Các công cụ E-Health thu thập các chỉ số kết quả tự báo cáo của bệnh nhân giúp giảm bớt gánh nặng đánh giá và khuyến khích sự tham gia của bệnh nhân trong chăm sóc ung thư (Nghiên cứu PaCC)

Springer Science and Business Media LLC - Tập 29 Số 12 - Trang 7715-7724 - 2021
Nicole Erickson1, Timo Schinkoethe2, Carla Eckhardt1, Lena J. Storck3, Andreas Joos3, L Liu1, Peter E. Ballmer3, Friederike Mumm4, Theres Fey1, Volker Heinemann1
1Comprehensive Cancer Center, Ludwig-Maximilian University Clinic, Munich, Germany
2CANKADO Service GmbH, Cologne, Germany
3Winterthur, Switzerland
4Psycho-Oncology, Department of Medicine III, Ludwig-Maximilian University Clinic, Munich, Germany

Tóm tắt

Tóm tắt

Các chỉ số kết quả tự báo cáo của bệnh nhân thông qua công cụ E-Health giảm bớt gánh nặng trong đánh giá và khuyến khích sự tham gia của bệnh nhân vào việc chăm sóc ung thư (Nghiên cứu PaCC)

Nền tảng

Các chỉ số kết quả tự báo cáo (PROMs) dựa trên E-health có khả năng tự động hóa quá trình xác định sớm tình trạng dinh dưỡng và tình trạng căng thẳng ở bệnh nhân ung thư, đồng thời thúc đẩy điều trị và khuyến khích sự tham gia của bệnh nhân. Nghiên cứu cắt ngang này đánh giá độ chấp nhận, độ chính xác và tính hữu ích lâm sàng của các PROMs được thu thập qua các công cụ E-Health ở những bệnh nhân đang điều trị khối u dạ dày, đại trực tràng và tuyến tụy.

Kết quả

Chín mươi phần trăm bệnh nhân đồng ý rằng các PROMs qua máy tính bảng nên được tích hợp vào quy trình chăm sóc lâm sàng thường xuyên. Đàn ông có khả năng cần trợ giúp hoàn thành bảng câu hỏi cao hơn đáng kể so với phụ nữ (inv.OR= 0.51, 95% CI=(0.27, 0.95), p = 0.035). Mức độ cần trợ giúp tăng 3% với mỗi năm gia tăng tuổi tác (inv. OR=1.03, 95% CI=(1.01, 1.06), p = 0.013). Trung bình, một bệnh nhân có xu hướng khai báo cân nặng thấp hơn 0.84 kg so với cân nặng thực tế của họ (Bland và Altman 95 % CI=(-3.9, 5.6); SD: 2.41) và chiều cao cao hơn 0.95 cm so với chiều cao thực tế (Bland và Altman 95 % CI=(−5, 3.1); SD 2.08). Tình trạng dinh dưỡng tự báo cáo của bệnh nhân có liên quan đáng kể với đánh giá của chuyên gia (95% CI=(2.27, 4.15), p < 0.001). Khi tình trạng dinh dưỡng giảm, điểm độ căng thẳng tăng lên (95%CI=(0.88, 1.68), p < 0.001). Trong số các bệnh nhân, 48.8% người vừa bị căng thẳng vừa suy dinh dưỡng đã yêu cầu hỗ trợ chăm sóc để giải quyết vấn đề của họ.

Kết luận

Các đánh giá tự báo cáo của bệnh nhân sử dụng công cụ E-health là một phương pháp chính xác và hiệu quả để khuyến khích sự tham gia của bệnh nhân vào việc chăm sóc ung thư, đồng thời đảm bảo rằng việc đánh giá định kỳ các khía cạnh tâm lý-xã hội và dinh dưỡng của chăm sóc được tích hợp hiệu quả vào quy trình lâm sàng hàng ngày.

