| [1] |
国家卫生和计划生育委员会. 安宁疗护中心基本标准(试行)[EB/OL].(2017-01-25)[2024-05-24]. http://www.nhc.gov.cn/yz-ygj/s3593/201702/88b4c10220c5474d905eeb43b272d24f.shtml.
|
|
National Health and Family Planning Commission. Basic standards and management norms of hospice care center (for trial implementation)[EB/OL].(2017-01-25)[2024-05-24]. http://www.nhc.gov.cn/yzygj/s3593/201702/88b4c10220c5474d905eeb-43b272d24f.shtml.
|
| [2] |
World Health Organization. Palliative care[EB/OL].(2020-08-05)[2024-05-24]. https://www.who.int/news-room/fact-sheets/detail/pa-lliative-care.
|
| [3] |
韩鸽鸽, 陈长英, 王盼盼, 等. 安宁疗护病房护士工作现状的质性研究[J]. 护理学杂志, 2020, 35(12):65-67.
|
|
Han GG, Chen CY, Wang PP, et al. Qualitative study on work status of palliative care nurses[J]. J Nurs Sci, 2020, 35(12):65-67.
|
| [4] |
Johnson K, Allen KE, West W, et al. Strengths,gaps,and oppor-tunities:results of a statewide community needs assessment of pediatric palliative care and hospice resources[J]. J Pain Sym-ptom Manage, 2020, 60(3):512-521.
|
| [5] |
Christakis NA. Extent and determinants of error in doctors' prognoses in terminally ill patients:prospective cohort study commentary:why do doctors overestimate? Commentary:prog-noses should be based on proved indices not intuition[J]. Bmj, 2000, 320(7233):469-473.
DOI
PMID
|
| [6] |
Bianchi V, Bassoli M, Lombardo G, et al. IoT wearable sensor and deep learning:an integrated approach for personalized hu-man activity recognition in a smart home environment[J]. IEEE Internet Things J, 2019, 6(5):8553-8562.
|
| [7] |
Peters MDJ, Marnie C, Tricco AC, et al. Updated methodological guidance for the conduct of scoping reviews[J]. JBI Evid Synth, 2020, 18(10):2119-2126.
DOI
PMID
|
| [8] |
张伟, 刘曦阳, 葛春花, 等. 基于公众判断的癌症患者安宁转诊智能分类预测模型的构建[J]. 护理学杂志, 2023, 38(18):1-5,11.
|
|
Zhang W, Liu XY, Ge CH, et al. Development of an artificial intelligence model for predicting palliative care referral of cancer patients based on public judgment[J]. J Nurs Sci, 2023, 38(18):1-5,11.
|
| [9] |
Zhuang QY, Zhang AY, Cong RSTY, et al. Towards proactive palliative care in oncology:developing an explainable EHR-based machine learning model for mortality risk prediction[J]. BMC Palliat Care, 2024, 23(1):124.
|
| [10] |
Sandham MH, Hedgecock EA, Siegert RJ, et al. Intelligent pal-liative care based on patient-reported outcome measures[J]. J Pain Symptom Manage, 2022, 63(5):747-757.
|
| [11] |
Murphree DH, Wilson PM, Asai SW, et al. Improving the deli-very of palliative care through predictive modeling and heal-thcare informatics[J]. J Am Med Inform Assoc, 2021, 28(6):1065-1073.
DOI
PMID
|
| [12] |
Huang YR, Roy N, Dhar E, et al. Deep learning prediction model for patient survival outcomes in palliative care using actigraphy data and clinical information[J]. Cancers, 2023, 15(8):2232.
|
| [13] |
Heinzen EP, Wilson PM, Storlie CB, et al. Impact of a ma-chine learning algorithm on time to palliative care in a primary care population:protocol for a stepped-wedge prag-matic randomized trial[J]. BMC Palliat Care, 2023, 22(1):9.
DOI
PMID
|
| [14] |
DiMartino L, Miano T, Wessell K, et al. Identification of un-controlled symptoms in cancer patients using natural langua-ge processing[J]. J Pain Symptom Manage, 2022, 63(4):610-617.
|
| [15] |
Courtright KR, Chivers C, Becker M, et al. Electronic health record mortality prediction model for targeted palliative care among hospitalized medical patients:a pilot quasi-experi-mental study[J]. J Gen Intern Med, 2019, 34(9):1841-1847.
