癌新診斷病人非計劃性入院及預測相關因素之探討
前 言
1/4 (Siegel, Ma, Zou, & Jemal, 2014) 20.1%( 2013);
21.3-23.6%(Chiang et al., 2008) (non-small cell lung cancer, NSCLC)
(Chiang et al., 2008; Pan et al., 2012)
肺癌新診斷病人非計劃性入院及
預測相關因素之探討
張麗蓉 陳雅智* 謝宗成** 黃彥晴***
慈濟技術學院講師 肯特州立大學助理教授* 佛教慈濟大學醫學科學研究所助理教授** 佛教慈濟醫療財團法人大林慈濟醫院胸腔內科專科護理師***
接受刊載：2014 年7月3日
通訊作者地址：謝宗成 97004花蓮市中央路三段701號 勤耕樓7樓
電話：886-3-8565301 #2015 電子信箱：tchsieh@https://www.doczj.com/doc/bd3986213.html,.tw
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Volume 13 . Number 5 . October 2014第十三卷 第五期
癌新診斷病人非計劃性入院及預測相關因素之探討
(Henretta, Scalici, Engelhard, & Duska, 2011; Lin, Wu, & Tsauo, 2012)
2004
18.7% 2008 22.2% (Lin, Wu, & Tsauo, 2012)
(Bottle,
et al., 2012; Henretta et al., 2011) Bottle et al.(2012)
21.8% 40% (Aprile et al.,
2013; McKenzie et al., 2011)
(27%-43%) (13.8 %-31%) (12%-17.6 %)(Aprile et al., 2013;
Brown, Cooley, Chernecky, & Sarna, 2011) (symptom cluster)
( ) (Wang,
Tsai, Chen, Lin & Lin, 2008)
( )
(Chiang et al., 2008; Wang et al., 2008; Lin, Wu, & Tsauo, 2012; Chen, Chang, Tsou, Chen, & Pai, 2013)
方法
一、研究設計與對象
2005 2007 963
583
40 ( ) 405
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癌新診斷病人非計劃性入院及預測相關因素之探討
( )
( )
( / / )-
C h a r l s o n C o m o r b i d i t y
Index Scale (Charlson, Pompei, Ales, &
MacKenzie, 1987)
(Eastern Cooperative Oncology Group;
Performance status; ECOG/PS)-
(
/ ) (
) (
)
2010
( B09803010)
二、資料分析及處理
SPSS for Windows
SPSS 21.0/SAS
t
(
)
圖一 研究對象篩選流程
* 6 1 (>250 ) SCLC: Small Cell Lung Cancer 78
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Volume 13 . Number 5 . October 2014第十三卷 第五期
癌新診斷病人非計劃性入院及預測相關因素之探討
(Generalized
Mixed Effect Model)
(odds ratio) 95% p < .05
結果
一、研究樣本之基本人口學
(65%) (63.5%) (45.4%)
(37.8%)
65% 83% IIIB/IV 84.5% (46.2% > 34%; ) (M = 71.4 vs. 64.9 ; t = 6.22, p <
.001) (68% vs. 32%;
t = 8.01, p < .001) (M = .5 vs. 1.1 ; t = -4.17, p < .001)
(M = 2.7 vs. 7.7; t = -14.89, p <
.001) (55.8% vs. 99.1%;
X 2 = 131.97, p < .001)
(Mdn = 126 vs. 477 ; t = -8.33;
p < .001)
(91.3 vs. 79.4%; X 2 =10.63, p = .001; )
二、症狀與(非)計劃性入院之影響
405 1,920 46.5% 53.5% 38.5%(N = 156) ( =332; 1-12 ) ( ) ( )
三、 非小細胞肺癌非計劃性入院之預測
因子
( -2 Res Log Pseudo-Likelihood
=9576.62 =1559.96)
(OR = 1.03; p = .001) (OR = 2.15;
p =.022) / (OR =5.43; p = .013)
>2 (OR = 1.73; p < .001)
(OR = 1.52~55.35; p < .022)
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癌新診斷病人非計劃性入院及預測相關因素之探討
表一 非小細胞肺癌病人人口學特徵( N = 405 )
(%) ( ): mean SD; range67.6 11.0; 40-95
: 257(63.5)
375(92.6)
30(7.4)
153(37.8)
184(45.4)
68(16.8)
311(76.8)
82(20.2)
12(3)
104(25.7)
134(33.1)
167(41.2)
27(6.7)
378(93.3)