Từ khóa


Tài liệu tham khảo

van Bokhorst-de van der Schueren MAE, Guaitoli PR, Jansma EP, de Vet HCW (2014) Nutrition screening tools: Does one size fit all? A systematic review of screening tools for the hospital setting. Clin Nutr 33(1):39–58. https://doi.org/10.1016/j.clnu.2013.04.008

Faithfull S, Turner L, Poole K, Joy M, Manders R, Weprin J et al (2019) Prehabilitation for adults diagnosed with cancer: A systematic review of long-term physical function, nutrition and patient-reported outcomes. Eur J Cancer Care (Engl) 28(4):e13023. https://doi.org/10.1111/ecc.13023

Tran K, Zomer S, Chadder J, Earle C, Fung S, Liu J et al (2018) Measuring patient-reported outcomes to improve cancer care in Canada: an analysis of provincial survey data. Curr Oncol 25(2):176–179. https://doi.org/10.3747/co.25.3995

Chrischilles EA, Hourcade JP, Doucette W, Eichmann D, Gryzlak B, Lorentzen R et al (2014) Personal health records: a randomized trial of effects on elder medication safety. J Am Med Inform Assoc 21(4):679–686. https://doi.org/10.1136/amiajnl-2013-002284

Abbott J, Teleni L, McKavanagh D, Watson J, McCarthy AL, Isenring E (2016) Patient-Generated Subjective Global Assessment Short Form (PG-SGA SF) is a valid screening tool in chemotherapy outpatients. Support Care Cancer 24(9):3883–3887. https://doi.org/10.1007/s00520-016-3196-0

Riba MB, Donovan KA, Andersen B, Braun I, Breitbart WS, Brewer BW et al (2019) Distress Management, Version 3.2019, NCCN Clinical Practice Guidelines in Oncology. J Natl Compre Cancer Netw 17(10):1229–49. https://doi.org/10.6004/jnccn.2019.0048

Erickson N, Vogt L, Kolm A, Norman K, Fey T, Schiffler V et al (2018) Linguistic and content validation of the german scored patient-generated subjective global assessment for the austrian, german and swiss setting. Clin Nutr 37:S125. https://doi.org/10.1016/j.clnu.2018.06.1470

Leser MLN, Bergerson S, Trujillo E (2018) Oncology Nutrition for Clinical Practice, 1st edn. Academy of Nutrition & Dietetics, Chicago

Sealy MJ, Hass U, Ottery FD, van der Schans CP, Roodenburg JLN, Jager-Wittenaar H (2018) Translation and cultural adaptation of the scored patient-generated subjective global assessment: an interdisciplinary nutritional instrument appropriate for Dutch cancer patients. Cancer Nurs 41(6):450–462. https://doi.org/10.1097/NCC.0000000000000505

Nitichai N, Angkatavanich J, Somlaw N, Voravud N, Lertbutsayanukul C (2019) Validation of the Scored Patient-Generated Subjective Global Assessment (PG-SGA) in Thai setting and association with nutritional parameters in cancer patients. Asian Pac J Cancer Prev 20(4):1249–1255. https://doi.org/10.31557/APJCP.2019.20.4.1249

De Groot LM, Lee G, Ackerie A, van der Meij BS (2020) Malnutrition Screening and Assessment in the Cancer Care Ambulatory Setting: Mortality Predictability and Validity of the Patient-Generated Subjective Global Assessment Short form (PG-SGA SF) and the GLIM Criteria. Nutrients 12(8). https://doi.org/10.3390/nu12082287

Erickson N, Storck LJ, Kolm A, Norman K, Fey T, Schiffler V et al (2019) Tri-country translation, cultural adaptation, and validity confirmation of the Scored Patient-Generated Subjective Global Assessment. Support Care Cancer 27(9):3499–3507. https://doi.org/10.1007/s00520-019-4637-3

Abbott J, Teleni L, McKavanagh D, Watson J, McCarthy AL, Isenring E (2016) Patient-Generated Subjective Global Assessment Short Form (PG-SGA SF) is a valid screening tool in chemotherapy outpatients. Support Care Cancer 24(9):3883–3887. https://doi.org/10.1007/s00520-016-3196-0

Vigano AL, di Tomasso J, Kilgour RD, Trutschnigg B, Lucar E, Morais JA et al (2014) The abridged patient-generated subjective global assessment is a useful tool for early detection and characterization of cancer cachexia. J Acad Nutr Diet 114(7):1088–1098. https://doi.org/10.1016/j.jand.2013.09.027

Kondrup J, Allison SP, Elia M, Vellas B, Plauth M (2003) ESPEN guidelines for nutrition screening 2002. Clin Nutr 22(4):415–421. https://doi.org/10.1016/s0261-5614(03)00098-0

