Original Article
Categorized hospital charges of acute ischemic stroke according to trial of org 10172 in acute stroke treatment classification Hyejung Chang, Sung Sang Yoon1, Young Dae Kwon2 Department of Health Services Management, Kyung Hee University School of Management, 1Department of Neurology, Kyung Hee University College of Medicine, 2Department of Humanities and Social Medicine, College of Medicine and Catholic Institute for Healthcare Management, The Catholic University of Korea, Seoul, Korea
Abstract
Address for correspondence: Prof. Young Dae Kwon, Department of Humanities and Social Medicine, College of Medicine and Catholic Institute for Healthcare Management, The Catholic University of Korea, 222 Banpo‑daero, Seocho‑gu, Seoul 137‑701, Korea. E‑mail: [email protected] Received : 17‑09‑2013 Review completed : 27‑09‑2013 Accepted : 18‑12‑2013
Background: Previous studies have shown that the cost of hospitalization due to stroke is significantly associated with the length of stay, stroke severity and other clinical characteristics, as well as various socio‑demographic factors. However, these studies have been rather inconsistent with regard to the influence of stroke subtypes on costs. Aims: This study was examined and compared hospital charges of in‑patients with acute ischemic stroke according to the Trial of Org 10172 in Acute Stroke Treatment classification. Materials and Methods: The costs of case of 749 patients with first ever ischemic stroke who were admitted to an academic medical center between January 2006 and December 2008 were analyzed. The hospital charges were compared among the stroke subtypes using Analysis of Variance. Multiple regression analyses were further performed to test the significance of the impact of the stroke subtype after controlling for other variables. Results: The stroke subtype turned out to be a statistically significant factor influencing both the total charge and several categorized charges even after controlling for other contributing factors such as hospital length of stay and stroke severity. Conclusions: This study concludes that the stroke subtype should be included when considering in‑patient medical expenses of acute ischemic stroke. Key words: Hospital charges, ischemic stroke, stroke subtype, Trial of Org 10172
in acute stroke treatment classification
Introduction The cost of hospitalization due to stroke is significantly associated with the length of stay and clinical Access this article online Quick Response Code:
Website: www.neurologyindia.com PMID: *** DOI: 10.4103/0028-3886.125271
Neurology India | Nov-Dec 2013 | Vol 61 | Issue 6
characteristics, as well as various socio‑demographic factors.[1‑5] Among the clinical factors, the stroke severity has been identified as a major factor in the escalation of costs.[4‑10] The ischemic stroke subtype classifications based on the underlying etiology can influence the treatment methods and process. [11] However, the observation in the earlier studies have been rather inconsistent with regard to the influence of stroke subtype on costs of acute ischemic stroke.[8,12‑15] This study assessed the hospital charges for acute ischemic stroke according to the stroke subtype and determined whether stroke subtype is a contributor to the hospital charges. 633
Chang, et al.: Hospital charges according to stroke subtypes
Materials and Methods Study population The study subjects include 749 consecutive patients with first‑ever ischemic stroke (within 7 days of stroke onset) admitted to the neurology ward in an academic medical center between January 2006 and December 2008. The hospital is a tertiary care center in the northeastern region of Seoul, Korea and patients are often referred to this hospital from other medical facilities. During the period, 1,302 patients with ischemic stroke were admitted. This included 956 patients with first‑ever acute ischemic stroke, of them 891 patients were admitted within 7 days of stroke onset. Ultimately, for the final analysis, 749 patients with all the required clinical information and billing data were included in the study. The diagnoses of ischemic stroke was based on the data obtained from the medical history, neurologic findings, computerized tomography, magnetic resonance imaging, magnetic resonance angiography and other neuroimaging findings. This study was approved by the Institutional Review Board of Kyung Hee University Medical Center, Seoul, Korea. The board permitted a waiver of informed consent