( : / ; M SD; range)55.8 34.9; 5-180
180(44.4)
156(38.6)
69(17)
(kg/m2; N=363; M SD; range)22.97 3.8; 14.0-42.3
39(10.7)
225(62.0)
99(27.3)
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Volume 13 . Number 5 . October 2014第十三卷 第五期
癌新診斷病人非計劃性入院及預測相關因素之探討
表二 非小細胞肺癌病人臨床疾病特徵( N = 405 )
(%)
180(44.4) 75(18.5) 76(18.8)
100(24.7) (CCI;Median/IQR)6(2-7)0 59(14.6)1-5
89(21.9)> 6
257(63.5) (ECOG,PS):score<2264(65.2) :IIIB/IV 336(83)
80(19.8)( )
24( 5.9) / 136(33.6)
27( 6.7)( ) >2
138(34)
[ ]CCI=Charlson Comorbidity Index scale IQR=Interquartile Range;ECOG=Eastern Cooperative Oncology Group PS=Performance Status 表三 肺癌計劃性及非計劃性入院者臨床特徵之比較( N = 405 )
a
(N = 172)
b
(N = 233)
t/X 2 ( ;M SD)64.9 9.771.4 11.5 6.22
<75197(84.5)96(55.8)>=75
36(15.5)76(44.2)
(N/%) 131.97
2(0.9)76(44.2) 110(47.2)68(39.5)
121(51.9)28(16.3) (M SD) 1.1 1.70.5 1.1 -4.17 (N/%)233(46.5)383(53.5) -14.89 M SD 7.7 4.4 2.7 2.2 (Mdn/IQR)477(257-941)126(38-372) -8.33 (N/%)
185(79.4)
157(91.3)
10.63 [ ]M=mean; SD= standard deviation;Mdn= median; IQR= interquartile range
a
;b ; p < .001
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癌新診斷病人非計劃性入院及預測相關因素之探討
表四 有無臨床症狀時發生非計劃性入院與計劃性入院之頻率
(%)
(%)
(%)
(%)
500(68.7)228(31.3)528(44.3)664(55.7)
539(73.6)193(26.4)489(41.2)699(58.8)
217(76.1)68(23.9)811(49.6)824(50.4)
427(63.2)249(36.8)601(48.3)643(51.7)
13(65.0)7(35.0) 1015(53.4)885(46.6)
522(75.8)167(24.2)506(41.1)725(58.9)
12(57.1)9(42.9) 1016(53.5)883(46.5)
814(64.6)447(35.4)214(32.5)445(67.5)
79(98.8)1( 1.3)949(51.6)891(48.4)
63(91.3)6( 8.7)965(52.1)886(47.9)
33(48.5)35(51.5)995(53.7)857(46.3) 286(92.3)24( 7.7)741(46.1)868(53.9)
表五 以廣義混合效果模式分析非計劃性住院預測因子結果
a,b Odds Ratio (95% CI)p-value
1.03(1.02, 1.05)<.001
2.15(1.11, 4.13).022
5.34(1.42, 20.70).013
>2 1.73(1.21, 2.48)<.001
2.87(2.12,
3.81)<.001
2.03(1.51, 2.73)<.001
1.80(1.18,
2.73).006
1.52(1.13,
2.06).006
4.49(3.34, 6.02)<.001
1.83(1.37,
2.44)<.001
55.37(7.06, 434.24)<.001
4.71(1.25, 17.74).022
10.21(6.24, 16.72)<.001
[ ]a : ( ) ( ) (ECOG <2 );
b
(p>.05)
CI=Confidence Interval
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癌新診斷病人非計劃性入院及預測相關因素之探討
討論與結論
Chen & Narsavage(2006)
Moore, Gao, &
Shulan(2013)
75 75
75 Pan
et al.(2012)
(Aprile et al.,
2013; Brown et al., 2011)
Chen et
al.(2013)
Wang et al.(2008)
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癌新診斷病人非計劃性入院及預測相關因素之探討
Aprile
et al.(2013)
( )
McDevitt et al.(2013)
(1) ( / )
(2)
( )
( ) (3)
(
/
)
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癌新診斷病人非計劃性入院及預測相關因素之探討
致謝
(TCCT-981A11)
參考文獻
衛生福利部(2013，6月6日) 101年國人主要
死因統計結果取自h t t p ://w w w.m o h w.