Cutillo A, O’Hea E, Person S, Lessard D, Harralson T, Boudreaux E (2017) The distress thermometer: cutoff points and clinical use. Oncol Nurs Forum 44(3):329–336. https://doi.org/10.1188/17.ONF.329-336

Wüller J, Küttner S, Foldenauer AC, Rolke R, Pastrana T (2016) Accuracy of the distress thermometer for home care patients with palliative care needs in Germany. Palliat Support Care 15(3):288–294. https://doi.org/10.1017/S1478951516000699

Richtering SS, Morris R, Soh SE, Barker A, Bampi F, Neubeck L et al (2017) Examination of an eHealth literacy scale and a health literacy scale in a population with moderate to high cardiovascular risk: Rasch analyses. PLoS ONE 12(4):e0175372. https://doi.org/10.1371/journal.pone.0175372

Hennemann S, Beutel ME, Zwerenz R (2017) Ready for eHealth? Health professionals’ acceptance and adoption of ehealth interventions in inpatient routine care. J Health Commun 22(3):274–284. https://doi.org/10.1080/10810730.2017.1284286

Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1(8476):307–310

Zhu C, Wang B, Gao Y, Ma X (2018) Prevalence and relationship of malnutrition and distress in patients with Cancer using questionnaires. BMC Cancer 18(1):1272. https://doi.org/10.1186/s12885-018-5176-x

Bjoernes CD, Laursen BS, Delmar C, Cummings E, Nohr C (2012) A dialogue-based Web application enhances personalized access to healthcare professionals–an intervention study. BMC Med Inform Decis Mak 12:96. https://doi.org/10.1186/1472-6947-12-96

Girgis A, Durcinoska I, Levesque JV, Gerges M, Sandell T, Arnold A et al (2017) eHealth System for collecting and utilizing Patient Reported Outcome Measures for Personalized Treatment and Care (PROMPT-Care) among cancer patients: mixed methods approach to evaluate feasibility and acceptability. J Med Internet Res 19(10):e330. https://doi.org/10.2196/jmir.8360

Abernethy AP, Herndon JE, Wheeler JL, Day JM, Hood L, Patwardhan M et al (2009) Feasibility and acceptability to patients of a longitudinal system for evaluating cancer-related symptoms and quality of life: pilot study of an e/tablet data-collection system in academic oncology. J Pain Symptom Manage 37(6):1027–1038. https://doi.org/10.1016/j.jpainsymman.2008.07.011

Mullen KH, Berry DL, Zierler BK (2004) Computerized symptom and quality-of-life assessment for patients with cancer part II: acceptability and usability. Oncol Nurs Forum 31(5):E84–E89. https://doi.org/10.1188/04.onf.e84-e89

Jansen F, van Uden-Kraan CF, van Zwieten V, Witte BI, Verdonck-de Leeuw IM (2015) Cancer survivors’ perceived need for supportive care and their attitude towards self-management and eHealth. Support Care Cancer 23(6):1679–1688. https://doi.org/10.1007/s00520-014-2514-7

Steele R, Lo A, Secombe C, Wong YK (2009) Elderly persons’ perception and acceptance of using wireless sensor networks to assist healthcare. Int J Med Informatics 78(12):788–801. https://doi.org/10.1016/j.ijmedinf.2009.08.001

Gorber SC, Tremblay M, Moher D, Gorber B (2007) A comparison of direct vs. self-report measures for assessing height, weight and body mass index: a systematic review. Obes Rev 8(4):307–26. https://doi.org/10.1111/j.1467-789X.2007.00347.x

Spencer EA, Appleby PN, Davey GK, Key TJ (2002) Validity of self-reported height and weight in 4808 EPIC-Oxford participants. Public Health Nutr 5(4):561–565. https://doi.org/10.1079/phn2001322

Touvier M, Méjean C, Kesse-Guyot E, Pollet C, Malon A, Castetbon K et al (2010) Comparison between web-based and paper versions of a self-administered anthropometric questionnaire. Eur J Epidemiol 25(5):287–296. https://doi.org/10.1007/s10654-010-9433-9

McAdams MA, Van Dam RM, Hu FB (2007) Comparison of self-reported and measured BMI as correlates of disease markers in US adults. Obesity (Silver Spring, Md) 15(1):188–196. https://doi.org/10.1038/oby.2007.504

