Latest Findings in Key Research Areas of Precision Nursing for Chronic Diseases in Older Adults

WU Junhui, ZHOU Weijiao, WANG Weixuan, SHANG Shaomei

Abstract

The advent of the era of biomedical big data has helped promote the development of precision nursing. Precision nursing for chronic diseases in older adults is an interdisciplinary research field in which accurate individualized data are utilized to carry out early screening and health management of older adult populations at high risk for chronic diseases and early intervention of diseases, which plays an important role in improving the prognosis of diseases and the health level of the older adult population. Herein, we introduced the concept of precision nursing, and discussed the latest research findings in the key areas of precision nursing for chronic diseases in older adults, including precision symptom management in cancer patients and precision nursing in older patients with multimorbidity. At present, research concerning precise symptom management of cancer patients is mainly focused on prediction modelling for risks of symptoms, longitudinal change trajectories, core symptom identification, etc. Investigations in the precise nursing of cancer patients are conducted in the following areas, risk prediction, the timing of interventions, and intervention targets. Research on precision nursing for multimorbidity is mainly focused on assessment of chronic disease multimorbidity, multimorbidity pattern recognition, and health management of multimorbidity. We also discussed potential opportunities and challenges of precision nursing in the future, in order to provide a scientific basis for the improving the practice and theories of precision nursing. In the future, precision nursing will play an ever more important role in uncovering pathogenic information, the diagnosis and treatment of diseases, the health of the research population, and the promotion of medical research.


Keywords: Precision nursing,  Precision medicine,  Chronic diseases,  Symptom management,  Multimorbidity in older adults,  Research progress

 

Full Text:

PDF


References


EMMONS-BELL S, JOHNSON C, ROTH G. Prevalence, incidence and survival of heart failure: a systematic review. Heart,2022,108(17): 1351–1360. doi: 10.1136/heartjnl-2021-320131.

KHAN M A B, HASHIM M J, KING J K, et al. Epidemiology of type 2 diabetes-global burden of disease and forecasted trends. J Epidemiol Glob Health,2020,10(1): 107–111. doi: 10.2991/jegh.k.191028.001.

Global Burden of Disease Cancer Collaboration; FITZMAURICE C, AKINYEMIJU T F, Al LAMI F H, et al. Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 29 cancer groups, 1990 to 2016: a systematic analysis for the global burden of disease study. JAMA Oncol, 2018,4(11): 1553–1568. doi: 10.1001/jamaoncol.2018.2706.

GBD 2017 Colorectal Cancer Collaborators. The global, regional, and national burden of colorectal cancer and its attributable risk factors in 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Gastroenterol Hepatol,2019,4(12): 913–933. doi: 10.1016/S2468-1253(19)30345-0.

COLLINS F S, VARMUS H. A new initiative on precision medicine. N Engl J Med,2015,372(9): 793–795. doi: 10.1056/NEJMp1500523.

ROSS J S, WANG K, GAY L, et al. Comprehensive genomic profiling of carcinoma of unknown primary site: new routes to targeted therapies. JAMA Oncol,2015,1(1): 40–49. doi: 10.1001/jamaoncol.2014.216.

GINSBURG G S, PHILLIPS K A. Precision medicine: from science to value. Health Aff (Millwood),2018,37(5): 694–701. doi: 10.1377/hlthaff. 2017.1624.

FAWAZ M. Role of nurses in precision health. Nurs Outlook,2021,69(6): 937–940. doi: 10.1016/j.outlook.2021.01.016.

FU M R, KURNAT-THOMA E, STARKWEATHER A, et al. Precision health: a nursing perspective. Int J Nurs Sci,2020,7(1): 5–12. doi: 10. 1016/j.ijnss.2019.12.008.

DEWELL S, BENZIES K, GINN C. Precision health and nursing: seeing the familiar in the foreign. Can J Nurs Res,2020,52(3): 199–208. doi: 10. 1177/0844562120945159.

Di MEGLIO A, HAVAS J, SOLDATO D, et al. Development and validation of a predictive model of severe fatigue after breast cancer diagnosis: toward a personalized framework in survivorship care. J Clin Oncol,2022,40(10): 1111–1123. doi: 10.1200/JCO.21.01252.

MOLASSIOTIS A, STAMATAKI Z, KONTOPANTELIS E. Development and preliminary validation of a risk prediction model for chemotherapy-related nausea and vomiting. Support Care Cancer,2013, 21(10): 2759–2767. doi: 10.1007/s00520-013-1843-2.

TSOU Y L, LEE J M, TANG C C. The trajectory of cancer-related fatigue and its associating factors in patients with esophageal cancer receiving treatments: a prospective longitudinal study. Ann Surg Oncol,2022, 29(5): 2784–2790. doi: 10.1245/s10434-021-11294-2.

VAZ-LUIS I, Di MEGLIO A, HAVAS J, et al. Long-term longitudinal patterns of patient-reported fatigue after breast cancer: a group-based trajectory analysis. J Clin Oncol,2022,40(19): 2148–2162. doi: 10.1200/JCO.21.01958.

BOWER J E, GANZ P A, IRWIN M R, et al. Do all patients with cancer experience fatigue? A longitudinal study of fatigue trajectories in women with breast cancer. Cancer,2021,127(8): 1334–1344. doi: 10.1002/cncr. 33327.

BAUSSARD L, PROUST-LIMA C, PHILIPPS V, et al. Determinants of distinct trajectories of fatigue in patients undergoing chemotherapy for a metastatic colorectal cancer: 6-month follow-up using growth mixture modeling. J Pain Symptom Manage,2022,63(1): 140–150. doi: 10.1016/j. jpainsymman.2021.06.019.

BORSBOOM D. A network theory of mental disorders. World Psychiatry,2017,16(1): 5–13. doi: 10.1002/wps.20375.

LIN Y, BRUNER D W, PAUL S, et al. A network analysis of self-reported psychoneurological symptoms in patients with head and neck cancer undergoing intensity-modulated radiotherapy. Cancer,2022, 128(20): 3734–3743. doi: 10.1002/cncr.34424.

MERANIUS M S, HAMMAR L M. How does the healthcare system affect medication self-management among older adults with multimorbidity? Scand J Caring Sci,2016,30(1): 91–98. doi: 10.1111/scs. 12225.

LEROY L, BAYLISS E, DOMINO M, et al. The agency for healthcare research and quality multiple chronic conditions research network: overview of research contributions and future priorities. Med Care,2014, 52(Suppl 3): S15–S22. doi: 10.1097/MLR.0000000000000095.

NOLTE E,DURAND-ZALESKI I. Developing and validating disease management evaluation methods for European healthcare system. Eur J Pub Health,2012,20: 12.

FARMER C, FENU E, O'FLYNN N, et al. Clinical assessment and management of multimorbidity: summary of NICE guidance. BMJ,2016, 354: i4843. doi: 10.1136/bmj.i4843.

MC NAMARA K P, BREKEN B D, ALZUBAIDI H T, et al. Health professional perspectives on the management of multimorbidity and polypharmacy for older patients in Australia. Age Ageing,2017,46(2): 291–299. doi: 10.1093/ageing/afw200.


Refbacks

  • There are currently no refbacks.