because the study involved anonymous data collected for non‑research purposes. Data and variables The data composed of two components: (1) Socio‑demographic and clinical characteristics of each patient; and (2) information on the hospital charges. The data for the first component were collected from the hospital stroke registry database and the data for the second component were retrieved from the hospital’s Patient Management Information System. The variables selected for this study were based on factors showing an effect on the hospital costs in the previous studies. The socio‑demographic characteristics included age, gender and health insurance type. The clinical characteristics consisted of the patient’s admission route, referral for admission, the time interval between onset and arrival at hospital, risk profile, stroke subtype and stroke severity at admission, treatment modalities, length of hospital stay (LOS) and the destination after discharge. Stroke severity was evaluated using the National Institutes of Health Stroke Scale (NIHSS) at the time of admission. Stroke subtype categorization was done using Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification by two board certified neurologists. Patients were broadly classified into five categories based on the underlying mechanism of stroke: Large artery atherosclerosis (LAA) small vessel occlusion (SVO), cardioembolism (CE), other determined etiology (OD), or undetermined etiology (UD). The UD type was further classified into three subcategories: Two or more 634
etiologies (2 or more), negative study results (negative) and incomplete study (incomplete). With regard to the data on medical expenses for each patient collected and analyzed were determined by a fee‑for‑service schedule based on the type and quantity of services provided. Although patients and the National Health Insurance Service share the payments for services covered by the National Health Insurance or Medical Aid, patients pay in full for services not covered by them. In this study, both insured and uninsured hospital charges were included in the analysis. The various hospital charges were categorized into seven items: Room and board, laboratory tests, imaging studies, oral medication, injections, operations and procedures and others. Six of these seven categories were grouped into three broad categories to simplify analyses and facilitate comparisons with previous studies. The three categories were: (1) Room and board (2) laboratory tests and imaging studies (investigations); and (3) medication, injections and operations and procedures (treatment). “Other charges were excluded from the classification of the three categories due to its complex characteristics. Statistical analysis The data analysis was descriptive for the demographic data and clinical characteristics using frequency, percentage, mean and median. The hospital charges among the stroke subtype groups were compared using Analysis of Variance and multiple regression analyses. In the multiple regression analyses, the hospital charges were log‑transformed to satisfy the normality and homoscedasticity assumptions of linear regression. The variance inflation factor for each predictor for all given cases were computed to determine the existence of multicollinearity. All analyses were performed using the Statistical Analysis System, version 9.2 (SAS Institute, Cary, NC, USA). In addition, all hospital charges were adjusted to the 2008 rates and converted into U.S. dollars. Since the fee schedule had been increased over 3 years, from January 2006 to December 2008, the adjustment to the 2008 rates excluded the effect of inflation on medical expense. A conversion rate of 1 U.S. dollar to 995.83 Korean won was utilized; this figure was determined by calculating the average exchange rate over the 3 year duration of the study.
Results Sample characteristics Of the 749 (60.0% males, mean age 64.5 years) patients included in the study, the distribution of stroke subtypes were: LLA 31.9%, SVO 32.7%, CE 10.9%, UD 23.5% and OD 1.0%. Among the UD, in 63 (8.6%) patients there was two or more mechanism for the stroke, in Neurology India | Nov-Dec 2013 | Vol 61 | Issue 6
Chang, et al.: Hospital charges according to stroke subtypes