Villarini M, Acito M, Gianfredi V, Berrino F, Gargano G, Somaini M et al (2019) Validation of self-reported anthropometric measures and body mass index in a subcohort of the DianaWeb population study. Clin Breast Cancer 19(4):e511–e518. https://doi.org/10.1016/j.clbc.2019.04.008

Dauphinot V, Wolff H, Naudin F, Guéguen R, Sermet C, Gaspoz JM et al (2009) New obesity body mass index threshold for self-reported data. J Epidemiol Community Health 63(2):128–132. https://doi.org/10.1136/jech.2008.077800

Hercberg S, Castetbon K, Czernichow S, Malon A, Mejean C, Kesse E et al (2010) The Nutrinet-Santé Study: a web-based prospective study on the relationship between nutrition and health and determinants of dietary patterns and nutritional status. BMC Public Health 10:242. https://doi.org/10.1186/1471-2458-10-242

Briot K, Legrand E, Pouchain D, Monnier S, Roux C (2010) Accuracy of patient-reported height loss and risk factors for height loss among postmenopausal women. CMAJ 182(6):558–562. https://doi.org/10.1503/cmaj.090710

Stehman CR, Buckley RG, Dos Santos FL, Riffenburgh RH, Swenson A, Mulligan S et al (2011) Bedside Estimation of Patient Height for Calculating Ideal Body Weight in the Emergency Department. J Emerg Med 41(1):97–101. https://doi.org/10.1016/j.jemermed.2009.12.016

Du H, Liu B, Xie Y, Liu J, Wei Y, Hu H et al (2017) Comparison of different methods for nutrition assessment in patients with tumors. Oncol Lett 14(1):165–170. https://doi.org/10.3892/ol.2017.6154

Håkonsen SJ, Pedersen PU, Bath-Hextall F, Kirkpatrick P (2015) Diagnostic test accuracy of nutritional tools used to identify undernutrition in patients with colorectal cancer: a systematic review. JBI Database Syst Rev Implement Rep 13(4):141–187. https://doi.org/10.11124/jbisrir-2015-1673

Mendes NP, Barros TA, Rosa COB, Franceschini S (2019) Nutritional Screening Tools Used and Validated for Cancer Patients: A Systematic Review. Nutr Cancer 71(6):898–907. https://doi.org/10.1080/01635581.2019.1595045

Zhang YH, Xie FY, Chen YW, Wang HX, Tian WX, Sun WG et al (2018) Evaluating the nutritional status of oncology patients and its association with quality of life. Biomed Environ Sci 31(9):637–644. https://doi.org/10.3967/bes2018.088

Fearon K, Strasser F, Anker SD, Bosaeus I, Bruera E, Fainsinger RL et al (2011) Definition and classification of cancer cachexia: an international consensus. Lancet Oncol 12(5):489–495. https://doi.org/10.1016/s1470-2045(10)70218-7

Pressoir M, Desne S, Berchery D, Rossignol G, Poiree B, Meslier M et al (2010) Prevalence, risk factors and clinical implications of malnutrition in French comprehensive cancer centres. Br J Cancer 102(6):966–971. https://doi.org/10.1038/sj.bjc.6605578

Nemer L, Krishna SG, Shah ZK, Conwell DL, Cruz-Monserrate Z, Dillhoff M et al (2017) Predictors of pancreatic cancer-associated weight loss and nutritional interventions. Pancreas 46(9):1152–1157. https://doi.org/10.1097/MPA.0000000000000898

Yoon SL, Kim JA, Kelly DL, Lyon D, George TJ Jr (2019) Predicting unintentional weight loss in patients with gastrointestinal cancer. J Cachexia Sarcopenia Muscle 10(3):526–535. https://doi.org/10.1002/jcsm.12398

Ross PJ, Ashley S, Norton A, Priest K, Waters JS, Eisen T et al (2004) Do patients with weight loss have a worse outcome when undergoing chemotherapy for lung cancers? Br J Cancer 90(10):1905–1911. https://doi.org/10.1038/sj.bjc.6601781

Martin L, Senesse P, Gioulbasanis I, Antoun S, Bozzetti F, Deans C et al (2015) Diagnostic criteria for the classification of cancer-associated weight loss. J Clin Oncol 33(1):90–99. https://doi.org/10.1200/jco.2014.56.1894