gov.tw/CHT/Ministry/DM2_P.aspx?f_list_no=7&fod_list_no=3914&doc_no=28706
Aprile, G., Pisa, F.E., Follador, A., Foltran, L.,
De Pauli, F., Mazzer, M., ... Fasola, G. (2013). Unplanned presentations of cancer outpatients: A retrospective cohort study.
Support Cancer Care, 21(2), 397-404.
doi:10.1007/s00520-012-1524-6
Bottle, A., Tsang, C., Parsons, C., Majeed, A.,
Soljak, M., & Aylin, P. (2012). Association between patient and general practice characteristics and unplanned first-time admissions for cancer: Observational study.
British Journal of Cancer, 107(8), 1213-1219.
doi:10.1038/bjc.2012.320
Brown, J.K., Cooley, M. E., Chernecky, C., &
Sarna, L. (2011). A symptom cluster and sentinel symptom experienced by women with lung cancer. Oncology Nursing Forum,
38(6): E425-435. doi:10.1188/11.ONF.
E425-E435
Chen, Y. J. & Narsavage, G. L. (2006). Factors
related to chronic obstructive pulmonary
disease readmission in Taiwan. Western
Journal of Nursing Research, 28(1), 105-124.
doi:10.1177/0193945905282354
Chen, Y.C., Chang, Y.J., Tsou, Y.C., Chen, M. C.,
& Pai, Y.C. (2013). Effectiveness of nurse case management compared with usual care in cancer patients at a single medical center in Taiwan: A quasi-experimental study.
BMC Health Services Research,13, 202-208.
doi:10.1186/1472-6963-13-202
Chiang, T. A., Chen, P. H., Wu, P. F., Wang, T.
N., Chang, P. Y., Ko, A. M. S., ... Ko, Y. C. (2008). Important prognostic factors for the long-term survival of lung cancer subjects in Taiwan. BioMed Central Cancer, 8, 324-331.doi:10.1186 /1471-2407-8-324
Charlson, M. E., Pompei, P., Ales, K. L. &
MacKenzie, C. R. (1987). A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of Chronic Disease, 40(5), 373-383.
Henretta, M. S., Scalici, J. M., Engelhard,
C. L., & D u s k a , L. R. (2011).T h e revolving door: Hospital readmissions of gynecologic oncology patients. Gynecology
Oncology, 122, 479-483. doi:10.1016/
j.ygyno.2011.05.011
Lin, H. F., Wu, Y. T., & Tsauo, J. Y. (2012).
Utilization of rehabilitation services for inpatient with cancer in Taiwan: A descriptive analysis from national health insurance database. BioMed Central Health Services
Research, 12, 255-261. doi:10.1186/1472-6963-12-255
McDevitt, J., Kelly, M., Comber, H., Kelleher, T.,
Dwane, F., & Sharp, L. (2013). A population-
85
癌新診斷病人非計劃性入院及預測相關因素之探討
based study of hospital length of stay and
emergency readmission following surgery for
non-small-cell lung cancer. European Journal
of Cardio-Thoracic Surgery, 44, e253-e259.
doi:10.1093/ejcts/ezt389
McKenzie, H., Hayes, L., White, K., Cox, K.,
Fethney, J., Boughton, M., & Dunn, J.