38 (4.9%) patients no cause could be demonstrated and in 75 (10.0%) patients the stroke work‑up was incomplete. The mean NIHSS score at admission was 5.5 and the average LOS was 13.9 days [Table 1]. Total and categorized hospital costs The mean total hospital cost of care was $4,608 and the per days with charges of $401. Costs of imaging accounted for 30.1% and room and board for 28.2% of total hospital charges. Other charges included: Laboratory tests for 13.6%, injections for 12.8%, medications for 3.5%, operations and procedures for 7.6% [Table 2]. Hospital charges according to the stroke subtypes The total and daily charges were significantly different across stroke subtypes. The highest total charge was for patients with OD stroke ($6,935), followed by patients with CE stroke ($6,510) and the lowest total charge patients with SVO stroke ($3,428). In contrast, the highest daily charge was for patients with UD‑incomplete stroke ($499) and these charges was 1.4 times higher than the lowest daily charge for patients with OD stroke ($366). Table 1: Baseline characteristics of patients with acute ischemic stroke (n=749) Gender Female/male (%) 40.0/60.0 Age (years) Mean/median (%) 64.5/65 Insurance type NHI/medical aid (%) 96.7/3.3 Admission route Emergency room/out‑patient departments (%) 75.0/25.0 Referral for admission Direct visit/referred (%) 70.4/29.6 Interval between onset and arrival (h) Mean/median 38.2/22 Risk factor TIA/hypertension/DM/hyperlipidemia/smoking/ 1.8/68.4/33.2/ heart diseases (%) 39.4/34.4/18.8 Subtype (TOAST) LAA/SVO/CE/OD/UD‑2 or more/UD‑negative/ 31.9/32.7/10.9/ UD‑incomplete (%) 1.0/8.6/4.9/10.0 NIHSS score at admission Mean/median 5.5/4 Treatment Operation/ICU/thrombolytic*/anti‑coagulant/ 2.2/10.5/6.2/ anti‑platelet (%) 18.0/72.5 Length of stay (days) Mean/median 13.9/9 Destination after discharge Referred to other institutions/to home/in‑hospital 19.3/79.3/1.4 death (%) *Intravenous injection of rt‑PA. NHI ‑ National health insurance, TIA ‑ Transient ischemic attack, DM ‑ Diabetes mellitus, LAA ‑ Large artery atherosclerosis, SVO ‑ Small vessel occlusion, CE ‑ Cardioembolism, OD ‑ Other determined etiology, UD ‑ Undetermined etiology, NIHSS ‑ National Institutes of Health Stroke Scale, ICU ‑ Intensive care unit, TOAST ‑ Trial of Org 10172 in acute stroke treatment
Neurology India | Nov-Dec 2013 | Vol 61 | Issue 6
The categorized analysis also showed significantly different hospital charges across the stroke subtypes. Charges for imaging studies were highest in patients with OD stroke ($2,168), but the proportion in the total charges was highest in patients with SVO stroke (37.1%). Patients with UD‑incomplete stroke had both the lowest amount ($1,152) and the lowest proportion (21.5%) of imaging study charges. The hospital charges according to the three broad categories of the room and board, examination were also different among the subtypes. Hospital charge was the highest for patient with OD stroke, $2,412, and $3,148 respectively for room and board and examination. Cost for treatment was highest for patients with UD‑incomplete stroke, $1,919 and for patients with SVO, the charges were lowest $931, $1,728 and $685 in all three categories, respectively. Effect of the stroke subtypes on hospital charges The stroke subtype was a statistically significant determining factor for total hospital charges after controlling for other contributing factors. The CE stroke subtype was a significant factor in escalating the in-hospital cost of care, whereas UD‑incomplete is a significant factor in reducing the in-hospital cost of care. The other factors associated with significant increasing in the total charges included stroke severity at admission and LOS. Referral at discharge was a significant factor in reducing total charges. Of the six multiple regression models for categorized charges, the stroke subtype was significant in five models: Room and board, laboratory tests, imaging studies, medication and injection. The CE stroke subtype was significantly associated with higher charges for room and board and laboratory tests and lower for charge for medication. The UD‑2 or more stroke subtype was significantly associated with higher charge for imaging studies and UD‑negative stroke subtype was associated with lower charges for injection. Moreover, the UD‑incomplete stroke subtype was significantly associated with lower charges for room and board, imaging studies and medication. Within the three broad categories, the CE subtype was a significant factor associated with increased charges for room and board and examination and the UD‑incomplete stroke subtype was a significant factor associated with decreased charges for room and board and examination [Table 3].
