factors for these encounters. For secondary analysis, we examined the available data one year later to identify follow-up rates of hospital encounters.
Hospital admissions and ER visits were analyzed individually and also as a single outcome termed “encounter”. A two-sample t-test for continuous variables and chisquare test for the categorical variable was used to compare between those who had ER visits vs those who did not, and between those hospitalized vs those who were not. For risk factor correlations, multivariate logistic regression with backward selection was performed to identify risk factors for the encounter at baseline. The above analyses were repeated excluding those patients who had DBS. Two more logistic regressions were conducted to identify risk factors for new ER visit or hospitalization after one year, stratified by whether the patients had an encounter at baseline.
3. Results
4. Longitudinal analysis 4.1. Repeat ER visit/hospitalizations Of the 1120 participants hospitalized at baseline, follow-up data was thus far available for 311 (28%) after one-year follow-up at the time of the data analysis (Fig. 1). Of these 311, 158 (51%) reported a repeat hospital encounter after one year. Multivariate logistic regression suggested that higher H&Y stage was the major risk factor associated with a repeat hospital encounter. The
A. Hassan et al. / Parkinsonism and Related Disorders 19 (2013) 949e954
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Table 1 Summary of baseline demographic and clinical data for PD patients with a hospital encounter vs those without.a Overall (N ¼ 3415)
Variable
Demographic variables Age Male, n (%) White, n (%) Disease duration Social variables Patient can stand unaided Living at home No regular care partner PD diagnosis/stage Hoehn & Yahr stage
Rest tremor present Motor fluctuations Clinical outcomes Standardized TUG Immediate word recall Delayed word recall Verbal fluency MoCA estimate Number of comorbidities Medications
Other treatments Physical therapy, n (%) Occupational therapy, n (%) Speech therapy, n (%) Social worker/counseling, n (%) Mental health Tx or referral, n (%) DBS, n (%) PDQ39 summary index MCSI index a
1 2 3 4e5
No 1 med Multi-meds
Hospital encounter
P-value
Yes (N ¼ 1120)
No (N ¼ 2295)
67.1 10.1 2100 3180 8.9 6.3
68.7 10.2 680 (61%) 1058 (96%) 10.1 6.5
66.3 9.9 1420 (62%) 2122 (94%) 8.4 6.1
<0.0001 0.475 0.013 <0.0001
3060 3267 507
958 (87%) 1033 (92%) 152 (14%)
2102 (94%) 2234 (97%) 355 (16%)
<0.0001 <0.0001 <0.0001
393 1608 871 274 2280 1664
91 (9%) 419 (41%) 356 (35%) 152 (15%) 719 (64%) 609 (55%)
302 (14%) 1189 (56%) 515 (24%) 122 (6%) 1561 (69%) 1055 (46%)
<0.0001
0.0 1.0 4.4 1.0 2.9 1.4 18.0 6.7 24.3 3.6 1.9 1.4 104 781 2524
0.3 1.0 4.2 1.0 2.8 1.4 16.8 6.3 23.7 3.7 2.3 1.4 20 (2%) 207 (19%) 890 (80%)
0.2 0.9 4.4 0.9 3.0 1.4 18.6 6.8 24.6 3.5 1.7 1.3 84 (4%) 574 (25%) 1634 (71%)
<0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
1303 451 452 328 328 356 25.3 16.0 19.2 16.6
560 (50%) 236 (21%) 209 (19%) 142 (13%) 155 (14%) 172 (15%) 29.5 16.1 23.0 16.5
743 (32%) 215 (9%) 243 (11%) 186 (8%) 173 (8%) 184 (8%) 23.3 15.5 17.1 16.3
<0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
0.017 <0.0001
See Supplementary online tables for more detailed comparison results, such as PDQ39 and MCSI subscales and event rates by study centers.
odds of having an event after one year for those with H&Y stages 1, 2, and 3 were 0.13 (95% CI: 0.03e0.54), 0.21 (0.09e0.49), and 0.33 (0.14e0.74) times lower than those with H&Y stage 4e5, respectively. In addition, presence of motor fluctuations (OR 1.76; 95% CI: 1.06e2.92) and poor quality of life (OR 1.02; 95% CI 1.01e1.03) were also associated with repeat hospital encounters (Table 3). A twosample comparison identified the following PD characteristics for hospital encounter at one-year follow-up: advanced age, inability
Fig. 1. Flowchart illustrating numbers of people with PD patients at baseline and oneyear follow-up, and those with and without hospital encounters.