(2011). Chemotherapy outpatients’ unplanned
presentations to hospital: A retrospective
study. Supportive Care in Cancer, 19(7), 963-
969.doi:10.1007/ s00520-010-0913-y
Moore, C. D., Gao, K., & Shulan, M. (2013).
Racial, income, and marital status disparities
in hospital readmissions within a veterans-
integrated health care network. Evaluation
&t h e H e a l t h P r o f e s s i o n s.R e t r i e v e d
from http://ehp. https://www.doczj.com/doc/bd3986213.html,/content/
early/2013/06/27/0163278713492982.
doi:10.1177/0163278713492982
Pan, H. H., Lin, K.C., Ho, S.T., Liang, C.Y.,
Lee, S.C., & Wang, K.Y. (2012). Factors
related to daily life interference in lung
cancer patients: A cross-sectional regression
tree study. European of Journal Oncology
Nursing, 16(4), 345-52. doi:10.1016/
j.ejon.2011.07.011
Siegel, R., Ma, J., Zou, Z., & Jemal, A. (2014).
Cancer statistics, 2014. CA: A Cancer Journal
for Clinicians, 64(1), 9-29. doi:10.3322/
caac.21208
Wang, S. Y., Tsai, C. M., Chen, B. C., Lin, C.
H., & Lin, C. C. (2008). Symptom clusters
and relationships to symptom interference
with daily life in Taiwanese lung cancer
p a t i e n t s.J o u r a n l o f P a i n S y m p t o m
Management, 35(3), 258-66. doi:10.1016/j.
jpainsymman.2007.03.017
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Predictors of Unplanned Rehospitalizations Among Patients with Newly Diagnosed Non-Small Cell Lung Cancer (NSCLC)
Li-Jung Chang, Yea-Jyh Chen*, Tsung-Cheng Hsieh**, Yen-Ching Huang***
Lecturer, Department of Nursing, Tzu Chi College of T echnology; Assistant Professor, College of Nursing, Kent State University*; Assistant Professor, Buddhist Tzu Chi University Institute of Medical Sciences**; Nurse Specialist , Chest Medical Department, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation***Accepted: July 3, 2014
Address correspondence to: T sung-Cheng Hsieh 701, Chung Y ang Rd., Sec.3 Hualien T aiwan 970T el: 886-3-8565301 #2015; E-mail: tchsieh@https://www.doczj.com/doc/bd3986213.html,.tw
ABSTRACT
Purpose: This study aimed to examine risk factors for predicting unplanned rehospitalizations related to lung cancer. Methods: Longitudinal, descriptive design was conducted with retrospective medical record review. A convenience sample of 405 newly diagnosed non-small cell lung cancer (NSCLC) patients was identi?ed through a hospital cancer registry database in southern Taiwan. Each patient was followed for three years to examine clinical symptoms and outcomes (planned/unplanned admissions) after the index hospitalization. Results: There were 1920 lung-cancer associated hospitalizations (46.5% planned vs. 53.5% unplanned) during the study time period. The unplanned rehospitalizations were more likely to occur in patients with pre-existing cancer symptoms versus not. The multivariate Generalized Mixed Effect model identi?ed 13 symptoms and patient characteristics as signi?cant predictors of unplanned re-hospitalizations in NSCLC (odds ratio = 1.04~50.32, p < .02). Conclusions: Our study demonstrated frequent unplanned acute care utilization related to worsening cancer symptoms among NSCLC patients in suburban areas. The ?ndings emphasize the importance of symptom management in preparation for discharge. Using significant predictors of unplanned rehospitalizations is warranted in developing continuous, effective care strategies for discharged patients with newly diagnosed lung cancer. (Tzu Chi Nursing Journal, 2014; 13:5, 76-87)
Keywords: cancer symptoms, non-small cell lung cancer (NSCLC), risk factors, Taiwan, unplanned rehospitalization
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