Discussion Previous studies have investigated the determinants of the costs of care for patients with ischemic stroke, but influence on the cost of care of the stroke subtype has not been well studied. The study by Yoneda et al. found 635
Chang, et al.: Hospital charges according to stroke subtypes
Table 2: Mean value of total and categorized in‑patient charges according to stroke subtype (Unit: $)
Total charges Room and board Examination Laboratory tests Imaging studies CT MRI Sonography Others Treatment Medication Injection Op/procedure Physicians fee Others Daily charges LOS (mean, days) NIHSS score at admission (mean)
All (n=749) (%)
LAA (n=239) (%)
SVO (n=243) (%)
CE (n=84) (%)
OD (n=7) (%)
2 or more (n=63) (%)
Negative (n=38) (%)
4,608 (100.0) 1,300 (28.2) 2,013 (43.7) 627 (13.6) 1,386 (30.1) 155 736 352 144 1,102 (23.9) 160 (3.5) 592 (12.8) 350 (7.6) 49 (1.1) 144 (3.1) 401 14 5
4,720 (100.0) 1,355 (28.7) 2,053 (43.5) 579 (12.3) 1,474 (31.2) 135 740 395 205 1,058 (22.4) 172.0 (3.6) 552 (11.7) 334 (7.1) 49 (1.0) 204 (4.3) 362 15 5
3,428 (100.0) 931 (27.2) 1,728 (50.4) 454 (13.2) 1,273 (37.1) 122 745 337 69 685 (20.0) 132 (3.9) 421 (12.3) 133 (3.9) 46 (1.3) 39 (1.1) 412 9 3
6,510 (100.0) 1,951 (30.0) 2,515 (38.6) 1,086 (16.7) 1,430 (22.0) 225 733 338 134 1,768 (27.2) 178 (2.7) 913 (14.0) 677 (10.4) 56 (0.9) 219 (3.4) 418 19 9
6,935 (100.0) 2,412 (34.8) 3,148 (45.4) 980 (14.1) 2,168 (31.3) 237 916 535 480 1,216 (17.5) 269 (3.9) 398 (5.7) 549 (7.9) 51 (0.7) 108 (1.6) 366 26 6
5,372 (100.0) 1,531 (28.5) 2,260 (42.1) 666 (12.4) 1,594 (29.7) 211 786 402 195 1,209 (22.5) 186 (3.5) 547 (10.2) 476 (8.9) 52 (1.0) 320 (6.0) 381 19 6
4,032 (100.0) 1,199 (29.7) 1,988 (49.3) 550 (13.6) 1,438 (35.7) 134 799 341 164 754 (18.7) 151 (3.7) 374 (9.3) 229 (5.7) 48 (1.2) 42 (1.0) 384 12 6
Incomplete F test (n=75) (%) 5,370 (100.0) 1,343 (25.0) 1,945 (36.2) 793 (14.8) 1,152 (21.5) 200 605 228 119 1,919 (35.7) 164 (3.1) 1,076 (20.0) 679 (12.6) 52 (1.0) 111 (2.1) 499 16 8
7.51‡ 8.49‡ 7.81‡ 10.22‡ 8.25‡ 6.99‡ 3.16† 11.12‡ 5.65‡ 3.04† 7.50‡ 6.74‡ 3.57† 1.32 4.44‡ 9.18‡ 20.53‡
P
Categorized hospital charges of acute ischemic stroke according to trial of org 10172 in acute stroke treatment classification Hyejung Chang, Sung Sang Yoon1, Young Dae Kwon2 Department of Health Services Management, Kyung Hee University School of Management, 1Department of Neurology, Kyung Hee University College of Medicine, 2Department of Humanities and Social Medicine, College of Medicine and Catholic Institute for Healthcare Management, The Catholic University of Korea, Seoul, Korea
Abstract
Address for correspondence: Prof. Young Dae Kwon, Department of Humanities and Social Medicine, College of Medicine and Catholic Institute for Healthcare Management, The Catholic University of Korea, 222 Banpo‑daero, Seocho‑gu, Seoul 137‑701, Korea. E‑mail: [email protected] Received : 17‑09‑2013 Review completed : 27‑09‑2013 Accepted : 18‑12‑2013
Background: Previous studies have shown that the cost of hospitalization due to stroke is significantly associated with the length of stay, stroke severity and other clinical characteristics, as well as various socio‑demographic factors. However, these studies have been rather inconsistent with regard to the influence of stroke subtypes on costs. Aims: This study was examined and compared hospital charges of in‑patients with acute ischemic stroke according to the Trial of Org 10172 in Acute Stroke Treatment classification. Materials and Methods: The costs of case of 749 patients with first ever ischemic stroke who were admitted to an academic medical center between January 2006 and December 2008 were analyzed. The hospital charges were compared among the stroke subtypes using Analysis of Variance. Multiple regression analyses were further performed to test the significance of the impact of the stroke subtype after controlling for other variables. Results: The stroke subtype turned out to be a statistically significant factor influencing both the total charge and several categorized charges even after controlling for other contributing factors such as hospital length of stay and stroke severity. Conclusions: This study concludes that the stroke subtype should be included when considering in‑patient medical expenses of acute ischemic stroke. Key words: Hospital charges, ischemic stroke, stroke subtype, Trial of Org 10172
in acute stroke treatment classification
Introduction The cost of hospitalization due to stroke is significantly associated with the length of stay and clinical Access this article online Quick Response Code:
Website: www.neurologyindia.com PMID: *** DOI: 10.4103/0028-3886.125271
Neurology India | Nov-Dec 2013 | Vol 61 | Issue 6
characteristics, as well as various socio‑demographic factors.[1‑5] Among the clinical factors, the stroke severity has been identified as a major factor in the escalation of costs.[4‑10] The ischemic stroke subtype classifications based on the underlying etiology can influence the treatment methods and process. [11] However, the observation in the earlier studies have been rather inconsistent with regard to the influence of stroke subtype on costs of acute ischemic stroke.[8,12‑15] This study assessed the hospital charges for acute ischemic stroke according to the stroke subtype and determined whether stroke subtype is a contributor to the hospital charges. 633