to stand unaided, not living at home, presence of a care partner, poor cognition, longer TUG, lower quality of life, higher PDQ-39 score (lower quality of life), and a higher caregiver burden (e-Table 6). 4.2. Initial ER visit/hospitalizations Among the 2295 (67% of 3415) participants who did not report either an ER visit or hospitalization at baseline, follow-up one-year data was thus far available for 719 patients (31%) (Fig. 1). The demographics of this subgroup included for the secondary analyses were 436 (61%) male, mean age 66.8years 9.6, mean disease duration 9.8years 6.4, 57% H&Y stage 2 and 24% H&Y stage 3. Of these 719 participants, 178 (25%) had a new ER visit/hospitalization after one year (e-Table 7). Those who had their first hospital encounter had a significantly higher history of falling and number of co-morbidities (both P < 0.0001) than those who remained out of hospital at follow-up. Multivariate logistic regression suggested that female gender (OR: 1.59; 95% CI: 1.10e2.30), higher number of co-morbidities (OR: 1.24; 95% CI: 1.08e1.41), lower MoCA estimate score (OR: 1.09; 95% CI: 1.04e1.15), and DBS (OR: 3.03; 95% CI: 1.76e5.24) remained significant predictors of a new encounter (Table 3). Similar to the baseline population, significant demographic and clinical differences were found between patients with new hospital encounters and those without after one year. Again, these did not substantially increase hospital encounter rates after considering the above significant risk factors.
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Table 2 Logistic regression analysis results on risk of hospital encounter at baseline. Parameter
Effect
Including DBS patients (N ¼ 3415) Adjusted odds ratio
Standardized TUG Number of comorbidities Does patient have motor fluctuations DBS
Yes vs no Yes vs no
Estimate
95% CI
1.33 1.25 1.32 2.49
1.18 1.16 1.06 1.79
Overall, subjects reporting a hospital encounter at baseline were 2.05 times (95% CI: 1.74e2.43) more likely to report an encounter after one year, compared to those who did not have an ER or hospital admission at baseline. The overall rate for hospital encounters in Year 1 was 33% (336/1030), similar to baseline. 5. Discussion Several important and previously unrecognized findings regarding PD hospital encounters emerged from this prospective longitudinal cohort. PD participants had a high rate of ER visits or hospital admissions (33%) in both years of the study. At one-year follow-up, repeat hospital encounter rates were much higher (51%) than first ever hospital presentations (25% rate). The risk of one or more hospital encounters was associated with more severe PD and presence of motor fluctuations. The association with a prolonged TUG test is important as this correlates to impaired balance, falls and poor cognition in PD [20]. Though DBS surgery was associated with hospital encounters, non-DBS patients also had high rates of hospitalization and a similar risk factor profile. Importantly, these findings were clinically relevant as hospital encounters were highly correlated to a worse QOL. While many risk factors could be targeted for prevention strategies, the main theme driving hospital encounters in this large PD cohort was disease severity. Our data would suggest that to reduce or to delay hospital encounters, future therapies will need to target strategies aimed at slowing PD clinical disability. For example, first ever hospital encounters appear to be associated with falls and number of co-morbidities, so targeting these factors in people with PD may be a platform for future research aimed at reducing hospital encounters. Ten percent of participants in the NPF-QII cohort had DBS surgery. We would speculate that this percentage was reflective of care provided within specialized PD centers. The association of DBS and hospital encounters was high (48%) and not unanticipated. DBS
1.51 1.35 1.64 3.47
Excluding DBS patients (N ¼ 3056) P-value
Adjusted odds ratio Estimate
95% CI
<0.0001 <0.0001 0.011 <0.0001
1.35 1.26 1.26
1.18 1.16 1.00
P-value
1.53 1.37 1.58
<0.0001 <0.0001 0.047