DOI
PMID
|
| [16] |
Chi S, Guo AX, Heard K, et al. Development and structure of an accurate machine learning algorithm to predict inpatient mortality and hospice outcomes in the coronavirus disease 2019 era[J]. Med Care, 2022, 60(5):381-386.
DOI
PMID
|
| [17] |
Aude CA, Vattipally VN, Das O, et al. Machine learning iden-tifies variation in timing of palliative care consultations among traumatic brain injury patients[J]. Res Sq, 2024,12(5):102-103.
|
| [18] |
Zhang HW, Li Y, McConnell W. et al. Predicting potential palliative care beneficiaries for health plans:a generalized machine learning pipeline[J]. J Biomed Inform, 2021,123:103922.
|
| [19] |
Uyeda AM, Randall Curtis J, Engelberg RA, et al. Mixed-me-thods evaluation of three natural language processing mode-ling approaches for measuring documented goals-of-care dis-cussions in the electronic health record[J]. J Pain Symptom Manage, 2022, 63(6):e713-e723.
|
| [20] |
Soltani M, Farahmand M, Pourghaderi AR. Machine learning-based demand forecasting in cancer palliative care home hospitalization[J]. J Biomed Inform, 2022,130:104075.
|
| [21] |
Shimada K, Tsuneto S. Novel method for predicting nonvisible symptoms using machine learning in cancer palliative care[J]. Sci Rep, 2023, 13(1):12088.
DOI
PMID
|
| [22] |
Liu JH, Shih CY, Huang HL, et al. Evaluating the potential of machine learning and wearable devices in end-of-life care in predicting 7-day death events among patients with terminal cancer:cohort study[J]. J Med Internet Res, 2023,25:e47366.
|
| [23] |
Durieux BN, Gramling CJ, Manukyan V, et al. Identifying con-nectional silence in palliative care consultations:a tandem machine-learning and human coding method[J]. J Palliat Med, 2018, 21(12):1755-1760.
|
| [24] |
Brar R, Isabel Friedman M, Dacosta N, et al. Automated iden-tification of patients with advanced illness[J]. AMIA Annu Symp Proc, 2022,2022:269-278.
|
| [25] |
Chu TS, Zhang HW, Xu YF, et al. Predicting the behavioral intentions of hospice and palliative care providers from real-world data using supervised learning:a cross-sectional survey study[J]. Front Public Health, 2022,10:927874.
|
| [26] |
郭俊晨, 刘超毅, 许湘华, 等. 终末期癌症患者远程居家安宁疗护照护系统的构建及应用研究[J]. 中华护理杂志, 2024, 59(16):1925-1933.
DOI
URL
|
|
Guo JC, Liu CY, Xu XH, et al. Construction and application of a telemedicine-based home care system of palliative care for end-of-life cancer patients[J]. Chin J Nurs, 2024, 59(16):1925-1933.
DOI
URL
|
| [27] |
张辰, 杨浩杰, 张哲, 等. 晚期心力衰竭患者安宁疗护准入评估指标的构建[J]. 中华护理杂志, 2023, 58(13):1544-1551.
DOI
URL
|
|
Zhang C, Yang HJ, Zhang Z, et al. Construction of an assess-ment index system of palliative care referral for patients with advanced heart failure[J]. Chin J Nurs, 2023, 58(13):1544-1551.
|
| [28] |
王心茹, 朱信雨, 贾玉玲, 等. 文化因素对安宁疗护实践影响的质性研究[J]. 中华护理杂志, 2023, 58(13):1552-1558.
DOI
URL
|
|
Wang XR, Zhu XY, Jia YL, et al. A qualitative study on the specificity of cultural factors in palliative care practice[J]. Chin J Nurs, 2023, 58(13):1552-1558.
DOI
URL
|
| [29] |
Cox DR. Regression models and life-tables[J]. J R Stat Soc Ser B Methodol, 1972, 34(2):187-202.
|
| [30] |
Kelley AS, Bollens-Lund E. Identifying the population with serious illness:the “denominator” challenge[J]. J Palliat Med, 2018, 21(S2):S7-S16.
|
| [31] |
Cheung JTK, Au D, Ip AHF, et al. Barriers to advance care planning:a qualitative study of seriously ill Chinese patients and their families[J]. BMC Palliat Care, 2020, 19(1):80.
|