Chang, et al.: Hospital charges according to stroke subtypes
Materials and Methods Study population The study subjects include 749 consecutive patients with first‑ever ischemic stroke (within 7 days of stroke onset) admitted to the neurology ward in an academic medical center between January 2006 and December 2008. The hospital is a tertiary care center in the northeastern region of Seoul, Korea and patients are often referred to this hospital from other medical facilities. During the period, 1,302 patients with ischemic stroke were admitted. This included 956 patients with first‑ever acute ischemic stroke, of them 891 patients were admitted within 7 days of stroke onset. Ultimately, for the final analysis, 749 patients with all the required clinical information and billing data were included in the study. The diagnoses of ischemic stroke was based on the data obtained from the medical history, neurologic findings, computerized tomography, magnetic resonance imaging, magnetic resonance angiography and other neuroimaging findings. This study was approved by the Institutional Review Board of Kyung Hee University Medical Center, Seoul, Korea. The board permitted a waiver of informed consent because the study involved anonymous data collected for non‑research purposes. Data and variables The data composed of two components: (1) Socio‑demographic and clinical characteristics of each patient; and (2) information on the hospital charges. The data for the first component were collected from the hospital stroke registry database and the data for the second component were retrieved from the hospital’s Patient Management Information System. The variables selected for this study were based on factors showing an effect on the hospital costs in the previous studies. The socio‑demographic characteristics included age, gender and health insurance type. The clinical characteristics consisted of the patient’s admission route, referral for admission, the time interval between onset and arrival at hospital, risk profile, stroke subtype and stroke severity at admission, treatment modalities, length of hospital stay (LOS) and the destination after discharge. Stroke severity was evaluated using the National Institutes of Health Stroke Scale (NIHSS) at the time of admission. Stroke subtype categorization was done using Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification by two board certified neurologists. Patients were broadly classified into five categories based on the underlying mechanism of stroke: Large artery atherosclerosis (LAA) small vessel occlusion (SVO), cardioembolism (CE), other determined etiology (OD), or undetermined etiology (UD). The UD type was further classified into three subcategories: Two or more 634
etiologies (2 or more), negative study results (negative) and incomplete study (incomplete). With regard to the data on medical expenses for each patient collected and analyzed were determined by a fee‑for‑service schedule based on the type and quantity of services provided. Although patients and the National Health Insurance Service share the payments for services covered by the National Health Insurance or Medical Aid, patients pay in full for services not covered by them. In this study, both insured and uninsured hospital charges were included in the analysis. The various hospital charges were categorized into seven items: Room and board, laboratory tests, imaging studies, oral medication, injections, operations and procedures and others. Six of these seven categories were grouped into three broad categories to simplify analyses and facilitate comparisons with previous studies. The three categories were: (1) Room and board (2) laboratory tests and imaging studies (investigations); and (3) medication, injections and operations and procedures (treatment). “Other charges were excluded from the classification of the three categories due to its complex characteristics. Statistical analysis The data analysis was descriptive for the demographic data and clinical characteristics using frequency, percentage, mean and median. The hospital charges among the stroke subtype groups were compared using Analysis of Variance and multiple regression analyses. In the multiple regression analyses, the hospital charges were log‑transformed to satisfy the normality and homoscedasticity assumptions of linear regression. The variance inflation factor for each predictor for all given cases were computed to determine the existence of multicollinearity. All analyses were performed using the Statistical Analysis System, version 9.2 (SAS Institute, Cary, NC, USA). In addition, all hospital charges were adjusted to the 2008 rates and converted into U.S. dollars. Since the fee schedule had been increased over 3 years, from January 2006 to December 2008, the adjustment to the 2008 rates excluded the effect of inflation on medical expense. A conversion rate of 1 U.S. dollar to 995.83 Korean won was utilized; this figure was determined by calculating the average exchange rate over the 3 year duration of the study.