surgery and battery replacements will both require hospitalization, and additionally hardware related issues and infections will increase the risk of hospitalization. However the hospital encounter rate was still high for non-DBS patients (31%). Thus, an important clinically relevant observation for hospital based practitioners will be to appreciate that the majority of ER visits for DBS patients are not DBS-related, a conclusion previously reached in a recent small study [21]. The NPF-QII study facilitated a unique look at longitudinal hospitalization data derived from PD patients. To our knowledge, this is the largest cohort of PD participants followed prospectively and drawn from a “naturalistic” setting. The increased rate of hospitalization occurred despite care being provided at an NPF peerreviewed Centers of Excellence. New presentations to the hospital were also associated with more advanced disease, higher comorbidities and DBS, as well as cognitive impairment and female gender. There is a complex interplay of gender and medical attendance that has been reported previously in the literature, and our data supports previous observations showing an increased tendency for female admissions [22,23]. Longitudinal data will be necessary to truly determine if care provided in specialized PD Centers of Excellence can be shown to reduce rates of repeat hospital encounters. The increased utilization of rehabilitative therapies and mental health services in patients with hospital encounters likely reflects inpatient practices. Patients that were hospitalized for falls, infection, or altered mental status are often referred for these services during and after presentation. Higher rates of hospital encounters at one-year follow-up, after an encounter at baseline, were associated with higher H&Y stage, thus suggesting that people with advanced PD are at particular risk for repeat hospitalization. There was some variation in center practice (e.g. admission for parenteral antiparkinsonism medications) that may have explained differences in hospital and ER odds ratio when comparing the centers [24]. However these specific practices were not recorded on the datasheet. In future studies, a comparison of the variables
Table 3 Logistic regression analysis results on risk of repeat hospital encounter after one year (with prior encounter at baseline) and risk of initial encounter after one year (no encounter at baseline). Parameter
Effect
Including DBS patients
Excluding DBS patients
Adjusted odds ratio
Repeat encounter PDQ-39 summary index (%) Hoehn & Yahr stage
Does Pt. have motor fluctuations Initial encounter MoCA estimate Number of comorbidities Gender DBS
P-value
Estimate
95% CI
1 vs 4e5 2 vs 4e5 3 vs 4e5 Yes vs no
1.02 0.13 0.21 0.33 1.76
1.01 0.03 0.09 0.14 1.06
1.04 0.54 0.49 0.74 2.92
M vs F Yes vs no
0.92 1.24 0.63 3.03
0.87 1.08 0.43 1.76
0.97 1.41 0.91 5.24
Adjusted odds ratio
P-value
Estimate
95% CI
0.01 0.01 0.00 0.01 0.03
1.03 0.18 0.22 0.55 1.91
1.01 0.04 0.08 0.22 1.04
1.05 0.80 0.56 1.40 3.50
0.0037 0.0242 0.00 0.21 0.04
0.001 0.002 0.01 <0.0001
0.92 1.30 0.63
0.87 1.14 0.43
0.97 1.49 0.94
0.001 0.0001 0.02
A. Hassan et al. / Parkinsonism and Related Disorders 19 (2013) 949e954
between all the centers would be of interest. In particular, to identify the centers with the highest and lowest risks of ER and hospital encounters, and whether these relate to patient- or centerspecific factors. There were a number of important limitations in this study. There was no control data for comparison in the NPF-QII study, but future recommendations for NPF-QII might be to collect normal controls. The reasons for hospital encounters were not detailed on the NPF-QII case report form, and only the most recent reason underpinning a hospital encounter was captured. This may have led to recall bias for hospital encounters. A follow-up study should be designed to review medical records and to attempt to uncover the reasons for ER visits and hospital admissions. People with PD attending an outpatient clinic tend in general to be more mobile and have a lower H&Y stage, and these findings could have introduced a potential bias in the data (under-representing sicker people with PD). It should be noted that participants included in NPF-QII represented a select group of people with PD attending specialist centers of care, as reflected by the rate of DBS (10%). Thus this cohort may have had more advanced disease and more complex medical issues than centers without this demographic. Despite these limitations, the extremely large sample of participants and the study findings remain important and compelling. It has been proposed that preventing the first hospitalization will reduce costs to the health care system, especially with the known association of hospital admissions and increased ER visits [25]. Further, once hospitalized, people with PD are at greater risk for hospital morbidity and mortality [4,7,8]. The increased risk for a person with PD in the hospital has been thought to be related to the complexity of medication regimens and challenges for the nursing staff who on average are not familiar with the special needs required for optimal PD care [5,24]. More efforts to improve access to care, and to deliver PD care outside of the hospital setting will be critical to relieving the burden on the health care system. The findings in this study on motor fluctuations and mobility would suggest that aggressive optimization of