Results Sample characteristics Of the 749 (60.0% males, mean age 64.5 years) patients included in the study, the distribution of stroke subtypes were: LLA 31.9%, SVO 32.7%, CE 10.9%, UD 23.5% and OD 1.0%. Among the UD, in 63 (8.6%) patients there was two or more mechanism for the stroke, in Neurology India | Nov-Dec 2013 | Vol 61 | Issue 6
Chang, et al.: Hospital charges according to stroke subtypes
38 (4.9%) patients no cause could be demonstrated and in 75 (10.0%) patients the stroke work‑up was incomplete. The mean NIHSS score at admission was 5.5 and the average LOS was 13.9 days [Table 1]. Total and categorized hospital costs The mean total hospital cost of care was $4,608 and the per days with charges of $401. Costs of imaging accounted for 30.1% and room and board for 28.2% of total hospital charges. Other charges included: Laboratory tests for 13.6%, injections for 12.8%, medications for 3.5%, operations and procedures for 7.6% [Table 2]. Hospital charges according to the stroke subtypes The total and daily charges were significantly different across stroke subtypes. The highest total charge was for patients with OD stroke ($6,935), followed by patients with CE stroke ($6,510) and the lowest total charge patients with SVO stroke ($3,428). In contrast, the highest daily charge was for patients with UD‑incomplete stroke ($499) and these charges was 1.4 times higher than the lowest daily charge for patients with OD stroke ($366). Table 1: Baseline characteristics of patients with acute ischemic stroke (n=749) Gender Female/male (%) 40.0/60.0 Age (years) Mean/median (%) 64.5/65 Insurance type NHI/medical aid (%) 96.7/3.3 Admission route Emergency room/out‑patient departments (%) 75.0/25.0 Referral for admission Direct visit/referred (%) 70.4/29.6 Interval between onset and arrival (h) Mean/median 38.2/22 Risk factor TIA/hypertension/DM/hyperlipidemia/smoking/ 1.8/68.4/33.2/ heart diseases (%) 39.4/34.4/18.8 Subtype (TOAST) LAA/SVO/CE/OD/UD‑2 or more/UD‑negative/ 31.9/32.7/10.9/ UD‑incomplete (%) 1.0/8.6/4.9/10.0 NIHSS score at admission Mean/median 5.5/4 Treatment Operation/ICU/thrombolytic*/anti‑coagulant/ 2.2/10.5/6.2/ anti‑platelet (%) 18.0/72.5 Length of stay (days) Mean/median 13.9/9 Destination after discharge Referred to other institutions/to home/in‑hospital 19.3/79.3/1.4 death (%) *Intravenous injection of rt‑PA. NHI ‑ National health insurance, TIA ‑ Transient ischemic attack, DM ‑ Diabetes mellitus, LAA ‑ Large artery atherosclerosis, SVO ‑ Small vessel occlusion, CE ‑ Cardioembolism, OD ‑ Other determined etiology, UD ‑ Undetermined etiology, NIHSS ‑ National Institutes of Health Stroke Scale, ICU ‑ Intensive care unit, TOAST ‑ Trial of Org 10172 in acute stroke treatment
Neurology India | Nov-Dec 2013 | Vol 61 | Issue 6
The categorized analysis also showed significantly different hospital charges across the stroke subtypes. Charges for imaging studies were highest in patients with OD stroke ($2,168), but the proportion in the total charges was highest in patients with SVO stroke (37.1%). Patients with UD‑incomplete stroke had both the lowest amount ($1,152) and the lowest proportion (21.5%) of imaging study charges. The hospital charges according to the three broad categories of the room and board, examination were also different among the subtypes. Hospital charge was the highest for patient with OD stroke, $2,412, and $3,148 respectively for room and board and examination. Cost for treatment was highest for patients with UD‑incomplete stroke, $1,919 and for patients with SVO, the charges were lowest $931, $1,728 and $685 in all three categories, respectively. Effect of the stroke subtypes on hospital charges The stroke subtype was a statistically significant determining factor for total hospital charges after controlling for other contributing factors. The CE stroke subtype was a significant factor in escalating the in-hospital cost of care, whereas UD‑incomplete is a significant factor in reducing the in-hospital cost of care. The other factors associated with significant increasing in the total charges included stroke severity at admission and LOS. Referral at discharge was a significant factor in reducing total charges. Of the six multiple regression models for categorized charges, the stroke subtype was significant in five models: Room and board, laboratory tests, imaging studies, medication and injection. The CE stroke subtype was significantly associated with higher charges for room and board and laboratory tests and lower for charge for medication. The UD‑2 or more stroke subtype was significantly associated with higher charge for imaging studies and UD‑negative stroke subtype was associated with lower charges for injection. Moreover, the UD‑incomplete stroke subtype was significantly associated with lower charges for room and board, imaging studies and medication. Within the three broad categories, the CE subtype was a significant factor associated with increased charges for room and board and examination and the UD‑incomplete stroke subtype was a significant factor associated with decreased charges for room and board and examination [Table 3].
Discussion Previous studies have investigated the determinants of the costs of care for patients with ischemic stroke, but influence on the cost of care of the stroke subtype has not been well studied. The study by Yoneda et al. found 635
Chang, et al.: Hospital charges according to stroke subtypes
Table 2: Mean value of total and categorized in‑patient charges according to stroke subtype (Unit: $)
Total charges Room and board Examination Laboratory tests Imaging studies CT MRI Sonography Others Treatment Medication Injection Op/procedure Physicians fee Others Daily charges LOS (mean, days) NIHSS score at admission (mean)
All (n=749) (%)
LAA (n=239) (%)
SVO (n=243) (%)
CE (n=84) (%)
OD (n=7) (%)
2 or more (n=63) (%)
Negative (n=38) (%)
4,608 (100.0) 1,300 (28.2) 2,013 (43.7) 627 (13.6) 1,386 (30.1) 155 736 352 144 1,102 (23.9) 160 (3.5) 592 (12.8) 350 (7.6) 49 (1.1) 144 (3.1) 401 14 5
4,720 (100.0) 1,355 (28.7) 2,053 (43.5) 579 (12.3) 1,474 (31.2) 135 740 395 205 1,058 (22.4) 172.0 (3.6) 552 (11.7) 334 (7.1) 49 (1.0) 204 (4.3) 362 15 5
3,428 (100.0) 931 (27.2) 1,728 (50.4) 454 (13.2) 1,273 (37.1) 122 745 337 69 685 (20.0) 132 (3.9) 421 (12.3) 133 (3.9) 46 (1.3) 39 (1.1) 412 9 3
6,510 (100.0) 1,951 (30.0) 2,515 (38.6) 1,086 (16.7) 1,430 (22.0) 225 733 338 134 1,768 (27.2) 178 (2.7) 913 (14.0) 677 (10.4) 56 (0.9) 219 (3.4) 418 19 9
6,935 (100.0) 2,412 (34.8) 3,148 (45.4) 980 (14.1) 2,168 (31.3) 237 916 535 480 1,216 (17.5) 269 (3.9) 398 (5.7) 549 (7.9) 51 (0.7) 108 (1.6) 366 26 6
5,372 (100.0) 1,531 (28.5) 2,260 (42.1) 666 (12.4) 1,594 (29.7) 211 786 402 195 1,209 (22.5) 186 (3.5) 547 (10.2) 476 (8.9) 52 (1.0) 320 (6.0) 381 19 6
4,032 (100.0) 1,199 (29.7) 1,988 (49.3) 550 (13.6) 1,438 (35.7) 134 799 341 164 754 (18.7) 151 (3.7) 374 (9.3) 229 (5.7) 48 (1.2) 42 (1.0) 384 12 6
Incomplete F test (n=75) (%) 5,370 (100.0) 1,343 (25.0) 1,945 (36.2) 793 (14.8) 1,152 (21.5) 200 605 228 119 1,919 (35.7) 164 (3.1) 1,076 (20.0) 679 (12.6) 52 (1.0) 111 (2.1) 499 16 8
7.51‡ 8.49‡ 7.81‡ 10.22‡ 8.25‡ 6.99‡ 3.16† 11.12‡ 5.65‡ 3.04† 7.50‡ 6.74‡ 3.57† 1.32 4.44‡ 9.18‡ 20.53‡
P