PD medications and the use of interdisciplinary services such as physical therapy could possibly reduce the hospitalization burden. We would suggest that the difference in rates of hospital encounters between the centers could provide important clues to improving care. The difference in rates could be explained by the complexity of patients in each center or alternatively by the type of care provided (e.g. urgent walk-in clinics). Also, the use of elective admissions at some centers (i.e. for inpatient therapy, or intravenous pharmacotherapy) should be studied as this practice, which is discouraged by insurance carriers, will increase hospital encounter rates. The identification of center differences could drive an improvement for PD care. 6. Conclusions People with PD attending NPF Centers of Excellence have high rates of ER visits and hospitalization (one-third of participants). Hospital encounters were associated with more advanced disease, more co-morbidities, reduced mobility and lower quality of life. Prior hospital encounters predicted a higher future encounter rate in the following year (one-half of participants). Previous studies have suggested that access to urgent outpatient neurology or movement disorders clinics may be an effective means to reduce PD hospitalizations, however we did not study this point. Identifying and addressing modifiable risk factors may have the potential to reduce hospital encounters and thus also reduce hospital related complications in PD. The greater challenge for future research will be to slow the progression of clinical disability in PD as a strategy to potentially reduce hospital encounters.
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Acknowledgments The National Parkinson Centers of Excellence included in the study were: University of Florida, Markham Stouffville Hospital, Struthers Parkinson’s Center, Oregon Health & Science University, Northwestern University, Pennsylvania Hospital, Baylor College of Medicine, BIDMC, The University of Kansas Medical Center, Johns Hopkins, The Parkinson’s Institute, Medical College of Georgia, University of South Florida, Vanderbilt, Mt. Sinai, Muhammad Ali Parkinson Center, Tel Aviv Sourasky Medical Center and Nijmegen Parkinson Center. Dr Hassan made substantial contributions to conception and design, analysis and interpretation of data; drafting the article and final approval of the version to be published. Dr Wu made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Mr Schmidt made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Mr Dai made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Dr Simuni made substantial contributions to acquisition of data, analysis and interpretation of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Dr Giladi made substantial contributions to acquisition of data, analysis and interpretation of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Dr Bloem made substantial contributions to acquisition of data, analysis and interpretation of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Dr Malaty made substantial contributions to acquisition of data; revising the draft critically for important intellectual content; and final approval of the version to be published. Dr Okun made substantial contributions to conception and design, analysis and interpretation of data; drafting the article, revising it critically for important intellectual content; and final approval of the version to be published. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.parkreldis.2013.06.006. References [1] Dodel RC, Singer M, Köhne-Volland R, Szucs T, Rathay B, Scholz E, et al. The economic impact of Parkinson’s disease. An estimation based on a 3-month prospective analysis. Pharmacoeconomics 1998;14:299e312. [2] Lindgren P, von Campenhausen S, Spottke E, Siebert U, Dodel R. Cost of Parkinson’s disease in Europe. Eur J Neurol 2005;12:68e73. [3] Guttman M, Slaughter PM, Theriault ME, DeBoer DP, Naylor CD. Burden of parkinsonism: a population-based study. Mov Disord 2003;18:313e9. [4] Woodford H, Walker R. Emergency hospital admissions in idiopathic Parkinson’s disease. Mov Disord 2005;20:1104e8. [5] Aminoff MJ, Christine CW, Friedman JH, Chou KL, Lyons KE, Pahwa R, et al. Management of the hospitalized patient with Parkinson’s disease: current state of the field and need for guidelines. Parkinsonism Relat Disord 2011;17: 139e45. [6] Gerlach OHH, Winogrodzka A, Weber WEJ. Clinical problems in the hospitalized Parkinson’s disease patient: systematic review. Mov Disord 2011;26: 197e208. [7] Guttman M, Slaughter PM, Theriault ME, DeBoer DP, Naylor CD. Parkinsonism in Ontario: comorbidity associated with hospitalization in a large cohort. Mov Disord 2004;19:49e53.
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